bluuebunny/crossref_metadata_2025_split huggingface dataset:
Cognitive Benefits of Exercise Interventions: An fMRI Activation Likelihood Estimation Meta-Analysis
Authors: Yu Qian , Herold Fabian , Becker Benjamin , KluGah-Brown Ben , Zhang Yanjie , Perrey Stephane , Veronese Nicola , Müller Notger G. , Zou Liye , Kramer Arthur F. 
Published: July 2020

AbstractDespite a growing number of functional MRI studies reporting exercise-induced changes during cognitive processing, a systematic determination of the underlying neurobiological pathways is currently lacking. To this end, our neuroimaging meta-analysis included 20 studies and investigated the influence of exercise on cognition-related functional brain activation. The overall meta-analysis encompassing all experiments revealed exercise-induced changes in the left parietal lobe during cognitive processing. Subgroup analysis further revealed that in the younger-age group (<35 years old) exercise induced more widespread changes in the right hemisphere whereas in the older-age group (≥35 years old) exercise-induced changes were restricted to the left parietal lobe. Furthermore, subgroup analysis for exercise intervention duration, showed that shorter exercise interventions induced changes in regions connected with frontoparietal and default mode networks whereas regions exhibiting effects of longer interventions connected with frontoparietal and dorsal attention networks. Our findings suggest that physical exercise training leads to changes in functional activation patterns primarily located in precuneus and associated with frontoparietal, dorsal attention and default mode networks. Furthermore, exercise-induced changes in functional brain activation varied as a function of age and exercise intervention duration.
Snapshot of the evolution and mutation patterns of SARS-CoV-2
Authors: Zhao Jin , Sun Jiumeng , He Wan-Ting , Ji Xiang , Gao Qi , Zhai Xiaofeng , Suchard Marc A. , Hong Samuel L. , Baele Guy , Su Shuo , Zhou Jiyong , Veit Michael 
Published: July 2020

AbstractThe COVID-19 pandemic is the most important public health threat in recent history. Here we study how its causal agent, SARS-CoV-2, has diversified genetically since its first emergence in December 2019. We have created a pipeline combining both phylogenetic and structural analysis to identify possible human-adaptation related mutations in a data set consisting of 4,894 SARS-CoV-2 complete genome sequences. Although the phylogenetic diversity of SARS-CoV-2 is low, the whole genome phylogenetic tree can be divided into five clusters/clades based on the tree topology and clustering of specific mutations, but its branches exhibit low genetic distance and bootstrap support values. We also identified 11 residues that are high-frequency substitutions, with four of them currently showing some signal for potential positive selection. These fast-evolving sites are in the non-structural proteins nsp2, nsp5 (3CL-protease), nsp6, nsp12 (polymerase) and nsp13 (helicase), in accessory proteins (ORF3a, ORF8) and in the structural proteins N and S. Temporal and spatial analysis of these potentially adaptive mutations revealed that the incidence of some of these sites was declining after having reached an (often local) peak, whereas the frequency of other sites is continually increasing and now exhibit a worldwide distribution. Structural analysis revealed that the mutations are located on the surface of the proteins that modulate biochemical properties. We speculate that this improves binding to cellular proteins and hence represents fine-tuning of adaptation to human cells. Our study has implications for the design of biochemical and clinical experiments to assess whether important properties of SARS-CoV-2 have changed during the epidemic.
A County-Level Susceptibility Index and Coronavirus Disease 2019 Mortality in the United States: A Socioecological Study
Authors: Khan Sadiya S. , McCabe Megan E. , Krefman Amy E. , Petito Lucia C. , Yang Xiaoyun , Kershaw Kiarri N. , Pool Lindsay , Allen Norrina B. 
Published: July 2020

ABSTRACTAs of June 2020, the United States (US) has experienced the highest number of deaths related to coronavirus disease 2019 (Covid-19) in the world, but significant geographic heterogeneity exists at the county-level. Therefore, we sought to classify counties in the United States across multiple domains utilizing a socioecological framework and examine the association between these county-level groups and Covid-19 mortality. We harmonized and linked county-level sociodemographic, health, and environmental metrics associated with increased susceptibility for Covid-19 mortality. Latent class analysis defined a county-level susceptibility index (CSI) based on these metrics (n=2701 counties). Next, we used linear regression models to estimate the associations of the CSI and Covid-19 deaths per capita and initial mortality doubling time (as of 6/2/20), adjusted for days since first Covid-19 case. We identified 4 groups classified by the CSI with distinct sociodemographic, health, and environmental profiles and widespread geographic dispersion. Covid-19 deaths per capita were significantly higher in the group consisting of rural, vulnerable counties (55.8 [95% CI 50.3-61.2] deaths per 100,000) compared with the group with diverse, urban counties (32.2 [27.3-37.0]) at similar points in the outbreak (76 days since first case). Our findings can inform equitable resource allocation for Covid-19 to allow targeted public health preparedness and response in vulnerable counties.
Wearable Respiration Monitoring: Interpretable Inference with Context and Sensor Biomarkers
Authors: Alam Ridwan , Peden David B. , Lach John C. 
Published: July 2020

AbstractBreathing rate (BR), minute ventilation (VE), and other respiratory parameters are essential for real-time patient monitoring in many acute health conditions, such as asthma. The clinical standard for measuring respiration, namely Spirometry, is hardly suitable for continuous use. Wearables can track many physiological signals, like ECG and motion, yet not respiration. Deriving respiration from other modalities has become an area of active research. In this work, we infer respiratory parameters from wearable ECG and wrist motion signals. We propose a modular and generalizable classification-regression pipeline to utilize available context information, such as physical activity, in learning context-conditioned inference models. Morphological and power domain novel features from the wearable ECG are extracted to use with these models. Exploratory feature selection methods are incorporated in this pipeline to discover application-specific interpretable biomarkers. Using data from 15 subjects, we evaluate two implementations of the proposed pipeline: for inferring BR and VE. Each implementation compares generalized linear model, random forest, support vector machine, Gaussian process regression, and neighborhood component analysis as contextual regression models. Permutation, regularization, and relevance determination methods are used to rank the ECG features to identify robust ECG biomarkers across models and activities. This work demonstrates the potential of wearable sensors not only in continuous monitoring, but also in designing biomarker-driven preventive measures.
Symbiont-mediated fly survival is independent of defensive symbiont genotype in the Drosophila melanogaster-Spiroplasma-wasp interaction
Authors: Jones Jordan E. , Hurst Gregory D. D. 
Published: July 2020

AbstractWhen a parasite attacks an insect, the outcome is commonly modulated by the presence of defensive heritable symbionts residing within the insect host. Previous studies noted markedly different strengths of Spiroplasma-mediated fly survival following attack by the same strain of wasp. One difference between the two studies was the strain of Spiroplasma used. We therefore performed a common garden laboratory experiment to assess whether Spiroplasma-mediated protection depends upon the strain of Spiroplasma. We perform this analysis using the two strains of male-killing Spiroplasma used previously, and examined response to challenge by two strains of Leptopilina boulardi and two strains of Leptopilina heterotoma wasp. We found no evidence Spiroplasma strain affected fly survival following wasp attack. In contrast, analysis of the overall level of protection, including the fecundity of survivors of wasp attack, did indicate the two Spiroplasma strains tested varied in protective efficiency against three of the four wasp strains tested. These data highlight the sensitivity of symbiont-mediated protection phenotypes to laboratory conditions, and the importance of common garden comparison. Our results also indicate that Spiroplasma strains can vary in protective capacity in Drosophila, but these differences may exist in the relative performance of survivors of wasp attack, rather than in survival of attack per se.
Predicting base editing outcomes with an attention-based deep learning algorithm trained on high-throughput target library screens
Authors: Marquart Kim F. , Allam Ahmed , Janjuha Sharan , Sintsova Anna , Villiger Lukas , Frey Nina , Krauthammer Michael , Schwank Gerald 
Published: July 2020

AbstractBase editors are chimeric ribonucleoprotein complexes consisting of a DNA-targeting CRISPR-Cas module and a single-stranded DNA deaminase. They enable conversion of C•G into T•A base pairs and vice versa on genomic DNA. While base editors have vast potential as genome editing tools for basic research and gene therapy, their application has been hampered by a broad variation in editing efficiencies on different genomic loci. Here we perform an extensive analysis of adenine- and cytosine base editors on thousands of lentivirally integrated genetic sequences and establish BE-DICT, an attention-based deep learning algorithm capable of predicting base editing outcomes with high accuracy. BE-DICT is a versatile tool that in principle can be trained on any novel base editor variant, facilitating the application of base editing for research and therapy.
Nitrergic neurons of the forepaw representation in the somatosensory and motor cortices
Authors: Guimaraes Bárbara de Paula P. F. , Curado Marco R. , Nogueira-Campos Anaelli Aparecida , Houzel Jean Christophe , Gattass Ricardo 
Published: July 2020

AbstractNitrergic neurons (NN) are inhibitory neurons capable of releasing nitric oxide (NO) that are labeled with NADPHd histochemistry, allowing the study of their distribution and morphology. The rat primary somatosensory (S1) and motor (M1) cortices are a favorable model to investigate the morphology of the NN population. The distribution of the type I NN of the forepaw representation in the primary somatosensory (S1) and motor (M1) cortices of the rat in different laminar compartments and the morphological parameters related to the cell body and dendritic arborization were measured and compared. We found that the neuronal density in the S1 (130 NN/mm3) was higher than in the M1 (119 NN/mm3). Most NN neurons are multipolar (S1 with 58%; M1 with 69%) and a minority are horizontal (S1 with 6%; M1 with 12%). NN found in the S1 had a higher verticality index than those of the M1, and no statistical differences was found for the others morphological parameters. We also demonstrated statistical differences for most of the morphological parameters of the NN between different cortical compartments of the S1 and M1. Our results indicate that the NN of the forepaw in the S1 and M1 correspond to a single neuronal population whose functionality is independent of the different types of sensory and motor processing. However, the morphological differences found between cortical compartments of S1 and M1, as well as the higher density of NN found in the S1 indicate that the release of NO varies along and between the areas.
Cell type-specific weighting-factors to solve solid organs-specific limitations of single cell RNA-sequencing
Authors: Tejima Kengo , Kozawa Satoshi , Sato Thomas N. 
Published: July 2020

AbstractWhile single-cell RNA-sequencing (scRNA-seq) is a popular method to analyze gene expression and cellular composition at single-cell resolution, it harbors shortcomings: The failure to account for cell-to-cell variations of transcriptome-size (i.e., the total number of transcripts per cell) and also cell dissociation/processing-induced cryptic gene expression. This is particularly a problem when analyzing highly heterogeneous solid tissues/organs, which requires cell dissociation for the analysis. As a result, there exists a discrepancy between bulk RNA-seq result and virtually reconstituted bulk RNA-seq result using its composite scRNA-seq data. To fix this problem, we propose a computationally calculated coefficient, “cell type-specific weighting-factor (cWF)”. Here, we introduce a concept and a method of its computation and report cWFs for 76 cell-types across 10 solid organs. Their fidelity is validated by more accurate reconstitution and deconvolution of bulk RNA-seq data of diverse solid organs using the scRNA-seq data and the cWFs of their composite cells. Furthermore, we also show that cWFs effectively predict aging-progression, implicating their diagnostic applications and also their association with aging mechanism. Our study provides an important method to solve critical limitations of scRNA-seq analysis of complex solid tissues/organs. Furthermore, our findings suggest a diagnostic utility and biological significance of cWFs.
Circuit-free, optoelectronic sensing of electrodermal activities based on photon recycling of a micro-LED
Authors: Ding He , Lv Guoqing , Shi Zhao , Cheng Dali , Huang Yunxiang , Yin Lan , Yang Jian , Wang YongTian , Sheng Xing 
Published: July 2020

AbstractConventional epidermal electronics integrate multiple power harvesting, signal amplification and data transmission components for wireless biophysical and biochemical signal detection. This paper reports the real-time electrodermal activities can be optically captured using a microscale light-emitting diode (micro-LED), eliminating the need for complicated sensing circuit. Owing to its strong photon-recycling effects, the micro-LED’s photoluminescence (PL) emission exhibits a superlinear dependence on the external resistance. Taking advantage of this unique mechanism, the galvanic skin response (GSR) of a human subject is optically monitored, and it demonstrates that such an optoelectronic sensing technique outperforms a traditional tethered, electrically based GSR sensing circuit, in terms of its footprint, accuracy and sensitivity. This presented optoelectronic sensing approach could establish promising routes to advanced biological sensors.
Genetic background modifies vulnerability to glaucoma related phenotypes inLmx1bmutant mice
Authors: Tolman NG , Macalinao DG , Kearney AL , MacNicoll KH , Montgomery CL , de Vries WN , Jackson IJ , Cross SH , Kizhatil K , Nair KS , John SWM 
Published: July 2020

AbstractVariants in the LIM homeobox transcription factor 1-beta gene (LMX1B) predispose individuals to elevated intraocular pressure (IOP), a key risk factor for glaucoma. However, the effect ofLMX1Bmutations varies widely between individuals. To better understand mechanisms underlying LMX1B-related phenotypes and individual differences, we backcrossed theLmx1bV265D(also known asLmx1bIcst) allele onto the C57BL/6J (B6), 129/Sj (129), C3A/BLiA-Pde6b+/J (C3H), and DBA/2J-Gpnmb+(D2-G) strain backgrounds. Strain background had a significant effect on the onset and severity of ocular phenotypes inLmx1bV265D/+mutant mice. Mice of the B6 background were the most susceptible to developing elevated IOP, severe anterior segment developmental anomalies (including malformed eccentric pupils, iridocorneal strands, and corneal abnormalities) and glaucomatous nerve damage. In contrast,Lmx1bV265Dmice of the 129 background were the most resistant to developing anterior segment abnormalities, had less severe IOP elevation than B6 mutants at young ages, and showed no detectable nerve damage. To identify genetic modifiers of susceptibility toLmx1bV265D-induced glaucoma-associated phenotypes, we performed a mapping cross between mice of the B6 (susceptible) and 129 (resistant) backgrounds. We identified a modifier locus on Chromosome 18, with the 129 allele(s) substantially lessening severity of ocular phenotypes, as confirmed by congenic analysis. By demonstrating a clear effect of genetic background in modulatingLmx1b-induced phenotypes, by providing a panel of strains with different phenotypic severities and by identifying a modifier locus, this study lays a foundation for better understanding the roles of LMX1B in glaucoma with the goal of developing new treatments.
Subsynaptic mobility of presynaptic mGluR types is differentially regulated by intra- and extracellular interactions
Authors: Bodzęta Anna , Berger Florian , MacGillavry Harold D. 
Published: July 2020

ABSTRACTPresynaptic metabotropic glutamate receptors (mGluRs) are essential for activity-dependent modulation of synaptic transmission. However, the mechanisms that control the subsynaptic dynamics of these receptors and their contribution to synaptic signaling are poorly understood. Here, using complementary super-resolution microscopy and single-molecule tracking techniques, we provide novel insights into the molecular mechanisms that control the nanoscale distribution and mobility of presynaptic mGluRs in hippocampal neurons. We demonstrate that the group II receptor mGluR2 localizes diffusely along the axon and boutons, and is highly mobile, while the group III receptor mGluR7 is stably anchored at the active zone, indicating that distinct mechanisms underlie the dynamic distribution of these receptor types. Surprisingly, using domain swapping experiments we found that intracellular interactions modulate surface diffusion of mGluR2, but not mGluR7. Instead, we found that immobilization of mGluR7 at the active zone relies on its extracellular domain. Importantly, receptor activation or increase in synaptic activity did not alter the surface mobility of presynaptic mGluRs. Finally, computational modeling of presynaptic mGluR activity revealed that the precise subsynaptic distribution of mGluRs controls their activation probability and thus directly impacts their ability to modulate neurotransmitter release. Altogether, this study demonstrates that distinct mechanisms control surface mobility of presynaptic mGluRs to differentially contribute to the regulation of glutamatergic synaptic transmission.
Analyzing the Lean Six Sigma enabled organizational performance to enhance operational efficiency
Authors: Raval Shruti J. , Kant Ravi , Shankar Ravi 
Published: July 2020

PurposeThe aim of this analysis is to review the Indian manufacturing organizations practicing Lean Six Sigma (LSS) tools/techniques with an objective of monitoring the performance of an organization and to develop recommendation for strategies to benchmark organizational operational efficiency.Design/methodology/approachThis study offers insights of the LSS performance measurement aspects of the Indian manufacturing organizations based on Data envelopment analysis (DEA) approach. The five inputs and two outputs are considered on the basis of literature review and discussed with the practitioners.FindingsIn this analysis, the relative efficiency score of 18 Indian manufacturing organizations has been determined in order to assist evaluation of the impact of monetary investment on the outputs. The present analysis not only investigates the optimum level of input variables but also lays down a significant observation that an organization having higher profit and inventory turnover ratio is not necessarily an efficient organization.Practical implicationsThe results assist to determine the best practice units, potential source of inefficiency and deliver beneficial data for the consistent enhancement of the operational efficiency. The DEA results assist managers and decision makers to derive appropriate strategies to enhance their performance with reference to the efficient organization and to regard it as their role model.Originality/valueThis analysis renders a DEA based framework of LSS practicing Indian manufacturing organizations. The framework is unique in terms of its input-outputs variable selection and measurement procedure.
Towards a framework for public relations practice in the financial services sector of Ghana
Authors: Anani-Bossman Albert , Mudzanani Takalani Eric 
Published: July 2020

PurposeThe goal of the study is to develop an integrated, non-sequential framework for excellent public relations management for the financial services sector in Ghana. The study empirically analyzes how PR is conceptualized and practiced in relation to the purpose (models) and roles (activities).Design/methodology/approachThe study adopted the qualitative in-depth interview approach to gauge the views of 22 PR practitioners.FindingsPractitioners of most communication departments have no PR background, and this influenced their conceptualization of PR. Essentially, PR in Ghana is shaped, to a large extent, by a western ideology. PR is however influenced greatly by strong interpersonal relationships, which is premised largely on the culture of the country. What is obvious is that PR in the financial services sector is not fully strategic. Although practitioners occupy managerial roles, they are limited in their ability to make impact due a lack of understanding by management about the purpose of PR and budgetary constraints.Research limitations/implicationsThe use of a qualitative approach means the result cannot be generalized. As the study focussed on one sector, it will be essential to look at other sectors using a generalized sample.Originality/valueThe study developed an integrative non-sequential PR framework based on literature and empirical findings. The framework differs in certain aspects from some of the recommendations made by literature for an excellent PR practice.
Who networks? – A meta-analysis of networking and personality
Authors: Bendella Hadjira , Wolff Hans-Georg 
Published: July 2020

PurposeNetworking refers to goal-directed behaviors focused on building and cultivating informal relationships to obtain career-related resources. According to Gibson et al.'s (2014) model, personality traits represent prominent and important antecedents of networking. This study seeks to provide robust evidence on relationships between personality and networking by summarizing prior research using meta-analytical tools.Design/methodology/approachThe authors classify linking attributes between networking and personality into social, idea-related, task-related and affective behavioral domains and additionally include three compound traits that relate to several domains. They investigate two potential moderators: internal vs. external networking and prominent networking measures. Their comprehensive literature search identified 41 studies with 46 independent samples.FindingsThe authors find that social, idea-related and task-related traits have positive relationships with networking of medium effect size, whereas affective traits exhibit small but significantly positive effects. The compound trait of proactive personality appears to be the best predictor of networking. Moderator analyses indicate that there were hardly any differences concerning internal and external networking and also prominent measures.Originality/valueThe present study goes beyond narrative reviews contributing the first quantitative summary of these relationships. It identifies four behavioral domains that represent characteristics relevant to networking. The findings largely corroborate, but at times correct, narrative reviews on dispositional antecedents of networking. The authors highlight the importance of compound traits that have yet been overlooked by narrative reviews (e.g. self-monitoring).