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To discover new molecules or review the biological activity and toxicity of therapeutic substances, drug development, and research relies on robust biological systems to obtain reliable results. Phenotype-based screenings can transpose the organism’s compensatory pathways by adopting multi-target strategies for treating complex diseases, and zebrafish emerged as an important model for biomedical research and drug screenings. Zebrafish’s clear correlation between neuro-anatomical and physiological features and behavior is very similar to that verified in mammals, enabling the construction of reliable and relevant experimental models for neurological disorders research. Zebrafish presents highly conserved physiological pathways that are found in higher vertebrates, including mammals, along with a robust behavioral repertoire. Moreover, it is very sensitive to pharmacological/environmental manipulations, and these behavioral phenotypes are detected in both larvae and adults. These advantages align with the 3Rs concept and qualify the zebrafish as a powerful tool for drug screenings and pre-clinical trials. This review highlights important behavioral domains studied in zebrafish larvae and their neurotransmitter systems and summarizes currently used techniques to evaluate and quantify zebrafish larvae behavior in laboratory studies.

The atmospheric boundary layer height (zi) is a key parameter in the vertical transport of mass, energy, moisture, and chemical species between the surface and the free atmosphere. There is a lack of long-term and continuous observations of zi, however, particularly for remote regions, such as the Amazon forest. Reanalysis products, such as ERA5, can fill this gap by providing temporally and spatially resolved information on zi. In this work, we evaluate the ERA5 estimates of zi (zi-ERA5) for two locations in the Amazon and corrected them by means of ceilometer, radiosondes, and SODAR measurements (zi-experimental). The experimental data were obtained at the remote Amazon Tall Tower Observatory (ATTO) with its pristine tropical forest cover and the T3 site downwind of the city of Manaus with a mixture of forest (63%), pasture (17%), and rivers (20%). We focus on the rather typical year 2014 and the El Niño year 2015. The comparison of the experimental vs. ERA5 zi data yielded the following results: (i) zi-ERA5 underestimates zi-experimental daytime at the T3 site for both years 2014 (30%, underestimate) and 2015 (15%, underestimate); (ii) zi-ERA5 overestimates zi-experimental daytime at ATTO site (12%, overestimate); (iii) during nighttime, no significant correlation between the zi-experimental and zi-ERA5 was observed. Based on these findings, we propose a correction for the daytime zi-ERA5, for both sites and for both years, which yields a better agreement between experimental and ERA5 data. These results and corrections are relevant for studies at ATTO and the T3 site and can likely also be applied at further locations in the Amazon.

The purpose of this study was to analyse whether contextual (perception of motivational climate and positive and negative spontaneous self-talk in sports), personal (positivity) and situational variables (positive and negative spontaneous self-talk employed in competition and precompetitive anxiety) predict performance in a competition of ensembles of rhythmic gymnastics. 258 female gymnasts between ages14 and 20 ( M = 15.24, SD = 1.46) participated in the study, completing pre- and post-competition measures. The results of the path-analysis showed that both the task-involving climate and positivity predicted positive self-talk in sport. This predicted self-confidence which, in turn, positively predicted positive situational self-talk in competition. For its part, the perception of an ego-involving climate positively predicted the use of both negative and positive self-talk in sport. Negative self-talk in sports predicted negative situational self-talk in competition and somatic and cognitive anxiety. In turn, cognitive anxiety positively predicted negative situational self-talk. Finally, performance was positively predicted by positive situational self-talk and negatively by negative situational self-talk. These results explain the functioning of spontaneous self-talk at different levels of generality and its relationship with sports performance.

PurposeThe aim of this study was to assess the effects of flexible intensive care unit (ICU) visitation on the 1-year prevalence of post-traumatic stress, anxiety and depression symptoms among family members of critically ill patients.MethodsThis is a long-term outcome analysis of a cluster-crossover randomized clinical trial that evaluated a flexible visitation model in the ICU (12 h/day) compared to a restrictive visitation model (median 1.5 h/day) in 36 Brazilian ICUs. In this analysis, family members were assessed 12 months after patient discharge from the ICU for the following outcomes: post-traumatic stress symptoms measured by the Impact Event Scale-6 and anxiety and depression symptoms measured by the Hospital Anxiety and Depression Scale.ResultsA total of 519 family members were analyzed (288 in the flexible visitation group and 231 in the restrictive visitation group). Three-hundred sixty-nine (71.1%) were women, and the mean age was 46.6 years. Compared to family members in the restrictive visitation group, family members in the flexible visitation group had a significantly lower prevalence of post-traumatic stress symptoms (21% vs. 30.5%; adjusted prevalence ratio [aPR], 0.91; 95% confidence interval [CI] 0.85–0.98; p = 0.01). The prevalence of anxiety (28.9% vs. 33.2%; aPR 0.93; 95% CI 0.72–1.21; p = 0.59) and depression symptoms (19.2% vs. 25%; aPR, 0.78; 95% CI 0.60–1.02; p = 0.07) did not differ significantly between the groups.ConclusionFlexible ICU visitation, compared to the restrictive visitation, was associated with a significant reduction in the 1-year prevalence of post-traumatic stress symptoms in family members.

The presence of pharmaceutical products in the aquatic environment has been reported in several studies. However, the impact of these drugs on living organisms is still uncharacterized. Here, we investigated the effects of acute exposure to either diazepam or fluoxetine on the stress response in Danio rerio. We showed that diazepam and fluoxetine inhibited the stress axis in zebrafish. Intermediate concentrations of diazepam suppressed the stress response as measured by cortisol levels, whereas fluoxetine inhibited cortisol increase at concentrations similar to those found in the environment. These data suggest that the presence of psychoactive drugs in aquatic ecosystems could cause neuroendocrine dysfunction in fish.

Despite the obvious morphological differences in the visual system, zebrafish share a similar architecture and components of the same embryonic origin as humans. The zebrafish retina has the same layered structure and cell types with similar metabolic and phototransduction support as humans, and is functional 72 h after fertilization, allowing tests of visual function to be performed. The zebrafish genomic database supports genetic mapping studies as well as gene editing, both of which are useful in the ophthalmological field. It is possible to model ocular disorders in zebrafish, as well as inherited retinal diseases or congenital or acquired malformations. Several approaches allow the evaluation of local pathological processes derived from systemic disorders, such as chemical exposure to produce retinal hypoxia or glucose exposure to produce hyperglycemia, mimicking retinopathy of prematurity or diabetic retinopathy, respectively. The pathogenesis of ocular infections, autoimmune diseases, or aging can also be assessed in zebrafish larvae, and the preserved cellular and molecular immune mechanisms can be assessed. Finally, the zebrafish model for the study of the pathologies of the visual system complements certain deficiencies in experimental models of mammals since the regeneration of the zebrafish retina is a valuable tool for the study of degenerative processes and the discovery of new drugs and therapies.

The environmental and occupational risk we confront from agricultural chemicals increases as their presence in natural habitats rises to hazardous levels, building a major part of the exposome. This is of particular concern in low- and middle-income countries, such as Brazil, known as a leading producer of agricultural commodities and consumer of pesticides. As long as public policies continue to encourage the indiscriminate use of pesticides and governments continue to support this strategy instead of endorsing sustainable agricultural alternatives, the environmental burden that damages epithelial barriers will continue to grow. Chronic exposure to environmental contaminants in early life can affect crucial barrier tissue, such as skin epithelium, airways, and intestine, causing increased permeability, leaking, dysbiosis, and inflammation, with serious implications for metabolism and homeostasis. This vicious cycle of exposure to environmental factors and the consequent damage to the epithelial barrier has been associated with an increase in immune-mediated chronic inflammatory diseases. Understanding how the harmful effects of pesticides on the epithelial barrier impact cellular interactions mediated by endogenous sensors that coordinate a successful immune system represents a crucial challenge. In line with the epithelial barrier hypothesis, this narrative review reports the available evidence on the effects of pesticides on epithelial barrier integrity, dysbiosis, AhR signaling, and the consequent development of immune-mediated inflammatory diseases.

The integration of machine learning (ML) techniques in coastal engineering marks a paradigm shift in how coastal processes are modeled and understood. While traditional empirical and numerical models have been stalwarts in simulating coastal phenomena, the burgeoning complexity and computational demands have paved the way for data-driven approaches to take center stage. This review underscores the increasing preference for ML methods in coastal engineering, particularly in predictive tasks like wave pattern prediction, water level fluctuation, and morphology change. Although the scope of this review is not exhaustive, it aims to spotlight recent advancements and the capacity of ML techniques to harness vast datasets for more efficient and cost-effective simulations of coastal dynamics. However, challenges persist, including issues related to data availability and quality, algorithm selection, and model generalization. This entails addressing fundamental questions about data quantity and quality, determining optimal methodologies for specific problems, and refining techniques for model training and validation. The reviewed literature paints a promising picture of a future where ML not only complements but significantly enhances our ability to predict and manage the intricate dynamics of coastal environments.

Seaports are highly energy demanding infrastructures and are exposed to wave energy, which is an abundant resource and largely unexploited. As a result, there has been a rising interest in integrating wave energy converters (WEC) into the breakwaters of seaports. The present work analyzes the performance of an innovative hybrid WEC module combining an oscillating water column (OWC) and an overtopping device (OWEC) integrated into a rubble mound breakwater, based on results of a physical model study carried out at a geometrical scale of 1:50. Before the experimental tests, the device’s performance was numerically optimized using ANSYS Fluent and WOPSim v3.11. The wave power captured by the hybrid WEC was calculated and the performance of the two harvesting principles discussed. It was demonstrated that hybridization could lead to systems with higher efficiencies than its individual components, for a broader range of wave conditions. The chosen concepts were found to complement each other: the OWEC was more efficient for the lower wave periods tested and the OWC for the higher. Consequently, the power production of the hybrid WEC was found to be less dependent on the wave’s characteristics.

Remodelling of the nuclear membrane is essential for the dynamic changes of nuclear architecture at different stages of the cell cycle and during cell differentiation. The molecular mechanism underlying the regulation of nuclear membrane biogenesis is not known. Here we show that Smp2, the yeast homologue of mammalian lipin, is a key regulator of nuclear membrane growth during the cell cycle. Smp2 is phosphorylated by Cdc28/Cdk1 and dephosphorylated by a nuclear/endoplasmic reticulum (ER) membrane–localized CPD phosphatase complex consisting of Nem1 and Spo7. Loss of either SMP2 or its dephosphorylated form causes transcriptional upregulation of key enzymes involved in lipid biosynthesis concurrent with a massive expansion of the nucleus. Conversely, constitutive dephosphorylation of Smp2 inhibits cell division. We show that Smp2 associates with the promoters of phospholipid biosynthetic enzymes in a Nem1–Spo7‐dependent manner. Our data suggest that Smp2 is a critical factor in coordinating phospholipid biosynthesis at the nuclear/ER membrane with nuclear growth during the cell cycle.