Miracle-dz/UniFAR-FTUs huggingface dataset:
OPTIMIZATION OF ENANTIOSEPARATION OF 2,6-DIKETOPIPERAZINE DERIVATIVES WITH β-CYCLODEXTRIN AND HYDROXY ACIDS AS COMPONENTS OF MOBILE PHASE IN LIQUID CHROMATOGRAPHY

A novel method for a direct separation of the enantiomers of 2,6-diketopiperazine derivatives was devised. The enantiomers were separated by means of chromatography on reversed-phase (RP-HPLC) column with β-cyclodextrin as a chiral mobile phase additive and hydroxy acids as solubility enhancers. The effect of β-cyclodextrin concentration, hydroxy acids type on retention, and enantioseparation were investigated. It was found that the systems with high concentrations of β-cyclodextrin in the presence of hydroxy acids, especially DL-tartaric acid, improve enantioselectivity, while the presence of citric acid aggravates it.
Assembly principles and stoichiometry of a complete human kinetochore module

Biochemical reconstitution of human kinetochore delivers complexes with all subunits in the expected stoichiometry. Centromeres are epigenetically determined chromosomal loci that seed kinetochore assembly to promote chromosome segregation during cell division. CENP-A, a centromere-specific histone H3 variant, establishes the foundations for centromere epigenetic memory and kinetochore assembly. It recruits the constitutive centromere-associated network (CCAN), which in turn assembles the microtubule-binding interface. How the specific organization of centromeric chromatin relates to kinetochore assembly and to centromere identity through cell division remains conjectural. Here, we break new ground by reconstituting a functional full-length version of CENP-C, the largest human CCAN subunit and a blueprint of kinetochore assembly. We show that full-length CENP-C, a dimer, binds stably to two nucleosomes and permits further assembly of all other kinetochore subunits in vitro with relative ratios closely matching those of endogenous human kinetochores. Our results imply that human kinetochores emerge from clustering multiple copies of a fundamental module and may have important implications for transgenerational inheritance of centromeric chromatin.
Bakers' yeast: an environment benign catalyst for the one-pot synthesis of indolyl chromenes and bisindolyl alkanes

A green protocol for one-pot synthesis of pharmacologically important indolyl chromenes and bis(indolyl)alkanes was achieved using Saccharomyces cerevisiae (commonly known as bakers' yeast) as catalyst under room temperature stirring condition. This method is relatively simple, efficient, inexpensive, and environment-friendly.
A functional-structural connectivity metric detects ipsilateral connections with distinct functional specialisation in each hemisphere

We introduce a connectomics metric that integrates information on structural connectivity (SC) from diffusion MRI tractography and functional connectivity (FC) from resting-state functional MRI, at individual subject level. The metric is based on the ability of SC to broadly predict FC using a simple linear predictive model; for each connection in the brain, the metric quantifies the deviation from that model. For the metric to capture underlying physiological properties, we minimise systematic measurement errors and processing biases in both SC and FC, and address several challenges with the joint analysis. This also includes a data-driven normalisation approach. The combined metric may provide new information by indirectly assessing white matter structural properties that cannot be inferred from diffusion MRI alone, and/or complex interregional neural interactions that cannot be inferred from functional MRI alone. To demonstrate the utility of the metric, we used young adult data from the Human Connectome Project to examine all bilateral pairs of ipsilateral connections, i.e. each left-hemisphere connection in the brain was paired with its right-hemisphere homologue. We detected a minority of bilateral pairs where the metric value is significantly different across hemispheres, which we suggest reflects cases of ipsilateral connections that have distinct functional specialisation in each hemisphere. The pairs with significant effects spanned all cortical lobes, and also included several cortico-subcortical connections. Our findings highlight the potential in a joint analysis of structural and functional measures of connectivity, both for clinical applications and to help in the interpretation of results from standard functional connectivity analysis. Significance Statement Based on the notion that structure predicts function, the scientific community sought to demonstrate that structural information on fibre bundles that connect brain regions is sufficient to estimate the strength of interregional interactions. However, an accurate prediction using MRI has proved elusive. This paper posits that the failure to predict function from structure originates from limitations in measurement or interpretation of either diffusion MRI (to assess fibre bundles), fMRI (to assess functional interactions), or both. We show that these limitations can be nevertheless beneficial, as the extent of divergence between the two modalities may reflect hard-to-measure properties of interregional connections, such as their functional role in the brain. This provides many insights, including into the division of labour between hemispheres.
Adsorption of Silver Nanoparticles on Glass Beads Surface

Colloidal silver is widely used owing to its specific properties, which enable it to be applied in various fields. In this work, adsorption of commercially available silver nanoparticles (AgNPs; NanoSilver PVP 1000) on glass beads was investigated. The glass microspheres (70–110 μm) were used as model particles. The adsorption of AgNPs on the glass beads surface was investigated in terms of adsorbent dosage. The adsorption isotherm was determined with the adsorbent dosage of 100 g/l and the AgNPs in range 100–1000 mg/l. It was found that adsorption isotherm data best fitted the Langmuir model. Kinetics of AgNPs adsorption onto glass beads followed a pseudo-second-order model. The interaction between glass microspheres surface and polyvinylpyrrolidone (PVP)-coated AgNPs is due to hydrogen bonding with oxygen of carbonyl groups of PVP and silanol groups on the glass surface.
Recognition of Z-RNA by ADAR1 limits interferon responses

Nucleic acids are powerful triggers of innate immunity and can adopt the unusual Z-conformation. The p150 isoform of adenosine deaminase acting on RNA 1 (ADAR1) prevents aberrant interferon (IFN) induction and contains a Z-nucleic acid binding (Zα) domain. We report that knock-in mice bearing two point mutations in the Zα domain of ADAR1, which abolish binding to Z-form nucleic acids, spontaneously induced type I IFNs and IFN-stimulated genes (ISGs) in multiple organs. This included the lung where both stromal and haematopoietic cells displayed ISG induction in Adar1mZα/mZα mice. Concomitantly, Adar1mZα/mZα mice showed improved control of influenza A virus. The spontaneous IFN response in Adar1mZα/mZα mice required MAVS, implicating cytosolic RNA sensing. Finally, analysis of A-to-I changes revealed a specific requirement of ADAR1’s Zα domain in editing of a subset of RNAs. In summary, our results reveal that endogenous RNAs in Z-conformation have immunostimulatory potential that is curtailed by ADAR1.
Bridging neuronal correlations and dimensionality reduction

Two commonly used approaches to study interactions among neurons are spike count correlation, which describes pairs of neurons, and dimensionality reduction, applied to a population of neurons. While both approaches have been used to study trial-to-trial correlated neuronal variability, they are often used in isolation and have not been directly related. We first established concrete mathematical and empirical relationships between pairwise correlation and metrics of population-wide covariability based on dimensionality reduction. Applying these insights to macaque V4 population recordings, we found that the previously reported decrease in mean pairwise correlation associated with attention stemmed from three distinct changes in population-wide covariability. Overall, our work builds the intuition and formalism to bridge between pairwise correlation and population-wide covariability and presents a cautionary tale about the inferences one can make about population activity by using a single statistic, whether it be mean pairwise correlation or dimensionality.
Parental feeding preferences rather than sibling competition determine the death of smaller nestlings in asynchronous broods

Hatching asynchrony is a reproductive tactic that, through the creation of competitive hierarchies among offspring, allows parents for a quick adjustment of brood size via the death of smaller nestlings. This strategy is considered to be adaptive in case of unpredictable and/or poor environments in which it would guarantee that at least larger nestlings will fledge. Brood reduction is the usual outcome in asynchronously hatched broods since first-hatched nestlings are larger and get a disproportionately larger share of the food delivered by parents, often leading the youngest nestling to starve to death soon after hatching. However, we still do not know the proximate mechanisms of such brood reduction. One possibility is that the smallest nestling is not fed because larger nestlings outcompete it, which implies that nestlings control resource allocation. Alternatively, parents might actively ignore the persistent begging from their smallest nestling, which would involve that parents control food allocation. To determine whether parents or nestlings ultimately induce brood reduction in this situation, we experimentally created asynchronous broods of Eurasian blackbird (Turdus merula) nestlings and quantified food allocation by parents in two different situations: when sibling competition was allowed and, alternatively, when competition was prevented by physically separating nestlings within the nests by using wooden barriers. Our results showed that experimentally introduced smaller nestlings received less food than their larger nestmates both when competition among nestlings was allowed and when it was prevented. When adult males and females are considered separately, males fed the smallest nestling less often regardless of whether sibling competition was allowed or not, but adult females showed no differences. We can conclude that the smallest nestling starves mainly because parents actively ignore its begging. The higher competitive ability of the larger nestlings seem to have little effect given that although the smallest nestling is fed at a higher rate when physical interactions are prevented by the wooden barrier than when not, this difference is not significant. These findings suggest that parents rather than nestlings have the main control over food allocation.
SARS-CoV-2 in Brazil: analysis of molecular variance and genetic diversity in viral haplotypes found in the states of Rio de Janeiro, São Paulo, Paraná and Tocantins

In this work, 18 sequences of the SARS-CoV-2 virus were used, from four Brazilian states (Rio de Janeiro, São Paulo, Paraná and Tocantins) with 09, 04, 04, 8 and 01 haplotypes, respectively, with lengths ranging from 234 to 29,903 bp. All sequences were publicly available on the National Biotechnology Information Center (NCBI) platform and were previously aligned with the MEGA X software, where all gaps and ambiguous sites were extracted for the construction of the phylogenetic tree. Of the 301 sites analyzed, 68% varied, 131 of which were parsimonium-informative sites. Phylogenetic analyses revealed the presence of two distinct subgroups, corroborated by the high FST (80%). The high degree of polymorphism found among these samples helped to establish a clear pattern of non-genetic structuring, based on the time of divergence between the groups. All molecular variance estimators confirmed that there was no consensus in the conservation of the studied sequences, also indicating a high variation for the protein products of the virus. In a highly miscegenational and diverse population such as the Brazilian population, this observation draws our attention to the need for an urgent increase in public health actions, awareness strategies, hygiene and distancing practices and not the other way around.
Array of bright silicon-vacancy centers in diamond fabricated by low-energy focused ion beam implantation

Among promising color centers for single-photon sources in diamond, the negatively charged silicon-vacancy (SiV−) has 70% of its emission to the zero-phonon line (ZPL), in contrast to the negatively charged nitrogen vacancy (NV−), which has a broad spectrum. Fabricating single centers of useful defect complexes with high yield and excellent grown-in defect properties by ion implantation has proven to be challenging. We have fabricated bright single SiV− centers by 60-keV focused ion beam implantation and subsequent annealing at 1000 °C with high positioning accuracy and a high yield of 15%.
Four-Dimensional Sparse Bayesian Tensor Decomposition for Gene Expression Data

Disease etiology may be better understood through the study of gene expression in four dimensional (4D) experiments that consist of measurements on multiple individuals, genes, tissues and under multiple conditions or through time. We have developed a sparse Bayesian four dimensional tensor decomposition method aimed at uncovering latent components or gene networks that could be linked to genetic variation. We used a Variational Bayes algorithm to fit the model which provides fast and accurate analysis. In this brief note we illustrate the utility of the method using simulated datasets, and show that when 4D data is available our method shows improved performance in estimating the true structure in the dataset, when compared to using a 3D method on a single slice of the 4D dataset. We also compare the results of the 4D method to that of the 3D method on a suitable unfolding of the dataset, demonstrating that similar performance is observed in this case, while the 4D method accurately recovers the additional structure in the data. We provide software that implements the method in R.
Exploring Binary Relations for Ontology Extension and Improved Adaptation to Clinical Text

Background The controlled domain vocabularies provided by ontologies make them an indispensable tool for text mining. Ontologies also include semantic features in the form of taxonomy and axioms, which make annotated entities in text corpora useful for semantic analysis. Extending those semantic features may improve performance for characterisation and analytic tasks. Ontology learning techniques have previously been explored for novel ontology construction from text, though most recent approaches have focused on literature, with applications in information retrieval or human interaction tasks. We hypothesise that extension of existing ontologies using information mined from clinical narrative text may help to adapt those ontologies such that they better characterise those texts, and lead to improved classification performance. Results We develop and present a framework for identifying new classes in text corpora, which can be integrated into existing ontology hierarchies. To do this, we employ the Stanford Open Information Extraction algorithm and integrate its implementation into the Komenti semantic text mining framework. To identify whether our approach leads to better characterisation of text, we present a case study, using the method to learn an adaptation to the Disease Ontology using text associated with a sample of 1,000 patient visits from the MIMIC-III critical care database. We use the adapted ontology to annotate and classify shared first diagnosis on patient visits with semantic similarity, revealing an improved performance over use of the base Disease Ontology on the set of visits the ontology was constructed from. Moreover, we show that the adapted ontology also improved performance for the same task over two additional unseen samples of 1,000 and 2,500 patient visits. Conclusions We report a promising new method for ontology learning and extension from text. We demonstrate that we can successfully use the method to adapt an existing ontology to a textual dataset, improving its ability to characterise the dataset, and leading to improved analytic performance, even on unseen portions of the dataset.
A Small-Scale shRNA Screen in Primary Mouse Macrophages Identifies a Role for the Rab GTPase Rab1b in Controlling Salmonella Typhi Growth

Salmonella Typhi, the causative agent of typhoid fever, a life-threatening systemic infection, is a human restricted bacterial pathogen. A fundamental aspect of S. Typhi pathogenesis is its ability to survive in human macrophages but not in macrophages from other animals (i.e. mice). Despite the importance of macrophages in establishing systemic S. Typhi infection, the mechanisms that macrophages use to control the growth of S. Typhi and the role of these mechanisms in the bacterium’s adaptation to the human host are mostly unknown. To facilitate unbiased identification of genes involved in controlling the growth of S. Typhi in macrophages, we report optimized experimental conditions required to perform loss-of function pooled shRNA screens in primary mouse bone-marrow derived macrophages. Following infection with a fluorescently-labeled S. Typhi, cells defective in genes important for controlling S. Typhi growth (and therefore unable to kill S. Typhi) are sorted based on the intensity of fluorescence (i.e. number of intracellular fluorescent bacteria). shRNAs enriched in the fluorescent population are identified by next-generation sequencing. A proof-of-concept screen targeting the mouse Rab GTPases confirmed Rab32 as important to restrict S. Typhi in mouse macrophages. Interestingly and rather unexpectedly, this screen also revealed that Rab1b controls S. Typhi growth in mouse macrophages. This constitutes the first report of a Rab GTPase other than Rab32 involved in S. Typhi host-restriction. The methodology described here should allow genome-wide screening to identify mechanisms controlling the growth of S. Typhi and other intracellular pathogens in primary immune cells.
Historical and cross-disciplinary trends in the biological and social sciences reveal an accelerating adoption of advanced analytics

Methods for data analysis in the biomedical, life and social sciences are developing at a rapid pace. At the same time, there is increasing concern that education in quantitative methods is failing to adequately prepare students for contemporary research. These trends have led to calls for educational reform to undergraduate and graduate quantitative research method curricula. We argue that such reform should be based on data-driven insights into within- and cross-disciplinary use of research methods. Our survey of peer-reviewed literature screened ∼3.5 million openly available research articles to monitor the cross-disciplinary usage of research methods in the past decade. We applied data-driven text-mining analyses to the methods and materials section of a large subset of this corpus to identify method trends shared across disciplines, as well as those unique to each discipline. As a whole, usage of T-test, analysis of variance, and other classical regression-based methods has declined in the published literature over the past 10 years. Machine-learning approaches, such as artificial neural networks, have seen a significant increase in the total share of scientific publications. We find unique groupings of research methods associated with each biomedical, life and social science discipline, such as the use of structural equation modeling in psychology, survival models in oncology, and manifold learning in ecology. We discuss the implications of these findings for education in statistics and research methods, as well as within- and cross-disciplinary collaboration.
An experimental assessment of the distribution of environmental DNA along the water column

The study of environmental DNA (eDNA) is increasingly becoming a valuable tool to survey and monitor aquatic communities. However, there are important gaps in our understanding of the dynamics governing the distribution of eDNA under natural conditions. In this report we carry out controlled experiments to assess the extent and timing of eDNA distribution along the water column. A sample of known eDNA concentration was placed at the bottom of a 5-m high tube (20 cm in diameter and total volume of 160 L), and water samples were obtained at different depths over an 8 h-period. The presence of the target eDNA was assessed by qPCR analysis. This sampling protocol allowed for assessing the timescale for the diffusion of eDNA while minimizing the influence of turbulence. We demonstrate that, after a time-period of as little as 30 min, the eDNA had spread across the entire container. The implications of these results for eDNA sampling protocols in the field are discussed.
Characterization of genetic diversity and population structure within Staphylococcus chromogenes by multilocus sequence typing

Staphylococcus chromogenes is a common skin commensal in cattle and has been identified as a frequent cause of bovine mastitis and intramammary infections. To better understand the extent of strain diversity within this species and to facilitate study of strain variation as a factor in pathogenicity, we have developed a seven locus Multilocus Sequence Typing (MLST) scheme. The scheme was tested on 120 isolates collected from three geographic locations, Vermont and Washington State in the United States and Belgium. A total of 46 sequence types (STs) were identified with most of the STs being location specific. The utility of the typing scheme is indicated by a discrimination power of 95.6% for all isolates and greater than 90% for isolates from each of the three locations. Phylogenetic analysis placed 39 of the 46 STs into single core group consistent with a common genetic lineage; the STs in this group differ by less than 0.5% at the nucleotide sequence level. Most of the diversification in this lineage group can be attributed to mutation; recombination plays a limited role. This lineage group includes two clusters of single nucleotide variants in starburst configurations indicative of recent clonal expansion; nearly 50% of the isolates sampled in this study are in these two clusters. The remaining seven STs were set apart from the core group by having alleles with highly variable sequences at one or more loci. Recombination had a higher impact than mutation in the diversification of these outlier STs. Alleles with hypervariable sequences were detected at five of the seven loci used in the MLST scheme; the average sequence distances between the hypervariable alleles and the common core alleles ranged from 12 to 34 nucleotides. The extent of these sequence differences suggests the hypervariable alleles may be remnants of an ancestral genotype.
A secreted endoribonuclease ENDU-2 from the soma protects germline immortality in C. elegans

Multicellular organisms coordinate tissue specific response to environmental information via both cell-autonomous and non-autonomous mechanisms. In addition to secreted ligands, secreted small RNAs have recently been reported to regulate gene expression across tissue boundaries. Here we show that the conserved poly-U specific endoribonuclease ENDU-2 is secreted from the soma and taken-up by the germline to ensure germline immortality at elevated temperature in C. elegans. ENDU-2 binds to mature mRNAs and negatively regulates mRNA abundance both in the soma and the germline. While ENDU-2 promotes RNA decay in the soma directly via its endoribonuclease activity, ENDU-2 prevents misexpression of soma-specific genes in the germline and preserves germline immortality independent of its RNA-cleavage activity. In summary, our results suggest that the secreted RNase ENDU-2 transmits environmental information across tissue boundaries and contributes to maintenance of stem cell immortality probably via retaining a stem cell specific program of gene expression.