Miracle-dz/UniFAR-FTUs huggingface dataset:
Role of an Atypical Cadherin Gene, Cdh23 in Prepulse Inhibition and Implication of CDH23 in Schizophrenia

We previously identified quantitative trait loci (QTL) for prepulse inhibition (PPI), an endophenotype of schizophrenia, on mouse chromosome 10 and reported Fabp7 as a candidate gene from an analysis of F2 mice from inbred strains with high (C57BL/6N; B6) and low (C3H/HeN; C3H) PPI levels. Here, we reanalyzed the previously reported QTLs with increased marker density. The highest LOD score (26.66) peaked at a synonymous coding and splice-site variant, c.753G>A (rs257098870), in the Cdh23 gene on chromosome 10; the c.753G (C3H) allele showed a PPI-lowering effect. Bayesian multiple QTL mapping also supported the same variant with a posterior probability of 1. Thus, we engineered the c.753G (C3H) allele into the B6 genetic background, which led to dampened PPI. We also revealed an e-QTL (expression-QTL) effect imparted by the c.753G>A variant for the Cdh23 expression in the brain. In a human study, a homologous variant (c.753G>A; rs769896655) in CDH23 showed a nominally significant enrichment in individuals with schizophrenia. We also identified multiple potentially deleterious CDH23 variants in individuals with schizophrenia. Collectively, the present study reveals a PPI-regulating Cdh23 variant and a possible contribution of CDH23 to schizophrenia susceptibility.
Value Shapes Abstraction During Learning

Abstractions are critical for flexible behaviours and efficient learning. However, how the brain forgoes the sensory dimension to forge abstract entities remains elusive. Here, in two fMRI experiments, we demonstrate a mechanism of abstraction built upon valuation of task-relevant sensory features. Human volunteers learned hidden association rules between visual features. Computational modelling of participants’ choice data with mixture-of-experts reinforcement learning algorithms revealed that, with learning, emerging high-value abstract representations increasingly guided behaviour. Moreover, the brain area encoding value signals - the ventromedial prefrontal cortex - also prioritized and selected latent task elements, both locally and through its connection to visual cortex. In a second experiment, we used multivoxel neural reinforcement to show how reward-tagging the neural sensory representation of a task’s feature evoked abstraction-based decisions. Our findings redefine the logic of valuation as a goal-dependent, key factor in constructing the abstract representations that govern intelligent behaviour.
CLOCK/BMAL1 interferes with segmentation clock oscillation in mouse embryonic organoids

In the mammalian developmental process, the segmentation clock and circadian clock appear sequentially in the embryo. However, there is no clear information about the biological significance of the mutual exclusiveness of these rhythms. Here we show that excess of the circadian components CLOCK/BMAL1 in mouse embryonic organoids, induced presomitic mesoderm and gastruloids, disrupts the Hes7 ultradian rhythm and somitogenesis. RNA sequencing analysis showed that CLOCK/BMAL1 activates the signaling pathways regulating Hes7. After establishment of the circadian clock, the expression of endogenous Hes7 and another segmentation clock gene, Lfng, tended to fluctuate with a circadian period, implying that the circadian clock potentially interferes with the segmentation clock. These results suggest that strict timing regulation of the emergence of circadian clock oscillation is essential for mammalian development. Competing Interest Statement The authors have declared no competing interest.
Structure of nonstructural protein 1 from SARS-CoV-2.

The periodic emergence of novel coronaviruses (CoVs) represents an ongoing public health concern with significant health and financial burden worldwide. The most recent occurrence originated in the city of Wuhan, China where a novel coronavirus (SARS-CoV-2) emerged causing severe respiratory illness and pneumonia. The continual emergence of novel coronaviruses underscores the importance of developing effective vaccines as well as novel therapeutic options that target either viral functions or host factors recruited to support coronavirus replication. The CoV nonstructural protein 1 (nsp1) has been shown to promote cellular mRNA degradation, block host cell translation, and inhibit the innate immune response to virus infection. Interestingly, deletion of the nsp1-coding region in infectious clones prevented the virus from productively infecting cultured cells. Because of nsp1’s importance in the CoV lifecycle, it has been highlighted as a viable target for both antiviral therapy and vaccine development. However, the fundamental molecular and structural mechanisms that underlie nsp1 function remain poorly understood, despite its critical role in the viral lifecycle. Here we report the high-resolution crystal structure of the amino, globular portion of SARS-CoV-2 nsp1 (residues 10 – 127) at 1. 77Å resolution. A comparison of our structure with the SARS-CoV-1 nsp1 structure reveals how mutations alter the conformation of flexible loops, inducing the formation of novel secondary structural elements and new surface features. Paired with the recently published structure of the carboxyl end of nsp1 (residues 148 – 180), our results provide the groundwork for future studies focusing on SARS-CoV-2 nsp1 structure and function during the viral lifecycle. IMPORTANCE The Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is the causative agent for the COVID-19 pandemic. One protein known to play a critical role in the coronavirus lifecycle is nonstructural protein1 (nsp1). As such, it has been highlighted in numerous studies as a target for both the development of antivirals and for the design of live-attenuated vaccines. Here we report the high-resolution crystal structure of nsp1 derived from SARS-CoV-2 at 1. 77Å resolution. This structure will facilitate future studies focusing on understanding the relationship between structure and function for nsp1. In turn, understanding these structure-function relationships will allow nsp1 to be fully exploited as a target for both antiviral development and vaccine design.
Putting Randomized Compiler Testing into Production (Artifact)

We describe our experience over the last 18 months on a compiler testing technology transfer project: taking the GraphicsFuzz research project on randomized metamorphic testing of graphics shader compilers, and building the necessary tooling around it to provide a highly automated process for improving the Khronos Vulkan Conformance Test Suite (CTS) with test cases that expose fuzzer-found compiler bugs, or that plug gaps in test coverage. We present this tooling for test automation – gfauto – in detail, as well as our use of diﬀerential coverage and test case reduction as a method for automatically synthesizing tests that ﬁll coverage gaps. We explain the value that GraphicsFuzz has provided in automatically testing the ecosystem of tools for transforming, optimizing and validating Vulkan shaders, and the challenges faced when testing a tool ecosystem rather than a single tool. We discuss practical issues associated with putting automated metamorphic testing into production, related to test case validity, bug de-duplication and ﬂoating-point precision, and provide illustrative examples of bugs found during our work.
The unbiased estimation of the fraction of variance explained by a model

The correlation coefficient squared, r2, is often used to validate quantitative models on neural data. Yet it is biased by trial-to-trial variability: as trial-to-trial variability increases, measured correlation to a model’s predictions decreases; therefore, models that perfectly explain neural tuning can appear to perform poorly. Many solutions to this problem have been proposed, but some prior methods overestimate model fit, the utility of even the best performing methods is limited by the lack of confidence intervals and asymptotic analysis, and no consensus has been reached on which is the least biased estimator. We provide a new estimator, , that outperforms all prior estimators in our testing, and we provide confidence intervals and asymptotic guarantees. We apply our estimator to a variety of neural data to validate its utility. We find that neural noise is often so great that confidence intervals of the estimator cover the entire possible range of values ([0, 1]), preventing meaningful evaluation of the quality of a model’s predictions. We demonstrate the use of the signal-to-noise ratio (SNR) as a quality metric for making quantitative comparisons across neural recordings. Analyzing a variety of neural data sets, we find ~ 40% or less of some neural recordings do not pass even a liberal SNR criterion. Author Summary Quantifying the similarity between a model and noisy data is fundamental to the verification of advances in scientific understanding of biological phenomena, and it is particularly relevant to modeling neuronal responses. A ubiquitous metric of similarity is the correlation coefficient. Here we point out how the correlation coefficient depends on a variety of factors that are irrelevant to the similarity between a model and data. While neuroscientists have recognized this problem and proposed corrected methods, no consensus has been reached as to which are effective. Prior methods have wide variation in their precision, and even the most successful methods lack confidence intervals, leaving uncertainty about the reliability of any particular estimate. We address these issues by developing a new estimator along with an associated confidence interval that outperforms all prior methods.
Differential response of macrophages and neutrophils to trypanosome infections in zebrafish: occurrence of foamy macrophages

A tightly regulated innate immune response to trypanosome infections is critical to strike a balance between parasite control and inflammation-associated pathology. In the present study, we make use of the recently established Trypanosoma carassii infection model in larval zebrafish to study the early response of macrophages and neutrophils to trypanosome infections in vivo. We consistently identified high- and low-infected individuals and were able to simultaneously characterize their differential innate response. Not only did macrophage and neutrophil number and distribution differ between the two groups, but also macrophage morphology and activation state. Exclusive to high-infected zebrafish, was the appearance of macrophages rich in lipid droplets, confirmed to be foamy macrophages and characterized by a strong pro-inflammatory profile. Altogether, we provide an in vivo characterization of the differential response of macrophage and neutrophil to trypanosome infection and identify foamy macrophages as potentially associated with an exacerbated immune response and susceptibility to the infection. To our knowledge this is the first report of the occurrence of foamy macrophages during an extracellular trypanosome infection.
Disentangling cause and consequence: Genetic dissection of the DANGEROUS MIX2 risk locus, and activation of the DM2h NLR in autoimmunity

Nucleotide-binding domain–leucine-rich repeat-type immune receptors (NLRs) protect plants against pathogenic microbes through intracellular detection of effector proteins. However, this comes at a cost, as NLRs can also induce detrimental autoimmunity in genetic interactions with foreign alleles. This may occur when independently evolved genomes are combined in inter- or intraspecific crosses, or when foreign alleles are introduced by mutagenesis or transgenesis. Most autoimmunity-inducing NLRs are encoded within highly variable NLR gene clusters with no known immune functions, which were termed autoimmune risk loci. Whether risk NLRs differ from sensor NLRs operating in natural pathogen resistance and how risk NLRs are activated in autoimmunity is unknown. Here, we analyzed the DANGEROUS MIX2 risk locus, a major autoimmunity hotspot in Arabidopsis thaliana. By gene editing and heterologous expression, we show that a single gene, DM2h, is necessary and sufficient for autoimmune induction in three independent cases of autoimmunity in accession Landsberg erecta. We focus on autoimmunity provoked by an EDS1-YFPNLS fusion protein to functionally characterize DM2h and determine features of EDS1-YFPNLS activating the immune receptor. Our data suggest that risk NLRs function reminiscent of sensor NLRs, while autoimmunity-inducing properties of EDS1-YFPNLS are in this context unrelated to the protein’s functions as immune regulator. We propose that autoimmunity may, at least in some cases, be caused by spurious, stochastic interactions of foreign alleles with co-incidentally matching risk NLRs.
Adaptive drought tolerance during germination of Salsola drummondii seeds from saline and nonsaline habitats of the arid Arabian deserts

The effects of temperature, light, salinity, and drought on germination of halophytes have been extensively studied. However, few studies have focused on the germination of plants that grow well in both saline and nonsaline habitats (i.e., habitat-indifferent halophytes). Here, we assess the impacts of population origin, temperature, and light on drought tolerance, as simulated with polyethylene glycol (PEG), during germination of Salsola drummondii Ulbr. , a habitat-indifferent halophyte from the arid Arabian deserts. Seeds were collected from both saline and nonsaline habitats and germinated at six concentrations of PEG at three temperatures and two light regimes. An increase in the concentration of PEG resulted in a significant reduction in seed germination, especially at higher temperatures. Seeds from the nonsaline habitat attained significantly greater germination efficiency at concentrations of PEG up to –1.2 MPa, but there was no difference in germination of seeds between the two habitats at concentrations of –1.5 MPa. Seeds from the saline habitat germinated significantly faster at higher concentrations of PEG. Germination was significantly higher in darkness than in light at –1.5 MPa at the lower temperatures, but the opposite was true for the higher temperatures. Seeds from saline habitats had higher levels of dormancy and faster rates of germination at higher concentrations of PEG because of their adaptation to low osmotic potentials.
Density responses of lesser-studied carnivores to habitat and management strategies in southern Tanzania’s Ruaha-Rungwa landscape

Compared to emblematic large carnivores, less charismatic or smaller carnivore species often receive little conservation attention, despite facing increasing anthropogenic pressure, and their status being poorly understood across much of their range. We employed systematic camera trapping and spatially explicit capture-recapture modelling to estimate variation in population density of serval, striped hyaena and aardwolf across the mixed-use Ruaha-Rungwa landscape in southern Tanzania. Three sites were selected as representative of different habitat types, management strategies, and levels of anthropogenic pressure: Ruaha National Park’s core tourist area, dominated by Acacia-Commiphora bushlands and thickets; the Park’s miombo woodland; and the neighbouring community-run MBOMIPA Wildlife Management Area, also covered in Acacia-Commiphora. Our results show that the Park’s miombo woodlands supported a higher serval density than the core tourist area and Wildlife Management Area, with 5.56 [Standard Error = ±2.45], 3.45 [±1.04] and 2.08 [±0.74] individuals per 100 km2, respectively. This variation is likely driven by precipitation, the abundance of apex predators, and the level of anthropogenic pressure. Striped hyaena were detected only in the Wildlife Management Area and at low density (1.36 [±0.5] individuals per 100 km2), potentially due to the location of the surveyed sites at the edge of the species’ global range, high densities of sympatric competitors and anthropogenic edge effects. Finally, aardwolf were captured in both the Park’s core tourist area and the Wildlife Management Area, with a higher density in the Wildlife Management Area (13.25 [±2.48] versus 9.19 [±1.66] individuals per 100 km2), possibly as a result of lower intraguild predation and late fire outbreaks in the area surveyed. By shedding light on three understudied African carnivore species, this study highlights the importance of miombo woodland conservation and community-managed conservation, as well as the value of camera trap data to improve ecological knowledge of lesser-studied carnivores.
Molecular mechanisms of LC3-associated phagocytosis in the macrophage response to Paracoccidioides spp

Paracoccidiomycosis is a systemic fungal infection that is endemic in Latin America. The etiologic agents are thermodimorphic fungi from the Paracoccidiodes genus, which are facultative intracellular parasites of macrophages. LC3-associated phagocytosis (LAP), a noncanonical form of autophagy, is important in the immune response to similar pathogens, so we sought to determine the role LAP plays in the macrophage response to Paracoccidioides spp. By immunofluorescence, we found that LC3 was recruited to phagosomes containing Paracoccidioides spp. in both RAW264.7 and J774.16 cell lines and in bone marrow-derived macrophages. Interference with autophagy using RNAi against ATG5 reduced the antifungal activity of J774.16 cells, showing that LC3 recrutiment is important for proper control of the fungus by macrophages. Finally, we used pharmacological Syk kinase and NAPH oxidase inhibitors, which inhibit signalling pathways necessary for macrophage LAP against Aspergillus fumigatus and Candida albicans, to dissect part of the signaling pathways that trigger LAP agains Paracoccidioides spp. Interestingly, these inhibitors did not decrease LAP against P. brasiliensis, possibly due to differences in the fungal cell surface compositions. These observations suggest a potential role for autophagy as target for host-directed paracoccidioidomycosis therapies.
Antioxidant and Anticancer Properties of Leaf and Fruit Extracts of the Wild Raspberry (Rubus idaeus L.)

In this study the leaves and fruits of wild raspberry (Rubus idaeus L.) populations from the central Balkan region were examined to determine the level of secondary metabolites and related antioxidant activity, as well as biological activity, upon existing ethnobotanical evidence, primarily linked to gastrointestinal disorders. The values obtained for total phenols ranged from 59.68 to 96.83 mg GA g-1 and 24.29 to 38.71 mg GA g-1 in leaf and fruit extracts, respectively. The highest values of tannins and anthocyanins were determined for leaf extracts from a population of east Serbia at a level of 1.27 mg mL-1 and 9.00 mg mL-1. Antioxidant activity was evaluated by measuring the scavenging capacity of the extracts on DPPH. Higher antioxidant activity was detected in the leaf extracts than in the fruit extracts. Leaf and fruit extract were the most effective against Escherichia coli (ATCC 8739). Anticancer activity was studied on a human colorectal cancer cell line HCT-116. Leaf extracts exhibited anticancer activity with IC50/24 h 162.38 μg mL-1 and IC50/48 h 95.69 μg mL-1. Wild raspberry leaf and fruit extracts contain numerous secondary metabolites providing marked antioxidant, antimicrobial and anticancer activity.
New Insights from Old Data: Multimodal Classification of Schizophrenia Using Automated Deep Learning Configurations

Schizophrenia is a heterogeneous cognitive disorder where clinical classification is challenging be-cause of the lack of well-established, non-invasive diagnoses biomarkers. There is, hence, a need for objective systems that can classify Schizophrenia despite challenges such as overlapping symptomatic factors, diverse internal clinical manifestations, and complex diagnostic process leading to delayed treatment. Thus, experimentation with automated machine learning architectural frameworks (Au-toML) is presented in order to handle multimodal Functional Network Connectivity(FNC) and Source Based Morphometry(SBM) features based on functional magnetic resonance imaging(fMRI) and structural magnetic resonance imaging(sMRI) components respectively. On evaluating the resultant AutoML models with respect to approximately 280 machine learning architectures on the Overall AUC metric, the former outperforms the latter despite remarkable limitations including complex high dimensional feature space with very little data.
CENP-C regulates centromere assembly, asymmetry and epigenetic age in Drosophila germline stem cells

Germline stem cells divide asymmetrically to produce one new daughter stem cell and one daughter cell that will subsequently undergo meiosis and differentiate to generate the mature gamete. The silent sister hypothesis proposes that in asymmetric divisions, the selective inheritance of sister chromatids carrying specific epigenetic marks between stem and daughter cells impacts cell fate. To facilitate this selective inheritance, the hypothesis specifically proposes that the centromeric region of each sister chromatid is distinct. In Drosophila germ line stem cells (GSCs), it has recently been shown that the centromeric histone CENP-A (called CID in flies) - the epigenetic determinant of centromere identity - is asymmetrically distributed between sister chromatids. In these cells, CID deposition occurs in G2 phase such that sister chromatids destined to end up in the stem cell harbour more CENP-A, assemble more kinetochore proteins and capture more spindle microtubules. These results suggest a potential mechanism of ‘mitotic drive’ that might bias chromosome segregation. Here we report that the inner kinetochore protein CENP-C, is required for the assembly of CID in G2 phase in GSCs. Moreover, CENP-C is required to maintain a normal asymmetric distribution of CID between stem and daughter cells. In addition, we find that CID is lost from centromeres in aged GSCs and that a reduction in CENP-C accelerates this loss. Finally, we show that CENP-C depletion in GSCs disrupts the balance of stem and daughter cells in the ovary, shifting GSCs toward a self-renewal tendency. Ultimately, we provide evidence that centromere assembly and maintenance via CENP-C is required to sustain asymmetric divisions in female Drosophila GSCs.
Shared genetic architecture underlying root metaxylem phenotypes under drought stress in cereals

Root metaxylem are phenotypically diverse structures whose function is related to their anatomy, particularly under drought stress. Much research has dissected the genetic machinery underlying metaxylem phenotypes in dicots, but monocots are relatively unexplored. In maize (Zea mays), a robust pipeline integrated a GWAS of root metaxylem phenes under well-watered and water stress conditions with a gene co-expression network to identify candidate genes most likely to impact metaxylem phenotypes. We identified several promising candidate genes in 14 gene co-expression modules inferred to be functionally relevant to xylem development. We also identified five gene candidates that co-localized in multiple root metaxylem phenes in both well-watered and water stress conditions. Using a rice GWAS conducted in parallel, we detected overlapping genetic architecture influencing root metaxylem phenotypes by identifying eight pairs of syntenic candidate genes significantly associated with metaxylem phenes. There is evidence that the genes of these syntenic pairs may be involved in biosynthetic processes related to the cell wall, hormone signaling, oxidative stress responses, and drought responses. Our study demonstrates a powerful new strategy for identifying promising gene candidates and suggests several gene candidates that may enhance our understanding of vascular development and responses to drought in cereals. One sentence summary Cross-species genome-wide association studies and a gene coexpression network identified genes associated with root metaxylem phenotypes in maize under water stress and non-stress and rice.