bluuebunny/crossref_metadata_2025_split huggingface dataset:
Accounting for stimulations that do not elicit motor-evoked potentials when mapping cortical representations of multiple muscles
Authors: Jin Fang , Bruijn Sjoerd M , Daffertshofer Andreas 
Published: July 2021

AbstractThe representation of muscles in the cortex can be mapped using navigated transcranial magnetic stimulation. The mapping can be quantified via measures like the centre of gravity or the size of the region of excitability. Determining these measures typically relies only on stimulation points that yield motor-evoked potentials (MEPs); stimulations that do not elicit an MEP, i.e., non-MEP points, are ignored entirely. In this study, we show how incorporating non-MEP points may affect the estimates of the size and centroid of the excitable area in eight hand and forearm muscles after mono-phasic single-pulse TMS. We performed test-retest assessments in twenty participants and estimated the reliability of centroids and sizes of the corresponding areas using inter-class correlation coefficients. For most muscles, the reliability turned out good, if not excellent. As expected, removing the non-MEP points significantly decreased area sizes and area weights, suggesting that conventional approaches that do not account for non-MEP points are likely to overestimate the regions of excitability.
The transcriptional cofactor IRF2BP2 plays a key role in T cell homeostasis and Treg cell expansion
Authors: Mognol Giuliana P. , Oliveira-Vieira Barbara , Pinheiro-Rosa Natalia , Peixoto Barbara C. , Boroni Marianna , González-Avalos Edahi , Secca Cristiane , Bandukwala Hozefa , Faria Ana Maria C. , Rao Anjana , Viola João P.B. 
Published: July 2021

AbstractThe levels of the co-transcriptional regulator IRF2BP2 (Interferon Regulatory Factor-2 Binding Protein-2) decrease with T cell activation and, when ectopically expressed, it reduces T cell proliferation. To further characterize the function of IRF2BP2 in T cell responses in vivo, we generated a conditional transgenic knock-in mouse that overexpresses IRF2BP2 in T lymphocytes. Overexpression of IRF2BP2 leads to a reduction in the T cell compartment of naive animals, upregulation of Foxp3 and Ifng; an increase in the frequency of regulatory T cells (Tregs), a preferential Th1 differentiation with increase of IFN-γ production and a reduction of T cell proliferation, suggesting a disruption in T cell homeostasis. Interestingly, knock-in mice displayed reduced clinical and inflammatory signs of Experimental Autoimmune Encephalomyelitis (EAE) when compared to the control mice, with an augmented frequency of Treg cells. Altogether, our findings indicate that IRF2BP2 might help to control exacerbated T cell responses and point to a role for IRF2BP2 in preventing T cell autoimmunity.
Semaphorin 3C exacerbates liver fibrosis
Authors: De Angelis Rigotti Francesca , Wiedmann Lena , Hubert Max Ole , Vacca Margherita , Hasan Sana S. , Moll Iris , Carvajal Silvia , Jiménez Wladimiro , Starostecka Maja , Billeter Adrian T , Müller-Stich Beat , Wolff Gretchen , Ekim-Üstünel Bilgen , Herzig Stephan , Mogler Carolin , Fischer Andreas , Rodriguez-Vita Juan 
Published: July 2021

AbstractBackground & AimsChronic liver disease is a growing epidemic leading to fibrosis and cirrhosis. TGF-β is the pivotal pro-fibrogenic cytokine which activates hepatic stellate cells (HSC), yet, other molecules can substantially modulate TGF-β signaling in the course of liver fibrosis. Expression of the axon guidance molecules Semaphorins (SEMAs), which signal through Plexins and Neuropilins (NRPs), have been associated with liver fibrosis in HBV-induced chronic hepatitis. This study aims at determining their function in the regulation of HSCs.Approach & ResultsWe analyzed publicly available patient databases and liver biopsies. We employed transgenic mice where genes are deleted only in activated HSCs to perform ex vivo analysis and animal models. SEMA3C is the most enriched member of the Semaphorin family in liver samples from cirrhotic patients. Higher expression of SEMA3C in patients with NASH, alcoholic hepatitis or HBV-induced hepatitis discriminates those with a more pro-fibrotic transcriptomic profile. SEMA3C expression is also elevated in different mouse models of liver fibrosis and in isolated HSCs upon activation. In keeping with this, deletion of SEMA3C in activated HSCs reduces myofibroblast marker expression. Conversely, SEMA3C overexpression exacerbates TGF-β-mediated myofibroblast activation, as shown by increased SMAD2 phosphorylation and target gene expression. Among SEMA3C receptors, only NRP2 expression is maintained upon activation of isolated HSCs. Interestingly, lack of NRP2 in those cells reduces myofibroblast marker expression. Finally, deletion of either SEMA3C or NRP2, specifically in activated HSCs, reduces liver fibrosis in mice.ConclusionSEMA3C is a novel marker for activated HSCs that plays a fundamental role in the acquisition of the myofibroblastic phenotype and liver fibrosis.
Artificial Neural Networks for classification of single cell gene expression
Authors: Zhong Jiahui , Lyu Minjie , Jin Huan , Cao Zhiwei , Chitkushev Lou T. , Zhang Guanglan , Keskin Derin B. , Brusic Vladimir 
Published: July 2021

AbstractBackgroundSingle-cell transcriptome (SCT) sequencing technology has reached the level of high-throughput technology where gene expression can be measured concurrently from large numbers of cells. The results of gene expression studies are highly reproducible when strict protocols and standard operating procedures (SOP) are followed. However, differences in sample processing conditions result in significant changes in gene expression profiles making direct comparison of different studies difficult. Unsupervised machine learning (ML) uses clustering algorithms combined with semi-automated cell labeling and manual annotation of individual cells. They do not scale up well and a workflow used on a specific dataset will not perform well with other studies. Supervised ML classification shows superior classification accuracy and generalization properties as compared to unsupervised ML methods. We describe a supervised ML method that deploys artificial neural networks (ANN), for 5-class classification of healthy peripheral blood mononuclear cells (PBMC) from multiple diverse studies.ResultsWe used 58 data sets to train ANN incrementally – over ten cycles of training and testing. The sample processing involved four protocols: separation of PBMC, separation of PBMC + enrichment (by negative selection), separation of PBMC + FACS, and separation of PBMC + MACS. The training data set included between 85 and 110 thousand cells, and the test set had approximately 13 thousand cells. Training and testing were done with various combinations of data sets from four principal data sources. The overall accuracy of classification on independent data sets reached 5-class classification accuracy of 94%. Classification accuracy for B cells, monocytes, and T cells exceeded 95%. Classification accuracy of natural killer (NK) cells was 75% because of the similarity between NK cells and T cell subsets. The accuracy of dendritic cells (DC) was low due to very low numbers of DC in the training sets.ConclusionsThe incremental learning ANN model can accurately classify the main types of PBMC. With the inclusion of more DC and resolving ambiguities between T cell and NK cell gene expression profiles, we will enable high accuracy supervised ML classification of PBMC. We assembled a reference data set for healthy PBMC and demonstrated a proof-of-concept for supervised ANN method in classification of previously unseen SCT data. The classification shows high accuracy, that is consistent across different studies and sample processing methods.
Targeted resurrection of chromosomal arm 1RS in two elite wheat lines with 1BL/1RS translocation for improved end-use quality
Authors: Kaur Ramandeep , Dhillon Guriqbal Singh , Kaur Amandeep , Kaur Sarabjit , Kaur Puneetinder , Kaur Diljot , Kumar Aman , Singh Rohtas , Mavi Gurvinder Singh , Grewal Satvir Kaur , Chhuneja Parveen , Kaur Satinder 
Published: July 2021

Abstract1BL/1RS translocation is widely used around the world to enhance wheat yield potential, resistance to various diseases, and adaptation. However, the translocation is combined with inherent quality problems associated with reduced dough strength and dough stickiness due to the presence ofSec-1on proximal end and absence ofGluB3/GliB1on distal end. Two NILs, one carrying the distal (1RSRW) and the other carrying the proximal (1RSWR) fragment from 1BS, in background of Pavon were used for transferring these two loci in yellow rust resistant version of two elite wheat varieties PBW550+Yr5and DBW17+Yr5. Foreground and background marker assisted selection was done for theSec-1-andGluB3+ alongwithLr26/Yr9/Sr31,Pm8and 1RS loci in the advancing generation. BC2F5:6NILs with absence ofSecalinand presence ofGluB3/GliB1loci were evaluated for two years in replicated yield trial. A positive correlation of thousand grain weight (TGW), harvest index (HI), and tiller number per meter (TNpM) with yield (YD) with significant GxE effect was observed. Further multivariate analysis of these traits contributed maximum to the effective yield. Thirty promising NILs were identified withSec-1-/GluB3+alongwith with high yield contributing parameters.
Deficiency in cytosine DNA methylation leads to high chaperonin expression and tolerance to aminoglycosides in Vibrio cholerae
Authors: Carvalho André , Mazel Didier , Baharoglu Zeynep 
Published: July 2021

ABSTRACTAntibiotic resistance has become a major global issue. Understanding the molecular mechanisms underlying microbial adaptation to antibiotics is of keen importance to fight Antimicrobial Resistance (AMR). Aminoglycosides are a class of antibiotics that target the small subunit of the bacterial ribosome, disrupting translational fidelity and increasing the levels of misfolded proteins in the cell. In this work, we investigated the role of VchM, a DNA methyltransferase, in the response of the human pathogen Vibrio cholerae to aminoglycosides. VchM is a V. cholerae specific orphan m5C DNA methyltransferase that generates cytosine methylation at 5′-RCCGGY-3′ motifs. We show that deletion of vchM, although causing a growth defect in absence of stress, allows V. cholerae cells to cope with aminoglycoside stress at both sub-lethal and lethal concentrations of these antibiotics. Through transcriptomic and genetic approaches, we show that groESL-2 (a specific set of chaperonin-encoding genes located on the second chromosome of V. cholerae), are upregulated in cells lacking vchM and are needed for the tolerance of vchM mutant to lethal aminoglycoside treatment, likely by fighting aminoglycoside-induced misfolded proteins. Interestingly, preventing VchM methylation of the four RCCGGY sites located in groESL-2 region, leads to a higher expression of these genes in WT cells, showing that VchM modulates the expression of these chaperonins in V. cholerae directly through DNA methylation.AUTHOR SUMMARYBacteria are organisms with a remarkable ability to adapt to several stress conditions, including to the presence of antibiotics. The molecular mechanisms underlying such adaptation lead, very often, to phenomena like antimicrobial tolerance and resistance, responsible for the frequent failure of antibiotic treatment. The study of these molecular mechanisms is thus an important tool to understand development of antimicrobial resistance in bacteria. In this work, we show that abrogating cytosine DNA methylation in Vibrio cholerae increases its tolerance to aminoglycosides, a class of antibiotics that cause protein misfolding. DNA methylation is known to affect gene expression and regulate several cellular processes in bacteria. Here we provide evidence that DNA methylation also has a more direct role in controlling antibiotic susceptibility in bacteria. Consequently, the study of bacterial DNA methyltransferases and DNA methylation should not be overlooked when addressing the problem of antimicrobial tolerance/resistance.
Small extracellular vesicles from young mice prevent frailty, improve healthspan and decrease epigenetic age in old mice
Authors: Sanz-Ros Jorge , Mas-Bargues Cristina , Monleón Daniel , Gordevicius Juozas , Brooke Robert T. , Dromant Mar , Derevyanko Aksinya , Guío-Carrión Ana , Román-Domínguez Aurora , Romero-García Nekane , Inglés Marta , Blasco María A. , Horvath Steve , Viña Jose , Borrás Consuelo 
Published: July 2021

SummaryAging is associated with an increased risk of frailty, disability, comorbidities, institutionalization, falls, fractures, hospitalization, and mortality. Searching for strategies to delay the degenerative changes associated with aging and frailty is interesting. We treated old animals intravenously with small extracellular vesicles (sEVs) derived from adipose mesenchymal stem cells (ADSCs) of young animals, and we found an improvement of several functional parameters usually altered with aging, such as motor coordination, grip strength, fatigue resistance, fur regeneration, and renal function. Frailty index analysis showed that 40% of old control mice were frail, whereas none of the old ADSCs-sEVs treated mice were. Molecular and structural benefits in muscle and kidney accompanied this functional improvement. ADSCs-sEVs induced pro-regenerative effects and a decrease in oxidative stress, inflammation, and senescence markers. Moreover, predicted epigenetic age was lower in tissues of old mice treated with ADSCs-sEVs and their metabolome changed to a youth-like pattern. Finally, we gained some insight into the miRNAs contained in sEVs that might be, at least in part, responsible for the effects observed. We propose that young sEVs treatment can be beneficial against frailty and therefore can promote healthy aging.
Detection and Spatiotemporal analysis of in-vitro 3D migratory Triple-Negative Breast cancer cells
Authors: Dimitriou Nikolaos M. , Flores-Torres Salvador , Kinsella Joseph Matthew , Mitsis Georgios D. 
Published: July 2021

AbstractThe invasion of cancer cells into the surrounding tissues is one of the hallmarks of cancer. However, a precise quantitative understanding of the spatiotemporal patterns of cancer cell migration and invasion still remains elusive. A promising approach to investigate these patterns are 3D cell cultures, which provide more realistic models of cancer growth compared to conventional 2D monolayers. Quantifying the spatial distribution of cells in these 3D cultures yields great promise for understanding the spatiotemporal progression of cancer. In the present study, we present an image processing and segmentation pipeline for the detection of 3D GFP-fluorescent Triple-Negative Breast Cancer cell nuclei, and we perform quantitative analysis of the formed spatial patterns and their temporal evolution. The performance of the proposed pipeline was evaluated using experimental 3D cell culture data, and was found to be comparable to manual segmentation, outperforming four alternative automated methods. The spatiotemporal statistical analysis of the detected distributions of nuclei revealed transient, non-random spatial distributions that consisted of clustered patterns across a wide range of neighbourhood distances, as well as dispersion for larger distances. Overall, the implementation of the proposed framework revealed the spatial organization of cellular nuclei with improved accuracy, providing insights into the 3 dimensional inter-cellular organization and its progression through time.
Large herbivorous wildlife and livestock differentially influence the relative importance of different sources of carbon for riverine food webs
Authors: Masese Frank O. , Fuss Thomas , Bistarelli Lukas Thuile , Buchen-Tschiskale Caroline , Singer Gabriel 
Published: July 2021

AbstractIn many regions around the world, large populations of native wildlife have declined or been replaced by livestock grazing areas and farmlands, with consequences on terrestrial-aquatic ecosystems connectivity and trophic resources supporting food webs in aquatic ecosystems. The river continuum concept (RCC) and the riverine productivity model (RPM) predict a shift of carbon supplying aquatic food webs along the river: from terrestrial inputs in low-order streams to autochthonous production in mid-sized rivers. Here, we studied the influence of replacing large wildlife (mainly hippos) with livestock on the relative importance of C3 vegetation, C4 grasses and periphyton on macroinvertebrates in the Mara River, which is an African montane-savanna river known to receive large subsidy fluxes of terrestrial carbon and nutrients mediated by LMH, both wildlife and livestock. Using stable carbon (δ13C) and nitrogen (δ15N) isotopes, we identified spatial patterns of the relative importance of allochthonous carbon from C3 and C4 plants (woody vegetation and grasses, respectively) and autochthonous carbon from periphyton for macroinvertebrates at various sites of the Mara River and its tributaries. Potential organic carbon sources and invertebrates were sampled at 80 sites spanning stream orders 1 to 7, various catchment land uses (forest, agriculture and grasslands) and different loading rates of organic matter and nutrients by LMH (livestock and wildlife, i.e., hippopotamus). The importance of different sources of carbon along the river did not follow predictions of RCC and RPM. First, the importance of C3 and C4 carbon was not related to river order or location along the fluvial continuum but to the loading of organic matter (dung) by both wildlife and livestock. Notably, C4 carbon was important for macroinvertebrates even in large river sections inhabited by hippos. Second, even in small 1st −3rd order forested streams, autochthonous carbon was a major source of energy for macroinvertebrates, and this was fostered by livestock inputs fuelling aquatic primary production throughout the river network. Importantly, our results show that replacing wildlife (hippos) with livestock shifts river systems towards greater reliance on autochthonous carbon through an algae-grazer pathway as opposed to reliance on allochthonous inputs of C4 carbon through a detrital pathway.
Modeling memory T cell states at single-cell resolution identifies in vivo state-dependence of eQTLs influencing disease
Authors: Nathan Aparna , Asgari Samira , Ishigaki Kazuyoshi , Amariuta Tiffany , Luo Yang , Beynor Jessica I. , Baglaenko Yuriy , Suliman Sara , Price Alkes , Lecca Leonid , Murray Megan B. , Moody D. Branch , Raychaudhuri Soumya 
Published: July 2021

AbstractMany non-coding genetic variants cause disease by modulating gene expression. However, identifying these expression quantitative trait loci (eQTLs) is complicated by gene-regulation differences between cell states. T cells, for example, have fluid, multifaceted functional states in vivo that cannot be modeled in eQTL studies that aggregate cells. Here, we modeled T cell states and eQTLs at single-cell resolution. Using >500,000 resting memory T cells from 259 Peruvians, we found over one-third of the 6,511 cis-eQTLs had state-dependent effects. By integrating single-cell RNA and surface protein measurements, we defined continuous cell states that explained more eQTL variation than discrete states like CD4+ or CD8+ T cells and could have opposing effects on independent eQTL variants in a locus. Autoimmune variants were enriched in cell-state-dependent eQTLs, such as a rheumatoid-arthritis variant near ORMDL3 strongest in cytotoxic CD8+ T cells. These results argue that fine-grained cell state context is crucial to understanding disease-associated eQTLs.
Robust adaptive distance functions for approximate Bayesian inference on outlier-corrupted data
Authors: Schälte Yannik , Alamoudi Emad , Hasenauer Jan 
Published: July 2021

AbstractApproximate Bayesian Computation (ABC) is a likelihood-free parameter inference method for complex stochastic models in systems biology and other research areas. While conceptually simple, its practical performance relies on the ability to efficiently compare relevant features in simulated and observed data via distance functions. Complications can arise particularly from the presence of outliers in the data, which can severely impair the inference. Thus, robust methods are required that provide reliable estimates also from outlier-corrupted data.We illustrate how established ABC distance functions are highly sensitive to outliers, and can in practice yield erroneous or highly uncertain parameter estimates and model predictions. We introduce self-tuned outlier-insensitive distance functions, based on a popular adaptive distance weighting concept, complemented by a simulation-based online outlier detection and downweighting routine. We evaluate and compare the presented methods on six test models covering different model types, problem features, and outlier scenarios. Our evaluation demonstrates substantial improvements on outlier-corrupted data, while giving at least comparable performance on outlier-free data.The developed methods have been made available as part of the open-source Python package pyABC (https://github.com/icb-dcm/pyabc).
Heme-stress activated NRF2 signaling skews fate trajectories of bone marrow cells from dendritic cells towards red pulp-like macrophages
Authors: Vallelian Florence , Buzzi Raphael M. , Pfefferlé Marc , Yalamanoglu Ayla , Wassmer Andreas , Gentinetta Thomas , Hansen Kerstin , Humar Rok , Schulthess Nadja , Schaer Dominik J. 
Published: July 2021

ABSTRACTHeme is an erythrocyte-derived toxin that drives disease progression in hemolytic anemias, such as sickle cell disease. During hemolysis, specialized bone marrow-derived macrophages with a high heme-metabolism capacity orchestrate disease adaptation by removing damaged erythrocytes and heme-protein complexes from the blood and supporting iron recycling for erythropoiesis. Since chronic heme-stress is noxious for macrophages, erythrophagocytes in the spleen are continuously replenished from bone marrow-derived progenitors. Here, we hypothesized that adaptation to heme stress progressively shifts differentiation trajectories of BM progenitors to expand the capacity of heme-handling monocyte-derived macrophages at the expense of the homeostatic generation of dendritic cells, which emerge from shared myeloid precursors. This heme-induced redirection of differentiation trajectories may contribute to hemolysis-induced secondary immunodeficiency. We performed single-cell RNA sequencing with directional RNA velocity analysis of GM-CSF-supplemented mouse bone marrow cultures to assess myeloid differentiation under heme stress. We found that heme-activated NRF2 signaling shifted the differentiation of bone marrow cells towards antioxidant, iron-recycling macrophages, suppressing the generation of dendritic cells in heme-exposed bone marrow cultures. Heme eliminated the capacity of GM-CSF-supplemented bone marrow cultures to activate antigen-specific CD4 T cells. The generation of functionally competent dendritic cells was restored by NRF2 loss. The heme-induced phenotype of macrophage expansion with concurrent dendritic cell depletion was reproduced in hemolytic mice with sickle cell disease and spherocytosis and associated with reduced dendritic cell functions in the spleen. Our data provide a novel mechanistic underpinning of hemolytic stress as a driver of hyposplenism-related secondary immunodeficiency.GRAPHICAL ABSTRACT