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explore the mechanisms of HCW and rutin on intestinal microflora. The results indicated that HCW and rutin could increase the diversity and richness of the intestinal flora, and regulate the specific intestinal microorganisms of the depressed mice. To sum up, the water extract of H. citrina flowers (HCW) has significant antidepressant activity, and its main active metabolites were determined and the related mechanism has been proposed. Data availability statement The original contributions presented in the study are included in the article/Supplementary Material, further inquiries can be directed to the corresponding authors. Ethics statement The animal study was reviewed and approved by Hunan Laboratory Animal Central (IACUC-2018 (3) 033).

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Current Understanding of Molecular Phase Separation in Chromosomes Biomolecular phase separation denotes the demixing of a specific set of intracellular components without membrane encapsulation. Recent studies have found that biomolecular phase separation is involved in a wide range of cellular processes. In particular, phase separation is involved in the formation and regulation of chromosome structures at various levels. Here, we review the current understanding of biomolecular phase separation related to chromosomes. First, we discuss the fundamental principles of phase separation and introduce several examples of nuclear/chromosomal biomolecular assemblies formed by phase separation. We also briefly explain the experimental and computational methods used to study phase separation in chromosomes. Finally, we discuss a recent phase separation model, termed bridging-induced phase separation (BIPS), which can explain the formation of local chromosome structures. Introduction The various components of cells (especially eukaryotic cells) are organized both spatially and temporally for efficient functioning; membrane-bound organelles are examples of spatiotemporal compartmentalization. However, other types of organelles exist that lack a membrane structure, known as membraneless organelles [1], and include: nucleoli for ribosomal synthesis in the nucleus [2], centrosomes for microtubule nucleation [3], Cajal bodies for the synthesis of spliceosomes [4], and stress granules for modulation of the stress response [5]. Although these organelles do not enclose their components within a membrane, they do not simply mix with their surroundings. Recent studies have found that demixing occurs spontaneously via liquid-liquid phase separation (LLPS) [6][7][8][9][10], a phenomenon known in physics and chemistry for more than a century. Demixing behavior occurs in a multi-component system

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when the energy gain for demixing is greater than the entropic loss for demixing. A good example is a typical water-oil system; water-oil mixing results in the formation of unfavorable water-oil molecular interactions, which exceeds the entropic penalty of demixing. Hence, such a system favors demixing under ambient conditions. In 2009, Brangwynne and colleagues published a pioneering study in this field [11], which showed the liquid-like properties of P granules, a type of membraneless organelle in C. elegans. P granules exchange their components with the cytoplasm and exhibit fusion, dripping, and wetting behaviors. The authors also estimated the viscosity and surface tension of the granules. Subsequently, the material properties and biological implications of membraneless organelles have attracted significant interest [12,13]; a membraneless organelle can recruit specific molecules, whose local concentration becomes significantly higher than the cytosol concentration. As the concentration determines the reaction rate, the membraneless organelle can serve as a reaction center of the recruited molecules. In the membraneless organelle can serve as a reaction center of the recruited molecules. In addition, because of their liquid-like nature, membraneless organelles allow the rapid arrangement of specific molecules upon perturbations such as temperature change; cells can use this mechanism to respond rapidly to an abrupt change of the environment. LLPS is involved in various biological processes, such as immune signaling [14], miRISC assembly [15], autophagy [16], nucleolus formation [17], stress granule assembly [18], transcriptional condensate assembly [19], and cohesin cluster formation [20]. It has also been suggested that phase separation drives chromosome organization and various genome-related biological

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functions [21,22]. DNA, which carries the genetic information of a cell, is densely packed in the nucleus. The efficient packing of DNA from a stretched, meters-long chain into a micrometer-scale structure is accomplished by chromatin, which is a molecular complex of DNA, protein, and RNA. Chromatin can be divided into two compartments, A and B, according to the gene content and location, and chromatin compartmentalization is believed to be driven by phase separation [23,24]. In addition, membraneless condensates form inside the nucleus, called nuclear condensates or nuclear bodies [25], whose formation and regulation can be explained by LLPS [22] ( Figure 1). In this review, we highlight recent advances in the contemporary understanding of phase separation in the nucleus, where phase separation involves the extremely long heteropolymer, DNA, for chromosome organization, and DNA-related biological functions. Figure 1. Biomolecular condensates in the nucleus: A and B compartments, nucleolus, paraspeckles, and transcriptional condensates. Chromosomes are largely segregated via phase separation into two compartments: euchromatin (A, red) and heterochromatin (B, blue). Phase separation is also involved in the formation and regulation of membraneless organelles such as the nucleolus (gray), transcription condensates (magenta), and paraspeckles (green) in the nucleus. Basic Models of Phase Separation Consider two types of molecules, X and Y, in a test tube. If homotypic interactions (X-X and Y-Y) are more favorable than heterotypic interactions (X-Y), the system energetically prefers the two components to separate (phase separation). Meanwhile, entropy always drives the system towards mixing. Hence, there is a "tug of war" between the two driving forces,

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energy and entropy, and the molecular details determine whether phase separation occurs under the given experimental conditions (temperature, concentration, salt condition, etc.). A phase diagram is utilized to summarize the conditions of phase separation for the system of interest (Figure 2). Figure 1. Biomolecular condensates in the nucleus: A and B compartments, nucleolus, paraspeckles, and transcriptional condensates. Chromosomes are largely segregated via phase separation into two compartments: euchromatin (A, red) and heterochromatin (B, blue). Phase separation is also involved in the formation and regulation of membraneless organelles such as the nucleolus (gray), transcription condensates (magenta), and paraspeckles (green) in the nucleus. Basic Models of Phase Separation Consider two types of molecules, X and Y, in a test tube. If homotypic interactions (X-X and Y-Y) are more favorable than heterotypic interactions (X-Y), the system energetically prefers the two components to separate (phase separation). Meanwhile, entropy always drives the system towards mixing. Hence, there is a "tug of war" between the two driving forces, energy and entropy, and the molecular details determine whether phase separation occurs under the given experimental conditions (temperature, concentration, salt condition, etc.). A phase diagram is utilized to summarize the conditions of phase separation for the system of interest (Figure 2). . The x-axis shows the multimer concentration, and has a different scale from panels A and B. The multimer concentration, however, is proportional to the unit molecule concentration, and the two can be interchangeably used. The Bragg-Williams model [26] describes the phase separation of two-component systems. For component X with a volume fraction

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of and component Y with a volume fraction ( + = 1), the model predicts the molar mixing free energy of the system, , as: where is the gas constant and is the absolute temperature. Here, is the exchange parameter that quantifies the average difference between the homotypic and heterotypic interactions of X and Y: where indicates the two-body interaction energy between molecules of types and , and is the coordination number. If 2, the strength of the homotypic interactions exceeds that of the heterotypic interactions to counterbalance the entropic effect, and phase separation occurs over a range of concentrations ( Figure 2A). To increase the tendency toward phase separation, unit molecules can be connected covalently to construct multimers (oligomers and polymers). Each multimer can simultaneously interact with multiple counterparts, which effectively reduces the entropic cost. For a multimer-solvent system, the molar mixing free energy of the Bragg-Williams model is generalized (known as the Flory-Huggins model [27,28]) as where is the number of binding units (valence) in each multimer. With this modification, the phase separation territory in the phase diagram can be markedly expanded (Figure 2B). The model can be further generalized to multicomponent systems [29,30]. The phase separation of multimers is coupled to another type of transition: networking transition, also known as percolation. Each multimer has multiple binding units; two multimers are (at least transiently) connected by the formation of a physical bond between the binding units of each multimer. Increasing the concentration of multimers increases . The x-axis shows the multimer concentration, and has

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a different scale from panels A and B. The multimer concentration, however, is proportional to the unit molecule concentration, and the two can be interchangeably used. The Bragg-Williams model [26] describes the phase separation of two-component systems. For component X with a volume fraction of φ X and component Y with a volume fraction φ Y (φ X + φ Y = 1), the model predicts the molar mixing free energy of the system, ∆F mix , as: where R is the gas constant and T is the absolute temperature. Here, χ XY is the exchange parameter that quantifies the average difference between the homotypic and heterotypic interactions of X and Y: where w ij indicates the two-body interaction energy between molecules of types i and j, and z is the coordination number. If χ XY > 2, the strength of the homotypic interactions exceeds that of the heterotypic interactions to counterbalance the entropic effect, and phase separation occurs over a range of concentrations ( Figure 2A). To increase the tendency toward phase separation, unit molecules can be connected covalently to construct multimers (oligomers and polymers). Each multimer can simultaneously interact with multiple counterparts, which effectively reduces the entropic cost. For a multimer-solvent system, the molar mixing free energy of the Bragg-Williams model is generalized (known as the Flory-Huggins model [27,28]) as where M is the number of binding units (valence) in each multimer. With this modification, the phase separation territory in the phase diagram can be markedly expanded ( Figure 2B). The model can be

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further generalized to multicomponent systems [29,30]. The phase separation of multimers is coupled to another type of transition: networking transition, also known as percolation. Each multimer has multiple binding units; two multimers are (at least transiently) connected by the formation of a physical bond between the binding units of each multimer. Increasing the concentration of multimers increases the fraction of connected multimers, and at a certain threshold concentration, a large network structure emerges abruptly. This transition is called percolation. The experimental conditions for networked and unnetworked systems can be depicted using a phase diagram ( Figure 2C, blue dashed line). The Flory-Stockmayer model [31,32] was the first model to investigate percolation; it concluded that for a multimer with a valence of M, the probability p for each binding unit to form a bond must exceed the threshold value to generate a system-spanning network. Because p < 1 for transient interactions, monomer and dimer systems (M ≤ 2) cannot undergo percolation [33]. At temperatures below the critical temperature T c (above which entropy disrupts phase separation), three different transition concentrations can be designated on the phase diagram (see Figure 2C). As the multimer concentration increases, the saturation concentration (c sat ) is reached in the system, after which the two phases are separated. Subsequently, the percolation concentration (c perc ) is reached, which divides unnetworked and networked systems. Because the spatial proximity of multimers is driven by bond formation, the percolation concentration is coupled to the saturation concentration [34,35]. Finally, at the droplet concentration (c drop ),

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the system re-enters the one-phase region. If the multimer concentration, c, is between c sat and c drop , the solute multimers are either in the dilute (whose concentration is c sat ) or in the dense phase (whose concentration is c drop ). The amounts of molecules in the two phases are governed by the conservation of molecule number and volume, and are determined by the following rule (called the lever rule): where N dilute and N dense indicate the amounts of solute multimers in the dilute and dense phases, respectively. The lever rule states that: (1) if c = c sat , all solutes are in the dilute phase; (2) if c = c drop , all solutes are in the dense phase; and (3) if c is between c sat and c drop , there are a finite number of solutes in each phase, and as c nears c drop , more solute molecules move from the dilute phase to the dense phase. This is reflected in the observations that after crossing c sat , the size and number of dense-phase droplets increases as the solute concentration increases. Stickers-and-Spacers Framework Proteins are the essential driver of biomolecular phase separation, and their roles and mode of action in LLPS have been extensively studied. In this section, we discuss a simple conceptual framework that can explain the phase behaviors of proteins. The framework is useful in understanding biomolecular LLPS and can be extended further to other multimer systems. Two representative types of protein are known

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to undergo phase separation. Multi-domain proteins possess well-defined folded domains connected by disordered linkers. Several multi-domain protein systems have been reported to exhibit phase separation behavior [36][37][38]. A more prominent group is comprised of intrinsically disordered proteins (IDPs), which lack well-defined three-dimensional structures, even under physiological conditions [39]. Many phase separation systems identified in vivo contain significant portions of intrinsically disordered regions (IDRs) [40]. DNA and RNA, an important group of biomolecules in living cells, can also participate in intracellular phase separation [41][42][43]. Multi-domain proteins and IDPs can be analyzed conceptually using the so-called stickers-and-spacers framework [8,44]. Inspired by theories of associative polymers [34,45], this framework partitions the target protein into two regions: molecular fragments responsible for chain-chain interactions (stickers), and the rest of the molecule, which is considered relatively inert (spacers). Spacers are assumed to modulate chain properties; however, their influence on chain-chain interactions is significantly weaker than that of stickers. In the case of multi-domain proteins, the partitioning is straightforward: interacting domains act as stickers, while disordered linkers act as spacers. IDP systems are more complicated, but experiments have shown that many systems can identify a set of amino acids that behave like stickers [44,46,47]. Notably, the dichotomy between multi-domain proteins and IDPs is fairly arbitrary, considering the spectrum of interactions involving amino acids, short linear motifs, peptides, and proteins. For example, short linear motifs on an IDP can interact with domains on a multi-domain protein to drive phase separation, in which the short linear motifs and the folded domains act as stickers, despite

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their different lengths. The stickers-and-spacers framework does not require the dichotomy. An IDP is considered as a prototypical model containing multiple types of stickers. There are 20 different canonical amino acids; considering post-translational modifications, the number of different types of IDP monomers in vivo far exceeds 20. Thus, it may appear unusual that only a handful of amino acids dictate the phase behavior of the whole protein chain, as there is a jumble of multiple different interactions. This apparent paradox can be answered by a mean-field model of multi-sticker systems, where each multimer contains different types and numbers of stickers [48]. According to this model, the percolation concentration, which can be used as a proxy for the saturation concentration, is as follows: where i and j are indices for sticker types, s i is the number of stickers of type i in each multimer, v ij is the bond volume, in which a pair of stickers is spatially constrained after bond formation, β = 1/k B T, and k B is the Boltzmann constant. Each term v ij e −βw ij s i s j in the denominator indicates the contribution of each sticker pair (i, j); the contributions are additive and independent. Note that the term contains both intrinsic and extrinsic properties of a sticker pair: the bond volume v ij and the interaction energy w ij are invariable for a given sticker pair, while the numbers of stickers, s i and s j , can be modulated by mutagenesis. If the contribution of a

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certain sticker pair (p, q) dominates the denominator, the apparent percolation concentration becomes: In this system, only monomer types p and q play the role of stickers, and other monomer types are considered spacers. Hence, depending on the amino acid composition of an IDP, the identity of stickers can differ between systems. Typical sticker interactions involve cation-anion interactions, π-cation, and π-π interactions [8]. Multi-Component Systems Different types of biomolecular condensates have distinct compositions. For example, the proteomes and interactomes of P-bodies and stress granules only marginally overlap [49]. Then, for a system containing multiple components, how many distinct condensates can we have? The generalized Flory-Huggins model was recently applied to address this question; the maximum number of distinct condensates was found to increase much faster than the number of components [30]. Biomolecular condensates consist of hundreds or thousands of different types of biomolecules. Do they all contribute to the formation of condensates, or is there a subset of essential players in condensate formation? The latter seems to be the case in most systems, and the essential drivers are termed scaffolds. Typically, scaffolds are defined as molecules that can form droplets when isolated in vitro (to be rigorous, the removal of scaffold molecules from in vivo condensates must be shown to interrupt phase separation). The other molecules are recruited to condensates by their interactions with the scaffolds and are termed clients [50]. Although clients are not necessary for the formation of condensates, they can modulate the properties of condensates [51]. Recruitment leads to the non-uniform distribution of

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client molecules inside the condensates, as they tend to remain around the scaffolds [52]. Microphase Separation Phase separation can be used to generate and modulate the structure of a gigantic macromolecule. From the perspective of polymer physics, chromosomes can be considered large polymers, resembling beads on a string. Each "bead" is slightly different, and the interactions between beads are complex. According to polymer models, if a polymer consists of building blocks with different interactions, it can undergo microphase separation, the formation of distinct microdomains enriched in different types of building blocks because of intrachain phase separation [53]. Depending on the fraction of each building block and their interaction strengths, the polymer system can exhibit diverse mesoscopic morphologies [54]. In the stickers-and-spacers framework, the stickers gather to form microdomains, and the spacers provide sticker connectivity, which prevents the perfect segregation of microdomains. The microphase separation model is appealing because it explains local and global structure formation, and the regulation of chromatin, although it may not be the only mechanism for genome folding [55]. Phase Separation in a Nucleus Phase separation seems to have diverse roles in the cell nuclei. For example, chromosome organization, transcription regulation, DNA damage repair, and RNA splicing are related to phase separation ( Figure 1). An important feature of these processes is that long DNA molecules are involved in the formation of their corresponding biomolecular condensates. In this section, we discuss a few examples of these processes and their biophysical properties. Chromatin Compartmentalization Interphase chromosomes are segregated into two distinct compartments. The transcriptionally

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active, gene-rich form of chromatin is called euchromatin, and the transcriptionally inactive form is called heterochromatin (Figure 1, red and blue denoting euchromatin and heterochromatin, respectively) [56][57][58][59][60][61]. Compartmentalization seems to be driven by the phase separation of some proteins, such as heterochromatin protein 1 alpha (HP1α), a protein enriched in heterochromatin. Recent studies have shown that HP1α induces liquid droplet formation, and droplet formation tightly compacts DNA, supporting a role for the phase separation of HP1α in chromosome organization [23,24]. The two compartments were originally defined by Emil Heitz (1892-1965) about a century ago using a DNA-staining method [62,63]. Because of the different DNA densities of the two compartments, Heitz differentiated the densely stained, condensed form of heterochromatin from the lightly stained, decondensed form of euchromatin. It was found later that nucleosomes are sparsely distributed in euchromatin and densely distributed in heterochromatin, and that this induces higher accessibility of DNA to transcriptional factors in the former than in the latter [21]. The inaccessibility of heterochromatin might be explained by HP1α driving phase separation, as it can tightly compact DNA via transient interactions between HP1α and specific histone markers, such as H3K9me3 or H3K27me3 [64,65]. However, the detailed molecular mechanism underlying chromatin compartmentalization is not clearly understood. Microphase separation has been proposed to explain the segregation of heterochromatin and euchromatin, as chromatin can be considered as a copolymer consisting of alternatively localized euchromatin and heterochromatin, forming distinct microdomains in two compartments [53]. Chromatin contact analysis (high-throughput chromosome conformation capture, or Hi-C, see Section 4) on interphase chromosomes

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was shown to present checkerboard contact patterns [56][57][58][59][60][61], indicating that the two types of chromatins are spatially segregated and that each type of chromatin prefers to interact with the same type [57,66]. Eigenvector deconvolution analysis of the experimental data revealed two principal compartments, termed A and B, corresponding to euchromatin and heterochromatin, respectively. Epigenetic analyses, such as chromatin immunopreciptation with high-throughput sequencing (ChIP-seq) and ATAC-seq, can also be used to identify chromatin domains, since the two types of chromatins are marked with different types of epigenetic modifications. Histones of euchromatin are marked by H3K4me3, H3K27ac, H4K8ac, and H4K16ac, whereas those of heterochromatin are marked by H3K9me3 or H3K27me3 [64,65]. Epigenetic analysis revealed that euchromatin and heterochromatin regions alternatively localize along the chain of each chromosome [67][68][69][70], which also supports the microphase separation of a large polymeric chromosome. Nucleolus The nucleolus is a membraneless organelle in each nucleus, which is formed by LLPS of nucleolar proteins [71]. The nucleolus provides a site for ribonucleoprotein particle assembly, primarily for ribosome biogenesis, and it also serves other processes to maintain cell homeostasis [17]. In mammalian cells, the nucleolus comprises an interesting, layered structure with three functionally and compositionally distinct subcompartments: the fibrillar center (FC), the dense fibrillar component (DFC), and the granular component (GC). The FC, the innermost layer, initiates ribosome biogenesis, and as preribosomal and ribosomal molecular components diffuse from FC to DFC to GC, the ribosome is assembled in an orderly manner through a complex and dynamic process [72]. The nucleolus is an example of the scaffold-client

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model. Among hundreds of different biomolecules within a nucleolus [73], only a few proteins correspond to the formation of droplets as well as layered structures. Fibrillarin (FBL) is a protein that participates in the processing of ribosomal RNA and is enriched in DFC. Nucleophosmin (NPM1) is a protein associated with nucleolar ribonucleoprotein structures and is abundant in GC. A mixture of FBL and NPM1 was shown to reproduce phase separation in vitro and generate two-layer droplets, similar to the DFC-GC structure [74]. The molecular structures of FBL and NPM1 illustrate the stickers-and-spacers architecture. Both FBL and NPM1 contain IDRs, with FBL displaying Arg-rich domains and NPM1 displaying acidic tracts, which consequently interact via electrostatic interactions. NPM1 forms a pentamer that provides multivalency. In addition, FBL and NPM1 can bind to RNA via their RNA-binding domains, permitting additional transient interactions [74]. Indeed, RNA has been shown to promote nucleation and lower saturation concentrations [6,75]. Therefore, these molecular features of the nucleolus show that the LLPS model provides a simple and powerful explanation of the structural maintenance and function of the nucleolus [17]. Transcription Condensates Recent studies have shown that transcription factors (TFs) and RNA induce the formation of transcriptional condensates via LLPS, which contain clusters of multiple enhancers (super-enhancers) [76,77]. This hypothesis is supported by the dynamic interaction of TF compartments with RNA polymerase II (Pol II) clusters [76,77]. To form transcriptional condensates, TFs bind to various cis-regulatory DNA elements (e.g., promoters and enhancers) and stimulate the transcription of active genes in proximity [78], facilitating the precise

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control of gene expression. Enhancers and promoters provide multiple binding sites for TFs, which are needed to concentrate TFs and form transcriptional condensates. In addition, transcriptional condensates present a liquid property; two different transcriptional condensates can be merged, and fluorescence recovery after photobleaching (FRAP, see Section 4) analysis revealed a clear exchange of TF molecules between the background and the condensates [19]. The structural features of typical TFs can explain how TFs induce LLPS. Typical TFs possess IDRs that can weakly interact with those of cofactors, and these multivalent interactions can induce dynamic assembly formation and be controlled by post-translational modification. Generally, TFs have stable structured domains for selective DNA/RNA binding, which provide additional weak interactions [79]. For example, FUS, EWSR1, and TAF15, known as the FET family, are mostly disordered and capable of binding to RNA molecules [80]. These are well-known model systems for phase separation in vitro [81,82]. The TFs interact with the intrinsically disordered C-terminal domain of Pol II, and this C-terminal domain is key to the formation of large spherical droplets, which possess a liquid property in living cells [83] even at endogenous expression levels [19,84]. Viral Genome Organization Like phase separation of eukaryotic nuclear proteins and prokaryotic nucleoid proteins, phase separation of viral proteins is involved in the cellular processes of virus [85][86][87]. For example, RNA viruses, such as respiratory syncytial virus (RSV), vesicular stomatitis virus (VSV), and coronaviruses, appear to replicate themselves in viral inclusion bodies, membraneless condensates formed by phase separation, in host cells [85,86,[88][89][90]. Moreover, several studies on

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coronaviruses have shown that the assembly of viral capsids and genomes occurs in dynamic cytoplasmic foci formed by phase separation [91,92], suggesting that phase separation plays a role in the replication and packaging of coronaviruses. Coronaviruses contain a relatively long 30 kbp single-stranded RNA genome and are compacted in a viral particle in a highly specific manner by excluding host RNA and many subgenomic RNAs [93]. In particular, the nucleocapsid protein (N-protein) of SARS-CoV-2 drives viral RNA genome packaging using LLPS, which is mediated by interactions between specific viral RNA sequences and multivalent RNA-binding domains and IDRs of the viral proteins [87,[94][95][96][97][98][99]. Some specific RNA sequences interact with the N-proteins for LLPS, and this seems to ensure that the viral RNA is not entangled with other long cellular RNA molecules [100,101]. LLPS studies on viruses provide novel perspectives on how the composition of RNA determines its packaging into a small viral particle. Technical Approaches to Study Phase Separation in Chromosome Different biophysical and biochemical approaches have been employed to study intracellular phase separation [13,[102][103][104]. One approach for investigating intracellular phase separation is to reconstitute biomolecular condensates in vitro, using minimal and essential components, and explore the physical properties of the condensates. In-vitro reconstitution can provide detailed information on how biomolecules interact to form a biomolecular condensate; typical chemical tools can be utilized here. Although invitro studies can provide detailed biophysical information on the condensates, the data should be confirmed using live-cell experiments to enable biologically relevant conclusions to be drawn. Live-cell imaging is used widely to

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monitor condensates and study the characteristics of condensates inside a cell [19,105]. Conversely, genomic analyses, such as sequencing techniques and Hi-C, have been used to study chromosome organization, where phase separation can play a role, as discussed earlier [106]. In addition, computer simulations can provide another perspective on the principles of phase separation in model systems [107][108][109][110]. Reconstitution of Biomolecular Condensates In Vitro A variety of biomolecular condensates have been reconstituted in vitro: (1) to identify essential factors to form biomolecular condensates; (2) to test the systematic effects of external variables such as pH, salt concentration, temperature, and buffer composition; and (3) to characterize the biophysical features and material properties of the condensates. Typically, with dye-labeled recombinant proteins, RNA, or DNA, fluorescence microscopy can be used to monitor the behavior of individual biomolecules and condensates, owing to the high signal-to-noise ratio ( Figure 3A). In addition, differential interference contrast (DIC) microscopy can be used to visualize biomolecular condensates of label-free biomolecules to avoid labeling artifacts. In addition, a DIC microscope can provide a higher contrast than a normal optical transmission microscope [111] (Figure 3B). Using these optical microscopes, solution-based biomolecular condensates can be reconstituted and visualized. For example, the interplay of proteins and DNA in in-vitro chromatin condensates was monitored by single-molecule fluorescence microscopy using immobilized fluorescence-stained DNA on the surface and labeled proteins [20,23,112,113] ( Figure 3C). The use of DNA-staining fluorophores, such as YoYo1 or SYTOX Orange, enables labeled proteins to be monitored via single-molecule resolution to determine how many condensates are formed around

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the DNA and how the proteins induce topological changes in DNA. Moreover, AFM imaging, which provides high-contrast images, can be used to analyze biomolecular condensates in vitro [20,114,115] (Figure 3D). This enables the clear distinction of biomolecular condensates from individual proteins, RNA, or DNA, on an AFM microscope at sub-nanometer resolution. owing to the high signal-to-noise ratio ( Figure 3A). In addition, differential interference contrast (DIC) microscopy can be used to visualize biomolecular condensates of label-free biomolecules to avoid labeling artifacts. In addition, a DIC microscope can provide a higher contrast than a normal optical transmission microscope [111] ( Figure 3B). Using these optical microscopes, solution-based biomolecular condensates can be reconstituted and visualized. For example, the interplay of proteins and DNA in in-vitro chromatin condensates was monitored by single-molecule fluorescence microscopy using immobilized fluorescence-stained DNA on the surface and labeled proteins [20,23,112,113] ( Figure 3C). The use of DNA-staining fluorophores, such as YoYo1 or SYTOX Orange, enables labeled proteins to be monitored via single-molecule resolution to determine how many condensates are formed around the DNA and how the proteins induce topological changes in DNA. Moreover, AFM imaging, which provides high-contrast images, can be used to analyze biomolecular condensates in vitro [20,114,115] ( Figure 3D). This enables the clear distinction of biomolecular condensates from individual proteins, RNA, or DNA, on an AFM microscope at sub-nanometer resolution. Live-Cell Imaging Live-cell imaging is vital for studying biomolecular condensates in a physiologically relevant context. Although in-vitro biomolecular condensates can provide quantitative and factorizable LLPS features, they should be tested under

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an in-vivo environment to provide biological context. Using live-cell imaging, we can study the material states of biomolecular condensates in a living cell by directly visualizing the condensates and monitoring the kinetics of fluorescence-labeled proteins (see Section 4.4). Although early phase separation research focused on large biomolecular condensates in cells, such as HP1α condensates or P granules, using a normal optical microscope [11] (Figure 3E), recent studies have investigated smaller biomolecular clusters, such as ParB in bacterial cells, cohesin condensates, and transcription condensates [19,117]. Super-resolution microscopes, such as stimulated emission depletion microscopy (STED), photoactivated localization microscopy (PALM), and stochastic optical reconstruction microscopy (STORM), have been used widely to monitor small condensates that scale tens or hundreds of nanometers [19,118]. For example, the formation of 100 nm-sized transcriptional condensates was captured by PALM [19] ( Figure 3F). In particular, super-resolution microscopes are essential for imaging biomolecular condensates in small prokaryotic cells. An optogenetic protein construct was used to manipulate biomolecular condensates in living cells. The construct was oligomerized via laser excitation and fused with various interacting IDRs, such as FUS, DDX4, and hnRNAPA1 [105] (Figure 3G). A blue laser activated the oligomerization of the oligomerization domains (e.g., Cry2) and induced cytoplasmic and nuclear "optoDroplets" when the concentration of expressed constructs was sufficiently high (Figure 3H). At moderately supersaturated conditions above the threshold, FUS optoDroplets presented liquid-like properties, indicating that LLPS can be manipulated in a living cell [105]. The optoDroplet technique has also been used to draw a phase diagram "in cells," which was consistent with that

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obtained in vitro [119]. Genomic Analysis Chromosome conformational capture techniques, such as Hi-C, split-pool recognition of interactions by tag extension (SPRITE), tyramide signal amplification sequencing (TSA)seq, and Hi-C chromatin immunoprecipitation (HiChipP), are widely used [56][57][58]60,61] to explain how LLPS is involved in the genome organization. For example, the genomic analysis was used to study chromosome compartmentalization probably induced by LLPS of HP1 or PolyComb [120,121]. In a typical Hi-C experiment, different chromatin regions that are in close spatial proximity are cross-linked, fragmented, ligated, and marked with adapters ( Figure 3I). Fragments are then reverse cross-linked, purified, sequenced, and mapped to their genomic locations, yielding genome-wide contact frequency matrices (called the Hi-C map of compartmentalization). The segregation of heterochromatin and euchromatin can be easily observed by the checkerboard pattern of the Hi-C map ( Figure 3J). In addition, techniques such as Chip-seq and ATAC-seq can be used to detect epigenetic marks or specific proteins involved in the phase separation of specific chromatin regions [67][68][69][70]. In particular, a combination of Hi-C and Chip-seq experiments has helped to determine how chromosome compartmentalization, at least partially induced by LLPS, can be linked to certain proteins, DNA sequences, and epigenetic marks [21]. Liquidity Test Multiple experimental options can be utilized to determine the material states of biomolecular condensates in vitro and in vivo [122] (Figure 4). First, the shape of a condensate can reveal the liquidity of the droplet to some extent, because surface tension minimizes the surface-volume ratio by rearranging the molecules of the droplet ( Figure 4A). To quantify

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the sphere-ness of a droplet, the circularity, defined as 4πA/P 2 , can be calculated by measuring the area of the droplet (A) and the perimeter of the droplet (P). The circularity is between 0 and 1 (perfect circle), depending on the closeness to a circle [20,24]. If two distinct droplets are fused to form a spherically reshaped droplet, this indicates that the droplet has liquidity that can rearrange molecules to minimize surface tension, as a single large sphere has a smaller surface-volume ratio than two smaller spheres ( Figure 4B). Multiple experimental options can be utilized to determine the material states of biomolecular condensates in vitro and in vivo [122] (Figure 4). First, the shape of a condensate can reveal the liquidity of the droplet to some extent, because surface tension minimizes the surface-volume ratio by rearranging the molecules of the droplet ( Figure 4A). To quantify the sphere-ness of a droplet, the circularity, defined as 4πA/P 2 , can be calculated by measuring the area of the droplet (A) and the perimeter of the droplet (P). The circularity is between 0 and 1 (perfect circle), depending on the closeness to a circle [20,24]. If two distinct droplets are fused to form a spherically reshaped droplet, this indicates that the droplet has liquidity that can rearrange molecules to minimize surface tension, as a single large sphere has a smaller surface-volume ratio than two smaller spheres ( Figure 4B). To quantify how much the droplet is close to a spherical shape, circularity is calculated by measuring

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the area (magenta regions) and the perimeter of a droplet (blue boundaries). The circularity is defined by 4πA/P 2 and it ranges from 0 (very different from a circular shape) to 1 (a circular shape). The mobility of individual molecules inside a droplet is a good indicator of liquidity. In a typical aqueous solution, liquid-like molecules diffuse much faster than solid-or gellike molecules. Hence, molecules inside a liquid droplet are mobile, and the molecules are (relatively quickly) exchangeable between a droplet and the background solution. This mobility has been tested using FRAP experiments ( Figure 4C). Using confocal microscopy, fluorescent molecules inside the small focal volume of a droplet are bleached, and the system is monitored to determine whether the bleached signals are recovered through the exchange of molecules between the bleached area and its surroundings. 1,6-hexanediol treatment is a typical method used to test the liquidity of condensates, since 1,6-hexanediol dissolves liquid droplets by inhibiting weakly hydrophobic interactions between molecules [123]. However, the results of recent studies suggested that 1,6hexanediol treatment should be carefully considered when droplets are associated with To quantify how much the droplet is close to a spherical shape, circularity is calculated by measuring the area (magenta regions) and the perimeter of a droplet (blue boundaries). The circularity is defined by 4πA/P 2 and it ranges from 0 (very different from a circular shape) to 1 (a circular shape). The mobility of individual molecules inside a droplet is a good indicator of liquidity. In a typical aqueous solution, liquid-like molecules diffuse much

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faster than solid-or gel-like molecules. Hence, molecules inside a liquid droplet are mobile, and the molecules are (relatively quickly) exchangeable between a droplet and the background solution. This mobility has been tested using FRAP experiments ( Figure 4C). Using confocal microscopy, fluorescent molecules inside the small focal volume of a droplet are bleached, and the system is monitored to determine whether the bleached signals are recovered through the exchange of molecules between the bleached area and its surroundings. 1,6-hexanediol treatment is a typical method used to test the liquidity of condensates, since 1,6-hexanediol dissolves liquid droplets by inhibiting weakly hydrophobic interactions between molecules [123]. However, the results of recent studies suggested that 1,6-hexanediol treatment should be carefully considered when droplets are associated with chromatin, because the high concentration of 1,6-hexanediol can facilitate cation-dependent chromatin compaction [124,125]. Alcohols, such as 1,6-hexanediol, seem to remove water molecules around the chromatin and compact the chromatin [124]. Finally, reversibility is a common feature of liquid droplets. When background molecules are depleted, dissociation of a liquid droplet can be observed [20,23] (Figure 4D). These qualitative criteria can be used to determine the liquid-state condensations; however, quantitative analysis (such as viscoelasticity and hydrodynamics measurement [126]) is needed to define the exact material states of the biomolecular condensates, especially for in-vivo experiments. Computational Modeling Computer simulations have been adopted to provide a deeper understanding of the role of phase separation in chromosomes. In computer simulations, one can systematically alter models and parameters, which is limited and challenging in experiments, and this reveals the

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effects of different physical factors on the phase behavior of the modeled system and its consequences for the system properties, such as the chromosome structure. Inspired by the polymeric nature of chromosomes, polymer simulations have been widely utilized to model chromosome systems. However, phase separation (and even microphase separation) is a collective behavior of particles and their interactions, which requires a large number of particles. Hence, to observe biomolecular phase separation in silico, a sizable system, and the corresponding computational costs, are inevitable. Therefore, atomistic simulations are rarely utilized to study phase behaviors [127]. A common strategy to overcome the system size problem is coarse-graining, which reduces the degree of freedom to describe each molecule [128,129]. Typically, a group of atoms is represented by a bead. For example, one can model each residue using a bead, and the whole protein becomes beads on a string. Although this (single-bead-per-residue) choice may seem natural, there is no golden rule for coarse-graining. As there is a tradeoff between resolution and computational cost, the details of coarse-graining depend on the system properties of the investigation. Coarse-grained models for biomolecular phase separation have been developed and deployed with a range of resolutions [35,37,47,74,[130][131][132][133][134][135][136][137][138]. To further reduce the computational cost, the polymer system can be depicted by functional integrals over fluctuating fields; this is referred to as the field-theoretic approach [139]. This approach has recently been utilized to study biomolecular phase separation, especially when electrostatic interactions are dominant [140][141][142]. For chromosome modeling, the primary experimental target to reproduce computationally is often the

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Hi-C maps, as the contact information can be readily extracted from the simulation trajectories. As A/B compartmentalization is a notable feature of the maps, it can be reproduced by most simulations [143][144][145], and is usually explained by microphase separation [66,146]. Even the field-theoretic approach can reproduce A/B compartmentalization [147]. Another interesting topic is the role of phase separation at the level of the local structure of the chromosome; computational analyses were recently used to study various scenarios of local phase separation [148]. Local Phase Separation Models: BIPS and SIPS Chromatin can undergo phase separation [149,150], and DNA-binding proteins can form liquid-like droplets around DNA in vitro and in vivo [19,20,83,84]. In addition, droplet formation can modulate the physicochemical properties of adjacent chromatin regions [105,151] through local changes in the effective interactions between different regions of the polymer, which induces a different microphase separation pattern. In the stickers-and-spacers framework, local phase separation can generate, modify, or remove stickers on chromatin. If phase separation locally gathers two distant chromatin regions by modulating their effective interaction strength, it can lead to a notable change in the chromatin structure. This mechanism is called bridging-induced phase separation (BIPS) [20] or polymer-polymer phase separation (PPPS) [152]. The hallmark of this model is that the mediating molecules do not undergo phase separation unless they are mixed with chromatin, which differentiates BIPS from typical phase separation [152]. BIPS versus SIPS The BIPS model states that biomolecular condensates are formed via bridging of distant regions on a long DNA chain by proteins that possess multiple

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DNA-binding sites [20,152,153] (Figure 5A). Once a multivalent chromatin-binding protein connects two different DNA segments and forms a DNA loop, the bridged region can function as a nucleation point for further growth of condensates of the chromatin bridging proteins ( Figure 5B). The BIPS model was initially suggested by molecular simulations, showing that a protein with more than two DNA-binding sites can be clustered along a DNA chain [108,154]. The clustering mechanism can be explained as follows: once a protein bridges two different DNA segments of a long DNA molecule to form a DNA loop, the local DNA concentration at the bridged region increases to recruit more DNA-binding proteins. In addition, the entropic loss (due to translational entropy of a DNA chain) is much lower when DNA-binding proteins bind to the bridged region of DNA than when they bind to a non-bridged region to form a new bridge [110,153]. [20,152,153] (Figure 5A). Once a multivalent chromatin-binding protein connects two different DNA segments and forms a DNA loop, the bridged region can function as a nucleation point for further growth of condensates of the chromatin bridging proteins ( Figure 5B). The BIPS model was initially suggested by molecular simulations, showing that a protein with more than two DNA-binding sites can be clustered along a DNA chain [108,154]. The clustering mechanism can be explained as follows: once a protein bridges two different DNA segments of a long DNA molecule to form a DNA loop, the local DNA concentration at the bridged region increases to recruit more DNA-binding proteins.

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In addition, the entropic loss (due to translational entropy of a DNA chain) is much lower when DNA-binding proteins bind to the bridged region of DNA than when they bind to a non-bridged region to form a new bridge [110,153]. Cartoon of a multivalent DNA-binding protein that has at least two DNA-binding sites. DNA-binding sites of the protein are depicted as orange circles, and the protein is denoted as a blue circle. (B) Schematic of the BIPS model. Two DNA-binding sites per protein are sufficient for condensation, and a long DNA molecule is irreplaceable in this mechanism. (C) Cartoon of a multivalent protein-binding protein that induces typical phase separation. Yellow circles on the protein (blue circle) depict protein binding sites. (D) Typical phase separation mechanism (SIPS), which uses multivalent protein-protein interactions. At least three binding sites are necessary DNA-binding sites of the protein are depicted as orange circles, and the protein is denoted as a blue circle. (B) Schematic of the BIPS model. Two DNA-binding sites per protein are sufficient for condensation, and a long DNA molecule is irreplaceable in this mechanism. (C) Cartoon of a multivalent protein-binding protein that induces typical phase separation. Yellow circles on the protein (blue circle) depict protein binding sites. (D) Typical phase separation mechanism (SIPS), which uses multivalent protein-protein interactions. At least three binding sites are necessary for phase separation, and DNA plays an auxiliary role in this process. (E,F) Dependence of the protein-DNA cluster size on the length of DNA shown in the previous study of cohesin-mediated BIPS [20].

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(E) Cartoons of possible protein-DNA complex topologies for a range of DNA lengths and (F) a plot showing cluster size versus DNA length [20]. With <3 kbp of DNA, a single protein binds to DNA with no cooperativity (blue line). With~3 kbp DNA, multivalent DNA-binding proteins can bridge a DNA to form a loop. For longer DNA (>3 kbp), a larger cluster can be formed, and the cluster size scales as a power law with the DNA length (red line). The BIPS mechanism differs from typical phase separation that employs interactions between multivalent soluble proteins ( Figure 5C), and some authors call this typical phase separation simply LLPS (as opposed to PPPS) [152,155]. However, since BIPS/PPPS can also induce liquid-like condensates [20], which is a hallmark of LLPS, we suggest that BIPS should be considered a type of LLPS. For non-BIPS LLPS, we propose a new term self-association-induced phase separation (SIPS). Note that LLPS implies that the resulting condensates possess liquidity, and SIPS can lead to the formation of gel-or even solid-like condensates [156], which may be confusing if we use LLPS instead of SIPS. Hence, we recommend that the use of LLPS be restricted to the formation of liquid-like condensates, regardless of the underlying molecular mechanism. Although a protein in the BIPS model is involved in multiple DNA interactions, it does not require multiple protein-protein interactions, which are the main driving forces of SIPS. Thus, BIPS does not require an IDR of a scaffold protein, which typically provides multivalency and flexibility because flexible and long

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DNA can provide multiple binding sites for multivalent DNA-binding proteins. Moreover, while DNA organization is strongly coupled to DNA-protein cluster formation in BIPS, the organization of DNA can be completely independent of phase separation in SIPS ( Figure 5D). Although the molecular mechanisms differ, BIPS shares many similarities with SIPS. For example, condensates formed by BIPS can have liquidity [20]. Hence, the techniques used to study SIPS can be applied to analyze BIPS. Cohesin-Mediated BIPS The cohesin-SMC complex is important for interphase chromosome organization [157,158], and in-vitro experiments have shown that the complex forms condensates via the BIPS mechanism [20]. Cohesin is a good model for a protein with multiple DNA-binding sites. Because it acts primarily as a motor protein to extrude a DNA loop for interphase chromosome organization, there are at least two DNA-binding sites on the surface of the cohesin protein for the relative motion of two different DNA-binding sites in an ATP hydrolysis-dependent manner. Multiple DNA-binding sites on the cohesin protein have been confirmed by various structural studies, suggesting that it can bridge distant DNA segments [158][159][160][161]. The cohesin-SMC complex has a non-monotonic size dependence on DNA length, and the cohesin-dependent BIPS mechanism can successfully explain the behavior by considering DNA bridging activity ( Figure 5E,F) [20]. In an experiment, the DNA length was varied from 100 bp to 50 kbp, while the DNA concentration was fixed. The DNA-cohesin mixture was incubated and imaged using an AFM. For short DNA lengths (l < 3 kbp), no clear cohesin-DNA cluster was formed; however, beyond

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a crossover point of l c~3 kbp, the cluster size increased rapidly with DNA length, scaling as a power law ( Figure 5F). The crossover point can be explained quantitatively by considering the free energy cost related to DNA looping by the bridging of a cohesin protein. When a single cohesin complex bridges two DNA sites to form a loop, the free energy change can be roughly estimated based on two contributions: (1) the DNA bending energy; and (2) the entropic cost due to DNA looping. The optimal length for DNA looping can be obtained by minimizing the following free energy: F k B T = 2εl p l + 1.5 log l l p (8) where l is the loop size when DNA is bridged by a single cohesin protein complex, l p = 50 nm is the persistence length of DNA, and ε = 16 is the shape parameter based on a tear drop [162]. The free energy is numerically minimized around the DNA length of 3 kbp, and hence, DNA must be at least 3 kbp to be bridged. A longer DNA construct (>3 kbp) provides a nucleation point for further growth of the condensates, which catalyzes cluster growth. The power-law scaling behavior of cluster size with DNA length was reproduced by computer simulations, which modeled cohesin as a patchy particle with two distinct DNA-binding sites [20]. Interplay of BIPS and SIPS Although BIPS and SIPS seem to be opposing concepts, they can work together to induce efficient phase separation. As discussed, in

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the BIPS model, a bridged loop can act as a nucleation point ( Figure 5B). The loop can attract multivalent proteins involved in SIPS ( Figure 5C), resulting in the interplay between BIPS and SIPS. It is probable that some topologically associating domains (TADs), observed via Hi-C analysis [163], might be formed by BIPS, since an extruded DNA loop at the convergent CCCTC-binding factor (CTCF)-binding sites can act as a nucleation point for the growth of multivalent DNAbinding proteins assemblies. If this model is correct, interactions between a DNA loop and other nuclear condensates, such as transcriptional condensates, would be observed. Concluding Remarks In this review, we discuss the fundamental principles of biomolecular phase separation, including the stickers-and-spacers model, and the current understanding of phase separation involved in DNA-related processes in chromosomes. The stickers-and-spacers model is a simple conceptual framework inspired by polymer theories and can be applied to the phase separation of biopolymers with various architectures. Microphase separation is another important concept adopted from polymer physics, which can explain the segregation of euchromatin and heterochromatin. Various nuclear/chromosomal biomolecular assemblies formed by phase separation are involved in chromosome organization or many genome-related biologically important functions. Notably, in chromosomes, very long DNA molecules are involved in phase separation. The BIPS model illustrates the role of DNA in phase separation and utilizes multivalent DNA interactions of a protein to drive phase separation. However, although a few in-silico and in-vitro examples have been identified, it needs more examples of phase separation driven by proteins bridging two different DNA segments

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using multiple DNA-binding sites. Moreover, the in-vivo relevance of the BIPS model needs to be clearly demonstrated. Currently, a complete conceptual framework to understand the phase separation involved in chromosome organization is lacking, as the inside of a cellular nucleus is filled with many molecules, forming a heterogeneous and disordered mass of biopolymers, which is far from being in equilibrium. To cut the Gordian knot of the chromosome, a fuller understanding of the local and global topologies of chromosomes is required. In particular, the static and dynamic actions of phase separation on DNA topology are key factors for determining the structure and properties of chromosomes, as illustrated by the BIPS model. We need to observe how topological changes in DNA induce phase separation in real time; however, the spatiotemporal resolution of current microscopes is limited. Monitoring the full dynamics of DNA topology and protein assembly may show this process clearly. Regarding simulations, although it is not yet possible to simulate the full nucleus on the atomic level, theoretical and numerical methods can provide valuable information that the experiment cannot access. In this complicated system, multi-scale simulations are promising for accessing a wide range of length and time scales. User-friendly and open-source packages will greatly benefit the community. In the future, we expect that these approaches will provide a clear understanding of the role of phase separation in the chromosome, such as how the chromosome is segregated into two compartments, and how other bimolecular condensates involved in DNA-related functions are condensed with DNA. This understanding will help

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to explain multiple phenomena in the nucleus throughout the cell cycle.

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Concussion Injury In Sports : Brief Review Of The Epidemiology And Initial Management Not available.Nepal Journal of Neuroscience, Volume 15, Number 2, 2018, page: 11-17 have investigated the characteristics of CIS in relation to mild head injury and the type of sports with different bodies having different methods of diagnosis and criteria for further play (Figure 1). 15,20efi nition and Epidemiology: Concussion is defi ned by Merriam-Webster dictionary as, a: a stunning, damaging, or shattering effect from a hard blow; especially: a jarring injury of the brain resulting in disturbance of cerebral function.b:a hard blow or collision.It means to "shake violently" from the Latin word Concutere.In the USA alone around 3.8 million concussions are reported each year and the many still go unreported.Concussion can occur in upto 14% of all sports related injuries with 700,000 concussion between 2005 -2010 and 13% of them being recurrent concussion. 5t is more common in female sports, younger age, and in actual matches than during training and certain type of sports as stated above. 10,21in males its due to player to player contact injury and in females due to trauma by fall, equipment or surface. 6Most of the symptoms last less than 72 hours and the majority will resolve within a week and brief loss of consciousness or seizure may not lead to delay in recovery. 4The majority (80%) will be asymptomatic within 10 days and the rest may exhibit symptoms for few weeks. Pathophysiology: Unlike head injury direct impact to the head is not needed for concussion which is

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caused by rotational and angular forces leading to neuronal disruption leading to potassium effl ux, release of calcium and excitatory amino acids leading to paradoxical blood fl ow. 14,18This leads to neuronal injury that may persist for weeks and hence delaying the recovery of the patient.Studies have shown that mild head injuries can lead to increases in hyperphosphorylated paired helical fi lament 1 tau in the hippocampus that produces long term behavioral defi cits. 8Another study showed that a panel of biomarkers, increases in NF-L and Tau markers, TNFα and IL8 markers, [SYP]CD11b+/[CD81]CD11b+, have the potential to surrogate chronic neural damage in CIS. 12,27iagnosing CIS: The fi rst step is to make the diagnosis of concussion which will help in early recovery, risk of further complications, reduce other musculoskeletal injuries, and other neurological or psychiatric illness.Due to the lack of a proper clinical or diagnostic pattern it is often a clinical diagnosis. 19CIS diagnosis will depend on the severity of the injury, the complains by the athlete and the signs seen by the attending medical person.The common symptoms are given in Table 1. Fatigue Table 1: Some of the common symptoms of concussion. Concussion can also be defi ned as mild, moderate or severe.Grade 1 concussion, symptoms last for less than 15 minutes.There is no loss of consciousness.Grade 2 concussion, there is no loss of consciousness but symptoms last longer than 15 minutes.Grade 3 concussion, the person loses consciousness, sometimes just for a few seconds.A history of CIS is associated with sustaining another concussion and the

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number of CIS, children and adolescents, duration or Grade and severity often will prolong the recovery.Other factors like headache more than 60 hours, presence of more than three symptoms are associated with prolonged recovery. The initial examination starts with airway, breathing and circulation followed by cervical spine injury assessment.Most of these fi ndings are normal in CIS and may need some form of assessment form to rule out severe concussion.The athlete must be barred from return to play till concussion is ruled out. Signs of concussion and check tools: Assessment tools: There is no single method to diagnose CIS and in literature there are many tools that have been described.The following Table gives the presently available tools (Table 2). 26 Management of CIS Sport-specifi c challenges for CIS Second impact injury: this was fi rst described by Schneider in 1973 and then used in an example of a football player who died with no apparent trauma but had sustained a injury 4 days earlier by Saunders and Harbaugh. 24,25classically the athlete suffers a concussion and before the symptoms resolve they return to the sport during which they suffer a relatively minor trivial injury.This lead to a stunned athlete who can resume the play but then suddenly they collapse with dilated pupils and respiratory failure.Pathologically it is due to cerebrovascular dysregulation with edema and herniation.This term means that a person is prone to repeated concussion after the fi rst injury and hence must be carefully observed and prevented to play, to prevent further complications. Using video in

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CIS With the use of more and more technology in sports it is common to fi nd and record an impact or injury that can be replayed again and again to study the nature of the severity of injury.Application of such in sports has led to the better understanding od CIS which can allow to individual or organizational policy making and management.Although video recording helps one must still understand its limitations in recording, showing the angle of impact or response from the athletes. 13he initial examination will either confi rm or rule out CIS and hence the athlete can either return to play/ home care with observation or will need further medical attention in a hospital.Rest is the most important prevention and precaution to be taken in CIS.In case of Grade 2, 3 concussion the athlete needs to be taken to a medical center with neurosurgical facilities.Repeated waking up is controversial in the detection of CIS. 9 Some patients may need neuroimaging to further diagnose severe head injury the guidelines of which have been laid down by the American College of Emergency Physicians, American academy of pediatrics and the American association of family physicians (Table 3). 11,26,28able 3.The present guidelines for neuroimaging in concussion from American association of family physicians, American Academy of Pediatrics and the American Academy of Family Physicians. 11,26,18 CIS Management at the fi eld When an athlete sustains an injury then the medical professional, trainer or coach should immediately examine with one of the CIS assessment tools.If it suspected the athlete should

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be bared from further play and continuous observation should be done and the index of medical center referral or neuroimaging should be kept low.Unless the symptoms have remitted they should not be allowed to return to sports. Treatment of CIS All CIS athletes are followed with a graduated play protocol each step of which requires 24 hours.At the end Concussion in sports the athlete needs a detailed checkup and then only allowed to play (Table 4). 17recent studies with functional MRI has shown that even with minor head injury players can have abnormal neuropsychological results which are called as subconcussion that can progress to chronic traumatic encephalopathy. 3Although well documented for adults the effi cacy of this graduated scale is unknown in younger children. There are no medications for CIS and most are used for symptomatic treatment of headache, nausea, vomiting, sleep disturbances or psychological problems.Rehabilitation, Buffalo concussion treadmill test, aerobics, exercises may be benefi cial in CIS. 22covery in CIS 22 The defi nition of recovery is ill defi ned for CIS with delayed recovery upto a month after injury.The cognitive or academic recovery may take time and needs to be further studied.15% of the athletes may return to play within one day and the same number took a month to return across younger age, high school and college groups.Adolescents may have longer recovery from CIS leading to altered academic performance which may suggest the younger brain may be more susceptible to injury.All aspects of the athlete's activity including, school, work, and daily activities must

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be assessed thoroughly before release from medical care.Neuropsychological, neurocognitive, motor, balance and physical examination must be made to avoid missing important signs of CIS. Concussion awareness and education All the sports can lead to CIS injury and awareness and education for the athlete, coach, organization, family and schools is important to avoid this injury.Some sports like football which has heading as part of the game it is diffi cult to control impact injury and presently there are no devices available to protect form CIS. Protective equipment like helmets, padding and covers can theoretically lower the risk of CIS injuries by 85% if it is worn properly.Children must always be supervised, rules of the game or the pool or outdoor park must be followed, and diving is discouraged in less than 12 feet deep pool/river/ponds.Avoid sports if ill, be aware of neighboring players and proper maintenance of the equipment can reduce injuries.Use of alcohol or other neuro depressant medication is to be banned and seat belts must be worn in all high speed activities.Few studies have though shown no benefi t of using helmets to prevent concussion, subconcussion or rotational injuries and thus strict rules implementation, avoidance of impact, preventing fi ghts or collision can reduce CIS injuries. 26ducation and awareness training including information on the risk of each sportis important not only to the athletes and the coach but also to the public.Teaching should be started as a curriculum in schools regarding the dangers of concussion and the importance of safe play will defi nitely help

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to reduce CIS injuries.The coach and the supporting team must be regularly appraised regarding new developments in the management of concussion. Current and future research Although much has been studied in CIS pathology yet its exact cause remains unknown.Future studies in animal models and artifi cial dummy models could help prevent CIS injuries. 1,7The current research of MRI on Guidelines from the American College of Emergency Physicians Imaging is indicated in patients with a loss of consciousness or amnesia if at least one of the following is present: headache (diffuse), vomiting, age older than 60 years, intoxication, defi cits in short-term memory, evidence of trauma above the clavicle, seizures, GCS score of less than 15, focal neurologic defi cits, coagulopathy. Imaging is indicated in patients with no loss of consciousness or amnesia if at least one of the following is present: focal neurologic defi cit, vomiting, severe headache, age older than 65 years, signs of basilar skull fracture, GCS score of less than 15, coagulopathy, signifi cant mechanism of injury (e.g., ejection from vehicle, pedestrian struck by vehicle, fall from a height greater than 3 ft or fi ve stairs). Guidelines from the American Academy of Pediatrics and the American Academy of Family Physicians Perform imaging in patients with loss of consciousness of greater than 60 seconds, evidence of skull fracture, or focal neurologic fi ndings. Consider imaging or observation if patient has brief loss of consciousness. Note that nonspecifi c signs (e.g., immediate seizures, headache, vomiting, lethargy) increase the likelihood of intracranial injury, but have

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very limited predictive value. Concussion in sports subconcussion and in specifi c cohorts of athletes can help increase our knowledge of CIS. Summary CIS is a complex injury the pathogenesis of which is yet to be fully understood.If not recognized early, it can lead to disastrous consequences including death.The entire supporting team should be aware of such injury and it clinical manifestations which if suspected the athlete must be barred from further play and given medical care.Recovery must be closely followed in a graduated step wise manner and made clear not to take part in physical impact sports.Proper education of the public, precautions taken during sports can help reduce CIS injury. Figure 1 : Figure 1: Defi nition of different bodies of Concussion. Table 4 . Halstead ME, Walter KD; Council on Sports Medicine and Fitness.American Academy of Pediatrics.Clinical report-sport-related concussion in children The graduated return to play protocol.17

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Prevention of Exercise-Associated Dysglycemia: A Case Study–Based Approach Regular physical activity is associated with many health benefits for people with type 1 diabetes, including improved quality of life, increased vigor, enhanced insulin sensitivity, and protection against cardiovascular disease and other diabetes-related complications (1). Despite its benefits, exercise can aggravate dysglycemia because it causes major changes to glucose production and utilization rates (2). For example, mild to intense aerobic exercise (e.g., walking, cycling, jogging, and most individual and team sports) increases the risk of hypoglycemia during the activity and in recovery because of impaired rates of glucose production, whereas very intense aerobic exercise (>80% of maximal aerobic capacity) and anaerobic exercise (e.g., sprinting and heavy weightlifting) can cause glucose levels to rise because of reduced rates of glucose disposal (3,4). Numerous strategies have been developed to help limit hypoglycemia during exercise in individuals with type 1 diabetes. One of the main reasons hypoglycemia occurs is the inability to naturally reduce insulin levels at the onset of exercise (1). Strategies to help limit hypoglycemia include exercising in the fasted state (5), reducing the insulin for the meal before exercise (6,7), interrupting basal insulin infusion for patients on insulin pump therapy (8–10), and increasing carbohydrate intake (11–14). Continuous glucose monitoring (CGM) can also help to prevent hypoglycemia in people with type 1 diabetes (15). In contrast, very little has been done to develop strategies for exercise-associated hyperglycemia, even though the mechanisms for this effect are largely established (16). The inability to naturally raise insulin levels after intense exercise to

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combat a rise in catecholamines is the main reason why post-exercise hyperglycemia occurs (17), although excursions associated with aggressive insulin reductions or excessive carbohydrate intake also likely bear some blame (18). In instances of exercise-associated hyperglycemia caused by intense exercise, insulin concentrations … R egular physical activity is associated with many health benefits for people with type 1 diabetes, including improved quality of life, increased vigor, enhanced insulin sensitivity, and protection against cardiovascular disease and other diabetes-related complications (1). Despite its benefits, exercise can aggravate dysglycemia because it causes major changes to glucose production and utilization rates (2). For example, mild to intense aerobic exercise (e.g., walking, cycling, jogging, and most individual and team sports) increases the risk of hypoglycemia during the activity and in recovery because of impaired rates of glucose production, whereas very intense aerobic exercise (>80% of maximal aerobic capacity) and anaerobic exercise (e.g., sprinting and heavy weightlifting) can cause glucose levels to rise because of reduced rates of glucose disposal (3,4). Numerous strategies have been developed to help limit hypoglycemia during exercise in individuals with type 1 diabetes. One of the main reasons hypoglycemia occurs is the inability to naturally reduce insulin levels at the onset of exercise (1). Strategies to help limit hypoglycemia include exercising in the fasted state (5), reducing the insulin for the meal before exercise (6,7), interrupting basal insulin infusion for patients on insulin pump therapy (8-10), and increasing carbohydrate intake (11)(12)(13)(14). Continuous glucose monitoring (CGM) can also help to prevent hypoglycemia in people with type 1 diabetes

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(15). In contrast, very little has been done to develop strategies for exercise-associated hyperglycemia, even though the mechanisms for this effect are largely established (16). The inability to naturally raise insulin levels after intense exercise to combat a rise in catecholamines is the main reason why post-exercise hyperglycemia occurs (17), although excursions associated with aggressive insulin reductions or excessive carbohydrate intake also likely bear some blame (18). In instances of exercise-associated hyperglycemia caused by intense exercise, insulin concentrations must increase rapidly in the bloodstream to help stabilize glucose levels (3), although evidence is lacking to guide the amount of insulin that should be administered as a correction dose. Unfortunately, glucose control in the hours after exercise is also challenging. There may be increased meal-associated hyperglycemia as a result of insulin dose reductions before exercise or excess carbohydrate consumption to prevent hypoglycemia (19-21). There also may be late-onset hypoglycemia because of heightened skeletal muscle insulin sensitivity (22) and reduced glucose counterregulatory responses (23). The risk of nocturnal hypoglycemia has been estimated to be as high as 30% when individuals perform moderate-intensity, steady-state, aerobic N U T R I T I O N F Y I exercise for 45 minutes in the late afternoon (24,25). The simplest approach for prevention of hypoglycemia during exercise may be to increase carbohydrate intake based on the pre-exercise blood glucose concentration (Table 1) (26). This strategy can be used both for exercise that occurs after a meal when circulating insulin levels are high and for exercise performed in a fasting or postabsorptive

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state, although the latter typically requires less carbohydrate intake because circulating insulin levels are lower. Consuming extra carbohydrates (henceforth called "extra carbs"), and therefore extra calories, may not be desirable, however; insulin dose adjustments may be preferable. Knowing how many extra carbs to consume is also a challenge. An additional strategy to help limit hypoglycemia is to use CGM and to initiate carbohydrate intake only when needed, perhaps in conjunction with pre-exercise insulin dose adjustments (15). Table 2 shows the recommended intake amounts of fast-acting carbohydrate based on measured CGM glucose values and the directional blood glucose trend arrows observed during exercise (15). A more physiological approach to preventing hypoglycemia is to attempt to lower circulating insulin levels for exercise. However, this can be difficult to manage precisely because of the pharmacokinetics of the various forms of insulin used and the ways in which they are delivered (i.e., subcutaneous rather than in the portal system). In general, basal insulin reductions and/or mealtime insulin adjustments should be considered for patients who can forecast the timing and intensity of their aerobic activity to help mimic normal physiology. Table 3 provides general adjustment strategies for bolus insulin based on one study conducted in adults with type 1 diabetes (6), and Table 4 provides basal rate reductions for insulin pump users based on the authors' experience and studies conducted on basal rate interruptions for exercise (8-10). Even when insulin adjustments are made, some additional carbohydrates may be needed if the exercise is prolonged or glucose levels drop to a critical

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level (<90 mg/dL). In such situations, directional trend arrows on CGM devices are particularly helpful in identifying when to initiate carbohydrate intake. In the following case studies, we highlight some common examples of exercise-associated dysglycemia and possible strategies to help improve glycemic control. These cases are hypothetical, and the recommendations have not been tested in real patients. Case 1. Aerobic Exercise and Hypoglycemia A 26-year-old woman (weight 55 kg) who has had type 1 diabetes for 12 years expresses concern to her health care team about repeated episodes of hypoglycemia during her aerobic workout (cycling and training on an elliptical machine). She is using a multiple daily injection (MDI) insulin regimen, taking insulin glargine at bedtime and insulin aspart at mealtimes. She takes her aspart with every meal and glargine each night. She begins exercising 4 hours af- Option 1. Add Extra Carbs One simple strategy to reduce the likelihood of hypoglycemia for this patient is to recommend that she consume fast-acting carbohydrates just before and throughout the activity. These extra carbs should be consumed without administering insulin. Additional carbohydrates are often recommended for activities that last >30 minutes (27,29). The amount of extra carbs to consume is based on the size of the individual and the intensity of exercise. Evidence suggests that adolescents and young adults oxidize carbohydrate at a rate of ~1 g/kg/hour of exercise (30,31), whereas carbohydrate absorption from the gastrointestinal tract appears to be limited to ~60 g/hour during exercise (14). Thus, the extra carbs needed may be as much as 60

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g/hour of exercise in this patient while she is exercising at a moderate intensity. A study by Francescato et al. (32) showed that the amount of carbohydrate required before and during exercise to prevent hypoglycemia in individuals with type 1 diabetes is correlated to plasma insulin, but not fitness, level. Therefore, this patient's training status may not affect her extra carbs requirement, but the timing of her exercise in relation to her last meal might. In one study (32), the amount of extra carbs needed by type 1 diabetes patients to prevent hypoglycemia decreased as the time elapsed from insulin administration (regular insulin) increased. However, in another study of people using insulin isophane (Humulin N) and lispro, there was a similar risk of hypoglycemia during early and late postmeal exercise (33). Based on a large survey of people with diabetes (the type of diabetes was not identified), exercising 1-2 hours after a meal was associated with greater drops in glucose than exercising within 30 minutes before or >3 hours after a meal (34). We have also found that fewer extra carbs will be needed if there is Intense (e.g., intense cycling, running, dancing, or individual or team sports) Many patients who are on lowcarbohydrate diets or who are interested in weight loss might find this amount of carbohydrate excessive. In this case, the woman could consume a total of 55 g of rapid-acting carbohydrate during the first hour of cycling and an additional few grams if needed before her 20-minute elliptical session. Although many patients find

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this amount of extra carbs excessive, one study of adolescents with type 1 diabetes found that it prevented hypoglycemia without promoting hyperglycemia (11). The subjects in this study were all on multiple daily injection insulin regimens using ultralente insulin as their basal insulin and lispro as their mealtime insulin. Using different basal and bolus insulins or using an insulin pump instead of taking multiple daily injections may influence the percentage of reduction in bolus insulin needed for aerobic exercise. Because excessive carbohydrate intake may promote gastric distress (35) and will add to the total daily calories consumed (220 extra kcals in this example), this option may not be preferred for routine exercise, as in this case. Regular exercise reduces total daily insulin needs in lean individuals with type 1 diabetes by ~10-20% (36)(37)(38). Moreover, this amount of training would be expected to lower her reliance on carbohydrates as a fuel for exercise (39). Option 2. Adjust Basal Insulin Because of the timing of her exercise, the health care team has noted that this patient has little to no active onboard prandial insulin at the start of her afternoon workout. During exercise, glucose is taken up into skeletal muscle and then oxidized via a noninsulin-mediated process (40). However, some insulin is still required in the blood during exercise to prevent hyperglycemia caused by excessive hepatic glucose production and impaired glucose uptake into working muscle (41,42). Thus, one strategy might be to lower her bedtime insulin glargine by 20% on the evening before exercise or to split her

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long-acting insulin into two equal doses (morning and night) and reduce the morning dose on the days she exercises. A reduction in bedtime insulin could also then be made if nocturnal hypoglycemia continued to occur after exercise. However, for MDI patients, this strategy may increase the risk of hyperglycemia throughout the day before the physical activity. In any case, this patient should measure glucose levels during the night after exercise at 3:00 a.m. to determine how much her glucose drops between bedtime to 3:00 a.m. Anyone whose glucose drops >40 mg/dL overnight should be considered to be at high risk for nocturnal hypoglycemia (43). Option 3. Frequent Glucose Monitoring and a Change to Insulin Pump Therapy It is usually recommended that at least two pre-exercise glucose measurements be taken and that monitoring be done intermittently during exercise (e.g., every 30 minutes). Frequent glucose monitoring after exercise should help protect against post-exercise hypoglycemia. Research has shown that the greatest susceptibility to hypoglycemia after exercise occurs at ~2:00-3:00 a.m. (43,44). However, nocturnal hypoglycemia can occur any time after exercise (45). If hypoglycemia cannot be managed through any of these recommendations, the health care team should ask this patient to consider continuous subcutaneous insulin infusion (CSII, or insulin pump therapy). Since the late 1970s, many studies have shown that CSII leads to significant improvements in glycemic control, with resulting improvements in A1C (46). Increased flexibility with regard to exercise has also been reported with CSII (19). For this patient, CGM and pump therapy should provide added flexibility with regard

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to basal insulin adjustments and carbohydrate intake based on directional trend arrows from the CGM. It should be acknowledged, however, that insulin pumps and CGM have not yet been widely adopted, perhaps because of accessibility issues, costs, device complexity, and attitudes about ease of use (47). Case 2. Post-Exercise Hyperglycemia and Nocturnal Hypoglycemia A 17-year-old boy who has had type 1 diabetes for 6 years has been experiencing nocturnal hypoglycemia after high-intensity interval training with sprints. He has been using an insulin pump for 3 years and has been participating in contact sports for numerous years. He has a low body fat percentage, weighs 84 kg, and is 6 feet, 2 inches tall. Because of the nature Option 1. Conservative Correction of Post-Exercise Hyperglycemia and a Bedtime Snack Post-exercise hyperglycemia can result from intense exercise (16), excessive carbohydrate intake (11,19), or large insulin dose reductions (18). Treating post-exercise hyperglycemia must be done cautiously, particularly at bedtime, because severe hypoglycemia may ensue (48). Although no standard guidelines exist for treating post-exercise hypoglycemia, a conservative insulin correction (50% correction dose), along with frequent glucose monitoring, seems prudent. Episodes of nocturnal hypoglycemia are a concern for active people with type 1 diabetes (49). Strategies for preventing nocturnal hypoglycemia differ for patients who are on MDI versus those on CSII. Kalergis et al. (50) suggest that patients on MDI should consume a bedtime snack that consists of protein and complex carbohydrates. Those on CSII can do this as well, but they also have the capacity to adjust their basal insulin

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infusion rate both during exercise and in recovery. Small bolus corrections are also more easily calculated and performed with pump therapy. In addition to consuming a bedtime snack, insulin adjustments may be required as discussed in option 2 below. Although low-glycemic index meals and bedtime snacks often help to limit postprandial hyperglycemia in MDI or CSII patients, it appears that this strategy does not entirely protect against post-exercise, late-onset hypoglycemia (21). Either way, some examples of appropriate snacks in the recovery period once post-exercise hyperglycemia has been resolved include fruit smoothies (dairy-based), yogurt drinks, or fruit mixed with yogurt. Studies have shown that dairy (e.g., chocolate milk) consists of a 4:1 ratio of carbohydrate to protein, is beneficial for muscle glycogen resynthesis, and aids in rehydration (51). For individuals who are lactose intolerant, protein options include nuts and seeds (e.g., almonds, peanuts, or pumpkin seeds), quinoa, and soy milk. Lactose-free yogurt or dairy options are also available. Because protein requirements are greater in athletes than in nonathletes (~1.2-1.7 g • kg • day -1 in endurance-trained and strength-trained athletes) (52), this patient would require ~100-140 g of protein daily. This could include a snack containing 7-10 g of protein and 30-40 g of carbohydrates. Option 2. Program a New Basal Insulin Infusion Pattern on the Pump Another recommendation would be to reduce the basal insulin infusion rate at bedtime on the evening after interval training. For young patients using CSII, Taplin et al. (53) demonstrated that reducing the basal rate by ~20% between 9:00 p.m. and

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3:00 a.m. largely prevented nocturnal hypoglycemia caused by afternoon aerobic exercise. On days when this patient is active, the health care team might consider setting a new preprogrammed basal insulin pattern on his pump (i.e., a 20% basal rate reduction starting at bedtime and con-tinuing for 6 hours). Once again, the post-exercise hyperglycemia would need to be resolved before initiating an overnight basal rate reduction. Option 3. Stay Connected If Possible It is common for individuals with type 1 diabetes to experience rebound hyperglycemia with intense exercise, particularly after an extended period of time (>1-2 hours) without basal insulin infusion. Competition stress may also promote hyperglycemia. The health care team might suggest that the patient maintain his insulin pump usage during interval training to help limit the hyperglycemia that occurs after exercise. If the insulin pump is to be worn, a basal rate reduction of 50-80% starting 1 hour before training would be recommended to help limit the risk of hyperglycemia but still offer some protection against hypoglycemia. This strategy should help to minimize the need for a post-exercise correction bolus that could be contributing to late-onset hypoglycemia. Aggressive post-exercise insulin corrections near bedtime may have contributed to severe hypoglycemia and death in at least one patient with type 1 diabetes (48). One key recommendation would be to perform more frequent glucose monitoring at bedtime. It is also important to stress that hyperglycemia during and after exercise can be caused by a number of factors, including stress, overconsumption of carbohydrates before exercise, or even miscalculating insulin

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dose adjustments (26). Going to bed with a slightly elevated blood glucose concentration after a bedtime snack or a 20% basal rate reduction would be expected to minimize hypoglycemia risk. Cautious (conservative) correction of postexercise hyperglycemia close to bedtime is also warranted. Case 3. Endurance Exercise and Strength Training Exhaustion A 46-year-old, lean, active man with type 1 diabetes incorporates both N U T R I T I O N F Y I aerobic and resistance training into his exercise regimen 4-5 days/week. He likes to run and cycle but also feels it is important to do some resistance activity during every workout to maintain strength and lean mass. The aerobic portion of exercise usually lasts from 30-45 minutes followed by 20-30 minutes of weight-lifting. The patient has been wearing an insulin pump for 12 years and recently added CGM to provide realtime information about changes in his glucose levels during exercise. He tells his health care team that his blood glucose control is better on an insulin pump than it was on MDI therapy. However, he sometimes still struggles with hypoglycemia during exercise despite a basal rate reduction at the onset of exercise. He also mentions that his glucose sensor appears to be "off" or at least delayed compared to his actual blood glucose levels based on the frequent monitoring he performs with a glucose meter during exercise. Hypoglycemia occurs within 30-40 minutes after the start of his aerobic workout, and this often delays his resistance workout or makes him too weak for weight training.

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Problem: Performing steady-state aerobic exercise before resistance exercise causes rapid hypoglycemia, leaving minimal energy for strength training. Option 1. Understanding and Responding to CGM-Derived Data The main concern for this patient is that he experiences hypoglycemia during the aerobic portion of his workout, and this deteriorates his strength for subsequent weight training. As mentioned above, hypoglycemia is a barrier to physical activity (54), and exercise training does not appear to minimize its risk (55). Real-time glucose sensing with a CGM device can help alleviate fear, increase glucose awareness, and improve glucose control during exercise. However, some limitations of CGM need to be acknowledged. Although exercise does not appear to affect sensor accuracy (55), the delay in equilibrium between interstitial fluid and capillary blood can be troublesome during rapid drops in glycemia, which tend to occur during aerobic exercise. Indeed, CGM readings have been reported to have lag times of anywhere from 5 to 28 minutes compared to capillary or venous glucose measurements in humans, depending on the experimental conditions (56)(57)(58)(59). Exercise-mediated acidosis has also been reported to reduce sensor accuracy (60). If blood glucose is increasing or decreasing at a rapid rate (220 mg/dL/hour -1 ), there may be a more pronounced mismatch between sensor values and actual blood glucose values because of an intrinsic sensor lag (61). However, when calibration conditions are optimized, sensor lag time has been reported to be as short as 1.5 or 8.9 minutes when glucose levels are falling or rising, respectively, in people with type 1 diabetes who are at

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rest (62). During aerobic (63,64) and resistance (64) exercise, CGM has been shown to track glucose changes accurately with a reduced lag time compared to during rest, perhaps because of increased blood flowmediated equilibrium. Although CGM can help to alert patients to drops in glycemia and thus help to prevent hypoglycemia, patients need to develop strategies for carbohydrate intake if downward trend arrows are observed. In one small pilot study of adolescents with type 1 diabetes (15), an intake algorithm for rapid-acting carbohydrate helped to eliminate hypoglycemia in a sports camp setting. Table 2 provides recommendations based on sensor glucose readings and trending arrows. Also, the starting blood glucose concentration before exercise is extremely important in determining when carbohydrate intake should be initiated. The health care team could suggest the strategies described in Table 1 for the aerobic portion of the exercise session. They should also rec-ommend a basal insulin infusion rate reduction to start well before the start of exercise (Table 4). Option 2. Change the Order of Exercise: Anaerobic First The order of this patient's exercise routine needs consideration. Yardley et al. (65) recently published evidence that performing resistance exercise before aerobic exercise reduces the likelihood of developing hypoglycemia in individuals with type 1 diabetes. In this case, the health care team could recommend doing the resistance training before the aerobic exercise, with the caveat to alternate daily the muscle groups used during strength training to help promote muscle recovery. Resistance training before aerobic exercise also has been shown to decrease reliance of fast-acting

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carbohydrates during exercise (66). Because resistance exercise may not be done every day for recovery reasons, sprinting either at the start (67) or at the end (68) of aerobic workouts may help boost glucose levels in recovery. It should be noted that for individuals who often experience pre-exercise hyperglycemia, performing an aerobic activity first might be preferable to help lower glucose levels to target before performing any anaerobic or resistance-based activities. Conclusion Numerous possible strategies exist for managing blood glucose levels during and after exercise for individuals with type 1 diabetes. These include increasing carbohydrate intake before, during, and after exercise; lowering pre-exercise insulin levels by reducing prandial or basal insulin or both; and changing the type or order of the exercise performed (anaerobic vs. aerobic). Because no strategy can guarantee stable blood glucose levels during and after exercise, using CGM may improve control; CGM can help to facilitate minute-by-minute changes in insulin delivery or nutrient intake. z a h a r i e va a n d r i d d e l l Patients and caregivers should be made aware of the multiple factors that can affect glucose levels during and after exercise, including the amount of active, or on-board, insulin at the time of exercise; the intensity, duration, and type of activity performed; and the type and amount of carbohydrates consumed before exercise. Although the fear of hypoglycemia during and after exercise may remain, implementing these reasonable management strategies can help to reduce this fear and enhance the overall well-being of active people

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with type 1 diabetes.

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Genetic variability in the Skyros pony and its relationship with other Greek and foreign horse breeds In Greece, seven native horse breeds have been identified so far. Among these, the Skyros pony is outstanding through having a distinct phenotype. In the present study, the aim was to assess genetic diversity in this breed, by using different types of genetic loci and available genealogical information. Its relationships with the other Greek, as well as foreign, domestic breeds were also investigated. Through microsatellite and pedigree analysis it appeared that the Skyros presented a similar level of genetic diversity to the other European breeds. Nevertheless, comparisons between DNA-based and pedigree-based results revealed that a loss of genetic diversity had probably already occurred before the beginning of breed registration. Tests indicated the possible existence of a recent bottleneck in two of the three main herds of Skyros pony. Nonetheless, relatively high levels of heterozygosity and Polymorphism Information Content indicated sufficient residual genetic variability, probably useful in planning future strategies for breed conservation. Three other Greek breeds were also analyzed. A comparison of these with domestic breeds elsewhere, revealed the closest relationships to be with the Middle Eastern types, whereas the Skyros itself remained isolated, without any close relationship, whatsoever. Introduction Today and worldwide, the populations of numerous domestic animals, especially horses, are in steady decline, with some already extinct, thereby affecting both interbreed (decline in the actual number of equine breeds themselves) and intra-breed (decline in the number of individuals) diversities. This, for example, is the case in Greece, where,

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according to the statistics of the Food and Agriculture Organisation (FAO), over the past twenty years the horse population has decreased by over 60%. Recently, arrays of DNA based markers have been developed, both to undertake studies of genetic variability, and to investigate genetic relationships between populations (Bradley et al., 1996;Cañon et al., 2000;Solis et al., 2005). Among these, microsatellites are considered by many to be the most suitable marker system for evaluating breed genetic diversity (Takezaki and Nei, 1996). Several genetic studies of equine populations have described the usefulness of microsatellite markers, as well as blood group and biochemical loci, for establishing genetic relationships between populations, and for describing genetic variability among and within breeds (Cothran et al., 1998;Cañon et al., 2000;Aranguren-Mendez et al., 2002;Juras et al., 2003;Aberle et al., 2004;Gupta et al., 2005;Glowatzki-Mullis et al., 2005;Luis et al., 2007;Royo et al., 2007). Nowadays, however, these are being progressively replaced by SNP markers, in, for example, the control of relationships (e.g. IBD matrix) (Flury et al., 2010). Nevertheless, in small breeds, genotyping with high density SNP chips turns out to be very expensive, thereby limiting the availability of such data. (Zafrakas, 1991;Alifakiotis, 2000), namely the Crete, the Elis Mountain (or Pinias), the Elis Valley (or Andravidas), the Skyros, the Thessalias, the Pindos and the Zakynthos. The names attributed to these breeds are those of the various regions where they were originally preponderant (Alifakiotis, 2000). Among these, the phenotype in the Skyros pony is distinct from those of the other breeds (Zafrakas, 1991). This in itself

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is a small-sized animal, with an average adult height of 109 cm in stallions and 107 cm in mares. They are mainly bay-colored with dark and strong hooves, and very long manes and tails (Alifakiotis, 2000). As shown by Apostolidis et al. (2001), this phenotypic difference seems to be linked to the Skyros pony being genetically less similar to the other Greek horse breeds than these themselves to one another. However, the literature is very poor concerning the description of Greek horse breeds in general. The Skyros pony population, in particular, has never been studied in its entirety, as neither have the genetic relationships of Greek horse breeds as a whole, either mutually or with other domestic breeds elsewhere. Population sizes in the Greek breeds are estimated to range from 50 to over 1000 individuals (Alifakiotis, 2000;DAD-IS 2007). Thus, most can be considered as small, and, according to criteria established by the FAO (FAO, 1998;DAD-IS, 2007), in a critical-or endangered-maintained risk status. Genetic principles, when applied to a small population, indicate that the genetic variability of such a population will decrease across generations, with the consequential need for increased conservation measures. Genetic variability may be defined as the 'genetic ability to change', and therefore, the capacity to respond to environmental variation and future needs (Rochambeau et al., 2000). Thus, the evaluation of genetic variability is one of the first steps in the process of species genetic conservation, in accordance with the hypothesis of correlations between preserving both genetic variability and population viability. The analysis of the

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information contained in registered pedigrees can also contribute towards knowledge on population structure and the evaluation of genetic variability (Valera et al., 2005). In this study, four of these native Greek horse breeds, viz., the Crete and Pinias horses, and the Skyros and Pindos ponies, were studied, with a special focus on the most distinct of the four, the Skyros pony, for which genetic markers and pedigree data were available. The Skyros pony is mainly found on the island of Skyros, situated in the Aegean Sea. Two reasons led to discerning the risk status of this genetically original breed as critical-maintained (DAD-IS, 2007), according to criteria established by the Food and Agriculture Organization (FAO, 1998), the first being the reduced population size (about 200 individuals), and the second, that this population, through being concentrated in three main herds (Skyros, Corfu and Thessaloniki), is vulnerable to demographic accidents. Initially the aim was to quantify genetic variability in the breed it-self, to thereafter compare the levels of genetic variability among all the four horse breeds studied and estimate mutual genetic distances, and then extend the comparison to other domestic horse breeds, as a way towards a better understanding of how the horses of Greece fit into the diversity of domestic horses as a whole. Population samples A total of 211 horses from the four Greek horse breeds chosen (see Table 4) were sampled and tested for genetic variation at seven blood-group, ten biochemical genetic and 12 microsatellite loci, using standard techniques (Sandberg and Cothran, 2000;Juras and Cothran, 2004).

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Although sample size for the Pindos pony was only 15 individuals, due the rarity of the breed, this represented about 10% of the total population. In all, 99 Skyros ponies (37 males and 62 females), coming from the three main related sub-populations, were tested for genetic variation at 16 microsatellite loci by using DNA extracted from hair samples (Vogelstein and Gillespie, 1979). This represents approximately 58% of the entire population of living animals considered as belonging to the Skyros pony breed. The two Skyros pony data sets could not be combined because samplings were done independently. Due to the lack of pedigree information, it was impossible to relate animals from the first sampling to those from the second, although it is probable that some animals were included in both. With more or the same number of markers in both sets, it would have been possible to control the relationships, with, for example, either a IBD matrix based on SNP data (VanRaden, 2008), or a combined relationship matrix of Bömcke and Gengler (2009). For the 99 Skyros ponies, the 16 microsatellite loci included the above 12, plus ASB23, ASB17, HMS1 and CA425. Polymerase chain reaction (PCR) and microsatellite genotyping were according to the StockMarks ® Horse protocol. Results for HTG10 could not be scored in this sampling. Statistical analysis of genotyping data Gene frequencies for biochemical loci and microsatellite loci were calculated by direct counting. Allele frequencies at blood-group loci were calculated by the allocation method (Andersson, 1985). The inter-breed genetic variation measures calculated were observed heterozygosity

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(Ho) and Hardy-Weinberg expected heterozygosity (He; Nei, 1987), the effective number of alleles (Ae, i.e. the inverse of the probability that two randomly taken genes represent the same allele), the total number of alleles (TNA), the mean number of alleles per locus (MNA), and the deviation in He from Ho (Fis; Caballero and Toro, 2002). Ho was not calculated for blood group loci due to the presence of recessive alleles and/or ambiguous genotypes at blood group loci. Therefore, for direct comparison, He was calculated only for biochemical or microsatellite loci. Genetic distances among the four breeds were calculated by Nei's modified genetic distance (Da). The resemblance to other domestic breeds, as well as Greek-breed interrelationships, were summarized in a dendrogram using the Restricted Maximum Likelihood method (REML from PHYLIP; Felsenstein, 1993). Dendrograms, calculated by employing SEQBOOT, CONTML and CONSENSE routines in the PHYLIP program, and drawn using TreeView (Page, 1996), were based upon 1000 bootstraped REML runs. Data, for both breed variability means and the dendrograms of breed relationships, were obtained from samples collected by EGC for an ongoing study of genetic diversity in domestic horses (see Juras et al., 2003;Luis et al., 2007). Genetic diversity within Skyros populations was measured with the same above-mentioned measures, plus Polymorphism Information Content (PIC) and Hardy-Weinberg Equilibrium (HWE) and p-value (HW-P). Most parameters were computed using Microsatellite Analyser (MSA) (Dieringer and Schlötterer, 2002). HWE tests were carried out with 'GENEPOP on the web' (Raymond and Rousset, 1995). Exact HW-Ps were calculated, along with their standard deviations, using the Guo

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and Thompson (1992) Markov-Chain algorithm, with 1,000 de-memorization steps for every 400 batches and 1,000 iterations per batch. The BOTTLENECK programme (Cornuet and Luikart, 1996) was employed for detecting any possible bottleneck when using various statistical tests, viz., the sign and standardized differences tests (Cornuet and Luikart, 1996;. As recommended by and Piry et al. (1999), the two-phase mutation model (TPM) was used, with 70% of the stepwise mutation model (SMM; Ohta and Kimura, 1973) and 30% of the infinite allele model (IAM; Kimura and Crow, 1964). Pedigree analysis The Skyros pony preliminary studbook was only very recently established, and thus contains only 395 animals, namely those born between 1958 and 2006. Based on these limited data, the pedigree completeness level was characterized by computing various parameters, such as: 1. The average generation interval, defined as the average age of parents at the birth of their descendants. This average was computed for the period of the last 15 years and four pathways (father-son/-daughter, motherson/-daughter). 2. The percent of known ancestors per parental generation. 3. The number of generation-equivalents (geq), often considered the best criterion for characterizing pedigree information. This was computed as the sum of (1/2) n , where n is the number of generations separating the individual from each known ancestor (Maignel et al., 1996). Additionally, in order to characterize genetic variability within the Skyros pony population, the following parameters were analyzed: 1. The effective number of founders (f e ), i.e., the number of equally contributing founders that would be expected to produce the

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same level of genetic diversity as in the population under study (Lacy, 1989). A founder is defined as an ancestor with unknown parents (Boichard et al., 1997). f e is a measure of how the balance in founder contributions is maintained across generations. The more balanced the contributions of the founders, the higher f e . It accounts for the selection rate and variation in family size (Maignel et al., 1996). 2. The effective number of ancestors (f a ), i.e. the minimum number of ancestors required to construe the complete genetic diversity of the studied population (Boichard et al., 1997), as an account of the losses in genetic variability produced, not only by the unbalanced use of reproductive individuals, but also by detected bottlenecks in the pedigree (Maignel et al., 1996). 3. The effective number of founder genomes (N g ), i.e. the number of equally contributing founders, with no random loss of founder alleles in the offspring, and with the expectancy of producing the same genetic diversity as in the population under study (MacCluer et al., 1986;Chevalet and de Rochambeau, 1986;Lacy, 1989). This is a measure of how many founder genes have been maintained in the population for a given locus and how stable their frequency (Maignel et al., 1996). Parameters 2 and 3 were studied only for the living population (represented by the animals born between 1992 and 2006). Most of the parameters were computed using the PEDIG package developed by Boichard (2002). Results The Skyros pony: Intra-breed diversity Most of the animals

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(77%) in the Skyros pony preliminary studbook were registered after 1989. The number of births has been on a global decline since 1998 (except in the years 2001 and 2004) (data not shown). Figure 1 characterizes the completeness level of the studbook. For the first parental generation, pedigree completeness was only about 75%, dropping to about 40% in the 2 nd and to less than 5% after the 3 rd . As parentages have only recently been regu- 70 Genetic variability of the Skyros pony breed larly recorded, and as the average generation interval is relatively high for an endangered breed (9.18 years, Table 1), and, furthermore, even considering this value as being consistent with the biology and behaviour of equines as a whole, the number of geq was calculated according to the individual year of birth ( Figure 2). This number increased regularly and reached values of 1.88 for females in 2006. The most relevant information on the concentration and origin of genomes in the Skyros small-horse breed appears in Table 1. f e was equal to 13.30 animals, f a to 13.08 and N g to 10.30. Even though the number of ancestors explaining 99.82% of genetic variability was 60, only 5 individuals were necessary to explain 50% and 10 to explain 70%. The results from DNA analysis of 15 microsatellite loci in the 99 Skyros ponies studied appears in Table 2. A total of 89 different alleles were detected across these 15 loci. TNA per locus in the complete population ranged from 4

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to 10, with an MNA of 5.93. The average Ae was 3.22. No significant (HW-P < 0.01) deviation from HWE was found. In most cases, the loci were highly polymorphic, thus implying heterozygosity was moderate to high (Ho > 0.5). The average Ho over all loci in the Skyros population was 0.647. This was similar to values obtained in the second part of the study, although there were certain differences between individual loci and loci in common. The average He was 0.621. Although the average Ho and He did Bömcke et al. 71 Figure 1 -The completeness level of the Skyros small-horse studbook assessed by means (over the last 10 years) by percentage of known ancestors per parental generation, with parental generation 1 corresponding to parents, 2 corresponding to grandparents, etc. not differ significantly in 8 loci, Ho was significantly higher than He, possibly indicating a genetic bottleneck in the population. Table 3 presents the results of the two tests carried out to detect this possible bottleneck (sign test and standardized differences test). As none was detected in the complete population, testing was extended to each subpopulation. Test results indicated significant heterozygosity excess in two herds, the Thessaloniki and Corfu. The average PIC for the 15 microsatellites was 0.598. From PIC values it was inferred that 11 of the 15 markers were highly informative (PIC > 0.5) in terms of their suitability for genetic diversity studies, whereas the remaining four were less so ( Table 2). The relationship between theSkyros pony and other Greek horse breeds

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The alleles observed at the 29 loci examined, as well as their frequencies, are available on request. No allele unique to any of the Greek breeds was observed. Unique or uncommon alleles have been observed on a regular, though infrequent, basis at blood group and biochemical loci (for example, see Cothran and Long, 1994), but are not common for microsatellites, due to the nature of the variation. Genetic variability measures are given in Table 4. Genetic associations among the breeds, as given in Table 5, show that these are not so closely related to each other as might be expected by geographic distances, although the Pindos and Pinias are believed to be so (Figure 3). The Crete Horse is closest to the Pindos and Pinias, whereas the Skyros revealed no close relationship to any of the Greek breeds examined. Due to the large number of breeds for comparison, the consensus tree is based on 1000 bootstrapped REML runs according to blood group and biochemical loci (Figure 3). Trees, based only upon microsatellite, as well as combined protein and microsatellite data, were also produced, but, through being substantially the same, are not shown. Discussion Genetic variability in the Skyros pony breed was investigated, using both pedigree and microsatellite information. Results based on pedigree analysis showed that the parameters computed for this breed were quite similar to those computed for other European horse breeds. 72 Genetic variability of the Skyros pony breed In comparison to other studbooks, the Skyros pony preliminary studbook proved to be much less complete.

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It is characterized by a very high percentage of animals with one or both parents unknown (26.33% and 35.45% as against 1.94% and 1.28% for the Andalusian studbook) (Valera et al., 2005). This situation is explained by long generation intervals, births having only recently been recorded, and mares roaming free, to return pregnant, the sire being obviously unknown. In comparison, the percentage of known ancestors in the Lipizzan studbook, for example, was above 90% at the 10 th generation and above 70% at the 14 th (Curik et al., 2003). This value is comparable to the first generation in the Skyros studbook, although the situation is improving, with the value of geq globally increasing according to the birth-year of the animals. Generation intervals computed for the Skyros breed were lower than those reported for other horse breeds with deeper pedigrees, as the 9.7 years in French Arabs and 11.8 in Trotteur Français (Moureaux et al., 1996). Even so, this is very high for an endangered breed. Generation intervals in horses are commonly long (Strom and Philipsson, 1978), this basically depending on its use (leisure or racing) being incompatible with pregnancy and a breeding life. For the Skyros pony, the cause is more linked to management, with 60 ancestors being accountable for about 100% of genetic variability. This value was lower than the 331 reported for Andalusian horses (Valera et al., 2005). Although the values for the number of ancestors explaining 70% (10) and 50% (5) of the genetic variability are quite similar (13 and 6, respectively

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for Andalusian), the lack of difference between f e (13.3) and f a (13.1) showed that, based on pedigree, no significant bottleneck had occurred. N g was low due to the high probability of gene loss in the last generation, as a result of few descendants (the number of births has been globally declining since 1997), and the repeated use of the same individuals for breeding. Parameters computed from the results of DNA analysis proved to be similar to those calculated for other breeds, especially for bottlenecked and small-sized populations. On a whole, these parameters showed higher or similar values than those obtained by Avdi and Banos (2008), consistent with the fact that we studied the entire Skyros pony population, instead of just one herd. MNA (5.93) was lower than that presented by Rognon et al. (2005) for seven Bömcke et al. 73 (Cañon et al., 2000;Curik et al., 2003;Aberle et al., 2004;Juras and Cothran, 2004;Gupta et al., 2005;Rognon et al., 2005;Luis et al., 2007). The number of loci tested ranged from 11 (Rognon et al., 2005) to 30 (Aberle et al., 2004). As there was no instance of exactly the same set of loci as ours being employed, a direct comparison becomes impossible, although these results are nevertheless useful for a better understanding of variation in the Skyros. The value of He (0.621) for the Skyros horse was well within the range for domestic horses, as a whole, although it was at the lower end of the range. The lowest values, viz. 0.442 for the

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Friesian (Juras and Cothran, 2004), 0.506 for the Sorraia and 0.609 for the Exmoor (Luis et al., 2007), were all from breeds with either small population-size or recent bottlenecks. The same pattern was seen for Ho. Thus, levels of heterozygosity in the Skyros breed are most like those observed in horse breeds with small population size that have undergone bottlenecks and inbreeding in recent times, which is consistent with the recent history of the Skyros horse. Actually, it is known that the population size has decreased, as confirmed by bottleneck-analysis of two of the three sub-populations. Nevertheless, no bottleneck signature was detected by testing in the population present on Skyros, even though the probability is high that this population has undergone outstanding reduction of late. There are five possible explanations : 1) although a bottleneck occurred in the past, possibly more than 12 to 15 generations ago, it did not constitute an immediate and permanent bottleneck in population size . 2) the bottleneck was too small to be detectable . 3) either insufficient polymorphic loci were sampled to acquire the required statistical power for detecting the bottleneck, or the individuals sampled were not representative of the bottlenecked population itself. 4) a demographic, and not a genetic bottleneck, occurred. 5) the bottlenecked population was incompletely isolated, and so, genes obtained from immigrants (e.g., rare alleles) obscured subsequent genetic effects. In this case, these immigrant genes could have originated from the white horses present on the island, and which had been introduced more recently than the original pony.

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Hypothesis 1, 3 and 5 were, in this case, the most plausible explanations, with preference for the first, since 12-15 generations ago falls into the time of the foundation of modern horse breeds. However, no sufficient informa-tion was available to choose or definitely exclude either one or the other of these assumptions. However, the relatively high level of heterozygosity and PIC values was comparable to those found in the Marwari horse population. This reflected high residual genetic variability that could be exploited for planning breeding strategies and giving precedence to this breed for conservation measures (Gupta et al., 2005). As to the relationship between the Skyros pony and other Greek horse breeds, this study confirmed the conclusions by Apostolidis et al. (2001), regarding the former. Levels of genetic variability among Greek horse breeds, in general, were all within the range seen for other domestic horses. Values for Ho of biochemical loci varied widely, with the lowest (0.307) found in the Pinias breed, a farm horse encountered in mountainous regions. This breed is relatively numerous, with a census population in Greece of about 5,000. The highest Ho was found in the Skyros pony from the island of the same name. As the census numbers of this small horse are less than 200, this high Ho was unexpected. Nevertheless, the Ho for microsatellites in this breed was the lowest in the four Greek breeds studied, and was even lower than the mean value for domestic breeds, as a whole. In general, there was no clear pattern of genetic

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variation associated with population size or degree of geographic isolation. This is most likely due to historical factors, such as how recently changes in population numbers took place or undocumented cross-breeding. Furthermore, individual genetic variation at biochemical loci does not correlate well with that at microsatellite loci. Variability at microsatellite loci is largely affected by the number of alleles, and, based upon demography, may change more rapidly than that at protein loci (Luis et al., 2007). In the Crete horse, another island population, the opposite pattern of variation is the case, with relatively low values for protein loci but relatively high variation at microsatellite loci. In a comparison with other domestic breeds, using blood group and biochemical data (Figure 3), the Crete, Pindos and Pinias breeds revealed the highest affinity to Oriental types, especially those from the Middle East. This is probably a reflection of the possible Eastern origin of their ancestry. The Skyros pony clusters with two breeds with no clear mutual relationship or geographical closeness ( Figure 3). These, two Zemaituki breeds, are Lithuanian horses, possibly of fairly ancient regional types, that show no clear relationship to any other breed tested up to that moment (Juras et al., 2003). The association of these with the Skyros, is most likely an artefact of the breeds tested, as well as the low level of breed diversity. Microsatellite and combined data (not shown) indicated that the Skyros has no close resemblance to any of the domestic breeds that were examined. This may be due, either to the

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low variability of the breed (Cothran and Luis, 2005), or to the true origins of the Skyros pony, tracing back to horse types not examined in this study. 74 Genetic variability of the Skyros pony breed Conclusion This study confirmed both the distinctiveness of the Skyros pony compared to the other Greek horse breeds, and the inexistence of a clear relationship with any other domestic breed. As genetic variability parameters showed similarities with bottlenecked and small-sized populations, the conclusion is that, probably, as a result of bottlenecks in two of the three subpopulations, a loss of this variability had already occurred within the Skyros horse population before the start of birth registration. However, further analysis, for example with SNP data, should be undertaken in order to prove this. At this moment, an effort by breeders to avoid mating between relatives would be helpful in reducing the rate of loss in genetic variability at the population level, as a means of conserving the relatively high genetic variability of the population, while genealogical parameters measuring pedigree depth (number of generation equivalents) continue to improve (Royo et al., 2007).

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Mutual associations between intellectual disability and epilepsy-related psychiatry disability Abstract Epilepsy is the third-leading cause of psychiatry disability in China, and intellectual disability (ID) is also 1 major type of disabilities in China. This study estimates the prevalence of comorbidities with ID and epilepsy-related psychiatry disability (EPD) and examines mutual associations within ID and EPD. Data were taken from the Second China National Sample Survey on Disability, which was a nationally representative, population-based survey. To derive a nationally representative sample, the survey used multistage, stratified, cluster random sampling with probability proportional to size. The disabled people who had ID and EPD based on the World Health Organization International Classification of Functioning, Disability, and Health and the International Statistical Classification of Diseases. The cox-proportional hazards model was used to examine the associations between ID and EPD considering the happened sequence of ID and EPD. The prevalence of ID with EPD was 0.14 (95% confidence interval: 0.09–0.19) per 1000 people. Age was strongly associated with the risk of EPD, which was diagnosed after ID, especially among young ID population. Except for age, other variables were also associated between ID and EPD considering sequence of ID and EPD. This study is the first national study to explore mutual associations with ID and EPD and highlights the young ID children with high risk of development of epilepsy. To address the challenge of ID with EPD disability in China, the government should adjust its strategies for healthcare systems to prevent disability. Introduction According to the World Health Organization (WHO)'s estimation, there

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were 8 out of 1000 people, who were suffered by epilepsy. [1] A number of people with epilepsy might also be effected by other health conditions, [2,3] such as psychiatric disorders, [4][5][6][7] somatic comorbidities, [2,8,9] or intellectual disorders. [10] In China, epilepsy has been reported as the third-leading cause of psychiatry disability. [11] Comparing with the general population, people with epilepsy nearly have 3 to 4 times risk for premature death. [12] Comorbidities of epilepsy with other health conditions are always associated with healthcare needs, quality of life, and mortality. [2,3] Intellectual disability (ID) refers to lower than normal intellectual ability and is accompanied by adaptive behavior disorders. This kind of disability results from impairment of the structure and functions of the nervous system, limits individual activity and participation, and requires all-round, extensive, limited, or intermittent support. [11] Previous articles suggested the prevalence of ID varies widely, it has been estimated that approximately 2% of the adult population have ID. [13,14] Comorbidities of ID and epilepsy may be a common combination of diseases. Over 50% of a representative sample with ID and active epilepsy were reported to have various psychiatric diagnoses. [10] Epilepsy-related psychiatry disability (EPD) was a serious performance of epilepsy, and was easily diagnosed in clinical researches. A previous study reported comorbidities of EPD with psychiatric disorders, such as organic mental disorders, dementia, and so on in China. [15] Although EPD is related with other mental disorders and epilepsy disease is more common in people with ID than in the general population, there is

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no a nationwide population-based survey on EPD with ID reported in China. In the study here, we used data from a nationwide survey on disabilities to assess the mutual associations between EPD and ID. [16] 2. Methods Data source In the present study, we used the Second China National Sample Survey on Disability, which was a nationally representative sample. The survey employed a multistage, stratified random cluster sampling scheme, with probability proportional to size to derive a representative sample. The survey protocol and questions were reviewed by leading national and international experts. [16] The sampling scheme of this survey was reviewed by experts from the Division of Statistics of the United Nations. [16] This survey was conducted from April 1 to May 31, 2006. The survey covered all provincial administrative areas in mainland China, excluding Hong Kong, Macau, and Chinese Taipei. Details of the survey design were described elsewhere. [11] Ethics The surveys were approved by the State Council (Guo Ban Fa No 73 [2004]). The survey was conducted within the legal framework governed by statistical law in China. All survey respondents provided consent to participate in these surveys and clinical diagnosis. Data collection procedures and data quality Before the formal survey, a pilot study was conducted. [16] During data collection, strict quality control measures were implemented at every step, a structured interview questionnaire was used to inquire about disabilities. [16] Subjects who responded "yes" to any of the corresponding questions were assigned to different designated physicians for further disability screening and confirmation. Following the guidelines

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of diagnostic manuals, designated physicians performed the medical examinations, made a final diagnosis of the disability, if any, then assessed its severity and confirmed the primary cause. [16] Respondents with multiple positive answers were examined by a separate doctor for each disability. After the field investigations, the teams made a home revisits for conduct surveys in the quarters chosen for postsurvey quality checks and calculate errors in the survey overall. The results of the quality checks showed that the omission rate of the resident population was 1.31 per 1000 persons; the omission rate of the disabled population was 1.12 per 1000 persons. [16] Identification of people with EPD and ID Psychiatry disability was defined and classified by the expert committee of the Second China National Sample Survey on Disability, based on the WHO International Classification of Functioning, Disability and Health (WHO-ICF). [17] EPD was diagnosed by professional psychiatrists according to the item G40 and G41 of the International Statistical Classification of Diseases, 10th Revision and WHO-ICF. [17,18] ID refers to psychiatry functioning generally lower than that of normal people, accompanied by adaptive behavior disorders. ID was diagnosed by the Gesell Developmental Scales among children aged 0 to 6 years, the Wechsler Intelligence Scale for Children-Chinese Revised among children 7 to 16 years, and the Wechsler Adult Intelligence Scale-Revised Chinese among those aged older 17 years. [19][20][21] Children aged 0 to 6 years with a development quotient lower than 75 and those aged 7 to 17 years with an intelligence quotient lower than 70 were diagnosed as

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having ID. [16] All the classifications and grading standards, screening methods, diagnosing methods, and relevant scales of disabilities were pretested in pilot studies, and had good reliability and validity. Statistical analysis The present study collected information on ID diagnosed time before EPD using a binary category (yes or no), EPD diagnosed time before ID using a binary category (yes or no), age groups in 2006 (40-64, 20-39, and 0-19), gender (male or female), residential area (urban or rural: according to "Hu Kou"), ethnicity (Han or other), household size (1-3, 4-6, or 7-9 people), and household income above average in 2006 (yes or no). We used a cox-proportional hazards model to estimate the hazard ratios and 95% confidence interval (CI) for the diagnosed time of ID before EPD and the diagnosed time of EPD before ID for selected variables. Diagnosed time of EPD or ID accorded to subjects' record during data collection. The sample size selecting steps were summarized in Fig. 1. Statistical significance was set at a 2-tailed P value of <.05. Statistical analyses were performed using SAS v. 9.2 (SAS Institute Inc, Cary, NC). Characteristics of the subjects Selected characteristics of the cases of ID with EPD and study subjects are presented in Table 1. The prevalence of ID with EPD was 0.14 (95% CI: 0.09-0.19) per 1000 people. Cases of ID with EPD aged between 10 and 49 accounted for 83.4% of the total number of cases. In the present study, ID with EPD cases or study subjects who were male, resided in rural

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areas, lived under average income, and were of Han nationality accounted for the majority of sample size. Mutual associations between ID and EPD Mutual associations between ID and EPD are presented in Tables 2 and 3. Under consideration of the fact that other variables were confounding variables, age was strongly associated with the risk of EPD which was diagnosed after ID, especially for those aged younger than 30. However, we did not observe similar association between age and the risk of EPD's diagnosed time before ID. We also found significant association between household size and the risk of EPD's diagnosed time before ID, considering other variables were confounding variables. Main findings and their significance The mutual association between ID and EPD has been investigated in China. We used detailed personal interviews and professional examinations of disabilities from the second China National Sample Survey on Disability. We obtained very unique and valuable information on ID with EPD among the Chinese population. The prevalence of ID with EPD was 0.14 per 1000 people. Furthermore, we observed strong mutual association between ID and EPD considering sequence of these disabilities. Comparison with others studies and implications of the findings In the study here, we used detailed personal interviews and professional examinations of disabilities from the 2006 nationally representative sample to examine the mutual associations within ID and EPD in China. We obtained valuable results on ID with EPD among the Chinese population. The observed prevalence of ID with EPD was lower than a review indicated. [10] One major reason is

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that the definition of disabilities in China is narrower than in other countries, which might lead to underestimation of the prevalence of ID with EPD disabilities in China. Moreover, the prevalence of ID with epilepsy might be due to the methods used and inherent population biases, because varied methods used might cause the differences in prevalence estimation. [22] Third, we estimated the prevalence of ID with EPD, did not estimate the prevalence of ID with epilepsy disease. The difference between disease and disability might contribute to this low prevalence. Although the prevalence of ID with EPD was lower than other studies, China was facing a challenge of disabilities. The upward trends in prevalence of disabilities were observed in China. [11] This increased prevalence might have been due to changes in attitudes to disability, increasing public awareness, and changes in diagnostic criteria. [23] Although the awareness about disabilities was improving, the increment in prevalence might also be attributed to the current underdevelopment status of psychiatry health service system in China. Nearly 45% of urban population and 80% of rural population could not access to any type of healthcare insurance in the 2006. [24] In mainland China, the percentage of China's financial expenditures and gross domestic product (approximately 5% in The sample size of the second China National Sample Survey on Disability was 2526145, including visual disability, hearing disability, physical disability, speech disability, intellectual disability and psychiatry disability. During the survey, we collected disability information, including type of disability, severities, diagnosed time and so on. Population with visual

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disability, or hearing disability, or physical disability, or speech disability and population without disabilities were excluded. Intellectual disability and psychiatry disability included Population aged over 65 years and population with other types of psychiatry disability excluded Intellectual disability (17001), epilepsy related psychiatry disability (1347) and intellectual disability with epilepsy related psychiatry disability (307) for analysis 67 epilepsy related psychiatry were developed after they firstly were diagnosed intellectual disability 32 intellectual disability were developed after they firstly were diagnosed epilepsy related psychiatry disability 208 intellectual disability with epilepsy related psychiatry who were diagnosed in the same time period were excluded for cox proportional hazards model analysis recent years) on healthcare system was much smaller than the percentage in Hong Kong, where the annual government recurrent expenditure on health care increased 40% from 2007 to 2012. [25] Slow development of specialized training, treatment of disability, and culturally rooted stigmas about disability were also barriers to the improvement of health status in Chinese population. In the present study, we presented more detailed association between age and EPD with ID. Age groups in previous studies were classified as adult, child, or mixed (adult and child) [10] or presented as broad age bands of 0 to 18, 19 to 49, and 50+. The highest prevalence of epilepsy among people with ID was observed among population aged between 19 and 49 years. In our study, the first 3 prevalences of ID with EPD were observed among population aged between 20 and 29 years (0.26 [95% CI: 0.20-0.32] per 1000 people), between 10

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and 19 years (0.20 [95% CI: 0.15-0.24] per 1000 people), and between 30 and 39 years (0.14 [95% CI: 0.10-0.17] per 1000 people). The lowest prevalence of ID with EPD was found among population aged 50 and older, which was similar to previous result. [10] Moreover, age was also found as a significant factor for disable sample of population with ID onset before EPD, especially for children. But we did not observe that age was a significant factor among those with EPD onset before ID. Age was not only a demographic variable, but also associated with social roles and social position which came with socioeconomic factors, prestige, and access to resources. [26] Furthermore, normal functioning of children with disability was affected by social participation limits and these children needed more health care. In developed countries, children with epilepsy had less accessed to educational resources [27,28] and presented poorer social skills and sense of control. [29] Under consideration of low development of healthcare or health insurance system in China, the situation was more serious if children had ID and EPD together. Strengths and limitations The limitations of this study should be noticed. We did not consider every potential confounder, such as marital status, education, etc., because these factors were consistent with disabled population, which should also be treated with caution for further researches. In addition, the design of this study was an ecological study with all of the limitations on assumptions about causality. The primary strengths of the present study included the large sample size and the

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representativeness of the sample, which covered all provincial administrative areas in mainland China. In addition, all subjects in the households selected were interviewed face to face at the time of data collection. Also, standardized quality control schemes were in place during the field interviews, the included training of the interviewers, and the cross-checking of returned surveys by contacting survey participants, which resulted in little response bias. Conclusion Currently, China is undergoing social and economic reforms. The current results will benefit our understanding of the prevalence of ID with EPD and risk factors within ID and EPD. Our findings will help policymakers to understand the current status of ID with EPD in China, and also help them to notice the mutual association between ID and EPD. These unique results will be helpful to improve strategies for individuals, communities, and the healthcare/healthcare insurance system to prevent disabilities. Characteristics of comorbid epilepsy caused psychiatry disability with intellectual disability. Variables Intellectual disability with epilepsy-related psychiatry disability, n (%)

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Effects of Oleo Gum Resin of Ferula assa-foetida L. on Senescence in Human Dermal Fibroblasts Objectives Based on data from Chinese and Indian traditional herbal medicines, gum resin of Ferula assa-foetida (sometimes referred to asafetida or asafoetida) has several therapeutic applications. The authors of various studies have claimed that asafetida has cytotoxic, antiulcer, anti-neoplasm, anti-cancer, and anti-oxidative effects. In present study, the anti-aging effect of asafetida on senescent human dermal fibroblasts was evaluated. Methods Senescence was induced in in vitro cultured human dermal fibroblasts (HDFs) through exposure to H2O2, and the incidence of senescence was recognized by using cytochemical staining for the activity of β-galactosidase. Then, treatment with oleo gum resin of asafetida was started to evaluate its rejuvenating effect. The survival rate of fibroblasts was evaluated by using methyl tetrazolium bromide (MTT) assays. Real-time quantitative reverse transcription-polymerase chain reaction (qRT-PCR) and western blot assays were performed to evaluate the expressions of apoptotic and anti-apoptotic markers. Results Our experiments show that asafetida in concentrations ranging from 5 × 10−8 to 10−7 g/mL has revitalizing effects on senescent fibroblasts and significantly reduces the β-galactosidase activity in these cells (P < 0.05). Likewise, treatment at these concentrations increases the proliferation rate of normal fibroblasts (P < 0.05). However, at concentrations higher than 5 × 10−7 g/mL, asafetida is toxic for cells and induces cell death. Conclusion The results of this study indicate that asafetida at low concentrations has a rejuvenating effect on senescent fibroblasts whereas at higher concentrations, it has the opposite effect of facilitating cellular apoptosis and

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death. Introduction Consumption of medicinal herbs is growing and people want to reduce the practice of using chemically synthesized drugs [1,2]. Despite this growing interest for herbal medicine, our knowledge of their possible benefits or adverse side effects is not sufficient [3]. Part of this lack of information arises from the complexity and the diversity of each plant's constituents, and the other part is the fact that each constituent can exert various effects on the body's organs [2]. One such medicinal herb is Ferula assa-foetida, which belongs to the umbelliferae family of plants; several therapeutic applications, such as anti-diabetic, anti-ulcer, aphro-disiac, antiepileptic, anthelmintic, and antispasmodic applications, have been proposed for this herb [4]. The oleogum-resin of Ferula assa-foetida is sometimes referred to as asafetida or asafoetida, but for consistency asafetida will be used throughout this paper. A review of the compounds in asafetida shows that some skin-friendly compounds, as well as some irritant substances, are contained in its gum resin. One of these skin-friendly compounds which has a known antioxidative effect is ferulic acid (FA) [5]. Several reports about the biological roles of FA have been published, and most are about its antioxidative properties [6]. FA protects skin from UV radiation by forming a resonance-stabilized phenoxy radical and by preventing the activation of caspase in dermal fibroblasts [7][8][9]. It is a potent antioxidant and synergizes the effects of ascorbic acid [10]; it also protects cells from oxidative damage by neutralizing different species of free radicals, such as hydroxyls, alkoxyls, peroxyls, nitric oxide, peroxynitrites, and superoxides [10][11][12][13][14][15][16][17].

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In addition to these reported properties, some evidence exists regarding the anti-mutagenicity of FA, indicating that it protects cells from menadione-induced oxidative DNA damage; its anti-carcinogenic effects have also been demonstrated in animal models of pulmonary and colon cancers [18][19][20][21][22][23]. In experiments regarding its dermal application, FA decreased UVB-induced erythema, 12-O-tetradecanoylphorbol-13-acetate (TPA)-induced ornithine decarboxylase activity, and TPA-induced skin tumor formation [24,25]. Apart from FA, some researchers have found that asafetida contains some other ingredients that can cause or inhibit skin irritation. For example, it contains alpha pinene with its reported anti-inflammatory and analgesic effects [26] and alpha terpineol with its reported anti-inflammatory and skin-irritating effects [27]. It also contains other compounds, such as diallyl disulfide, luteolin, and isopimpinellin with their confirmed capabilities for the prevention of chemically-induced skin tumor development in mice [28][29][30][31], as well as Azulene [4], which is beneficial for the prevention of skin irritation and skin damage and is widely used in cosmetic products [32]. Based on the above data, asafetida contains many compounds that can affect skin cells, and most of them have or may have therapeutic applications for skin problems such as aging. Until now, to the best of our knowledge, no report on the effect of asafetida extract on skin cells has been reported. For that reason, we designed this study to evaluate the effect of asafetida on normal and senescent human dermal fibroblasts (HDFs). To evaluate the effect of asafetida on HDFs, we used a reactive oxygen species (ROS)-mediated model of senescence; consequently, we selected, some important regulators of

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the ROS-mediated apoptosis pathway, which are listed in Table 1, for further analysis. BCL2, BAD and BAX are apoptosis regulators acting on the mitochondrial membrane [33,34], and p21 is the main downstream regulator of p53-dependent cell cycle arrest and senescence in response to DNA damage [35]. CASP3 was selected because its activation could be triggered by both extrinsic (death ligand) and intrinsic (mitochondrial) pathways [36]. ALOX5 was selected so that we could evaluate the inflammatory responses of senescent HDFs after treatment with asafetida [37]. Journal of Pharmacopuncture 2017;20(3):213-219 Table1List of the primers used for the real-time qRT-PCR assay qRT-PCR, quantitative reverse transcription-polymerase chain reaction. Gene Primer sequences GenBank Materials and Methods Oleo-gum resin of Ferula assa-foetida L. (asafetida) was prepared based on our previous study [38]. In our experiments, we used a special, pure type of asafetida (Ashki asafetida in local dialect) that, based on high performance liquid chromatography (HPLC) assays, has a higher concentration of FA [38]. Briefly, Oleo-gum resin was collected in June from Ferula assa-foetida L. (Herbarium code: P1006636, IBRC, Tehran, Iran) by making some small incisions (1 -5 cm) on its stem near to its roots, from which high-quality oleo-gum resin (asafetida) could be obtained. The collected asafetida was cut into small pieces and placed under a hood until it had dried. For preparation of the asafetida solution, a specified amount (10 mg) of dried asafetida was dissolved in 10 mL of distilled water and filtered by using 0.02-um filters. Different volumes of this asafetida solution were added to the culture media

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of cells to obtain the final treatment concentrations. A HDF cell line (NCBI Code: C646, Pasteur Institute, Tehran, Iran), cell passage numbers 5 -8, was used for cell assessments. According to the manufacturer's data, this cell line was derived from the dermis of normal human neonatal foreskin and cryopreserved at the end of primary culture; a cell passage number less than 10 is safe and cytogenetically stable. Cells were cultured in DMEM medium containing 10% FBS (2 × 10 4 cells/well of 24-well plates for MTT and staining assays and 10 6 cells/well of 6-well plates for real time qRT-PCR assays). The effects of asafetida on normal and senescent HDFs were evaluated after 10 days of treatment with different doses of asafetida (10 -8 , 5 × 10 -8 , 10 -7 , 5 × 10 -7 and 10 -6 g/mL). ROS-mediated senescence was induced on HDFs by using hydrogen peroxide [39]. For this purpose, passage-four HDFs were cultured in 24-well culture plates at a density of 2 × 10 4 /well. The following day, the medium was replaced with a medium containing 600-µM H 2 O 2 (hydrogen peroxide), after which the plates were placed in a CO 2 incubator for 2 hours. Next, the medium was replaced with a normal fibroblast medium (DMEM + 10% FBS). After the cells had been incubated in the CO 2 incubator for 24 hours, they were exposed for the second time to 600-µM H 2 O 2 . Two hours later, the medium was replaced with normal fibroblast

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medium containing different concentrations of asafetida extract. The culture medium was changed every 3 days while fresh asafetida was added to the medium daily for 10 days. The final concentrations of asafetida were 0 (nontreated, control), 10 -8 , 5 × 10 -8 , 10 -7 , 5 × 10 -7 , and 10 -6 g/mL of gum resin of asafetida dissolved in the culture medium. Each treatment was repeated in four replicates. After 10 days of treatment with asafetida, the density of senescent cells was measured by staining the senescent cells. Cell staining was performed by using Senescence Cells Histochemical Staining Kits (Sigma, CS0030). The assay is based on a cytochemical stain for β-galactosidase activity at pH 6. After staining, 20 images with 40 x magnification were captured from each treated group, and the numbers of senescent cells were counted in each image. Cell viability was measured using the 3-(4, 5-dimethyl-2thiazolyl)-2, 5-diphenyl-2H-tetrazolium bromide (MTT, Sigma) assay. This method is based on the mitochondrial dehydrogenase activity of vivid cells in the culture dish. For this purpose, cells belonging to each treatment group were cultured in one 24-well culture dish; then, two days after initiation of asafetida treatment, 50 µL of MTT (5 mg/ mL) were added to the culture medium, and the cells were incubated for 4 hours. After that, the culture medium was removed completely and replaced with 250 µL of DMSO. The absorbance of each well was measured at 560 nm by using a spectrophotometer, and the results were shown as the percent of

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each group compared to the control group. Real time PCR was performed on senescent HDFs to measure the expression rates of the apoptotic markers p21, BAX, BAD, and caspase 3 (CASP3), the antiapoptotic marker BCL2, and an inflammatory marker ALOX5 (Arachidonate 5-lipoxygenase). β-actin mRNA (ACTB) was used as a housekeeping gene. The list of primers sequences is presented in Table 1. After isolation of total RNA (Vivantis RNA isolation Kit), CDNAs were synthesized using MMLV Reverse Transcriptase and Oligo (dT) Primers according to the manufacturer's instructions (Vivantis, Easy cDNA reverse transcription kit). For gene expression analysis, relative quantitation PCR (qPCR) was performed using SYBR-Green master mix (Qiagen) in a Qiagen Rotor Gene 6000 system and software. The qPCR conditions were 1 cycle of incubation in 94ºC for 10 min for denaturation, and then DNA amplification was performed in 40 cycles using 1 min in 53°C for annealing, 20 seconds in 72°C for elongation, and 15 seconds in 95°C for denaturation. The expression levels of these target genes in each sample were calculated by using the comparative Ct method (2-ΔΔCt formula), after having been normalized by the Ct value of the housekeeping gene in each group. All experiments were repeated three times for each group. For the Western blot analyses, cells were lysed on ice in a lysis buffer containing 20-mM Tris-HCl (pH 7.5), 150-mM NaCl, 10-mM EDTA (pH 7.5), 1% Triton X-100, and 1% deoxycholate. Then, the cell extracts were clarified by centrifugation, resolved on SDS-PAGE, and transferred onto PVDF membranes (Millipore, USA). After having been

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blocked with 5% BSA overnight at 4°C, the membranes were incubated for 1.5 h at room temperature with rabbit primary anti-BCL-2 antibody (Abcam, ab59348, 1 ∶ 500) and mouse primary anti-GAPDH antibody (Abcam, ab8245, 1 : 1000). Following three rinses (15 min each) with PBS-Tween20 (0.05%), incubation with the peroxidase (HRP)-conjugated goat anti-rabbit IgG H&L (Abcam, ab205718, 1:2000) and goat anti mouse secondary antibody (Abcam, ab97240, 1∶2000) was performed for 2 hours at RT. After three washes with TBST, western blotting chemiluminescence reagent (Thermo Scientific, USA) was used for protein detection. The relative intensities of western blot bands were semi-quantified by using Image J software. The relative band intensity for each protein was normalized to glyceraldehyde 3-phosphate dehydrogenase (GAPDH). Statistical analyses were performed using SPSS software. Each experiment was repeated a minimum of three times, and the data were expressed as means ± standard errors of the mean (SEMs). Statistical differences between the groups were assessed by using the one-way analysis of variance (ANOVA) followed by Tukey's test. Statistical sig-nificance was established at P < 0.05. Results The results of the MTT assays showed that treatments with asafetida at concentrations of 5 × 10 -8 and 10 -7 g/mL could increase the survival rates of normal and senescent HDFs compared with the other groups (P < 0.05, Fig. 1A). To evaluate the anti-aging effect of asafetida, we treated senescent cells with different concentrations of asafetida for 10 days and then measured the density of senescent cells by using β-galactosidase staining. The mean percentage of senescent cells

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per total number of cells showed that the numbers of senescent cells in the groups treated at concentration of 5 × 10 -8 and 10 -7 g/mL were significantly lower than the numbers of such cells in the other groups (P < 0.05, Fig. 1). Our data also showed that asafetida was toxic at higher concentrations (10 -6 g/mL) and that it significantly reduced the survival rate of HDFs and subsequently increased the number of senescent cells (P < 0.05, Fig. 1). As shown in Fig. 2A, gene expression assays revealed that treatments with 5 × 10 -8 and 10 -7 g/mL of asafetida in-Figure1(A) MTT assay results in normal and senescent fibroblasts (*P < 0.05). (B) Effect of treatment with asafetida on human senescent fibroblasts in percent of senescent cells/total number of cells counted in the images from each group (*P < 0.05). (C) Images of cells after staining for β-galactosidase activity, with the blue color representing senescent cells: (a) control, (b) 10 -8 , (c) 5 × 10 -8 , (d) 10 -7 , (e) 5 × 10 -7 , and (f) 10 -6 g/mL of asafetida. Data are presented as means ± SEMs, and scale bars represent 100 µm. MTT, methyl tetrazolium bromide; SEMs, standard errors of the mean. creased the expression of BCL2 (P < 0.01), but decreased the expressions of p21, CASP3, BAX and BAD as compared with the control group (P < 0.01 for p21 and CASP3; P < 0.05 for BAD and BAX). The expression level of ALOX5 revealed

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no change at these concentrations as compared with the control group. Otherwise, for doses above 10 -7 g/ mL, asafetida prompted apoptotic function, and the expression rate of anti-apoptotic BCL2 was significantly decreased to very low levels as compared with the control group (P < 0.05); however, the expressions of the apoptotic inducer factors BAX, BAD, CASP3 and p21 were increased (P < 0.05). The expression of ALOX5 was also increased, as compared with the control group, in the groups that were treated with higher doses of asafetida (P < 0.01). Results of western blot analyses also confirmed an approximately threefold increase in BCL2 protein expression in groups treated at asafetida concentrations of 5 × 10 -8 and 10 -7 g/ mL as compared with the other groups (P < 0.01, Fig. 2B). Discussion In present study, we measured the effects of water soluble parts of asafetida (gum resin of Ferula assa-foetida) on human dermal fibroblasts. Asafetida has multiple components, and among them, FA is a well-known compound because of its anti-apoptotic effects. Plants of the ferula species also have high amounts of sulfide compounds and rare concentrations of sesquiterpene coumarins and terpenes with anti-inflammatory effects [40][41][42]. The results of MTT and β-galactosidase staining assays showed that treatments with low concentrations of asafetida could protect senescent HDFs from apoptosis. To evaluate this effect at a molecular level, we performed real-time qRT-PCR and western blot assays, and the results showed that treatment with asafetida altered the expression rates of apoptotic and anti-apoptotic markers in fibroblasts. Reductions in

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the expressions of p21 (anti-proliferative and senescenceinducing factor) [43], CASP3, BAX, and BAD (mediators of programmed cell death), as well as surges in the expression of BCL2 (anti-apoptotic marker) [44], revealed that asafetida had a potent anti-apoptotic effect. Furthermore, the results of cell staining for beta-galactosidase activity confirmed that these reductions of BAX and BAD (as positive regulators of cell apoptosis) and the increase in BCL2 effectively rejuvenated senescent fibroblasts. Based on the recent findings about the roles of 5-lipoxigenase (ALOX5, 5-LO) in the activation of pro-inflammatory pathways [37], we also evaluated the expression of ALOX5 in our experiments. When the treatment dosage of asafetida was increased above 10 -7 g/mL, the expression level of ALOX5 was increased in cells, which revealed that asafetida could activate pro-inflammatory signals. In confirmation, one report indicated that topical administration of asafetida could cause contact dermatitis in infants [45]. This skin-irritating effect of asafetida might be due to its disulfide-containing compounds [46]. Thus, this pro-inflammatory side effect of asafetida should be diminished by reducing the concentration of its sulfide compounds through chemical processing or by combining it with ALOX-5 inhibitory herbal supplements, such as an extract of Tripterygium wilfordii [47]. The results of the present study demonstrate that asafetida has both apoptotic and anti-apoptotic effects. In optimal doses, it reverses senescence, but has the opposite effect at higher concentrations. Moreover, toxic concentrations of asafetida can be useful for skin exfoliation. Nevertheless, further studies are needed to identify its efficacy in vivo. Conclusion The results of the present study revealed that

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asafetida in low concentrations had an anti-senescence effect on human dermal fibroblasts. This effect was due to its role on enhancing the expression of the anti-apoptotic factor BCL2. Figure2(A) Expression levels of apoptotic and anti-apoptotic mRNAs in asafetida-treated senescent cells. The expression of BCL2 was increased in the groups treated with 5 × 10 -8 and 10 -7 g/ mL of asafetida compared with the control group (P < 0.01). Also, in those groups, the expression rates of apoptotic markers were significantly reduced as compared with the control group while in the groups treated with 5 × 10 -7 and 10 -6 g/mL of asafetida, the expression rates of apoptotic markers were increased. (B) Western blot assay for BCL2 protein in different groups (*P < 0.05 and $ P < 0.01, compared with the control group).

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Case report: a case of eruptive collagenoma occurring in esophagus and intestine Background Eruptive collagenoma is a rare disease. All of the previously reported cases were located on the skin. Here we report such a case occurring in esophagus and intestine. Case presentation Our patient is a Chinese woman. Two years ago, hundreds of small nodules were identified in her esophagus and intestine. The lesions were characterized by thickened hyalinized collagen fibers and haphazard neoplastic stellate cells. The tumor cells showed generally positive for vimentin and negative for h-CALD, CD34, desmin, CD163, AE1/AE3, CK7 and CK20. The nodules were blue with Masson Trichrome stain. The clinicopathological, immunohistochemical and histochemical features of the tumor were consistent with eruptive collagenoma. The patient was not given specific treatment after diagnosis, and a routine examination indicated that there was no progress for 2 years. Conclusion Hitherto, this is the first case of eruptive collagenoma to have been reported occurring in esophagus and intestine. Case presentation Our patient is a 51-year-old female. Two years ago, she presented with minor abdominal discomfort and dyspepsia for one month. Endoscopy revealed that hundreds of nodules, ranging from 2 mm to 5 mm in diameter, protruded from mucosa in her whole esophagus and intestine ( Fig. 1a-c). No ulcer or other abnormal manifestations could be observed. Biopsies were taken from different sites. Laboratory analysis indicated a slightly high IgG level of 25.9 g/L (normal 8.0-17.0 g/L), IgA level of 4.46 g/L (normal 0.72-4.29 g/L) and a slightly low complement C3 level of 0.73 g/L (normal

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0.79-1.52 g/L), complement C4 level of 0.14 g/L (normal 0.16-0.38 g/L), and normal ranges for CEA (1.17 ng/ml, normal 0.00-5.00 ng/ml) and AFP (1.40 ng/ml, normal 0.00-8.10 ng/ ml). Qualitative check of Bence-Jones protein was negative in urine. The suspected clinical diagnosis was primary systemic amyloidosis, and whether it is a hereditary disease should be differentiated. Her parents and younger sister were all given endoscopy examinations following the patient, but no similar nodules were found in them. Biopsy tissues from esophagus, terminal ileum, cecum, colon and rectum were submitted for pathological examination. The histopathological characteristics of each specimen were similar. The mucosa was unremarkable, epithelial cells demonstrated bland nuclei, with no atypia or mitotic activity. And no lymphoid inflammatory infiltration in the stroma was observed. In submucosa, there were several small round nodules which were well circumscribed and unencapsulated. The nodules were predominantly composed of collagen bundles, and a variable number of stellate tumor cells located within the collagen (Fig. 1d-f). The collagen were hyalinized and no skeinoid fibers could be observed. The tumor cells were haphazard and not arranged in storiform or palisading pattern. In most nodules, they located peripherally; but in a few nodules, they located diffusely. In all of the lesions, inflammatory cells, calcification, mitoses and necrosis were absent. After diagnosis, the patient was given some medicines of proton pump inhibitors and modulating intestinal flora for her symptoms, and no specific treatment was given for collagenoma. One month later, all of the discomfort disappeared. After that, she had a routine endoscopy examination once

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