Deep Learning-Based Three-Dimensional Analysis Reveals Distinct Patterns of Condylar Remodelling After Orthognathic Surgery in Skeletal Class III Patients.

Objective: This retrospective study aimed to evaluate morphometric changes in mandibular condyles of patients with skeletal Class III malocclusion following two-jaw orthognathic surgery planned using virtual surgical planning (VSP) and analysed with automated three-dimensional (3D) image analysis based on deep-learning techniques.

Materials And Methods: Pre-operative (T1) and 12-18 months post-operative (T2) Cone-Beam Computed Tomography (CBCT) scans of 17 patients (mean age: 24.8 ± 3.

Type 2 inflammation: a Portuguese consensus using Web-Delphi and decision conferencing (INFLAT2-PT).

Objectives: Atopic/allergic diseases impose a growing burden on public health, affecting millions of patients worldwide. The main objective of this study was to develop a national expert consensus on relevant clinical questions related to type 2 inflammation.

Methods: We conducted: a comprehensive literature review with a qualitative analysis to identify the most repeated themes on the overlap of conditions; a modified 3-round Web-Delphi (or e-Delphi); and a final online decision conference.

Correction: Barriers to care for dependent older adults: Brazilian Primary Health Care managers' perspective.

[This corrects the article DOI: 10.1371/journal.pone.

Effects of 12-Week Moderate-Intensity Versus High-Intensity Water-Aerobic Training on Physical Fitness, Cardiovascular Health, and Well-Being in Adults and Older Adults: A Pragmatic Randomized Controlled Trial.

Background And Aims: The current study aimed to compare the effects of 12 weeks of moderate versus high-intensity water aerobics on muscle strength, body composition, lipid profile, blood pressure, and quality of life in both adults and older adults.

Methods: Twenty-one women (65.19 ± 9.

Dual-Energy Integration in Photoresponsive Micro/Nanomotors: From Strategic Design to Biomedical Applications.

Micro/nanomotors (MNMs) are highly versatile small-scale devices capable of converting external energy inputs into active motion. Among the various energy sources, light stands out due to its abundance and ability to provide spatiotemporal control. However, the effectiveness of light-driven motion in complex environments, such as biological tissues or turbid water, is often limited by light scattering and reduced penetration.