Purpose Of Review: Although glomerular cell apoptosis may be detrimental in acute and chronic inflammation, it is also a key component of the reparative glomerular remodelling that can follow injury. All glomerular cells are vulnerable to apoptosis although there are often differences in the nature of the initiating stimulus and the factors that are protective. The purpose of this review is to outline how modulation of this process may inhibit glomerular injury and promote tissue repair.
Recent Findings: In-vitro studies are providing more information on the factors that regulate apoptosis in individual glomerular cell types. It has now become apparent that growth factors such as vascular endothelial growth factor may have protective actions on several cell types and this may facilitate future treatments that promote the survival of multiple cell types within injured glomeruli. Work in this field has also emphasized that many current treatment strategies may exert a beneficial impact upon renal cell death.
Summary: Although the advent of various antiapoptotic agents such as caspase inhibitors and recombinant growth factors does provide future opportunities to modulate apoptosis for therapeutic gain in patients with glomerulonephritis, there is still some way to go before such reagents are used to treat human disease. However, there is scope for optimism that such treatments will reach the clinic in due course.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1097/01.mnh.0000172728.82993.4e | DOI Listing |
Arch Pathol Lab Med
January 2025
the Department of Pathology, Keck School of Medicine, University of Southern California, Los Angeles (Petersen, Stuart, He, Ju, Ghezavati, Siddiqi, Wang).
Context.—: The co-occurrence of plasma cell neoplasm (PCN) and lymphoplasmacytic lymphoma (LPL) is rare, and their clonal relationship remains unclear.
Objective.
Brief Bioinform
November 2024
State Key Laboratory of Digital Medical Engineering, School of Biological Science and Medical Engineering, Southeast University, 2 Sipailou, Xuanwu District, Nanjing 210096, China.
Spatial transcriptomics technologies have been extensively applied in biological research, enabling the study of transcriptome while preserving the spatial context of tissues. Paired with spatial transcriptomics data, platforms often provide histology and (or) chromatin images, which capture cellular morphology and chromatin organization. Additionally, single-cell RNA sequencing (scRNA-seq) data from matching tissues often accompany spatial data, offering a transcriptome-wide gene expression profile of individual cells.
View Article and Find Full Text PDFBrief Bioinform
November 2024
School of Electrical Engineering and Computer Science, Gwangju Institute of Science and Technology (GIST), Buk-gu, Gwangju 61005, Republic of Korea.
Combination therapies have emerged as a promising approach for treating complex diseases, particularly cancer. However, predicting the efficacy and safety profiles of these therapies remains a significant challenge, primarily because of the complex interactions among drugs and their wide-ranging effects. To address this issue, we introduce DD-PRiSM (Decomposition of Drug-Pair Response into Synergy and Monotherapy effect), a deep-learning pipeline that predicts the effects of combination therapy.
View Article and Find Full Text PDFBrief Bioinform
November 2024
College of Computer Science and Electronic Engineering, Hunan University, Changsha 410082, China.
The role of cell-cell communications (CCCs) is increasingly recognized as being important to differentiation, invasion, metastasis, and drug resistance in tumoral tissues. Developing CCC inference methods using traditional experimental methods are time-consuming, labor-intensive, cannot handle large amounts of data. To facilitate inference of CCCs, we proposed a computational framework, called CellMsg, which involves two primary steps: identifying ligand-receptor interactions (LRIs) and measuring the strength of LRIs-mediated CCCs.
View Article and Find Full Text PDFBrief Bioinform
November 2024
School of Computer Science and Technology, Harbin Institute of Technology, HIT Campus, Shenzhen University Town, Nanshan District, Shenzhen 518055, Guangdong, China.
Antimicrobial peptides (AMPs) emerge as a type of promising therapeutic compounds that exhibit broad spectrum antimicrobial activity with high specificity and good tolerability. Natural AMPs usually need further rational design for improving antimicrobial activity and decreasing toxicity to human cells. Although several algorithms have been developed to optimize AMPs with desired properties, they explored the variations of AMPs in a discrete amino acid sequence space, usually suffering from low efficiency, lack diversity, and local optimum.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!