[Cerebral hemodynamic disorders in patients with schizophrenia with concomitant metabolic syndrome].

Objective: To identify the differences or comparability of parameters of cerebral hemodynamics between patients with schizophrenia with or without concomitant metabolic syndrome (MS).

Material And Methods: The study included 94 patients with schizophrenia (48 men and 46 women). A control group consisted of 40 mentally and somatically healthy individuals (17 men and 23 women) comparable in sex and age to the main group of patients.

Gene Variants and Their Role in Metabolic Syndrome: A Study of Patients with Schizophrenia.

Metabolic syndrome (MetS) is common among schizophrenia patients, and one of MetS's causes may be an imbalance in nitric oxide regulation. In this study, we examined associations of three polymorphic variants of the nitric oxide synthase 1 adapter protein () gene with MetS in schizophrenia. NOS1AP regulates neuronal nitric oxide synthase, which controls intracellular calcium levels and may influence insulin secretion.

Untargeted Plasma Metabolomic Profiling in Patients with Depressive Disorders: A Preliminary Study.

Depressive disorder is a multifactorial disease that is based on dysfunctions in mental and biological processes. The search for biomarkers can improve its diagnosis, personalize therapy, and lead to a deep understanding of the biochemical processes underlying depression. The purpose of this work was a metabolomic analysis of blood serum to classify patients with depressive disorders and healthy individuals using Compound Discoverer software.

Building Predictive Models for Schizophrenia Diagnosis with Peripheral Inflammatory Biomarkers.

Machine learning and artificial intelligence technologies are known to be a convenient tool for analyzing multi-domain data in precision psychiatry. In the case of schizophrenia, the most commonly used data sources for such purposes are neuroimaging, voice and language patterns, and mobile phone data. Data on peripheral markers can also be useful for building predictive models.