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Integrase strand transfer inhibitors (INSTIs) have emerged as the first-line choice for treating human immunodeficiency virus (HIV) infection due to their superior efficacy and safety. However, the impact of INSTIs on the development of neuropsychiatric conditions in people living with HIV (PLWH) is not fully understood due to limited data. In this study, we conducted a cross-sectional examination of PLWH receiving antiretroviral therapy, with a specific focus on HIV-positive men who have sex with men (MSM) on INSTI-based regimens (n = 61) and efavirenz (EFV)-based regimens (n = 28).

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Impact of short-term tinnitus treatment on cognitive function and neural synchronization.

Front Neurol

February 2025

Department of Otorhinolaryngology-Head and Neck Surgery, Ewha Womans University School of Medicine, Seoul, Republic of Korea.

We aimed to evaluate the impact of short-term tinnitus treatment on cognitive function and identify the effects of various treatment combinations on cognitive and tinnitus outcomes. A non-randomized prospective study was conducted with 32 tinnitus patients at a tertiary university hospital between May 2022 and May 2024. Patients received treatments, including neuromodulation, diuretics, gabapentin, selective serotonin reuptake inhibitors (SSRI), anxiolytics, muscle relaxants, hearing aids, and counseling.

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Background: Whole exome sequencing (WES) aids in diagnosing monogenic diseases, yet > 50% of all cases remain undiagnosed. We aimed to improve diagnostic precision by developing an effective WES-based strategy for detecting congenital anomalies.

Methods: Initially, 128 probands with congenital anomalies were assessed using trio-WES and copy number variation analysis-variant interpretation was for exons and splice sites.

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This study explores the application of various machine learning (ML) models for the real-time prediction of the FOS/TAC ratio in microbial electrolysis cell anaerobic digestion (MEC-AD) systems using data collected during a 160-day trial treating brewery wastewater. This study investigated models including decision trees, XGBoost, support vector regression, a variant of support vector machine (SVM), and artificial neural networks (ANNs) for their effectiveness in the soft sensing of system stability. The ANNs demonstrated superior performance, achieving an explained variance of 0.

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Background: In many epidemiological HIV studies, patients are frequently monitored over time to predict their survival by examining their CD4 levels repeatedly. This study aims to evaluate factors related to longitudinal CD4 count and the risk of death among HIV-infected patients using Bayesian joint models.

Methods: The information of patients who were infected with HIV in Fars Province, from 2011 to 2016 and followed up until 2022 was used in this study.

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