One of the steepest reductions in jaguar distribution in the Americas is occurring at the southern end of its range, in Argentina. The species has disappeared from the central portion of the country and is currently confined to three northern ecoregions: the Yungas, the Chaco and the Green Corridor of the Upper Paraná Atlantic Forest. Using nine microsatellite loci we characterise the genetic diversity and structure of these three jaguar populations (n = 54). We also analyse our data in conjunction with those previously reported for Amazonian, Pantanal and other Atlantic Forest populations (n = 255). Argentine jaguars are structured into two genetic groups: Chaco+Yungas and the Green Corridor of the Upper Paraná Atlantic Forest. Both groups show similar genetic diversity, which is lower than that reported elsewhere in South America. On a continental scale, jaguars from Chaco and Yungas were grouped along with individuals from the Amazon and northern Pantanal, while Upper Paraná Atlantic Forest jaguars were assigned to the coastal Atlantic forest population. We associate the observed genetic pattern with a strong signal of local genetic drift, coupled with isolation by distance and little or no gene flow between populations. In this context, it is essential that the increasing ecological disconnection between the Chaco and Yungas ecoregions caused by landscape alterations does not become a genetic disconnection. The isolation of the Upper Paraná Atlantic Forest population is particularly worrying because is isolated from both other Atlantic Forest and Chaco+Yungas populations. Our results emphasize the urgent need for management actions at the regional level, taking into account Jaguar Conservation Units and Corridors.
Emerging evidence suggests associations between gut microbiota patterns and autism-related behavioral and gastrointestinal features, increasing interest in probiotic interventions. This trial aimed to evaluate the effects of kefir-derived probiotics (K11 and K11-TMAX) on adaptive functioning, autism-related traits, and inflammatory/metabolic markers in children with Autism Spectrum Disorder (ASD). In this parallel double-blind randomized clinical trial, 182 children with ASD (3–11 years) were randomly assigned (1:1:1) to the placebo, K11, or K11-TMAX groups. Assessments were conducted at baseline, day 45, and day 90. The primary outcome was the change in the Vineland-3 Adaptive Behavior Composite. The secondary outcomes included the Autism Diagnostic Observation Schedule (ADOS-2) Calibrated Severity Score (CSS), the Childhood Autism Rating Scale (CARS), inflammatory/metabolic biomarkers (insulin, C-reactive protein, prolactin, serum cortisol, and fecal calprotectin) and the fecal microbiota (Colony-Forming Units [CFUs] of Lactobacillus spp. and Escherichia coli). Randomization was computer-generated, and participants, caregivers, and outcome assessors were blinded. A total of 182 children was randomized to placebo (n = 57), K11 (n = 65), or K11-TMAX (n = 60) groups. On Day 90, participants in the K11 and K11-TMAX groups showed significant within-group improvements in Vineland-3 Adaptive Behavior Composite (p < 0.05), with consistent changes across domains. The number of participants analyzed for the primary outcome was 182 (100
A inclusão educacional constitui um princípio fundamental das políticas públicas de educação, buscando garantir o acesso, a permanência e o sucesso de todos os estudantes no processo de aprendizagem. Nesse contexto, o avanço das tecnologias digitais, especialmente da Inteligência Artificial (IA), apresenta novas possibilidades para promover acessibilidade e equidade no ambiente educacional. O presente artigo tem como objetivo analisar as contribuições da Inteligência Artificial para a inclusão educacional, destacando ferramentas e estratégias que favorecem a aprendizagem de estudantes com diferentes necessidades educacionais. Trata-se de um estudo de natureza qualitativa, desenvolvido por meio de pesquisa bibliográfica em produções científicas que abordam educação inclusiva, tecnologias assistivas e inteligência artificial. Os resultados indicam que a IA pode contribuir significativamente para a personalização do ensino, adaptação de conteúdos, acessibilidade comunicacional e apoio pedagógico, ampliando as oportunidades de aprendizagem para estudantes com deficiência e dificuldades educacionais. Contudo, também se identificam desafios relacionados à formação docente, infraestrutura tecnológica e desigualdades de acesso. Conclui-se que a integração consciente e ética da Inteligência Artificial na educação pode fortalecer práticas pedagógicas inclusivas, contribuindo para a construção de sistemas educacionais mais equitativos e acessíveis.
Este artigo analisa como o tecnoconservadorismo brasileiro produziu um repertório moral sobre “justiça social” no contexto do capitalismo de plataforma e de vigilância. Sustenta-se que essa crítica não opera apenas como opinião econômica, mas como gramática moral antielitista, ao converter a “justiça social” em signo de “engenharia social”, “correção política” e “captura universitária”, mobilizando ressentimento, pureza e indignação na busca de um novo regime de “justiça global”. Inicialmente, reconstrói-se o pano de fundo sociotécnico das plataformas publicitárias e do capitalismo de vigilância, enfatizando seus efeitos tecnopolíticos. Em seguida, discute-se o papel de Olavo de Carvalho na curadoria e difusão de autores conservadores, como Thomas Sowell, no interior do diagrama do tecnoconservadorismo brasileiro. Por fim, toma-se o Brasil Paralelo como caso ilustrativo da articulação entre entretenimento, pedagogia política e guerra cultural, mostrando que a disputa em torno da “justiça social” envolve autoridade epistêmica, governo dos afetos e gestão algorítmica da visibilidade.
Abstract The increase in outdoor temperatures resulting from global warming, together the intensive use of HVAC systems without an adequate air change rate in schools have highlighted the need to monitor indoor air quality. This study presents the validation of a low-cost IoT (Internet of Things) device, named Healthy Classroom, developed to estimate the air change rate and indicate, in real-time, the need for corrective actions such as the controlled opening of doors and windows. The validation experiment was conducted through measurements of carbon dioxide (CO₂), air temperature, and relative humidity, which were compared with those obtained from a reference instrument. The results demonstrated a strong correlation between the measurements, confirming the reliability of the device as an accessible and applicable solution for continuous monitoring of indoor air quality in educational settings, supporting informed ventilation management and the promotion of health-promoting indoor environments.
