Miracle-dz/UniFAR-FTUs huggingface dataset:
Diffusion Kurtosis Imaging of the neonatal Spinal Cord: design and application of the first processing pipeline implemented in Spinal Cord Toolbox

Diffusion Kurtosis Imaging (DKI) has undisputed advantages over more classical diffusion Magnetic Resonance Imaging (dMRI), as witnessed by a fast-increasing number of clinical applications and software packages widely adopted in brain imaging domain. Despite its power in probing tissue microstructure compared to conventional MRI, DKI is still largely underutilized in Spinal Cord (SC) imaging because of its inherently demanding technological requirements. If state-of-the-art hardware advancements have recently allowed to make great strides in applying this emerging method to adult and child SC, the same does not apply to neonatal setting. Indeed, amplified technical issues related to SC district in this age range have made this field still unexplored. However, results arising from recent application of DKI to adult and child SC are promising enough to suggest how informative this technique would be in investigating newborns, too. Due to its extreme sensitivity to non-gaussian diffusion, DKI proves particularly suitable for detecting complex, subtle, fast microstructural changes occurring in this area at this early and critical stage of development, and not identifiable with only DTI. Given the multiplicity of congenital anomalies of the spinal canal, their crucial effect on later developmental outcome, and the close interconnection between SC region and the above brain, managing to apply such a method to neonatal cohort becomes of utmost importance. In this work, we illustrate the first semi-automated pipeline for handling with DKI data of neonatal SC, from acquisition setting to estimation of diffusion (DTI & DKI) measures, through accurate adjustment of processing algorithms customized for adult SC. Each processing step of this pipeline, built on Spinal Cord Toolbox (SCT) software, has undergone Quality Control check by supervision of an expert pediatric neuroradiologist, and the overall procedure has preliminarily been tested in a pilot clinical case study. Results of this application agree with findings achieved in a corresponding adult survey, thus confirming validity of adopted pipeline and diagnostic value of DKI in pediatrics. This novel tool hence paves the wave for extending its application also to other promising advanced dMRI models, such as Neurite Orientation Dispersion and Density Imaging (NODDI), and to a wider range of potential clinical applications concerning neonatal period.
Support Program to Reduce Anxiety in Grandparents of Children with Autism Spectrum Disorder Abstract

María del Sol Fortea Sevilla*, José Juan Castro Sánchez and María Olga Escandell Bermúdez University of Las Palmas de Gran Canaria, Spain *Corresponding Author: María del Sol Fortea Sevilla, University of Las Palmas de Gran Canaria, Spain. Received: January 03, 2021; Published: February 27, 202
SEMICONDUCTORS AND DIELECTRICS

The structural and thermodynamic properties of the alkaline-earth metal oxides and chalcogenides (AEMOCs) with the cubic structure (CaX, SrX, and BaX, where X =O, S, Se, and Te) and the parameters of the pressure-induced B1–B2 structural phase transitions in them have been calculated from the first principles. The crystalline and ionic radii in the AEMOCs are studied including the dependences of the ionic radii in the B1 and B2 structures on the pressure. The magnitudes of interband transitions and the band gaps in the examined compounds are calculated in the framework of the first-principles approach of the density functional theory and using the method of pseudopotential. The first-principles band calculations are carried out to determine the metallization pressures for the researched compounds.
Growth of poly(methyl methacrylate) brushes on silicon surfaces by atom transfer radical polymerization

Poly(methyl methacrylate) (PMMA) brushes are grown by surface-initiated atom transfer radical polymerization on silicon surfaces at various polymerization temperatures. Kinetic studies show that the layer thickness scales linearly with the degree of polymerization of the polymers under some conditions, indicating a constant graft density of the surface-attached chains. At high temperatures, the layer growth is a controlled process only for short reaction times, and after a rapid increase, the film growth levels off, and a constant thickness is obtained. At lower reaction temperatures, polymers with a lower polydispersity are obtained, but at the expense of a much slower growth rate. Accordingly, intermediate temperatures yield the highest film thickness on experimentally feasible timescales. The reinitiation of these surface-grafted PMMA chains at room temperature to either extend the chains or grow a chemically different polyglycidylmethacrylate block demonstrates the presence of active ends and the living nature of the surface-grafted PMMA chains.
Development of deﬁnitive endoderm from embryonic stem cells in culture

establish this differentiation system as a unique murine model for studying the development and speciﬁcation of this germ layer. Cell aggregates were harvested from the matrigel cultures by cell scraping and then transplanted under the kidney capsule of 5-week-old female SCID-beige mice. Three to four weeks following transplantation, the recipients were sacriﬁced, the kidneys removed and ﬁxed in 4% paraformaldehyde. After ﬁxation, kidneys were embedded in paraffin wax and sectioned for H/E and D-PAS staining, for immunostaining and for in situ hybridization.
DYNAMIC WETTING OF AN OCCLUSION

This paper investigates how and under which conditions the lamella of an impacting droplet is punctured by the presence of a small occlusion. Better understanding the conditions which lead to the rupture of the lamella is critical to produce defect free coating layers in the context of spray coating, for example. An analytical model based on surface energy analysis is proposed to obtain the critical thickness below which the liquid layer above the occlusion is unstable and lamella rupture occurs. Furthermore, we have developed a three dimensional multiphase lattice Boltzmann code to confirm the surface energy analysis and study the influence of key parameters like size of the occlusion, impact velocity and wettability of substrate on hole formation. Results show that a hole is more likely to appear as the diameter of the occlusion, the impact velocity, and the hydrophobicity of the surface increase.
A General Perspective of the Characterization and Quantification of Nanoparticles: Imaging, Spectroscopic, and Separation Techniques

This article gives an overview of the different techniques used to identify, characterize, and quantify engineered nanoparticles (ENPs). The state-of-the-art of the field is summarized, and the different characterization techniques have been grouped according to the information they can provide. In addition, some selected applications are highlighted for each technique. The classification of the techniques has been carried out according to the main physical and chemical properties of the nanoparticles such as morphology, size, polydispersity characteristics, structural information, and elemental composition. Microscopy techniques including optical, electron and X-ray microscopy, and separation techniques with and without hyphenated detection systems are discussed. For each of these groups, a brief description of the techniques, specific features, and concepts, as well as several examples, are described.
Evolution of Development Priorities in Key-value Stores Serving Large-scale Applications: The RocksDB Experience

RocksDB is a key-value store targeting large-scale distributed systems and optimized for Solid State Drives (SSDs). This paper describes how our priorities in developing RocksDB have evolved over the last eight years. The evolution is the result both of hardware trends and of extensive experience running RocksDB at scale in production at a number of organizations. We describe how and why RocksDB’s resource optimization target migrated from write amplification, to space amplification, to CPU utilization. Lessons from running large-scale applications taught us that resource allocation needs to be managed across different RocksDB instances, that data format needs to remain backward and forward compatible to allow incremental software rollout, and that appropriate support for database replication and backups are needed. Lessons from failure handling taught us that data corruption errors needed to be detected earlier and at every layer of the system.
Does Education Predict Gender Role Attitudes?: Evidence from European Datasets

This paper presents the first empirical evidence of the causal impact of individuals' education on their attitudes towards traditional gender roles in Europe. We employ two national panel datasets from the UK and Switzerland and a repeated cross-sectional dataset with information from 13 Western European countries for the analysis. To estimate the causal impact of education on gender role attitudes, we exploit the exogenous variation in individuals' education induced by the compulsory school reforms implemented in European countries after World War II. Our results suggest that an additional year of education instigates egalitarian gender role attitudes equivalent of 0.1-0.3 of a standard deviation. While education's moderating effect is particularly prominent among women, we find no evidence of effect heterogeneity concerning individuals' religiosity. Our findings are robust to numerous checks performed and are briefly discussed for their policy relevance.
A dynamical system model for predicting gene expression from the epigenome

Gene regulation is an important fundamental biological process. The regulation of gene expression is managed through a variety of methods including epigenetic processes (e.g., DNA methylation). Understanding the role of epigenetic changes in gene expression is a fundamental question of molecular biology. Predictions of gene expression values from epigenetic data have tremendous research and clinical potential. Despite active research, studies to date have focused on using statistical models to predict gene expression from methylation data. In contrast, dynamical systems can be used to generate a model to predict gene expression using epigenetic data and a gene regulatory network (GRN) which can also serve as a mechanistic hypothesis. Here we present a novel stochastic dynamical systems model that predicts gene expression levels from methylation data of genes in a given GRN. We provide an evaluation of the model using real patient data and a GRN created from robust reference sources. Software for dataset preparation, model parameter fitting and prediction generation, and reporting are available at \verb|https://github.com/kordk/stoch_epi_lib|.
ACE2-lentiviral transduction enables mouse SARS-CoV-2 infection and mapping of receptor interactions

SARS-CoV-2 uses the human ACE2 (hACE2) receptor for cell attachment and entry, with mouse ACE2 (mACE2) unable to support infection. Herein we describe an ACE2-lentivirus system and illustrate its utility for in vitro and in vivo SARS-CoV-2 infection models. Transduction of non-permissive cell lines with hACE2 imparted replication competence, and transduction with mACE2 containing N30D, N31K, F83Y and H353K substitutions, to match hACE2, rescued SARS-CoV-2 replication. Intranasal hACE2-lentivirus transduction of C57BL/6J mice permitted significant virus replication in lungs. RNA-Seq analyses illustrated that the model involves an acute inflammatory disease followed by resolution and tissue repair, with a transcriptomic profile similar to that seen in COVID-19 patients. Intranasal hACE2-lentivirus transduction of IFNAR-/- and IL-28RA-/- mice lungs was used to illustrate that loss of type I or III interferon responses have no significant effect on virus replication. However, their importance in driving inflammatory responses was illustrated by RNA-Seq analyses. We also demonstrate the utility of the hACE2-lentivirus transduction system for vaccine evaluation in C57BL/6J mice. The ACE2-lentivirus system thus has broad application in SARS-CoV-2 research, providing a tool for both mutagenesis studies and mouse model development. AUTHOR SUMMARY SARS-CoV-2 uses the human ACE2 (hACE2) receptor to infect cells, but cannot infect mice because the virus cannot bind mouse ACE2 (mACE2). We use an ACE2-lentivirus system in vitro to identify four key amino acids in mACE2 that explain why SARS-CoV-2 cannot infect mice. hACE2-lentivirus was used to express hACE2 in mouse lungs in vivo, with the inflammatory responses after SARS-CoV-2 infection similar to those seen in human COVID-19. Genetically modified mice were used to show that type I and III interferon signaling is required for the inflammatory responses. We also show that the hACE2-lentivirus mouse model can be used to test vaccines. Overall this paper demonstrates that our hACE2-lentivirus system has multiple applications in SARS-CoV-2 and COVID-19 research.
ProfileView: multiple probabilistic models resolve protein families functional diversity

Sequence functional classification has become a fundamental bottleneck to the understanding of the myriad of protein sequences accumulating in our databases due to the recent progress in genomics and metagenomics. The large diversity of homologous sequences hides, in many cases, a variety of functional activities that cannot be anticipated. Their identification appears critical for a fundamental understanding of living organisms and for biotechnological applications. ProfileView is a novel computational method designed to functionally classify sets of homologous sequences. Its architecture strongly relies on the structure of biological data, and answers to the challenge of automatically partitioning datasets of protein sequences in pertinent subfamilies based on meaningful conservation patterns. It constructs a library of probabilistic models accurately representing the functional variability of protein families, and extracts biologically interpretable information from the classification process. It applies to protein families that are not necessarily large, nor conserved, whose homologs might be very divergent and for which functions should be discovered or characterised more precisely. As a proof of concept, we apply ProfileView to the Cryptochrome/Photolyase family (CPF) and to the WW domain family, two widespread classes of proteins showing a large variety of functions and high sequence divergence. Decades of experimental studies on these families, functionally characterizing sequences and highlighting constitutive motifs, allow us to validate the two functional organisations obtained with the ProfileView approach. In addition, the method allows to identify a distinct functional group for the CPF, likely corresponding to novel photoreceptors. Thus, ProfileView appears as a powerful tool to classify protein sequences by function, screen sequences towards the design of accurate functional testing experiments and, possibly, discover new functions of natural sequences. Software and data availability http://www.lcqb. upmc.fr/profileview/ A restrained access is momentarily set. Once the article is accepted, all information will be freely accessible.
FisB relies on homo-oligomerization and lipid binding to catalyze membrane fission in bacteria

Little is known about mechanisms of membrane fission in bacteria despite their requirement for cytokinesis. The only known dedicated membrane fission machinery in bacteria, fission protein B (FisB), is expressed during sporulation in Bacillus subtilis and is required to release the developing spore into the mother cell cytoplasm. Here, we characterized the requirements for FisB-mediated membrane fission. FisB forms mobile clusters of approximately 12 molecules that give way to an immobile cluster at the engulfment pole containing approximately 40 proteins at the time of membrane fission. Analysis of FisB mutants revealed that binding to acidic lipids and homo-oligomerization are both critical for targeting FisB to the engulfment pole and membrane fission. Experiments using artificial membranes and filamentous cells suggest that FisB does not have an intrinsic ability to sense or induce membrane curvature but can bridge membranes. Finally, modeling suggests that homo-oligomerization and trans-interactions with membranes are sufficient to explain FisB accumulation at the membrane neck that connects the engulfment membrane to the rest of the mother cell membrane during late stages of engulfment. Together, our results show that FisB is a robust and unusual membrane fission protein that relies on homo-oligomerization, lipid binding, and the unique membrane topology generated during engulfment for localization and membrane scission, but surprisingly, not on lipid microdomains, negative-curvature lipids, or curvature sensing.
Global organization of neuronal activity only requires unstructured local connectivity

Modern electrophysiological recordings simultaneously capture single-unit spiking activities of hundreds of neurons spread across large cortical distances. Yet, this parallel activity is often confined to relatively low-dimensional manifolds. This implies strong coordination also among neurons that are most likely not even connected. Here, we combine in vivo recordings with network models and theory to characterize the nature of mesoscopic coordination patterns in macaque motor cortex and to expose their origin: We find that heterogeneity in local connectivity supports network states with complex long-range cooperation between neurons that arises from multi-synaptic, short-range connections. Our theory explains the experimentally observed spatial organization of covariances in resting state recordings as well as the behaviorally related modulation of covariance patterns during a reach-to-grasp task. The ubiquity of heterogeneity in local cortical circuits suggests that the brain uses the described mechanism to flexibly adapt neuronal coordination to momentary demands.
Electrophysiological correlates of mood and reward dynamics in human adolescents

Despite its omnipresence in everyday interactions and its importance for mental health, mood and its neuronal underpinnings are poorly understood. Computational models can help identify parameters affecting self-reported mood during mood induction tasks. Here we test if computationally modelled dynamics of self-reported mood during monetary gambling can be used to identify trial-by-trial variations in neuronal activity. To this end, we shifted mood in healthy (N=24) and depressed (N=30) adolescents by delivering individually tailored reward prediction errors whilst recording magnetoencephalography (MEG) data. Following a pre-registered analysis, we hypothesize that expectation (defined by previous reward outcomes) would be predictive of beta-gamma oscillatory power (25-40Hz), a frequency shown to modulate to reward feedback. We also hypothesize that trial variations in the evoked response to the presentation of gambling options and in source localized responses to reward feedback. Through our multilevel statistical analysis, we found confirmatory evidence that beta-gamma power is positively related to reward expectation during mood shifts, with possible localized sources in the posterior cingulate cortex. We also confirmed reward prediction error to be predictive of trial-level variations in the response of the paracentral lobule and expectation to have an effect on the cerebellum after presentation of gambling options. To our knowledge, this is the first study to relate fluctuations in mood on a minute timescale to variations in neural oscillations with noninvasive electrophysiology. Significance Statement Brain mechanisms underlying mood and its relationship with changes in reward contingencies in the environment are still elusive but could have a strong impact on our understanding and treatment of debilitating mood disorders. Building on a previously proposed computational mood model we use multilevel statistical models to find relationship between trial-by-trial variations in model components of mood and neural responses to rewards measured with non-invasive electrophysiology (MEG). Through confirmatory analysis we show that it is possible to observe relationships between trial variations in neural responses and computational parameters describing mood dynamics. Identifying the dynamics of mood and the neural processes it affects could pave the way for more effective neuromodulation treatments.
Recovery of high-quality assembled genomes via metagenome binning guided with single-cell amplified genomes

Background Obtaining high-quality (HQ) reference genomes from microbial communities is crucial for understanding the phylogeny and function of uncultured microbes in complex microbial ecosystems. Despite the improved bioinformatic approaches to generate curated metagenome-assembled genomes (MAGs), existing metagenomic binners often fail to obtain reliable MAGs, and thus, they are nowhere comparable to genomes sequenced from isolates in terms of strain level resolution. Here, we present a single-cell genome-guided metagenome binning (MetaSAG) to reconstruct the strain-resolved genomes from microbial communities at once. Results MetaSAG employs single-cell amplified genomes (SAGs) generated with microfluidic technology as binning guides to recover improved draft genomes with the metagenomic data. To assess the performance of reconstructing genomes from various microbial communities, we compared MetaSAG with four conventional metagenomic binners using a cell mock community, human gut microbiota, and skin microbiota samples. MetaSAG showed precise contig binning and higher recovery rates (>97%) of rRNA and plasmids compared to conventional binners in genome reconstruction from the cell mock community. In human microbiota samples, MetaSAG recovered the largest number of genomes with a total of 103 gut microbial genomes (21 HQ and 65 showed >90% completeness) and 45 skin microbial genomes (10 HQ and 40 showed >90% completeness), respectively. Conventional binners recovered one Staphylococcus hominis genome, whereas MetaSAG recovered two S. hominis genomes from the identical skin microbiota sample. Single-cell sequencing indicated that these S. hominis genomes clearly derived from two distinct strains harboring specifically different plasmids. We found that all conventional S. hominis MAGs had substantial lack or excess of the genome sequences and contamination of other Staphylococcus bacteria (S. epidermidis). Conclusions MetaSAG enabled us to obtain the strain-resolved genomes in the mock community and human microbiota samples by assigning metagenomic sequences correctly and covering both highly conserved genes such as rRNA genes and unique extrachromosomal elements, including plasmids. MetaSAG will provide HQ genomes that are difficult to obtain with metagenomic analyses alone and will facilitate the understanding of microbial ecosystems by elucidating detailed metabolic pathways and horizontal gene transfer networks through microbial genomes. MetaSAG is available at https://github.com/kojiari/metasag.
Etkisi The Effect of Stress Perceived by Adults Due to the COVID-19 Pandemic on Their Sleep Quality

respiratory system and causes many diseases and deaths, and has the ability to infect humans by transmitting from animals (1). An outbreak of not fully known etiology that manifest itself with pneumonia was reported to have started in Wuhan city, Hubei Province, China in late December of 2019 (2). On March 11th, 2020, the World Health Organization (WHO) declared the CoV disease-2019 (COVID-19) outbreak caused