bluuebunny/crossref_metadata_2025_split huggingface dataset:
Inference based accuracy of metagenome prediction tools varies across sample types and functional categories
Authors: Sun Shan , Jones Roshonda B. , Fodor Anthony A. 
Published: January 2020

Abstract
Background: Despite recent decreases in the cost of sequencing, shotgun metagenome sequencing remains more expensive compared with 16S rRNA amplicon sequencing. Methods have been developed to predict the functional profiles of microbial communities based on their taxonomic composition. In this study, we evaluated the performance of three commonly used metagenome prediction tools (PICRUSt, PICRUSt2 and Tax4Fun) by comparing the significance of the differential abundance of predicted functional gene profiles to those from shotgun metagenome sequencing across different environments. Results: We selected 7 datasets of human, non-human animal and environmental (soil) samples that have publicly available 16S rRNA and shotgun metagenome sequences. As we would expect based on previous literature, strong Spearman correlations were observed between predicted gene compositions and gene relative abundance measured with shotgun metagenome sequencing. However, these strong correlations were preserved even when the abundance of genes were permuted across samples. This suggests that simple correlation coefficient is a highly unreliable measure for the performance of metagenome prediction tools. As an alternative, we compared the performance of genes predicted with PICRUSt, PICRUSt2 and Tax4Fun to sequenced metagenome genes in inference models associated with metadata within each dataset. With this approach, we found reasonable performance for human datasets, with the metagenome prediction tools performing better for inference on genes related to “house-keeping” functions. However, their performance degraded sharply outside of human datasets when used for inference. Conclusion: We conclude that the utility of PICRUSt, PICRUSt2 and Tax4Fun for inference with the default database is likely limited outside of human samples and that development of tools for gene prediction specific to different non-human and environmental samples is warranted.
Mutational signatures shift induced by chemotherapeutic agents, 5-Fluorouracil and Oxaliplatin, in the gut microbiome
Authors: Su Fei , Liu Zhao , Zou Lihui , Xu Xue , Luo Qingfeng , Li Hexin , Jia Wenzhuo , Tang Min , Huang Yingying , Zhao Yunbo , Li Lin , Ai Bin , Chen Meng , Ma Jie , Zhao Gang , Xu Hongtao , Xiao Fei 
Published: January 2020

Abstract
We developed a powerful framework for taxonomy composition and genomic variation analysis to investigate the mutagenesis effect and proliferation influence of chemotherapeutic agents, such as 5-Fluorouracil (5-FU) and Oxaliplatin (Oxi) on gut microbiota. Using the gut microbiome data of 68 time serial stool samples, we detected 1.45 million variations among the chemotherapy groups and found the drugs significantly affected mutation signatures of gut microbiota. About 786 faecal metagenomes of 755 individuals from 5 different cohorts were analyzed to build the mutation pattern of gut microbiota from health samples. Oxi notably increase transversion rate, while 5-FU reduced the rate. We also performed in vitro experiments to confirm that chemotherapeutic agents could disrupt the pattern of genetic variant in the intestinal microorganisms. Post-chemotherapy samples had specific gut microbiome signatures with higher abundance of Bacilli and a lack of anaerobic bacteria. In addition, drug-associated functional alterations were also found: metabolism changes in the 5-FU group implied that gut microbiota could provide additional NAD + to inhibit cancer cell autophagy; in the Oxi group, the ribosome and lysine biosynthesis genes were obviously enriched. According to molecular evolution analysis, traits related to protein secretion system showed evidence of strong selection pressure from the drugs, which could be a novel potential treatment strategy for chemotherapy-induced diarrhea. Our study provides a blueprint for characterizing the role of microbes and drug-microbe interaction in the gut microbiota response to chemotherapy.
In vivo and in silico characterization of Lactobacillus reuteri SKKU-OGDONS-01, a potential probiotic from chicken intestine
Authors: Kim Dongjun , Cho Mun-ju , Lee Yongjun , Cho Seungchan , Kil Eui-Joon , Byun Sung June , Lee Sukchan 
Published: January 2020

Abstract
Background: Lactobacillus reuteri SKKU-OGDONS-01 was isolated from chicken intestines for further development as an antiviral feed additive. This study aimed to investigate probiotic properties of chicken isolates in mice model and in silico analysis.Results: Compared to known probiotics, Lactobacillus paracasei ATCC 334, Lactobacillus reuteri SKKU-OGDONS-01 showed immune-boosting effects despite short persistence in the mice intestine. Especially, the expression levels of IFN-β and IFN-γ were increased 4 and 40 times higher than those of the control mice. In proportion to the immune-boosting effects elicited by chicken isolates, the antiviral efficacy against murine norovirus (MNV) was also remarkable. For the purpose of evaluating the potential for development as feed additives, the expression levels of probiotic markers such as long-term acid adaptation, stress response, and adhesion-related proteins were investigated using in silico method, and the results showed that these proteins were expressed at high levels in chicken isolate. Conclusion: Our study demonstrated that chicken isolate, Lactobacillus reuteri SKKU-OGDONS-01 can also elicit high probiotic properties in mice even though it originated in chicken. We expect that this chicken isolate will be able to induce much higher probiotic activity in chickens to develop feed additives for poultry.Keywords: Lactobacillus reuteri SKKU-OGDONS-01, probiotics, antiviral efficacy, probiotic marker, cytokine
Who responds? An examination of response rates to a national postal survey of Aboriginal and Torres Strait Islander adults, 2018-2019
Authors: Wright Alyson Jane , Thurber Katherine Anne , Yap Mandy , Du Wei , Banks Emily , Walker Jennie , Irwin Faye , Sanders William , Lovett Raymond 
Published: January 2020

Abstract
Background Evidence on the effectiveness of postal recruitment methods for Indigenous peoples is lacking. Mayi Kuwayu, the National Study of Aboriginal and Torres Strait Islander Wellbeing, uses multi-staged sampling. We aimed to test postal surveys as a primary recruitment method, analysing preliminary response rate data to inform the Study’s ongoing sampling approach.Methods Our sample included 20,000 Aboriginal and Torres Strait Islander adults >16 years enrolled in the Medicare Australia Enrolment Database. We calculated response rates at 4 and 15 weeks, overall and by age group, gender, state/territory and remoteness.Results The overall response rate was 2.3% (n=456/20000). Highest response rates were observed among males and females ≥50 years from major cities (6.0%, 95%CI 4.4–7.9 and 5.5%, 4.1–7.2, respectively) and regional areas (6.0%, 4.6–7.6 and 6.2%, 4.9–7.7, respectively). Younger age groups and remote areas had lower response rates; all remote age groups <50 years had a response rate ≤0.6%. While most participants responded on the paper surveys, online responses were more common among younger age groups and, respondents with higher education levels and whose first language was not English.Conclusion Using a postal survey, we observed response rates of ≥5.5% among older Aboriginal and Torres Strait Islander adults in major cities and regional areas; response rates were lower in other groups. A two-stage postal distribution approach provided an opportunity to adapt sampling approaches to different demographic groups. Based on initial response rates, the sampling strategy was revised to send postal surveys to groups with higher response rates groups and focus field recruitment strategies on low response groups.
A Novel Method for Identifying a Parsimonious and Accurate Predictive Model for Multiple Clinical Outcomes
Authors: Diaz-Ramirez Ledif Grisell , Lee Sei J. , Smith Alexander K. , Gan Siqi , Boscardin Walter John 
Published: January 2020

Abstract
Background: Most methods for developing clinical prognostic models focus on identifying parsimonious and accurate models to predict a single outcome; however, patients and providers often want to predict multiple outcomes simultaneously. For example, older adults are often interested in predicting nursing home admission as well as mortality. We propose and evaluate a novel predictor selection method for multiple outcomes.Methods: Our proposed method selected the best subset of common predictors based on the minimum average normalized Bayesian Information Criterion (BIC) across outcomes: the Best Average BIC (baBIC) model. We compared the predictive accuracy (Harrell’s C-statistic) and parsimony (number of predictors) of the baBIC model with a subset of common predictors obtained from the union of optimal models for each outcome (Union model). We used example data from the Health and Retirement Study (HRS) to demonstrate our method and conducted a simulation study to investigate performance considering correlated and uncorrelated outcomes.Results: In the example data, the average Harrell’s C-statistics across outcomes of the baBIC and Union models were comparable (0.657 vs. 0.662 respectively). Despite the similar discrimination, the baBIC model was more parsimonious than the Union model (15 vs. 23 predictors respectively). Likewise, in the simulations with correlated outcomes, the mean C-statistic across outcomes of the baBIC and Union models were the same after rounding: 0.650, and the baBIC model had an average number of predictors of 13.8 (95% CI: 13.7, 13.9) compared with 21.6 (95% CI: 21.5, 21.7) in the Union model. In the simulations, the baBIC method performed well by identifying on average the same predictors as in the example data 90.4% times for correlated outcomes.Conclusions: Our method identified a common subset of variables to predict multiple clinical outcomes with superior parsimony and comparable accuracy to current methods.
Modeling Variables with a Detection Limit using a Truncated Normal Distribution with Censoring
Authors: Williams Justin R. , Kim Hyung-Woo , Crespi Catherine M. 
Published: January 2020

Abstract
Background: When data are collected subject to a detection limit, observations below the detection limit may be considered censored. In addition, the domain of such observations may be restricted; for example, values may be required to be non-negative. Methods We propose a regression method for censored observations that also accounts for domain restriction. The method finds maximum likelihood estimates assuming an underlying truncated normal distribution. Results: We show that our method, tcensReg, outperforms other methods commonly used for data with detection limits such as Tobit regression and single imputation of the detection limit or half detection limit with respect to bias and mean squared error under a range of simulation settings. We apply our method to analyze vision quality data collected from ophthalmology clinical trials comparing different types of intraocular lenses implanted during cataract surgery. All methods tested returned similar conclusions for non-inferiority testing, but estimates from the tcensReg method suggest that there may be greater mean differences and overall variability. Conclusions: In the presence of detection limits, our new method tcensReg provides a way to incorporate known domain restrictions when modeling limited dependent variables that substantially improves inferences.
Comparing Multiple Statistical Software for Multiple-Indicator, Multiple-Cause Modeling: An Application of Gender Disparity in Adult Cognitive Functioning Using MIDUS II Dataset
Authors: Chang Chi , Gardiner Joseph , Houang Richard T , Yu Yan-Liang 
Published: January 2020

Abstract
Background: The Multiple-indicator, multiple-cause model (MIMIC) incorporates covariates of interest in the factor analysis using structural equation modeling framework. The model provides rigorous results and becomes broadly available in multiple statistical software. The current study introduces the MIMIC model and how it can be implemented using statistical software SAS CALIS procedure, R lavaan package, and M plus version 8.0. Methods: In this paper, we first discussed the formulation of the MIMIC model with regard to model specification and identification. We then demonstrated the empirical application of the MIMIC model with the Midlife in the United States II (MIDUS II) Study (N=4,109) using SAS CALIS procedure, R lavaan package and M plus version 8.0 to examine gender disparities in cognitive functioning. The input, output, and diagram syntaxes of the three statistical software programs were also presented. Results In terms of data structure, all three statistical programs can be conducted using both raw data and empirical covariance matrix. While SAS and R are comprehensive statistical analytic packages and encompass numerous data manipulation capacities, M plus is designed primarily for structural equation modeling and therefore is limited in data manipulation. Differences in model results from the three statistical programs are trivial. Overall, the results show that while men show better performance in executive function than women, women demonstrate better episodic memory than men. Conclusions: Our study demonstrates the utility of the MIMIC model in its empirical application, fitted with three popular statistical software packages. Results from our models align with empirical findings from previous research. We provide coding procedures and examples with detailed explanations in the hopes of providing a concise tutorial for researchers and methodologists interested in incorporating latent constructs with multiple indicators and multiple covariates in their research projects. Future researchers are encouraged to adopt this flexible and rigorous modeling approach.
Applicability of the Five Case Model to African eHealth investment decisions
Authors: Broomhead Sean C , Mars Maurice , Scott Richard E. , Jones Tom 
Published: January 2020

Abstract

Background: eHealth programmes in African countries face fierce competition for scarce resources. Such initiatives should not proceed without adequate appraisal of their probable impacts, thereby acknowledging their opportunity costs and the need for appraisals to promote optimal use of available resources. However, since there is no broadly accepted eHealth impact appraisal framework available to provide guidance, and local expertise is limited, African health ministries have difficulty completing such appraisals. The Five Case Model, used in several countries outside Africa, has the potential to function as a decision-making tool in African eHealth environments and serve as a key component of an eHealth impact model for Africa. Methods: This study identifies internationally recognised metrics and readily accessible data sources to assess the applicability of the model’s five cases to African countries. Results: Ten metrics are identified that align with the Five Case Model’s five cases, including nine component metrics and one summary metric that aggregates the nine. The metrics cover the eHealth environment, human capital and governance, technology development, and finance and economics. Fifty-four African countries are scored for each metric. Visualisation of the metric scores using spider charts reveals profiles of the countries’ relative performance and provides an eHealth Investment Readiness Assessment Tool. Conclusion: The utility of these comparisons to strengthen eHealth investment planning suggests that the five cases are applicable to African countries’ eHealth investment decisions. The potential for the Five Case Model to have a role in an eHealth impact appraisal framework for Africa should be validated through field testing.
TIMP-2*IGFBP7 as an auxiliary identification of successful discontinuation CRRT and prediction of renal recovery in critically ill patients: a case control study
Authors: xie yuanyuan , Zarbock Alexander , Brendolan Alessandra , Martino Francesca , Samoni Sara , Marchionna Nicola , fan Weixuan , Rosa Silvia De , Giavarina Davide , Romero-González Gregorio , Ronco Claudio 
Published: January 2020

Abstract
Background Predicting the successful discontinuation of continues renal replacement therapy (CRRT) may decrease under- and-overtreatment of critically ill patients and subsequently improve patients’ outcome and utilization of health care resources. The aim of this study was to investigate whether TIMP-2*IGFBP7 in addition to renal and non-renal parameters can predict the successful weaning from CRRT. Methods All patients admitted to ICU requiring CRRT were enrolled. Urine samples for measuring urinary TIMP-2*IGFBP7 levels were collected immediately upon enrollment and at the moment when CRRT was discontinued. The primary endpoint was the independence from RRT for at least 7 days after CRRT discontinuation. Persistent renal dysfunction, which was defined as a SCr level >1.5 times the baseline value at ICU discharge or day 28, was the secondary endpoint. Results 73 patients were enrolled of whom 45 patients effectively discontinued CRRT (61.6%). The patients with a TIMP-2*IGFBP7 concentration >2(ng/ml)2/1000 at enrollment were longer CRRT-dependent. The ROC-AUC values for the prediction of successful discontinuation with TIMP-2*IGFBP7 concentrations at enrollment, at discontinuation of CRRT and with the final model were 0.828, 0.814 and 0.882, respectively. The risk for CRRT discontinuation failure was nearly 5 times higher patients with a positive biomarker at CRRT discontinuation (OR 4.879, P=0.043), and 3.5 times higher in patients with a TIMP-2*IGFBP7 concentration >2(ng/ml)2/1000 at patient enrollment (OR 3.515, P=0.016). Multivariate Cox regression analysis showed a significant association between successful discontinuation of CRRT and TIMP-2*IGFBP7-negative patients at CRRT discontinuation (RR 0.436, 95% CI 0.202-0.939, P=0.034). Kaplan-Meier curves revealed that TIMP-2*IGFBP7 concentration <2 (ng/ml)2/1000 at enrollment and TIMP-2*IGFBP7 turning negative were positively related to high renal recovery rate. Conclusions Urinary TIMP-2*IGFBP7 can serve as a biomarker for identifying successful discontinuation CRRT and predicting renal recovery in critically ill patients.
Clinical results of radiotherapy for hepatocellular carcinoma with tumor thrombosis.
Authors: Nagano Takuya , Hoshi Akihiko , Kurosaki Masayuki , Toda Kazuma , Tsuchiya Kaoru , Yoshimura Ryoichi , Izumi Namiki 
Published: January 2020

Abstract
Background: The aim of this study was to evaluate the clinical outcome of radiotherapy (RT) for hepatocellular carcinoma (HCC) with the portal vein (PV), hepatic vein (HV), inferior vena cava (IVC), and bile duct (BD) tumor thrombosis (TT). Methods: Patients who received RT for the treatment of a primary tumor and tumor thrombosis at Musahino Red Cross Hospital between 2011 and 2019 were retrospectively reviewed. We compared patient characteristics, radiation dose, overall survival (OS), the combined chemotherapy regimen, and objective response rates (ORRs) between the treatment modalities. Results: We evaluated 43 patients who were treated with RT, 27 of whom received combined chemotherapy with RT. The total equivalent dose in 2 Gy fractions ranged from 42.25 to 72 Gy (median 48.75 Gy). The median follow-up period after RT was 13 months (range of 2–90 months). Multivariate analysis showed that the length of tumor thrombosis was a unique significant prognostic factor for OS (p = 0.01) and the prescribed equivalent dose of more than 48.75 Gy significantly contributed to ORRs (p = 0.02). When compared, the one-year OS rates of responders (n = 25) and non-responders (n = 18) were 75% and 35%, respectively (p = 0.009). The odds ratio of ORRs between the two total dose groups (42.35 Gy versus more than 48.75 Gy) was 9.8 (95% CI [2.1, 58.9], p = 0.001). Combined chemotherapy with RT was a prognostic factor for OS (p = 0.03), but it was not correlated with response rate (p = 0.53). Conclusion: Local control of tumor thrombosis was found to be a significant prognostic factor for OS in patients with HCC and its tumor thrombosis. Although various drug and treatment options for tumor thrombosis exist, RT provides a better OS.
Jiao-tai-wan for insomnia symptoms caused by the disharmony of the heart and kidney: a study protocol for a randomized, double-blind, placebo-controlled trial
Authors: Zeng Congcong , Liu Xi , Hu Lufeng , Feng Yuan , Xia Nengzhi , Zeng Haihuan , Luo Lin , Ye Ren , Yuan zhengzhong 
Published: January 2020

Abstract
Background: Insomnia seriously affects people’s normal lives and work. However, effective treatment strategies are scarce. The purpose of this study is to explore the efficacy and safety of Jiao-tai-wan (JTW) for ameliorating insomnia symptoms caused by disharmony of the heart and kidney.
Design: This is a randomized, double-blind, placebo-controlled pilot
clinical trial. One hundred twenty-four participants suffering from insomnia symptoms will randomly assigned to the JTW or placebo group in an equal ratio. The participants will be asked to take JTW or placebo granules twice a day for 1 week. All data will be gathered at baseline and at the end of drug intervention. The primary outcome measures will be the mean change in the Pittsburgh sleep quality index (PSQI) from baseline to the end of drug intervention. Secondary outcome measures will include the the altered sleep parameters in polysomnography, 1H-magnetic resonance spectroscopy (1H-MRS) evalution, the Disharmony of Heart and Kidney Scoring System score and blood tests, including the levels of serum adenosine and melatonin. A laboratory test will be taken before and after treatment to assess the safety of JTW.
Discussion: The outcomes of this study will confirm the efficacy of JTW for the treatment of insomnia symptoms, and will also be used to monitor the safety of JTW.
Trial registration: Chinese Clinical Trial Registry, ChiCTR1800019239.Registered on 1st November 2018-
Retrospectively registered, http://www.chictr.org.cn/.
Keywords: Jiao-tai-wan, Insomnia, Traditional herbal medicine,
Randomized controlled trial, Study protocol, Pattern identification
Protocol version: Manuscript based on study protocol version 1.3, 1 November 2018.