Meta-analysis of the experimental coefficient of variation in wheat using the Bayesian and Frequentist approaches

A large set of variables is assessed for progeny selection in a plant-breeding program and other agronomic fields. The meta-analysis of the coefficient of variation (CVe) produces information for researchers and breeders on the experimental quality of trials. This analysis can also be applied in the decision-making process of the experimental plan regarding the experimental design, the number of repetitions, and the treatments and plants/progenies to be measured. In this study, we evaluated the dataset distribution and the descriptive statistics of CVe through the Frequentist and Bayesian approaches, aiming to establish the credibility and confidence intervals. We submitted CVe data of ten wheat (Triticum aestivum L.) traits reported in 1,068 articles published to the Bayesian and Frequentist analyses. Sample data were analyzed via Gamma and normal models. We selected the model with the lowest Akaike Information Criterion (AIC) value, and then we tested three link functions. In the Bayesian analysis, uniform distributions were used as non-informative priors for the Gamma distribution parameters with three ranges of q~U (a,b,). Thus, the prior probability density function was given by: [formula] The Bayesian and Frequentist approaches with the Gamma model presented similar results for CVe; however, the range Bayesian credible intervals was narrower than the Frequentist confidence intervals. Gamma distribution fitted the CVe data better than the normal distribution. The credible and confidence intervals of CVe were successfully applied to wheat traits and could be used as experimental accuracy measurements in other experiments.(AU)

Evaluating Journal Impact Factor: a systematic survey of the pros and cons, and overview of alternative measures

Journal Impact Factor (JIF) has several intrinsic flaws, which highlight its inability to adequately measure citation distributions or indicate journal quality. Despite these flaws, JIF is still widely used within the academic community, resulting in the propagation of potentially misleading information. A critical review of the usefulness of JIF is needed including an overview of the literature to identify viable alternative metrics. The objectives of this study are: (1) to assess the usefulness of JIF by compiling and comparing its advantages and disadvantages; (2) to record the differential uses of JIF within research environments; and (3) to summarize and compare viable alternative measures to JIF. Methods: Three separate literature search strategies using MEDLINE and Web of Science were completed to address the three study objectives. Each search was completed in accordance with PRISMA guidelines. Results were compiled in tabular format and analyzed based on reporting frequency. Results: For objective (1), 84 studies were included in qualitative analysis. It was found that the recorded advantages of JIF were outweighed by disadvantages (18 disadvantages vs. 9 advantages). For objective (2), 653 records were included in a qualitative analysis. JIF was found to be most commonly used in journal ranking (n = 653, 100%) and calculation of scientific research productivity (n = 367, 56.2%). For objective (3), 65 works were included in qualitative analysis. These articles revealed 45 alternatives, which includes 18 alternatives that improve on highly reported disadvantages of JIF. Conclusion: JIF has many disadvantages and is applied beyond its original intent, leading to inaccurate information. Several metrics have been identified to improve on certain disadvantages of JIF. Integrated Impact Indicator (I3) shows great promise as an alternative to JIF. However, further scientometric analysis is needed to assess its properties.(AU)

Exopolysaccharide production from Bacillus velezensis KY471306 using statistical experimental design

Exopolysaccharide (EPS) biopolymers produced by microorganisms play a crucial role in the environment such as health and bio-nanotechnology sectors, gelling agents in food and cosmetic industries in addition to bio-flocculants in the environmental sector as they are degradable, nontoxic. This study focuses on the improvement of EPS production through manipulation of different culture and environmental conditions using response surface methodology (RSM). Plackett-Burman design indicated that; molasses, yeast extract and incubation temperature are the most effective parameters. Box-Behnken RSM indicated that; the optimum concentration for each parameter was 12% (w/v) for molasses, 6 g/L yeast extract and 30 °C for incubation temperature. The most potent bacterial isolate was identified as Bacillus velezensis KY498625. After production, EPS was extracted, purified using DEAE-cellulose, identified using Fourier transform infrared (FTIR), gel permeation chromatography (GPC) and gas chromatography-mass spectroscopy (GC-MS). The result indicated that; it has molecular weight 1.14 × 105 D consisting of glucose, mannose and galactose.(AU)

Fundamental steps in experimental design for animal studies / Passos fundamentais em desenhos experimentais de estudos envolvendo animais

Estudos em animais continuam a ser vital para o desenvolvimento da ciência. O objetivo dessa revisão é o de apresentar a novos pesquisadores, uma visão geral dos passos importantes envolvidos no desenho experimental e, ao mesmo tempo, sugerir algumas informações de ordem prática que geralmente estão incluídas no processo da pesquisa. Os pesquisadores devem atentar sempre aos princípios éticos e seguir estritamente o método científico. Hipóteses bem formuladas e objetivas claros são essenciais e práticos. Nesse contexto, uma pesquisa bibliográfica profunda deve ser executada previamente e o pesquisador deve contar, se possível, com o auxilio de um estatístico experiente. A necessidade de randomização, de planejar um estudo cego e de se minimizar a variação são discutidas e enfatizadas. A escolha de bons grupos controles e o emprego de um estudo piloto são recomendados. Finalmente, a formulação de novas questões para serem respondidas por novas pesquisas é esperada. (AU)