Leprosy is a neglected tropical disease that can cause physical injury and mental disability. Diagnosis is primarily clinical, but can be inconclusive due to the absence of initial symptoms and similarity to other dermatological diseases. Artificial intelligence (AI) techniques have been used in dermatology, assisting clinical procedures and diagnostics. In particular, AI-supported solutions have been proposed in the literature to aid in the diagnosis of leprosy, and this Systematic Literature Review (SLR) aims to characterize the state of the art. This SLR followed the preferred reporting items for systematic reviews and meta-analyses (PRISMA) framework and was conducted in the following databases: ACM Digital Library, IEEE Digital Library, ISI Web of Science, Scopus, and PubMed. Potentially relevant research articles were retrieved. The researchers applied criteria to select the studies, assess their quality, and perform the data extraction process. Moreover, 1659 studies were retrieved, of which 21 were included in the review after selection. Most of the studies used images of skin lesions, classical machine learning algorithms, and multi-class classification tasks to develop models to diagnose dermatological diseases. Most of the reviewed articles did not target leprosy as the study’s primary objective but rather the classification of different skin diseases (among them, leprosy). Although AI-supported leprosy diagnosis is constantly evolving, research in this area is still in its early stage, then studies are required to make AI solutions mature enough to be transformed into clinical practice. Expanding research efforts on leprosy diagnosis, coupled with the advocacy of open science in leveraging AI for diagnostic support, can yield robust and influential outcomes.

The increasing integration of Artificial Intelligence (AI) into dermatology holds significant potential to enhance the diagnosis and prognosis of skin diseases, which represent a considerable public health burden. While numerous AI models for skin conditions have been developed, their successful translation into real-world clinical practice critically depends on rigorous external validation to ensure generalizability and reliability beyond their development environment. Despite the growing recognition of external validation’s importance in medical AI, a comprehensive synthesis specifically addressing this process for AI models in dermatology has been lacking. This systematic literature review aimed to identify and synthesize studies focused exclusively on the external validation of AI models for skin diseases, thereby assessing their clinical applicability, methodological robustness, and identifying key challenges. Following the PRISMA framework, a systematic search was conducted across five major digital libraries (ACM Digital Library, IEEE Xplore, Web of Science, PubMed, and Scopus). Study quality was assessed using a customized checklist, and data extraction focused on validation practices, model characteristics, targeted diseases, performance assessment, and identified limitations. The systematic study selection led to a detailed analysis of 41 studies. We observed a clear predominance of retrospective external validation studies focused on diagnostic models, while prognostic models and prospective validation designs were notably scarce. Although some models demonstrated promising performance in external validation, several critical limitations persist. These include the narrow representation of skin disease categories, lack of subgroup fairness analyses, small and imbalanced sample sizes, and insufficient standardization of data collection and evaluation metrics. These findings underscore the need for more rigorous and transparent validation frameworks to support the reliable integration of AI into dermatological practice.

A Doença de Parkinson (DP) apresenta-se na senescência, limitando o movimento e progredindo para demência, sendo assim a segunda doença neurodegenerativa no mundo relacionada a idade. Desse modo, esta revisão bibliográfica tem como objetivo reunir informações relevantes sobre a DP para direcionar novas abordagens científicas que favorecerão à aplicação clínica, e assim, a qualidade de vida dos pacientes da PD. Foram selecionados e analisados 80 estudos publicados nos últimos 20 anos em base de dados com descritores indexados. O resultado observado direciona para a compreensão de teorias causais, sintomas motores e não-motores, diagnóstico e tratamento. Concluiu-se que o estudo norteia, a partir das informações levantadas, novos estudos experimentais para a melhora da qualidade de vida de pacientes da DP.

The circadian rhythm deregulation can result in an alteration in the sleep-wake cycle, causing sleep disturbances and promoting mental and mood disorders development. Conditions that can disrupt this rhythm, such as shift work schedule (SWS) can unbalance neural functioning and favors those professional classes may have a greater tendency to develop depression. In this context, this study aims to carry out a systematic review to understand the relationship between SWS and the risk of depression, so 1,001 articles were selected for eligibility analysis for the study. After an evaluation sequence starting from the title, abstract and complete work, 31 works that responded to the proposed theme were included. Depression was found to be higher in JTT workers such as nurses, company employees, physicians, residents, and firefighters compared to other professionals. The main explanations involve decreased melatonin production, stressful conditions linked to professional activity and lifestyle habits. Thus, it is important to delineate new therapeutic forms, control, prevention, and health promotion for these workers, since the SWS is strongly associated with depression.

Bromazepam emulates the inhibitory effect of the neurotransmitter gamma-aminobutyric acid (GABA) and can lead to impaired visuomotor performance. However, few studies have evaluated its effects on cortical coupling in target shooting activities. The present study aimed to analyze the acute effects of bromazepam administration in a target shooting task and the EEG theta rhythm coherence between frontal, temporal, and motor cortical areas in four shooting preparation periods. Thus, a double blind, crossover study was conducted with 30 subjects under two conditions: bromazepam (6mg) and placebo, with electroencephalographic analysis to simultaneously study the theta rhythm coherence in frontal, temporal, and motor cortex in a target shooting task; and the possible interferences of bromazepam administration. Subjects in the bromazepam group showed lower performance on the task compared to placebo (p=0.001). In addition, our analysis showed decreased coherence between regions in the same hemisphere, increased theta rhythm coherence in interhemispheric regions in frontal, temporal and motor cortex at different intervals in the preparation preceding the shooting (p=0.001). The use of bromazepam may influence task execution, possibly due to neurochemical modulation, during decision making, developing shooting preparation strategies, as well as interfering with the flow of information at the level of attention during task execution.

Além do trato respiratório ser o principal acometido pela COVID-19, o envolvimento neurológico não é incomum em pacientes internados podendo resultar em complicações graves. Encefalopatia e encefalite são complicações graves e devastadoras do Sistema Nervoso Central (SNC) que vêm sendo associadas à COVID-19. Esta revisão sistemática reúne dados existentes na literatura a respeito do desenvolvimento de diversos tipos de encefalites e encefalopatias em pacientes com COVID-19. Foi realizada busca nas bases de dados PubMed, Scopus e Web of Science, resultando em 231 artigos. Restaram 25 trabalhos para compor esta revisão sistemática. Entre eles, 2 foram estudos retrospectivos e 23 são relatos de casos. 12 estudos apresentaram casos com dados consistentes com encefalite e 14 com encefalopatias. Entre eles, alguns casos com tipos mais específicos foram observados mais de uma vez em nossas pesquisas: 3 de meningoencefalite, 3 de Acute Necrotizing Encephalopathy (ANE), 2 de Posterior Reversible Encephalopathy Syndrome (PRES), 2 de Acute Disseminated Encephalomyelitis (ADEM). Foram comuns os achados de hiperintensidades da substância branca, cortical ou subcortical. Hipodensidades e hipoatenuação de estruturas profundas da substância branca e hipodensidades focais das estruturas profundas, assim como múltiplas lesões envolvendo hipocampo, gânglios de base, medula, tronco encefálico, tálamo, dentre outras regiões. Estudos pós-morte já demonstraram a presença de partículas virais de SARS-CoV-2 em tecido cerebral. Esse envolvimento do SNC associado à COVID-19 é considerado indicador de prognóstico ruim, podendo levar a rápida deterioração clínica dos pacientes.