Publications by authors named "L Y Xing"

Objective: To investigate the association between the cumulative exposure to triglyceride-glucose index (cumTyG index) and fragility fractures in the general population.

Methods: This prospective cohort study analyzed active and retired employees of Kailuan Group who participated in three consecutive health examinations in 2006, 2008 and 2010, and were followed up until 31st December 2022. The cohort comprised 55,824 participants who met the inclusion and exclusion criteria and were grouped using the cumTyG index quartiles.

View Article and Find Full Text PDF

Background And Purpose: Radiation therapy (RT) is highly effective, but its success depends on accurate, manual target delineation, which is time-consuming, labor-intensive, and prone to variability. Despite AI advancements in auto-contouring normal tissues, accurate RT target volume delineation remains challenging. This study presents Radformer, a novel visual language model that integrates text-rich clinical data with medical imaging for accurate automated RT target volume delineation.

View Article and Find Full Text PDF

Exosomes play a role in cell communication by transporting content between cells. Here, we tested whether renal podocyte-derived exosomes affect the injury of glomerular endothelial cells in lupus nephritis (LN). We found that exosomes containing high levels of high mobility group box 1 (HMGB1) were released from podocytes in patients with LN, BALB/c mice injected with pristane (which induces lupus-like disease in mice), and cultured human renal glomerular endothelial cells (HRGECs) treated with LN plasma.

View Article and Find Full Text PDF

Background Detection and segmentation of lung tumors on CT scans are critical for monitoring cancer progression, evaluating treatment responses, and planning radiation therapy; however, manual delineation is labor-intensive and subject to physician variability. Purpose To develop and evaluate an ensemble deep learning model for automating identification and segmentation of lung tumors on CT scans. Materials and Methods A retrospective study was conducted between July 2019 and November 2024 using a large dataset of CT simulation scans and clinical lung tumor segmentations from radiotherapy plans.

View Article and Find Full Text PDF

Objective: Patients with hematological malignancies have an elevated risk of developing pneumonia after contracting COVID-19. Lymphoma is the most prevalent hematologic malignancy. It is critical to identify patients at high risk of contracting COVID-19-associated pneumonia.

View Article and Find Full Text PDF