Pericarotid Fat as a Marker of Cerebrovascular Risk.

Vascular inflammation is widely recognized as an important factor in the atherosclerotic process, particularly in terms of plaque development and progression. Conventional tests, such as measuring circulating inflammatory biomarkers, lack the precision to identify specific areas of vascular inflammation. In this context, noninvasive imaging modalities can detect perivascular fat changes, serving as a marker of vascular inflammation.

The pharmacological blockade of P2X4 receptor as a viable approach to manage visceral pain in a rat model of colitis.

Nowadays, the pharmacological management of visceral hypersensitivity associated with colitis is ineffective. In this context, targeting purinergic P2X4 receptor (P2X4R), which can modulate visceral pain transmission, could represent a promising therapeutic strategy. Herein, we tested the pain-relieving effect of two novel and selective P2X4R antagonists (NC-2600 and NP-1815-PX) in a murine model of DNBS-induced colitis and investigated the mechanisms underlying their effect.

Structural Brain MR Imaging Alterations in Patients with Systemic Lupus Erythematosus with and without Neuropsychiatric Events.

Background And Purpose: Systemic lupus erythematosus is a complex autoimmune disease known for its diverse clinical manifestations, including neuropsychiatric systemic lupus erythematosus, which impacts a patient's quality of life. Our aim was to explore the relationships among brain MR imaging morphometric findings, neuropsychiatric events, and laboratory values in patients with systemic lupus erythematosus, shedding light on potential volumetric biomarkers and diagnostic indicators for neuropsychiatric systemic lupus erythematosus.

Materials And Methods: Twenty-seven patients with systemic lupus erythematosus (14 with neuropsychiatric systemic lupus erythematosus, 13 with systemic lupus erythematosus), 24 women and 3 men (average age, 43 years, ranging from 21 to 62 years) were included in this cross-sectional study, along with 10 neuropsychiatric patients as controls.

Artificial Intelligence in the Differential Diagnosis of Cardiomyopathy Phenotypes.

Artificial intelligence (AI) is rapidly being applied to the medical field, especially in the cardiovascular domain. AI approaches have demonstrated their applicability in the detection, diagnosis, and management of several cardiovascular diseases, enhancing disease stratification and typing. Cardiomyopathies are a leading cause of heart failure and life-threatening ventricular arrhythmias.