Using artificial intelligence to prioritize pathology samples: report of a test drive.

The digital transformation of pathology, through automation and computational tools, addresses current challenges in the field. This study evaluates Paige Pan Cancer, a novel artificial intelligence tool based on the Virchow foundation model, designed to flag invasive cancer in haematoxylin and eosin-stained slides from 16 primary tissue types. Using 62 cases from the Ipatimup Pathology Laboratory, we found the tool had a sensitivity of 93.

The role of disease modifying therapies in late-onset multiple sclerosis: A Portuguese multicentric characterization study.

Introduction: Knowledge about the effect of disease modifying treatment (DMT) in late-onset multiple sclerosis (LOMS, onset ≥50 years-old) is scarce. This study aims to evaluate the association between DMT use and multiple sclerosis (MS) evolution in a LOMS cohort.

Methods: This multicentre, retrospective and observational study included LOMS patients with ≥2 years of follow-up.

Validation of the Portuguese MDS-UPDRS: Challenges to Obtain a Scale Applicable to Different Linguistic Cultures.

Background: The MDS-UPDRS has been available in English since 2008, showing satisfactory clinimetric results and being proposed as the new official benchmark scale for Parkinson's disease (PD), being cited as a core instrument for PD in the National Institutes of Neurological Disorders and Stroke Common Data Elements program. For this reason, the MDS created guidelines for development of MDS-UPDRS official, clinimetrically validated translations.

Objective: This study presents the formal process used to obtain the officially approved Portuguese version of the MDS-UPDRS.

Blood neutrophils, oligoclonal bands and bridging corticosteroids as predictive factors for MOGAD course: Insights from a multicentric Portuguese cohort.

Background: Myelin oligodendrocyte glycoprotein (MOG) antibody-associated disease (MOGAD) is a heterogeneous entity with either a monophasic or relapsing course. Well-established predictors of relapsing disease are lacking.

Objective: Identifying predictors of relapsing MOGAD, particularly at disease onset.

High-Risk HPV Detection in Paraffin-Embedded Tissue from Cervical Lesions.

Background: Human papillomavirus (HPV), a leading cause of cervical cancer, is present in most cases of the disease and ranks as the fourth most common cancer in women globally. Among the HPV types, fourteen (HPV 16/18/31/33/35/39/45/51/52/56/58/59/66/68) are recognized as high-risk (hrHPV), each with varying levels of oncogenic potential. Detecting and genotyping these hrHPV types in cervical lesions is crucial, requiring the development of new diagnostic methods.