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Examines the indication for short-acting nifedipine in children with arterial hypertension. Hypertensive crisis; Relationship between blood flow and arterial pressure; Risk of rapid arterial pressure lowering.

The objective of this review was to critically examine existing digital applications, tailored for use by citizens and professionals, to provide diet monitoring, diet planning, and precision nutrition. We sought to identify the strengths and weaknesses of such digital applications, while exploring their potential contributions to enhancing public health, and discussed potential developmental pathways. Nutrition is a critical aspect of maintaining good health, with an unhealthy diet being one of the primary risk factors for chronic diseases, such as obesity, diabetes, and cardiovascular disease. Tracking and monitoring one's diet has been shown to help improve health and weight management. However, this task can be complex and time-consuming, often leading to frustration and a lack of adherence to dietary recommendations. Digital applications for diet monitoring, diet generation, and precision nutrition offer the promise of better health outcomes. Data on current nutrition-based digital tools was collected from pertinent literature and software providers. These digital tools have been designed for particular user groups: citizens, nutritionists, and physicians and researchers employing genetics and epigenetics tools. The applications were evaluated in terms of their key functionalities, strengths, and limitations. The analysis primarily concentrated on artificial intelligence algorithms and devices intended to streamline the collection and organization of nutrition data. Furthermore, an exploration was conducted of potential future advancements in this field. Digital applications designed for the use of citizens allow diet self-monitoring, and they can be an effective tool for weight and diabetes management, while digital precision nutrition solutions for professionals can provide scalability, personalized recommendations for patients, and a means of providing ongoing diet support. The limitations in using these digital applications include data accuracy, accessibility, and affordability, and further research and development are required. The integration of artificial intelligence, machine learning, and blockchain technology holds promise for improving the performance, security, and privacy of digital precision nutrition interventions. Multidisciplinarity is crucial for evidence-based and accessible solutions. Digital applications for diet monitoring and precision nutrition have the potential to revolutionize nutrition and health. These tools can make it easier for individuals to control their diets, help nutritionists provide better care, and enable physicians to offer personalized treatment., (© The Author(s) 2024. Published by Oxford University Press on behalf of the International Life Sciences Institute. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Objective: Maintaining plasma glucose homeostasis is vital for mammalian survival, but the masticatory function, which influences glucose regulation, has, to our knowledge, been overlooked., Research Methods and Procedures: In this study, we investigated the relationship between the glycemic response curve and chewing performance in a group of 8 individuals who consumed 80 g of apple. A device called "Chewing" utilizing electromyographic (EMG) technology quantitatively assesses chewing pattern, while glycemic response is analyzed using continuous glucose monitoring. We assessed chewing pattern characterizing chewing time (t chew ), number of bites (n chew ), work (w), power (wr), and chewing cycles (t cyc ). Moreover, we measured the principal features of the glycemic response curve, including the area under the curve (α) and the mean time to reach the glycemic peak (t mean ). We used linear regression models to examine the correlations between these variables., Results: t chew , n chew , and wr were correlated with α (R 2 =  0.44,   P  <  0.05 for t chew and n chew , P  <  0.001 for wr), and t mean was correlated with t chew (R 2   =  0.25,  P  <  0.05). These findings suggest that increasing chewing time and power, while reducing the number of chews, resulted in a wider glycemic curve and an earlier attainment of the glycemic peak., Conclusions: These results emphasize the influence of proper chewing techniques on blood sugar levels. Implementing correct chewing habits could serve as an additional approach to managing the glycemic curve, particularly for individuals with diabetes., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Giuseppe Maulucci reports financial support was provided by Regione Lazio PO FSE 2014-2020. “Chewing Performance” was taken from the article by Alessia Riente et al. title “Evaluation of the masticatory pattern through an electromyographic device” by the same co-authors., (Copyright © 2024 The Author(s). Published by Elsevier Inc. All rights reserved.)