Miracle-dz/UniFAR-FTUs huggingface dataset:
Analysis of wall-modelled particle/mesh PDF methods for turbulent parietal flows

Abstract Lagrangian stochastic methods are widely used to model turbulent flows. Scarce consideration has, however, been devoted to the treatment of the near-wall region and to the formulation of a proper wall-boundary condition. With respect to this issue, the main purpose of this paper is to present an in-depth analysis of such flows when relying on particle/mesh formulations of the probability density function (PDF) model. This is translated into three objectives. The first objective is to assess the existing an-elastic wall-boundary condition and present new validation results. The second objective is to analyse the impact of the interpolation of the mean fields at particle positions on their dynamics. The third objective is to investigate the spatial error affecting covariance estimators when they are extracted on coarse volumes. All these developments allow to ascertain that the key dynamical statistics of wall-bounded flows are properly captured even for coarse spatial resolutions.
Outcomes of people with psychotic disorders in a community-based rehabilitation programme in rural India

Background There is little evidence of the feasibility, acceptability and impact of services for the care of people with psychotic disorders in low- and middle-income countries. Aims To describe the scaling up and impact of a community-based rehabilitation programme for people with psychotic disorders in a very-low-resource setting. Methods Longitudinal study of people with psychotic disorders who had been ill for an average of 8 years in a rural Indian community. All individuals received a community-based intervention package comprising psychotropic medications, psychoeducation, adherence management, psychosocial rehabilitation and support for livelihoods. The primary outcome was change in disability scores. Results The cohort consisted of 256 people with psychotic disorders (schizophrenia, bipolar affective disorder and other psychosis) of whom 236 people completed the end-point assessments (92%), with a median follow-up of 46 months. There were significant reductions (P<0.05) in the levels of disability for the cohort, the vast majority (83.5%) of whom engaged with the programme. On multivariate analyses, lower baseline disability scores, family engagement with the programme, medication adherence and being a member of a self-help group were independent determinants of good outcomes. Lack of formal education, a diagnosis of schizophrenia and dropping out of the programme were independent determinants of poor outcomes. Conclusions Community-based rehabilitation is a feasible and acceptable intervention with a beneficial impact on disability for the majority of people with psychotic disorders in low-resource settings. The impact on disability is influenced by a combination of clinical, programme and social determinants.
Hidden evolutionary constraints dictate the retention of coronavirus accessory genes

Coronaviruses exhibit many mechanisms of genetic innovation1–5, including the acquisition of accessory genes that originate by capture of cellular genes or through duplication of existing viral genes6,7. Accessory genes influence viral host range and cellular tropism, but little is known about how selection acts on these variable regions of virus genomes. We used experimental evolution of mouse hepatitis virus (MHV) encoding a cellular AKAP7 phosphodiesterase and an inactive native phosphodiesterase, NS2 (ref 8) to simulate the capture of a host gene and analyze its evolution. After courses of serial infection, the gene encoding inactive NS2, ORF2, unexpectedly remained intact, suggesting it is under cryptic constraint uncoupled from the function of NS2. In contrast, AKAP7 was retained under strong selection but rapidly lost under relaxed selection. Guided by the retention of ORF2 and similar patterns in related betacoronaviruses, we analyzed ORF8 of SARS-CoV-2, which arose via gene duplication6 and contains premature stop codons in several globally successful lineages. As with MHV ORF2, the coding-defective SARS-CoV-2 ORF8 gene remains largely intact, mirroring patterns observed during MHV experimental evolution, challenging assumptions on the dynamics of gene loss in virus genomes and extending these findings to viruses currently adapting to humans.
Unlocking cellular plasticity: Enhancing human iPSC reprogramming through bromodomain inhibition and extracellular matrix gene expression regulation

The transformation of fibroblasts into epithelial cells is critical for iPSC reprogramming. In this report, we describe studies with PFI-3, a small molecule inhibitor that specifically targets the bromodomains of SMARCA2/4 and PBRM1 subunit of SWI/SNF complex, as an enhancer of iPSC reprogramming efficiency. Our findings revealed that PFI-3 induces cellular plasticity in multiple human dermal fibroblasts, leading to a mesenchymal-epithelial transition (MET) during iPSC formation. This transition was characterized by the upregulation of E-cadherin expression, a key protein involved in epithelial cell adhesion. Additionally, we identified COL11A1 as a reprogramming barrier and demonstrated COL11A1 knockdown increased reprogramming efficiency. Notably, we found that PFI-3 significantly reduced the expression of numerous extracellular matrix (ECM) genes, particularly those involved in collagen assembly. Our research provides key insights into the early stages of iPSC reprogramming, highlighting the crucial role of ECM changes and cellular plasticity in this process.
ATOMDANCE: kernel-based denoising and allosteric resonance analysis for functional and evolutionary comparisons of protein dynamics

Comparative methods in molecular biology and molecular evolution rely exclusively upon the analysis of DNA sequence and protein structure, both static forms of information. However, it is widely accepted that protein function results from changes in dynamic machine-like motions induced by molecular interactions, a type of data for which comparative methods of analysis are challenged by the large fraction of protein motion created by random thermal noise in the surrounding solvent. Here, we introduce ATOMDANCE, a suite of statistical and kernel-based machine learning tools designed for comparing and denoising functional states of protein motion captured in time-series from molecular dynamics simulations. ATOMDANCE employs interpretable Gaussian kernel functions to compute site-wise maximum mean discrepancy (MMD) between learned features of motion representing two functional, malfunctional or evolutionary protein states (e.g. bound vs. unbound, wild-type vs. mutant). ATOMDANCE derives empirical p-values identifying functional similarity/difference in dynamics at each amino acid site on the protein. ATOMDANCE also employs MMD to contextually analyze potential random amino-acid replacements thus allowing for a site-wise test of neutral vs. non-neutral evolution in the divergence of dynamic function in protein homologs. Lastly, ATOMDANCE also employs mixed-model ANOVA combined with graph network community detection to identify functional shifts in protein regions that exhibit time-coordinated dynamics or resonance of motion across sites. Here, we demonstrate the utility of the software for identifying key sites involved in dynamic responses during functional binding interactions involving DNA, small molecule drugs, and virus-host recognition. We also demonstrate its utility in understanding dynamic resonance changes occurring during the allosteric activation of a pathogenic protease. ATOMDANCE offers a user-friendly interface and only requires an input structure, topology and trajectory files for each of the two proteins being compared (i.e .pdb, .prmtop, and .nc). A separate interface for generating molecular dynamics simulations via open-source tools is also offered. Lay Audience Summary – ATOMDANCE is a suite of software pipelines controlled by a single user interface and designed to comprehensively simulate, calculate and compare protein motions between two functional or evolutionary states while controlling for random noise. It is useful for finding amino acid sites on a given protein that are important in binding other proteins, DNA, or drugs/toxins. It can also be used to assess the effect of genetic mutation on protein motion, and identifies regions of sites on proteins that tend to move together or ‘resonate’ as a whole unit or community.
The H3.3 K36M oncohistone disrupts the establishment of epigenetic memory through loss of DNA methylation

Histone H3.3 is frequently mutated in cancers, with the lysine 36 to methionine mutation (K36M) being a hallmark of chondroblastomas. While it is known that H3.3K36M changes the cellular epigenetic landscape, it remains unclear how it affects the dynamics of gene expression. Here, we use a synthetic reporter to measure the effect of H3.3K36M on silencing and epigenetic memory after recruitment of KRAB: a member of the largest class of human repressors, commonly used in synthetic biology, and associated with H3K9me3. We find that H3.3K36M, which decreases H3K36 methylation, leads to a decrease in epigenetic memory and promoter methylation weeks after KRAB release. We propose a new model for establishment and maintenance of epigenetic memory, where H3K36 methylation is necessary to convert H3K9me3 domains into DNA methylation for stable epigenetic memory. Our quantitative model can inform oncogenic mechanisms and guide development of epigenetic editing tools.
Synaptic Activity Causes Minute-scale Changes in BAF Complex Composition and Function

Genes encoding subunits of the SWI/SNF or BAF ATP-dependent chromatin remodeling complex are among the most enriched for deleterious de novo mutations in intellectual disabilities and autism spectrum disorder, but the causative molecular pathways are not fully known1,2. Synaptic activity in neurons is critical for learning and memory and proper neural development3. Neural activity prompts calcium influx and transcription within minutes, facilitated in the nucleus by various transcription factors (TFs) and chromatin modifiers4. While BAF is required for activity-dependent developmental processes such as dendritic outgrowth5–7, the immediate molecular consequences of neural activity on BAF complexes and their functions are unknown. Here we mapped minute-scale biochemical consequences of neural activity, modeled by membrane depolarization of embryonic mouse primary cortical neurons, on BAF complexes. We used acute chemical perturbations of BAF ATPase activity and kinase signaling to define the activity-dependent effects on BAF complexes and activity-dependent BAF functions. Our studies found that BAF complexes change in subunit composition and are selectively phosphorylated within 10 minutes of depolarization. Increased levels of the core PBAF subunit Baf200/Arid2, uniquely containing an RFX-like DNA-binding domain, are concurrent with ATPase-dependent opening of chromatin at RFX/X-box motifs. Changes in BAF composition and phosphorylation lead to the regulation of chromatin accessibility for critical neurogenesis TFs. These biochemical effects are a convergent phenomenon downstream of multiple growth factor signaling pathways in mouse neurons and fibroblasts suggesting that BAF integrates signaling information from the membrane. In support of such a membrane-to-nucleus signaling cascade, we also identified a BAF-interacting kinase, Dclk2, whose inhibition attenuates BAF phosphorylation selectively. Our findings support a direct role of BAF complexes in responding to synaptic activity to regulate TF binding and transcription.
Geochemistry of Mesozoic mafic volcanic rocks from the Yanshan belt in the northern margin of the North China Block: relations with post-collisional lithospheric extension

Abstract Major element, trace element and Sr–Nd isotope data for three suites of mafic volcanic rocks that erupted at c. 180 Ma (Group 1), c. 163–140 Ma (Group 2) and 136–110 Ma (Group 3) in the Yanshan belt in the northern margin of the North China Block (NCB) are presented in this paper. All the rocks show significant enrichment in large ion lithophile elements and light REE (LREE) but depletion in Nb–Ta and Th–U, and moderately radiogenic Sr (87Sr/86Sr(i)= 0.7052–0.7068) and unradiogenic Nd (ϵNd(t)=−15.1 to −7.2) isotopic compositions. Sr–Nd isotopic modelling suggests an insignificant role of crustal contamination or assimilation fractional crystallization, and the geochemical variations in these rocks were mainly attributed to source heterogeneity and variable degrees of ferromagnesian, plagioclase and accessory mineral fractionation. The low Th/La (0.039-0.10) points to recycling of low-Th/La (e.g. Th/La <0.2) ancient crustal materials into the source region, probably related to the palaeo-Asian Ocean subduction. Compared with the late Mesozoic mafic rocks from the NCB interior, the Yanshan belt mafic lavas generally have higher Al2O3, TiO2, P2O5, LREE, high field strength elements, Sr and 87Sr/86Sr(i) but lower MgO and compatible elements. Major element extrapolation (MgO=8% normalization) reveals that the Yanshan belt mafic volcanic rocks have higher Ti8 and Fe8, and lower Si8 than those from the NCB interior, suggesting that they were probably derived from a relatively fertile mantle source, different from the Mesozoic chemically refractory lithospheric mantle beneath the NCB interior. Combining the geochemical features of the mafic rocks with Mesozoic deformation events in the northern NCB, we suggest that the three stages of mafic volcanism were caused by episodic lithospheric extension. The Group 1 rocks, which occur locally along major faults, were generated during a post-compressional extension related to the collision between the NCB and Mongolian Block; the Group 2 rocks formed as a result of post-collisional lithospheric extension related to the collision between the North China–Mongolian Block and the Siberian plate; and the Group 3 rocks were extruded in an extensional regime in response to lateral escape related to surrounding plate interactions.
Sinefungin, a natural nucleoside analog of S-adenosyl methionine, impairs the pathogenicity of Candida albicans

Candida albicans, an opportunistic fungal human pathogen, is a major threat to the healthcare system due to both infections in immunocompromised individuals and the emergence of antifungal resistance. Fungal infection caused by C. albicans, candidiasis, is a life-threatening condition in immunocompromised patients and the current treatments are mostly restricted to polyenes, azoles, and echinocandins. Use of these antifungals is limited by toxicity, drug-drug interactions, and the emergence of resistance, underscoring the importance of identifying novel therapeutic targets and the need for new treatment approaches. C. albicans can undergo a morphological transition from yeast to hyphae and this transition is central to C. albicans virulence. Here, we determine the impact of sinefungin, a natural nucleoside analog of S-adenosyl methionine, on the virulence of C. albicans strain SC5314 by evaluating treatment effects on the morphological transition, human epithelial cell adhesion, and biofilm formation. Our data indicate that sinefungin impairs pathogenic traits of C. albicans including hyphal lengthening, biofilm formation and the adhesion to the human epithelial cell lines, without adversely affecting human cells, therefore highlighting sinefungin as a potential avenue for therapeutic intervention. We determine that the formation of N6-methyladenosine (m6A) is particularly disturbed by sinefungin. More broadly, this study underscores the importance of considering the post-transcriptional control mechanisms of pathogenicity when designing therapeutic solutions to fungal infection.
A familiar face and person processing area in the human temporal pole

How does the brain process the faces of familiar people? Neuropsychological studies have argued for an area of the temporal pole (TP) linking faces with person identities, but magnetic susceptibility artifacts in this region have hampered its study with fMRI. Using data acquisition and analysis methods optimized to overcome this artifact, we identify a familiar face response in TP, reliably observed in individual brains. This area responds strongly to visual images of familiar faces over images of unfamiliar faces, objects, and scenes. However, TP did not just respond to images of faces, but also to a variety of high-level cognitive tasks that involve thinking about people, including semantic, episodic, and theory of mind tasks. The response profile of TP contrasted from a nearby region of perirhinal cortex that responded specifically to faces, but not to social cognition tasks. TP was functionally connected with a distributed network in association cortex associated with social cognition, while PR was functionally connected with face-preferring areas of ventral visual cortex. This work identifies a missing link in the human familiar face processing system that specifically processes familiar faces, and is well placed to integrate visual information about faces with higher-order conceptual information about other people. The results suggest that separate streams for person and face processing reach anterior temporal areas positioned at the top of the cortical hierarchy.
The eukaryome of modern microbialites reveals distinct colonization across aquatic ecosystems

Microbial diversity includes bacteria, archaea, eukaryotes, and viruses; however, protists are less studied for their impact and diversity within ecosystems. Protists have been suggested to shape the emergence and decline of ancient stromatolites. Modern microbialites offer a unique proxy to study the deposition of carbonate by microbial communities due to analog status for ancient ecosystems and their cosmopolitan abundance. We examined protists across aquatic ecosystems between freshwater (Kelly and Pavilion Lake in British Columbia, Canada) and marine microbialites (Shark Bay, Australia and Highborne Cay, Bahamas) to decipher the transition with respect to diversity and composition. While factors such as sequencing technology and primer-bias might influence our conclusions, we found that at the taxonomic compositional-level, the freshwater microbialite communities were clearly distinct from the marine microbialite communities. Chlorophytes were significantly more abundant in the freshwater microbialites, while saltwater microbialites communities were primarily composed of pennate diatoms. Despite the differences in taxonomic make-up, we can infer the convergent important role of these protists to microbialite community health and function. These results highlight not only the consistency and potential role of microbialite eukaryotic communities across geographic locations, but also that other factors such as salinity seem to be the main drivers of community composition.
Deconvolution of Nascent Sequencing Data Using Transcriptional Regulatory Elements

The problem of microdissection of heterogeneous tissue samples is of great interest for both fundamental biology and biomedical research. Until now, microdissection in the form of supervised deconvolution of mixed sequencing samples has been limited to assays measuring gene expression (RNA-seq) or chromatin accessibility (ATAC-seq). We present here the first attempt at solving the supervised deconvolution problem for run-on nascent sequencing data (GRO-seq and PRO-seq), a readout of active transcription. Then, we develop a novel filtering method suited to the mixed set of promoter and enhancer regions provided by nascent sequencing, and apply best-practice standards from the RNA-seq literature, using in-silico mixtures of cells. Using these methods, we find that enhancer RNAs are highly informative features for supervised deconvolution. In most cases, simple deconvolution methods perform better than more complex ones for solving the nascent deconvolution problem. Furthermore, undifferentiated cell types confound deconvolution of nascent sequencing data, likely as a consequence of transcriptional activity over the highly open chromatin regions of undifferentiated cell types. Our results suggest that while the problem of nascent deconvolution is generally tractable, stronger approaches integrating other sequencing protocols may be required to solve mixtures containing undifferentiated celltypes.
Household Food Insecurity among African Immigrants of the United States: Evidence from the National Health Interview Survey

ABSTRACT The annual number of immigrants from sub-Saharan Africa to the United States (US) has roughly doubled every decade between 1980 and 2010. By 2015 the current and growing population of African Immigrants was estimated at 1.7 million, accounting for 4% of the 43.3 million immigrants in the US. The objective of this study is to investigate factors that influence the food security status of African Immigrant households in the US. Data from the Integrated Public Use Microdata Series (IPUMS) Health Survey, a harmonized data of the 2015 National Health Interview Survey (NHIS) was used. Food security (dependent variable) was measured using the USDA Household Food Security Survey Module (HFSSM) included in the NHIS data set. Independent variables included variables on immigration, economic and household characteristics. Multivariate logistic regression testing relationship of food security with the independent variables was done.
POD-Galerkin reduced order models and physics-informed neural networks for solving inverse problems for the Navier-Stokes equations

We present a Reduced Order Model (ROM) which exploits recent developments in Physics Informed Neural Networks (PINNs) for solving inverse problems for the Navier--Stokes equations (NSE). In the proposed approach, the presence of simulated data for the fluid dynamics fields is assumed. A POD-Galerkin ROM is then constructed by applying POD on the snapshots matrices of the fluid fields and performing a Galerkin projection of the NSE (or the modified equations in case of turbulence modeling) onto the POD reduced basis. A $\textit{POD-Galerkin PINN ROM}$ is then derived by introducing deep neural networks which approximate the reduced outputs with the input being time and/or parameters of the model. The neural networks incorporate the physical equations (the POD-Galerkin reduced equations) into their structure as part of the loss function. Using this approach, the reduced model is able to approximate unknown parameters such as physical constants or the boundary conditions. A demonstration of the applicability of the proposed ROM is illustrated by two cases which are the steady flow around a backward step and the unsteady turbulent flow around a surface mounted cubic obstacle.
Failure Handling in BDI Plans via Runtime Enforcement

Engineering a software system can be a complex process and prone to failure. This is exacerbated when the system under consideration presents some degree of autonomy, such as in cognitive agents. In this paper, we use runtime veriﬁcation as a way to enforce safety properties on Belief-Desire-Intention (BDI) agents by enveloping certain plans in safety shields. These shields function as a failure handling mechanism, they can detect and avoid violations in shielded plans. The safety shields also provide automated failure recovery by attempting alternative execution paths to avoid violations.
Anchor Characteristics and Consumer Purchasing Behavior: Based on Perceived Value Theory

With the rapid development of e-commerce live streaming platforms, network anchors have more and more obvious advantages in E-marketing. Based on the live streaming and perceived value theory, this paper explores the inﬂuence mechanism of network anchor characteristics on consumer purchasing behavior. The mediation effect of perceived value is veriﬁed through empirical analysis, which provides theoretical basis for subsequent research and feasible marketing suggestions for live streaming e-commerce platforms.