Publications by authors named "R Lis"
Detailed evaluation of prostate cancer glands is an essential yet labor-intensive step in grading prostate cancer. Gland segmentation can serve as a valuable preliminary step for machine-learning-based downstream tasks, such as Gleason grading, patient classification, cancer biomarker building, and survival analysis. Despite its importance, there is currently a lack of a reliable gland segmentation model for prostate cancer.
View Article and Find Full Text PDFMice with lymphatic dysfunction develop pathogenic lung tertiary lymphoid organs that model an autoimmune emphysema phenotype of COPD.
Am J Physiol Lung Cell Mol Physiol
January 2025
Article Synopsis
- Researchers observed that mice lacking a protein called CLEC2, which affects lymphatic function, develop lung issues similar to emphysema in COPD due to the formation of tertiary lymphoid organs (TLOs).
- Blocking the formation of these TLOs with an anti-CD20 antibody in these mice partially prevented the progression of emphysema and revealed that TLOs contributed to increased autoantibodies.
- The study also found that chronic exposure to cigarette smoke enlarged TLOs and was linked to more severe lung injury, and similar lymphatic changes were noted in lung tissues from COPD patients with emphysema, suggesting a connection between lymphatic dysfunction and autoimmune responses in lung disease.
Article Synopsis
- Dark fermentation (DF) generates biohydrogen and volatile fatty acids (VFAs) but struggles with slow butyrate consumption.
- This study explores using artificial microalgae-bacteria consortia to enhance butyrate removal rates, demonstrating that certain microalgae growth isn't hindered by bacteria but actually benefits from their presence.
- Findings suggest that coupling DF effluents with microalgal cultivation can improve substrate removal and promote the production of valuable biomass.
The Gleason score is an important predictor of prognosis in prostate cancer. However, its subjective nature can result in over- or under-grading. Our objective was to train an artificial intelligence (AI)-based algorithm to grade prostate cancer in specimens from patients who underwent radical prostatectomy (RP) and to assess the correlation of AI-estimated proportions of different Gleason patterns with biochemical recurrence-free survival (RFS), metastasis-free survival (MFS), and overall survival (OS).
View Article and Find Full Text PDF