Publications by authors named "S S F Yung"
Prevention of end-stage kidney disease (ESKD) is a major objective in the management of patients with lupus nephritis (LN). Chronic kidney disease (CKD) of variable severity is common in these patients, but recent literature has mostly focused on novel immunosuppressive treatments for acute LN, while the data on CKD is relatively limited. This scoping review aims to summarise available data on the prevalence and risk factors for CKD in patients with LN.
View Article and Find Full Text PDFCancer adhesion to the mesothelium is critical for peritoneal metastasis, but how metastatic cells adapt to the biomechanical microenvironment remains unclear. Our study demonstrates that highly metastatic (HM), but not non-metastatic, ovarian cancer cells selectively activate the peritoneal mesothelium. HM cells exert a stronger adhesive force on mesothelial cells via P-cadherin, an adhesion molecule abundant in late-stage tumors.
View Article and Find Full Text PDFPublic fertility preservation programme for cancer patients in Hong Kong.
Hong Kong Med J
December 2024
Introduction: Fertility preservation (FP) offers cancer patients the opportunity to have biological children after completing treatment. This study was performed to review the experience and changes in service demand since the implementation of a public FP programme for cancer patients in Hong Kong.
Methods: This retrospective study included men and women who attended an assisted reproduction unit for public FP services before cancer treatment from August 2020 to February 2023.
Article Synopsis
- CD44 is a glycoprotein linked to kidney inflammation and fibrosis, specifically studied in a mouse model for lupus nephritis (LN) and in human patients with active LN.
- The research showed that CD44 was absent in healthy kidneys but expressed in kidney cells of LN patients, and treatment with anti-CD44 antibodies improved kidney health in mice by reducing immune cell infiltration and fibrosis markers.
- Serum CD44 levels increased before clinical symptoms of renal flare in patients, effectively distinguishing those with active LN from healthy individuals and other kidney-related conditions.
Article Synopsis
- * This study used a vertebral landmark extraction method and a Feedforward Neural Network (FNN) to predict scoliosis progression in 79 AIS patients, achieving a mean absolute error of 1.5 degrees in intervertebral angle progression and a strong correlation of 0.86 with predicted Cobb angles.
- * The FNN showed high accuracy (0.85) in classifying different Cobb angle ranges, indicating its potential for enhancing tailored treatments, although addressing issues like over-fitting could further improve results.