bluuebunny/crossref_metadata_2025_split huggingface dataset:
Under detection of depression in primary care settings in low and middle-income countries: A systematic review and meta-analysis
Authors: Fekadu Abebaw , Demissie Mekdes , Berhane Rahel , Medhin Girmay , Bitew Teserra , Hailemariam Maji , Minaye Abebaw , Habtamu Kassahun , Milkias Barkot , Petersen Inge , Patel Vikram , Cleare Anthony J , Mayston Rosie , Thornicroft Graham , Alem Atalay , Hanlon Charlotte , Prince Martin 
Published: March 2020

ABSTRACTObjectiveDepression is the commonest mental disorder in primary care but is poor identified. The objective of this review was to determine the level of detection of depression by primary care clinicians and its determinants in studies from low-and middle-income countries (LMICs).MethodsDesignSystematic review and meta-analysis. Review protocol was registered in the PROSPERO database (CRD42016039704).DatabasesPubMed, PsycINFO, Medline, EMBASE, LILAC and AJOL.Quality assessmentRisk of bias within studies evaluated with the Effective Public Health Practice Project (EPHPP).Synthesis“Gold standard” diagnosis for the purposes of this review were based on the 9-item Patient Health Questionnaire (PHQ-9; cutoff scores of 5 and 10), structured interview or expert diagnosis. Meta-analysis was conducted excluding studies on special populations. Analysis of pooled data were stratified by diagnostic approaches.ResultsA total of 2223 non-duplicate publications were screened. Ten publications, from two multi-country studies and eight single country studies, making 18 country level reports, were included. One of the multi-country studies used an enriched sample of screen positive participants. Overall methodological quality of the studies was good. Depression detection was 0.0% in five reports and <12% in another five. The pooled detection for two reports that used PHQ-9 at a cutoff point of 5 (combined sample size = 1426) was 3.9% (95% CI = 2.3%, 5.5%); in the four reports that used PHQ-9 cutoff score of 10 (combined sample size =5481), the pooled detection was 7.0% (95% CI = 3.9%, 10.2%). For the enriched sample, the pooled detection was 43.5 % (95% CI: 25.7%, 61.0%). Severity of depression and suicidality were significantly associated with detection.ConclusionsThe extremely low detection of depression by primary care clinicians poses a serious threat to scaling up mental healthcare in LMICs. Interventions to improve detection should be prioritized.Strength and limitation of study▸This is the first review of detection of depression in LMIC settings▸The review was comprehensive in terms of databases searched▸Screening tools were used as gold standards, which may lead to overestimation of prevalence and underestimation of detection▸The small number of studies and the use of different instruments and cutoff▸points precluded exploration of sources of heterogeneity▸The review does not include studies on distress or sub-threshold depression
Development and Evaluation of an AI System for COVID-19 Diagnosis
Authors: Jin Cheng , Chen Weixiang , Cao Yukun , Xu Zhanwei , Zhang Xin , Deng Lei , Zheng Chuansheng , Zhou Jie , Shi Heshui , Feng Jianjiang 
Published: March 2020

AbstractEarly detection of COVID-19 based on chest CT will enable timely treatment of patients and help control the spread of the disease. With rapid spreading of COVID-19 in many countries, however, CT volumes of suspicious patients are increasing at a speed much faster than the availability of human experts. Here, we propose an artificial intelligence (AI) system for fast COVID-19 diagnosis with an accuracy comparable to experienced radiologists. A large dataset was constructed by collecting 970 CT volumes of 496 patients with confirmed COVID-19 and 260 negative cases from three hospitals in Wuhan, China, and 1,125 negative cases from two publicly available chest CT datasets. Trained using only 312 cases, our diagnosis system, which is based on deep convolutional neural network, is able to achieve an accuracy of 94.98%, an area under the receiver operating characteristic curve (AUC) of 97.91%, a sensitivity of 94.06%, and a specificity of 95.47% on an independent external verification dataset of 1,255 cases. In a reader study involving five radiologists, only one radiologist is slightly more accurate than the AI system. The AI system is two orders of magnitude faster than radiologists and the code is available at https://github.com/ChenWWWeixiang/diagnosis_covid19.
Financing Vaccines for Global Health Security
Authors: Vu Jonathan T. , Kaplan Benjamin K. , Chaudhuri Shomesh , Mansoura Monique K. , Lo Andrew W. 
Published: March 2020

AbstractRecent outbreaks of infectious pathogens such as Zika, Ebola, and COVID-19 have underscored the need for the dependable availability of vaccines against emerging infectious diseases (EIDs). The cost and risk of R&D programs and uniquely unpredictable demand for EID vaccines have discouraged vaccine developers, and government and nonprofit agencies have been unable to provide timely or sufficient incentives for their development and sustained supply. We analyze the economic returns of a portfolio of EID vaccine assets, and find that under realistic financing assumptions, the expected returns are significantly negative, implying that the private sector is unlikely to address this need without public-sector intervention. We have sized the financing deficit for this portfolio and propose several potential solutions, including price increases, enhanced public-private partnerships, and subscription models through which individuals would pay annual fees to obtain access to a portfolio of vaccines in the event of an outbreak.
Automatic identification of relevant genes from low-dimensional embeddings of single cell RNAseq data
Authors: Angerer Philipp , Fischer David S. , Theis Fabian J. , Scialdone Antonio , Marr Carsten 
Published: March 2020

AbstractDimensionality reduction is a key step in the analysis of single-cell RNA sequencing data and produces a low-dimensional embedding for visualization and as a calculation base for downstream analysis. Nonlinear techniques are most suitable to handle the intrinsic complexity of large, heterogeneous single cell data. With no linear relation between genes and embedding however, there is no way to extract the identity of genes most relevant for any cell’s position in the low-dimensional embedding, and thus the underlying process.In this paper, we introduce the concepts of global and local gene relevance to compute an equivalent of principal component analysis loadings for non-linear low-dimensional embeddings. Whileglobal gene relevanceidentifies drivers of the overall embedding,local gene relevancesingles out genes that change in small, possibly rare subsets of cells. We apply our method to single-cell RNAseq datasets from different experimental protocols and to different low dimensional embedding techniques, shows our method’s versatility to identify key genes for a variety of biological processes.To ensure reproducibility and ease of use, our method is released as part of destiny 3.0, a popular R package for building diffusion maps from single-cell transcriptomic data. It is readily available through Bioconductor.
ipADMIXTURE: R package for inferring sub-population clusters based on genetic admixture
Authors: Amornbunchornvej Chainarong , Wangkumhang Pongsakorn , Tongsima Sissades 
Published: March 2020

AbstractipADMIXTURE is an R package to infer clusters and their phylogeny based on Q matrices of genetic admixture analysis. It is the first software of its kind to infer not just only clusters, but also the hierarchy of sub-populations w.r.t. the minimum number of ancestors that split any pair of clusters apart. Since inputs of the package, Q matrices, can be obtained from well-known software (ADMIXTURE, STRUCTURE, etc.) and the Q matrices are mandatory information that are used in genetic population structure study, our package has a potential to help scientists and researchers to find deeper explanation of admixture analysis in their studies. Our package comes with a user-friendly interface to make the software accessible for everyone.
Docking of peptides to GPCRs using a combination of CABS-dock with FlexPepDock refinement
Authors: Badaczewska-Dawid Aleksandra E. , Kmiecik Sebastian , Koliński Michał 
Published: March 2020

AbstractThe structural description of peptide ligands bound to G protein-coupled receptors (GPCRs) is important for the discovery of new drugs and deeper understanding of the molecular mechanisms of life. Here we describe a three-stage protocol for the molecular docking of peptides to GPCRs using a set of different programs: (1) CABS-dock for docking fully flexible peptides; (2) PD2 method for the reconstruction of atomistic structures from C-alpha traces provided by CABS-dock and (3) Rosetta FlexPepDock for the refinement of protein-peptide complex structures and model scoring. We evaluated the proposed protocol on the set of 7 different GPCR-peptide complexes (including one containing a cyclic peptide) for which crystallographic structures are available. We show that CABS-dock produces high resolution models in the sets of top-scored models. These sets of models, after reconstruction to all-atom representation, can be further improved by Rosetta high-resolution refinement and/or minimization, leading in most of the cases to sub-Angstrom accuracy in terms of interface RMSD measure.
Translational adaptation to heat stress is mediated by 5-methylcytosine RNA modification inCaenorhabditis elegans
Authors: Navarro Isabela Cunha , Tuorto Francesca , Jordan David , Legrand Carine , Price Jonathan , Braukmann Fabian , Hendrick Alan , Akay Alper , Kotter Annika , Helm Mark , Lyko Frank , Miska Eric A. 
Published: March 2020

ABSTRACTMethylation of carbon-5 of cytosines (m5C) is a post-transcriptional nucleotide modification of RNA found in all kingdoms of life. While individual m5C-methyltransferases have been studied, the impact of the global cytosine-5 methylome on development, homeostasis and stress remains unknown. Here, usingCaenorhabditis elegans, we generated the first organism devoid of m5C in RNA, demonstrating that this modification is non-essential. We determined the localisation and enzymatic specificity of m5C sites in RNAin vivoand showed that animals devoid of m5C are sensitive to temperature stress. At the molecular level, we showed that loss of m5C specifically impacts decoding of leucine and proline thus reducing the translation efficiency of transcripts enriched in these amino acids. Finally, we found translation of leucine UUG codons to be the most strongly affected upon heat shock, suggesting a role of m5C tRNA wobble methylation in the adaptation to heat stress.
Use of short-read RNA-Seq data to identify transcripts that can translate novel ORFs
Authors: Erady Chaitanya , Puntambekar Shraddha , Prabakaran Sudhakaran 
Published: March 2020

AbstractIdentification of as of yet unannotated or undefined novel open reading frames (nORFs) and exploration of their functions in multiple organisms has revealed that vast regions of the genome have remained unexplored or ‘hidden’. Present within both protein-coding and noncoding regions, these nORFs signify the presence of a much more diverse proteome than previously expected. Given the need to study nORFs further, proper identification strategies must be in place, especially because they cannot be identified using conventional gene signatures. Although Ribo-Seq and proteogenomics are frequently used to identify and investigate nORFs, in this study, we propose a workflow for identifying nORF containing transcripts using our precompiled database of nORFs with translational evidence, using sample transcript information. Further, we discuss the potential uses of this identification, the caveats involved in such a transcript identification and finally present a few representative results from our analysis of naive mouse B and T cells, human post-mortem brain and cichlid fish transcriptome. Our proposed workflow can identify noncoding transcripts that can potentially translate intronic, intergenic and several other classes of nORFs.One-line summaryA systematic workflow to identify nORF containing transcripts using sample transcript information.
SARS-CoV-2, an evolutionary perspective of interaction with human ACE2 reveals undiscovered amino acids necessary for complex stability
Authors: Armijos-Jaramillo Vinicio , Yeager Justin , Muslin Claire , Perez-Castillo Yunierkis 
Published: March 2020

AbstractThe emergence of SARS-CoV-2 has resulted in more than 200,000 infections and nearly 9,000 deaths globally so far. This novel virus is thought to have originated from an animal reservoir, and acquired the ability to infect human cells using the SARS-CoV cell receptor hACE2. In the wake of a global pandemic it is essential to improve our understanding of the evolutionary dynamics surrounding the origin and spread of a novel infectious disease. One way theory predicts selection pressures should shape viral evolution is to enhance binding with host cells. We first assessed evolutionary dynamics in select betacoronavirus spike protein genes to predict where these genomic regions are under directional or purifying selection between divergent viral lineages at various scales of relatedness. With this analysis, we determine a region inside the receptor-binding domain with putative sites under positive selection interspersed among highly conserved sites, which are implicated in structural stability of the viral spike protein and its union with human receptor hACE2. Next, to gain further insights into factors associated with coronaviruses recognition of the human host receptor, we performed modeling studies of five different coronaviruses and their potential binding to hACE2. Modeling results indicate that interfering with the salt bridges at hot spot 353 could be an effective strategy for inhibiting binding, and hence for the prevention of coronavirus infections. We also propose that a glycine residue at the receptor binding domain of the spike glycoprotein can have a critical role in permitting bat variants of the coronaviruses to infect human cells.
Clinical characteristics and reasons of different duration from onset to release from quarantine for patients with COVID-19 Outside Hubei province, China
Authors: Tian Suochen , Chang Zhenqin , Wang Yunxia , Wu Min , Zhang Wenming , Zhou Guijie , Zou Xiuli , Tian Hui , Xiao Tingfang , Xing Junmin , Chen Juan , Han Jian , Ning Kang , Wu Tiejun 
Published: March 2020

AbstractObjectiveTo find out more characteristics and rules of COVID-19 by analyzing the clinical course of COVID-19 patients in a region outside Hubei province.Methods37 cases diagnosed adult COVID-19 cases of general characteristics, history of epidemiology, chronic underlying diseases, clinical symptoms and complications, chest CT, biochemical monitoring, severity assessment, treatment and outcome were retrospectively analyzed, and according to the duration from onset to release from quarantine were divided into ≤20 -day group and > 20 -day group, compare the similarities and differences between the two groups.ResultsAmong the 37 patients, 5 were mild, 30 were moderate, 1 was severe and 1 was critical. All the patients were released from quarantine without death. The average duration from onset to release from quarantine was 20.2±6.6 days, The average length of stay from onset to hospitalization was 4.1±3.7 days, and hospitalization duration average 16.1 ±6.2 days. The average age was 44.3±1.67 years. 78.4% of cases were caused by exposure to a confirmed patient or the workplace of a confirmed patient. The main symptoms were cough (67.6%), fever (62.2%), shortness of breath (32.4%), fatigue (24.3%), sore throat (21.6%,) vomiting or diarrhea (21.6%). The white blood cell count was decreased in 27.0% of the patients, and the lymphocyte count was decreased in 62.2% of the patients, of which 43.5% patients were ≤0.6×109/L. On admission, 86.5% of patients with chest CT showed pneumonia, including some asymptomatic patients. 68.8% of patients showed bilateral infiltration. In the > 20-day group, the average age was 49.9±1.38 years old, and the duration from onset to hospitalization was 5.5±3.9 days. Compared with the ≤ 20-day group, the age was older and duration was longer, P < 0.05. All the 7 asymptomatic patients were ≤20 –day group. When 37 patients were released from quarantine, the white blood cell count of 16.2% patients was < 4.0×109/L, and the lymphocyte count of 59.5% patients was <1.1×109/L, and the absolute count of white blood cells and lymphocytes was 5.02±1.3 4×109/L and 1.03±0.34×109/L respectively, compared with those on admission, P > 0.05.ConclusionThe majority of COVID-19 cases in the study area were mild and moderate, with good clinical outcomes. There were some special characteristics in the clinical process. The reasons of duration from onset to release from quarantine were complex. There was no significant change in the number of granulocytes at the time of release from quarantine compared to the time of admission.
Prognostic value of C-reactive protein in patients with COVID-19
Authors: Luo Xiaomin , Zhou Wei , Yan Xiaojie , Guo Tangxi , Wang Benchao , Xia Hongxia , Ye Lu , Xiong Jun , Jiang Zongping , Liu Yu , Zhang Bicheng , Yang Weize 
Published: March 2020

AbstractBackgroundElevated serum C-reactive protein (CRP) level was observed in most patients with COVID-19.MethodsData of COVID-19 patients with clinical outcome in a designated hospital in Wuhan, China, were retrospectively collected and analyzed from Jan 30 to Feb 20, 2020. The prognostic value of admission CRP was evaluated in patients with COVID-19.ResultsOut of 298 patients enrolled, 84 died and 214 recovered. Most non-survivors tended to be males, old aged, or with chronic diseases. Compared to survivors, non-survivors showed significantly elevated white blood cell and neutrophil count, neutrophil to lymphocyte ratio (NLR), systemic immune-inflammation index (SII, defined by platelet count multiply by NLR), CRP, procalcitonin, and D-dimer, and decreased red blood cell, lymphocyte, and platelet count. Age, neutrophil count, platelet count, and CRP were identified as independent predictors of adverse outcome. The area under the receiver operating characteristic (ROC) curve (AUC) of CRP (0.896) was significantly higher than that of age (0.833), neutrophil count (0.820), and platelet count (0.678) in outcome prediction (all p<0.05). With a cut-off value of 41.4, CRP exhibited sensitivity 90.5%, specificity 77.6%, positive predictive value 61.3%, and negative predictive value 95.4%. Subgroup analysis revealed that CRP remained robust accuracy in adverse outcome prediction in patients with different disease severity (AUC 0.832, z=10.23, p<0.001; AUC 0.989, z=44.04, p<0.001). CRP was also an independent discriminator of severe/critical illness on admission (AUC 0.783, z=10.69, p<0.001).ConclusionsIn patients with COVID-19, admission CRP correlated with disease severity and tended to be a good predictor of adverse outcome.
Organizational virtuousness, subjective well-being, and job performance
Authors: Magnier-Watanabe Remy , Uchida Toru , Orsini Philippe , Benton Caroline F. 
Published: March 2020

PurposePast research has convincingly shown that higher employee subjective well-being, or happiness, is a source of higher job performance and retention. This paper therefore examines the relationships between organizational virtuousness, subjective well-being, and individual job performance among French and Japanese employees.Design/methodology/approachA questionnaire survey was conducted among Japanese and French managers and staff at Japanese and French domestic companies and structural equation modeling was employed to compare those associations.FindingsWe found that the Japanese and the French have different conceptualizations of organizational virtuousness, suggesting that firms must tailor their virtue-building activities based on the local culture. Subjective well-being is comparatively more important in Japan since it acts in complement to organizational virtuousness to positively affect job performance, while in France, only organizational virtuousness counts as a source of job performance.Research implicationsNational culture is revealed to be a new factor explaining differences in how employees consider organizational virtuousness and we provide evidence of positive associations of organizational virtuousness with positive subjective well-being and with job performance for both the Japanese and the French.Practical implicationsOrganizational virtuousness cannot be construed from a universalistic perspective where virtues are conceptualized on the same basis regardless of location or region, and firms should also consider their employees' individualist or collectivist inclination when trying to influence work outcomes.Originality/valueThese findings point to the role of national culture on the perception of organizational virtuousness and its effect on subjective well-being and job performance.
A read-disturb-free stable low power and high-density GNRFET 6T SRAM with multi-VT technology
Authors: Patel Pramod Kumar , Malik M.M. , Gutpa Tarun Kumar 
Published: March 2020

Purpose
The performance of the conventional 6T SRAM cell can be improved by using GNRFET devices with multi-threshold technology. The proposed cell shows the strong capability to operate at the minimum supply voltage of 325 mV, whereas the conventional Si-CMOS 6 T SRAM unable to operate below 725 mV, which result in an acceptable failure rate.The advance of Si-CMOS (complementary metal-oxide-semiconductor) based 6 T SRAM cell faces inherent limitation with aggressive downscaling. Hence, there is a need to propose alternatives for the conventional cells.

Design/methodology/approach
This study aims to improve the performance of the conventional 6T SRAM cell using dual threshold technology, device sizing, optimization of supply voltage under process variation with GNRFET technology. Further performance can be enhanced by resolving half-select issue.

Findings
The GNRFET-based 6T SRAM cell demonstrates that it is capable of continued improve the performance under the process, voltage, and temperature (PVT) variations significantly better than its CMOS counterpart.

Research limitations/implications
Nano-material fabrication technology of GNRFETs is in the early stage; hence, the different transistor models can be used to evaluate the parameters of future GNRFETs circuit.

Practical implications
GNRFET devices are suitable for implementing low power and high density SRAM cell.

Social implications
The conventional Si-CMOS 6 T SRAM cell is a core component and used as the mass storage element in cache memory in computer system organization, mobile phone and other data storage devices.

Originality/value
This paper presents a new approach to implement an alternative design of GNRFET -based 6T SRAM cell with doped reservoirs that also supports process variation. In addition, multi-threshold technology optimizes the performance of the proposed cell. The proposed design provides a means to analyze delay and power of GNRFET-based SRAM under process variation with considering edge roughness, and offers design and fabrication insights for cell in the future.