bluuebunny/crossref_metadata_2025_split huggingface dataset:
Immunosuppressive Regulation of Dendritic Cells and T Cells in Allergic Rhinitis by Semaphorin 3A
Authors: Liu Honghui , Xia Jinye , Chen Yu , Ai Jingang , Wang Tiansheng , Tan Guolin 
Published: March 2021

Background Semaphrin3A (Sema3A) was found to play a major role in immune regulation in autoimmune diseases and to be of importance in allergic disease. However, the effect of Sema3A on allergic rhinitis (AR) is not fully clear. Objective We sought to elucidate the effects of Sema3A on the regulation of dendritic cells (DCs) and naive CD4+ T cells in AR. Methods The expression of Sema3A in nasal mucosa was measured by immunohistochemical staining and western blotting. Human peripheral blood mononuclear cells were separated by the Ficoll-Hypaque method. DCs and naive CD4+ T cells were purified by magnetic selection. A human Sema3A Fc chimera was added to DCs and naive CD4+ T cells in vitro to evaluate the effect of Sema3A on the function of DCs and T cells. Labeling T cells with CFSE was used to determine cell proliferation. Flow cytometry was used to detect the DC maturation markers (CD40 and CD83) and T helper 17 (Th17) and regulatory T cell (Treg) percentages. ELISA was used to detect the IL10, IL17, IL4, and IFNγ cytokine levels. Results The expression of Sema3A in AR inferior turbinate tissue was lower than that in healthy control tissue. Compared with healthy control DCs, AR DCs showed decreased levels of the DC maturation markers CD40 and CD83 after Sema3A treatment. Furthermore, Sema3A decreased naive CD4+ T cell proliferation in AR. In addition, Sema3A increased the percentage of Tregs but had no obvious effect on Th17 cells. Moreover, Sema3A significantly increased levels of IL10 and IFNγ, and decreased level of IL4, but had no obvious effect on level of IL17. Conclusion AR presented with low expression of Sema3A in nasal mucosa, and Sema3A could decrease DC maturation, T cell proliferation, and Treg polarization.
A Comprehensive Resiliency Framework: Theoretical Model, Treatment, and Evaluation
Authors: Park Elyse R , Luberto Christina M , Chad-Friedman Emma , Traeger Lara , Hall Daniel L , Perez Giselle K , Goshe Brett , Vranceanu Ana-Maria , Baim Margaret , Denninger John W , Fricchione Gregory , Benson Herbert , Lechner Suzanne C 
Published: March 2021

Background There is heterogeneity in conceptualizations of resiliency, and there is, to date, no established theoretically driven resiliency assessment measure that aligns with a targeted resiliency intervention. We operationalize resiliency as one’s ability to maintain adaptive functioning in response to the ongoing, chronic stress of daily living, and we use a novel resiliency measure that assesses the target components of an evidence based resiliency intervention. We present our resiliency theory, treatment model, and corresponding assessment measure (Current Experience Scale; CES). Methods To establish the psychometric properties of the CES, we report the factor structure and internal consistency reliability (N = 273). Among participants in our resiliency intervention (N = 151), we explored construct validity in terms of associations with theoretical model constructs, a validated resiliency measure, and sensitivity to change from before to after the intervention. Results Results indicated that a 23-item, 6-factor solution was a good fit to the data (RMSEA = .08, CFI = .97; TLI =.96) and internal consistency was good (α = .81 to .95). The CES showed correlations in the expected direction with resiliency model constructs (all p’s < .001) and significant post intervention improvements. Conclusion Our resiliency theory, treatment model, and outcome appear aligned; the CES demonstrated promise as a psychometrically sound outcome measure for our resiliency intervention and may be used in future longitudinal studies and resiliency building interventions to assess individuals’ resiliency to adapt to ongoing stress.
Inherited glycosylphosphatidylinositol defects cause the rare Emm-negative blood phenotype and developmental disorders
Authors: Duval Romain , Nicolas Gaël , Willemetz Alexandra , Murakami Yoshiko , Mikdar Mahmoud , Vrignaud Cedric , Megahed Hisham , Cartron Jean-Pierre , Masson Cecile , Wehbi Samer , Koehl Bérengere , Hully Marie , Siquier Karine , Chemlay Nicole , Rotig Agnes , Lyonnet Stanislas , Colin Yves , Barcia Giulia , Cantagrel Vincent , Le Van Kim Caroline , Hermine Olivier , Kinoshita Taroh , Peyrard Thierry , Azouzi Slim 
Published: March 2021

Abstract
Glycosylphosphatidylinositol (GPI) is a glycolipid that anchors &gt;150 proteins to the cell surface. Pathogenic variants in several genes that participate in GPI biosynthesis cause inherited GPI deficiency disorders. Here, we reported that homozygous null alleles of PIGG, a gene involved in GPI modification, are responsible for the rare Emm-negative blood phenotype. Using a panel of K562 cells defective in both the GPI-transamidase and GPI remodeling pathways, we show that the Emm antigen, whose molecular basis has remained unknown for decades, is carried only by free GPI and that its epitope is composed of the second and third ethanolamine of the GPI backbone. Importantly, we show that the decrease in Emm expression in several inherited GPI deficiency patients is indicative of GPI defects. Overall, our findings establish Emm as a novel blood group system, and they have important implications for understanding the biological function of human free GPI.
A large-scale genome-wide association analysis of lung function in the Chinese population identifies novel loci and highlights shared genetic aetiology with obesity
Authors: Zhu Zhaozhong , Li Jiachen , Si Jiahui , Ma Baoshan , Shi Huwenbo , Lv Jun , Cao Weihua , Guo Yu , Millwood Iona Y. , Walters Robin G. , Lin Kuang , Yang Ling , Chen Yiping , Du Huaidong , Yu Bo , Hasegawa Kohei , Camargo Carlos A. , Moffatt Miriam F. , Cookson William O.C. , Chen Junshi , Chen Zhengming , Li Liming , Yu Canqing , Liang Liming 
Published: March 2021

BackgroundLung function is a heritable complex phenotype with obesity being one of its important risk factors. However, knowledge of their shared genetic basis is limited. Most genome-wide association studies (GWASs) for lung function have been based on European populations, limiting the generalisability across populations. Large-scale lung function GWASs in other populations are lacking.MethodsWe included 100 285 subjects from the China Kadoorie Biobank (CKB). To identify novel loci for lung function, single-trait GWAS analyses were performed on forced expiratory volume in 1 s (FEV1), forced vital capacity (FVC) and FEV1/FVC in the CKB. We then performed genome-wide cross-trait analysis between lung function and obesity traits (body mass index (BMI), BMI-adjusted waist-to-hip ratio and BMI-adjusted waist circumference) to investigate the shared genetic effects in the CKB. Finally, polygenic risk scores (PRSs) of lung function were developed in the CKB and their interaction with BMI's association on lung function were examined. We also conducted cross-trait analysis in parallel with the CKB using up to 457 756 subjects from the UK Biobank (UKB) for replication and investigation of ancestry-specific effects.ResultsWe identified nine genome-wide significant novel loci for FEV1, six for FVC and three for FEV1/FVC in the CKB. FEV1and FVC showed significant negative genetic correlation with obesity traits in both the CKB and UKB. Genetic loci shared between lung function and obesity traits highlighted important biological pathways, including cell proliferation, embryo, skeletal and tissue development, and regulation of gene expression. Mendelian randomisation analysis suggested significant negative causal effects of BMI on FEV1and on FVC in both the CKB and UKB. Lung function PRSs significantly modified the effect of change in BMI on change in lung function during an average follow-up of 8 years.ConclusionThis large-scale GWAS of lung function identified novel loci and shared genetic aetiology between lung function and obesity. Change in BMI might affect change in lung function differently according to a subject's polygenic background. These findings may open new avenues for the development of molecular-targeted therapies for obesity and lung function improvement.
Maternal metal concentration during gestation and pediatric morbidity in children: an exploratory analysis
Authors: Karakis Isabella , Landau Daniella , Gat Roni , Shemesh Nofar , Tirosh Ofir , Yitshak-Sade Maayan , Sarov Batia , Novack Lena 
Published: March 2021

Abstract
Background
The majority of studies linking exposure to metals with certain health outcomes focus on known toxic metals. Alternatively, this study assesses the extent to which exposure to a wider range of metals during gestation is associated with childhood morbidity.

Methods
We analyzed the concentrations of 25 metals found in urine samples of 111 pregnant women of Arab-Bedouin origin collected prior to birth. In addition, we collected medical records on their offspring for six years following birth, including every interaction with HMOs, local hospitals, and pharmacies.

Results
The main types of morbidities diagnosed and treated during this period were preterm births, malformations, asthma-like morbidity, cardiovascular and behavioral problems, and obesity. Multivariable analysis showed that offspring born before term were more likely to have been exposed to elevated maternal concentrations of zinc, thallium, aluminum, manganese, and uranium, all with adjusted relative risk above 1.40 for an increase by each quintile. Likewise, children with asthma had been exposed to higher levels of magnesium, strontium, and barium at gestation, while behavioral outcomes were associated with elevated biometals, i.e., sodium, magnesium, calcium, selenium, and zinc, as well as higher levels of lithium, cobalt, nickel, strontium, cadmium, vanadium, arsenic, and molybdenum. A heatmap of adjusted relative risk estimates indicates the considerable implications that exposure to metals may have for preterm birth and developmental outcomes.

Conclusions
The current study shows that perinatal exposure to metals is adversely associated with pediatric morbidity. Further such analyses on additional samples are warranted.
RiboA: a web application to identify ribosome A-site locations in ribosome profiling data
Authors: Shao Danying , Ahmed Nabeel , Soni Nishant , O’Brien Edward P. 
Published: March 2021

AbstractBackgroundTranslation is a fundamental process in gene expression. Ribosome profiling is a method that enables the study of transcriptome-wide translation. A fundamental, technical challenge in analyzing Ribo-Seq data is identifying the A-site location on ribosome-protected mRNA fragments. Identification of the A-site is essential as it is at this location on the ribosome where a codon is translated into an amino acid. Incorrect assignment of a read to the A-site can lead to lower signal-to-noise ratio and loss of correlations necessary to understand the molecular factors influencing translation. Therefore, an easy-to-use and accurate analysis tool is needed to accurately identify the A-site locations.ResultsWe present RiboA, a web application that identifies the most accurate A-site location on a ribosome-protected mRNA fragment and generates the A-site read density profiles. It uses an Integer Programming method that reflects the biological fact that the A-site of actively translating ribosomes is generally located between the second codon and stop codon of a transcript, and utilizes a wide range of mRNA fragment sizes in and around the coding sequence (CDS). The web application is containerized with Docker, and it can be easily ported across platforms.ConclusionsThe Integer Programming method that RiboA utilizes is the most accurate in identifying the A-site on Ribo-Seq mRNA fragments compared to other methods. RiboA makes it easier for the community to use this method via a user-friendly and portable web application. In addition, RiboA supports reproducible analyses by tracking all the input datasets and parameters, and it provides enhanced visualization to facilitate scientific exploration. RiboA is available as a web service athttps://a-site.vmhost.psu.edu/. The code is publicly available athttps://github.com/obrien-lab/aip_web_dockerunder the MIT license.
Denoising large-scale biological data using network filters
Authors: Kavran Andrew J. , Clauset Aaron 
Published: March 2021

AbstractBackgroundLarge-scale biological data sets are often contaminated by noise, which can impede accurate inferences about underlying processes. Such measurement noise can arise from endogenous biological factors like cell cycle and life history variation, and from exogenous technical factors like sample preparation and instrument variation.ResultsWe describe a general method for automatically reducing noise in large-scale biological data sets. This method uses an interaction network to identify groups of correlated or anti-correlated measurements that can be combined or “filtered” to better recover an underlying biological signal. Similar to the process of denoising an image, a single network filter may be applied to an entire system, or the system may be first decomposed into distinct modules and a different filter applied to each. Applied to synthetic data with known network structure and signal, network filters accurately reduce noise across a wide range of noise levels and structures. Applied to a machine learning task of predicting changes in human protein expression in healthy and cancerous tissues, network filtering prior to training increases accuracy up to 43% compared to using unfiltered data.ConclusionsNetwork filters are a general way to denoise biological data and can account for both correlation and anti-correlation between different measurements. Furthermore, we find that partitioning a network prior to filtering can significantly reduce errors in networks with heterogenous data and correlation patterns, and this approach outperforms existing diffusion based methods. Our results on proteomics data indicate the broad potential utility of network filters to applications in systems biology.
BugSeq: a highly accurate cloud platform for long-read metagenomic analyses
Authors: Fan Jeremy , Huang Steven , Chorlton Samuel D. 
Published: March 2021

Abstract
Background
As the use of nanopore sequencing for metagenomic analysis increases, tools capable of performing long-read taxonomic classification (ie. determining the composition of a sample) in a fast and accurate manner are needed. Existing tools were either designed for short-read data (eg. Centrifuge), take days to analyse modern sequencer outputs (eg. MetaMaps) or suffer from suboptimal accuracy (eg. CDKAM). Additionally, all tools require command line expertise and do not scale in the cloud.

Results
We present BugSeq, a novel, highly accurate metagenomic classifier for nanopore reads. We evaluate BugSeq on simulated data, mock microbial communities and real clinical samples. On the ZymoBIOMICS Even and Log communities, BugSeq (F1 = 0.95 at species level) offers better read classification than MetaMaps (F1 = 0.89–0.94) in a fraction of the time. BugSeq significantly improves on the accuracy of Centrifuge (F1 = 0.79–0.93) and CDKAM (F1 = 0.91–0.94) while offering competitive run times. When applied to 41 samples from patients with lower respiratory tract infections, BugSeq produces greater concordance with microbiological culture and qPCR compared with “What’s In My Pot” analysis.

Conclusion
BugSeq is deployed to the cloud for easy and scalable long-read metagenomic analyses. BugSeq is freely available for non-commercial use at https://bugseq.com/free.
Combined embedding model for MiRNA-disease association prediction
Authors: Liu Bailong , Zhu Xiaoyan , Zhang Lei , Liang Zhizheng , Li Zhengwei 
Published: March 2021

AbstractBackgroundCumulative evidence from biological experiments has confirmed that miRNAs have significant roles to diagnose and treat complex diseases. However, traditional medical experiments have limitations in time-consuming and high cost so that they fail to find the unconfirmed miRNA and disease interactions. Thus, discovering potential miRNA-disease associations will make a contribution to the decrease of the pathogenesis of diseases and benefit disease therapy. Although, existing methods using different computational algorithms have favorable performances to search for the potential miRNA-disease interactions. We still need to do some work to improve experimental results.ResultsWe present a novel combined embedding model to predict MiRNA-disease associations (CEMDA) in this article. The combined embedding information of miRNA and disease is composed of pair embedding and node embedding. Compared with the previous heterogeneous network methods that are merely node-centric to simply compute the similarity of miRNA and disease, our method fuses pair embedding to pay more attention to capturing the features behind the relative information, which models the fine-grained pairwise relationship better than the previous case when each node only has a single embedding. First, we construct the heterogeneous network from supported miRNA-disease pairs, disease semantic similarity and miRNA functional similarity. Given by the above heterogeneous network, we find all the associated context paths of each confirmed miRNA and disease. Meta-paths are linked by nodes and then input to the gate recurrent unit (GRU) to directly learn more accurate similarity measures between miRNA and disease. Here, the multi-head attention mechanism is used to weight the hidden state of each meta-path, and the similarity information transmission mechanism in a meta-path of miRNA and disease is obtained through multiple network layers. Second, pair embedding of miRNA and disease is fed to the multi-layer perceptron (MLP), which focuses on more important segments in pairwise relationship. Finally, we combine meta-path based node embedding and pair embedding with the cost function to learn and predict miRNA-disease association. The source code and data sets that verify the results of our research are shown athttps://github.com/liubailong/CEMDA.ConclusionsThe performance of CEMDA in the leave-one-out cross validation and fivefold cross validation are 93.16% and 92.03%, respectively. It denotes that compared with other methods, CEMDA accomplishes superior performance. Three cases with lung cancers, breast cancers, prostate cancers and pancreatic cancers show that 48,50,50 and 50 out of the top 50 miRNAs, which are confirmed in HDMM V2.0. Thus, this further identifies the feasibility and effectiveness of our method.
Distinction between vaginal and cervical microbiota in high-risk human papilloma virus-infected women in China
Authors: Zhang Zhan , Li Ting , Zhang Dai , Zong Xiaonan , Bai Huihui , Bi Hui , Liu Zhaohui 
Published: March 2021

Abstract
Background
High-risk human papilloma virus (hrHPV) is the main causal factor of cervical precancer and cancer when persistent infection is left untreated. Previous studies have confirmed the vaginal microbiota is associated with HPV infection and the development of cervical lesions. The microbiota at different parts of the female genital tract is closely related but different from each other. To analyze the distinction between the vaginal and cervical microbiota of hrHPV(+) women in China, one hundred subjects were recruited, including 10 patients with HPV16/18(+) and cervical carcinoma, 38 patients with HPV16/18(+) but no cervical carcinoma, 32 patients with other hrHPV(+) and 20 healthy controls with HPV(−). Vaginal and cervical microbiota were separately tested through next-generation sequencing (NGS) targeting the variable region (V3-V4) of the bacterial ribosome 16S rRNA gene.

Results
HrHPV(+) subjects had higher percentages of vaginal douching history (P = 0.001), showed more frequent usage of sanitary pads (P = 0.007), had more sex partners (P = 0.047), were more sexually active (P = 0.025) and more diversed in ways of contraception (P = 0.001). The alpha diversity of the cervical microbiota was higher than that of the vagina. The cervical microbiota consisted of a lower percentage of Firmicutes and a higher percentage of Proteobacteria than the vagina at the phylum level. Sphingomonas, belonging to α-Proteobacteria, was almost below the detection limit in the vagina but accounted for five to 10 % of the bacteria in the hrHPV(−) cervix (P<0.001) and was inversely associated with hrHPV infection (P<0.05). Pseudomonas, belonging to γ-Proteobacteria, could hardly be seen in the normal vagina and shared a small percentage in the normal cervix but was significantly higher in the HPV16/18(+) (P<0.001) and cancerous cervix (P<0.05). No significant difference was shown in the percentage of BV associated anaerobes, like Gardnerella, Prevotella, Atopobium and Sneathia, between the cevix and vigina.

Conclusions
The proportion of Proteobacteria was significantly higher in the cervical microbiota than that of vagina. The hrHPV infection and cervical cancer was positively associated with Pseudomonas and negatively associated with Sphingomonas. It is of great improtance to deeply explore the cervical microbiota and its function in cervical cacinogenesis.
A patient with single coronary artery, bicuspid aortic valve and sinus of Valsalva aneurysm
Authors: Mohammad Ahmed N. , Eboh Oghenesuvwe , Mian Muna , Shammas Rony L. 
Published: March 2021

Abstract
Background
We report a rare case of a patient who presented with chest pain and was found to have a constellation of rare cardiac anomalies.

Case presentation
A 67-year-old patient with no past medical history presented with chest pain. He had mild troponin elevation, but no ischemic changes on ECG. He underwent a CT coronary angiogram for further evaluation. He was found to have a type 0 bicuspid aortic valve, large left sinus of Valsalva aneurysm and type R-III single coronary artery. These findings were confirmed with transesophageal echocardiogram and coronary angiogram. He underwent a successful repair of his aortic root aneurysm with a synthetic patch.

Conclusions
The combination of type R-III single coronary artery, bicuspid aortic valve, and left sinus of Valsalva aneurysm congenital anomalies in one individual is extremely rare and marks our case unique. Given the size of his Sinus of Valsalva aneurysm, the patient underwent surgical repair of his aneurysm and was asymptomatic when seen in follow-up.
Associations between essential medicines and health outcomes for cardiovascular disease
Authors: Steiner Liane , Fraser Shawn , Maraj Darshanand , Persaud Nav 
Published: March 2021

Abstract
Background
National essential medicines lists are used to guide medicine reimbursement and public sector medicine procurement for many countries therefore medicine listings may impact health outcomes.

Methods
Countries’ national essential medicines lists were scored on whether they listed proven medicines for ischemic heart disease, cerebrovascular disease and hypertensive heart disease. In this cross sectional study linear regression was used to measure the association between countries’ medicine coverage scores and healthcare access and quality scores.

Results
There was an association between healthcare access and quality scores and health expenditure for ischemic heart disease (p ≤ 0.001), cerebrovascular disease (p ≤ 0.001) and hypertensive heart disease (p ≤ 0.001). However, there was no association between medicine coverage scores and healthcare access and quality scores for ischemic heart disease (p = 0.252), cerebrovascular disease (p = 0.194) and hypertensive heart disease (p = 0.209) when country characteristics were accounted for.

Conclusions
Listing more medicines on national essential medicines lists may only be one factor in reducing mortality from cardiovascular disease and improving healthcare access and quality scores.