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Not too much, not too little. Titrating flow rate to minimise inspiratory effort during helmet CPAP: A bench study.
Pulmonology
December 2025
Department of Emergency and Intensive Care, Fondazione IRCCS San Gerardo dei tintori, Monza, Italy.
Background: Non-invasive helmet respiratory support is suitable for several clinical conditions. Continuous-flow helmet CPAP systems equipped with HEPA filters have become popular during the recent Coronavirus pandemic. However, HEPA filters generate an overpressure above the set PEEP.
View Article and Find Full Text PDFDental Pulp Stem Cells Attenuate Early Brain Injury After Subarachnoid Hemorrhage via miR-26a-5p/PTEN/AKT Pathway.
Neurochem Res
January 2025
Department of Neurosurgery, Renmin Hospital of Wuhan University, Wuhan, 430060, Hubei, China.
Subarachnoid hemorrhage (SAH) is a type of hemorrhagic stroke with high morbidity, mortality and disability, and early brain injury (EBI) after SAH is crucial for prognosis. Recently, stem cell therapy has garnered significant attention in the treatment of neurological diseases. Compared to other stem cells, dental pulp stem cells (DPSCs) possess several advantages, including abundant sources, absence of ethical concerns, non-invasive procurement, non-tumorigenic history and neuroprotective potential.
View Article and Find Full Text PDFA systematic review on whole-body photobiomodulation for exercise performance and recovery.
Lasers Med Sci
January 2025
Cornell University, Ithaca, USA.
Purpose: Photobiomodulation (PBM) is a non-invasive therapeutic procedure that consists of irradiating a local area of the skin with red and near-infrared lasers or light emitting diodes (LEDs). Local PBM has been studied as a method to improve exercise performance and recovery. This review aims to evaluate the efficacy of whole-body PBM for exercise performance and recovery, comparing its findings to the established effects of localized PBM.
View Article and Find Full Text PDFMultiparametric MRI-based machine learning system of molecular subgroups and prognosis in medulloblastoma.
Eur Radiol
January 2025
Beijing Tiantan Hospital, Capital Medical University, Beijing, China.
Objectives: We aimed to use artificial intelligence to accurately identify molecular subgroups of medulloblastoma (MB), predict clinical outcomes, and incorporate deep learning-based imaging features into the risk stratification.
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An explainable transformer model integrating PET and tabular data for histologic grading and prognosis of follicular lymphoma: a multi-institutional digital biopsy study.
Eur J Nucl Med Mol Imaging
January 2025
Department of Nuclear Medicine, West China Hospital, Sichuan University, No.37, Guoxue Alley, Chengdu City, Sichuan Province, 610041, China.
Background: Pathological grade is a critical determinant of clinical outcomes and decision-making of follicular lymphoma (FL). This study aimed to develop a deep learning model as a digital biopsy for the non-invasive identification of FL grade.
Methods: This study retrospectively included 513 FL patients from five independent hospital centers, randomly divided into training, internal validation, and external validation cohorts.
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