Circulating biomarkers in high-grade gliomas: current insights and future perspectives.

Purpose: High-grade gliomas (HGG) represent a challenging subset of brain tumors characterized by aggressive nature and poor prognosis. Histopathology remains to be the standard for diagnosis, however, it is invasive, prone to sampling errors, and may not capture the full tumor heterogeneity and evolution over time. In recent years, there has been a growing interest in the potential utility of circulating biomarkers, obtained through minimally-invasive liquid biopsies, providing an opportunity for diagnosis, prognostication, monitoring treatment response and developing targeted therapies.

Classification algorithms trained on simple (symmetric) lifting data perform poorly in predicting hand loads during complex (free-dynamic) lifting tasks.

The performance of machine learning (ML) algorithms is dependent on which dataset it has been trained on. While ML algorithms are increasingly used for lift risk assessment, many algorithms are often trained and tested on controlled simulation datasets, lacking the diversity of the lifting conditions. Consequently, concerns arise regarding their applicability in real-world scenarios characterized by substantial variations in lifting scenarios and postures.

Primary and salvage radiosurgery for neurofibromatosis type 2-associated meningiomas.

Objective: The optimal management of neurofibromatosis type 2 (NF2)-associated meningiomas must be personalized case by case. Stereotactic radiosurgery (SRS) is one option for patients with one or multiple intracranial meningiomas associated with the NF2 mutation. In this study, the authors evaluated their single-institution experience of SRS treatment for NF2-associated meningiomas.