J Med Imaging Radiat Oncol
January 2025
Background: Pelvic Congestion Syndrome (PCS) is a condition characterised by chronic pelvic pain resulting from the dilation and reflux of veins within the pelvis. While pelvic pain is the primary symptom of PCS, other associated symptoms may vary among individuals. Bladder symptoms have been commonly observed in PCS, including increased urination frequency, urinary urgency, nocturia and rarely haematuria.
View Article and Find Full Text PDFClinical swallow examination (CSE) following laryngectomy (± pharyngeal resection) remains a critical step in dysphagia evaluation. Whilst the core components of a standard CSE service a broad spectrum of patient populations, no evidence exists examining the essential assessment items specific to CSE in the laryngectomy population. The aim of this study was to identify the tasks, measures and observations considered necessary to include in a CSE post laryngectomy.
View Article and Find Full Text PDFMaturation of conventional dendritic cells (cDCs) is crucial for maintaining tolerogenic safeguards against auto-immunity and for promoting immunogenic responses to pathogens and cancer. The subcellular mechanism for cDC maturation remains poorly defined. We show that cDCs mature by leveraging an internal reservoir of cholesterol (harnessed from extracellular cell debris and generated by de novo synthesis) to assemble lipid nanodomains on cell surfaces of maturing cDCs, enhance expression of maturation markers and stabilize immune receptor signaling.
View Article and Find Full Text PDFAims: To describe the 12-month effectiveness, persistence, tolerability, and safety of ofatumumab (OMB), a highly effective disease-modifying therapy (DMT) for relapsing multiple sclerosis (MS), in a real-world MS population.
Patients & Methods: Electronic medical records of patients starting OMB from October 2020 to August 2022 at two comprehensive MS centers were reviewed. Demographics and disease characteristics and 6- and 12-month clinical, patient-reported, and radiologic outcome measures were analyzed.
Machine learning (ML) models now play a crucial role in predicting properties essential to drug development, such as a drug's logscale acid-dissociation constant (p). Despite recent architectural advances, these models often generalize poorly to novel compounds due to a scarcity of ground-truth data. Further, these models lack interpretability.
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