Category Ranking

98%

Total Visits

921

Avg Visit Duration

2 minutes

Citations

20

Article Abstract

Download full-text PDF

Source
http://dx.doi.org/10.1055/a-2524-5086DOI Listing

Publication Analysis

Top Keywords

[correction differential
4
differential diagnosis
4
diagnosis age-related
4
age-related macular
4
macular degeneration]
4
[correction
1
diagnosis
1
age-related
1
macular
1
degeneration]
1

Similar Publications

The QT interval is a key indicator in assessing arrhythmia risk, evaluating drug safety, and supporting clinical diagnosis in cardiology. The QT interval is significantly influenced by heart rate so it must be accurately corrected to ensure reliable clinical interpretation. Conventional correction formulas, such as Bazett's formula, are widely utilized but often criticized for inaccuracies, either under- or overcorrecting QT intervals in different physiological conditions.

View Article and Find Full Text PDF

CBCT Analysis of Incisor Movement and Alveolar Bone Changes in Class II Malocclusion Treatment with Premolar Extraction using Clear Aligner: A Retrospective Study.

J Dent

September 2025

State Key Laboratory of Oral Diseases & National Clinical Research Center for Oral Diseases; Department of Orthodontics, West China Hospital of Stomatology, Sichuan University, Chengdu, China.. Electronic address:

Objectives: This retrospective study evaluates alveolar bone remodeling patterns and their association with incisor displacement in adults undergoing clear aligner therapy with premolar extractions for Class II malocclusion correction.

Methods: Cone-beam computed tomography (CBCT) scans of 38 maxillary and 37 mandibular incisors were analyzed. Displacement vectors for four anatomical landmarks (cusp tip [C], root apex [R], root neck midpoint [M], labial cementoenamel junction [L]) were quantified.

View Article and Find Full Text PDF

Machine learning-based identification of a transcriptomic blood signature discriminating between systemic autoimmunity and infection.

Med

August 2025

Joint Academic Rheumatology Program, School of Medicine, National and Kapodistrian University of Athens, 11527 Athens, Greece; Centre of New Biotechnologies and Precision Medicine (CNBPM), School of Medicine, National and Kapodistrian University of Athens, 11527 Athens, Greece. Electronic address: p

Background: Pathogenic responses against self and foreign antigens in systemic autoimmunity and infection, respectively, engage similar immunologic components, thus lacking distinguishing diagnostic biomarkers. Herein, we tested whether whole-blood transcriptome analysis discriminates autoimmune from infectious diseases.

Methods: We applied nested cross-validation methodology to tune and validate random forests, k-nearest neighbors, and support vector machines, using a new preprocessing method on 22 publicly available datasets, including 594 patients with a broad spectrum of systemic autoimmune diseases and 615 patients with diverse viral, bacterial, and parasitic infections.

View Article and Find Full Text PDF

FGF9-FGFR2 Signaling via Osteocytes-Preosteoblasts Crosstalks to Mediate Mechanotransduction-Driven Intramembranous Osteogenesis in the Underdeveloped Maxilla.

Adv Sci (Weinh)

September 2025

Department of Orthodontics, Nanjing Stomatological Hospital, Affiliated Hospital of Medical School, Institute of Stomatology, Nanjing University, 30 Zhongyang Road, Nanjing, Jiangsu, 210008, China.

Maxillary underdevelopment is a critical component of skeletal Class III malocclusion, closely linked to altered biomechanical signaling. Mechanical stimulation through early facemask protraction can effectively promote maxillary growth, yet the underlying mechanotransduction mechanisms remain unclear. In this study, fibroblast growth factor 9 (FGF9) is identified as a key biomechanical responder in maxillary development.

View Article and Find Full Text PDF

Background: We sought to investigate the association between circulating inflammatory and cardiovascular proteomics biomarkers and cardiac autonomic nervous dysfunction-sensitive heart rate variability indices.

Methods: Using the population-based KORA (Cooperative Health Research in the Region of Augsburg) cohort, 233 proteomics biomarkers were quantified in baseline plasma samples of 1389 individuals using proximity extension assay technology. Five heart rate variability indices (Rényi entropy of the histogram with order [α] 4, total power of the density spectra, SD of word sequence, SD of the short-term normal-to-normal interval variability, compression entropy) were assessed at baseline in 982 individuals and in 407 individuals at baseline and at 14-year follow-up.

View Article and Find Full Text PDF