bluuebunny/crossref_metadata_2025_split huggingface dataset:
Quantitative analysis of differentially expressed proteins in psoriasis vulgaris using tandem mass tags and parallel reaction monitoring
Authors: Li Yu , Lin Peng , Wang Siyao , Li Shuang , Wang Rui , Yang Lin , Wang Hongmei 
Published: August 2020

Abstract
Background
Psoriasis vulgaris (PV) is a chronic autoimmune inflammatory disease with epidermal hyperkeratosis and parakeratosis.

Methods
The study was to elucidate the pathogenesis of PV by quantitative proteomic analysis of skin lesion biopsies of PV and healthy tissues with tandem mass tags (TMTs) coupled with liquid chromatography–mass spectrometry (LC–MS)/MS.

Results
A total of 4562 differentially expressed proteins (DEPs) between PV lesional tissues (n = 11) and healthy tissues (n = 11) were identified, of which 299 were upregulated and 206 were downregulated using |fold change| > 1.3 as the cutoff threshold. The Gene Ontology (GO) annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis revealed that the DEPs were mainly enriched in the activation of immune cells (drug metabolism pathway, NOD-like pathway, and IL-17 pathway), cell proliferation (ribosomal pathway, DNA replication pathway, and base replication pathway), metabolism-related pathways (fatty acid biosynthesis and metabolism, PPAR pathway, glycerophospholipid metabolism, and cortisol synthesis and breakdown), and glandular secretion (saliva secretion, gastric acid secretion, and pancreatic fluid secretion). Thirteen DEPs that were relatively highly expressed in the drug metabolism pathway were validated with parallel reaction monitoring (PRM), of which MPO, TYMP, IMPDH2, GSTM4, and ALDH3A1 were highly expressed in PV, whereas CES1, MAOB, MGST1, and GSTT1 were less expressed in PV.

Conclusions
These findings confirmed that these proteins participate in the drug metabolism-other enzyme pathways and play crucial roles in the activation and proliferation of immune cells in the pathogenesis of PV.
UvAtg8-Mediated Autophagy Regulates Fungal Growth, Stress Responses, Conidiation, and Pathogenesis in Ustilaginoidea virens
Authors: Meng Shuai , Xiong Meng , Jagernath Jane Sadhna , Wang Congcong , Qiu Jiehua , Shi Huanbin , Kou Yanjun 
Published: August 2020

Abstract
Background
Ustilaginoidea virens has become one of the most devastating rice pathogens in China, as well as other rice-growing areas. Autophagy is an important process in normal cell differentiation and development among various organisms. To date, there has been no optimized experimental system introduced for the study of autophagy in U. virens. In addition, the function of autophagy in pathogenesis remains unknown in U. virens. Therefore, the functional analyses of UvAtg8 may potentially shed some light on the regulatory mechanism and function of autophagy in U. virens.

Results
In this study, we characterized the functions of UvAtg8, which is a homolog of Saccharomyces cerevisiae ScAtg8, in the rice false smut fungus U. virens. The results showed that UvATG8 is essential for autophagy in U. virens. Also, the GFP-UvATG8 strain, which could serve as an appropriate marker for monitoring autophagy in U. virens, was generated. Furthermore, this study found that the ΔUvatg8 mutant was defective in the vegetative growth, conidiation, adaption to oxidative, hyperosmotic, cell wall stresses, and production of toxic compounds. Pathogenicity assays indicated that deletion of UvATG8 resulted in significant reduction in virulence of U. virens. Further microscopic examinations of the infection processes revealed that the severe virulence defects in the ∆Uvatg8 were mainly caused by the highly reduced conidiation and secondary spore formation.

Conclusions
Our results indicated that the UvAtg8 is necessary for the fungal growth, stresses responses, conidiation, secondary spore formation, and pathogenicity of U. virens. Moreover, our research finding will potentially assist in further clarifying the molecular mechanism of U. virens infection, as well as provide a good marker for autophagy in U. virens and a good reference value for the further development of effective fungicides based on gene targeting.
NPF:network propagation for protein function prediction
Authors: Zhao Bihai , Zhang Zhihong , Jiang Meiping , Hu Sai , Luo Yingchun , Wang Lei 
Published: August 2020

AbstractBackgroundThe accurate annotation of protein functions is of great significance in elucidating the phenomena of life, treating disease and developing new medicines. Various methods have been developed to facilitate the prediction of these functions by combining protein interaction networks (PINs) with multi-omics data. However, it is still challenging to make full use of multiple biological to improve the performance of functions annotation.ResultsWe presented NPF (Network Propagation for Functions prediction), an integrative protein function predicting framework assisted by network propagation and functional module detection, for discovering interacting partners with similar functions to target proteins. NPF leverages knowledge of the protein interaction network architecture and multi-omics data, such as domain annotation and protein complex information, to augment protein-protein functional similarity in a propagation manner. We have verified the great potential of NPF for accurately inferring protein functions. According to the comprehensive evaluation of NPF, it delivered a better performance than other competing methods in terms of leave-one-out cross-validation and ten-fold cross validation.ConclusionsWe demonstrated that network propagation, together with multi-omics data, can both discover more partners with similar function, and is unconstricted by the “small-world” feature of protein interaction networks. We conclude that the performance of function prediction depends greatly on whether we can extract and exploit proper functional information of similarity from protein correlations.
Game theoretic centrality: a novel approach to prioritize disease candidate genes by combining biological networks with the Shapley value
Authors: Sun Min Woo , Moretti Stefano , Paskov Kelley M. , Stockham Nate T. , Varma Maya , Chrisman Brianna S. , Washington Peter Y. , Jung Jae-Yoon , Wall Dennis P. 
Published: August 2020

AbstractBackgroundComplex human health conditions with etiological heterogeneity like Autism Spectrum Disorder (ASD) often pose a challenge for traditional genome-wide association study approaches in defining a clear genotype to phenotype model. Coalitional game theory (CGT) is an exciting method that can consider the combinatorial effect of groups of variants working in concert to produce a phenotype. CGT has been applied to associate likely-gene-disrupting variants encoded from whole genome sequence data to ASD; however, this previous approach cannot take into account for prior biological knowledge. Here we extend CGT to incorporate a priori knowledge from biological networks through a game theoretic centrality measure based on Shapley value to rank genes by their relevance–the individual gene’s synergistic influence in a gene-to-gene interaction network. Game theoretic centrality extends the notion of Shapley value to the evaluation of a gene’s contribution to the overall connectivity of its corresponding node in a biological network.ResultsWe implemented and applied game theoretic centrality to rank genes on whole genomes from 756 multiplex autism families. Top ranking genes with the highest game theoretic centrality in both the weighted and unweighted approaches were enriched for pathways previously associated with autism, including pathways of the immune system. Four of the selected genes HLA-A, HLA-B, HLA-G, and HLA-DRB1–have also been implicated in ASD and further support the link between ASD and the human leukocyte antigen complex.ConclusionsGame theoretic centrality can prioritize influential, disease-associated genes within biological networks, and assist in the decoding of polygenic associations to complex disorders like autism.
To bloom once or more times: the reblooming mechanisms of Iris germanica revealed by transcriptome profiling
Authors: Fan Zhuping , Gao Yike , Ren Yi , Guan Chunjing , Liu Rong , Zhang Qixiang 
Published: August 2020

Abstract
Background
The reblooming bearded iris (Iris germanica) can bloom twice a year, in spring and autumn. The extended ornamental period makes it more popular and brings additional commercial values. However, little is known about the reblooming mechanisms, making the breeding programs time-consuming and labor-wasting. Therefore, a comparative transcriptome profiling was conducted on once-bloomers and rebloomers from the same F1 generation on six development stages, and the candidate genes associated with reblooming were identified.

Results
A total of 100,391 unigenes were generated, the mean length being 785 bp. In the three comparisons (the floral initiation stage of spring flowering in once-bloomers (OB-T1) vs the floral initiation stage of spring flowering in rebloomers (RB-T1); RB-T1 vs the floral initiation stage of autumn flowering in rebloomers (RB-T5); OB-T1 vs RB-T5), a total of 690, 3515 and 2941 differentially expressed genes (DEGs) were annotated against the public databases, respectively. The Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis focused on the photoperiod response, the temperature insensitivity and the growth speed, to remove the redundant DEGs and figure out the candidate key genes. As a result, the following four genes, PHYTOCHROME A (PHYA), GIGANTEA (GI), SHORT VEGETATIVE PERIOD (SVP) and AUXIN RESPONSE FACTOR (ARF), were considered to be involved in the second floral initiation of the rebloomers.

Conclusion
This research provides valuable information for the discovery of the reblooming-related genes. The insights into the molecular mechanisms of reblooming may accelerate the breeding of bearded iris and other perennials.
Gut microbiome of endangered Tor putitora (Ham.) as a reservoir of antibiotic resistance genes and pathogens associated with fish health
Authors: Khurana Himani , Singh Durgesh Narain , Singh Anoop , Singh Yogendra , Lal Rup , Negi Ram Krishan 
Published: August 2020

Abstract
Background
Tor putitora, the largest freshwater fish of the Indian subcontinent, is an endangered species. Several factors have been attributed towards its continuous population decrease, but very little is known about the gut microbiome of this fish. Also, the fish gut microbiome serves as a reservoir of virulence factors and antibiotic resistance determinants. Therefore, the shotgun metagenomic approach was employed to investigate the taxonomic composition and functional potential of microbial communities present in the gut of Tor putitora, as well as the detection of virulence and antibiotic resistance genes in the microbiome.

Results
The analysis of bacterial diversity showed that Proteobacteria was predominant phylum, followed by Chloroflexi, Bacteroidetes, and Actinobacteria. Within Proteobacteria, Aeromonas and Caulobacter were chiefly present; also, Klebsiella, Escherichia, and plant symbionts were noticeably detected. Functional characterization of gut microbes endowed the virulence determinants, while surveillance of antibiotic resistance genes showed the dominance of β-lactamase variants. The antibiotic-resistant Klebsiella pneumoniae and Escherichia coli pathovars were also detected. Microbial genome reconstruction and comparative genomics confirmed the presence of Aeromonads, the predominant fish pathogens.

Conclusions
Gut microbiome of endangered Tor putitora consisted of both commensals and opportunistic pathogens, implying that factors adversely affecting the non-pathogenic population would allow colonization and proliferation of pathogens causing diseased state in asymptomatic Tor putitora. The presence of virulence factors and antibiotic resistance genes suggested the potential risk of dissemination to other bacteria due to horizontal gene transfer, thereby posing a threat to fish and human health. The preservation of healthy gut microflora and limited use of antibiotics are some of the prerequisites for the conservation of this imperilled species.
A randomised dose-response study of prophylactic Methoxamine infusion for preventing spinal-induced hypotension during Cesarean delivery
Authors: Fu Feng , Tang Yu-wen , Chen Hong , Jiao Cui-cui , Ma Na , Chen Xin-zhong 
Published: August 2020

Abstract
Background
α-receptor agonists have been reported to be safe and effective for treating or preventing spinal-induced hypotension during cesarean delivery. As a pure α1 adrenergic agonist, methoxamine has potential advantages of reducing myocardial oxygen consumption and protecting the heart in obstetric patients compared to phenylephrine. The aim of this study was to determine the optimal prophylactic methoxamine infusion dose that would be effective for preventing spinal-induced hypotension in 50% (ED50) and 95% (ED95) of parturients.

Methods
Eighty parturients with a singleton pregnancy scheduled for elective cesarean delivery were randomly allocated to receive prophylactic methoxamine infusion at one of four different fixed-rates: 1 μg/kg/min (group M1), 2 μg/kg/min (group M2), 3 μg/kg/min (group M3), or 4 μg/kg/min (group M4). An adequate response was defined as absence of hypotension (maternal SBP < 80% of baseline or SBP < 90 mmHg). The values for ED50 and ED95 of prophylactic methoxamine infusion were determined by probit regression model. The outcomes of maternal hemodynamics and fetal status were compared among the groups.

Results
The calculated ED50 and ED95 (95% confidence interval) of prophylactic methoxamine infusion dose were 2.178 (95% CI 1.564 to 2.680) μg/kg/min and 4.821 (95% CI 3.951 to 7.017) μg/kg/min, respectively. The incidence of hypotension decreased with increasing methoxamine infusion dose (15/20, 11/20, 7/20 and 2/20 in group M1, M2, M3 and M4 respectively, P <  0.001). 1-min Apgar scores and umbilical arterial PaO2 were lower but umbilical arterial PaCO2 was higher in Group M1. No difference was found in the other incidence of adverse effects and neonatal outcomes among groups.

Conclusions
Under the conditions of this study, when prophylactic methoxamine infusion was given at a fixed-rate based on body weight for preventing spinal-induced hypotension in obstetric patients, the values for ED50 and ED95 were 2.178 μg/kg/min and 4.821 μg/kg/min respectively.

Clinical trial registration
Chinese Clinical Trial Registry (ChiCTR), registry number of clinical trial: ChiCTR-1,800,018,988, date of registration: October 20, 2018.
A four-step strategy for handling missing outcome data in randomised trials affected by a pandemic
Authors: Cro Suzie , Morris Tim P. , Kahan Brennan C. , Cornelius Victoria R. , Carpenter James R. 
Published: August 2020

AbstractBackgroundThe coronavirus pandemic (Covid-19) presents a variety of challenges for ongoing clinical trials, including an inevitably higher rate of missing outcome data, with new and non-standard reasons for missingness. International drug trial guidelines recommend trialists review plans for handling missing data in the conduct and statistical analysis, but clear recommendations are lacking.MethodsWe present a four-step strategy for handling missing outcome data in the analysis of randomised trials that are ongoing during a pandemic. We consider handling missing data arising due to (i) participant infection, (ii) treatment disruptions and (iii) loss to follow-up. We consider both settings where treatment effects for a ‘pandemic-free world’ and ‘world including a pandemic’ are of interest.ResultsIn any trial, investigators should; (1) Clarify the treatment estimand of interest with respect to the occurrence of the pandemic; (2) Establish what data are missing for the chosen estimand; (3) Perform primary analysis under the most plausible missing data assumptions followed by; (4) Sensitivity analysis under alternative plausible assumptions. To obtain an estimate of the treatment effect in a ‘pandemic-free world’, participant data that are clinically affected by the pandemic (directly due to infection or indirectly via treatment disruptions) are not relevant and can be set to missing. For primary analysis, a missing-at-random assumption that conditions on all observed data that are expected to be associated with both the outcome and missingness may be most plausible. For the treatment effect in the ‘world including a pandemic’, all participant data is relevant and should be included in the analysis. For primary analysis, a missing-at-random assumption – potentially incorporating a pandemic time-period indicator and participant infection status – or a missing-not-at-random assumption with a poorer response may be most relevant, depending on the setting. In all scenarios, sensitivity analysis under credible missing-not-at-random assumptions should be used to evaluate the robustness of results. We highlight controlled multiple imputation as an accessible tool for conducting sensitivity analyses.ConclusionsMissing data problems will be exacerbated for trials active during the Covid-19 pandemic. This four-step strategy will facilitate clear thinking about the appropriate analysis for relevant questions of interest.
Disease progression of cancer patients during COVID-19 pandemic: a comprehensive analytical strategy by time-dependent modelling
Authors: Bhattacharjee Atanu , Vishwakarma Gajendra K. , Banerjee Souvik , Shukla Sharvari 
Published: August 2020

AbstractBackgroundAs the whole world is experiencing the cascading effect of a new pandemic, almost every aspect of modern life has been disrupted. Because of health emergencies during this period, widespread fear has resulted in compromised patient safety, especially for patients with cancer. It is very challenging to treat such cancer patients because of the complexity of providing care and treatment, along with COVID-19. Hence, an effective treatment comparison strategy is needed. We need to have a handy tool to understand cancer progression in this unprecedented scenario. Linking different events of cancer progression is the need of the hour. It is a huge challenge for the development of new methodology.MethodsThis article explores the time lag effect and makes a statistical inference about the best experimental arm using Accelerated Failure Time (AFT) model and regression methods. The work is presented as the occurrence of other events as a hazard rate after the first event (relapse). The time lag effect between the events is linked and analysed.ResultsThe results were presented as a comprehensive analytical strategy by joining all disease progression. An AFT model applied with the transition states, and the dependency structure between the gap times was used by the auto-regression model. The effects of arms were compared using the coefficient of auto-regression and accelerated failure time (AFT) models.ConclusionsWe provide the solutions to overcome the issue with intervals between two consecutive events in motivating head and neck cancer (HNC) data. COVID-19 is not going to leave us soon. We have to conduct several cancer clinical trials in the presence of COVID-19. A comprehensive analytical strategy to analyse cancer clinical trial data during COVID-19 pandemic is presented.
Effect of financial stress on self-rereported health and quality of life among older adults in five developing countries: a cross sectional analysis of WHO-SAGE survey
Authors: Huang Rui , Ghose Bishwajit , Tang Shangfeng 
Published: August 2020

Abstract
In developing countries, older adults (65 years of age and above) share an increased vulnerability to catastrophic health expenditures and financial stress which can have significant bearing on their health and well-being. Currently, research evidence on how financial stress correlates with health and well-being among older adults in the developing countries is limited. Therefore, in this study, we aimed to assess the relationship between financial stress and subjective 1) health, 2) depression, 3) quality of life, and 4) life satisfaction among older adults in five developing countries.

Methods
Data used in this study were cross-sectional which were collected from the first wave of Study on Global AGEing and Health (SAGE) survey of World Health Organization. Sample population were 12,299 community dwelling men and women in China (n = 4548), Ghana (n = 1968), India (n = 2441), South Africa (n = 1924), and Russia (n = 1418). Using generalized linear models with logit links, we assessed the correlation between self-reported financial stress and income inequality with the four outcome measures by adjusting for various sociodemographic factors.

Results
Overall, the prevalence of good self-reported health, quality of life and positive life-satisfaction was 47.11, 79.25 and 44.40% respectively, while 20.13% of the participants reported having depression during past 12 months. Only about a fifth (18.67%) of the participants reported having enough money to meet daily their necessities completely, while more than quarter (28.45%) were in the lowest income quintile. With a few exceptions, the odds of reporting good self-reported health, quality of life, and life satisfaction were generally lower among those with varying degrees of financial stress, and larger among those in the higher income quintiles. Conversely, the likelihood of self-reported depression was significantly higher among those with any level of financial stress, and lower among those in the higher income quintiles.

Conclusion
This study concludes that both subjectively and objectively measured financial stress are inversely associated with good self-reported health, quality of life, life satisfaction, and positively associated with self-reported depression among older adults.
Genetic diversity of group A rotavirus in acute gastroenteritis outpatients in Shanghai from 2017 to 2018
Authors: Kuang Xiaozhou , Gong Xiaohuan , Zhang Xi , Pan Hao , Teng Zheng 
Published: August 2020

AbstractBackgroundGroup A Rotavirus (RVA), despite being an important pathogen in hospitalized children, is less studied in pediatric outpatients, and even rarely investigated in adults. This study aims to understand the genetic diversity of RVA in outpatients across all age groups in Shanghai, and thus providing a molecular basis for vaccine implementation and evaluation.MethodsStool samples were first screened by Real-time Reverse Transcription Polymerase Chain Reaction (rRT-PCR). RVA genotyping was performed through the amplification of partial VP7 and VP4 gene. Strains of interest were further sequenced and analyzed using MEGA 6.0.ResultsFour thousand nine hundred one samples were collected, from which 7.61% (373 cases) were screened positive for RVA. RVA prevalence was higher in children (9.30%) than in adults (7.21%) (χ2 = 4.72,P < 0.05). 9.38% RVA positive cases had taken antibiotics before hospital visit while 49.60% had been prescribed antibiotics afterwards. RVA displayed a strong seasonality in both adults and children with a shared commonality in genotype repertoire, where G9P[8] was the most prevalent strain (67.96%) followed by G3P[8] (15.49%) and G1P[8] (12.32%). Meanwhile the first local case of fecal shedding of the G10P[15] vaccine strain was also discovered.ConclusionsWhile the prevalence of rotavirus is highest during cold seasons, it is revealed for the first time that G9P[8] is the predominant genotype in both adults and pediatric outpatients. Clinically, higher occurrence of nausea or vomiting was observed in RVA positive cases. Antibiotic overuse was implicated in both non-clinical and clinical settings. The finding emphasizes the importance of RVA genotyping in surveillance as it provides the basis for new vaccine application as well as a baseline for future vaccine efficacy evaluation.