Background: Chronic graft-versus-host disease (cGVHD) manifests with characteristics of autoimmune disease with organs attacked by pathogenic helper T cells. Recent studies have highlighted the role of T cells in cGVHD pathogenesis. Due to limited understanding of underlying mechanisms, preventing cGVHD after allogenic hematopoietic cell transplantation (HCT) has become a major challenge.
View Article and Find Full Text PDFBackground: Hemodynamic instability related to renal replacement therapy (HIRRT) is a common complication affecting critically ill patients that require renal replacement therapy (RRT). There is currently no consensus regarding the definition of HIRRT in critically ill patients. In this context, the impacts of HIRRT on clinical outcomes such as mortality or renal recovery in critically ill patients are unclear.
View Article and Find Full Text PDFThe placenta is vital to maternal and child health but often overlooked in pregnancy studies. Addressing the need for a more accessible and cost-effective method of placental assessment, our study introduces a computational tool designed for the analysis of placental photographs. Leveraging images and pathology reports collected from sites in the United States and Uganda over a 12-year period, we developed a cross-modal contrastive learning algorithm consisting of pre-alignment, distillation, and retrieval modules.
View Article and Find Full Text PDFDisrupted hippocampal functions and progressive neuronal loss represent significant challenges in the treatment of Alzheimer's disease (AD). How to achieve the improvement of pathological progression and effective neural regeneration to ameliorate the intracerebral dysfunctional environment and cognitive impairment is the goal of the current AD therapy. We examined the therapeutic potential of clinical-grade human derived dental pulp stem cells (hDPSCs) in cognitive function and neuropathology in AD.
View Article and Find Full Text PDFBackground: Early differentiation between spinal tuberculosis (STB) and acute osteoporotic vertebral compression fracture (OVCF) is crucial for determining the appropriate clinical management and treatment pathway, thereby significantly impacting patient outcomes.
Objective: To evaluate the efficacy of deep learning (DL) models using reconstructed sagittal CT images in the differentiation of early STB from acute OVCF, with the aim of enhancing diagnostic precision, reducing reliance on MRI and biopsies, and minimizing the risks of misdiagnosis.
Methods: Data were collected from 373 patients, with 302 patients recruited from a university-affiliated hospital serving as the training and internal validation sets, and an additional 71 patients from another university-affiliated hospital serving as the external validation set.