Increasing hub disruption parallels dementia severity in autosomal dominant Alzheimer's disease.

Hub regions in the brain, recognized for their roles in ensuring efficient information transfer, are vulnerable to pathological alterations in neurodegenerative conditions, including Alzheimer's disease (AD). Computational simulations and animal experiments have hinted at the theory of activity-dependent degeneration as the cause of this hub vulnerability. However, two critical issues remain unresolved.

Cystine urolithiasis-free duration after first occurrence and treatment is longer for castrated dogs than for sexually intact male dogs.

Objective: To evaluate outcome in 60 dogs with cystine urolithiasis treated with surgical removal with and without castration and postoperative therapeutic diet to determine frequency of recurrence and urolith-free duration.

Methods: Patient records were reviewed for dogs with documented cystine urolithiasis from September 2010 to December 2020. Medical records, client interviews, and referring veterinarians were contacted to document the absence of clinical signs associated with subsequent urolith formation and to evaluate risk factors for urolith reoccurrence.

Network-level enrichment provides a framework for biological interpretation of machine learning results.

Machine learning algorithms are increasingly being utilized to identify brain connectivity biomarkers linked to behavioral and clinical outcomes. However, research often prioritizes prediction accuracy at the expense of biological interpretability, and inconsistent implementation of ML methods may hinder model accuracy. To address this, our paper introduces a network-level enrichment approach, which integrates brain system organization in the context of connectome-wide statistical analysis to reveal network-level links between brain connectivity and behavior.

A foundation model for clinical-grade computational pathology and rare cancers detection.

The analysis of histopathology images with artificial intelligence aims to enable clinical decision support systems and precision medicine. The success of such applications depends on the ability to model the diverse patterns observed in pathology images. To this end, we present Virchow, the largest foundation model for computational pathology to date.

Likelihood-of-harm/help of microsurgery compared to radiosurgery in large vestibular schwannoma.

Purpose: It has been shown that in large vestibular schwannomas (VS), radiosurgery (SRS) is inferior with respect to tumor control compared to microsurgical resection (SURGERY). However, SURGERY poses a significantly higher risk of facial-function deterioration (FFD). The aim of this study was to illustrate the effectiveness in terms of number-needed-to-treat/operate (NNO), number-needed-to-harm (NNH), and likelihood-of-harm/help (LHH) by comparing both treatment modalities in large VS.