Metabolic health's central role in chronic kidney disease progression: a 20-year study of obesity-metabolic phenotype transitions.

This study investigates the risk of chronic kidney disease (CKD) across four metabolic phenotypes: Metabolically Healthy-No Obesity (MH-NO), Metabolically Unhealthy-No obesity (MU-NO), Metabolically Healthy-Obesity (MH-O), and Metabolically Unhealthy-Obesity (MU-O). Data from the Tehran Lipid and Glucose Study, collected from 1999 to 2020, were used to categorize participants based on a BMI ≥ 30 kg/m2 and metabolic health status, defined by the presence of three or four of the following components: high blood pressure, elevated triglycerides, low high-density lipoprotein, and high fasting blood sugar. CKD, characterized by a glomerular filtration rate < 60 ml/min/1.72 m2. The hazard ratio (HR) of CKD risk was evaluated using Cox proportional hazard models. The study included 8731 participants, with an average age of 39.93 years, and identified 734 incidents of CKD. After adjusting for covariates, the MU-O group demonstrated the highest risk of CKD progression (HR 1.42-1.87), followed by the MU-NO group (HR 1.33-1.67), and the MH-O group (HR 1.18-1.54). Persistent MU-NO and MU-O posed the highest CKD risk compared to transitional states, highlighting the significance of exposure during early adulthood. These findings emphasize the independent contributions of excess weight and metabolic health, along with its components, to CKD risk. Therefore, preventive strategies should prioritize interventions during early-adulthood.

Advances in Neuro-Oncological Imaging: An Update on Diagnostic Approach to Brain Tumors.

This study delineates the pivotal role of imaging within the field of neurology, emphasizing its significance in the diagnosis, prognostication, and evaluation of treatment responses for central nervous system (CNS) tumors. A comprehensive understanding of both the capabilities and limitations inherent in emerging imaging technologies is imperative for delivering a heightened level of personalized care to individuals with neuro-oncological conditions. Ongoing research in neuro-oncological imaging endeavors to rectify some limitations of radiological modalities, aiming to augment accuracy and efficacy in the management of brain tumors. This review is dedicated to the comparison and critical examination of the latest advancements in diverse imaging modalities employed in neuro-oncology. The objective is to investigate their respective impacts on diagnosis, cancer staging, prognosis, and post-treatment monitoring. By providing a comprehensive analysis of these modalities, this review aims to contribute to the collective knowledge in the field, fostering an informed approach to neuro-oncological care. In conclusion, the outlook for neuro-oncological imaging appears promising, and sustained exploration in this domain is anticipated to yield further breakthroughs, ultimately enhancing outcomes for individuals grappling with CNS tumors.