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Introduction: Chronic Kidney Disease (CKD) is recognized as a major global public health problem. Dialysis is the mainstay of treatment for patients with end-stage renal disease and can prolong survival in patients with CKD. As patient survival increases, the treatment of complications becomes more important.

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Sedentary lifestyles and prolonged physical inactivity are often linked to poor mental and physical health as well as an increased risk of a number of chronic illnesses, including cancer, obesity, type 2 diabetes, and cardiovascular problems. Metabolic Syndrome (MetS), as the new disease, has emerged as the world's leading cause of illness. Despite having its roots in the West, this issue has now completely globalized due to the development of the Western way of life throughout the world.

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Background: Inadequate glycemic control in patients with type 2 diabetes (T2DM) is a major public health problem and a significant risk factor for the progression of diabetic complications.

Aim: To evaluate the effects of intensive and supportive glycemic management strategies over a 12-month period in individuals with T2DM with glycated hemoglobin (HbA1c) ≥ 10% and varying backgrounds of glycemic control.

Methods: This prospective observational study investigated glycemic control in patients with poorly controlled T2DM over 12 months.

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Background: Surgical treatment of therapy-resistant radiculopathy associated with lumbar herniated discs in patients with extreme obesity is a challenge for neurosurgeons. In addition to technical problems in surgery due to the abundant subcutaneous adipose tissue and perioperative risks, there are significant anesthetic risks when anesthesia is performed with a patient in the prone position. A surgical procedure should preferably be minimally traumatic and quick with minimal risks of complications.

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3T dilated inception network for enhanced autism spectrum disorder diagnosis using resting-state fMRI data.

Cogn Neurodyn

December 2025

Department of Computational Intelligence, School of Computing, SRM Institute of Science and Technology, Kattankulathur, Tamilnadu India.

Autism spectrum disorder (ASD) is one of the complicated neurodevelopmental disorders that impacts the daily functioning and social interactions of individuals. It includes diverse symptoms and severity levels, making it challenging to diagnose and treat efficiently. Various deep learning (DL) based methods have been developed for diagnosing ASD, which rely heavily on behavioral assessment.

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