Publications by authors named "R De Vito"

Spinal muscular atrophy (SMA) is a neuromuscular disorder caused by reduced expression of the survival motor neuron (SMN) protein. In addition to motor neuron survival, SMN deficiency affects the integrity and function of afferent synapses that provide glutamatergic excitatory drive essential for motor neuron firing and muscle contraction. However, it is unknown whether deficits in the metabolism of excitatory amino acids and their precursors contribute to neuronal dysfunction in SMA.

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Plants, including pumpkins ( spp.), are an interesting source of nutrients and bioactives with various health benefits. In this research, carotenoid extracts obtained from the pulp of eight pumpkin varieties, belonging to the and species, were tested for cytotoxicity on SH-SY5Y neuroblastoma cells.

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Background/objectives: Adherence to dietary recommendations is a critical component in the management of type 1 diabetes (T1D). Taste and flavor significantly influence food choices. The aim of this study was to investigate taste sensitivity and flavor recognition ability in adults with T1D compared to healthy individuals.

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This contribution addresses some bioethical and medico-legal issues of the opinion formulated by the Italian National Bioethics Committee (CNB) in response to the dilemma between the State's duty to protect the life and health of the prisoner entrusted to its care and the prisoner's right to exercise his freedom of expression. The prisoner hunger strike is a form of protest frequently encountered in prison and it is a form of communication but also a language used by the prisoner in order to provoke changes in the prison condition. There are no rules in the prison regulations, nor in the laws governing the legal status of prisoners, that allow the conscious will of the capable and informed subject to be opposed and forced nutrition to be carried out.

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Background: Understanding the trend of the severe acute respiratory syndrome Coronavirus 2 (SARS-CoV-2) is becoming crucial. Previous studies focused on predicting COVID-19 trends, but few papers have considered models for disease estimation and progression based on large real-world data.

Methods: We used de-identified data from 60,938 employees of a major financial institution in Italy with daily COVID-19 status information between 31 March 2020 and 31 August 2021.

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