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The role of immune system components in the development of myocardial remodeling in chronic kidney disease (CKD) and kidney transplantation remains an open question. Our aim was to investigate the associations between immune cell subpopulations in the circulation of CKD patients and kidney transplant recipients (KTRs) with subclinical indices of myocardial performance. We enrolled 44 CKD patients and 38 KTRs without established cardiovascular disease. A selected panel of immune cells was measured by flow cytometry. Classical and novel strain-related indices of ventricular function were measured by speckle-tracking echocardiography at baseline and following dipyridamole infusion. In CKD patients, the left ventricular (LV) relative wall thickness correlated with the CD14++CD16− monocytes (β = 0.447, p = 0.004), while the CD14++CD16+ monocytes were independent correlates of the global radial strain (β = 0.351, p = 0.04). In KTRs, dipyridamole induced changes in global longitudinal strain correlated with CD14++CD16+ monocytes (β = 0.423, p = 0.009) and CD4+ T-cells (β = 0.403, p = 0.01). LV twist and untwist were independently correlated with the CD8+ T-cells (β = 0.405, p = 0.02 and β = −0.367, p = 0.03, respectively) in CKD patients, whereas the CD14++CD16+ monocytes were independent correlates of LV twist and untwist in KTRs (β = 0.405, p = 0.02 and β = −0.367, p = 0.03, respectively). Immune cell subsets independently correlate with left ventricular strain and torsion-related indices in CKD patients and KTRs without established CVD. [ABSTRACT FROM AUTHOR]

Screening and evaluation of developmental disorders include complex and challenging procedures, exhibit uncertainties in the diagnostic fit, and require high clinical expertise. Although typically, clinicians' evaluations rely on diagnostic instrumentation, child observations, and parents' reports, these may occasionally result in subjective evaluation outcomes. Current advances in artificial intelligence offer new opportunities for decision making, classification, and clinical assessment. This study explores the performance of different neural network optimizers in biometric datasets for screening typically and non-typically developed children for speech and language communication deficiencies. The primary motivation was to give clinicians a robust tool to help them identify speech disorders automatically using artificial intelligence methodologies. For this reason, in this study, we use a new dataset from an innovative, recently developed serious game collecting various data on children's speech and language responses. Specifically, we employed different neural network approaches such as Artificial Neural Networks (ANNs), K-Nearest Neighbor (KNN), Support Vector Machines (SVM), along with state-of-the-art Optimizers, namely the Adam, the Broyden–Fletcher–Goldfarb–Shanno (BFGS), Genetic algorithm (GAs), and Particle Swarm Optimization algorithm (PSO). The results were promising, while Integer-bounded Neural Network proved to be the best competitor, opening new inquiries for future work towards automated classification supporting clinicians' decisions on neurodevelopmental disorders. [ABSTRACT FROM AUTHOR]

In this paper, motivated by the current increasing interest and action on food waste reduction, inventory decisions of a retailer who deals with a product that has a fixed shelf life are studied. Being a common strategy of many retail stores, we assume that at a specific time instant, close to the expiration date, a price markdown is offered in order to increase demand. However, at the same time, due to customers' attention to the freshness of the product, the demand becomes a decreasing function with respect to the time remaining before the expiration date. In accordance with the European Union food donation guidelines, we assume that if at the end of the reorder interval unsold items remain that have not exceeded their expiration date, they can be donated to non-profit organizations for human consumption. The donated products can generate direct revenue from tax deductions and indirect revenue by increasing the company's reputation and gain of goodwill from the customers. If the unsold items have expired, they can be sold at a salvage price to the livestock market. The aim of our model is to determine the reorder interval, the time instant to markdown the product's initial selling price and the quantity that will be donated or sold to the livestock market so that the profit of the system is maximized. Closed form solutions are obtained, which depend on specific parametric conditions, providing managerial insights. [ABSTRACT FROM AUTHOR]