scholarly journals The Brazilian Reproducibility Initiative: a systematic assessment of Brazilian biomedical science

2018 ◽  
Author(s):  
Olavo Bohrer Amaral ◽  
Kleber Neves ◽  
Ana Paula Wasilewska-Sampaio ◽  
Clarissa França Dias Carneiro
Keyword(s):  
Biomedical Research ◽  
National Level ◽  
Life Sciences ◽  
Biomedical Science ◽  
Laboratory Methods ◽  
Systematic Assessment ◽  
Interlaboratory Variability ◽  
Systematic Effort ◽  
Common Laboratory

With concerns over research reproducibility on the rise, systematic replications of published science have become an important tool to estimate the replicability of findings in specific areas. Nevertheless, such initiatives are still uncommon in biomedical science, and have never been performed at a national level. The Brazilian Reproducibility Initiative is a multicenter, systematic effort to assess the reproducibility of the country’s biomedical research by replicating between 60 and 100 experiments from Brazilian life sciences articles. The project will focus on a set of common laboratory methods, performing each experiment in multiple institutions across the country, with the reproducibility of published findings analyzed in the light of interlaboratory variability. The results, due in 2021, will allow us not only to estimate the reproducibility of Brazilian biomedical science, but also to investigate if there are aspects of the published literature that can be used to predict it.

scholarly journals Two years into the Brazilian Reproducibility Initiative: reflections on conducting a large-scale replication of Brazilian biomedical science

2020 ◽  
Author(s):  
Kleber Neves ◽  
Clarissa França Dias Carneiro ◽  
Ana Paula Wasilewska-Sampaio ◽  
Mariana Abreu ◽  
Bruna Valério Gomes ◽  
...  
Keyword(s):  
Random Sample ◽  
Biomedical Research ◽  
Large Scale ◽  
Scientific Literature ◽  
Biomedical Science ◽  
Current Status ◽  
Laboratory Methods ◽  
Publish Or Perish ◽  
Common Laboratory ◽  
Successes And Failures

Scientists have increasingly recognized that low methodological and analytical rigor combined with publish-or-perish incentives can make the published scientific literature unreliable. As a response to this, large-scale systematic replications of the literature have emerged as a way to assess the problem empirically. The Brazilian Reproducibility Initiative is one such effort, aimed at estimating the reproducibility of Brazilian biomedical research. Its goal is to perform multicenter replications of a quasi-random sample of at least 60 experiments from Brazilian articles published over a 20-year period, using a set of common laboratory methods. In this article, we describe the challenges of managing a multicenter project with collaborating teams across the country, as well as its successes and failures over the first two years. We end with a brief discussion of the Initiative’s current status and its possible future contributions after the project is concluded in 2021.

scholarly journals Capacity-Building for Career Paths in Public Health and Biomedical Research for Undergraduate Minority Students: A Jackson Heart Study Success Model

2016 ◽  
Vol 26 (3) ◽  
pp. 399 ◽  
Author(s):  
Wendy Brown White ◽  
Asoka Srinivasan ◽  
Cheryl Nelson ◽  
Nimr Fahmy ◽  
Frances Henderson
Keyword(s):  
Public Health ◽  
Minority Students ◽  
Undergraduate Students ◽  
Biomedical Research ◽  
Population Based ◽  
Black College ◽  
Biomedical Science ◽  
Individual Student ◽  
Underrepresented Minority ◽  
Professional Programs

<p><strong>Objective: </strong>This article chronicles the building of individual student capacity as well as faculty and institutional capacity, within the context of a population-based, longitudinal study of African Americans and cardiovascular disease. The purpose of this article is to present preliminary data documenting the results of this approach. <strong></strong></p><p><strong>Design: </strong>The JHS Scholars program is designed, under the organizational structure of the Natural Sciences Division at Tougaloo College, to provide solid preparation in quantitative skills through: good preparation in mathematics and the sciences; a high level of reading comprehension; hands-on learning experiences; and mentoring and counseling to sustain the motivation of the students to pursue further studies. </p><p><strong>Setting: </strong>This program is on the campus of a private Historically Black College in Mississippi. <strong></strong></p><p><strong>Participants: </strong>The participants in the program are undergraduate students. <strong></strong></p><p><strong>Main Outcome Measures: </strong>Data, which included information on major area of study, institution attended, degrees earned and position in the workforce, were analyzed using STATA 14. <strong></strong></p><p><strong>Results: </strong>Of 167 scholars, 46 are currently enrolled, while 118 have graduated. One half have completed graduate or professional programs, including; medicine, public health, pharmacy, nursing, and biomedical science; approximately one-fourth (25.4 %) are enrolled in graduate or professional programs; and nearly one tenth (9.3%) completed graduate degrees in law, education, business or English. </p><p><strong>Conclusions: </strong>These data could assist other institutions in understanding the career development process that helps underrepresented minority students in higher education to make career choices on a path toward public health, health professions, biomedical research, and related careers. <em>Ethn Dis. </em>2016;26(3):399-406; doi:10.18865/ed.26.3.399 </p>

scholarly journals Drivers of Change in National Disaster Governance under the Hyogo Framework for Action

2020 ◽  
Vol 8 (4) ◽  
pp. 256-269 ◽  
Author(s):  
Maximilian S. T. Wanner
Keyword(s):  
Natural Hazard ◽  
National Level ◽  
Development Aid ◽  
Small Scale ◽  
Substantial Variation ◽  
Drivers Of Change ◽  
Governance Capacity ◽  
Systematic Assessment ◽  
First Results ◽  
National Disaster

Many suggestions have been made on what motivates countries to expand their measures for disaster risk reduction (DRR), including the frequency and severity of natural hazards, accountability mechanisms, and governance capacity. Despite the fact that theoretical arguments have been developed and evidence collected from small-scale case studies, few studies have attempted to explain the substantial variation in the adoption of DRR measures across countries. This study combines available data on DRR measures, natural hazard events, governance, and socioeconomic characteristics to provide a systematic assessment of the changes that have occurred in the state of DRR at the national level. In line with theoretical explanations, there are indeed associations between several measures of frequency and severity and the development of DRR status. Additionally, voice and accountability mechanisms, as well as development aid, might facilitate positive change. Although these first results of a global comparative study on change in DRR have to be taken cautiously, it is a step forward to understanding the drivers of change at the national level.

scholarly journals The rise and fall of machine learning methods in biomedical research

F1000Research ◽  
2017 ◽  
Vol 6 ◽  
pp. 2012 ◽  
Author(s):  
Hashem Koohy
Keyword(s):  
Machine Learning ◽  
Biomedical Research ◽  
Life Sciences ◽  
Biological Data ◽  
Research Note ◽  
Machine Learning Techniques ◽  
Learning Methods ◽  
The Past ◽  
Machine Learning Methods ◽  
Learning Techniques

In the era of explosion in biological data, machine learning techniques are becoming more popular in life sciences, including biology and medicine. This research note examines the rise and fall of the most commonly used machine learning techniques in life sciences over the past three decades.

Welcome Note from Editor-in-Chief

2019 ◽  
Vol 1 (2) ◽  
Author(s):  
Prof. Dr. Anna Maria Lavezzi
Keyword(s):  
Biological Sciences ◽  
Biomedical Research ◽  
Cell Biology ◽  
Biomedical Science ◽  
Process Time ◽  
Biomedical Sciences ◽  
High Quality ◽  
Health Initiatives ◽  
Science Domain

It is with great pleasure that I write this editorial to welcome you to the first issue of this new International journal, “Pakistan Biomedical Journal” (PBMJ). The topics covered by the journal are certainly broad and interesting. Biomedical science is a collection of applied sciences that help us understand, research, and innovate within the _eld of healthcare. It includes disciplines like molecular biology, clinical virology, bioinformatics, and biomedical engineering, among others. It's designed to apply the biological sciences to advance not only individual health but also the area of public health. Biomedical Research can help health professions better understand things like the human body and cell biology, making advances in our understanding of epidemics, health initiatives, and human health in the age of longer life expectancy. It aids our understanding of infectious disease and provides research opportunities into some of our most troubling health issues. The journal will continue to publish high quality clinical and biomedical research in health and disease later in life. Peer review will remain a vital component of our assessment of submitted articles. I am very happy to have a team of excellent editors and editorial board members from the top international league covering in depth the related topics. They will ensure the highest standards of quality for the published manuscripts and, at the same time, keep the process time as short as possible. We hope to bring best researches in the _eld of biomedical sciences that may serve as a guideline in health awareness, understanding the mechanisms and its management in future. We definitely look forward to receiving your excellent studies to making PBMJ synonymous with high quality in the biomedical science domain.

Boosting – An Unusual Yet Attractive Optimiser

2014 ◽  
Vol 53 (06) ◽  
pp. 417-418 ◽  
Author(s):  
T. Hothorn
Keyword(s):  
Machine Learning ◽  
Biomedical Research ◽  
Life Sciences ◽  
Statistical Modelling ◽  
Discussion Section ◽  
Boosting Algorithms

SummaryThis editorial is part of a For-Discussion- Section of Methods of Information in Medicine about the papers “The Evolution of Boosting Algorithms – From Machine Learning to Statistical Modelling” [1] and “Ex-tending Statistical Boosting – An Overview of Recent Methodological Developments” [2], written by Andreas Mayr and co authors. It preludes two discussed reviews on developments and applications of boosting in biomedical research. The two review papers, written by Andreas Mayr, Harald Binder, Olaf Gefeller, and Matthias Schmid, give an overview on recently published methods that utilise gradient or likelihood-based boosting for fitting models in the life sciences. The reviews are followed by invited comments [3] by experts in both boosting theory and applications.

scholarly journals Singapore's multibillion dollar gamble

2006 ◽  
Vol 203 (5) ◽  
pp. 1139-1142 ◽  
Author(s):  
Heather L. Van Epps
Keyword(s):  
Rhode Island ◽  
Biomedical Research ◽  
Large Dose ◽  
Biomedical Science

Biopolis, Singapore's futuristic research hub. How does a country one-fourth the size of Rhode Island with little history in biomedical science become one of the world's biomedical research giants? The answer: with a pile of money and a large dose of chutzpah. Since 2000, Singapore has dumped more than US$2 billion into developing a biomedical research industry—from scratch. Is the gamble paying off?

scholarly journals Global, Regional, and National Burden of Myocarditis and Cardiomyopathy, 1990–2017

2021 ◽  
Vol 8 ◽  
Author(s):  
Haijiang Dai ◽  
Dor Lotan ◽  
Arsalan Abu Much ◽  
Arwa Younis ◽  
Yao Lu ◽  
...  
Keyword(s):  
National Level ◽  
Treatment Programs ◽  
Years Of Life Lost ◽  
Global Public Health ◽  
Geographic Variations ◽  
Systematic Assessment ◽  
National Burden ◽  
Potential Risk Factors ◽  
System Resource ◽  
Disease Study

Objective: To estimate the burden of myocarditis (MC), alcoholic cardiomyopathy (AC), and other cardiomyopathy (OC) for 195 countries and territories from 1990 to 2017.Methods: We collected detailed information on MC, AC, and OC between 1990 and 2017 from the Global Burden of Disease study 2017, which was designed to provide a systematic assessment of health loss due to diseases and injuries in 21 regions, covering 195 countries and territories. Estimates of MC, AC, and OC burden were produced using a standard Cause of Death Ensemble model and a Bayesian mixed-effects meta-regression tool, and included prevalence, deaths, years lived with disability (YLDs), and years of life lost (YLLs). All estimates were presented as counts, age-standardized rates per 100,000 people and percentage change, with 95% uncertainty intervals (UIs).Results: Worldwide, there were 1.80 million (95% UI 1.64–1.98) cases of MC, 1.62 million (95% UI 1.37–1.90) cases of AC and 4.21 million (95% UI 3.63–4.87) cases of OC, contributing to 46,486 (95% UI 39,709–51,824), 88,890 (95% UI 80,935–96,290), and 233,159 (95% UI 213,677–248,289) deaths in 2017, respectively. Furthermore, globally, there were 131,376 (95% UI 90,113–183,001) YLDs and 1.26 million (95% UI 1.10–1.42) YLLs attributable to MC, 139,087 (95% UI 95,134–196,130) YLDs and 2.84 million (95% UI 2.60–3.07) YLLs attributable to AC, and 353,325 (95% UI 237,907–493,908) YLDs and 5.51 million (95% UI 4.95–5.99) YLLs attributable to OC in 2017. At the national level, the age-standardized prevalence rates varied by 10.4 times for MC, 252.6 times for AC and 38.1 times for OC; the age-standardized death rates varied by 43.9 times for MC, 531.0 times for AC and 43.3 times for OC; the age-standardized YLD rates varied by 12.4 times for MC, 223.7 times for AC, and 34.1 times for OC; and the age-standardized YLL rates varied by 38.4 times for MC, 684.8 times for AC, and 36.2 times for OC. Between 1990 and 2017, despite the decreases in age-standardized rates, the global numbers of prevalent cases, deaths, YLDs, and YLLs have increased for all the diseases.Conclusion: Accurate assessment of the burden of MC, AC, and OC is essential for formulating effective preventative prevention and treatment programs and optimizing health system resource allocation. Our results suggest that MC, AC, and OC remain important global public health problems with increasing numbers of prevalent cases, deaths, YLDs, and YLLs over the past decades, and there are significant geographic variations in the burden of these diseases. Further research is warranted to expand our knowledge of potential risk factors and to improve the prevention, early detection and treatment of these diseases.

scholarly journals Addressing selective reporting of experiments – the case for predefined exclusion criteria

2019 ◽  
Author(s):  
Kleber Neves ◽  
Olavo Bohrer Amaral
Keyword(s):  
Experimental Data ◽  
Biomedical Research ◽  
Life Sciences ◽  
Reporting Bias ◽  
Selective Reporting ◽  
Exclusion Criteria ◽  
Research Reporting ◽  
Experimental Validity

Articles describing experimental data in the life sciences are meant to tell a clear story to the reader. This means that not every experimental attempt ends up published, as failed experiments and uninformative data are typically filtered out by researchers. Freedom to exclude data from an article, however, can lead to reporting bias when exclusion decisions are made after results are in. We discuss how to balance clarity and thoroughness in biomedical research reporting, and suggest that predefined criteria for experimental validity might help in solving this conflict.

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