Comparison between Measured and Predicted Resting Metabolic Rate Equations in Cross-Training Practitioners.

This study aimed to investigate the resting metabolic rate (RMR) in cross-training practitioners (advanced and novice) using indirect calorimetry (IC) and compare it with predictive equations proposed in the scientific literature. METHODS: A cross-sectional and comparative study analyzed 65 volunteers, both sexes, practicing cross-training (CT). Anthropometry and body composition were assessed, and RMR was measured by IC (FitMate PRO®), bioimpedance (BIA-InBody 570®), and six predictive equations. Data normality was tested by the Kolgomorov-Smirnov test and expressed as mean ± standard deviation with 95% confidence intervals (CI), chi-square test was performed to verify ergogenic resources, and a Bland-Altman plot (B&A) was made to quantify the agreement between two quantitative measurements. One-way ANOVA was applied to body composition parameters, two-way ANOVA with Bonferroni post hoc was used to compare the RMR between groups, and two-way ANCOVA was used to analyze the adjusted RMR for body and skeletal muscle mass. The effect size was determined using Cohen's d considering the values adjusted by ANCOVA. If a statistical difference was found, post hoc Bonferroni was applied. The significance level was p < 0.05 for all tests. RESULTS: The main results indicated that men showed a higher RMR than women, and the most discrepant equations were Cunningham, Tinsley (b), and Johnstone compared to IC. Tinsley's (a) equation indicated greater precision in measuring the RMR in CM overestimated it by only 1.9%, and BIA and the Harris-Benedict in CW overestimated RMR by only 0.1% and 3.4%, respectively. CONCLUSIONS: The BIA and Harris-Benedict equation could be used reliably to measure the RMR of females, while Tinsley (a) is the most reliable method to measure the RMR of males when measuring with IC is unavailable. By knowing which RMR equations are closest to the gold standard, these professionals can prescribe a more assertive diet, training, or ergogenic resources. An assertive prescription increases performance and can reduce possible deleterious effects, maximizing physical sports performance.

Imidacloprid Induces Histopathological Damage in the Midgut, Ovary, and Spermathecal Stored Spermatozoa of Queens After Chronic Colony Exposure.

Bee colony health is declining as a result of several factors, including exposure to pesticides. The development and strength of honey bee colonies depend on the reproductive success of queen bees. Because flowers are sources of food for bees, foragers can accidentally collect and carry contaminated pollen and nectar to their hives; and this may compromise the longevity and the life span of individuals. Thus, the present study aimed to observe the action of imidacloprid in the midgut and ovaries of Apis mellifera queens, as well as the effects on sperm stored in their spermatheca. To this end, the apiary was divided into three experimental groups: control, commercial imidacloprid, and active ingredient imidacloprid. For toxicity assays, a sucrose solution containing 1 µg/L of imidacloprid was offered to the colonies for 42 days. A control group received only food in the same period. In both treatments with imidacloprid, the midgut of queens showed modifications in the external musculature and cellular alterations. Such changes could lead to the nonrecovery of the epithelium and subsequently malabsorption of nutrients. Moreover, the digestive cells of queen bees exposed to the commercial imidacloprid presented pyknotic nuclei, suggesting a cell death process. The main alterations observed in the ovaries of these reproductive bees treated with commercial imidacloprid were degeneration and resorption of the ovariole content, which probably affected their fertilization and colony development. There were no significant changes in the spermatozoa morphology for both treatments with imidacloprid, but this insecticide may interfere with the development and reproductive success of A. mellifera colonies because it affects the morphology and function of essential organs for the survival of queens. Environ Toxicol Chem 2022;41:1637-1648. SETAC.

Analysis of a dose-response assay in Scaptotrigona bipunctatabees, Lepeletier, 1836 (Hymenoptera: Apidae) using the logistic regression model under the Bayesian approach

This paper shows the results of a dose-response study in Scaptotrigona bipunctatabees, Lepeletier, 1836 (Hymenoptera: Apidae) exposed to the insecticide Fastac Duo. The aim was to evaluate the lethal concentration that causes the death of 50% of bees (LC50) and investigate the odd of mortality after exposure to different concentrations, using the logistic regression model under the Bayesian approach. In this approach, it is possible to incorporate a prior information and gives more accurate inferential results. Three independent dose-response experiments were analyzed, dissimilar in their lead time according to guidelines from the Organisation for Economic Co-operation and Development (OECD), in which each assay contained four replicates at the concentration levels investigated, including control. Observing exposure to the agrochemical, it was identified that the higher the concentration, the greater the odd of mortality. Regarding the estimated lethal concentrations for each experiment, the following values were found, 0.03 g a.i. L-1, for 24hours, 0.04 g a.i. L-1, for 48hoursand 0.06 g a.i. L-1for 72hours, showing that in experiments with longer exposure times there was an increase in LC50. Concluding, the study showed an alternative approach to classical methods for dose-response studies in Scaptotrigona bipunctatabees exposed to the insecticide Fastac Duo.

Analyzing weight evolution in mice infected by Trypanosoma cruzi

Concerning the specificities of a longitudinal study, the trajectories of a subject's mean responses not always present a linear behavior, which calls for tools that take into account the non-linearity of individual trajectories and that describe them towards associating possible random effects with each individual. Generalized additive mixed models (GAMMs) have come to solve this problem, since, in this class of models, it is possible to assign specific random effects to individuals, in addition to rewriting the linear term by summing unknown smooth functions, not parametrically specified, then using the P-splines smoothing technique. Thus, this article aims to introduce this methodology applied to a dataset referring to an experiment involving 57 Swiss mice infected by Trypanosoma cruzi, which had their weights monitored for 12 weeks. The analyses showed significant differences in the weight trajectory of the individuals by treatment group; besides, the assumptions required to validate the model were met. Therefore, it is possible to conclude that this methodology is satisfactory in modeling data of longitudinal sort, because, with this approach, in addition to the possibility of including fixed and random effects, these models allow adding complex correlation structures to residuals.