Several physicochemical parameters were determined to study the behavior of three commercial oils with different chemical composition in deep fat frying at 160°C. Peroxide value seems not to be an accurate tool to control the quality of frying oils. On the contrary, iodine value, conjugated diene, and viscosity gave useful information about the oils' degradation during deep fat frying. Sunflower oil (SO) showed the highest increase in conjugated diene value. The increase in viscosity was lower for olive oil. The fatty acid profile changed throughout the fryings. Levels of palmitic acid increased and levels of linoleic acid decreased, and high correlations between palmitic acid, oleic acid, and linoleic acid in all oils were found. Trans fatty acids increased in all oils with increasing frying cycles. Extra virgin olive oil and high-oleic acid sunflower oil seem to be the more suitable oils for frying at 160°C. Se determinaron varios parámetros fisicoquímicos (compuestos polares, índice de yodo, índice de peróxidos, dienos conjugados, viscosidad, ácidos grasos y ácidos grasos trans) para estudiar el comportamiento de tres aceites comerciales con diferente composición (aceite de oliva extra virgen, aceite alto oleico de girasol y aceite de girasol) en fritura por inmersión a 160°C. El índice de peróxidos parece no ser una herramienta exacta para el control de los aceites de fritura. Por el contrario, el índice de yodo, los dienos conjugados y la viscosidad proporcionan información útil sobre la degradación del aceite durante la fritura por inmersión. El aceite de girasol mostró el aumento más alto en el valor de dienos conjugados. El incremento de la viscosidad más bajo fue en el aceite de oliva virgen extra. El perfil de ácidos grasos cambió a lo largo de la fritura. Los niveles de ácido palmítico aumentaron y los de ácido linoleico disminuyeron, habiéndose encontrado altas correlaciones entre el ácido palmítico, oleico y linoleico en todos los aceites. Los ácidos grasos trans aumentaron en todos los aceites a medida que aumentaban los ciclos de fritura. Los aceites de oliva virgen extra y de girasol alto oleico parecen ser los más adecuados para fritura a 160°C.

Background: We investigated the postprandial effects of an alcohol-free beer with modified carbohydrate (CH) composition compared to regular alcohol-free beer. Methods: Two randomized crossover studies were conducted. In the first study, 10 healthy volunteers received 25 g of CH in four different periods, coming from regular alcohol-free beer (RB), alcohol-free beer enriched with isomaltulose and a resistant maltodextrin (IMB), alcohol-free beer enriched with resistant maltodextrin (MB), and a glucose-based beverage. In the second study, 20 healthy volunteers were provided with 50 g of CH from white bread (WB) plus water, or with 14.3 g of CH coming from RB, IMB, MB, and extra WB. Blood was sampled after ingestion every 15 min for 2 h. Glucose, insulin, incretin hormones, TG, and NEFAs were determined in all samples. Results: The increase in glucose, insulin, and incretin hormones after the consumption of IMB and MB was significantly lower than after RB. The consumption of WB with IMB and MB showed significantly less increase in glucose levels than WB with water or WB with RB. Conclusions: The consumption of an alcohol-free beer with modified CH composition led to a better postprandial response compared to a conventional alcohol-free beer.

Proper nutrition is a critical component in supporting the overall health and development of individuals with autism spectrum disorder (ASD) who experience eating difficulties associated with their autistic traits. Evidence regarding the prevalence, origins, and consequences of eating issues related to ASD is largely derived from studies on autistic children, while information pertaining to adults remains scarce. It is therefore essential to critically review existing research focusing on autistic adults to draw robust conclusions and identify clear research gaps. A computer-aided search in PubMed, Science Direct, Scopus, and Web of Science databases spanning the years 2013–2024 using the search terms covering ASD/Autism, Adult, Nutrition/Nutritional Status, and Diet yielded 43 full-text articles. In our literature review, we explored three critical aspects of nutrition in adults with ASD: their food preferences and sensory processing patterns, studies on nutritional status, and whether dietary and nutritional interventions have improved their adherence to healthier diets. Autistic adults appear to select food based on sensory perceptions. This selection pattern can affect their nutritional status, with a tendency toward overweight and nutritional deficiencies. The most promising intervention strategies incorporate sensory adaptation and structured meal planning. Further research should apply rigorous methodologies that account for this population’s specific characteristics.

In this study, we developed an improved contact-cooking model that incorporates variations in fat content and its retention capacity, aiming to accurately simulate products with different compositions. The proposed approach incorporates the structural heterogeneity of meat by distinguishing between muscle fibers and interstitial fluid, and simulates the transport of water and fat between these regions. The model also accounts for heat transfer and meat deformation, representing the tissue as a hyperelastic material. The computational framework was implemented for the pan-cooking of hamburgers with different fat contents (ranging from 3% to 24%) and periodic flipping during the process. To validate the model, cooking experiments were performed. Although increasing fat content did not significantly affect water loss or core temperature (p>0.05), it strongly influenced other critical aspects of cooking performance and product quality, such as surface temperature, fat loss, total cooking losses, and shrinkage. These changes are relevant because they impact texture and consumer perception. In addition, hamburgers with a higher fat content exhibited lower hardness, cohesiveness, gumminess, and chewiness. The model successfully predicted these trends, demonstrating its potential to capture fat-related effects beyond thermal behavior and enabling the use of model-generated data for the training, validation, and testing of a simple neural network to predict fat loss during the cooking of hamburgers with varying water, fat, and protein contents.