The temporal balance between self-renewal and differentiation of human neural stem cells requires the Amyloid Precursor Protein The approximately 16 billion neurons of the human neocortex are derived from a relatively limited number of developmental neural stem cells (NSCs). During embryogenesis, human cortical NSCs initially generate neurons at a particularly slow rate while preserving their progenitor state for a relatively long time. How this balance between the progenitor state and neurogenic state is regulated, and whether it contributes to species-specific brain patterning, is poorly understood. Here we show that the characteristic potential of human NSCs to remain in a progenitor state as they generate neurons for a prolonged amount of time requires the Amyloid Precursor Protein (APP). In contrast, APP is dispensable in mouse NSCs, which undergo neurogenesis at a much faster rate. Mechanistically, loss of APP cell-autonomously accelerates neurogenesis through activation of the AP1 transcription factor and repression of WNT signaling. We propose that the fine balance between self-renewal and differentiation is homeostatically regulated by APP, which may contribute to human-specific temporal patterns of neurogenesis.
Probabilistic solvers enable a straight-forward exploration of numerical uncertainty in neuroscience models Understanding neural computation on the mechanistic level requires models of neurons and neuronal networks. To analyze such models one typically has to solve coupled ordinary differential equations (ODEs), which describe the dynamics of the underlying neural system. These ODEs are solved numerically with deterministic ODE solvers that yield single solutions with either no, or only a global scalar bound on precision. It can therefore be challenging to estimate the effect of numerical uncertainty on quantities of interest, such as spike-times and the number of spikes. To overcome this problem, we propose to use recently developed sampling-based probabilistic solvers, which are able to quantify such numerical uncertainties. They neither require detailed insights into the kinetics of the models, nor are they difficult to implement. We show that numerical uncertainty can affect the outcome of typical neuroscience simulations, e.g. jittering spikes by milliseconds or even adding or removing individual spikes from simulations altogether, and demonstrate that probabilistic solvers reveal these numerical uncertainties with only moderate computational overhead.
Affordable Caenorhabditis elegans tracking system for classroom use For decades the nematode C. elegans has served as an outstanding research organism owing to its unsurpassed experimental amenability. This advantage has also made this tiny worm an attractive vehicle for science instruction across higher learning institutions. However, the prohibitive cost associated with the automated behavioral assessment of these animals remains an obstacle preventing their full adoption in undergraduate and high school settings. To improve this situation, we developed an inexpensive worm tracking system for use by high school interns and undergraduate students. Over the past two years this tracker has been successfully used by undergraduate students in our introductory Cell and Molecular lab (BSC220) at Illinois State University. Here we describe and demonstrate the use of our inexpensive worm tracking system. TXN, a Xanthohumol Derivative, Attenuates High-Fat Diet Induced Hepatic Steatosis by Antagonizing PPARγ We previously reported xanthohumol (XN), and its synthetic derivative tetrahydro-XN (TXN) attenuates high-fat diet (HFD) induced obesity and metabolic syndrome in C57BL/6J mice. The objective of the current study was to determine the effect of XN and TXN on lipid accumulation in the liver. Non-supplemented mice were unable to adapt their caloric intake to 60% HFD, resulting in obesity and hepatic steatosis; however, TXN reduced weight gain and decreased hepatic steatosis. Liver transcriptomics indicated TXN might antagonize lipogenic PPAR{gamma} actions in vivo. XN and TXN inhibited rosiglitazone-induced 3T3-L1 cell differentiation concomitant with decreased expression of lipogenesis-related genes. A PPAR{gamma} competitive binding assay showed XN and TXN bind to PPAR{gamma} with an IC50 similar to pioglitazone and 8-10 times stronger than oleate. Molecular docking simulations demonstrated XN and TXN bind in the PPAR{gamma} ligand-binding domain pocket. Our findings are consistent with XN and TXN acting as antagonists of PPAR{gamma}. Adult fibroblasts use aggresomes only in distinct cell-states The aggresome is a protein turnover system in which proteins are trafficked along microtubules to the centrosome for degradation. Despite extensive focus on aggresomes in immortalized cell lines, it remains unclear if the aggresome is conserved in all primary cells and all cell-states. Here we examined the aggresome in primary adult mouse dermal fibroblasts shifted into four distinct cell-states. We found that in response to proteasome inhibition, quiescent and immortalized fibroblasts formed aggresomes whereas proliferating and senescent fibroblasts did not. Using this model, we generated a resource to better understand the aggresome, providing a characterization of the proteostasis networks in which the aggresome is used and transcriptomic features associated with the presence or absence of aggresome formation. Using this resource, we validate a previously reported role for p38 MAPK signaling in aggresome formation and identify TAK1 as a novel driver of aggresome formation upstream of p38 MAPKs. Together, our data demonstrate that the aggresome is a non-universal protein degradation system which can be used cell-state specifically and provide a resource for better understanding aggresome formation and function. Wnt target enhancer regulation by a CDX/TCF transcription factor collective and a novel DNA motif Transcriptional regulation by Wnt signalling is primarily thought to be accomplished by a complex of {beta}-catenin and TCF family transcription factors (TFs). Although numerous studies have suggested that additional TFs play roles in regulating Wnt target genes, their mechanisms of action have not been investigated in detail. We characterised a Wnt-responsive element (WRE) downstream of the Wnt target gene Axin2 and found that TCFs and Caudal-related homeodomain (CDX) proteins were required for its activation. Using a new separation-of-function TCF mutant, we found that WRE activity requires the formation of a TCF/CDX complex. Our systematic mutagenesis of this enhancer identified other sequences essential for activation by Wnt signalling, including several copies of a novel CAG DNA motif. Computational and experimental evidence indicates that the TCF/CDX/CAG mode of regulation is prevalent in multiple WREs. Put together, our results demonstrate the complex nature of cis- and trans- interactions required for signal-dependent enhancer activity. Light activation of Orange Carotenoid Protein reveals initial C8'-C7' double bond trans/cis isomerization Orange Carotenoid protein (OCP) is the only known photoreceptor which uses carotenoid for its activation1,2. It is found exclusively in cyanobacteria, where it functions to control light-harvesting of the photosynthetic machinery. However, the photochemical reactions and structural dynamics of this unique photosensing process are not yet resolved. We present time-resolved crystal structures at second-to-minute delays under bright illumination, capturing the early photoproduct and structures of the subsequent reaction intermediates. The first stable photoproduct shows carotenoid trans/cis isomerization at the C7-C8double bond and structural changes in the N-terminal domain with minute timescale kinetics. These are followed by a thermally-driven cis/trans isomerization that recovers to the dark state carotenoid configuration. Structural changes propagate to the C-terminal domain, resulting, at later time, in the H-bond rupture of the carotenoid keto group with protein residues. The isomerization and its transient nature are confirmed in OCP crystals and solution by FTIR and UV/Vis spectroscopy. This study reveals the isomerization of the carotenoid and subsequent thermal structural reactions as the basis of OCP photoreception. Understanding and potentially controlling the OCP dynamics offers the prospect of novel applications in biomass engineering3 as well as in optogenetics and bioimaging. Estimating animal density with camera traps: a practitioner's guide of the REST model Camera traps are increasingly popular in wildlife research and have the potential to be reliable and cost-effective for estimating animal density. Although density estimation using this automatic technique has long been restricted to species with individually recognizable markings, several analytical approaches have been proposed to target animals lacking such markings (i.e., unmarked populations). Among these approaches, the random encounter and staying time (REST) model may be an efficient and cost-effective approach, even though the procedures for the implementations have not yet been shared with researchers. This paper presents a working protocol for implementing the REST model our research group has been developing. We also present the R code to perform parameter estimation with a maximum likelihood and Bayesian approach. We suggest that this model has potential for further development. We strongly hope that this paper will encourage many researchers to use the REST for density estimation in a wide variety of species in various habitats and make a significant contribution to advancing wildlife conservation and management. Human cells contain myriad excised linear intron RNAs with links to gene regulation and potential utility as biomarkers By using TGIRT-seq, we identified >8,500 short full-length excised linear intron (FLEXI) RNAs in human cells. Subsets of FLEXIs accumulated in a cell-type specific manner, and [~]200 corresponded to agotrons or mirtrons or encoded snoRNAs. Analysis of CLIP-seq datasets identified potential interactions between FLEXIs and >100 different RNA-binding proteins (RBPs), 53 of which had binding sites in [&ge;]30 different FLEXIs. In addition to proteins that function in RNA splicing, these 53 RBPs included transcription factors, chromatin remodeling proteins, and cellular growth regulators that impacted FLEXI host gene alternative splicing and/or mRNA levels in knockdown datasets. We computationally identified six groups of RBPs whose binding sites were enriched in different subsets of FLEXIs: AGO1-4 and DICER associated with agotrons and mirtrons; AATF, DKC1, NOLCI, and SMNDC1 associated with snoRNA-encoding FLEXIs; two different combinations of alternative splicing factors found in stress granules; and two novel RBP-intron combinations, one including LARP4 and PABC4, which function together in the cytoplasm to regulate ribosomal protein translation. Our results suggest a model in which proteins involved in transcriptional regulation, alternative splicing, or post-splicing secondary functions bind and stabilize cell-type specific subsets of FLEXIs that perform different biological functions and have potential utility as biomarkers. Population differences in the length and early-life dynamics of telomeres among European pied flycatchers Telomere length and shortening rate are increasingly used as biomarkers for long-term costs in ecological and evolutionary studies because of their relationships with survival and fitness. Both early-life conditions and growth, and later-life stressors can create variation in telomere shortening rate. Studies on between- population telomere length and dynamics are scarce, despite the expectation that populations exposed to varying environmental constraints would present divergent telomere length patterns. The pied flycatcher (Ficedula hypoleuca) is a passerine bird breeding across Eurasia (from Spain to western Siberia) and migrating through the Iberian Peninsula to spend the non-breeding period in sub-Saharan Africa. Thus, different populations show marked differences in migration distance. We studied the large-scale variation of telomere length and early-life dynamics in the pied flycatcher by comparing six European populations across a north- south gradient (Finland, Estonia, England, and Spain) predicting negative effect of migration distance on adult telomere length, and of nestling growth on nestling telomere dynamics. There were clear population differences in telomere length, with English birds from mid-latitudes having the longest telomeres. Telomere length did not thus show consistent latitudinal variation and was not linearly linked to differences in migration distance. Early-life telomere shortening rate tended to vary between populations. Fast growth was associated with shorter telomeres in the early life, but faster nestling growth affected telomeres more negatively in northern than southern populations. While the sources of between-population differences in telomere-related biology remain to be more intensively studied, our study illustrates the need to expand telomere studies at the between-population level. Higher-order effects, continuous species interactions, and trait evolution shape microbial spatial dynamics The assembly and maintenance of microbial diversity in natural communities, despite the abundance of toxin-based antagonistic interactions, presents major challenges for biological understanding. A common framework for investigating such antagonistic interactions involve cyclic dominance games with pairwise interactions. The incorporation of higher-order interactions in such models permits increased levels of microbial diversity, especially in communities where antibiotic producing, sensitive, and resistant strains co-exist. However, most such models involve a small number of discrete species, assume a notion of pure cyclic dominance, and focus on low mutation rate regimes, none of which well represents the highly interlinked, quickly evolving, and continuous nature of microbial phenotypic space. Here, we present an alternative vision of spatial dynamics for microbial communities based on antagonistic interactions--one in which a large number of species interact in continuous phenotypic space, are capable of rapid mutation, and engage in both direct and higher-order interactions mediated by production of and resistance to antibiotics. Focusing on toxin production, vulnerability, and inhibition among species, we observe highly divergent patterns of diversity and spatial community dynamics. We find that species interaction constraints (rather than mobility) best predict spatiotemporal disturbance regimes, whereas community formation time, mobility, and mutation size best explain patterns of diversity. We also report an intriguing relationship among community formation time, spatial disturbance regimes, and diversity dynamics. This relationship, which suggests that both higher-order interactions and rapid evolution are critical for the origin and maintenance of microbial diversity, has broad-ranging links to the maintenance of diversity in other systems.

Significance StatementPersistently diverse microbial communities are one of biologys great puzzles. Using a novel continuous trait space modeling framework that accommodates high mutation rates, elevated species richness, and direct and higher-order antagonistic species interactions, we find that two parameters characterizing mutation size and mobility best explain patterns of microbial diversity. Moreover, community formation time (the duration of the transient phase in community assembly) provides an unexpectedly clear guide to the diversity profiles of the resulting communities. These discoveries showcase how complex, antagonistic interactions mediated by the production of, inhibition of, and vulnerability to toxins (antibiotics) can shape microbial communities, allowing for extraordinarily high levels of diversity and temporal persistence. The Digital 3D-Atlas MAKER (DAMAKER): a dynamic and expandable digital 3D-tool for monitoring the temporal changes in tissue growth during hindbrain morphogenesis Reconstruction of prototypic three-dimensional (3D) atlases at the scale of whole tissues or organs requires specific methods to be developed. We have established a digital 3D-atlas maker (DAMAKER) and built a digital 3D-temporal atlas to monitor the changes in the growth of the tissue and neuronal differentiation domain in the zebrafish hindbrain. DAMAKER integrates spatial and temporal data from cell populations, neuronal differentiation and brain morphogenesis, through in vivo imaging techniques paired with image analyses and segmentation tools. First, we generated a 3D-reference from several imaged hindbrains and segmented them using a trainable tool; these were aligned using rigid registration, revealing distribution of neuronal differentiation growth patterns along the axes. Second, we quantified the dynamic growth of the neuronal differentiation domain vs. the progenitor domain, and by in vivo neuronal birthdating experiments we generated a digital 3D-temporal map of the neuronal growth in the whole hindbrain, revealing the spatiotemporal dynamics of neuronal differentiation upon morphogenesis. Last, we applied it to glutamatergic and GABAergic neurons, as proof-of-concept that the digital 3D-temporal map could be used as a proxy to infer neuronal birthdate. As this protocol uses open-access tools and algorithms, it can be shared for standardized, accessible, tissue-wide cell population atlas construction. Sugar Signaling Induces Dynamic Changes during Meristem Development to Regulate Flowering in Arabidopsis Aerial parts of plants originate from pluripotent stem cells in the shoot apical meristem. Their population is maintained via the maintenance regulators WUSCHEL and CLAVATA3 in a negative feed-back loop. Meristem size is dynamic and undergoes a more than 2-fold expansion upon the transition to reproductive growth. The mechanism controlling this doming is largely unknown, but coinciding increased trehalose 6-phosphate and changed meristem size in overexpressing or knockdown lines of TREHALOSE PHOSPHATE SYNTHASE1 suggest a participation of sugar signaling. Here we show that TREHALOSE PHOSPHATE PHOSPHATASEJ is directly regulated by WUSCHEL. Plants with reduced levels of TREHALOSE PHOSPHATE PHOSPHATASEJ in the outer meristem layer are flowering early and its reduction in the late flowering clavata3 mutant, restores wild-type flowering. This is caused by a reduction of mature miR156 and increased expression of SQUAMOSA PROMOTER-BINDING PROTEIN-LIKE genes. We demonstrate that these are important for age pathway-induced flowering, in a negative feed-back loop with WUSCHEL downstream of the trehalose 6-phosphate pathway. In summary, our findings demonstrate a dynamic feed-back regulation between central maintenance and flowering time regulators with sugar signaling.



O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=169 SRC="FIGDIR/small/439483v2_ufig1.gif" ALT="Figure 1">
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org.highwire.dtl.DTLVardef@988d6eorg.highwire.dtl.DTLVardef@16d469borg.highwire.dtl.DTLVardef@1366ce5org.highwire.dtl.DTLVardef@2753f0_HPS_FORMAT_FIGEXP  M_FIG O_FLOATNOSynopsis:C_FLOATNO Schematic illustration of dynamic feedback-regulations between sugar signaling, meristem maintenance and the age pathway of the flowering network in the transition SAM as compared to the vegetative SAM.During vegetative growth SAM maintenance is controlled by spatially separated WUS and CLV3 expression in a negative feedback-loop. At floral transition increased activity of the T6P pathway in the SAM uncouples this regulation. This results in an unreported special relocation of WUS expression and involves a transient negative feedback-loop between WUS and SPL4.

C_FIG Versatile mixotrophs employ CO2 fixation as fill-up function to dominate in modern groundwater The current understanding of organic carbon inputs into ecosystems lacking photosynthetic primary production is predicated on data and inferences derived almost entirely from metagenomic analyses. The elevated abundances of putative chemolithoautotrophs in groundwaters suggest that dark CO2 fixation is an integral component of subsurface trophic webs. To understand the impact of autotrophically-fixed carbon, the flux of CO2-derived carbon through various subpopulations of subsurface microbiota must first be resolved, both quantitatively and temporally. Here, we implement novel stable isotope cluster analysis to render a time-resolved and quantitative evaluation of 13CO-derived carbon flow through a groundwater microbiome stimulated with reduced sulfur compounds. We demonstrate that mixotrophs, not obligate chemolithoautotrophs, were the most abundant active organisms in groundwater microcosms. Species of Hydrogenophaga, Polaromonas, Dechloromonas, and other metabolically versatile mixotrophs drove the recycling of organic carbon and, when chance afforded, supplemented their carbon requirements via chemolithoautotrophy and uptake of available organic compounds. Mixotrophic activity facilitated the replacement of 43 and 80% of total microbial carbon stores with 13C in just 21 and 70 days, respectively. This opportunistic "utilize whatever pathways net the greatest advantage in fitness" strategy may explain the great abundances of mixotrophs in other oligotrophic habitats, like the upper ocean and boreal lakes. 3D Reconstruction of Bird Flight Trajectories Using a Single Video Camera Video cameras are finding increasing use in the study and analysis of bird flight over short ranges. However, reconstruction of flight trajectories in three dimensions typically requires the use of multiple cameras and elaborate calibration procedures. We present an alternative approach that uses a single video camera and a simple calibration procedure for the reconstruction of such trajectories. The technique combines prior knowledge of the wingspan of the bird with a camera calibration procedure that needs to be used only once in the lifetime of the system. The system delivers the exact 3D coordinates of the position of the bird at the time of every full wing extension and uses interpolated height estimates to compute the 3D positions of the bird in the video frames between successive wing extensions. The system is inexpensive, compact and portable, and can be easily deployed in the laboratory as well as the field. Caspase-1-driven neutrophil pyroptosis promotes an incomplete NETosis upon Pseudomonas aeruginosa infection Multiple neutrophil death programs contribute to host defense against infections. Although expressing all necessary components, neutrophils specifically fail to undergo pyroptosis, a lytic form of cell death triggered by the activation of the pro-inflammatory complex inflammasome. In the light of the arm race, we hypothesized that intrinsic neutrophil pyroptosis resistance might be bypassed in response to specific microbial species. We show that Pseudomonas aeruginosa (P. aeruginosa) stimulates Caspase-1-dependent pyroptosis in human and murine neutrophils. Mechanistically, activated NLRC4 inflammasome supports Caspase-1-driven Gasdermin-D (GSDMD) activation, IL-1{beta} cytokine release and neutrophil pyroptosis. Furthermore, GSDMD activates Peptidyl Arginine Deaminase-4 which drives an "incomplete NETosis" where neutrophil DNA fills the cell cytosol but fails crossing plasma membrane. Finally, we show that neutrophil Caspase-1 account for IL-1{beta} production and contributes to various P. aeruginosa strains spread in mice. Overall, we demonstrate that neutrophils are fully competent for Caspase-1-dependent pyroptosis, which drives an unsuspected "incomplete NETosis".

SummaryNeutrophils play an essential roles against infections. Although multiple neutrophil death programs contribute to host defense against infections, they fail to undergo pyroptosis, a pro-inflammatory form of cell death. Upon Infections, pyroptosis can be induced in macrophages or epithelial cells upon activation of pro-inflammatory complexes, inflammasomes that trigger Caspase-1-driven Gasdermin dependent plasma membrane lysis. In the light of host-microbe interactions, we hypothesized that yet to find microbial species might hold the capacity to overcome neutrophil resistance to inflammasome-driven pyroptosis. Among several bacterial species, we describe that the bacterium Pseudomonas aeruginosa specifically engages the NLRC4 inflammasome, which promotes Caspase-1-dependent Gasdermin-D activation and subsequent neutrophil pyroptosis. Furthermore, inflammasome-driven pyroptosis leads to DNA decondensation and expansion into the host cell cytosol but not to the so called Neutrophil Extracellular Trap (NET) release as DNA fails breaching the plasma membrane. Finally, in vivo P. aeruginosa infections highlight that Caspase-1-driven neutrophil pyroptosis is functional and is detrimental upon P. aeruginosa infection. Altogether, our results unexpectedly underline neutrophil competence for Caspase-1-dependent pyroptosis, a process that contributes to host susceptibility to P. aeruginosa infection. DNA-controlled Spatio-temporal Patterning of a Cytoskeletal Active Gel Living cells move and change their shape because signaling chemical reactions modify the state of their cytoskeleton; an active gel that converts chemical energy into mechanical forces. To create life-like materials, it is thus key to engineer chemical pathways that drive active gels. Here, we describe the preparation of DNA-responsive surfaces that control the activity of a cytoskeletal active gel comprised of microtubules: a DNA signal triggers the release of molecular motors from the surface into the gel bulk, generating forces that structure the gel. Depending on the DNA sequence and concentration, the gel forms a periodic band pattern or contracts globally. Finally, we show that the structuration of the active gel can be spatially controlled in the presence of a gradient of DNA concentration. We anticipate that such DNA-controlled active matter will contribute to the development of life-like materials with self-shaping properties. IRGM/Irgm1 Aggravates Progression of Atherosclerosis by Inducing Macrophage Apoptosis through the MAPK Signaling Pathway AimsAtherosclerosis underlies most cardiovascular diseases, among which acute coronary syndrome (ACS) caused by plaque rupture (PR) often leads to death. Immune-related GTPases (IRGM/Irgm1) have been extensively studied in inflammatory diseases, but their role in atherosclerosis is unclear. Determining how IRGM/Irgm1 promotes atherosclerotic plaque vulnerability will provide information for new biomarkers and/or therapeutic targets.

Methods and resultsWe identified ruptured and unruptured plaques by optical coherence tomography, and found that serum IRGM was highly expressed in patients with ST-segment elevation myocardial infarction in PR. We used ApoE-/-Irgm1+/+, ApoE-/-Irgm1+/- mice and chimeric mice to establish a model of advanced atherosclerosis. The results of pathological experiments showed that Irgm1 caused plaque necrosis. The ratio of neutral lipids and cholesterol crystals increases, while the content of collagen fibers decreases, aggravating the destabilization of atherosclerotic plaques. In vitro, we used multiple approaches to confirm that Irgm1 promotes macrophage apoptosis by promoting the production of reactive oxygen species and activating the MAPK signaling pathway.

ConclusionsIRGM may be a potential risk factor for PR. Mechanistic studies have shown that IRGM/Irgm1 contributes to the formation and rupture of fragile plaques. This is partly mediated by the induction of macrophage apoptosis via the MAPK signaling pathway. IRGM may offer new strategies for early treatment of ACS.

Translation viewOur findings indicate that IRGM/Irgm1 contributes to formation and rupture of vulnerable plaques. It suggests that IRGM may provide a new target for the early treatment of ACS. From fitting the average to fitting the individual: A cautionary tale for mathematicalmodelers An outstanding challenge in the clinical care of cancer is moving from a one-size-fits-all approach that relies on population-level statistics towards personalized therapeutic design. Mathematical modeling is a powerful tool in treatment personalization, as it allows for the incorporation of patient-specific data so that treatment can be tailor-designed to the individual. Herein, we work with a mathematical model of murine cancer immunotherapy that has been previously-validated against the average of an experimental dataset. We ask the question: what happens if we try to use this same model to perform personalized fits, and therefore make individualized treatment recommendations? Typically, this would be done by choosing a single fitting methodology, and a single cost function, identifying the individualized best-fit parameters, and extrapolating from there to make personalized treatment recommendations. Our analyses show the potentially problematic nature of this approach, as predicted personalized treatment response proved to be sensitive to the fitting methodology utilized. We also demonstrate how a small amount of the right additional experimental measurements could go a long way to improve consistency in personalized fits. Finally, we show how quantifying the robustness of the average response could also help improve confidence in personalized treatment recommendations.

Author summaryAs we enter the era of healthcare where personalized medicine becomes a more common approach to treating cancer patients, harnessing the power of mathematical models will only become more essential. Using a preclinical dataset on cancer immunotherapy, we explore the challenges and limitations that arise when trying to move from fitting and making predictions for the population-level average, to fitting and making predictions for an individual. We find that the standard of approach of picking a single fitting methodology and a single cost function may end up having limited predictive value when applied to individual data. We also show how having a small amount of the right additional experimental data, and establishing the robustness of average treatment response, can help improve confidence in personalized model predictions. New Segmentation and Feature Extraction Algorithm for Classification of White Blood Cells in Peripheral Smear Images This article addresses a new method for the classification of white blood cells (WBCs) using image processing techniques and machine learning methods. The proposed method consists of three steps: detecting the nucleus and cytoplasm, extracting features, and classification. At first, a new algorithm is designed to segment the nucleus. For the cytoplasm to be detected, only a part of it located inside the convex hull of the nucleus is involved in the process. This attitude helps us overcome the difficulties of segmenting the cytoplasm. In the second phase, three shapes and four novel color features are devised and extracted. Finally, by using an SVM model, the WBCs are classified. The segmentation algorithm can detect the nucleus with a dice similarity coefficient of 0.9675. The proposed method can categorize WBCs in Raabin-WBC, LISC, and BCCD datasets with accuracies of 94.65 %, 92.21 %, and 94.20 %, respectively. It is worth mentioning that the hyperparameters of the classifier are fixed only with the Raabin-WBC dataset, and these parameters are not readjusted for LISC and BCCD datasets. The obtained results demonstrate that the proposed method is robust, fast, and accurate. Ultrahigh-Throughput Ambient MS: Direct Analysis at 22 Samples per Second by Infrared Matrix-Assisted Desorption Electrospray Ionization Mass Spectrometry Infrared Matrix-Assisted Laser Desorption Electrospray Ionization (IR-MALDESI) mass spectrometry is an ambient-direct sampling method being developed for high-throughput, label-free, biochemical screening of large-scale compound libraries. Here, we report the development of an ultrahigh-throughput continuous motion IR-MALDESI sampling approach capable of acquiring data at rates up to 22.7 samples per second in a 384-well microtiter plate. At top speed, less than 1% analyte carryover is observed from well-to-well and signal intensity relative standard deviations (RSD) of 11.5% and 20.9% for 3 M 1-hydroxymidazolam and 12 M dextrorphan, respectively, are achieved. The ability to perform parallel kinetics studies on 384 samples with ~30s time resolution using an isocitrate dehydrogenase 1 (IDH1) enzyme assay is shown. Finally, we demonstrate the repeatability and throughput of our approach by measuring 115,200 samples from 300 microtiter plate reads consecutively over 5.54 hours with RSDs under 8.14% for each freshly introduced plate. Taken together, these results demonstrate the use of IR-MALDESI at sample acquisition rates that surpass other currently reported direct sampling mass spectrometry approaches used for high throughput compound screening.

For Table of Contents Only

O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=125 SRC="FIGDIR/small/465730v3_ufig1.gif" ALT="Figure 1">
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org.highwire.dtl.DTLVardef@5f916corg.highwire.dtl.DTLVardef@4473b4org.highwire.dtl.DTLVardef@82e8forg.highwire.dtl.DTLVardef@128b57b_HPS_FORMAT_FIGEXP  M_FIG C_FIG A Hierarchy of Biomolecular Proportional-Integral-Derivative Feedback Controllers for Robust Perfect Adaptation and Dynamic Performance Proportional-Integral-Derivative (PID) feedback controllers have been the most widely used controllers in industry for almost a century due to their good performance, simplicity, and ease of tuning. Motivated by their success in various engineering disciplines, PID controllers recently found their way into synthetic biology, where the design of feedback molecular control systems has been identified as an important goal. In this paper, we consider the mathematical realization of PID controllers via biomolecular interactions. We propose an array of topologies that offer a compromise between simplicity and high performance. We first demonstrate that different Proportional-Integral (PI) controllers exhibit different capabilities for enhancing the dynamics and reducing variance (cell-to-cell variability). Next, we introduce several derivative controllers that are realized based on incoherent feedforward loops acting in a feedback configuration. Alternatively, we show that differentiators can be realized by placing molecular integrators in a negative feedback loop--an arrangement that can then be augmented by PI components to yield PID feedback controllers. We demonstrate that the derivative component can be exploited for enhancing system stability, dramatically increasing the molecular control systems dynamic performance, and for reducing the noise effect on the output of interest. The PID controller features are established through various deterministic and stochastic analyses as well as numerical simulations. Finally, we provide an experimental demonstration using a recently developed hybrid setup, the cyberloop, where the controller is implemented in silico to control a biological genetic circuit in vivo. The large array of novel biomolecular PID controllers introduced here forms a basis for the design and construction of advanced high-performance biomolecular control systems that robustly regulate the dynamics of living systems. Evolutionary rates of testes-expressed genes differ in monogamous and promiscuous Peromyscus species Reproductive proteins, including those expressed in the testes, are among the fastest evolving proteins across the tree of life. Sexual selection on traits involved in sperm competition is thought to be a primary driver of testes gene evolution and is expected to differ between promiscuous and monogamous species due to intense competition between males to fertilize females in promiscuous lineages and lack thereof in monogamous ones. Here, we employ the rodent genus Peromyscus as a model to explore differences in evolutionary rates between testes-expressed genes in monogamous and promiscuous species. We find candidate genes that may be associated with increased sperm production in promiscuous species and gene ontology categories that show patterns of molecular convergence associated with phenotypic convergence in independently evolved monogamous species. Overall, our results highlight the possible molecular consequences of differences in mating system, likely due to differences in selective pressures. Diverse stem-chondrichthyan oral structures and evidence for an independently acquired acanthodid dentition The teeth of sharks famously form a series of transversely-organised files with conveyor-belt replacement that are borne directly on the jaw cartilages, in contrast to the dermal plate-borne dentition of bony fishes that undergoes site-specific replacement. A major obstacle in understanding how this system evolved is the poorly understood relationships of the earliest chondrichthyans and the profusion of morphologically and terminologically diverse bones, cartilages, splints and whorls that they possess. Here we use tomographic methods to investigate mandibular structures in several early branching  acanthodian-grade stem-chondrichthyans. We show that the dentigerous jaw bones of disparate genera of ischnacanthids are united by a common construction, being growing bones with non-shedding dentition. Mandibular splints, which support the ventro-lateral edge of the Meckels cartilage in some taxa, are formed from dermal bone and may be an acanthodid synapomorphy. We demonstrate that the teeth of Acanthodopsis are borne directly on the mandibular cartilage and that this taxon is deeply nested within an edentulous radiation, representing an unexpected independent origin of teeth. Many or even all of the range of unusual oral structures may be apomorphic, but they should nonetheless be considered when building hypotheses of tooth and jaw evolution, both in chondrichthyans and more broadly. RNA splicing analysis using heterogeneous and large RNA-seq datasets The ubiquity of RNA-seq has led to many methods that use RNA-seq data to analyze variations in RNA splicing. However, available methods are not well suited for handling heterogeneous and large datasets. Such datasets scale to thousands of samples across dozens of experimental conditions, exhibit increased variability compared to biological replicates, and involve thousands of unannotated splice variants resulting in increased transcriptome complexity. We describe here a suite of algorithms and tools implemented in the MAJIQ v2 package to address challenges in detection, quantification, and visualization of splicing variations from such datasets. Using both large scale synthetic data and GTEx v8 as benchmark datasets, we demonstrate that the approaches in MAJIQ v2 outperform existing methods. We then apply MAJIQ v2 package to analyze differential splicing across 2,335 samples from 13 brain subregions, demonstrating its ability to offer new insights into brain subregion-specific splicing regulation. Small extracellular vesicles from young mice prevent frailty, improve healthspan and decrease epigenetic age in old mice. Aging is associated with an increased risk of frailty, disability, comorbidities, institutionalization, falls, fractures, hospitalization, and mortality. Searching for strategies to delay the degenerative changes associated with aging and frailty is interesting. We treated old animals intravenously with small extracellular vesicles (sEVs) derived from adipose mesenchymal stem cells (ADSCs) of young animals, and we found an improvement of several functional parameters usually altered with aging, such as motor coordination, grip strength, fatigue resistance, fur regeneration, and renal function. Frailty index analysis showed that 40% of old control mice were frail, whereas none of the old ADSCs-sEVs treated mice were. Molecular and structural benefits in muscle and kidney accompanied this functional improvement. ADSCs-sEVs induced pro-regenerative effects and a decrease in oxidative stress, inflammation, and senescence markers. Moreover, predicted epigenetic age was lower in tissues of old mice treated with ADSCs-sEVs and their metabolome changed to a youth-like pattern. Finally, we gained some insight into the miRNAs contained in sEVs that might be, at least in part, responsible for the effects observed. We propose that young sEVs treatment can be beneficial against frailty and therefore can promote healthy aging.