Dataset Information

Meta-Analysis: Randomized Trials of Lactobacillus plantarum on Immune Regulation Over the Last Decades.

ABSTRACT: Lactobacillus (L.) plantarum strains, belong to lactic acid bacteria group, are considered indispensable probiotics. Here, we performed meta-analysis to evaluate the regulatory effects of L. plantarum on the immunity during clinical trials. This meta-analysis was conducted by searching across four most common literature databases, namely, Cochrane Central Register of Controlled Trials, Web of Science, Embase, and PubMed. Clinical trial articles that met the inclusion and exclusion criteria were analyzed by Review Manager (version 5.3). p-value < 0.05 of the total effect was considered statistically significant. Finally, total of 677 references were retrieved, among which six references and 18 randomized controlled trials were included in the meta-analysis. The mean differences observed at 95% confidence interval: interleukin (IL)-4, -0.48 pg/mL (-0.79 to -0.17; p < 0.05); IL-10, 9.88 pg/mL (6.52 to 13.2; p < 0.05); tumor necrosis factor (TNF)-α, -2.34 pg/mL (-3.5 to -1.19; p < 0.05); interferon (IFN)-γ, -0.99 pg/mL (-1.56 to -0.41; p < 0.05). Therefore, meta-analysis results suggested that L. plantarum could promote host immunity by regulating pro-inflammatory and anti-inflammatory cytokines.

SUBMITTER: Zhao W

PROVIDER: S-EPMC8019694 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Meta-Analysis: Randomized Trials of Lactobacillus plantarum on Immune Regulation Over the Last Decades.

Zhao Wei W Peng Chuantao C Sakandar Hafiz Arbab HA Kwok Lai-Yu LY Zhang Wenyi W

Frontiers in immunology 20210322

Lactobacillus (L.) plantarum strains, belong to lactic acid bacteria group, are considered indispensable probiotics. Here, we performed meta-analysis to evaluate the regulatory effects of L. plantarum on the immunity during clinical trials. This meta-analysis was conducted by searching across four most common literature databases, namely, Cochrane Central Register of Controlled Trials, Web of Science, Embase, and PubMed. Clinical trial articles that met the inclusion ...[more]

PMID: 33828554

Similar Datasets

Project description:ObjectiveAs the number of female medical students and surgical residents increases, the increasing number of female academic surgeons has been disproportionate. The purpose of this brief report is to evaluate the AAMC data from 1969 to 2018 to compare the level of female academic faculty representation for surgical specialties over the past four decades.DesignThe number of women as a percentage of the total surgeons per year were recorded for each year from 1969-2018, the most recent year available. Descriptive statistics were performed. Poisson regression examined the percentage of women in each field as the outcome of interest with the year and specialty (using general surgery as a reference) as two predictor variables.SettingData from the American Association of Medical Colleges (AAMC).ParticipantsAll full-time academic faculty physicians in the specialties of obstetrics and gynecology (OB/GYN), general surgery, ophthalmology, otolaryngology (ENT), plastic surgery, plastic surgery, urology, neurosurgery, orthopaedic surgery and cardiothoracic surgery as per AAMC records.ResultsThe percentage of women in surgery for all specialties evaluated increased from 1969 to 2018 (OR 1.04, p<0.001). Compared with general surgery, the rate of yearly percentage change increased more slowly in neurosurgery (OR 0.84; P = .004), orthopaedic surgery (OR 0.82; P = .002), urology (OR 0.59; P < .001), and cardiothoracic surgery (OR 0.38; P < .001). There was no significant difference in the rate of yearly percentage change for plastic surgery (OR 1.01; P = .840). The rate of yearly percentage change increased more rapidly in OB/GYN (OR 2.86; P < .001), ophthalmology (OR 1.79; P < .001) and ENT (OR 1.70; P < .001).ConclusionsRepresentation of women in academic surgery is increasing overall but is increasing more slowly in orthopaedic surgery, neurosurgery, cardiothoracic surgery and urology compared with that in general surgery. These data may be used to inform and further the discussion of how mentorship and sponsorship of female students and trainees interested in surgical careers may improve gender equity in the future.

Project description:ObjectiveTo conduct a comprehensive bibliometric analysis of the application of artificial intelligence (AI) in Rare diseases (RDs), with a focus on analyzing publication output, identifying leading contributors by country, assessing the extent of international collaboration, tracking the emergence of research hotspots, and detecting trends through keyword bursts.MethodsIn this bibliometric study, we identified and retrieved publications on AI applications in RDs spanning 2003 to 2023 from the Web of Science (WoS). We conducted a global research landscape analysis and utilized CiteSpace to perform keyword clustering and burst detection in this field.ResultsA total of 1501 publications were included in this study. The evolution of AI applications in RDs progressed through three stages: the start-up period (2003-2010), the steady development period (2011-2018), and the accelerated growth period (2019-2023), reflecting this field's increasing importance and impact at the time of the study. These studies originated from 85 countries, with the United States as the leading contributor. "Mutation", "Diagnosis", and "Management" were the top three keywords with high frequency. Keyword clustering analysis identified gene identification, effective management, and personalized treatment as three primary research areas of AI applications in RDs. Furthermore, the keyword burst detection indicated a growing interest in the areas of "biomarker", "predictive model", and "data mining", highlighting their potential to shape future research directions.ConclusionsOver two decades, research on the AI applications in RDs has made remarkable progress and shown promising results in the development. Advancing international transboundary cooperation is essential moving forward. Utilizing AI will play a more crucial role across the spectrum of RDs management, encompassing rapid diagnosis, personalized treatment, drug development, data integration and sharing, and continuous monitoring and care.

Dataset Information

Meta-Analysis: Randomized Trials of Lactobacillus plantarum on Immune Regulation Over the Last Decades.

Publications

Meta-Analysis: Randomized Trials of <i>Lactobacillus plantarum</i> on Immune Regulation Over the Last Decades.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets