ASCHOPLEX: A generalizable approach for the automatic segmentation of choroid plexus.

Background: The Choroid Plexus (ChP) plays a vital role in brain homeostasis, serving as part of the Blood-Cerebrospinal Fluid Barrier, contributing to brain clearance pathways and being the main source of cerebrospinal fluid. Since the involvement of ChP in neurological and psychiatric disorders is not entirely established and currently under investigation, accurate and reproducible segmentation of this brain structure on large cohorts remains challenging. This paper presents ASCHOPLEX, a deep-learning tool for the automated segmentation of human ChP from structural MRI data that integrates existing software architectures like 3D UNet, UNETR, and DynUNet to deliver accurate ChP volume estimates.

Choroid plexus volume in multiple sclerosis can be estimated on structural MRI avoiding contrast injection.

We compared choroid plexus (ChP) manual segmentation on non-contrast-enhanced (non-CE) sequences and reference standard CE T1- weighted (T1w) sequences in 61 multiple sclerosis patients prospectively included. ChP was separately segmented on T1w, T2-weighted (T2w) fluid-attenuated inversion-recovery (FLAIR), and CE-T1w sequences. Inter-rater variability assessed on 10 subjects showed high reproducibility between sequences measured by intraclass correlation coefficient (T1w 0.

Assessing suffering of patients on cancer treatment and of those no longer treated using ESAS-Total Care (TC).

Aim: The aim of the study was to assess the suffering of patients on oncologic treatment and of those no longer on treatment. Preliminarily, we aimed to confirm the psychometric properties of Edmonton Symptom Assessment System-Total Care (ESAS-TC) in different stages of the disease. The ESAS-TC screens physical and psychological symptoms, but also spiritual pain, discomfort deriving from financial problems associated with illness, and suffering related to social isolation.

COVID-19 challenges: From SARS-CoV-2 infection to effective point-of-care diagnosis by electrochemical biosensing platforms.

In January 2020, the World Health Organization (WHO) identified a new zoonotic virus, SARS-CoV-2, responsible for causing the COVID-19 (coronavirus disease 2019). Since then, there has been a collaborative trend between the scientific community and industry. Multidisciplinary research networks try to understand the whole SARS-CoV-2 pathophysiology and its relationship with the different grades of severity presented by COVID-19.

Toward a point-of-care diagnostic for specific detection of Mycobacterium tuberculosis from sputum samples.

This study reports the development of a new PCR-free device, using IS6110 gene as biomarker, for Tuberculosis (TB) diagnosis. An arginine film (ARGFILM) was used to prepare the biosensor platform. MT-probe was immobilized on this biosensor platform to identify IS6110 gene.