Citations of microRNA Biomarker Articles That Were Retracted: A Systematic Review.

Importance: Retraction is a tool that journals can use to deter research misconduct and alert their audience to erroneous content published in the journals. However, retracted articles may continue to damage science if they are still cited as legitimate articles. Objective: To characterize patterns of postretraction citations, particularly in microRNA biomarker research, a field with one of the highest rates of retraction. Evidence Review: Retracted scientific articles on microRNAs were retrieved from PubMed, Web of Science, and Retraction Watch between database inception and July 17, 2021, according to preestablished search strategies. Control articles with characteristics in common with retracted articles (ie, published in the same journals in the same years and months and with the same number of authors) were matched and retrieved from PubMed. Citation metrics of retractions and control articles were collected from Web of Science. PubPeer was referenced to examine the public response or comments on included retractions. Data were analyzed from September 2021 through March 2023. Findings: A total of 10 461 articles were analyzed, with 887 retractions and 9574 articles as controls. Among retracted articles, which were published from 1999 to 2021, there were 756 articles (85.23%) written by researchers affiliated with Chinese institutions. Retracted articles were cited 6327 times after retraction. Of 792 retracted articles that were cited, 621 articles (78.41%) were cited at least once after retraction and 238 articles (30.05%) were cited more often after retraction than before retraction. Overall citations (comprising citations before and after retraction) and postretraction citations accumulated over time (eg, the median [IQR] number of postretraction citations was 1 [1-2] and 23 [9-44] citations at the first 6 and 66 months, respectively, between retraction and citation retrieval). A random sample of 87 retracted articles (9.81%) recorded 478 citations after retraction, with 208 citations (43.51%) in articles published 12 months or longer after retraction. Of these citing articles, 19 articles (3.97%) mentioned the retractions. Compared with the control group of 1620 nonretracted articles, no significant differences were found in overall number of citations or citations after retraction. Among 478 articles citing retracted articles, 414 articles were found on PubMed and had matched control articles; these articles had higher odds of being subsequently retracted than 7954 matched control articles (odds ratio, 6.57; 95% CI, 3.39-12.72). Conclusions and Relevance: In this study, retraction was not associated with a reduction in citations of retracted articles, but articles that cited retracted publications had higher odds of later retraction. These findings suggest that journals may need to implement mechanisms for detection of postretraction citations.

The efficacy of Chinese herbal drugs for adults with angina pectoris: Bayesian network meta-analysis of 331 RCTs involving 36,467 individuals.

ETHNOPHARMACOLOGICAL RELEVANCE: Hundreds of randomized controlled trials (RCT) on Chinese herbal drugs (CHDs) including Shexiang baoxin pill (BXP), compound Danshen dripping pill (DSP), compound Danshen tablet (DST), Suxiao jiuxin pill (JXP), Naoxintong capsule (NXT), Tongxinluo capsule (TXL), and Di'ao xinxuekang capsule (XXK) and conventional chemical drugs, such as isosorbide dinitrate (ISDN), for angina pectoris are available but have not been evaluated by a PRISMA-compliant network meta-analysis (NMA). AIM OF THE STUDY: This study aimed to compare the efficacy of nine anti-anginal drugs through NMA on RCTs. METHODS: RCTs of drug treatment for adult patients with angina pectoris for improvements in symptoms and electrocardiography were retrieved. Odds ratios and 95% credible intervals were computed to measure effect sizes. RCT quality was evaluated with the Cochrane risk of bias tool. Evidence synthesis was performed with Bayesian NMA. Essential analyses including subgroup analysis, sensitivity analysis, meta-regression analysis, publication bias analysis, and ranking analysis were conducted to assess the robustness of efficacies. Evidence strength was assessed with the GRADE approach. RESULTS: A total of 331 RCTs with 36,467 participants were eligible. The overall quality of all included RCTs was low. Overall efficacy estimates from different approaches of evidential synthesis found that BXP, TXL, and DSP were more efficacious than DST and ISDN. Essential analyses indicated consistent efficacy estimates, insignificant publication bias, and corroborative ranking results. The overall GRADE evidence strength was low. CONCLUSION: This comprehensive Bayesian NMA found BXP, TXL, and DSP to be the top three candidates among the seven tested CHDs for treating adults suffering from angina pectoris. However, the quality and the evidence strength of eligible RCTs were low. Further high-quality RCTs with more outcome measures and their NMAs are warranted. REGISTRATION: PROSPERO CRD42014007035.

MicroRNA biomarkers of type 2 diabetes: evidence synthesis from meta-analyses and pathway modelling.

AIMS/HYPOTHESIS: MicroRNAs are being sought as biomarkers for the early identification of type 2 diabetes. This study aimed to synthesise the evidence from microRNA-type 2 diabetes association studies and microRNA-regulated type 2 diabetes pathway delineation studies that met stringent quality criteria to identify and validate microRNAs of both statistical and biological significance as type 2 diabetes biomarkers. METHODS: Eligible controlled studies on microRNA expression profiling of type 2 diabetes were retrieved from PubMed, ScienceDirect and Web of Science. MicroRNA-regulated type 2 diabetes pathway delineation studies were conducted by integrating and cross-verifying the data from miRTarBase, TransmiR, miRecords, TargetScanHuman, the Kyoto Encyclopedia of Genes and Genomes (KEGG) and the Retraction Watch database. Before meta-analysis, quality assessment was performed according to the corresponding reporting guidelines for evidence-based medicine. To select the most statistically significant microRNAs, we conducted extensive meta-analyses according to the latest methodology. Subgroup and sensitivity analyses were carried out to further examine the microRNA candidates for their tissue specificity and blood fraction specificity and the robustness of the evidence. Signalling pathway impact analysis of dysregulated microRNAs identified from meta-analyses was performed to select biologically significant microRNAs that were enriched in our newly built microRNA-regulated pathways. RESULTS: Of the 404 differentially expressed microRNAs identified in the 156 controlled profiling studies with a combined sample size of >15,000, only 60 were both consistently and significantly dysregulated in human type 2 diabetes. No microRNAs were both consistently and significantly dysregulated in multiple tissues according to subgroup analyses. In total, 58 microRNAs were found to be robust in sensitivity analyses. A total of 1966 pathway delineation studies were identified, including 3290 microRNA-target interactions, which were further combined with KEGG pathways, producing 225 microRNA-regulated pathways. Impact analysis found that 16 dysregulated microRNAs identified from extensive meta-analyses were statistically significantly enriched in the augmented KEGG type 2 diabetes pathway. CONCLUSIONS/INTERPRETATION: Sixteen microRNAs met the criteria for biomarker selection. In terms of both significance and relevance, the order of priority for verification of these microRNAs is as follows: miR-29a-3p, miR-221-3p, miR-126-3p, miR-26a-5p, miR-503-5p, miR-100-5p, miR-101-3p, mIR-103a-3p, miR-122-5p, miR-199a-3p, miR-30b-5p, miR-130a-3p, miR-143-3p, miR-145-5p, miR-19a-3p and miR-311-3p. REGISTRATION: PROSPERO registration number CRD42017081659.

How efficacious are traditional Chinese medicine injections in treating angina pectoris? A network meta-analysis of randomized controlled trials.

ETHNOPHARMACOLOGICAL RELEVANCE: Over 50 million adults in China suffer from angina pectoris, which are often treated with traditional Chinese medicine injections (TCMIs). However, the efficacies of TCMIs and conventional drugs as determined by randomized controlled trials (RCTs) were not rigorously compared with one another by network meta-analysis (NMA). This PRISMA-compliant NMA aimed to compare the efficacy and assess the evidence strengths of 24 TCMIs in treating adults with angina pectoris of RCTs. MATERIALS AND METHODS: Following the protocol (PROSPERO registration number CRD42018117720), the RCTs that compared any TCMI with another TCMI or conventional drug on outcome measures including symptomatic and electrocardiography improvements were included. The quality of included RCTs was assessed with the Cochrane's risk of bias 2 tool. Frequentist statistical analyses were performed, including NMA, pairwise meta-analysis (PMA), subgroup analysis, sensitivity analysis, meta-regression, and publication bias analysis. The certainty of evidence was assessed with the GRADE approach. RESULTS: Totally, 556 eligible RCTs with 57015 participants were identified while the quality of all but five included RCTs was poor. The significant efficacy estimates and insignificant heterogeneity assessment from PMA and NMA indicated that nearly all TCMIs were more efficacious than conventional treatments for angina pectoris. Adequate subgroup and sensitivity analyses found the robust and consistent results. However, the evidence strengths of meta-analyses were assessed as very low to low due to the high risk of RCTs. The comprehensive efficacy estimates suggested that 4 TCMIs (HH, Honghua injection; HHH, Honghua Huangsesu injection; GLP, Gualoupi injection; and SM, Shenmai injection) was the best anti-anginal drugs for adults with angina pectoris. CONCLUSION: TCMIs appear to be efficacious for angina pectoris, although evidence evaluation of high-quality RCTs of TCMIs would be necessary. In particular, randomization and blinding procedures of the RCTs should be explicated to meet the CONSORT requirements.

Big Data Reality Check (BDRC) for public health: to what extent the environmental health and health services research did meet the 'V' criteria for big data? A study protocol.

INTRODUCTION: Big data technologies have been talked up in the fields of science and medicine. The V-criteria (volume, variety, velocity and veracity, etc) for defining big data have been well-known and even quoted in most research articles; however, big data research into public health is often misrepresented due to certain common misconceptions. Such misrepresentations and misconceptions would mislead study designs, research findings and healthcare decision-making. This study aims to identify the V-eligibility of big data studies and their technologies applied to environmental health and health services research that explicitly claim to be big data studies. METHODS AND ANALYSIS: Our protocol follows Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols (PRISMA-P). Scoping review and/or systematic review will be conducted. The results will be reported using PRISMA for Scoping Reviews (PRISMA-ScR), or PRISMA 2020 and Synthesis Without Meta-analysis guideline. Web of Science, PubMed, Medline and ProQuest Central will be searched for the articles from the database inception to 2021. Two reviewers will independently select eligible studies and extract specified data. The numeric data will be analysed with R statistical software. The text data will be analysed with NVivo wherever applicable. ETHICS AND DISSEMINATION: This study will review the literature of big data research related to both environmental health and health services. Ethics approval is not required as all data are publicly available and involves confidential personal data. We will disseminate our findings in a peer-reviewed journal. PROSPERO REGISTRATION NUMBER: CRD42021202306.

Putative Factors Interfering Cell Cycle Re-Entry in Alzheimer's Disease: An Omics Study with Differential Expression Meta-Analytics and Co-Expression Profiling.

BACKGROUND: Neuronal cell cycle re-entry (CCR) is a mechanism, along with amyloid-ß (Aß) oligomers and hyperphosphorylated tau proteins, contributing to toxicity in Alzheimer's disease (AD). OBJECTIVE: This study aimed to examine the putative factors in CCR based on evidence corroboration by combining meta-analysis and co-expression analysis of omic data. METHODS: The differentially expressed genes (DEGs) and CCR-related modules were obtained through the differential analysis and co-expression of transcriptomic data, respectively. Differentially expressed microRNAs (DEmiRNAs) were extracted from the differential miRNA expression studies. The dysregulations of DEGs and DEmiRNAs as binary outcomes were independently analyzed by meta-analysis based on a random-effects model. The CCR-related modules were mapped to human protein-protein interaction databases to construct a network. The importance score of each node within the network was determined by the PageRank algorithm, and nodes that fit the pre-defined criteria were treated as putative CCR-related factors. RESULTS: The meta-analysis identified 18,261 DEGs and 36 DEmiRNAs, including genes in the ubiquitination proteasome system, mitochondrial homeostasis, and CCR, and miRNAs associated with AD pathologies. The co-expression analysis identified 156 CCR-related modules to construct a protein-protein interaction network. Five genes, UBC, ESR1, EGFR, CUL3, and KRAS, were selected as putative CCR-related factors. Their functions suggested that the combined effects of cellular dyshomeostasis and receptors mediating Aß toxicity from impaired ubiquitination proteasome system are involved in CCR. CONCLUSION: This study identified five genes as putative factors and revealed the significance of cellular dyshomeostasis in the CCR of AD.

Comparative efficacy of single-inhaler triple therapies for COPD: A protocol for systematic review and network meta-analysis.

INTRODUCTION: 2021 Global Initiative for Chronic Obstructive Lung Disease (GOLD) Reports recommends that patients with clinically significant symptoms and exacerbations of chronic obstructive pulmonary disease (COPD) should escalate to triple therapy, a combined use of inhaled corticosteroids (ICS), long-acting muscarinic antagonists (LAMA) and long-acting b2-agonists (LABA)(ICS/LAMA/LABA). Triple therapy in fixed-dose combinations (FDCs), i.e., combining ICS, LABA with LAMA and administrating by a single inhalation device, has appeared in recent years. This study aims to compare the efficacy of triple therapy in FDCs in treating patients with moderate to severe COPD. METHODS AND ANALYSES: Literature search will be conducted on PubMed, Embase and Web of science, according to pre-specified and corresponding search strategies, for relevant reports published since the inception dates of the databases. Randomised controlled trials (RCT) which compared the triple therapy in FDCs with other pharmacological therapies will be included. The Cochrane risk of bias assessment tool (RoB 2) will be used to assess the RCT quality. The outcomes will be analyzed as rate ratios and mean differences under a random-effects model in a frequentist network meta-analysis (NMA). Additional statistical analyses including subgroup analysis, sensitivity analysis, and publication bias analysis will be performed to assess the evidential heterogeneity and robustness. The strength of evidence from the NMA will be evaluated with the Grading of Recommendation, Assessment, Development and Evaluation (GRADE) methods. ETHICS AND DISSEMINATION: No ethics approval is required as this systematic review and network meta-analysis do not collect confidential personal data and do not carry out interventions in treating patients. PROTOCOL REGISTRATION NUMBER: CRD42021240823.

Prediction of differentially expressed microRNAs in blood as potential biomarkers for Alzheimer's disease by meta-analysis and adaptive boosting ensemble learning.

BACKGROUND: Blood circulating microRNAs that are specific for Alzheimer's disease (AD) can be identified from differentially expressed microRNAs (DEmiRNAs). However, non-reproducible and inconsistent reports of DEmiRNAs hinder biomarker development. The most reliable DEmiRNAs can be identified by meta-analysis. To enrich the pool of DEmiRNAs for potential AD biomarkers, we used a machine learning method called adaptive boosting for miRNA disease association (ABMDA) to identify eligible candidates that share similar characteristics with the DEmiRNAs identified from meta-analysis. This study aimed to identify blood circulating DEmiRNAs as potential AD biomarkers by augmenting meta-analysis with the ABMDA ensemble learning method. METHODS: Studies on DEmiRNAs and their dysregulation states were corroborated with one another by meta-analysis based on a random-effects model. DEmiRNAs identified by meta-analysis were collected as positive examples of miRNA-AD pairs for ABMDA ensemble learning. ABMDA identified similar DEmiRNAs according to a set of predefined criteria. The biological significance of all resulting DEmiRNAs was determined by their target genes according to pathway enrichment analyses. The target genes common to both meta-analysis- and ABMDA-identified DEmiRNAs were collected to construct a network to investigate their biological functions. RESULTS: A systematic database search found 7841 studies for an extensive meta-analysis, covering 54 independent comparisons of 47 differential miRNA expression studies, and identified 18 reliable DEmiRNAs. ABMDA ensemble learning was conducted based on the meta-analysis results and the Human MicroRNA Disease Database, which identified 10 additional AD-related DEmiRNAs. These 28 DEmiRNAs and their dysregulated pathways were related to neuroinflammation. The dysregulated pathway related to neuronal cell cycle re-entry (CCR) was the only statistically significant pathway of the ABMDA-identified DEmiRNAs. In the biological network constructed from 1865 common target genes of the identified DEmiRNAs, the multiple core ubiquitin-proteasome system, that is involved in neuroinflammation and CCR, was highly connected. CONCLUSION: This study identified 28 DEmiRNAs as potential AD biomarkers in blood, by meta-analysis and ABMDA ensemble learning in tandem. The DEmiRNAs identified by meta-analysis and ABMDA were significantly related to neuroinflammation, and the ABMDA-identified DEmiRNAs were related to neuronal CCR.

MicroRNA biomarkers of type 2 diabetes: A protocol for corroborating evidence by computational genomics and meta-analyses.

BACKGROUND: Few microRNAs were found consistently dysregulated in type 2 diabetes (T2D) that would gain confidence from Big Pharma to develop diagnostic or therapeutic biomarkers. This study aimed to corroborate evidence from eligible microRNAs-T2D association studies according to stringent quality criteria covering both biological and statistical significance in T2D for biomarker development. METHODS AND ANALYSES: Controlled microRNA expression profiling studies on human with T2D will be retrieved from PubMed, ScienceDirect, and Embase for selecting the statistically significant microRNAs according to pre-specified search strategies and inclusion criteria. Multiple meta-analyses with restricted maximum-likelihood estimation and empirical Bayes estimation under the random-effects model will be conducted by metafor package in R. Subgroup and sensitivity analyses further examine the microRNA candidates for their disease specificity, tissue specificity, blood fraction specificity, and statistical robustness of evidence. Biologically relevant microRNAs will then be selected through genomic database corroboration. Their association with T2D is further measured by area under the curve (AUC) of receive operating characteristic (ROC). Meta-analysis of AUC of potential biomarkers will also be conducted. Enrichment analysis on potential microRNA biomarkers and their target genes will be performed by iPathwayGuide and clusterProfiler, respectively. The corresponding reporting guidelines will be used to assess the quality of included studies according to their profiling methods (microarray, RT-PCR, and RNA-Seq). ETHICS AND DISSEMINATION: No ethics approval is required since this study does not include identifiable personal patient data. PROTOCOL REGISTRATION NUMBER: CRD42017081659.

MEPHAS: an interactive graphical user interface for medical and pharmaceutical statistical analysis with R and Shiny.

BACKGROUND: Even though R is one of the most commonly used statistical computing environments, it lacks a graphical user interface (GUI) that appeals to students, researchers, lecturers, and practitioners in medicine and pharmacy for conducting standard data analytics. Current GUIs built on top of R, such as EZR and R-Commander, aim to facilitate R coding and visualization, but most of the functionalities are still accessed through a command-line interface (CLI). To assist practitioners of medicine and pharmacy and researchers to run most routines in fundamental statistical analysis, we developed an interactive GUI; i.e., MEPHAS, to support various web-based systems that are accessible from laptops, workstations, or tablets, under Windows, macOS (and IOS), or Linux. In addition to fundamental statistical analysis, advanced statistics such as the extended Cox regression and dimensional analyses including partial least squares regression (PLS-R) and sparse partial least squares regression (SPLS-R), are also available in MEPHAS. RESULTS: MEPHAS is a web-based GUI (https://alain003.phs.osaka-u.ac.jp/mephas/) that is based on a shiny framework. We also created the corresponding R package mephas (https://mephas.github.io/). Thus far, MEPHAS has supported four categories of statistics, including probability, hypothesis testing, regression models, and dimensional analyses. Instructions and help menus were accessible during the entire analytical process via the web-based GUI, particularly advanced dimensional data analysis that required much explanation. The GUI was designed to be intuitive for non-technical users to perform various statistical functions, e.g., managing data, customizing plots, setting parameters, and monitoring real-time results, without any R coding from users. All generated graphs can be saved to local machines, and tables can be downloaded as CSV files. CONCLUSION: MEPHAS is a free and open-source web-interactive GUI that was designed to support statistical data analyses and prediction for medical and pharmaceutical practitioners and researchers. It enables various medical and pharmaceutical statistical analyses through interactive parameter settings and dynamic visualization of the results.

A Systematic Bioinformatics Workflow With Meta-Analytics Identified Potential Pathogenic Factors of Alzheimer's Disease.

Potential pathogenic factors, other than well-known APP, APOE4, and PSEN, can be further identified from transcriptomics studies of differentially expressed genes (DEGs) that are specific for Alzheimer's disease (AD), but findings are often inconsistent or even contradictory. Evidence corroboration by combining meta-analysis and bioinformatics methods may help to resolve existing inconsistencies and contradictions. This study aimed to demonstrate a systematic workflow for evidence synthesis of transcriptomic studies using both meta-analysis and bioinformatics methods to identify potential pathogenic factors. Transcriptomic data were assessed from GEO and ArrayExpress after systematic searches. The DEGs and their dysregulation states from both DNA microarray and RNA sequencing datasets were analyzed and corroborated by meta-analysis. Statistically significant DEGs were used for enrichment analysis based on KEGG and protein-protein interaction network (PPIN) analysis based on STRING. AD-specific modules were further determined by the DIAMOnD algorithm, which identifies significant connectivity patterns between specific disease-associated proteins and non-specific proteins. Within AD-specific modules, the nodes of highest degrees (>95th percentile) were considered as potential pathogenic factors. After systematic searches of 225 datasets, extensive meta-analyses among 25 datasets (21 DNA microarray datasets and 4 RNA sequencing datasets) identified 9,298 DEGs. The dysregulated genes and pathways in AD were associated with impaired amyloid-ß (Aß) clearance. From the AD-specific module, Fyn, and EGFR were the most statistically significant and biologically relevant. This meta-analytical study suggested that the reduced Aß clearance in AD pathogenesis was associated with the genes encoding Fyn and EGFR, which were key receptors in Aß downstream signaling.

Identification of certain Panax species to be potential substitutes for Panax notoginseng in hemostatic treatments.

Panax notoginseng (Burkill) F. H. Chen ex C. H. Chow (P. notoginseng) is a highly valued Chinese materia medica having a hemostatic effect and mainly used for the treatment of trauma and ischemic cardiovascular diseases. Stringent growth requirements, weak resistance to insect pests and plant diseases, arsenic contamination and continuous cropping constitute hurdles to further increases in the agricultural production of P. notoginseng. This review focuses on the traditional uses (based on traditional Chinese medicine theory), major chemical components, biological activities, pharmacological properties, geographical distributions and historical development of taxonomy of P. notoginseng and its related species in Panax genus, including Panax japonicus C. A. Meyer (P. japonicus), Panax japonicus C. A. Meyer var. major (Burkill) C. Y. Wu et K. M. Feng (P. japonicus var. major) and Panax japonicus C. A. Meyer var. bipinnatifidus (Seem.) C. Y. Wu et K. M. Feng (P. japonicus var. bipinnatifidus) are reviewed. This review sheds light on the origin herbs of Zhujieshen (ZJS) and Zhuzishen (ZZS), e.g., P. japonicas var japonicas, P. japonicus var. major and P. japonicus var. bipinnatifidus could be used as a substitute for P. notoginseng as hemostatic herbs.

Building Molecular Interaction Networks from Microarray Data for Drug Target Screening.

Potential drug targets for the disease treatment can be identified from microarray studies on differential gene expression of patients and healthy participants. Here, we describe a method to use the information of differentially expressed (DE) genes obtained from microarray studies to build molecular interaction networks for identification of pivotal molecules as potential drug targets. The quality control and normalization of the microarray data are conducted with R packages simpleaffy and affy, respectively. The DE genes with adjusted P values less than 0.05 and log fold changes larger than 1 or less than -1 are identified by limma package to construct a molecular interaction network with InnateDB. The genes with significant connectivity are identified by the Cytoscape app jActiveModules. The interactions among the genes within a module are tested by psych package to determine their associations. The gene pairs with significant association and known protein structures according to the Protein Data Bank are selected as potential drug targets. As an example for drug target screening, we demonstrate how to identify potential drug targets from a molecular interaction network constructed with the DE genes of significant connectivity, using a microarray dataset of type 2 diabetes mellitus.

Identification of Potential MicroRNA Biomarkers by Meta-analysis.

Meta-analysis statistically assesses the results (e.g., effect sizes) across independent studies that are conducted in accordance with similar protocols and objectives. Current genomic meta-analysis studies do not perform extensive re-analysis on raw data because full data access would not be commonplace, although the best practice of open research for sharing well-formed data have been actively advocated. This chapter describes a simple and easy-to-follow method for conducting meta-analysis of multiple studies without using raw data. Examples for meta-analysis of microRNAs (miRNAs) are provided to illustrate the method. MiRNAs are potential biomarkers for early diagnosis and epigenetic monitoring of diseases. A number of miRNAs have been identified to be differentially expressed, i.e., overexpressed or underexpressed, under diseased states but only a small fraction would be highly effective biomarkers or therapeutic targets of diseases. The meta-analysis method as described in this chapter aims to identify the miRNAs that are consistently found dysregulated across independent studies as biomarkers.

How Efficacious is Danshen (Salvia miltiorrhiza) Dripping Pill in Treating Angina Pectoris? Evidence Assessment for Meta-Analysis of Randomized Controlled Trials.

BACKGROUND: More than 230 randomized controlled trials (RCTs) of danshen dripping pill (DSP) and isosorbide dinitrate (ISDN) in treating angina pectoris after the first preferred reporting items for systematic reviews and meta-analyses-compliant comprehensive meta-analysis were published in 2010. Other meta-analyses had flaws in study selection, statistical meta-analysis, and evidence assessment. This study completed the meta-analysis with an extensive assessment of the evidence. METHODS: RCTs published from 1994 to 2016 on DSP and ISDN in treating angina pectoris for at least 4 weeks were included. The risk of bias (RoB) of included RCTs was assessed with the Cochrane's tool for assessing RoB. Meta-analyses based on a random-effects model were performed on two outcome measures: symptomatic (SYM) and electrocardiography (ECG) improvements. Subgroup analysis, sensitivity analysis, metaregression, and publication bias analysis were also conducted. The evidence strength was evaluated with the Grades of Recommendation, Assessment, Development, and Evaluation (GRADE) method. RESULTS: Among the included 109 RCTs with 11,973 participants, 49 RCTs and 5042 participants were new (after 2010). The RoB of included RCTs was high in randomization and blinding. Overall effect sizes in odds ratios for DSP over ISDN were 2.94 (95% confidence interval [CI]: 2.53-3.41) on SYM (n = 108) and 2.37 (95% CI: 2.08-2.69) by ECG (n = 81) with significant heterogeneities (I2 = 41%, p < 0.0001 on SYM and I2 = 44%, p < 0.0001 on ECG). Subgroup, sensitivity, and metaregression analyses showed consistent results without publication bias. However, the evidence strength was low in GRADE. CONCLUSION: The efficacy of DSP was still better than ISDN in treating angina pectoris, but the confidence decreased due to high RoB and heterogeneities.

Is self-monitoring of blood glucose effective in improving glycaemic control in type 2 diabetes without insulin treatment: a meta-analysis of randomised controlled trials.

OBJECTIVE: The present study aimed to verify the effectiveness of self-monitoring of blood glucose (SMBG) in patients with non-insulin-treated type 2 diabetes (T2D). METHODS: A comprehensive literature search was conducted in PubMed, Cochrane Library, Web of Science, ScienceDirect and ClinicalTrials.gov from their respective inception dates to 26 October 2015. Eligible randomised controlled trials (RCTs) were included according to prespecified criteria. The quality of the included RCTs was evaluated according to the Cochrane risk of bias tool, and the evidence quality of meta-analyses was assessed by the Grading of Recommendation, Assessment, Development, and Evaluation (GRADE) criteria. A meta-analysis of primary and secondary outcome measures was performed. Sensitivity and subgroup analyses were carried out to evaluate the robustness and heterogeneity of the findings. Begg's and Egger's tests were used to quantify publication biases. RESULTS: A total of 15 RCTs, comprising 3383 patients with non-insulin-treated T2D, met the inclusion criteria. The SMBG intervention improved glycated haemoglobin (HbA1c) (mean difference -0.33; 95% CI -0.45 to -0.22; p=3.0730e-8; n=18), body mass index (BMI; -0.65; -1.18 to -0.12; p=0.0164; n=9) and total cholesterol (TC; -0.12; -0.20 to -0.04; p=0.0034; n=8) more effectively than the control in overall effect. The sensitivity analysis revealed little difference in overall effect, indicating the robustness of the results. SMBG moderated HbA1c levels better than the control in all subgroup analyses. Most of the RCTs had high risk of bias in blinding, while the overall quality of evidence for HbA1c was moderate according to the GRADE criteria. Publication bias was moderate for BMI. CONCLUSIONS: SMBG improved HbA1c levels in the short term (≤6-month follow-up) and long term (≥12-month follow-up) in patients with T2D who were not using insulin. TRIAL REGISTRATION NUMBER: CRD42015019099.

Comparative efficacy of selective serotonin reuptake inhibitors (SSRI) in treating major depressive disorder: a protocol for network meta-analysis of randomised controlled trials.

INTRODUCTION: There have been inconsistent findings from randomised controlled trials (RCTs) and systematic reviews on the efficacies of selective serotonin reuptake inhibitors (SSRIs) as the first-line treatment of major depressive disorder (MDD). Besides inconsistencies among randomised controlled trials (RCTs), their risks of bias and evidence grading have seldom been evaluated in meta-analysis. This study aims to compare the efficacy of SSRIs by conducting a Bayesian network meta-analysis, which will be the most comprehensive evaluation of evidence to resolve the inconsistency among previous studies. METHODS AND ANALYSES: SSRIs including citalopram, escitalopram, fluoxetine, fluvoxamine, paroxetine, sertraline and vilazodone have been selected. Systematic database searching and screening will be conducted for the RCTs on drug treatment of patients with MDD according to pre-specified search strategies and selection criteria. PubMed, the Cochrane Library, EMBASE, ScienceDirect, the US Food and Drug Administration Website, ClinicalTrial.gov and WHO Clinical Trials will be searched. Outcome data including Hamilton Depression Rating Scale (HDRS), Montgomery-Åsberg Depression Rating Scale (MADRS) and Clinical Global Impression (CGI) from eligible RCTs will be extracted. The outcomes will be analysed as ORs and mean differences under a random-effects model. A Bayesian network meta-analysis will be conducted with WinBUGS software, to compare the efficacies of SSRIs. Subgroup and sensitivity analysis will be performed to explain the study heterogeneity and evaluate the robustness of the results. Meta-regression analysis will be conducted to determine the possible factors affecting the efficacy outcomes. The Cochrane risk of bias assessment tool will be used to assess the RCT quality, and the Grading of Recommendation, Assessment, Development and Evaluation will be used to assess the strength of evidence from the meta-analysis. ETHICS AND DISSEMINATION: No ethical approval is required because this study includes neither confidential personal patient data nor interventions with patients. PROTOCOL REGISTRATION NUMBER: CRD42015024879.

Ligand-based virtual screening and inductive learning for identification of SIRT1 inhibitors in natural products.

Sirtuin 1 (SIRT1) is a nicotinamide adenine dinucleotide-dependent deacetylase, and its dysregulation can lead to ageing, diabetes, and cancer. From 346 experimentally confirmed SIRT1 inhibitors, an inhibitor structure pattern was generated by inductive logic programming (ILP) with DMax Chemistry Assistant software. The pattern contained amide, amine, and hetero-aromatic five-membered rings, each of which had a hetero-atom and an unsubstituted atom at a distance of 2. According to this pattern, a ligand-based virtual screening of 1 444 880 active compounds from Chinese herbs identified 12 compounds as inhibitors of SIRT1. Three compounds (ZINC08790006, ZINC08792229, and ZINC08792355) had high affinity (-7.3, -7.8, and -8.6 kcal/mol, respectively) for SIRT1 as estimated by molecular docking software AutoDock Vina. This study demonstrated a use of ILP and background knowledge in machine learning to facilitate virtual screening.

Comparative Efficacy of Tongxinluo Capsule and Beta-Blockers in Treating Angina Pectoris: Meta-Analysis of Randomized Controlled Trials.

OBJECTIVE: There have been no systematic reviews, let alone meta-analyses, of randomized controlled trials (RCTs) comparing tongxinluo capsule (TXL) and beta-blockers in treating angina pectoris. This study aimed to evaluate the efficacy of TXL and beta-blockers in treating angina pectoris by a meta-analysis of eligible RCTs. METHODS: The RCTs comparing TXL with beta-blockers (including metoprolol) in treating angina pectoris were searched and retrieved from databases including PubMed, Chinese National Knowledge Infrastructure, and WanFang Data. Eligible RCTs were selected according to prespecified criteria. Meta-analysis was performed on the odds ratios (OR) of symptomatic and electrocardiographic (ECG) improvements after treatment. Subgroup analysis, sensitivity analysis, meta-regression, and publication biases analysis were conducted to evaluate the robustness of the results. RESULTS: Seventy-three RCTs published between 2000 and 2014 with 7424 participants were eligible. Overall ORs comparing TXL with beta-blockers were 3.40 (95% confidence interval [CI], 2.97-3.89; p<0.0001) for symptomatic improvement and 2.63 (95% CI, 2.29-3.02; p<0.0001) for ECG improvement. Subgroup analysis and sensitivity analysis found no statistically significant dependence of overall ORs on specific study characteristics except efficacy criteria. Meta-regression found no significant except sample sizes for data on symptomatic improvement. Publication biases were statistically significant. CONCLUSION: TXL seems to be more effective than beta-blockers in treating angina pectoris, on the basis of the eligible RCTs. Further RCTs are warranted to reduce publication bias and verify efficacy.