Heterogeneous blood pressure treatment effects on cognitive decline in type 2 diabetes: A machine learning analysis of a randomized clinical trial.

Aim: We aimed to identify the characteristics of patients with diabetes who can derive cognitive benefits from intensive blood pressure (BP) treatment using machine learning methods.

Materials And Methods: Using data from the Action to Control Cardiovascular Risk in Diabetes Memory in Diabetes (ACCORD-MIND) study, 1349 patients with type 2 diabetes who underwent BP treatment (intensive treatment targeting a systolic BP <120 mmHg vs. standard treatment targeting <140 mmHg) were included in the machine learning analysis.

A new BWO-based RGB vegetation index and ensemble learning strategy for the pests and diseases monitoring of CCB trees using unmanned aerial vehicle.

Introduction: The Cinnamomum Camphora var. Borneol (CCB) tree is a valuable timber species with significant medicinal importance, widely cultivated in mountainous areas but susceptible to pests and diseases, making manual surveillance costly.

Methods: This paper proposes a method for detecting CCB pests and diseases using Unmanned aerial vehicle (UAV) as an advanced data collection carrier, capable of gathering large-scale data.

Endocrine disruptors and bladder function: the role of phthalates in overactive bladder.

Background: Phthalates, widely used as plasticizers, are pervasive environmental contaminants and endocrine disruptors. Their potential role in overactive bladder (OAB) pathogenesis is underexplored, necessitating further investigation into their impact on OAB using large-scale epidemiological data.

Methods: This study utilized data from the National Health and Nutrition Examination Survey (NHANES) spanning from 2011 to 2018.

Depression in middle-aged and older adults with hearing loss: the use and construction of a nomogram tool.

Objective: This study aims to explore the influencing factors of depressive symptoms in middle-aged and older adult patients with hearing loss and to construct a nomogram risk prediction model.

Methods: A total of 2,729 middle-aged and older adult patients with hearing loss from the community were selected as the study subjects. Single-factor and multifactorial stepwise logistic regression analyses were used to screen influencing factors.

Impact of SARS-CoV-2 infection on patients with myasthenia gravis: a retrospective study in a Chinese population.

Background And Purpose: Myasthenia gravis (MG) is characterized by fluctuating muscle weakness due to immune-mediated damage to acetylcholine receptors. Viral infections can exacerbate symptoms of muscle weakness, and the clinical status of patients with MG may influence the outcomes of such infections. Here, we identified factors of symptom exacerbation, severe SARS-CoV-2 infection, and pneumonia in patients with MG who are infected with SARS-CoV-2.