In this article, we introduce a new continuous distribution based on the unit interval. This distribution is generated from a transformation of a random variable with half-normal distribution. We study its basic properties, percentiles, moments and order statistics. Maximum likelihood estimation is applied, and we present a simulation study to observe the behavior of the maximum likelihood estimators. We examine two applications to real proportions datasets, where the new distribution is shown to provide a better fit than other distributions defined in the unit interval.

Skewness and bimodality properties are frequently observed when analyzing environmental data such as wind speeds, precipitation levels, and ambient temperatures. As an alternative to modeling data exhibiting these properties, we propose a flexible extension of the skew-logistic distribution. The proposal corresponds to a weighted version of the skewed logistic distribution, defined by a parametric weight function that allows shapes with up to three modes for the resulting density. Parameter estimation via the maximum likelihood approach is discussed. Simulation experiments are carried out to evaluate the performance of the estimators. Applications to environmental data illustrating the utility of the proposal are presented.

In Chile, individuals are commonly exposed to high altitude due to the work shift system, involving days of exposure to high altitude followed by days at sea level over the long term, which can result in chronic intermittent hypobaric hypoxia (CIHH). CIHH can cause high-altitude pulmonary hypertension (HAPH), the principal manifestation of which is right ventricular hypertrophy (RVH), in some cases leading to heart failure and eventually death. Studies have shown the contribution of oxidative stress and inflammation to RVH development. Recently, it was determined that the pigment astaxanthin has high antioxidant capacity and strong anti-inflammatory and cardioprotective effects. Therefore, the aim of this study was to determine the effects of astaxanthin on RVH development in rats subjected to CIHH. Methods: Thirty two male Wistar rats were randomly assigned to the following groups (n = 8 per group): the normoxia with vehicle (NX), normoxia with astaxanthin (NX + AS), chronic intermittent hypobaric hypoxia with vehicle (CIHH), and chronic intermittent hypobaric hypoxia with astaxanthin (CIHH + AS) groups. CIHH was simulated by 2 days in a hypobaric chamber followed by 2 days at sea level for 29 days. Results: Exposure to CIHH induced RVH and increased lipid peroxidation (MDA), Nox2 expression, and SOD activity, however, it decreased pro-IL-1β expression. Astaxanthin restored oxidative stress markers (Nox2 and MDA), increased GPx activity, and decreased RVH compared to CIHH. Conclusion: Astaxanthin alleviates RVH and reduces Nox2 and MDA levels while increasing GPx activity in rats subjected to CIHH. These findings provide new insights of astaxanthin as a new nutraceutical against high-altitude effects.

Lead is a harmful heavy metal known to alter the environment and affect human health. Several industries have contributed to the increase in lead contamination, making it a major global concern. Thus, remediation strategies are necessary to prevent lead bioaccumulation and deleterious health effects. The aim of this study was to determine the capacity of the green microalga Chlorella vulgaris (C. vulgaris or CV) to remove lead in an animal model and prevent the accumulation of this heavy metal in the principal organs (brain, liver, and kidney) and blood. Forty male Wistar rats were randomly assigned to four groups (n = 10): control group (CT); C. vulgaris supplementation group, 5% of the diet (CV); lead acetate administration group, 500 ppm (Pb); and C. vulgaris supplementation group, 5% of the diet plus lead acetate administration group, 500 ppm (CV–Pb). After 4 weeks of exposure, we measured lead accumulation, memory function, oxidative stress, and antioxidant activity (SOD and GSH). Lead exposure altered memory function, increased oxidative stress in the brain and kidney, and increased SOD activity in the brain. Supplementation with C. vulgaris restored memory function to control levels; reduced oxidative stress in the brain and kidney; and decreased the accumulation of lead in the liver, kidney, and blood of rats exposed to lead. Based on our results, C. vulgaris is a lead chelating and antioxidant agent in animal models.

This paper introduces a new family of quantile regression models whose response variable follows a reparameterized Marshall-Olkin distribution indexed by quantile, scale, and asymmetry parameters. The family has arisen by applying the Marshall-Olkin approach to distributions belonging to the location-scale family. Models of higher flexibility and whose structure is similar to generalized linear models were generated by quantile reparameterization. The maximum likelihood (ML) method is presented for the estimation of the model parameters, and simulation studies evaluated the performance of the ML estimators. The advantages of the family are illustrated through an application to a set of nutritional data, whose results indicate it is a good alternative for modeling slightly asymmetric response variables with support on the real line.

In this article, we introduce a new model with positive support. This model is an extension of the truncated Gumbel distribution, where a shape parameter is incorporated that provides greater flexibility to the new model. The model is parameterized in terms of the p-th quantile of the distribution to perform quantile regression in this model. An extensive simulation study demonstrates the good performance of the maximum likelihood estimators in finite samples. Finally, two applications to real datasets related to the level of beta-carotene and body mass index are presented.