Search

Abstract The lamb meat tenderness acceptance threshold has been little studied and has never been evaluated for the Brazilian population. So, this study aimed to find the maximum acceptable shear force for Brazilian lamb meat consumers. Three muscles were previously tested and chosen Longissimus thoracis et lumborum (LTL), psoas major and semimembranosus muscles received different treatments in the post-slaughter period (Hot deboning followed by cooling on ice, Standard carcass cooling and Ageing), aiming to create samples with varying levels of tenderness, which were evaluated by acceptance tests and descriptive analysis of tenderness by a trained team. Sarcomere length, myofibril fragmentation index, proximate composition, weight loss and pH analyses were performed to observe the biochemical phenomena in each treatment's meats. Variations caused in samples by treatments were more significant than differences inherent to the different muscles. Pearson and Multiple Factor correlation analyses indicated positive correlations between sarcomere length, myofibril fragmentation index and the scores assigned in sensory tests by 140 panelists and a trained team. Both groups noted that the differences between the meats in terms of tenderness and the sarcomere length also influenced the perception of juiciness observed by the groups. The maximum shear force indicated as acceptable for lamb meat was 44.1 N. The results obtained are important to guide the lamb meat producer for certain practices in the post-slaughter moments, avoiding actions that lead to sarcomere shortening and encouraging the production of aged meats.

This theoretical paper presents the development and analysis of an inclusive educational framework designed to manage cognitive load for neurodivergent students in online learning environments. Drawing from cognitive load theory and neurodiversity studies, the framework is based on existing literature, empirical work conducted by the authors, and iterative feedback from a participatory research advisory board. Taking a neurodiversity-informed perspective that focuses on interventions addressing challenges common across a range of conditions, it identifies six critical areas that might impact cognitive load in online learning for neurodivergent students: format, environment, delivery, instruction, support, and research (FEDIS+R). To assess the external factors influencing the potential implementation of the framework and its place within the broader landscape of inclusive education, a PESTEL (Political, Economic, Social, Technological, Environmental, and Legal) analysis was conducted. The analysis highlights challenges such as resource disparities, institutional commitment to inclusion, and legal requirements for accessibility, which may affect the adoption of the framework. Given the evolving nature of both cognitive load theory and neurodiversity studies, future research directions are suggested to evaluate its effectiveness across diverse educational contexts. This paper contributes to the growing body of knowledge on neurodiversity in education and offers practical recommendations for educators and policymakers seeking to create inclusive online learning environments.

Air temperature (Ta) measurements are crucial for characterizing phenomena like the urban heat island (UHI), which can create critical conditions in cities during summer. This study aims to develop a machine learning-based model, namely gradient boosting, to estimate Ta from geostationary satellite LST data and to apply these estimates to investigate UHI dynamics. Using Rome, Italy, as a case study, the model was trained with Ta data from 15 weather stations, taking multi-temporal LST values (instantaneous and lagged up to 4 h) and additional predictors. The model achieved an overall RMSE of 0.9 °C. The resulting Ta fields, with a 3 km spatial and hourly temporal resolution, enabled a detailed analysis of UHI intensity and dynamics during the summers of 2019–2020, significantly enhancing the spatial and temporal detail compared to previous studies based solely on in situ data. The results also revealed a slightly higher nocturnal UHI intensity than previously reported, attributed to the inclusion of rural areas with near-zero imperviousness, thanks to the complete mapping of Ta across the domain now accessible.

Background and Purpose: Therapeutic hypothermia (TH) has become the standard care to reduce morbidity and mortality in neonates affected by moderate‐to‐severe hypoxic–ischaemic encephalopathy (HIE). Despite the use of TH for HIE, the incidence of mortality and disabilities remains high. Experimental Approach: Nerve growth factor (NGF) is a potent neurotrophin, but clinical use is limited by its pain eliciting effects. CHF6467 is a recombinant modified form of human NGF devoid of algogenic activity (painless NGF). Key Results: In rodent hippocampal slices exposed to oxygen and glucose deprivation, CHF6467 protected neurons from death and reverted neurotransmission impairment when combined with hypothermia. In a model of rat neonatal HIE, intranasal CHF6467 (20 μg kg−1) significantly reduced brain infarct volume versus vehicle when delivered 10 min or 3 h after the insult. CHF6467 (20 and 40 μg kg−1, i.n.), significantly decreased brain infarct volume to a similar extent to TH and when combined, showed a synergistic neuroprotective effect. CHF6467 (20 μg kg−1, i.n.) per se and in combination with hypothermia reversed locomotor coordination impairment (Rotarod test) and memory deficits (Y‐maze and novel object recognition test) in the neonatal HIE rat model. Intranasal administration of CHF6467 resulted in meaningful concentrations in the brain, blunted HIE‐induced mRNA elevation of brain neuroinflammatory markers and, when combined to TH, significantly counteracted the increase in plasma levels of neurofilament light chain, a peripheral marker of neuroaxonal damage. Conclusion and Implications: CHF6467 administered intranasally is a promising therapy, in combination with TH, for the treatment of HIE. [ABSTRACT FROM AUTHOR]

This theoretical paper presents the development and analysis of an inclusive educational framework designed to manage cognitive load for neurodivergent students in online learning environments. Drawing from cognitive load theory and neurodiversity studies, the framework is based on existing literature, empirical work conducted by the authors, and iterative feedback from a participatory research advisory board. Taking a neurodiversity-informed perspective that focuses on interventions addressing challenges common across a range of conditions, it identifies six critical areas that might impact cognitive load in online learning for neurodivergent students: format, environment, delivery, instruction, support, and research (FEDIS+R). To assess the external factors influencing the potential implementation of the framework and its place within the broader landscape of inclusive education, a PESTEL (Political, Economic, Social, Technological, Environmental, and Legal) analysis was conducted. The analysis highlights challenges such as resource disparities, institutional commitment to inclusion, and legal requirements for accessibility, which may affect the adoption of the framework. Given the evolving nature of both cognitive load theory and neurodiversity studies, future research directions are suggested to evaluate its effectiveness across diverse educational contexts. This paper contributes to the growing body of knowledge on neurodiversity in education and offers practical recommendations for educators and policymakers seeking to create inclusive online learning environments. [ABSTRACT FROM AUTHOR]