The effect of being overweight was significant for Western European  countries only. When analysing the whole OECD region, an increase in unemployment retained its significant negative influence on the fertility rate , while being overweight did not. Interestingly, divergent influences of time were revealed and fertility rates increased with time in Eastern Europe while they decreased in Western Europe. Conclusion: Importantly, a significant negative influence of increase in unemployment on the fertility rate was revealed—irrespective of the region and time analysed. Furthermore, an adverse effect of being overweight on the fertility rate in Western European countries was revealed. Interestingly, time was associated with a decreasing fertility rate in Western but not in Eastern Europe.Background: The rationale of a postulated decrease in fertility rate development is still being debated. Among the multiple influencing factors, socioeconomic variables and their complex influence are of particular interest. Methods: Data on socioeconomic and health variables from 1976–2014 of 30 countries within the OECD region were analysed for their respective influence on fertility rates by using mixed-effect regression models. Results: A significant negative influence of the increase in unemployment rate on the following year’s changes in fertility rate in Western (−0.00256;  Disagreement on the rationale of the often-postulated declining fertility rates (defined as the number of children born per woman aged 15–49 years of age per year per region) of the recent decades in literature persists ,3,4,5. NPrevious literature on this topic revealed inconsistent and often conflicting results. While some studies reported a significant positive influence of being employed on fertility ,2,5,9, o2, the chance for a spontaneous pregnancy declined linearly [2) is known to be a risk factor for lower fertility [The effect of financial well-being is further complicated by its reported inverted “U-shape” association with body mass index (BMI)—with the highest rates of obesity being reported in women of average financial well-being. These rates gradually decrease towards the very low as well as very high range of financial well-being . Obesitylinearly . In addiertility . Thus, eertility ,18.As a lack of consensus on the rationale of declining fertility rates exists and complex interactions of health and financial well-being are postulated, our study aimed to investigate these interactions in a large, multinational cohort. To ensure comparability of data quality as well as health care systems, only data on countries partaking in the Organization for Economic Co-Operation and Development (OECD) were used. Data on socioeconomic variables as well as on health of the population for the last four decades were included. To the best of our knowledge, this is the first multicountry study investigating the influence of wealth and obesity on fertility rates.2); socioeconomic data that included the unemployment rate (defined as the number of persons currently unemployed per 1000 of the population). Only those countries for which a complete dataset of the examined variables was available for the analysed period were included Western European OECD Countries (taken from the ones listed in ): Austri(ii)Eastern European OECD Countries: Czech Republic, Estonia, Hungary, Latvia, Poland, Slovak Republic, Slovenia.(iii)Excluded (neither of the above groups or no data available on obesity): Australia, Canada, Chile, Iceland, Israel, Japan, Korea, Lithuania, Mexico, New Zealand, Turkey, United States.Data were retrieved from the “Organization for Economic Co-operation and Development Statistics Database” (OECD Stats Database) as well as the “World Health Organization—Health for All Database” (WHO-HFA) for the period of 1976–2014. The following data were collected for each country: the fertility rate (defined as the number of children born per woman aged 15–49 years of age); percentage of the population diagnosed as being overweight or obese  was set to t-1960, with t representing the year. As opposed to [βi to 0.)posed to , we did For comparison purposes, we also took data from the same 22 OECD countries considering the period from 1976–2014. In addition, we chose the data from 8 Eastern European OECD countries and recalculated the models for those and the totality of 30 countries. All calculations were performed with the SAS University Edition software (2021), using the mixed model, and the level of significance was set at <0.05.There were pronounced differences in fertility rates across the 30 OECD countries see  included2 aged 18 years and over) as well as “unemployment”, diverging trends were observed in our dataset: While the highest rates of unemployment  were reported as 14,827,000 in 2010 for the UK, the lowest (and most stable) rate was 2000 reported for Luxembourg in 1988–1992. For the above-mentioned period, the incidence of unemployment fluctuated , as well as year, revealed significant influences of these parameters on changes in fertility rates (“dFertility”) in the respective countries. The analyses were performed for Western and Eastern countries separately as well as all OECD countries combined. Details are provided in p < 0.01). Thus, an increase of one percent in the percentage of the population diagnosed with being overweight resulted in a decrease of the natural logarithm of the fertility rate by 0.0088 .When the effect of the change in the percentage of population being overweight was analysed, a significant negative influence on the change in fertility rate of the following year was observed in the Western OECD countries . Thus, an increase of one percent in the percentage of the population being unemployed resulted in a decrease of fertility rate in the following year of 0.25%.Furthermore, a significant negative influence for the variable “dUnemplrate” on the change in fertility rate of the affected countries was revealed in our analysis .Contrary to our analysis of Western OECD countries, in our analysis of data from Eastern OECD countries, we failed to reveal a significant influence of the effect of change in rate of overweight of the affected population on the change in fertility rate of the following year .However, when the effect of the change in the unemployment rate of the affected population on the change of fertility rate of the following year was analysed, a significant negative influence was also revealed for the Eastern OECD countries . Thus, for Eastern OECD countries, with ongoing time, fertility rate increased per year by 0.08%.Again, differing from the group of Western OECD countries, the variable time was revealed to exhibit a significant influence on the fertility rate of the affected population . In addition, the variable time was revealed to exhibit a significant influence on the change in fertility rate of the affected population . Thus, with ongoing time, the fertility rate increased per year by 0.04%. However, the variable “dOverweight” failed to retain the previously described negative significant association the model had revealed for Western OECD countries.The model, including data on all included OECD countries available (Western and Eastern countries combined) and analysing the possible influence of the variables overweight, unemployment and time, revealed a significant influence of “dUnemplrate” on the change in fertility rate on the respective countries included . Similar effects had been reported in the analyses of data in Europe and Latin America by Adsera et al. and Lee [In our analysis, an increase of one percent in the unemployment rate corresponded to a decrease in the following year’s fertility rate by 0.28% , following 1975, the fertility rate and the unemployment rate were pro-cyclical (high unemployment rates were associated with low fertility rates). However, older data may be of limited quality or validity. Furthermore, the correlation changing its vector of association may be partly caused by the increasing availability of oral hormonal contraceptives . These cAnalysis of our data supports the previously postulated hypothesis that couples may tend to decide against having children in more stressful and economically uncertain times and postpone the time of childbearing to times with better economic conditions . HoweverHowever, our findings corroborate the fertility rate of a population to be dependent on a multitude of factors. Therefore, it is important to clarify that changes in fertility rates are not merely a reaction to unemployment. Furthermore, (fear of) unemployment and economic uncertainty cause stress , which ip < 0.001, compared to Western: −0.0026; p < 0.001). We hypothesise couples in Eastern countries to be under more economic pressure, in part due to fewer funds available for welfare as well as the health care system. Thus, people in Eastern Europe may feel more insecure. To finance a family, it could be necessary to have both parents employed. In contrast, in Western Europe, a more robust health care system and a denser system of governmental social support may exist [In contrast to previous studies, both countries from Western as well as from Eastern Europe were included in the present analysis. Interestingly, the significant, negative effect of an increase in unemployment rate on the fertility rate of the corresponding population was more pronounced in Eastern countries  was included in this variable, limiting the ability to analyse the possible distinction in fertility rates due to hypothesised changes in hormonal values. Furthermore, on an aggregate level, the fact that the availability of data for the two sexes separately was limited may, however, be of importance [Several study limitations should be addressed. For the present analysis, we relied on administrative registry data. As these are limited to accuracy on a population level, no direct conclusions at the individual level may be drawn. Furthermore, the variable “overweight” was limited in resolution, as data were imputed as BMI > 25 kg/mportance . In addiIn conclusion, an ongoing reduction in fertility rates across all included OECD countries was observed. In all countries analysed as well as in the sub-analysis of Western OECD countries, a significant negative influence of the unemployment rate on the following year’s fertility rate was observed. From 1976 onwards, the effect of the percentage of the population diagnosed with being overweight was significant for Western European OECD countries only. Our findings underline the manifold influencing factors on fertility rates. The relationships are large-scale, and more multifactorial and multinational studies are required.


Giardia duodenalis, is an intestinal diarrheal disease affecting almost one billion people worldwide. A small endosymbiotic dsRNA viruses, G. lamblia virus (GLV), genus Giardiavirus, family Totiviridae, might inhabit human and animal isolates of G. duodenalis. Three GLV genomes have been sequenced so far, and only one was intensively studied; moreover, a positive correlation between GLV and parasite virulence is yet to be proved. To understand the biological significance of GLV infection in Giardia, the characterization of several GLV strains from naturally infected G. duodenalis isolates is necessary. Here we report high-throughput sequencing of four GLVs strains, from Giardia isolates of human and animal origin. We also report on a new, unclassified viral sequence (designed GdRV-2), unrelated to Giardiavirus, encoding and expressing for a single large protein with an RdRp domain homologous to Totiviridae and Botybirnaviridae. The result of our sequencing and proteomic analyses challenge the current knowledge on GLV and strongly suggest that viral capsid protein translation unusually starts with a proline and that translation of the RNA-dependent RNA polymerase (RdRp) occurs via a +1/−2 ribosomal frameshift mechanism. Nucleotide polymorphism, confirmed by mass-spectrometry analysis, was also observed among and between GLV strains. Phylogenetic analysis indicated the occurrence of at least two GLV subtypes which display different phenotypes and transmissibility in experimental infections of a GLV naïve Giardia isolate.Giardiasis, caused by the protozoan parasite  Giardia duodenalis  is a flagellated protozoan parasite pathogenic for humans and various mammals, including pets and livestock. It is responsible for giardiasis, the most common non-viral/non-bacterial diarrheal disease worldwide  and GLVJ17/10A [C-CCU-AUA]. In addition, in all GLV strains, the two downstream nucleotide insertions, C2909 and U3239 (according to GLVHP sequence), alter ORF1 reading frame extending its 3′ end, that lead to a capsid protein with an extended C-terminus, and prevent translation of the RdRp by any -1 frameshifting. The original 220 nt overlapping region within ORF1 and ORF2 [HP sequence) and must contain a slippery motif that might promote the required access to the +1 frame for RdRp translation by either +1 or −2 PRF [Totiviridae the expression of the RdRp by a +1 PRF, centered on CCC_GAA sequence, was suggested to occur for a strain of Leishmaniavirus LRV1-4  between CP and RdRp ORFs [CC-UUU-CUU-GAC sequence present in the ORF1/ORF2 overlapping region in our GLV stains possesses the necessary characteristics to promote either +1 or −2 PRF mechanism. Slippage may occur following ribosome stall while awaiting delivery of tRNA complementary to either the UUU codon for Phe or the CUU codon for Leu, both seldom-used codons in the genomes of G. duodenalis [Phe) in G. duodenalis hosts with slightly different genetic phenotypes  in GLVymerases  and/or tymerases  where twic level . Co-infecumented . HoweverHP and GLVCAT, respectively. Indeed, early report on infection with uncharacterized RNA viruses from different G. duodenalis isolates, suggested that differences in growth adaptation of naïve G. duodenalis isolates could be associated to variability in each virus infectivity [G. duodenalis isolates/Assemblages (in particular Assemblage B) will indeed help to strength our conclusions.Viral genomes and infection phenotypes clearly support the existence of two GLV subtypes, being represented by GLVectivity . SequencCAT strain could be associated to the limited intracellular accumulation of GLVCAT viral particles, due to an efficient release of the viral particles outside the cell. This is in agreement with previous observations that accumulation of high amount of GLV ceases G. duodenalis trophozoites division and cellular function, leading to the arrest of parasite growth [HP infection could be explained by an impaired release of viral particles that remain trapped inside the parasite, accumulating faster than they are released. Alternative strategies for virions egress has been described for non-enveloped naked viruses hijacking different types of extracellular vesicles, such as microvesicles (MVs), secretory autophagosomes and exosomes for non-lytic release [HP egress, leading to virions accumulation at cell periphery beneath the plasma membrane, could be associated to the tendency of viral particles to aggregate, as observed by electron microscopy and due to low repulsion forces at the virion surface, preventing viral exploitation of MVs secretion.Concerning the different viral infection phenotypes, the milder cytopathic effect we report in the WBC6e growth ,29. The  release ,71,72. TLeishmania and survive longer in the extracellular environment thus behaving as an envelope-like virus, facilitating LRV1 transmission and increasing infectivity in the host [G. duodenalis [G. duodenalis hosts.For instance, LVR1 can exploit exosome secretion pathway to be released from the host . Despiteodenalis , we coulG. duodenalis Assemblage E, co-infected with GLV. Based on the sequence homology of the RdRp domain in the expressed GdRV-2 large protein, the virus could be closely related to Totiviridae. Nevertheless, the absence of an independent ORF encoding for a putative capsid protein and the lack of evidence of capsid-like structures in the infected G. duodenalis trophozoites, might suggest that GdRV-2 belongs to a new unclassified family of capsid-less virus, such as the ssRNA(+) Narnaviruses and dsRNA Hypoviruses in fungi and dsRNA Endornaviruses in fungi and plants [G. duodenalis genome [G. duodenalis isolate J17/10, neither by PCR assay nor by whole-genome sequencing (data not shown). Instead, co-infection of Totivirus with satellite replication defective virus has been well documented in Saccharomyces yeasts [Totiviridae with capsid-less Narnaviridae has also been reported for the trypanosomatid parasite Blechomonas spp. [Narnaviruses, persistently infecting several S. cerevisiae strains [G. duodenalis RNAi machinery is present but does not work efficiently [G. duodenalis progeny. More efforts will be needed in the future to yield additional GdRV-2-like sequences, verify its distribution among different G. duodenalis Assemblages and allow the characterization of this virus from a functional and evolutionary perspective.We report here for the first time, a new putative RNA virus, GdRV-2 in at least one isolate of d plants . RdRp isd plants . We excld plants  and virus genome , no tracs yeasts . Some ofs yeasts . Recentlnas spp. . Persistnas spp. . The pro strains , by pack strains . Noteworiciently ,83. It wG. duodenalis and strengthens the possibility that GLV, or other endosymbiont virus infections, can be associated with alteration of particular phenotypic G. duodenalis traits, including virulence.Our study provides new evidence on GLV genome organization and biology, highlights the importance of performing in deep transcriptomic studies to reveal the potential diversity of viral infections in the protozoan parasite


G-protein-coupled receptors (GPCRs) and G-proteins have a range of roles in many physiological and pathological processes and are among the most studied signaling proteins. A plethora of extracellular stimuli can activate the GPCR and can elicit distinct intracellular responses through the activation of specific transduction pathways. For many years, biologists thought that GPCR signaling occurred entirely on the plasma membrane. However, in recent decades, many lines of evidence have proved that the GPCRs and G-proteins may reside on endomembranes and can start or propagate signaling pathways through the organelles that form the secretory route. How these alternative intracellular signaling pathways of the GPCR and G-proteins influence the physiological and pathological function of the endomembranes is still under investigation. Here, we review the general role and classification of GPCRs and G-proteins with a focus on their signaling pathways in the membrane transport apparatus. The family of G-protein-coupled receptors (GPCRs) is the largest class of membrane proteins in mammals. GPCRs are seven-transmembrane-domain protein receptors that initiate signal transduction upon binding to specific ligands. Their canonical transduction process requires a conformational switch of the receptor followed by the rearrangement of their principal effectors, i.e., the heterotrimeric G-proteins Gα, Gβ and Gγ, to start the signaling cascade. So far, over 800 GPCRs have been classified in the human genome , most ofFor many years, scientists have assumed the canonical signaling route of the GPCR to be initiated only from the plasma membrane. However, recent studies have demonstrated that GPCRs also localize to other intracellular compartments and can signal from these different locations, proposing a correlation between GPCRs’ subcellular location and its signaling properties ,5. In thOne of the most frequently used classification systems defines classes based on how their ligand binds, or on both their physiological and structural features ,7. One cClass A, also known as the rhodopsin-like family (R) is the largest group of GPCRs in many organisms, including 80% of the human receptors . The memClass B GPCRs are the secretin-like family, containing around 70 receptors , and onlClass C includes the glutamate receptors, GABA receptors, calcium-sensing receptors, and taste receptors . Seven tFinally, class D includes fungal mating pheromone receptors, class E includes cAMP receptors, and class F includes frizzled/smoothened receptors.This last GPCR class, with almost 11 members identified in the human genome , is ofteG-proteins represent by far the dominant class of signal mediators, started with GPCR receptors. These two protein groups (GPCR and G-protein) can be considered a frequent and important type of functional unit. G proteins are defined by their ability to bind and hydrolyze the GTP molecule and can be divided in to small (or monomeric) G-proteins and heterotrimeric G-proteins. The first class is also the more numerous, since the human genome comprises 150 small GTPases belonging to the RAS superfamily , which hIn this article, we mainly deal with the heterotrimeric G-proteins. The members of this family are composed of three subunits, i.e., Gα, Gβ and Gγ. The Gα subunits have GTPase activity, i.e., they catalyze the hydrolysis of GTP to GDP; this is a central event in their function, as the forms linked to the GTP and GDP are active or inactive, respectively. They are often anchored to the membrane by N-terminal palmitoylation and can also be myristoylated .GPCR activates G-protein by promoting GDP/GTP exchange in the Gα subunit. In the classic model of the function of heterotrimeric G-proteins, the Gα subunit changes its conformation after GTP binding, allowing it to detach from the Gβγ dimer. Both the Gα and the Gβγ subunits are then free to interact with downstream targets, usually components of signaling pathways. When the Gα hydrolyses GTP into GDP, it becomes inactivated, allowing it to associate again with Gβγ. The GPCR-G-protein system, thus, represents a complex hub with at least three exit paths to different signaling networks; therefore, it is probably the most complex and versatile multi-protein signaling mechanism created by evolution in the eukaryotic cell. All organisms encode several types of G-proteins, and different combinations of these proteins into heterotrimers preferentially activate different signaling pathways.There are 23 known genes encoding for Gα proteins grouped into four subclasses with each targeting different signaling pathways ,29. ScheBesides the relatively high number of Gα protein subunits identified so far, there are five Gβ and twelve Gγ genes , which cGPCR receptor activation is triggered by a ligand binding to different domains, according to the GPCR class and to the biochemical proprieties of the ligand; this occurs to stimulate G protein signaling through the conformational change in the seven-transmembrane region of the receptor that enables the insertion of the α5 helix of the Gα subunit .Class A GPCRs bind the ligand in the seven-transmembrane region, leading to conformational changes that involve mainly a switch of TM3 interaction from TM6 to TM7, thanks to TM6 movement towards the cytosol and the opposite movement of TM7 ,37. ClasMost GPCRs can activate different signal cascades in response to extracellular stimuli, thus providing the opportunity to have a diversification of the type of intracellular signaling, for example, through different second messengers. Moreover, the magnitude of the signaling cascade initiated by GPCR is amplified by many orders in each step, for example, through the multiple activation of many adenylyl cyclases by a single G-protein molecule .Following activation, desensitization mechanisms must inactivate the signaling process; this occurs though different approaches that are all deputed to interrupt the interaction between the GPCR and its ligand. These regulatory processes are essential to avoid over-activation of the downstream pathways and comprise GPCR internalization followed by either recycling through the endosomal compartment or lysosomal degradation, or the desensitization mechanism can act through the degradation of the ligand itself. GPCR internalization is regulated by phosphorylation of the C-tail by specific kinases, such as PKA ,45,46,47The phosphorylated C-tail of GPCR has a high affinity for the arrestin proteins ,57. ArreGPCR and G-protein signaling have the important function of transducing the effect of a ligand into specific and potent intracellular signaling, but the desensitization process also occurs at an intracellular level, i.e., through the rapid degradation of second messengers such as cAMP and Calcium, or through the inactivation of other specific targets . An impoAltogether, all the steps in the GPCR signaling and inactivation chain can be separate targets for regulation, including the receptor itself, further illustrating the concept that the GPCR-G-protein signaling system is one of the most complex and sophisticated regulatory systems of the eukaryotic cell. Indeed, G-protein signaling can also be activated and regulated in a GPCR-independent manner, for example, thanks to the action of two main classes of protein such as the Regulators of G-protein signaling (RGS) and the Activators of G protein signaling (AGS).The RGS superfamily is a group of 20 proteins in mammals  that share the RGS domain ,71. RGS As mentioned above, GPCRs can not only activate G-proteins, but they can also activate a heterogeneous protein group, the AGS . AGS proteins have been identified initially as GPCR-independent activators of G-protein signaling ,81. ThisThe endomembrane system is rich in monomeric G-proteins, and in particular, the Golgi complex harbors a huge number of RABs and Arf proteins with important roles in membrane trafficking . While tMoving forward in the secretory pathway, the Golgi complex hosts three different classes of G proteins, such as Gα(s), Gα(q/11) and Gα(i/o) ,94,95. TMore recently, the KDELR has been found to also bind and activate Gα(o) at the Golgi . Gα(o) sAlso, the Gαi3 protein is unconventionally activated on the Golgi membrane by GIV/Girdin, an AGS acting as a GEF, to regulate the Arf1 activation cycles . More reAs seven-transmembrane proteins, GPCRs start the journey through the secretory pathway at the level of the ER, and in fact, ER-export is the first critical point for GPCR trafficking. Indeed, ER-chaperones  play a crucial role in the acquisition of correct folding for a broad number of GPCRs , and thiMoving forward in the secretory pathway, the GPCRs gains further post-translational modifications, such as glycosylation, at the level of the Golgi complex. The role of glycosylation in receptor trafficking strictly depends on the receptors itself, in that it is essential for the follicle-stimulating hormone receptor but completely dispensable for the M2-muscarinic receptor .cis-Golgi protein, Golgin-160, promotes the membrane localization of b1-adrenergic receptor [2B-adrenergic receptor [Several Golgi proteins regulate GPCRs’ localization on the plasma membrane. For example, the receptor , while treceptor ,113. Thereceptor . The molThe secretory pathway, and in particular, the ER and the Golgi complex, plays an essential role in the transport, maturation, and sorting of GPCR. Indeed, most of the time, the pool of TGN/Golgi localized GPCRs are derived from retrograde transport from the endosomes, as with PTHR and TSHR ,116, or An interesting aspect about GPCRs’ localization on endomembranes is that their endogenous ligand should be either membrane-permeable or actively transported to access the putative binding site that is embedded in the lumen of intracellular organelles, such as the ER or the Golgi.The latter possibility explains how mGluR5 can be activated on ER and nuclear membranes, although its endogenous ligand Glutamate is not membrane permeable. Indeed, two transporters, the sodium-dependent excitatory amino acid transporters and the cystine/glutamate exchanger, have been identified as responsible for the intracellular signaling of mGluR5 . Recent Apart from the KDELR, the ER stably hosts the GPR30 and mGluR5 proteins, both involved in calcium signaling ,129. IndSimilarly, the protease-activated receptor 4 (PAR4) shows a strong ER-localization in a steady state condition, because of the presence of the ER-retention sequence on the cytosolic tail that is recognized by the COPI complex. Indeed, PAR4 trafficking to the plasma membrane can happen in the presence of the PAR2 receptor, which recruits 14-3-3 subunits to mask the ER-retention motif and allows trafficking towards the Golgi . ConversOne of the most interesting signaling pathways of the endomembrane pool of receptors is the one coming from internalized compartments such as the early endosomes . AccordiHowever, it has now become clear that internalized GPCRs can use several mechanisms to also promote G-protein signaling from internalized compartments ,145,146.The hypothesis of the capability of the GPCR to signal through the endosomal pathway has been built overall the years, looking at receptors such as the activation of the parathyroid hormone receptor (PTHR) , the neuIndeed, it has been reported that these types of receptors, after agonist activation and internalization, induce an unexpected increased amount of cellular cAMP ,152. RecThe evidence supporting GPCR signaling in the endosomes also opens questions about the possibility of distinguishing between GPCRs able to signal acutely through specific components expressed in the endosomal compartment, such as with the D1DR and β2-AR. Alternatively, the GPCRs can continue to produce a wave of cAMP signaling after desensitization of the initial plasma membrane signaling, as observed in the case of vasopressin receptor-2 (V2R) . V2R intTherefore, the growing interest in GPCR endosomal signaling has also pushed for the development of many new biosensors. Indeed, these tools can detect the dynamic of the activation of different pools of GPCR along the endocytic pathway during agonist activation. The most well-known example is nanobodies , which aDespite the many new findings about the GPCR endosomal signaling, there are still open questions that need to be answered. For example, how this specific type of compartmentalized signaling can modulate, or sometimes even drive, different responses, and how these phenomena can be linked to distinct physiological results. The specific functional meaning of GPCR signaling from endosomes is still an open field, with many questions that do not have a straightforward answer. The specific signaling targets and molecular components are supposed to differ from the ones activated by the GPCRs on the plasma membrane, but clear data are still missing. Indeed, the signaling activated on the plasma membrane is rapidly switched off once the receptor is internalized, while the endosomal signaling may be more prolonged, depending on the class of GPCR involved.Finally, nuclear GPCRs are one of the most interesting permanent intracellular pools of receptors. So far, over 40 GPCRs show a nuclear localization, along with many of the proteins classically associated with GPCR-mediated events, ranging from Gα and Gβγ subunits , to adenGPCR nuclear signaling has been demonstrated by both pharmacological approaches using membrane-permeable and impermeable ligands, as well as by assaying GPCR signaling in isolated nuclei. In several neuronal cell types, the stimulation of mGluR5 and consequent Gq activation using membrane-permeable agonists promotes sustained calcium signaling ,185. TheThere are studies supporting the hypothesis that nuclear GPCRs can signal in the nucleus through the classical signaling pathways that are detectable in the cytoplasm after the activation of the plasma membrane pool of the receptors. Indeed, the activation of nuclear GPCRs is often followed by the activation of phosphorylation pathways and fluctuations in the level of the cAMP ; this isTransport endomembranes are enriched with many types of small G-proteins that control various cell functions and other cellular signaling components, such as kinases; however, as we have seen, they are also equipped with an unexpected number of heterotrimeric G-proteins. What functional significance can the presence of the various GTPase and signaling proteins have in the transport apparatus of the intracellular membrane?In the last two decades, a growing body of evidence has led to the understanding that transport apparatus is controlled by a complex regulatory network that ensures that the transport compartments function in a stable, robust and efficient fashion; it also ensures that they coordinate their activities amongst themselves, and with those of other cellular functional modules, to ensure harmonic cellular responses to environmental stimuli.This regulatory network is based schematically on two main types of mechanisms: the intracellular homeostatic control and coordination mechanism, and the regulatory mechanisms activated by environmental cues. The first, the internal homeostatic mechanisms, monitor the activities of the transport apparatus via sensors that are localized in the transport endomembranes. In the event of imbalances in the transport processes, for example, those caused by internal or external perturbations, these sensors react by triggering signaling and transcriptional pathways to correct the imbalances and restore homeostasis. In addition, when necessary, to protect cellular and organismal function from damage caused by temporary transport failures, the homeostatic regulators can also influence transport-unrelated cellular functions such as general protein synthesis, energy metabolism and survival/apoptotic mechanisms through additional signaling and transcriptional responses.The fundamental mechanism is that of feedback by which the cell returns the controlled parameter to the optimal level. The cell can achieve feedback with very different degrees of complexity, therefore starting from the simple regulatory mechanism derived from product-inhibition (very frequent in various metabolic reactions) to the simple event of phosphorylation, to the more complex chains of events that include small G-proteins, to the highest level of complexity that involves heterotrimeric G-proteins.Heterotrimeric G-protein-based control systems are likely to be more complex regulatory hubs and able to integrate and produce different functional inputs and outputs. A second class of transport regulatory mechanisms is based on externally activated systems, i.e., by environmental cues. Surface receptors or nutritional inputs generally start signaling there, and drive complex cellular programs  that involve the coordinated intervention of several cellular functional modules in response to environmental demands. In this context, proteins normally operating in signaling mechanisms can also be present in endomembranes only as relay stations of extracellular signals, or as modifiers and processors of extracellular signals.An interesting question is that of whether the signaling activated by intracellular sensors might make up a significant fraction of the overall cellular signaling activity. Indeed, the density of the regulatory network active on the transport endomembranes and in other intracellular signaling organelles—such as lysosomes, mitochondria and peroxisomes—highlights that a large fraction of the proteins involved in signaling are localized on intracellular membranes. GPCR and G-protein signaling play a crucial role in regulating many fundamental processes that have an impact not only on cellular homeostasis, but also on the correct functioning of the whole organism. Moreover, GPCRs represent, by far, the largest family of cell-surface molecules involved in signal transmission, and their dysfunction could be correlated to many human diseases; hence, GPCRs represent the target, directly or indirectly, of 30–40% of therapeutic agents .The discovery of multiple cellular compartments from where these signaling platforms activate different signaling pathways has changed the way researchers think about GPCR and G-proteins. From a pharmacological viewpoint it has opened the possibility of selectively targeting one specific pool of these molecules, leaving the rest unperturbed.


A single-atom catalyst of A–Co–NG is explored for electrochemical uric acid (UA) detection for the first time and realize practical UA monitoring in serum samples.The A–Co–NG sensor demonstrates high performance for UA detection with a wide detection range from 0.4 to 41950 μM and an extremely low detection limit of 33.3 nM.Combination of experimental and theoretical calculation discovers mechanism for the UA oxidation on the single-atom catalyst.The online version of this article (10.1007/s40820-020-00536-9) contains supplementary material, which is available to authorized users. (II) atoms coordinated by an average of 3.4 N atoms on an N-doped graphene matrix (A–Co–NG) to build an electrochemical biomimetic sensor for UA detection. The A–Co–NG sensor achieves a wide detection range over 0.4–41,950 μM and an extremely low detection limit of 33.3 ± 0.024 nM, which are much better than previously reported sensors based on various nanostructured materials. Besides, the A–Co–NG sensor also demonstrates its accurate serum diagnosis for UA for its practical application. Combination of experimental and theoretical calculation discovers that the catalytic process of the A–Co–NG toward UA starts from the oxidation of Co species to form a Co3+–OH–UA*, followed by the generation of Co3+–OH + *UA_H, eventually leading to N–H bond dissociation for the formation of oxidized UA molecule and reduction of oxidized Co3+ to Co2+ for the regenerated A–Co–NG. This work provides a promising material to realize UA detection with wide detection range and low detection limit to meet the practical diagnosis requirements, and the proposed sensing mechanism sheds light on fundamental insights for guiding exploration of other biosensing processes.Uric acid (UA) detection is essential in diagnosis of arthritis, preeclampsia, renal disorder, and cardiovascular diseases, but it is very challenging to realize the required wide detection range and low detection limit. We present here a single-atom catalyst consisting of CoThe online version of this article (10.1007/s40820-020-00536-9) contains supplementary material, which is available to authorized users. Nitric oxide (NO) was prepared through the reaction between H2SO4 and NaNO2 and purified with different concentrations of KOH. Buffer solution was prepared using Mettler-Toledo pH meter. All of the other chemical reagents were purchased from Sigma-Aldrich and used directly without further purification. Milli-Q water (resistivity over 18 MΩ cm) from a Millipore-Q water purification system was used in all experiments.Graphene oxide was synthesized from graphite flakes using the improved Hummers method . Sodium 10 mbar using a monochromatic Al Kα X-ray beam (1486.60 eV). All measured binding energies were referenced to the C 1s peak (284.60 eV) arising from the adventitious hydrocarbons. N2 adsorption–desorption isotherms were conducted on an 3H-2000PS1 accelerated surface area and porosimetry system  at 77 K using Barrett–Emmett–Teller (BET) calculations for the surface area. The pore size distribution plot was determined with the desorption branch of the isotherm on the Barrett–Joyner–Halenda (BJH) model. X-ray diffraction (XRD) was conducted at Bruker D8 advance (Germany). Electrochemical measurements were performed in 0.1 M NaOH (pH = 13) on a CHI 760e electrochemical workstation . Three-electrode setup was employed with Pt plate (1.0 × 1.0 cm2) and saturated calomel electrode (SCE) as the counter and reference electrode, respectively. And a working electrode was prepared by using different materials modified electrode. The metal contents of the catalysts were measured by ICP-MS, which were carried out by a Thermo Scientific iCAP6300 . X-ray absorption spectra were collected at Shanghai Synchrotron Radiation Facility (SSRF) on beamline BL14W1. All the data were collected in the transmission mode at ambient temperature. Data analysis was performed with Artemis and IFEFFIT software 3−/[Fe(CN)6]4−(5 mM) as a probe (data not show); n is the electron transfer number.We further measured the cyclic voltammograms of A–Co–NG toward 500 μM UA in 0.1 M NaOH pH = 13) at various scan rates form 0.03–0.4 V s at varioequation  as follo00 μM UA ; C0 is t+, Na+, SO42−, and Cl−. The current responses of these molecules, a key evaluate measurement for the specificity of proposed sensors, were summarized in Fig. +, Na+, SO42−, and Cl−, which do not cause any noticeable interference to the UA response with the current signals relative standard deviation (RSD) less than 5%.Moreover, under oxidizing conditions, the presence of antioxidant species, such as AA, DA, NO, and so on can interfere with the UA detection in biological applications. The selectivity of the A–Co–NG and referenced catalysts toward UA oxidation was examined using amperometric method at 0.3 V versus SCE by analyzing various potential interfering species coexisting with UA, such as AA, DA, Glu, NO, KI−t response of A–Co–NG upon successive addition of UA to a continuous stirred NaOH  was recorded. The influence of applied potential controlled from 0.1 to 0.4 V versus SCE on response of the A–Co–NG toward 33 μM UA was investigated . The amperometric currents gradually increased along with the increasing of potential and exhibited a sharp increase at 0.3 V versus SCE. Considering the interference of many coexisted foreign species at too positive potential, 0.3 V versus SCE was chosen as the working potential to maintain a high sensitivity. As shown in Fig. I (μA) = 1.3 + 0.022 CUA (μM) and I (μA) = 22.9 + 0.0015 CUA (μM) at a correlation coefficient of 0.9981 (n = 24) and 0.9986 (n = 7), respectively. A low detection limit of 33.3 ± 0.024 nM is achieved, which is estimated from the expression of LOD = 3 S/K, where S is the standard deviation of the blank signals (nB = 20), K is the analytical sensitivity that can be estimated from the slope of calibration curve at lower concentration ranges. The accomplished sensitivities of A–Co–NG nanozyme calculated from slopes of the calibration curves are 297.2 and 21.2 μA mM−1 cm−2, respectively. The calculated limit of quantitation (LOQ) of A–Co–NG for UA detection is 400 nM. Moreover, A–Co–NG can give a much wider linear range and a lower detection limit than the reported materials  group accompanying the Co2+ oxidized to Co3+ [3+ rather than Co2+. The CV curve of A–Co–NG nanozyme  in alkaline media. In process of OER on single Co atom catalyst, the step of second electron transfer (from *OH to *O) with a larger energy barrier (1.23 + 0.52 eV) is a rate limiting step [3+–OH–UA* state is energetic favorable with free energy of −0.796 eV, as shown in Fig. 3+–OH–UA* state, the charger redistribution in the system happens under the driving force of oxidation potential. The insets of Fig. 3+–OH + *UA and Co2+–H2O + *UA_H states, respectively. It is obvious electron transfers from UA to Co3+–OH, which results in N–H bond dissociation, and a reduction of center Co atom from +3 to +2. The calculated energy barrier is 0.3 eV for Co3+–OH + *UA state transferring to Co2+–H2O + *UA_H . The DFT results display long interaction distance of 2.31 and 2.38 Å for vertically and parallel adsorption configurations of UA on Co atom in A–Co–NG, respectively, indicating that interaction between UA and Co atom of A–Co–NG is weak. According to earlier study, A–Co–NG in aqueous solution were usually terminated by hydroxyl anion  and Co (III), respectively. As shown in Fig. S14a, the UA oxidation current for biased at 0.4 V is about 3 times of that of at -0.05 V, indicating higher UA oxidation catalytic activity of the *OH− assistant reaction pathway. Moreover, although the redox behavior is not obvious, the potential-dependent UA detection performances of other cobalt-based samples (P–Co–NG) are similar with that of A–Co–NG nanozyme , which indicate that the catalytic mechanism of UA oxidation on the A–Co–NG is a general mechanism for UA oxidation.The proposed catalytic mechanism was further confirmed by the comparison of the catalytic activity of A–Co–NG nanozyme at different states, in which the atomic Co center in +2 and +3 valence state, respectively. As shown in Fig. In summary, we report a single-atom catalyst A–Co–NG offering atomically dispersed Co–N center sites for building an electrochemical biomimetic sensor to highly sensitively and selectively detect UA. The A–Co–NG sensor also demonstrates its application in accurate serum examination toward UA, holding a great promise to its practical application in analysis of UA in real samples. This work provides a promising material with high active site density to realize UA detection with wide detection range and low detection limit, and the mechanism finding could be used to design and fabricate other kinds of SACs with enzyme-like activities for a wide range of biomimetic applications.Supplementary material 1 (PDF 1165 kb)Below is the link to the electronic supplementary material.


Background: Previous retrospective cohorts showed that Rehmannia-6  formulations were associated with significant kidney function preservation and mortality reduction among chronic kidney disease patients with diabetes. This study aimed to investigate the potential mechanism of action of common R-6 variations in a clinical protocol for diabetic nephropathy (DN) from a system pharmacology approach.Study Design and Methods: Disease-related genes were retrieved from GeneCards and OMIM by searching “Diabetic Nephropathy” and “Macroalbuminuria”. Variations of R-6 were identified from a published existing clinical practice guideline developed from expert consensus and pilot clinical service program. The chemical compound IDs of each herb were retrieved from TCM-Mesh and PubChem. Drug targets were subsequently revealed via PharmaMapper and UniProtKB. The disease gene interactions were assessed through STRING, and disease–drug protein–protein interaction network was integrated and visualized by Cytoscape. Clusters of disease–drug protein–protein interaction were constructed by Molecular Complex Detection (MCODE) extension. Functional annotation of clusters was analyzed by DAVID and KEGG pathway enrichment. Differences among variations of R-6 were compared. Binding was verified by molecular docking with AutoDock.Results: Three hundred fifty-eight genes related to DN were identified, forming 11 clusters which corresponded to complement and coagulation cascades and signaling pathways of adipocytokine, TNF, HIF-1, and AMPK. Five variations of R-6 were analyzed. Common putative targets of the R-6 variations on DN included ACE, APOE, CCL2, CRP, EDN1, FN1, HGF, ICAM1, IL10, IL1B, IL6, INS, LEP, MMP9, PTGS2, SERPINE1, and TNF, which are related to regulation of nitric oxide biosynthesis, lipid storage, cellular response to lipopolysaccharide, inflammatory response, NF-kappa B transcription factor activity, smooth muscle cell proliferation, blood pressure, cellular response to interleukin-1, angiogenesis, cell proliferation, peptidyl-tyrosine phosphorylation, and protein kinase B signaling. TNF was identified as the seed for the most significant cluster of all R-6 variations. Targets specific to each formulation were identified. The key chemical compounds of R-6 have good binding ability to the putative protein targets.Conclusion: The mechanism of action of R-6 on DN is mostly related to the TNF signaling pathway as a core mechanism, involving amelioration of angiogenesis, fibrosis, inflammation, disease susceptibility, and oxidative stress. The putative targets identified could be validated through clinical trials. In 2021, 10.5% of the world population were diabetic, with a rising trend . Of the Diabetic kidney disease (DKD) is conventionally diagnosed by the presence of albuminuria, reduced kidney function, and clinical history excluding other etiologies . MacroalRehmanniae Radix (Di-huang) (Corni Fructus (Shan-zhu-yu) (Dioscoreae Rhizoma (Shan-yao) (Poria (Fu-ling) (Moutan Cortex (Mu-dan-pi) (Alismatis Rhizoma (Ze-xie)  treatment was associated with slower decline of kidney function and reduced risk of end-stage kidney failure and mortality among patients with CKD and diabetes . CM formi-huang) , Corni F-zhu-yu) , Dioscorhan-yao) , Poria (Fu-ling) , Moutan -dan-pi) , and Ali(Ze-xie) . Accordiin vivo and in vitro studies focusing on specific mechanisms may have limitations for the assessment of interaction between CM formulations and disease with multifactorial pathophysiology  (https://www.omim.org/)   and the im.org/) . GeneCarim.org/)  and is cim.org/) . The genim.org/) .The variations of R-6 were identified from an existing clinical practice guideline developed based on expert consensus in mainland China , which ihttp://mesh.tcm.microbioinformatics.org/) (https://pubchem.ncbi.nlm.nih.gov/) (http://www.lilab-ecust.cn/pharmmapper/) (https://www.uniprot.org/) (TCM-Mesh (cs.org/) , with dacs.org/) . Compounih.gov/) , a freelmapper/) , to idenot.org/) , a centrhttps://string-db.org/, version 11.0)   (on 11.0)  to assesn 3.7.2) , to intehttps://david.ncifcrf.gov/summary.jsp, version 6.8)  (ion 6.8) , a web shttps://www.rcsb.org/). Water molecules and inactive ligands were removed before the proteins were hydrogenated and charged , negative regulation of lipid storage (GO: 0010888), cellular response to lipopolysaccharide (GO: 0071222), and inflammatory response (GO: 0006954) and positive regulation of NF-kappa B transcription factor activity (GO: 0051092) in cluster 1; positive regulation of phosphatidylinositol 3-kinase signaling (GO: 0014068), angiogenesis (GO: 0001525), positive regulation of cellular protein metabolic process (GO: 0032270), response to hypoxia (GO: 0001666), positive regulation of peptidyl-tyrosine phosphorylation (GO: 0050731), platelet degranulation (GO: 0002576), and renin–angiotensin regulation of aldosterone production (GO: 0002018) in cluster 2; and inflammatory response (GO: 0006954) and leukocyte migration (GO: 0050900) in cluster 3, which was highly similar to R-6. Both formulations 1 and 4 also had a cluster with significant interaction on complement activation (GO: 0006956).There were six clusters with a significant function between formulation 2 and DN. The major cluster of interaction involved regulation of blood pressure (GO: 0008217), positive regulation of ERK1 and ERK2 cascade (GO: 0070374), positive regulation of cell proliferation (GO: 0008284), positive regulation of cell migration (GO: 0030335), positive regulation of T-cell proliferation (GO: 0042102), negative regulation of the endothelial cell apoptotic process (GO: 2000352), cellular response to interleukin-1 (GO: 0071347), negative regulation of the extrinsic apoptotic signaling pathway via death domain receptors (GO: 1902042), positive regulation of MAPK cascade (GO: 0043410), positive regulation of protein kinase B signaling (GO: 0051897), aging (GO: 0007568), cellular response to tumor necrosis factor (GO: 0071356), and extracellular matrix organization (GO: 0030198) in addition to that of R-6 and DN alone.Formulation 5 formed eight clusters with significant interactions with DN. The two clusters with the most significant interactions included positive regulation of phosphatidylinositol 3-kinase signaling (GO: 0014068), angiogenesis (GO: 0001525), positive regulation of cellular protein metabolic process (GO: 0032270), response to hypoxia (GO: 0001666), positive regulation of peptidyl-tyrosine phosphorylation (GO: 0050731), platelet degranulation (GO: 0002576), and renin–angiotensin regulation of aldosterone production (GO: 0002018) in cluster 2; inflammatory response (GO: 0006954) and leukocyte migration (GO: 0050900) in cluster 3; and complement activation (GO: 0006956) in cluster 6 .KEGG analysis showed that formulations 1, 3, and 5 involved the TNF signaling pathway, NOD-like receptor signaling pathway, non-alcoholic fatty liver disease, and inflammatory bowel disease, and formulations 2 and 4 involved inflammatory mediator regulation of TRP channels in addition to the shared pathways .From the molecular docking, the key chemical constituents from R-6 have good binding affinity to APOE, CCL2, EDN1, FN1, HGF, ICAM1, IL10, IL1B, IL6, INS, LEP, MMP9, PTGS2, SERPINE1, TNF, and TNF receptor 1, which supported the mechanistic involvement of these related pathways in the R-6’s effect on DN. ACE, CRP, PTGS, and TNF receptor 2 were not assessable due to the large crystal structure .in vivo and in vitro studies. These pathways are also shared by insulin resistance, rheumatoid arthritis, non-alcoholic fatty liver disease, and various types of infectious diseases and cancers, indicating a possibility in repurposing established therapeutics of these diseases for the DN management.Eleven clusters of pathophysiology were identified from DN. From a systemic perspective, the complement and coagulation cascades, adipocytokine signaling pathway, TNF signaling pathway, HIF-1 signaling pathway, and AMPK signaling pathway were the key pathways mediating the pathogenesis of DN based on the current evidence from R-6’s mechanistic action involves modulation of complement, coagulation, angiogenesis (VEGF), oxidative stress (HIF-1), innate and adaptive immunity , cell proliferation and survival , cell adhesion (Rap1 and MAPK), and hormonal  and metabolism  pathways.From the network inferences, R-6 likely acts on DN via the TNF, NOD-like receptor, HIF-1 and PI3K-Akt signaling pathway, complement and coagulation cascades, and renin–angiotensin system. These share similar mechanisms with non-alcoholic fatty liver disease, inflammatory bowel disease, and rheumatoid arthritis, which could support the use of R-6 in these conditions.in silico binding affinity assessment, alisol (Alismatis Rhizoma), 7-o-methyl morroniside (Corni Fructus), campesterol (Dioscoreae Rhizoma), paeoniflorin (Moutan Cortex), beta-amyrin acetate (Poria), and catalpol (Rehmanniae Radix) have the highest likelihood of interacting with the proteins involved in these pathways.From the From KEGG enrichment analysis, the TNF signaling pathway was demonstrated as the key signaling involved in the action of R-6 on DN with the highest number of involved pathways. TNF signaling activates multiple pathways  via receptors including TNF receptor type I (TNFR1) and TNF receptor type II (TNFR2), leading to apoptosis, necroptosis, inflammatory response, and vascular response. The TNF signaling pathway has been suggested as a therapeutic target for general CKD , autoimmIns2Akita mice  the study medication involves multiple drugs and chemicals, (2) network pharmacology analysis is already a systematic integration of all existing in vivo and in vitro data sessment . Subsequsessment .The complement and coagulation cascades, adipocytokine signaling pathway, TNF signaling pathway, HIF-1 signaling pathway, and AMPK signaling pathway orchestrated the pathogenesis of DN from a systemic perspective. The therapeutic effect of R-6 on DN likely involves the TNF, NOD-like receptor, HIF-1, and PI3K-Akt signaling pathways; the complement and coagulation cascades; and the renin–angiotensin system. The analysis of R-6 and the comparative analysis of R-6 variations converged to suggest that the TNF signaling pathway is the key mechanism involved in the action of R-6 on DN among patients with DN presenting with different clinical phenotypes. Variations of R-6 used in clinical protocols may also involve the NOD-like receptor signaling pathway and TRP channels on top of the common mechanisms from indirect inferences. These putative targets could be validated through further trials with clinical samples.


Helicobacter pylori. To discover novel cocrystals of VPZ, we adopted an artificial neural network (ANN)-based machine learning model as a virtual screening tool that can guide selection of the most promising coformers for VPZ cocrystals. Experimental screening by liquid-assisted grinding (LAG) confirmed that 8 of 19 coformers selected by the ANN model were likely to create new solid forms with VPZ. Structurally similar benzenediols and benzenetriols, i.e., catechol (CAT), resorcinol (RES), hydroquinone (HYQ), and pyrogallol (GAL), were used as coformers to obtain phase pure cocrystals with VPZ by reaction crystallization. We successfully prepared and characterized three novel cocrystals: VPZ–RES, VPZ–CAT, and VPZ–GAL. VPZ–RES had the highest solubility among the novel cocrystals studied here, and was even more soluble than the commercially available fumarate salt of VPZ in solution at pH 6.8. In addition, novel VPZ cocrystals had superior stability in aqueous media than VPZ fumarates, demonstrating their potential for improved pharmaceutical performance.Vonoprazan (VPZ) is the first-in-class potassium-competitive acid blocker (P-CAB), and has many advantages over proton pump inhibitors (PPIs). It is administered as a fumarate salt for the treatment of acid-related diseases, including reflux esophagitis, gastric ulcer, and duodenal ulcer, and for eradication of  The combination with a value 0 ≤ ΔapK ≤ 3 is much less predictable and falls within a “salt-cocrystal continuum” [apK values > 3. In contrast, coformers with phenol groups showed ΔapK < 0, indicating a higher probability of cocrystal formation with VPZ. Therefore, we judged that the new PXRD patterns of VPZ–CAT, VPZ–HYQ, VPZ–RES, and VPZ–GAL resulted from the formation of cocrystals. As the discovery of new cocrystals for VPZ was the main objective of this study, we focused on these four cocrystals and performed detailed characterization.As VPZ has a strong basic group (amine) with a e of 9.4 , it is lntinuum” . We applThe bulk cocrystals that crystallized using the RC method were characterized by PXRD, DSC, TGA, and FT-IR. The PXRD patterns of the cocrystals prepared by RC showed several distinct diffraction peaks, which were different from the characteristic peaks corresponding to VPZ and the coformers . The absonset). This may be one of the reasons why the fumarate salt of VPZ is used commercially. The newly discovered VPZ–RES, VPZ–CAT, and VPZ–GAL cocrystals all showed a single endothermic peak corresponding to the melting (Tonset) of pure cocrystals at 93, 103.9, and 130 °C, respectively. Furthermore, no significant weight change was observed before decomposition, confirming the unsolvated nature of VPZ cocrystals . In the VPZ cocrystals, the broad phenolic O–H stretching peaks were shifted to wavenumbers about 60–200 cm−1 lower and superimposed on the C–H stretching regions (around 3000 cm−1). These marked downward shifts in the region of phenolic O–H stretching suggested that the O–H groups were involved in strong intermolecular hydrogen bonding without proton transfer, thereby forming new phases. The weak N–H stretching band at 3321 cm−1 in the VPZ spectrum was also shifted to a slightly lower wavenumber (by around 20 cm−1) in the spectra of VPZ cocrystals, indicating the presence of interactions between VPZ and the corresponding coformer molecules.The major differences between the cocrystals and their respective components appeared in the region of 3600–2800 cm−1 . RES, CA−1 in the spectra of VPZ cocrystals  via a combination of virtual and experimental screening. Among the eight new solid forms synthesized, three materials were proved to be the novel VPZ cocrystals, VPZ–RES, VPZ–CAT, and VPZ–GAL, which were eventually characterized. The dissolution rates and solubilities of the VPZ cocrystals were comparable to those of the commercial VPZ fumarate salt. The dissolution behavior of the VPZ cocrystals appears to be mainly determined by the intermolecular interaction as a correlation between the melting point, the enthalpy of fusion, and the dissolution rate exists.Three VPZ cocrystals and the fumarate salt remained stable in the solid state during the accelerated stability testing. On the other hand, the stabilities of the 3 VPZ cocrystals in pH 6.8 buffer solution were superior to the fumarate salt, suggesting the new VPZ cocrystals as a potential alternative to the marketed VPZ fumarate salt. This study not only contributes to extending the knowledge about the solid state of pharmaceutically important drug substances, but also provides a good example of the successful integration of a machine-learning approach with experimental screening for the discovery of novel pharmaceutical solid forms.


Purpose: Exosome component 5 (EXOSC5) is a non-catalytic component of the RNA exosome complex, which is interacted with the Zinc-finger antiviral protein to degrade the target RNA and aberrantly expressed in various malignances. We explored the molecular mechanisms and biological roles by which EXOSC5 promotes the progression of GC.Methods: We used quantitative real-time PCR, Western blotting and immunohistochemistry to analyze EXOSC5 expression in GC samples. An GC organoid-based functional model was assessed, and cancer cell CCK-8 assay, colony formation assay and flow cytometry were performed to reveal the role of EXOSC5 in GC cell proliferation and tumorigenesis. In vivo, nude mice tumorigenesis assay were performed to explore the effects of EXOSC5 knockdown on growth of GC. The roles of EXOSC5 on AKT and STAT3 signaling pathways were measured by Western blot.Results: The expression of EXOSC5 was up-regulated in GC tissues and cell lines compared with normal group, and highly expressed EXOSC5 indicated a poorer clinical outcome for GC patients and was positively correlated with tumor size and TNM stage. EXOSC5 overexpression facilitated the growth of GC cells and organoids, while EXOSC5 downregulation inhibited proliferation and induced G1/S phase transition arrest. Moreover, mechanistic studies demonstrated that EXOSC5 increased cyclinD1 expression levels and decreasing the expression levels of p21 and p27 via regulation of the AKT and STAT3 pathway.Conclusion: The expression of EXOSC5 is upregulated and correlated with tumorigenesis and poor prognosis of GC. EXOSC5 increases GC proliferation partly through activating AKT and STAT3 pathways. Gastric cancer (GC) is the second commonest cause of cancer related death among both men and women worldwide The exosome complex is a ribonuclease complex composed of ten evolutionarily conserved subunits capable of processing and degrading multiple classes of RNA molecules both in the nucleus and cytoplasm In this study, the expression profile and clinical features of EXOSC5 and its correlations with GC patients were explored by analyzing several public databases and clinical samples. We demonstrated that EXOSC5 contributed to the growth of GC and alters the cell cycle distributions. EXOSC5 can promote the proliferation in GC, at least partially, by activating AKT and STAT3 signaling pathways, thus leading to regulate the expression of cell-cycle regulator p21, p27 and cyclin D1 in GC cells and organoids. Importantly, this is the first study reporting the oncogenic and prognostic roles of EXOSC5 in GC.A total of primary GC and matched normal tissue specimens  were obtained from the First Affiliated Hospital of Zhejiang university from 2015 to 2016. All patients had not received preoperative radiotherapy and chemotherapy before surgery, and underwent pathological diagnosis by two professional pathologists according to the criteria of the American Joint Committee on Cancer (AJCC) TNM classification.Five human GC cell lines  and the immortal normal gastric mucosa epithelium cell line (GES-1) were purchased from the Cell Bank of Chinese Academy of Sciences . GC cell lines were cultured in the Roswell Park Memorial Institute (RPMI)-1640 medium with 10% feta bovine serum , and GES-1 was grown in Dulbecco's modified Eagle's medium  with 10% FBS, maintained at 37 °C incubator in a 5% CO2 humidified atmosphere consisting.2O2 in methanol for 10 mins. Non-specific binding was blocked by incubation with 10% normal goat serum in phosphate-buffered saline (PBS) for 1 hour at room temperature. The slides were incubated with primary antibody EXOSC5  overnight at 4 °C, followed by biotinylated goat anti-rabbit lgG  for 1 hour at room temperature. Then, a streptavidin-biotin-peroxidase complex assay was carried out. The peroxidase activity was developed by incubating with 0.1% 3,3-diaminobenzidine (Sigma) in PBS with 0.05% H2O2 for 5 min at room temperature. Based on the frequency and intensity of staining, the positive rate was scored as 0 (no staining), 1 (1-25%), 2 (26-50%), 3 (51-75%) or 4 (76-100%), and the staining intensity was graded as 0 (negative), 1 (weak), 2 (intermediate) or 3 (strong).Immunohistochemistry was performed as described previously TRIzol reagent  was used for the extraction of the total RNA from frozen tissues and cultured cells. PrimeScript RT Reagent Kit  was used to synthesize for complementary DNA (cDNA). SYBR Green Premix Ex Taq  on an ABI 7500 PCR system  was used to carry out qRT-PCR, according to the standard quantitative PCR program. The primer sequences used were: EXOSC5 forward: 5'- ACTTTGCCTGCGAACAGAACC-3′, EXOSC5 reverse: 5′-CTCTTTGCTGACCTTCACCTC-3′; GAPDH forward: 5′-GGAGCGAGATCCCTCCAAAAT-3′, and ′′GAPDH reverse: 5- GGCTGTTGTCATACTTCTCATGG-3. Relative expression of EXOSC5 was calculated by 2-ΔΔCt method according to the internal control GAPDH.4 g, 4 °C for 20 min. The concentrations of the proteins were detected using the BCA Protein assay kit . Identical quantities of proteins were separated by SDS-PAGE, and transferred onto PVDF membranes . After that, membranes were incubated with primary antibodies at 4 °C overnight. Then, the membrane was washed with TBST three times and incubated with an HRP-conjugated secondary antibody . GAPDH  was used as standard loading control. The primary antibodies are as following: EXOSC5 ; p21 ; p27 ; cyclin D1 ; p-AKT ; AKT ; p-STAT3 ; AKT .The total proteins of frozen tissues and cultured cells were extracted in RIPA buffer  with phosphatase inhibitor and protease inhibitor . The Cell lysates were centrifuged at 1.2 × 105) were seeded in 6-well plates, incubated for 24 h and then transfected with 1μg of plasmids and 1μg Lentivirus Package plasmid mix diluted in 200 μl Opti-MEM  with 4 μl Lipofectamine 3000  according to this protocol. At 48 h and 72 h, the virus-containing medium was harvested for the first and second time, and then transferred through 0.45 μm filter. Next, the medium were centrifuged at 2×104 g for 2 hour. The precipitate were suspended in 50 μl PBS and stored at -80 °C. For lentivirus infections, the AGS and HGC-27 cells were cultured in 24-well plates for infection by virus-containing PBS with polybrene , incubated at 37 °C for 24 h and replaced by 1640 medium with 10% FBS. For overexpression plasmid transfection, MGC-803 and MKN45 were transfected with EXOSC5 overexpression plasmids using Lipofectamine 3000 following the manufacturer's protocol.EXOSC5 short hairpin RNAs (shEXOSC5), EXOSC5 overexpression plasmid and their control were purchased from GeneRay Company . The target sequences are: shRNA1#1, 5′- GAAGGTCAGCAAAGAGATT-3′; shRNA#2, 5′- CGAAGTGATCCTGAGGCCGAAGATT-3′. For lentiviral packaging, HEK293T cells  solution was added to each well and absorbance at 450 nm was measured after 2 hour of incubation once a day for 5 days. For colony formation assay is as follows: 1000 cells were seeded in 6-well plate and cultured for 10 days. Then cell colonies were fixed using 4% paraformaldehyde, and stained with 0.1% crystal violet . The number and size of colonies with more than 50 cells was detected. All experiments were performed in triplicate.Human GC organoids were cultured as described previously to simulate the tumor microenvironment of the human body 5 cells per well. After 48 h, the cells were collected, centrifuged and rinsed with precooling PBS twice. Then the cells were fixed with 75% ethanol at 4 °C overnight or -20 °C for long-term storage. Finally, the cells were centrifuged and added with 500 μl DNA staining solution  to stain the DNA. The stained cells were evaluated by flow cytometry  and the data was analyzed by FlowJo 10.1.The AGS and HGC-27 cells were seeded into 6-well culture plate with 2 × 106 HGC-27 stably transfected with shRNA-EXOSC5 or shRNA-NC injected subcutaneously in the right flank of mice (four mice per group). Tumor volume was measured every 5 days, and tumor weight was weighed at the end of the experiment.Female nude mice  were purchased from Hangzhou Ziyuan Laboratory Animal Technology Company. All animal experiments were approved by the Institutional Animal Care and Use Committee at the First Affiliated Hospital of Zhejiang university. For xenograft models, 5 × 10T-test and one-way ANOVA was performed to compare the differences between groups. The correlations between IHC scores and clinicopathologic characteristics were using chi-square test and Logistic multivariate analysis. Survival rates were calculated using Kaplan-Meier method. Cox regression model was used to identify independent prognostic factors associated with overall survival. P value < 0.05 was considered statistically significant. All statistical analyses were performed by SPSS version 22.0 .First, we analyzed the mRNA expression of EXOSC5 in GC and normal tissues using the Cancer Genome Atlas (TCGA). The result revealed that EXOSC5 was remarkably up-regulated in GC tissues compared to normal tissues Figure A. In ordAs shown in Table in vitro  was detected by qRT-PCR and Western blot  (Figure To better understand the molecular mechanisms of EXOSC5-driven GC progression, we collected the overlapping genes between cBioPortal and Coexpedia to carry out GO and KEGG analyses in David v6.7 (To further explore whether EXOSC5 could promote proliferation of GC via AKT and STAT3 signaling pathways, the EXOSC5 overexpression MKN45 were treated by the AKT inhibitor MK-2206 or STAT3 inhibitor S31-201. As shown in Figure in vitro, while can be used to model organ development to offer unprecedented genomic and environmental manipulation Recent studies have demonstrated that organoids capture stably preserve genetic, proteomic, morphological and pharmacotypic features of the parent tumor in vivo.Tumorigenesis assays by subcutaneous injection with HGC27 cell lines stably expression scramble control and two EXOSC5 shRNAs were performed in nude mice, and tumor growth was monitored and measured every day. As can be seen in Figure Previously, there was little known about the prognostic roles and molecular function of EXOSC5 in GC development. In this study, we used a straightforward approach to uncover the expression pattern and clinicopathological features of EXOSC5 in GC and its prognostic function with prognosis by integrative analysis of multiple cancer databases and clinical samples. Furthermore, functional and mechanism exploration revealed that knockdown of EXOSC5 significantly inhibited the growth of GC cells and targeted regulation of cell cycle factors cyclin D1, p21 and p27 via AKT and STAT3-associated signaling pathways (Figure in vivo and in vitro experiments.Although the expression of EXOSC5 has been studied in different cancers, there are limited reports about the clinical relevance and functional roles of EXOSC5 in solid tumors. Compared to normal tissues, increased expression of EXOSC5 was reported in many types of tumor cell lines, such as hematopoietic tumor, cervical carcinoma, melanoma, colon cancer cell and renal cell carcinoma To test the roles of EXOSC5 in GC, we investigated the function of EXOSC5 in the regulation of GC cell proliferation using gain- and loss-of biological function assay. In this study, our findings indicated that EXOSC5 depletion suppressed proliferation by regulating G1/S transition, while opposite results were observed in EXOSC5 overexpressing GC cells. The cyclin-CDK complex cyclin D1 was widely reported to be an essential regulator of cell cycle process by inducing the transition from G1 to S phase To investigate the molecular mechanisms of EXOSC5 in proliferation of GC, we found that AKT and STAT3 pathways might be involved in the stimulatory effects. The AKT and STAT3 signaling pathways are responsible for proliferation and cell cycle, and function as an oncogene in various types of tumors, including GC In summary, this study reports an altered EXOSC5 expression pattern in GC and reveals its clinicopathologic relevance. Furthermore, functional and mechanistic studies suggested a crucial function of EXOSC5 in GC cell proliferation through the regulation of cell cycle related proteins cyclin D1, p21 and p27 partially via AKT and STAT3 signaling pathways. Therefore, we proved that EXOSC5 assumes the role of oncogene to promote the proliferation of GC cells and will be a promising therapeutic target in GC in the years to come.Supplementary figure.Click here for additional data file.


Connexins are a family of gap junction forming proteins widely expressed by mammalian cells. They assemble into hexameric hemichannels, which can either function independently or dock with opposing hemichannels on apposite cells, forming a gap junction. Pannexins are structurally related to the connexins but extensive glycosylation of these channels prevents docking to form gap junctions and they function as membrane channels. Platelets express pannexin-1 and several connexin family members . These channels are permeable to molecules up to 1,000 Daltons in molecular mass and functional studies demonstrate their role in non-vesicular ATP release. Channel activation is regulated by (patho)physiological stimuli, such as mechanical stimulation, making them attractive potential drug targets for the management of arterial thrombosis. This review explores the structure and function of platelet pannexin-1 and connexins, the mechanisms by which they are gated and their therapeutic potential. Platelets circulate in a complex environment, interacting with other blood cells and the vessel wall. Vascular injury or rupture of atherosclerotic plaques expose thrombogenic molecules  that initiate platelet recruitment, activation and thrombus formation, resulting in hemostasis or thrombosis, respectively. The platelet response to injury is rapid and proportionate, orchestrated by complex interplay of activatory and inhibitory signals . ConversConnexins have been studied widely and members of this family of 21 proteins ) since cXenopus laevis oocytes expressing Panx1. When the glycosidase PNGaseF was applied to the bath solution, N-linked glycans on Panx1 were broken down and a junctional conductance could be recorded 0) was demonstrated by atomic force microscopy studies in HeLa cells expressing recombinant Cx40. In this study hemichannels were open in Ca+ free conditions but closed when [Ca2+]0 was elevated to 3.6 mM [0 sensing motif within the hemichannel pore is responsible for channel closure and this motif is conserved between connexin family members [2+] markedly reduce the open probability of connexin hemichannels, it is not clear whether this phenomenon can be overcome by other regulatory mechanisms, such as phosphorylation or mechanical stimulation. Given that connexins contribute to platelet activation in flow cytometric studies with physiological levels of [Ca2+]0 [2+]o [2+]o) leads to the activation of Panx1, via an unknown mechanism [2+]o+ calcium signaling, leading to ATP release and amplification of the aggregation response [Gating of connexin hemichannels by extracellular  has been shown to be sensitive to connexin and Panx1 inhibitors [Platelets and megakaryocytes express stretch-activated Piezo 1 , TRPM7 ,46 and Tomponent . The patomponent . Furtheromponent . Platelehibitors ,21.Protein trafficking represents an alternative mechanism for the regulation of pannexins and connexins. The half-life of connexin hemichannels at the plasma membrane is estimated to be between 1.5 and 5 h . By comp−/- mice do not have a cardiovascular phenotype and Cx40−/- mice have reduced cardiac conduction velocity, leading to increased incidence of arrhythmias, suggesting that there may be some functional redundancy between family members [Connexins and Panx1 have been studied using the inhibitors carbenoxolone, probenecid, and spironolactone, which are also FDA-approved drugs for the management of tracheal ulcers, gouty arthritis and hypertension, respectively ,21,27,51 members . Further members ,56. Pharin vitro and in vivo. These target sequences could therefore be used to inform the development of small molecule inhibitors to target these proteins on platelets and manage thrombosis.An alternative approach would be to develop small molecule inhibitors that target specific connexin or pannexin isoforms. Isotype specific inhibitory peptides that target the extracellular loops of connexins ,57 and PEx vivo analyses demonstrated that mouse platelets treated with probenecid, reduced murine platelet aggregation [In vitro thrombus formation assays also demonstrate reduced thrombus formation in the presence of carbenoxolone or probenecid [regation ,51. In vobenecid ,21. Furtobenecid . These dTo date, studies have primarily focussed on the role of platelet connexins and pannexins, however, these proteins are also expressed within the megakaryocyte. Within the bone marrow, Cx43 is the predominant connexin isoform and is expressed by megakaryocytes . Indeed,−/-, Panx1−/- and Cx40−/-Panx1−/- mice [−/- mice. This phenotype was explored further with the double knockout and Panx1 depletion could not rescue the vascular phenotype of Cx40−/- [In vivo thrombosis studies with Cx40−/- [−/- [Despite their structural and functional similarities, there is relatively little data available on the interactions between the pannexins and connexins. Noveielli-Kuntz and colleagues evaluated the cardiovascular phenotype of Cx40−/- mice . Cx40-de Cx40−/- . However Cx40−/-  and Panx−/- [−/-  mice botPlatelets express Panx1 and multiple members of the connexin gap junction family. These channels are activated following platelet stimulation, contributing to ATP release, Ca+ signali