Recent evidence indicates that many clinical and preclinical studies are not reproducible. Prominent causes include design and implementation issues, low statistical power, unintentional bias, and incomplete reporting in the published literature. The primary goal of this study was to assess the quality of published research in three prominent cardiovascular research journals by examining statistical power and assessing the adherence to augmented ARRIVE guidelines (Animal Research: Reporting of In Vivo Experiments). For unpaired t-tests, the average median power for a 20% and 50% change was 0.27 ± 0.06 and 0.88 ± 0.08, respectively. For analysis of guidelines, 40 categories were assessed with a 0-2 scale. Although many strengths were observed, several key elements that were needed for reproducibility were inadequate, including differentiation of primary and secondary outcomes, power calculations for group size, allocation methods, use of randomization and blinding, checks for normality, reports of attrition, and adverse events of subjects, and assessment of bias. A secondary goal was to examine whether a required checklist improved the quality of reporting; those results indicated that a checklist improved compliance and quality of reporting, but adequacy levels in key categories were still too low. Overall, the findings of this study indicated that the probability for reproducibility of many clinical and preclinical cardiovascular research studies was low because of incomplete reporting, low statistical power, and lack of research practices that decrease experimental bias. Expansion of group sizes to increase power, use of detailed checklists, and closer monitoring for checklist adherence by editors and journals should remediate many of these deficits and increase the likelihood of reproducibility.
Advancement in sequencing techniques and transformative progress in metagenomics provides an unprecedented platform for functional and taxonomic characterization of the enormous microbial diversity inhabiting and governing various biochemical processes of the freshwater sources. Metagenomic analysis of freshwater resources has led to the discovery and identification of novel microbial genes and an understanding of how microorganisms mediate energy and carbon. In this study, we report the taxonomical classification of bacterial sequences obtained from 6 dam reservoir sites in Pune city, Maharashtra, India. The analysis was performed using two different alignment tools: BLAST and Kaiju. The bacterial diversity was dominated by the presence of Vogecella indigofera, uncultured Proteobacterium, Wolinella Succinogenes, Chromobacterium violaceum, and Heliobacter billis. It was further observed that, despite an identical bacterial composition over various reservoir sites, there were nominal differences in the relative abundance of the inhabitant species. Almost all reservoirs were dominated by Vogecella indigofera (~29%) and uncultured Proteobacterium (~15%). A seasonal analysis performed using BLAST resulted in a number of species exclusive to the season and the site of their growth. A high proportion of unidentified sequences were also reported which demands sequential identification. The results obtained through BLAST and Kaiju, were significantly different, suggesting inconsistencies and inaccuracies in existing metagenomic reads comparison.
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