Genetic interactions drive heterogeneity in causal variant effect sizes for gene expression and complex traits Despite the growing number of genome-wide association studies (GWAS), it remains unclear to what extent gene-by-gene and gene-by-environment interactions influence complex traits in humans. The magnitude of genetic interactions in complex traits has been difficult to quantify because GWAS are generally underpowered to detect individual interactions of small effect. Here, we develop a method to test for genetic interactions that aggregates information across all trait-associated loci. Specifically, we test whether SNPs in regions of European ancestry shared between European American and admixed African American individuals have the same causal effect sizes. We hypothesize that in African Americans, the presence of genetic interactions will drive the causal effect sizes of SNPs in regions of European ancestry to be more similar to those of SNPs in regions of African ancestry. We apply our method to two traits: gene expression in 296 African Americans and 482 European Americans in the Multi-Ethnic Study of Atherosclerosis (MESA) and low-density lipoprotein cholesterol (LDL-C) in 74K African Americans and 296K European Americans in the Million Veteran Program (MVP). We find significant evidence for genetic interactions in our analysis of gene expression; for LDL-C, we observe a similar point estimate although this is not significant, likely due to lower statistical power. These results suggest that gene-by-gene or gene-by-environment interactions modify the effect sizes of causal variants in human complex traits.
Genome-wide association study of musical beat synchronization demonstrates high polygenicity Moving in synchrony to the beat is a fundamental component of musicality. Here, we conducted a genome-wide association study (GWAS) to identify common genetic variants associated with beat synchronization in 606,825 individuals. Beat synchronization exhibited a highly polygenic architecture, with sixty-nine loci reaching genome-wide significance (p<5x10-8) and SNP-based heritability (on the liability scale) of 13%-16%. Heritability was enriched for genes expressed in brain tissues, and for fetal and adult brain-specific gene regulatory elements, underscoring the role of central nervous system-expressed genes linked to the genetic basis of the trait. We performed validations of the self-report phenotype (through internet-based experiments) and of the GWAS (polygenic scores for beat synchronization were associated with patients algorithmically classified as musicians in medical records of a separate biobank). Genetic correlations with breathing function, motor function, processing speed, and chronotype suggest shared genetic architecture with beat synchronization and provide avenues for new phenotypic and genetic explorations.
On Rank Deficiency in Phenotypic Covariance This paper is concerned with rank deficiency in phenotypic covariance matrices: first to establish it is a problem by measuring it, and then proposing methods to treat for it. Significant rank deficiency can mislead current measures of whole-shape phenotypic integration, because they rely on eigenvalues of the covariance matrix, and highly rank deficient matrices will have a large percentage of meaningless eigenvalues. This paper has three goals. The first is to examine a typical geometric morphometric data set and establish that its covariance matrix is rank deficient. We employ the concept of information, or Shannon, entropy to demonstrate that a sample of dire wolf jaws is highly rank deficient. The different sources of rank deficiency are identified, and include the Generalized Procrustes analysis itself, use of the correlation matrix, insufficient sample size, and phenotypic covariance. Only the last of these is of biological interest.

Our second goal is to examine a test case where a change in integration is known, allowing us to document how rank deficiency affects two measures of whole shape integration (eigenvalue standard deviation and standardized generalized variance). This test case utilizes the dire wolf data set from Part 1, and introduces another population that is 5000 years older. Modularity models are generated and tested for both populations, showing that one population is more integrated than the other. We demonstrate that eigenvalue variance characterizes the integration change incorrectly, while the standardized generalized variance lacks sensitivity. Both metrics are impacted by the inclusion of many small eigenvalues arising from rank deficiency of the covariance matrix. We propose a modification of the standardized generalized variance, again based on information entropy, that considers only the eigenvalues carrying non-redundant information. We demonstrate that this metric is successful in identifying the integration change in the test case.

The third goal of this paper is to generalize the new metric to the case of arbitrary sample size. This is done by normalizing the new metric to the amount of information present in a permuted covariance matrix. We term the resulting metric the  relative dispersion, and it is sample size corrected. As a proof of concept we us the new metric to compare the dire wolf data set from the first part of this paper to a third data set comprising jaws of Smilodon fatalis. We demonstrate that the Smilodon jaw is much more integrated than the dire wolf jaw. Finally, this information entropy-based measures of integration allows comparison of whole shape integration in dense semilandmark environments, allowing characterization of the information content of any given shape, a quantity we term  latent dispersion. 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. Transfer learning framework for cell segmentation with incorporation of geometric features With recent advances in multiplexed imaging and spatial transcriptomic and proteomic technologies, cell segmentation is becoming a crucial step in biomedical image analysis. In recent years, Fully Convolutional Networks (FCN) have achieved great success in nuclei segmentation in in vitro imaging. Nevertheless, it remains challenging to perform similar tasks on in situ tissue images with more cluttered cells of diverse shapes. To address this issue, we propose a novel transfer learning, cell segmentation framework incorporating shape-aware features in a deep learning model, with multi-level watershed and morphological post-processing steps. Our results show that incorporation of geometric features improves generalizability to segmenting cells in in situ tissue images, using solely in vitro images as training data. Ineffectual AEC1 differentiation from KRT8hi transitional state without fibrosis is associated with fatal COVID-19 ARDS ARDS due to COVID-19 and other etiologies results from injury to the alveolar epithelial cell (AEC) barrier resulting in noncardiogenic pulmonary edema, which causes acute respiratory failure; clinical recovery requires epithelial regeneration. During physiologic regeneration in mice, AEC2s proliferate, exit the cell cycle, and transiently assume a transitional state before differentiating into AEC1s; persistence of the transitional state is associated with pulmonary fibrosis in humans. It is unknown whether transitional cells emerge and differentiate into AEC1s without fibrosis in human ARDS and why transitional cells differentiate into AEC1s during physiologic regeneration but persist in fibrosis. We hypothesized that incomplete but ongoing AEC1 differentiation from transitional cells without fibrosis may underlie persistent barrier permeability and fatal acute respiratory failure in ARDS. Immunostaining of postmortem ARDS lungs revealed abundant transitional cells in organized monolayers on alveolar septa without fibrosis. They were typically cuboidal or partially spread, sometimes flat, and occasionally expressed AEC1 markers. Immunostaining and/or interrogation of scRNAseq datasets revealed that transitional cells in mouse models of physiologic regeneration, ARDS, and fibrosis express markers of cell cycle exit but only in fibrosis express a specific senescence marker. Thus, in severe, fatal early ARDS, AEC1 differentiation from transitional cells is incomplete, underlying persistent barrier permeability and respiratory failure, but ongoing without fibrosis; senescence of transitional cells may be associated with pulmonary fibrosis. Deep learning tools and modeling to estimate the temporal expression of cell cycle proteins from 2D still images Automatic characterization of fluorescent labeling in intact mammalian tissues remains a challenge due to the lack of quantifying techniques capable of segregating densely packed nuclei and intricate tissue patterns. Here, we describe a powerful deep learning-based approach that couples remarkably precise nuclear segmentation with quantitation of fluorescent labeling intensity within segmented nuclei, and then apply it to the analysis of cell cycle dependent protein concentration in mouse tissues using 2D fluorescent still images. First, several existing deep learning-based methods were evaluated to accurately segment nuclei using different imaging modalities with a small training dataset. Next, we developed a deep learning-based approach to identify and measure fluorescent labels within segmented nuclei, and created an ImageJ plugin to allow for efficient manual correction of nuclear segmentation and label identification. Lastly, using fluorescence intensity as a readout for protein concentration, a three-step global estimation method was applied to the characterization of the cell cycle dependent expression of E2F proteins in the developing mouse intestine. Environment dependent benefits of inter-individual variation in honey bee recruitment Inter-individual differences in behaviour within the members of a social group can affect the groups productivity. In eusocial insects, individual differences amongst workers in a colony play a central role division of labour and task allocation. Extensive empirical and theoretical work has highlighted variation in response thresholds as a proximate mechanism underlying individual behavioural differences and hence division of labour. However, other response parameters, like response probability and intensity, can affect these differences. In this study, we first extended a previously published agent-based model on honey bee foraging to understand the relative importance of response (dance) probability and response (dance) intensity in the task of recruitment. Comparing variation obtained from the simulations with previously published empirical data, we found that response intensity plays a more important role than probability in producing consistent inter-individual differences in recruitment behaviour. We then explored the benefits provided by this individual variation in recruitment behaviour to the colonys collective foraging effort under different environmental conditions. Our results revealed that individual variation leads to a greater energetic yield per forager, but only when food is abundant. Our study highlights the need to consider all response parameters while studying division of labour and adds to the growing body of evidence linking individual variation in behavioural responses to the success of social groups. Chemomechanically voxelated niches for programmable histogenesis Stem-cell derived tissue models are commonly cultured under globally-delivered stimuli that trigger histogenesis via self-organizing activity. However, the culture of such tissue models is prone to stochastic behavior, limiting the reproducibility of cellular composition and resulting in non-physiological architectures. To overcome these shortcomings, we developed a method for printing cell niche microenvironments with microstructured cues that mediate local histogenic processes, including mechanosensing and differentiation of selected cell types. Microstructured cues include independently tunable mechano-chemical properties, with conjugated peptides, proteins, and morphogens across a range of Youngs moduli. By rationally designing niches, we mediate the structure of tissues derived from stem-cell-progenitor sources, including a bone-fat assembly from stromal mesenchyme, and embryonic tissues derived from hiPSC. We show that microstructured cues can recapitulate mechano-chemical signals resembling early embryonic histogenesis. This outcome includes a role for niche mechanics in human embryonic organization, where soft niche mechanics bias markers of mesendodermal differentiation and epithelial-to-mesenchymal-transition (EMT), as well as a demonstration of a material-mediated morphogen signaling centers able to induce foci of mesenchymal and EMT differentiation. Thus, microstructured materials can mediate local histogenic processes to enhance the structure and composition of tissue models. Comparing genome-based estimates of relatedness for use in pedigree-based conservation management Researchers have long debated which estimator of relatedness best captures the degree of relationship between two individuals. In the genomics era, this debate continues, with relatedness estimates being sensitive to the methods used to generate markers, marker quality, and levels of diversity in sampled individuals. Here, we compare six commonly used genome-based relatedness estimators (kinship genetic distance (KGD), Wang Maximum Likelihood (TrioML), Queller and Goodnight (Rxy), Kinship INference for Genome-wide association studies (KING-robust), and Pairwise Relatedness (RAB), allele-sharing co-ancestry (AS)) across five species bred in captivity-including three birds and two mammals-with varying degrees of reliable pedigree data, using reduced-representation and whole genome resequencing data. Genome-based relatedness estimates varied widely across estimators, sequencing methods, and species, yet the most consistent results for known first order relationships were found using Rxy, RAB, and AS. However, AS was found to be less consistently correlated with known pedigree relatedness than either Rxy or RAB. Our combined results indicate there is not a single genome-based estimator that is ideal across different species and data types. To determine the most appropriate genome-based relatedness estimator for each new dataset, we recommend assessing the relative: (1) correlation of candidate estimators with known relationships in the pedigree and (2) precision of candidate estimators with known first-order relationships. These recommendations are broadly applicable to conservation breeding programs, particularly where genome-based estimates of relatedness can complement and complete poorly pedigreed populations. Given a growing interest in the application of wild pedigrees, our results and are also applicable to in-situ wildlife management. TAK1 blockade as a therapy for retinal neovascularization Retinal neovascularization, or pathological angiogenesis in the retina, is a leading cause of blindness in developed countries. Transforming growth factor-{beta}-activated kinase 1 (TAK1) is a mitogen-activated protein kinase kinase kinase (MAPKKK) activated by TGF-{beta}1 and other pro-inflammatory cytokines. TAK1 is also a key mediator of inflammation, innate immune responses, apoptosis and tissue homeostasis and plays an important role in physiological angiogenesis. Its role in pathological angiogenesis, particularly in retinal neovascularization, remains unclear. We investigated the regulatory role of TAK1 in pathological angiogenesis in the retina. Transcriptome analysis of human retina featuring retinal neovascularization revealed enrichment of known TAK1-mediated signaling pathways. Selective inhibition of TAK1 activation by 5Z-7-oxozeaenol attenuated aberrant retinal angiogenesis in rats following oxygen-induced retinopathy. Transcriptome profiling revealed that TAK1 activation in human microvascular endothelial cells under TNF stimulation led to increase the gene expression related to cytokines and leukocyte-endothelial interaction, mainly through nuclear factor kappa B (NF{kappa}B) signaling pathways. These results reveal that inhibition of TAK1 signaling may have therapeutic value for the treatment of pathological angiogenesis in the retina. Exploitation of the genetic variability in the genotype of Egyptian Wheat by studding Molecular Markers, Molecular Docking and Nano Composites. Regulation of leaf and stem rust This manuscript has been withdrawn by the authors as it was submitted and made public without the full consent of all the authors. Therefore, the authors do not wish this work to be cited as reference for the project. If you have any questions, please contact the corresponding author. Herbivore life histories are altered by drought stress in their hosts plants Drought associated with climate change can stress plants, altering their interactions with phytophagous arthropods. Dryness not only impacts cultivated plants but also their parasites, which in some cases are favoured by drought. Herbivorous arthropods feeding on drought-stressed plants typically produce bigger offspring and develop faster. However, how much responses to abiotic factors differ among populations of a species remains poorly documented. Here, we evaluate variability among populations of a major agricultural pest, the two spotted spider mite, Tetranychus urticae, in response to drought-stress. We compare key life-history parameters of twelve populations that originate from climates ranging from wet and cool Atlantic locations to medium to dry hot Mediterranean locations. We evaluated how plant drought stress affects four life history traits: development time, fecundity, sex-ratio and emigration rate in an experiment comparing well-watered and drought-stressed bean plants. Mites feeding on drought-stressed plants developed faster and attempted to leave leaves less often, and young females were more fecund. The mites from wet temperate climates exhibited greater plasticity between the two water regimes than mites originating from dryer and hot climates. Thus, climate in the area of origin influences mite response to drought. An RNA-based feed-forward mechanism ensures motor switching in oskar mRNA transport Regulated recruitment and activity of motor proteins is essential for intracellular transport of cargoes, including ribonucleoprotein complexes (RNP). Here we show that orchestration of oskar RNP transport in the Drosophila germline relies on the interplay of two double-stranded RNA binding proteins, Staufen and the dynein adaptor Egalitarian (Egl). Following delivery of nurse cell-synthesized oskar mRNA into the oocyte by dynein, enhanced recruitment of Staufen to the RNPs results in dissociation of Egl and reduced minus end-directed transport without overtly affecting overall dynein levels on the cargo. This mechanism allows kinesin-1 to translocate the mRNA to its final destination at the posterior pole of the oocyte. Using in vitro motility assays with purified components, we find that Staufen directly antagonizes Egl-mediated activation of oskar mRNA transport by dynein. We additionally show that Egl associates with staufen mRNA in the nurse cells and mediates enrichment of the mRNA and its protein product in the ooplasm. Our observations identify a feed-forward mechanism, whereby dynein-dependent accumulation of staufen mRNA and protein in the oocyte enables motor switching during oskar mRNA transport by downregulating dynein activity. Force correction analysis method for derivation of multidimensional free energy landscapes from adaptively-biased replica simulations A methodology is proposed for the calculation of multidimensional free-energy landscapes of molecular systems, based on analysis of multiple Molecular Dynamics trajectories wherein adaptive biases have been applied to enhance the sampling of different collective variables. In this approach, which we refer to as Force Correction Analysis Method (FCAM), local averages of the total and biasing forces are evaluated post-hoc, and the latter are subtracted from the former to obtain unbiased estimates of the mean force across collective-variable space. Multidimensional free-energy surfaces and minimum free-energy pathways are then derived from integration of the mean force landscape through kinetic Monte Carlo algorithm. To evaluate the proposed method, a series of numerical tests and comparisons with existing approaches were carried out for small molecules, peptides, and proteins, based on all-atom trajectories generated with standard, concurrent and replica-exchange Metadynamics in collective-variable spaces ranging from one- to six-dimensional. The tests confirm the correctness of the FCAM formulation and demonstrate that calculated mean forces and free energies converge rapidly and accurately, outperforming other methods used to unbias this kind of simulation data.



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C_FIG A diagnostic primer pair to distinguish between wMel and wAlbB Wolbachia infection - A simplified real-time PCR approach for use in field collected Aedes aegypti in dengue reduction trials Detection of the Wolbachia endosymbiont in Aedes aegypti mosquitoes through real-time PCR assays is widely used during and after Wolbachia releases in dengue reduction trials involving the wMel and wAlbB strains. However, primers applied in current successful Wolbachia releases cannot be used in a single assay to distinguish between these strains. Here, we developed a new diagnostic primer pair wMA which can detect wMel or wAlbB infection in the same assay. We also tested current Wolbachia primers and show that there is variation in their performance when they are used to assess the relative density of Wolbachia. The new wMA primers provide an accurate and efficient estimate of the presence and density of both Wolbachia infections. Early functional mismatch between breast cancer cells and their tumour microenvironment suppresses long term growth Cancer cells thrive embedded in a fine-tuned cellular and extracellular environment or tumour microenvironment (TME). There is a general understanding of a co-evolution between cancer cells and their surrounding TME, pointing at a functional connection between cancer cells characteristics and the perturbations induced in their surrounding tissue. However, whether this functional connection needs to be set from the start or if aggressive cancer cells can always be dominating their microenvironment has never been formally proven with a dedicated experimental setting where malignant cells can be challenged to grow in a different TME from the one they would naturally create. Here we generated an experimental setting where we transiently perturb the secretory profile of aggressive breast cancer cells without affecting their intrinsic growth ability. This led to the initial establishment of an atypical TME. Interestingly, even if initially tumours are formed, this atypical TME evolves to impair long term in vivo cancer growth. Using a combination of in vivo transcriptomics, protein arrays and in vitro co-cultures, we found that the atypical TME culminates in the infiltration of macrophages with STAT1high activity. These macrophages show strong anti-tumoural functions which reduce long-term tumour growth, despite lacking canonical M1 markers. Importantly, gene signatures of the mesenchymal compartment of the TME, as well as the anti-tumoural macrophages show striking prognostic power-correlating with less aggressive human breast cancers. Is Pisum sativum a good model species for the study of root responses to neighbours and barriers in soil? A bayesian hierarchical meta-analysis Plant-plant competition is ubiquitous in nature. However, studying below ground behaviour of roots has always posed certain difficulties. Pea (Pisum sativum L.) has become a sort of model species for ecological studies about how plant roots respond to neighbouring plant roots and barriers in soil. However, published results point in several different directions. This has sometimes been interpreted as pea having sophisticated context dependent responses that can change in complex ways depending on its surroundings. To explore this further, here, we combine the result of five new experiments with published results to examine 18 unique experiments from 7 different studies for a total of 254 replicates. We used a Bayesian hierarchical meta-analysis approach to estimating the likely effect size from the available data, as well as quantify heterogeneity among different experiments, studies and cultivars. The posterior distributions show that, at the coarsest possible scale of total root production, it is unlikely that P. sativum root growth is influenced by either neighbours or barriers to root growth imposed by the walls of pots that vary in volume. We suggest that further work should consider repeating experiments that reported finer scale root plasticity in pea at the rhizosphere scale, and also consider alternative model species for the study of plant root responses to external cues. Creation of a single cell RNA seq meta-atlas to define human liver immune homeostasis The liver is unique in both its ability to maintain immune homeostasis and in its potential for immune tolerance following solid organ transplantation. Single-cell RNA sequencing (scRNA seq) is a powerful approach to generate highly dimensional transcriptome data to understand cellular phenotypes. However, when scRNA data is produced by different groups, with different data models, different standards, and samples processed in different ways, it can be challenging to draw meaningful conclusions from the aggregated data. The goal of this study was to establish a method to combine  human liver scRNA seq datasets by 1) characterizing the heterogeneity between studies and 2) using the meta-atlas to define the dominant phenotypes across immune cell subpopulations in healthy human liver. Publicly available scRNA seq data generated from liver samples obtained from a combined total of 17 patients and [~]32,000 cells were analyzed. Liver-specific immune cells (CD45+) were extracted from each dataset, and immune cell subpopulations (myeloid cells, NK and T cells, plasma cells, and B cells) were examined using dimensionality reduction (UMAP), differential gene expression, and ingenuity pathway analysis. All datasets co-clustered, but cell proportions differed between studies. Gene expression correlation demonstrated similarity across all studies, and canonical pathways that differed between datasets were related to cell stress and oxidative phosphorylation rather than immune-related function. Next, a meta-atlas was generated via data integration and compared against PBMC data to define gene signatures for each hepatic immune subpopulation. This analysis defined key features of hepatic immune homeostasis, with decreased expression across immunologic pathways and enhancement of pathways involved with cell death. This method for meta-analysis of scRNA seq data provides a novel approach to broadly define the features of human liver immune homeostasis. Specific pathways and cellular phenotypes described in this human liver immune meta-atlas provide a critical reference point for further study of immune mediated disease processes within the liver. Mouse lemur, a new primate model to investigate cardiac pacemaker activity. BackgroundGray mouse lemurs (Microcebus murinus) are one of the smallest and most ancestral primates known. Their size falls in between that of mice and rats, and their genetic proximity to humans makes them an emerging model to study age-related neurodegeneration. Since Microcebus murinus replicates similar senescence processes of humans, it constitutes a useful model also for studying cardiovascular dysfunctions. However, its cardiac physiology is unknown. Thus, we investigated sinoatrial node (SAN) pacemaker activity of mouse lemurs, presenting the first characterization of heart automaticity in nonhuman primates.

Methods and ResultsWe recorded the heart automaticity in freely moving mouse lemurs and in their SAN tissues and pacemaker myocytes. Mouse lemurs have a heart rate (HR) in between those of mice and rats and a similar generation of electrical impulses in the SAN tissue. Conversely, their ventricular depolarization is more similar to large mammals. Mouse lemur SAN myocytes express the main pacemaker currents at densities similar to mice: the hyperpolarization-activated current (If) and the L-type (ICa,L) and T-type (ICa,T) calcium currents. Moreover, mouse lemur SAN myocytes display spontaneous ryanodine receptor (RyR)-dependent Ca2+ transients. Using muscle-derived stem cells (MDSCs) from the Microcebus murinus skeletal muscle, we also differentiated pacemaker-like (PML) cells showing spontaneous automaticity and expressing markers of native SAN myocytes (HCN4 and connexin-45).

ConclusionsIn conclusion, our characterization of heart automaticity in Microcebus murinus provides new opportunities for comparative cardio-physiology studies in primates and with humans, and for pharmacologic testing of molecules that could assist in modulating age-related dysfunctions of automaticity. Plant biomechanics and resilience to environmental changes are controlled by specific lignin chemistries in each vascular cell type and morphotype The biopolymer lignin, deposited in the cell walls of vascular cells, is essential for long-distance water conduction and structural support of plants. Independently of the species, each different vascular cell type contains a conserved lignin chemistry with specific aromatic and aliphatic substitutions. Yet, the biological role of this conserved and specific lignin chemistry for each cell type remained unclear. Herein, we investigate the role of specific lignin chemistries for cellular function by producing single cell analyses on vascular cell morphotypes, all enabling sap conduction but differing in morphology. We found that specific lignin chemistries accumulate in each morphotype. Moreover, lignin accumulates dynamically, increasing in quantity and changing composition, to alter the cell wall biomechanics of each morphotype during their maturation. For similar aromatic substitution, residues with alcohol aliphatic functions increased stiffness whereas aldehydes increased flexibility. Modifying this specific lignin chemistry impairs the cell wall biomechanics of each morphotype and consequently reduces their capacity to optimally conduct water in normal conditions, and to recover from drought. Altogether, lignin chemistry is differently controlled for each sap conducting cell types during their maturation to dynamically adjust their biomechanics and hydraulic properties to adapt to developmental and environmental constraints. Here's the twist: How the brain updates the representations of naturalistic events as our understanding of the past changes The brain actively reshapes our understanding of past events in light of new incoming information. In the current study, we ask how the brain supports this updating process during the encoding and recall of naturalistic stimuli. One group of participants watched a movie ("The Sixth Sense") with a cinematic "twist" at the end that dramatically changed the interpretation of previous events. Next, participants were asked to verbally recall the movie events, taking into account the new "twist" information. Most participants updated their recall to incorporate the twist. Two additional groups recalled the movie without having to update their memories during recall: one group never saw the twist; another group was exposed to the twist prior to the beginning of the movie, and thus the twist information was incorporated both during encoding and recall. We found that providing participants with information about the twist beforehand altered neural response patterns during movie-viewing in the default mode network (DMN). Moreover, presenting participants with the twist at the end of the movie changed the neural representation of the previously-encoded information during recall in a subset of DMN regions. Further evidence for this transformation was obtained by comparing the neural activation patterns during encoding and recall and correlating them with behavioral signatures of memory updating. Our results demonstrate that neural representations of past events encoded in the DMN are dynamically integrated with new information that reshapes our understanding in natural contexts. Actomyosin activity-dependent apical targeting of Rab11 vesicles reinforces apical constriction During tissue morphogenesis, cell shape changes resulting from cell-generated forces often require active regulation of intracellular trafficking. How mechanical stimuli influence intracellular trafficking and how such regulation impacts tissue mechanics are not fully understood. In this study, we identify an actomyosin dependent mechanism involving Rab11- mediated trafficking in regulating apical constriction in the Drosophila embryo. During Drosophila mesoderm invagination, apical actin and Myosin II (actomyosin) contractility induces apical accumulation of Rab11-marked vesicle-like structures ("Rab11 vesicles") by promoting a directional bias in dynein mediated vesicle transport. At the apical domain, Rab11 vesicles are enriched near the adherens junctions (AJs). The apical accumulation of Rab11 vesicles is essential to prevent fragmented apical AJs, breaks in the supracellular actomyosin network and a reduction in the apical constriction rate. This Rab11 function is separate from its role in promoting apical Myosin II accumulation. These findings suggest a feedback mechanism between actomyosin activity and Rab11-mediated intracellular trafficking that regulates the force generation machinery during tissue folding. Comparison of hybrid learning and remote education in the implementation of the 'Adopt a Microorganism' methodology The Internet has changed the way teachers and students access information and build knowledge. The recent COVID-19 pandemic has created challenges for both teachers and students and a demand for new methodologies of remote learning. In the life sciences, mixing online content with practical activities represents an even greater challenge. In microbiology, the implementation of an active teaching methodology, the #Adopt project, based on the social network Facebook(R), represents an excellent option for connecting remote education with classroom activities. In 2020, the version applied in high school, "Adopt a Microorganism", was adapted to meet the demands of emergency remote education owing to the suppression of face-to-face activities caused by the pandemic. In the present study, we assessed how the change in methodology impacted the discourse richness of students from high school integrated with technical education in the Business Administration program of the Federal Institute of Sao Paulo, Sorocaba Campus. Three questionnaires related to the groups of microorganisms (Archaea, Bacteria, Virus, Fungi, and Protozoan) were applied. The students responses in the 2019 and 2020 classes were compared concerning content richness and multiplicity of concepts through the application of the Shannon diversity index, an approach that is generally used to assess biodiversity in different environments. The observed results suggest that remote learning provided students with a conceptual basis and richness of content equivalent to that achieved by students subjected to the hybrid teaching model. In conclusion, this study suggests that the #Adopt project methodology increases students discourse richness in microbiology even without face-to-face traditional classes. 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. Multi-omics investigation of tacrolimus nephrotoxicity BackgroundTacrolimus, an immunosuppressive drug prescribed to a majority of transplanted patients is nephrotoxic, through still unclear mechanisms. This study aims to evaluate the impact of tacrolimus on a lineage of proximal tubular cells using a multi-omics approach.

MethodsLLC-PK1 cells were exposed to 5 M of tacrolimus for 24h. Intracellular proteins and metabolites, and extracellular metabolites were extracted and analysed by LC-MS/MS. The transcriptional expression of the dysregulated proteins PCK-1, FBP1 and FBP2 was measured using RT-qPCR.

ResultsIn our cell model, tacrolimus impacted different metabolic pathways including those of arginine (e.g., citrulline, ornithine) (p < 0.0001), amino acids (e.g., valine, isoleucine, aspartic acid) (p < 0.0001) and pyrimidine (p<0.01). In addition, it induced oxidative stress (p < 0.01) as shown by a decrease in total cell glutathione quantity. It impacted cell energy through an increase in Krebs cycle intermediates (e.g., citrate, aconitate, fumarate) (p < 0.01) and down-regulation of PCK-1 (p < 0.05) and FPB1 (p < 0.01), which are key enzymes in gluconeogenesis. Apart from glucose synthesis, gluconeogenesis is an important process in kidney mediated acid-base balance control.

ConclusionThe variations found using this multi-omics approach clearly point towards a dysregulation of energy production in epithelial cells of the renal tubule, and potentially of their functions, that may be implicated in tacrolimus nephrotoxicity in the clinics.