bluuebunny/crossref_metadata_2025_split huggingface dataset:
A Bayesian Sensitivity Analysis to Partition Body Mass Index Into Components of Body Composition: An Application to Head and Neck Cancer Survival
Authors: Bradshaw Patrick T , Zevallos Jose P , Wisniewski Kathy , Olshan Andrew F 
Published: August 2019

AbstractPrevious studies have suggested a “J-shaped” relationship between body mass index (BMI, calculated as weight (kg)/height (m)2) and survival among head and neck cancer (HNC) patients. However, BMI is a vague measure of body composition. To provide greater resolution, we used Bayesian sensitivity analysis, informed by external data, to model the relationship between predicted fat mass index (FMI, adipose tissue (kg)/height (m)2), lean mass index (LMI, lean tissue (kg)/height (m)2), and survival. We estimated posterior median hazard ratios and 95% credible intervals for the BMI-mortality relationship in a Bayesian framework using data from 1,180 adults in North Carolina with HNC diagnosed between 2002 and 2006. Risk factors were assessed by interview shortly after diagnosis and vital status through 2013 via the National Death Index. The relationship between BMI and all-cause mortality was convex, with a nadir at 28.6, with greater risk observed throughout the normal weight range. The sensitivity analysis indicated that this was consistent with opposing increases in risk with FMI (per unit increase, hazard ratio = 1.04 (1.00, 1.08)) and decreases with LMI (per unit increase, hazard ratio = 0.90 (0.85, 0.95)). Patterns were similar for HNC-specific mortality but associations were stronger. Measures of body composition, rather than BMI, should be considered in relation to mortality risk.
What is Machine Learning? A Primer for the Epidemiologist
Authors: Bi Qifang , Goodman Katherine E , Kaminsky Joshua , Lessler Justin 
Published: August 2019

AbstractMachine learning is a branch of computer science that has the potential to transform epidemiologic sciences. Amid a growing focus on “Big Data,” it offers epidemiologists new tools to tackle problems for which classical methods are not well-suited. In order to critically evaluate the value of integrating machine learning algorithms and existing methods, however, it is essential to address language and technical barriers between the two fields that can make it difficult for epidemiologists to read and assess machine learning studies. Here, we provide an overview of the concepts and terminology used in machine learning literature, which encompasses a diverse set of tools with goals ranging from prediction to classification to clustering. We provide a brief introduction to 5 common machine learning algorithms and 4 ensemble-based approaches. We then summarize epidemiologic applications of machine learning techniques in the published literature. We recommend approaches to incorporate machine learning in epidemiologic research and discuss opportunities and challenges for integrating machine learning and existing epidemiologic research methods.
Complement Components sC5b-9 and CH50 Predict Prognosis in Heart Failure Patients Combined With Hypertension
Authors: Wang Wenyuan , Cai Dinghua 
Published: August 2019

AbstractBACKGROUNDHeart failure (HF), resulting from inflammation and vessel injury, is one of the leading causes of poor quality of life and premature death. The complement system plays a leading role in vessel integrity and inflammation response. However, the association between serum complement level and the prognosis of HF remains unclear.METHODSIn our study, a total of 263 newly diagnosed hypertension patients with HF were included. Eight classical cardiovascular risk factors were collected, and plasma C3a, C3b, C5a, sC5b-9, and CH50 levels were detected.RESULTSCompared with the control group, plasma C5a (P&lt;0.001), sC5b-9 (P&lt;0.001), and CH50 (P = 0.004) levels of hypertension patients with HF were significantly increased. On the basis of univariate analysis, an older age, higher frequency of alcohol consumption, high level of body mass index, medium or high risk of hypertension, hyperlipidemia, and diabetes were poor prognostic factors whereas low levels of C5a, sC5b-9, and CH50 were associated with favorable overall survival (OS). When these factors fit into a multivariate regression model, patients with hyperlipidemia (P = 0.002, hazard ratio [HR] = 3.09), N-terminal pro-Brain Natriuretic Peptide (NT-pro-BNP) ≥ 14.8 (P &lt; 0.001, HR = 11.14), sC5b-9 level ≥ 1,406.2 µg/ml (P = 0.180, HR = 5.51) or CH50 level ≥ 294.6 µg/ml (P &lt; 0.001, HR = 4.57) remained statistically factors for worsened OS and regarded as independent risk factors. These independently associated risk factors were used to form an OS estimation nomogram. Nomogram demonstrated good accuracy in estimating the risk, with a bootstrap-corrected C index of 0.789.CONCLUSIONSsC5b-9 and CH50 levels are increased in hypertension patients with HF. Nomogram based on multivariate analysis has good accuracy in estimating the risk of OS.
Reward, Relief and Habit Drinking: Initial Validation of a Brief Assessment Tool
Authors: Grodin Erica N , Bujarski Spencer , Venegas Alexandra , Baskerville Wave-Ananda , Nieto Steven J , Jentsch J David , Ray Lara A 
Published: August 2019

AbstractAimsAlcohol use disorder is highly heterogeneous. One approach to understanding this heterogeneity is the identification of drinker subtypes. A candidate classification consists of reward and relief subtypes. The current study examines a novel self-report measure of reward, relief, and habit drinking for its clinical correlates and subjective response (SR) to alcohol administration.MethodsNon-treatment-seeking heavy drinkers (n = 140) completed the brief reward, relief, habit drinking scale (RRHDS). A subset of this sample (n = 67) completed an intravenous alcohol administration. Individuals were classified into drinker subtypes. A crowdsourced sample of heavy drinkers (n = 187) completed the RRHDS and a validated reward relief drinking scale to compare drinking classification results.ResultsThe majority of the sample was classified as reward drinkers (n = 100), with fewer classified as relief (n = 19) and habit (n = 21) drinkers. Relief and habit drinkers reported greater tonic alcohol craving compared to reward drinkers. Reward drinkers endorsed drinking for enhancement, while relief drinkers endorsed drinking for coping. Regarding the alcohol administration, the groups differed in negative mood, such that relief/habit drinkers reported a decrease in negative mood during alcohol administration, compared to reward drinkers. The follow-up crowdsourcing study found a 62% agreement in reward drinker classification between measures and replicated the tonic craving findings.ConclusionsOur findings suggest that reward drinkers are dissociable from relief/habit drinkers using the brief measure. However, relief and habit drinkers were not successfully differentiated, which suggests that these constructs may overlap phenotypically. Notably, measures of dysphoric mood were better at detecting group differences than measures capturing alcohol’s rewarding effects.
Fitness costs of delayed pollination in a mixed-mating plant
Authors: Hildesheim Laura S , Opedal Øystein H , Armbruster W Scott , Pélabon Christophe 
Published: August 2019

AbstractBackground and AimsTo predict the evolutionary consequences of pollinator declines, we need to understand the evolution of delayed autonomous self-pollination, which is expected to evolve as a mechanism of reproductive assurance when cross-pollination becomes unreliable. This involves estimating the costs of increased levels of selfing as well as those associated with floral senescence.MethodsWe studied the mechanisms and costs of delayed self-pollination in the mixed-mating vine Dalechampia scandens (Euphorbiaceae) by first assessing among-population variation in herkogamy and dichogamy, which together determine the rate and timing of autonomous self-pollination. We then tested whether floral longevity responds plastically to delayed pollination. Finally, we assessed the costs of delayed self-pollination in terms of seed number and size, explicitly separating inbreeding depression from effects of floral senescence.Key ResultsHerkogamy varied extensively, while variation in dichogamy was more limited. Unpollinated blossoms increased their longevity, but seed quantity and quality decreased with increasing delays in pollination, independently of inbreeding depression.ConclusionsIn D. scandens, earlier autonomous selfing is facilitated by reduced herkogamy rather than reduced protogyny, providing reproductive assurance while maintaining the possibility for outcrossing events. Effective early autonomous self-pollination may evolve under reduced cross-pollination reliability in response to costs associated with floral senescence.
‘I Was Surprised to See You in a Chinese School’: Researching Multilingually Opportunities and Challenges in Community-Based Research
Authors: Ganassin Sara , Holmes Prue 
Published: August 2019

AbstractResearchers working in multilingual contexts must draw on their own linguistic resources when conceptualizing, planning, conducting, and reporting their studies, whether for theses or publications, or in dissemination to other stakeholders. However, these multilingual processes have received little attention in previous research. Drawing on an ethnographic study undertaken by Sara Ganassin in Chinese community language education, we investigate what opportunities and challenges a ‘researching multilingually’ perspective offers the researcher. We analyse narrative data and ethnographic observations to illustrate how the researcher drew on her multilingual resources vis-a-vis the linguistic spaces of her research context, the reflexive aspects of her multilingual positionality, and the ethical choices faced by her. From these insights, we make a theoretical and methodological case for embedding a researching multilingually approach in research that recognizes the linguistic resources of the researcher. The study has implications for building researcher capacity in multilingual research contexts, and for highlighting multilingual researcher processes that improve understanding, reporting, and representation of people from diverse linguistic and cultural horizons.
Optimization of in silico tools for predicting genetic variants: individualizing for genes with molecular sub-regional stratification
Authors: Tang Bin , Li Bin , Gao Liang-Di , He Na , Liu Xiao-Rong , Long Yue-Sheng , Zeng Yang , Yi Yong-Hong , Su Tao , Liao Wei-Ping 
Published: August 2019

Abstract
Genes are unique in functional role and differ in their sensitivities to genetic defects, but with difficulties in pathogenicity prediction. This study attempted to improve the performance of existing in silico algorithms and find a common solution based on individualization strategy. We initiated the individualization with the epilepsy-related SCN1A variants by sub-regional stratification. SCN1A missense variants related to epilepsy were retrieved from mutation databases, and benign missense variants were collected from ExAC database. Predictions were performed by using 10 traditional tools with stepwise optimizations. Model predictive ability was evaluated using the five-fold cross-validations on variants of SCN1A, SCN2A, and KCNQ2. Additional validation was performed in SCN1A variants of damage-confirmed/familial epilepsy. The performance of commonly used predictors was less satisfactory for SCN1A with accuracy less than 80% and varied dramatically by functional domains of Nav1.1. Multistep individualized optimizations, including cutoff resetting, domain-based stratification, and combination of predicting algorithms, significantly increased predictive performance. Similar improvements were obtained for variants in SCN2A and KCNQ2. The predictive performance of the recently developed ensemble tools, such as Mendelian clinically applicable pathogenicity, combined annotation-dependent depletion and Eigen, was also improved dramatically by application of the strategy with molecular sub-regional stratification. The prediction scores of SCN1A variants showed linear correlations with the degree of functional defects and the severity of clinical phenotypes. This study highlights the need of individualized optimization with molecular sub-regional stratification for each gene in practice.
AntiHIV-Pred: web-resource for in silico prediction of anti-HIV/AIDS activity
Authors: Stolbov Leonid , Druzhilovskiy Dmitry , Rudik Anastasia , Filimonov Dmitry , Poroikov Vladimir , Nicklaus Marc 
Published: August 2019

Abstract

Motivation
Identification of new molecules promising for treatment of HIV-infection and HIV-associated disorders remains an important task in order to provide safer and more effective therapies. Utilization of prior knowledge by application of computer-aided drug discovery approaches reduces time and financial expenses and increases the chances of positive results in anti-HIV R&D. To provide the scientific community with a tool that allows estimating of potential agents for treatment of HIV-infection and its comorbidities, we have created a freely-available web-resource for prediction of relevant biological activities based on the structural formulae of drug-like molecules.

Results
Over 50 000 experimental records for anti-retroviral agents from ChEMBL database were extracted for creating the training sets. After careful examination, about seven thousand molecules inhibiting five HIV-1 proteins were used to develop regression and classification models with the GUSAR software. The average values of R2 = 0.95 and Q2 = 0.72 in validation procedure demonstrated the reasonable accuracy and predictivity of the obtained (Q)SAR models. Prediction of 81 biological activities associated with the treatment of HIV-associated comorbidities with 92% mean accuracy was realized using the PASS program.

Availability and implementation
Freely available on the web at http://www.way2drug.com/hiv/.

Supplementary information
Supplementary data are available at Bioinformatics online.
Distinct preterm labor phenotypes have unique inflammatory signatures and contraction associated protein profiles†
Authors: Singh Natasha , Herbert Bronwen , Sooranna Gavin , Das Anya , Sooranna Suren R , Yellon Steven M , Johnson Mark R 
Published: August 2019

AbstractPreterm labor (PTL) is the predominant cause of childhood morbidity and mortality. It has several phenotypes, each with a distinct etiology often involving inflammation. Here, in samples of reproductive tissues obtained in early PTL from women with phenotypically defined PTL, we examined the presence and distribution of inflammation and its relationship with prolabor gene expression. In chorioamnionitis (CA-PTL), cytokine protein concentrations were increased across all tissues; in idiopathic (I-PTL), the inflammatory changes were limited to the choriodecidua; inflammation was not a feature of placental abruption (PA-PTL). CA-PTL was associated with activation of p65 in the myometrium and AP-1 in the choriodecidua, and PA-PTL with CREB in the choriodecidua. In the myometrium, PGHS-2 mRNA level was increased in CA- and I-PTL; in the amnion, PGHS-2 mRNA level was higher in PA- and I-PTL, while in CA-PTL, OT, OTR mRNA, and CX-43 expression were increased. In the choriodecidua, PGHS-2 mRNA level was unchanged, but in CA and I-PTL, OT mRNA level were increased and OTR was reduced. These data show that CA-PTL is associated with widespread inflammation and prolabor gene expression. In contrast, in I-PTL, inflammation is limited to the choriodecidua, with discrete increases in PGHS-2 in the amnion and OT in the choriodecidua. Inflammation is not a feature of PA-PTL, which is associated with increased OT and OTR in the amnion.
Reasons for Staying: A Longitudinal Study of Work Conditions Predicting Social Workers’ Willingness to Stay in Their Organisation
Authors: Astvik Wanja , Welander Jonas , Larsson Robert 
Published: August 2019

AbstractExtensive staff turnover within the statutory social services is a serious problem in Sweden and in other European countries. This study examines which work conditions predict social workers’ willingness to stay in their organisation. A web-based questionnaire was used to gather data. The participating social workers responded to two questionnaires over a one-year period. To identify the social workers who wanted to stay and also remained in the organisation, the group ‘Stayers’ (n = 1,368) consisted of social workers who reported low intentions to quit at T1. The group ‘Leavers’ (n = 1,182) were social workers who had actually resigned at T2. The data were analysed using univariate and multivariate logistic regression analyses. The multivariate analysis shows that the work conditions that predicted staying in the organisation were low degrees of conflicting demands and quantitative demands, high degrees of openness and human resource orientation in the organisation and a high degree of perceived service quality. The results are discussed in relation to public management and managerial responsibility to create sustainable work conditions that facilitate the provision of good social services for citizens.
Synergistic anti-breast cancer effect of pulsatilla saponin D and camptothecin through interrupting autophagic–lysosomal function and promoting p62-mediated ubiquitinated protein aggregation
Authors: Wang Kai , Tu Yanbei , Wan Jian-Bo , Chen Meiwan , He Chengwei 
Published: August 2019

AbstractAutophagy is an evolutionarily conserved mechanism to protect the cells from unfavorable environmental conditions. Inhibition of autophagy has been contemplated as a novel strategy to enhance anticancer efficacy of existing chemotherapeutic agents. We previously reported that pulsatilla saponin D (PSD) was a potent autophagy inhibitor. However, its anticancer potential as adjuvant and underlying mechanisms are still unknown. In this study, we identified that PSD induced the formation of autophagosome in MCF-7 and MDA-MB-231 breast cancer cells. However, PSD alone and particularly co-treatment with camptothecin remarkably increased p62 protein levels, indicating that PSD strongly inhibited the autophagic cargo degradation. The mechanistic study indicated that PSD profoundly abolished the co-localization of EGFP-LC3 and lysosomal-specific probe LysoTracker Red, suggesting that the autophagosome–lysosome fusion was blocked by PSD, which is similar to the action of chloroquine. In addition, PSD significantly increased lysosomal pH and inhibited the activation of lysosomal cathepsins in both breast cancer cell lines. Furthermore, the accrued p62 resulted in accumulation of ubiquitinated proteins owing to the interaction with p62 and delivery to the malfunctioned autophagosome by PSD. Finally, we demonstrated that PSD synergistically enhanced the anticancer activity of camptothecin (CPT) in cultured breast cancer cells and in mouse xenograft tumor models. Our results indicated that PSD inhibited autophagic flux via blocking autophagosome–lysosome fusion and lysosomal acidification, which may confer a synergistic anti-breast cancer activity of PSD and CPT.
Neural Dynamics of Associative Learning during Human Sleep
Authors: Canales-Johnson Andrés , Merlo Emiliano , Bekinschtein Tristan A , Arzi Anat 
Published: August 2019

Abstract
Recent evidence indicates that humans can learn entirely new information during sleep. To elucidate the neural dynamics underlying sleep-learning, we investigated brain activity during auditory–olfactory discriminatory associative learning in human sleep. We found that learning-related delta and sigma neural changes are involved in early acquisition stages, when new associations are being formed. In contrast, learning-related theta activity emerged in later stages of the learning process, after tone–odor associations were already established. These findings suggest that learning new associations during sleep is signaled by a dynamic interplay between slow-waves, sigma, and theta activity.
Hospital-based Surveillance Provides Insights Into the Etiology of Pediatric Bacterial Meningitis in Yaoundé, Cameroon, in the Post-Vaccine Era
Authors: Boula Angeline , Senghore Madikay , Ngoh Rose , Tassadjo Flaubert , Fonkoua Marie-Christine , Nzouankeu Ariane , Njiki Mina Kenkela , Musi Jeanne , Bebey Sandrine , Ngo Baleba Madeline , Nkembe Angeline , Médjina Sidonie , Ndow Peter S , Worwui Archibald , Kobela Marie , Nimpa Marceline , Mwenda Jason M , N’diaye Aboubacar , Kwambana-Adams Brenda A , Antonio Martin 
Published: August 2019

Abstract

Background
Meningitis is endemic to regions of Cameroon outside the meningitis belt including the capital city, Yaoundé. Through surveillance, we studied the etiology and molecular epidemiology of pediatric bacterial meningitis in Yaoundé from 2010 to 2016.

Methods
Lumbar puncture was performed on 5958 suspected meningitis cases; 765 specimens were further tested by culture, latex agglutination, and/or polymerase chain reaction (PCR). Serotyping/grouping, antimicrobial susceptibility testing, and/or whole genome sequencing were performed where applicable.

Results
The leading pathogens detected among the 126 confirmed cases were Streptococcus pneumoniae (93 [73.8%]), Haemophilus influenzae (18 [14.3%]), and Neisseria meningitidis (15 [11.9%]). We identified more vaccine serotypes (19 [61%]) than nonvaccine serotypes (12 [39%]); however, in the latter years non–pneumococcal conjugate vaccine serotypes were more common. Whole genome data on 29 S. pneumoniae isolates identified related strains (<30 single-nucleotide polymorphism difference). All but 1 of the genomes harbored a resistance genotype to at least 1 antibiotic, and vaccine serotypes harbored more resistance genes than nonvaccine serotypes (P < .05). Of 9 cases of H. influenzae, 8 were type b (Hib) and 1 was type f. However, the cases of Hib were either in unvaccinated individuals or children who had not yet received all 3 doses. We were unable to serogroup the N. meningitidis cases by PCR.

Conclusions
Streptococcus pneumoniae remains a leading cause of pediatric bacterial meningitis, and nonvaccine serotypes may play a bigger role in disease etiology in the postvaccine era. There is evidence of Hib disease among children in Cameroon, which warrants further investigation.