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Gastrointestinal lesions of eosinophilic granulomatosis with polyangiitis: a prediction model and clinical patterns.
Arthritis Res Ther
January 2025
Department of Rheumatology and Clinical Immunology, Peking Union Medical College Hospital, the Ministry of Education Key Laboratory, Chinese Academy of Medical Sciences & Peking Union Medical College, National Clinical Research Center for Dermatologic and Immunologic Diseases, Beijing, China.
Objective: Severe gastrointestinal lesions are associated with a poor prognosis in eosinophilic granulomatosis with polyangiitis (EGPA). The goal of this study was to develop an effective predictive model for gastrointestinal lesions and to examine clinical patterns, associated factors, treatment, and outcomes of gastrointestinal lesions in EGPA.
Methods: We retrospectively enrolled 165 EGPA patients.
Machine Learning-Based Estimation of Hoarseness Severity Using Acoustic Signals Recorded During High-Speed Videoendoscopy.
J Voice
January 2025
Division of Phoniatrics and Pediatric Audiology at the Department of Otorhinolaryngology, Head and Neck Surgery, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, 91054 Erlangen, Germany.
Objectives: This study investigates the use of sustained phonations recorded during high-speed videoendoscopy (HSV) for machine learning-based assessment of hoarseness severity (H). The performance of this approach is compared with conventional recordings obtained during voice therapy to evaluate key differences and limitations of HSV-derived acoustic recordings.
Methods: A database of 617 voice recordings with a duration of 250 ms was gathered during HSV examination (HS).
Exploring the potential of machine learning models to predict nasal measurements through facial landmarks.
J Prosthet Dent
January 2025
Professor and Chairman, Department of Prosthodontics, School of Dental Medicine, University of Pittsburgh, Pittsburgh, PA, United States. Electronic address:
Statement Of Problem: Information on predicting the measurements of the nose from selected facial landmarks to assist in maxillofacial prosthodontics is lacking.
Purpose: The objective of this study was to identify the efficiency of machine learning models in predicting the length and width of the nose from selected facial landmarks.
Material And Methods: Two-dimensional frontal and lateral photographs were made of 100 men and 100 women.
Stability of expansion effects following Miniscrew-assisted Rapid Palatal expansion: a prospective longitudinal cohort study.
Oral Maxillofac Surg
January 2025
Department of Orthodontics and Craniofacial Biology, Radboud Institute for Health Sciences, Radboud University Medical Center, Nijmegen, The Netherlands.
Purpose: This study aimed to evaluate the dental and skeletal stability one year after Miniscrew-Assisted Rapid Palatal Expansion (MARPE) by using 3D image data.
Methods: Patients with transverse maxillary deficiency from the age of 16 onwards were enrolled consecutively in this prospective longitudinal cohort study. The MARPE appliance was digitally and individually designed and fabricated.
Predicting airway immune responses and protection from immune parameters in blood following immunization in a pig influenza model.
Front Immunol
January 2025
Nuffield Department of Medicine, Pandemic Sciences Institute, University of Oxford, Oxford, United Kingdom.
Whereas the intranasally delivered influenza vaccines used in children affect transmission of influenza virus in the community as well as reducing illness, inactivated influenza vaccines administered by intramuscular injection do not prevent transmission and have a variable, sometimes low rate of vaccine effectiveness. Although mucosally administered vaccines have the potential to induce more protective immune response at the site of viral infection, quantitating such immune responses in large scale clinical trials and developing correlates of protection is challenging. Here we show that by using mathematical models immune responses measured in the blood after delivery of vaccine to the lungs by aerosol can predict immune responses in the respiratory tract in pigs.
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