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Background: People with cerebral palsy are largely dependent on their caregivers, who are most often members of their family. Caring for people with disabilities can be challenging as both dependents and caregivers face problems of social isolation and stigmatization.

Aim: The aim of this study was to understand the experiences of caregivers of dependents with cerebral palsy in Greece.

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Purpose: To develop and validate an MRI-based model for predicting postoperative early (≤2 years) recurrence-free survival (RFS) in patients receiving upfront surgical resection (SR) for beyond Milan hepatocellular carcinoma (HCC) and to assess the model's performance in separate patients receiving neoadjuvant therapy for similar-stage tumors.

Method: This single-center retrospective study included consecutive patients with resectable BCLC A/B beyond Milan HCC undergoing upfront SR or neoadjuvant therapy. All images were independently evaluated by three blinded radiologists.

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Global concern regarding transformation products (TPs) derived from contaminants, including pesticides, in the environment and during water treatment has been growing markedly. In the present study, we investigated the anti-acetylcholinesterase (AChE) activity of an aqueous solution of the organophosphorus insecticide disulfoton, a toxicological endpoint for determining the acceptable daily intake of disulfoton, both in the presence and the absence of metabolism during chlorination. Disulfoton rapidly reacted with free chlorine and completely disappeared within 0.

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Photoacoustic tomography (PAT) is a non-destructive, non-ionizing, and rapidly expanding hybrid biomedical imaging technique, yet it faces challenges in obtaining clear images due to limited data from detectors or angles. As a result, the methodology suffers from significant streak artifacts and low-quality images. The integration of deep learning (DL), specifically convolutional neural networks (CNNs), has recently demonstrated powerful performance in various fields of PAT.

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