Miracle-dz/UniFAR-FTUs huggingface dataset:
The transcription factor Rreb1 regulates epithelial architecture and invasiveness in gastrulating mouse embryos

Ras-responsive element-binding protein 1 (Rreb1) is a zinc-finger transcription factor downstream of RAS signaling. Rreb1 has been implicated in cancer but little is known about its role in mammalian non-disease states. Here, we found that Rreb1 is essential for mouse embryonic development. Loss of Rreb1 led to a reduction in the expression of vasculogenesis factors, cardiovascular defects and embryonic lethality. During gastrulation, the absence of Rreb1 also resulted in the upregulation of cytoskeleton-associated genes, a change in the organization of F-ACTIN and adherens junctions within the pluripotent epiblast, and perturbed epithelial architecture characterized by irregular tissue folding and abnormal accumulations of cells. Moreover, Rreb1 mutant cells ectopically exited the epiblast epithelium through the underlying basement membrane, paralleling cell behaviors observed during metastasis. Thus, disentangling the function of Rreb1 in development could shed light on its role in cancer and other diseases involving loss of epithelial integrity.
Synaptic vesicle pools are a major hidden resting metabolic burden of nerve terminals

The human brain is a uniquely vulnerable organ as interruption in fuel supply leads to acute cognitive impairment on rapid time scales. The reasons for this vulnerability are not well understood, but nerve terminals are likely loci of this vulnerability as they do not store sufficient ATP molecules and must synthesize them on-demand during activity or suffer acute degradation in performance. The requirements for on-demand ATP synthesis however depends in part on the magnitude of resting metabolic rates. We show here that, at rest, synaptic vesicle (SV) pools are a major source of presynaptic basal energy consumption. This basal metabolism arises from SV-resident V-ATPases compensating for a hidden resting H+ efflux from the SV lumen. We show that this steady-state H+ efflux is 1) mediated by vesicular neurotransmitter transporters, 2) independent of the SV cycle, 3) accounts for ~half of the resting synaptic energy consumption and 4) contributes to nerve terminal intolerance of fuel deprivation. Nerve terminals consume large amounts of ATP even at rest A large fraction of the resting metabolic burden arises from the V-ATPase Steady-state V-ATPase activity is driven by a synaptic vesicle H+ leak This H+ leak is mediated vesicular neurotransmitter transporters
Thermal acclimation alters the roles of Na+/K+-ATPase activity in a tissue-specific manner in Drosophila melanogaster

Insects, like the model species Drosophila melanogaster, lose neuromuscular function and enter a state of paralysis (chill coma) at a population- and species-specific low temperature threshold that is decreased by cold acclimation. Entry into this coma is related to a spreading depolarization in the central nervous system, while recovery involves restoration of electrochemical gradients across muscle cell membranes. The Na+/K+-ATPase helps maintain ion balance and membrane potential in both the brain and hemolymph (surrounding muscles), and changes in thermal tolerance traits have therefore been hypothesized to be closely linked to variation in the expression and/or activity of this pump in multiple tissues. Here, we tested this hypothesis by measuring activity and thermal sensitivity of the Na+/K+-ATPase at the tagma-specific level (head, thorax and abdomen) in warm-(25°C) and cold-acclimated (15°C) flies by Na+/K+-ATPase activity at 15, 20, and 25°C. We relate differences in pump activity to differences in chill coma temperature, spreading depolarization temperature, and thermal dependence of muscle cell polarization. Differences in pump activity and thermal sensitivity induced by cold acclimation varied in a tissue-specific manner: While cold-acclimated flies had decreased thermal sensitivity of Na+/K+-ATPase that maintains activity at low temperatures in the thorax (mainly muscle), activity instead decreased in the heads (mainly brain). We argue that these changes may assist in maintenance of K+ homeostasis and membrane potential across muscle membranes and discuss how reduced Na+/K+-ATPase activity in the brain may counterintuitively help insects delay coma onset in the cold.
Genetic variation at the species and population levels in the Rocky Mountain ridged mussel (Gonidea angulata)

Freshwater mussels in western North America are threatened by water diversions, climate change, loss of required host fish, and other factors, and have experienced marked decline in the past several decades. All four of the primary lineages (potentially species) of freshwater mussels in the western U.S. and Canada are widespread and have somewhat generalist host fish requirements. Of these lineages, perhaps the most poorly understood and of greatest conservation concern is Gonidea angulata (Rocky Mountain ridged mussel). Gonidea is a monotypic genus occurring only in the western continental U.S. and southern Canada. Here we describe the patterns of genetic variation across the species range, including several populations in the Okanagan Valley at the northern edge of the range. We detected only ten mitochondrial cytochrome oxidase I haplotypes, three of which ere commonly found across major hydrologic basins, and the remainder of which were basin-specific variants. Haplotypes differed by a maximum of 5 of 537 nucleotides. New microsatellite loci were developed for G. angulata as a part of this study. Data from these microsatellite loci indicated that the population in the Chehalis River, Washington, was distinct from other locations, and that the Okanagan lake population was somewhat diverged from the remaining populations in the Columbia River and Klamath Lake. Only low levels of inbreeding were detected, in contrast to previous findings in Margartifera falcata, suggesting that hermaphroditism is not common. The population with the least diversity, according to microsatellite data, was the northernmost known population in Okanagan Lake We discuss the biogeographic and conservation implications of our findings.
Small RNAs couple embryonic developmental programs to gut microbes

Maternal exposure to microbes and other environmental factors is known to induce adaptive changes in the progeny, but little is understood about how development of the progeny is changed. We show that Caenorhabditis elegans undergoes additional embryonic cell divisions in response to maternal gut microbes such as one producing the biopolymer γ-poly-DL-glutamic acid. The divisions coincide with anatomical changes including left-right asymmetric cell alignment, doubling the association between intestinal cells and primordial germ cells, and improved fecundity. The developmental changes are regulated by soma-to-germline transmission of endogenous RNAi and the miR-35 microRNA family, which targets the LIN-23/CDC-25 pathway. Our findings challenge the widespread assumption that C. elegans has an invariant cell lineage that consists of 959 somatic cells and provide insights into how organisms optimize embryogenesis to adapt to environmental changes through epigenetic controls.
Trees and their seed networks: The social dynamics of urban fruit trees and implications for genetic diversity

Trees are a traditional component of urban spaces where they provide ecosystem services critical to urban wellbeing. In the Tropics, urban trees’ seed origins have rarely been characterized. Yet, understanding the social dynamics linked to tree planting is critical given their influence on the distribution of associated genetic diversity. This study examines elements of these dynamics (seed exchange networks) in an emblematic indigenous fruit tree species from Central Africa, the African plum tree (Dacryodes edulis, Burseraceae), within the urban context of Yaoundé. We further evaluate the consequences of these social dynamics on the distribution of the genetic diversity of the species in the city. Urban trees were planted predominantly using seeds sourced from outside the city, resulting in a level of genetic diversity as high in Yaoundé as in a whole region of production of the species. Debating the different drivers that foster the genetic diversity in planted urban trees, the study argued that cities and urban dwellers can unconsciously act as effective guardians of indigenous tree genetic diversity.
CAMP: a Convolutional Attention-based Neural Network for Multifaceted Peptide-protein Interaction Prediction

Peptide-protein interactions (PepPIs) are involved in various fundamental cellular functions and their identification is crucial for designing efficacious peptide therapeutics. To facilitate the peptide drug discovery process, a number of computational methods have been developed to predict peptide-protein interactions. However, most of the existing prediction approaches heavily depend on high-resolution structure data. Although several deep-learning-based frameworks have been proposed to predict compound-protein interactions or protein-protein interactions, few of them are particularly designed to specifically predict peptide-protein interactions. In this paper, We present a sequence-based Convolutional Attention-based neural network for Multifaceted prediction of Peptide-protein interactions, called CAMP, including predicting binary peptide-protein interactions and corresponding binding residues in the peptides. We also construct a benchmark dataset containing high-quality peptide-protein interaction pairs with the corresponding peptide binding residues for model training and evaluation. CAMP incorporates convolution neural network architectures and attention mechanism to fully exploit informative sequence-based features, including secondary structures, physicochemical properties, intrinsic disorder features and position-specific scoring matrix of the protein. Systematical evaluation of our benchmark dataset demonstrates that CAMP outperforms the state-of-the-art baseline methods on binary peptide-protein interaction prediction. In addition, CAMP can successfully identify the binding residues involved non-covalent interactions for peptides. These results indicate that CAMP can serve as a useful tool in peptide-protein interaction prediction and peptide binding site identification, which can thus greatly facilitate the peptide drug discovery process. The source code of CAMP can be found in https://github.com/twopin/CAMP.
A ‘How-to’ Guide for Interpreting Parameters in Resource- and Step-Selection Analyses

Resource-selection and step-selection analyses allow researchers to link animals to their environment and are commonly used to address questions related to wildlife management and conservation efforts. Step-selection analyses that incorporate movement characteristics, referred to as integrated step-selection analyses, are particularly appealing because they allow modeling of both movement and habitat-selection processes. Despite their popularity, many users struggle with interpreting parameters in resource-selection and step-selection functions. Integrated step-selection analyses also require several additional steps to translate model parameters into a full-fledged movement model, and the mathematics supporting this approach can be challenging for biologists to understand. Using simple examples, we demonstrate how weighted distribution theory and the inhomogeneous Poisson point-process model can facilitate parameter interpretation in resource-selection and step-selection analyses. Further, we provide a “how to” guide illustrating the steps required to implement integrated step-selection analyses using the amt package. By providing clear examples with open-source code, we hope to make resource-selection and integrated step-selection analyses more understandable and accessible to end users.
The landscape of autosomal-recessive pathogenic variants in European populations reveals phenotype-specific effects

The number and distribution of recessive alleles in the population for various diseases are not known at genome-wide-scale. Based on 6447 exome-sequences of healthy, genetically-unrelated Europeans of two distinct ancestries, we estimate that every individual is a carrier of at least 2 pathogenic variants in currently known autosomal recessive (AR) genes, and that 0.8-1% of European couples are at-risk of having a child affected with a severe AR genetic disorder. This risk is 16.5-fold higher for first cousins, but is significantly more increased for skeletal disorders and intellectual disabilities due to their distinct genetic architecture.
Deleting Mecp2 from the entire cerebellum rather than its neuronal subtypes causes a delay in motor learning in mice

Rett syndrome is a devastating childhood neurological disorder caused by mutations in MECP2. Of the many symptoms, motor deterioration is a significant problem for patients. In mice, deleting Mecp2 from the cortex or basal ganglia causes motor dysfunction, hypoactivity, and tremor, which are abnormalities observed in patients. However, little is known about the consequences of deleting Mecp2 from the cerebellum, a brain region critical for motor function. Here we show that deleting Mecp2 from the entire cerebellum, but not from individual cerebellar cell types, causes a delay in motor learning that is overcome by additional training. We also observed irregular firing rates of Purkinje cells and transcriptional misregulation within the cerebellum of knockout mice. These findings demonstrate that the motor deficits present in Rett syndrome arise, in part, from cerebellar dysfunction. For Rett syndrome as well as other neurodevelopmental disorders, our results highlight the importance of understanding which brain regions contribute to disease phenotypes.
Extracellular glutamate and GABA transients at the transition from interictal spiking to seizures

Focal epilepsy is associated with intermittent brief population discharges (interictal spikes), which resemble sentinel spikes that often occur at the onset of seizures. Why interictal spikes self-terminate whilst seizures persist and propagate is incompletely understood. We used fluorescent glutamate and GABA sensors in an awake rodent model of neocortical seizures to resolve the spatiotemporal evolution of both neurotransmitters in the extracellular space. Interictal spikes were accompanied by brief glutamate transients which were maximal at the initiation site and rapidly propagated centrifugally. GABA transients lasted longer than glutamate transients and were maximal ∼1.5 mm from the focus where they propagated centripetally. Prior to seizure initiation GABA transients were attenuated, whilst glutamate transients increased, consistent with a progressive failure of local inhibitory restraint. As seizures increased in frequency, there was a gradual increase in the spatial extent of spike-associated glutamate transients associated with interictal spikes. Neurotransmitter imaging thus reveals a progressive collapse of an annulus of feed-forward GABA release, allowing seizures to escape from local inhibitory restraint.
Analysis of the Dynamics and Distribution of SARS-CoV-2 Mutations and its Possible Structural and Functional Implications

After eight months of the pandemic declaration, COVID-19 has not been globally controlled. Several efforts to control SARS-CoV-2 dissemination are still running including vaccines and drug treatments. The effectiveness of these procedures depends, in part, that the regions to which these treatments are directed do not vary considerably. Although, it is known that the mutation rate of SARS-CoV-2 is relatively low it is necessary to monitor the adaptation and evolution of the virus in the different stages of the pandemic. Thus, identification, analysis of the dynamics, and possible functional and structural implication of mutations are relevant. Here, we first estimate the number of COVID-19 cases with a virus with a specific mutation and then calculate its global relative frequency (NRFp). Using this approach in a dataset of 100 924 genomes from GISAID, we identified 41 mutations to be present in viruses in an estimated number of 750 000 global COVID-19 cases (0.03 NRFp). We classified these mutations into three groups: high-frequent, low-frequent non-synonymous, and low-frequent synonymous. Analysis of the dynamics of these mutations by month and continent showed that high-frequent mutations appeared early in the pandemic, all are present in all continents and some of them are almost fixed in the global population. On the other hand, low-frequent mutations (non-synonymous and synonymous) appear late in the pandemic and seems to be at least partially continent-specific. This could be due to that high-frequent mutation appeared early when lockdown policies had not yet been applied and low-frequent mutations appeared after lockdown policies. Thus, preventing global dissemination of them. Finally, we present a brief structural and functional review of the analyzed ORFs and the possible implications of the 25 identified non-synonymous mutations.
Monte Carlo Simulations of the Fast Remagnetization Process in Fept Granular Films

We utilize the Metropolis algorithm to obtain statistical averages of the domain wall length in a FePt granular structure after remagnetization is performed by an ultrashort polarized laser impulse. We propose and check the cluster-size-based order parameter, which along with magnetization, shows the domain wall length, and as a consequence, the average cluster size in the system. We treat the inverse Faraday effect as an external directed magnetic field and show impulse time- and laser power- dependent estimates within the Heisenberg model.
Expression Profiles of Circular RNA in Human Atrial Fibrillation With Valvular Heart Diseases

Circular RNAs (circRNA) are involved in a variety of human heart diseases, however, circRNA expression profiles and circRNA-miRNA-mRNA regulatory network in human atrial fibrillation (AF) especially with valvular heart diseases (VHD) remain poorly understood. A high-throughput RNA sequencing was used to investigate the differentially expressed circRNAs in left atrial appendage from VHD patients with or without persistent AF. The Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were performed to predict the potential functions of the host genes of differentially expressed circRNA and their downstream targets. CircRNA–miRNA-mRNA regulatory network was constructed to identify mechanisms underlying circRNAs. qRT-PCR and sanger sequencing were further performed to validate the results. Compared with sinus rhythm (SR) patients, there were 3094 upregulated and 4472 downregulated circRNAs in AF patients respectively. The expression of 10 most differentially expressed circRNAs (circ 255-ITGA7, circ 418-KCNN2, circ 13913-MIB1, circ 44670-BARD1, circ 44782-LAMA2, circ 81906-RYR2, circ 35880-ANO5, circ 22249-TNNI3K, circ 3136-TNNI3K, circ 56186-TNNI3K) between SR and persistent AF patients were verified by qRT-PCR. In addition, specific back-splicing sites of these circRNAs was confirmed by sanger sequencing. GO and KEGG pathway analysis indicated that cAMP signal pathway and Wnt signal pathway might play important role in the development of AF in VHD patients, which might be affected by circRNAs. This study provided a preliminary landscape of circRNAs expression profiles which are involved in persistent AF due to VHD, and established the possibility for future related researches in this field.
Review of Deep Learning Approaches for the Segmentation of Multiple Sclerosis Lesions on Brain MRI

In recent years, there have been multiple works of literature reviewing methods for automatically segmenting multiple sclerosis (MS) lesions. However, there is no literature systematically and individually review deep learning-based MS lesion segmentation methods. Although the previous review also included methods based on deep learning, there are some methods based on deep learning that they did not review. In addition, their review of deep learning methods did not go deep into the specific categories of Convolutional Neural Network (CNN). They only reviewed these methods in a generalized form, such as supervision strategy, input data handling strategy, etc. This paper presents a systematic review of the literature in automated multiple sclerosis lesion segmentation based on deep learning. Algorithms based on deep learning reviewed are classified into two categories through their CNN style, and their strengths and weaknesses will also be given through our investigation and analysis. We give a quantitative comparison of the methods reviewed through two metrics: Dice Similarity Coefficient (DSC) and Positive Predictive Value (PPV). Finally, the future direction of the application of deep learning in MS lesion segmentation will be discussed.
Concentration Phase Transition in a Two-Dimensional Ferromagnet

The concentration phase transition (CPT) in a two-dimensional ferromagnet was simulated by the Monte Carlo method. The description of the CPT was carried out using various order parameters (OP): magnetic, cluster, and percolation. For comparison with the problem of the geometric (percolation) phase transition, the thermal effect on the spin state was excluded, and thus, CPT was reduced to percolation transition. For each OP, the values of the critical concentration and critical indices of the CPT are calculated.
Salmonella subverts autophagy balancing bacterial fate and cellular inflammation

Salmonella Typhimurium (S. Typhimurium) is an enteric bacterium capable of invading a wide range of host cell types and adopting different intracellular lifestyles for survival. Host endocytic trafficking and autophagy have been implied to regulate the S. Typhimurium subcellular localization and survival. To reveal alternative host regulators on S. Typhimurium lifestyle, we combined a novel fluorescent reporter, Salmonella Intracellular Analyzer (SINA) with haploid forward genetic screening. This identified transcription factor c-MYC as a negative regulator of S. Typhimurium cytosolic lifestyle via stabilizing the Salmonella-containing vacuole (SCV). We further confirmed that c-MYC downstream regulated LC3 acts to maintain SCV stability and limits S. Typhimurium cytosolic lifestyle. We demonstrated that LC3 is recruited to the SCV prior to the endomembrane damage marker Galectin 3, and it regulates SCV stability independent of the autophagosome adaptor NDP52. The LC3 processing enzymes ATG3 and ATG4 reciprocally act on SCV stability, where the loss of LC3-PE conjugation in the absence of ATG3 limits SCV damages. We further identified the dosage-dependent function of the S. Typhimurium effector SopF in mediating SCV stability by actively avoiding LC3 recruitment to the proximity of the SCV to reduce its catastrophic rupture and host cell death. Altogether, we offer insights on the significance of cellular transcription profile in the determination of S. Typhimurium pathophysiology as well as the underlying host-evasion strategy of S. Typhimurium.