Miracle-dz/UniFAR-FTUs huggingface dataset:
Brain Substrates of Episodic Memory for Identity, Location, and Action Information: A Lesion-Behavior Mapping Study

Brain networks supporting visual memory include extrastriate and other cortical regions associated with visual perception, which manifest domain-specific processing of “where,” “how,” and various aspects of “what” information. However, whether and how such specialization affects memory for these types of information is still a matter of debate. Functional neuroimaging studies point to dissociable as well as common network components supporting the perception and memory of different aspects of visual information. In the current neuropsychological study, we assess the impact of stroke lesion topography on recall of identity, location, and action of event participants, as assessed by the WMS-III Family Pictures subtest. We used voxel-based lesion-behavior mapping (VLBM) to identify brain lesions specifically implicated in memory deficits for each dimension. Behavioral analysis disclosed impaired performance by both right- and left-hemisphere damage patients, with lesions on each side yielding distinct effects. VLBM analysis revealed a bi-hemispheric network supporting these various aspects of visual memory. In the right hemisphere, the network includes frontal, parietal, and temporal cortical regions and the basal ganglia. In the left hemisphere, the network is more restricted, including visual association areas and medial temporal lobe regions. We further observed that a subset of these regions - those included in the ventral (“what”) stream, and in the putative core recollection network - is implicated in multiple aspects of visual memory, whereas other areas are specifically implicated in memory for specific aspects of the visual scene.
Intrathecal administration of bone marrow stromal cells and TGF-β1 alleviate chemotherapy-induced neuropathic pain in male mice

Chemotherapy-induced peripheral neuropathy (CIPN) is the de facto clinical side effect that limits the administration of anti-cancer treatments. Recently, we reported that intrathecally injected bone marrow stromal cells (BMSCs) reduced nerve trauma-induced neuropathic pain in male mice via TGF-β1 signaling. In this study, we examined sex-dependent pain relief mediated by intrathecally delivered BMSCs and TGF-β1 in paclitaxel (PTX)-induced CIPN. BMSCs were prepared from primary cultures of male or female mice separately. A single intrathecal injection of BMSCs, prepared from male donors, completely prevented the development of PTX-evoked mechanical allodynia in male mice. However, female mice showed no analgesic response to either male or female BMSCs. Additionally, male mice did not demonstrate an analgesic response to BMSCs from female donors. Intrathecal injection of TGF-β1 neutralizing antibody reversed the analgesic action of BMSCs. Interestingly, spinal administration of TGF-β1 reduced mechanical allodynia in male mice but not in female mice. Ex vivo patch-clamp recordings in spinal cord slices revealed that TGF-β1 inhibited PTX-induced synaptic plasticity, i.e. increase in spontaneous excitatory synaptic currents (sEPsCs), in spinal cord neurons from male mice only. Intrathecal TGF-β1 increased the paw withdrawal threshold in von Frey testing in naïve mice of males but not females, and the antinociceptive effect of TGF-β1 in males was blocked by orchiectomy-induced androgen deficiency. Together, these findings reveal sex dimorphism in BMSC control of mechanical pain through spinal TGF-β1 signaling.
VStrains: De Novo Reconstruction of Viral Strains via Iterative Path Extraction From Assembly Graphs

With the high mutation rate in viruses, a mixture of closely related viral strains (called viral quasispecies) often co-infect an individual host. Reconstructing individual strains from viral quasispecies is a key step to characterizing the viral population, revealing strain-level genetic variability, and providing insights into biomedical and clinical studies. Reference-based approaches of reconstructing viral strains suffer from the lack of high-quality references due to high mutation rates and biased variant calling introduced by a selected reference. De novo methods require no references but face challenges due to errors in reads, the high similarity of quasispecies, and uneven abundance of strains. In this paper, we propose VStrains, a de novo approach for reconstructing strains from viral quasispecies. VStrains incorporates contigs, paired-end reads, and coverage information to iteratively extract the strain-specific paths from assembly graphs. We benchmark VStrains against multiple state-of-the-art de novo and reference-based approaches on both simulated and real datasets. Experimental results demonstrate that VStrains achieves the best overall performance on both simulated and real datasets under a comprehensive set of metrics such as genome fraction, duplication ratio, NGA50, error rate, etc. Availability VStrains is freely available at https://github.com/MetaGenTools/VStrains.
KBeagle: An Adaptive Strategy and Tool for Improvement of Imputation Accuracy and Computing Efficiency

With the development of molecular biology and genetics, deep sequencing technology has become the main way to discover genetic variation and reveal the molecular structure of genome. Due to the complexity of the whole genome segment structure, a large number of missing genotypes have appeared after sequencing, and these missing genotypes can be imputed by genotype imputation method. With the in-depth study of genotype imputation methods, computational intensive and computationally efficient imputation software come into being. Beagle software, as an efficient imputation software, is widely used because of its advantages of low memory consumption, fast running speed and relatively high imputation accuracy. K-Means clustering can divide individuals with similar population structure into a class, so that individuals in the same class can share longer haplotype fragments. Therefore, combining K-Means clustering algorithm with Beagle software can improve the interpolation accuracy. The Beagle and KBeagle method was used to compare the imputation efficiency. The KBeagle method presents a higher imputation matching rate and a shorter computing time. In the genome selection and heritability estimated section, the genotype dataset after imputed, unimputed, and with real genotype show similar prediction accuracy. However the estimated heritability using genotype dataset after imputed is closer to the estimation by the dataset with real genotype. We generated a compounds and efficient imputation method, which presents valuable resource for improvement of imputation accuracy and computing time. We envisage the application of KBeagle will be focus on the livestock sequencing study under strong genetic structure.
Diverse patterns of secondary structure across genes and transposable elements are associated with siRNA production and epigenetic fate

RNA molecules carry information in their primary sequence and also their secondary structure. Secondary structure can confer important functional information, but it is also a potential signal for an RNAi-like host epigenetic response mediated by small interfering RNAs (siRNAs). In this study, we predicted local secondary structures in features of the maize genome, focusing on small regions that had folding energies similar to pre-miRNA loci. We found secondary structures to be common in retrotransposons, in Helitrons, and in genes. These structured regions mapped higher diversities of siRNAs than regions without structure, explaining up to 24% of variation of the siRNA distribution across some TE types. Among genes, those with secondary structure were 1.5-fold more highly expressed, on average, than genes without secondary structure. However, these genes were also more variably expressed across the 26 NAM lines, and this variability correlated with the number of mapping siRNAs. We conclude that local stem-loop structures are a nearly ubiquitous feature of expressed regions of the maize genome, that they correlate with higher siRNA mapping, and that they can represent a trade-off between functional need and the potentially negative consequences of siRNA production.
Convergence of coined quantum walks on d-dimensional Euclidean space

Coined quantum walks may be interpreted as the motion in position space of a quantum particle with a spin degree of freedom; the dynamics are determined by iterating a unitary transformation which is the product of a spin transformation and a translation conditional on the spin state. Coined quantum walks on the d-dimensional lattice can be treated as special cases of coined quantum walks on d-dimensional Euclidean space. We study quantum walks on d-dimensional Euclidean space and prove that the sequence of rescaled probability distributions in position space associated to the unitary evolution of the particle converges to a limit distribution.
Tunnel magnetoresistance and robust room temperature exchange bias with multiferroic BiFeO3 epitaxial thin films

The authors report on the functionalization of multiferroic BiFeO3 epitaxial films for spintronics. A first example is provided by the use of ultrathin layers of BiFeO3 as tunnel barriers in magnetic tunnel junctions with La2∕3Sr1∕3MnO3 and Co electrodes. In such structures, a positive tunnel magnetoresistance up to 30% is obtained at low temperature. A second example is the exploitation of the antiferromagnetic spin structure of a BiFeO3 film to induce a sizable (∼60Oe) exchange bias on a ferromagnetic film of CoFeB at room temperature. Remarkably, the exchange bias effect is robust upon magnetic field cycling, with no indications of training.
Biochemical analysis, photosynthetic gene (psbA) down–regulation, and in silico receptor prediction in weeds in response to exogenous application of phenolic acids and their analogs

Chemical herbicides are the primary weed management tool, although several incidences of herbicide resistance have been emerged, causing serious threat to agricultural sustainability. Plant derived phenolic acids with herbicidal potential may provide organic and eco-friendly substitute to such harmful chemicals. In present study, efficacy of two phenolic compounds, ferulic acid (FA) and gallic acid (GA), were evaluated in vitro and in vivo against three prevalent herbicide-resistant weed species (Sinapis arvensis, Lolium multiflorum and Parthenium hysterophorus). FA and GA not only suppressed the weed germination (80 to 60 % respectively), but also inhibited biochemical and photosynthetic pathway of weeds. In addition to significantly lowering the total protein and chlorophyll contents of the targeted weed species, the application of FA and GA treatments increased the levels of antioxidant enzymes and lipid peroxidation. Photosynthetic gene (psbA) expression was downregulated (10 to 30 folds) post 48 h of phenolic application. In silico analysis for receptor identification of FA and GA in psbA protein (D1) showed histidine (his-198) and threonine (thr-286) as novel receptors of FA and GA. These two receptors differ from the D1 amino acid receptors which have previously been identified (serine-264 and histidine-215) in response to PSII inhibitor herbicides. Based on its toxicity responses, structural analogs of FA were also designed. Four out of twelve analogs (0.25 mM) significantly inhibited weed germination (30 to 40%) while enhancing their oxidative stress. These results are unique which provide fundamental evidence of phytotoxicity of FA and GA and their analogs to develop cutting-edge plant based formulation to suppress weed growth in future.
Fast yet force-effective mode of supracellular collective cell migration on aligned fibers due to extracellular force transmission

Cell collectives, like other motile entities, generate and use forces to move forward. Here, we ask whether environmental configurations alter this proportional force-speed relationship, since aligned extracellular matrix fibers are known to cause directed migration. We show that aligned fibers serve as active conduits for spatial propagation of cellular mechanotransduction through matrix exoskeleton, leading to efficient directed collective cell migration. Epithelial (MCF10A) cell clusters adhered to soft substrates with aligned collagen fibers (AF) migrate faster with much lesser traction forces, compared to random fibers (RF). Fiber alignment causes higher motility waves and transmission of normal stresses deeper into cell monolayer while minimizing shear stresses and increased cell-division based fluidization. By contrast, fiber randomization induces cellular jamming due to breakage in motility waves, disrupted transmission of normal stresses, and heightened shear driven flow. Using a novel motor-clutch model, we explain that such ‘force-effective’ fast migration phenotype occurs due to rapid stabilization of contractile forces at the migrating front, enabled by higher frictional forces arising from simultaneous compressive loading of parallel fiber-substrate connections. We also model ’haptotaxis’ to show that increasing ligand connectivity (but not continuity) increases migration efficiency. According to our model, increased rate of front stabilization via higher resistance to substrate deformation is sufficient to capture ‘durotaxis’. Thus, our findings reveal a new paradigm wherein the rate of leading-edge stabilization determines the efficiency of supracellular collective cell migration.
Consolidation-dependent behavioral integration of sequences related to mPFC neural overlap and hippocampal-cortical connectivity

Systems consolidation theories propose two mechanisms that enable the behavioral integration of related memories: coordinated reactivation between hippocampus and cortex, and the emergence of cortical traces that reflect overlap across memories. However, there is limited empirical evidence that links these mechanisms to the emergence of behavioral integration over time. In two experiments, participants implicitly encoded sequences of objects with overlapping structure. Assessment of behavioral integration showed that response times during a recognition task reflected behavioral priming between objects that never occurred together in time but belonged to overlapping sequences. This priming was consolidation-dependent and only emerged for sequences learned 24 hours prior to the test. Critically, behavioral integration was related to changes in neural pattern similarity in the medial prefrontal cortex and increases in post-learning rest connectivity between the posterior hippocampus and lateral occipital cortex. These findings suggest that memories with a shared predictive structure become behaviorally and neurally integrated through a consolidation-related restructuring of the learned sequences, providing insight into the relationship between different consolidation mechanisms that support behavioral integration.
Vector-clustering Multiple Sequence Alignment: Aligning into the twilight zone of protein sequence similarity with protein language models

Multiple sequence alignment is a critical step in the study of protein sequence and function. Typically, multiple sequence alignment algorithms progressively align pairs of sequences and combine these alignments with the aid of a guide tree. These alignment algorithms use scoring systems based on substitution matrices to measure amino-acid similarities. While successful, standard methods struggle on sets of proteins with low sequence identity - the so-called twilight zone of protein alignment. For these difficult cases, another source of information is needed. Protein language models are a powerful new approach that leverage massive sequence datasets to produce high-dimensional contextual embeddings for each amino acid in a sequence. These embeddings have been shown to reflect physicochemical and higher-order structural and functional attributes of amino acids within proteins. Here, we present a novel approach to multiple sequence alignment, based on clustering and ordering amino acid contextual embeddings. Our method for aligning semantically consistent groups of proteins circumvents the need for many standard components of multiple sequence alignment algorithms, avoiding initial guide tree construction, intermediate pairwise alignments, gap penalties, and substitution matrices. The added information from contextual embeddings leads to higher accuracy alignments for structurally similar proteins with low amino-acid similarity. We anticipate that protein language models will become a fundamental component of the next generation of algorithms for generating MSAs. Software availability: https://github.com/clairemcwhite/vcmsa
Evolutionary blocks to anthocyanin accumulation and the loss of an anthocyanin carrier protein in betalain-pigmented Caryophyllales

◻ The order Caryophyllales exhibits complex pigment evolution, with mutual exclusion of anthocyanin and betalain pigments. Given recent evidence for multiple shifts to betalain pigmentation, we re-evaluated potential mechanisms underpinning the exclusion of anthocyanins from betalain-pigmented lineages. ◻ We examined the evolution of the flavonoid pathway using transcriptomic and genomic datasets covering 309 species in 31 families. Orthologs and paralogs of known flavonoid synthesis genes were identified by sequence similarity, with gene duplication and gene loss inferred by phylogenetic and syntenic analysis. Relative transcript abundances were assessed to reveal broad-scale gene expression changes between betalain- and anthocyanin-pigmented lineages. ◻ Most flavonoid genes are retained and transcribed in betalain-pigmented lineages, and many also show evidence of extensive gene duplication within betalain-pigmented lineages. However, expression of several flavonoid genes is reduced in betalain-pigmented lineages, especially the late-stage genes dihydroflavonol 4-reductase (DFR) and anthocyanidin synthase (ANS). Notably flavonoid 3′,5′-hydroxylase (F3′5′H) homologs have been repeatedly lost in belatain-pigmented lineages, and Anthocyanin9 (AN9) homologs are undetectable in any betalain-pigmented lineages. ◻ Down-regulation of ANS and DFR homolog expression (limiting synthesis) and reiterative loss of AN9 homologs (limiting transport), coincident with multiple shifts to betalain pigmentation, are likely crucial the loss of anthocyanins in betalain-pigmented Caryophyllales.
Using mechanistic models to highlight research priorities for tick-borne zoonotic diseases: Improving our understanding of the ecology and maintenance of Kyasanur Forest Disease in India

The risk of spillover of zoonotic diseases to humans is changing in response to multiple environmental and societal drivers, particularly in tropical regions where the burden of neglected zoonotic diseases is highest and land use change and forest conversion is occurring most rapidly. In these regions, neglected zoonotic diseases can have significant impacts on poor and marginalised populations in low-resource settings but ultimately receive less attention and funding for research and interventions. As such, effective control measures and interventions are often hindered by a limited ecological evidence base, which results in a limited understanding of epidemiologically relevant hosts or vectors and the processes that contribute to the maintenance of pathogens and spillover to humans. Here, we develop a generalisable next generation matrix modelling framework to better understand the transmission processes and hosts that have the greatest contribution to the maintenance of tick-borne diseases with the aim of improving the ecological evidence base and framing future research priorities for tick-borne diseases. Using this model we explore the relative contribution of different host groups and transmission routes to the maintenance of a neglected zoonotic tick-borne disease, Kyasanur Forest Disease Virus (KFD). The results highlight the potential importance of transovarial transmission and small mammals and birds in maintaining this disease. This contradicts previous hypotheses that primates play an important role influencing the distribution of infected ticks. There is also a suggestion that risk could vary across different habitat types. In light of these results we outline the key knowledge gaps for this system and future research priorities that would aid in informing effective interventions and control measures.
Identification of aryl hydrocarbon receptor as a barrier to HIV-1 infection and outgrowth in CD4+ T cells

The Aryl hydrocarbon receptor (AhR) identifies “non-pathogenic” Th17-polarized CD4+ T-cells in autoimmune models. Thus, we explored whether AhR restricts HIV-1 in Th17-cells, consistent with its antiviral role in macrophages. AhR-specific CRISPR/Cas9-mediated knockout and pharmacological blockade decreased AhR target gene expression (CYP1A1/IL-22/IL-17A/IL-10/ ITGB7), while increasing HIV-1 replication in CD4+ T-cells. Pharmacological AhR activation caused opposite effects. AhR agonism/antagonism modulated HIV-1 replication mainly in Th17/Th22-polarized CCR6+CD4+ T-cells. Single-round VSV-G-pseudotyped HIV-1 infection demonstrated that AhR acts at post-entry levels, with AhR blockade increasing the efficacy of early/late reverse transcription steps and subsequently integration/translation. In viral outgrowth assay, the AhR blockade boosted the detection of replication-competent viral reservoirs in CD4+ T-cells of people living with HIV-1 (PLWH) receiving antiretroviral therapy (ART). Finally, RNA-Sequencing revealed genes/pathways modulated by AhR blockade in CD4+ T-cells of ART-treated PLWH, with known HIV-1 interactor activities (NCBI HIV Interactor Database) and AhR responsive elements in their promoters (ENCODE). Among them, HIC1, a repressor of Tat-mediated HIV-1 transcription and a tissue-residency inducer, represents a putative AhR mechanism of action. These results demonstrate that AhR governs an antiviral transcriptional program in CD4+ T-cells and point to the use of AhR inhibitors to boost viral outgrowth in “shock and kill” HIV-1 remission/cure strategies. Model of AhR-mediated transcriptional reprogramming with implications for “silent” HIV-1 reservoir persistence and gut homing/residency. RNA-Sequencing revealed genes sets modulated by AhR blockade in CD4+ T-cells of ART-treated PLWH, with known HIV-1 interactor activities (NCBI HIV Interactor Database) and AhR responsive elements in their promoters (ENCODE). Among them, HIC1, a repressor of Tat-mediated HIV-1 transcription and a tissue-residency regulator, represents a putative AhR mechanism of action. These results support a model in which AhR activation favors the gut homing and residency via the induction of ITGB7 and CXCR6 expression, respectively, and fuels the persistence of ‘silent” HIV-1 reservoirs in CD4+ T-cells of ART-treated PLWH. At the opposite, pharmacological AhR blockade facilitates viral outgrowth, and by interfering with tissue residency, likely promotes the mobilization of « reactivated » reservoir cells from deep tissues into the circulations. BRIEF SUMMARY We identified the aryl hydrocarbon receptor as a barrier to HIV-1 infection/outgrowth in Th17-polarized CD4+ T-cells and a novel therapeutic target in HIV-1 cure/remission interventions.
Astrocytic Sleep Homeostasis Model

Sleep awake cycle is critical for cognitive and functional abilities. Conventional sleep homeostasis mechanisms are neuronal in nature and recent views indicate glial regulation of the sleep-wake process. Mechanisms of homeostatic regulation of sleep remain to be understood. A simplified astrocytic sleep-awake homeostasis mathematical model with sleep pressure and synaptic strength dynamics is proposed using feedback control loops. The model provides insights into the emergence of two discrete states through sleep and awake promoting neuronal populations giving rise to a homeostatic process S and oscillatory process C is regulated by astrocytic sleep pressure. It also explains the variations seen in synaptic strength dynamics during sleep and awake states.