A multi-expert ensemble system for predicting Alzheimer transition using clinical features.

Alzheimer's disease (AD) diagnosis often requires invasive examinations (e.g., liquor analyses), expensive tools (e.

Cerebellum-Cortical Interaction in Spatial Navigation and Its Alteration in Dementias.

The cerebellum has a homogeneous structure and performs different computational functions such as modulation/coordination of the communication between cerebral regions, and regulation/integration of sensory information. Albeit cerebellar activity is generally associated with motor functions, several recent studies link it to various cognitive functions, including spatial navigation. In addition, cerebellar activity plays a modulatory role in different cognitive domains and brain processes.

Machine Learning analysis of high-grade serous ovarian cancer proteomic dataset reveals novel candidate biomarkers.

Ovarian cancer is one of the most common gynecological malignancies, ranking third after cervical and uterine cancer. High-grade serous ovarian cancer (HGSOC) is one of the most aggressive subtype, and the late onset of its symptoms leads in most cases to an unfavourable prognosis. Current predictive algorithms used to estimate the risk of having Ovarian Cancer fail to provide sufficient sensitivity and specificity to be used widely in clinical practice.

Increasing Serotonin to Reduce Parkinsonian Tremor.

While current dopamine-based drugs seem to be effective for most Parkinson's disease (PD) motor dysfunctions, they produce variable responsiveness for resting tremor. This lack of consistency could be explained by considering recent evidence suggesting that PD resting tremor can be divided into different partially overlapping phenotypes based on the dopamine response. These phenotypes may be associated with different pathophysiological mechanisms produced by a cortical-subcortical network involving even non-dopaminergic areas traditionally not directly related to PD.