Adult Neurogenesis in the Subventricular Zone of Patients with Huntington's and Parkinson's Diseases and following Long-Term Treatment with Deep Brain Stimulation.

Objective: Parkinson's and Huntington's diseases are characterized by progressive neuronal loss. Previous studies using human postmortem tissues have shown the impact of neurodegenerative disorders on adult neurogenesis. The extent to which adult neural stem cells are activated in the subventricular zone and whether therapeutic treatments such as deep brain stimulation promote adult neurogenesis remains unclear.

The plasma metabolome of juvenile idiopathic arthritis varies according to subtype and underlying inflammatory status.

Background: Juvenile idiopathic arthritis (JIA) is challenging to classify and effectively monitor due to the lack of disease- and subtype-specific biomarkers. A robust molecular signature that tracks with specific JIA features over time is urgently required, and targeted plasma metabolomics may reveal such a signature. The primary aim of this study was to characterise the differences in the plasma metabolome between JIA patients and non-JIA controls and identify specific markers of JIA subtype.

MULTIPLE, REDUNDANT CARBOXYLIC ACID TRANSPORTERS SUPPORT MITOCHONDRIAL METABOLISM IN .

Unlabelled: The mitochondrion of the deadliest human malaria parasite, is an essential source of cellular acetyl-CoA during the asexual blood-stage of the parasite life cycle. Blocking mitochondrial acetyl-CoA synthesis leads to a hypoacetylated proteome and parasite death. We previously determined that mitochondrial acetyl-CoA is primarily synthesized from glucose-derived pyruvate by α-ketoacid dehydrogenases.

Predicting and Accelerating Nanomaterial Synthesis Using Machine Learning Featurization.

Materials synthesis optimization is constrained by serial feedback processes that rely on manual tools and intuition across multiple siloed modes of characterization. We automate and generalize feature extraction of reflection high-energy electron diffraction (RHEED) data with machine learning to establish quantitatively predictive relationships in small sets (∼10) of expert-labeled data, saving significant time on subsequently grown samples. These predictive relationships are evaluated in a representative material system (WVSe on c-plane sapphire (0001)) with two aims: 1) predicting grain alignment of the deposited film using pregrowth substrate data and 2) estimating vanadium dopant concentration using in situ RHEED as a proxy for ex situ methods (e.