Irritability as a Transdiagnostic Construct Across Childhood and Adolescence: A Systematic Review and Meta-analysis.

This meta-analytic review examined irritability across childhood and adolescence as it relates to symptoms of common mental health disorders in these periods. Of key interest was whether the relationship between irritability and symptom severity varies according to symptom domain. This was tested at the level of broad symptom dimensions (internalizing versus externalizing problems) as well as discrete diagnostic domains (e.

Machine learning validation of a simple prediction model for the correlation between advanced age and clinical outcomes in patients with aneurysmal subarachnoid hemorrhage.

Adverse effects of advanced age and poor initial neurological status on outcomes of patients with aneurysmal subarachnoid hemorrhage (SAH) have been documented. While a predictive model of the non-linear correlation between advanced age and clinical outcome has been reported, no previous model has been validated. Therefore, we created a prediction model of the non-linear correlation between advanced age and clinical outcome by machine learning and validated it using a separate cohort.

Risk factors of short-term poor functional outcomes and long-term durability of ruptured large or giant intracranial aneurysms.

Objective: Aneurysmal subarachnoid hemorrhage (SAH) is associated with high morbidity and mortality rates. In particular, functional outcomes of SAH caused by large or giant (≥ 10 mm) ruptured intracranial aneurysms are worsened by high procedure-related complication rates. However, studies describing the risk factors for poor functional outcomes specific to ruptured large/giant aneurysms are sparse.

Novel high-content and open-source image analysis tools for profiling mitochondrial morphology in neurological cell models.

Mitochondria undergo dynamic morphological changes depending on cellular cues, stress, genetic factors, or disease. The structural complexity and disease-relevance of mitochondria have stimulated efforts to generate image analysis tools for describing mitochondrial morphology for therapeutic development. Using high-content analysis, we measured multiple morphological parameters and employed unbiased feature clustering to identify the most robust pair of texture metrics that described mitochondrial state.