The engagement of B cells with surface-tethered antigens triggers the formation of an immune synapse (IS), where the local secretion of lysosomes can facilitate antigen uptake. Lysosomes intersect with other intracellular processes, such as Toll-like Receptor (TLR) signaling and autophagy coordinating immune responses. However, the crosstalk between these processes and antigen presentation remains unclear. Here, we show that TLR stimulation induces autophagy in B cells and decreases their capacity to extract and present immobilized antigens. We reveal that TLR stimulation restricts lysosome repositioning to the IS by triggering autophagy-dependent degradation of GEF-H1, a Rho GTP exchange factor required for stable lysosome recruitment at the synaptic membrane. GEF-H1 degradation is not observed in B cells that lack αV integrins and are deficient in TLR-induced autophagy. Accordingly, these cells show efficient antigen extraction in the presence of TLR stimulation, confirming the role of TLR-induced autophagy in limiting antigen extraction. Overall, our results suggest that resources associated with autophagy regulate TLR and BCR-dependent functions, which can finetune antigen uptake by B cells. This work helps to understand the mechanisms by which B cells are activated by surface-tethered antigens in contexts of subjacent inflammation before antigen recognition, such as sepsis.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9741325 | PMC |
http://dx.doi.org/10.3390/cells11233883 | DOI Listing |
ACS Sens
January 2025
Department of Engineering Physics, McMaster University, 1280 Main Street West, L8S 4L8 Hamilton, Ontario, Canada.
Current approaches for classifying biosensor data in diagnostics rely on fixed decision thresholds based on receiver operating characteristic (ROC) curves, which can be limited in accuracy for complex and variable signals. To address these limitations, we developed a framework that facilitates the application of machine learning (ML) to diagnostic data for the binary classification of clinical samples, when using real-time electrochemical measurements. The framework was applied to a real-time multimeric aptamer assay (RT-MAp) that captures single-frequency (12.
View Article and Find Full Text PDFInt J Gynaecol Obstet
January 2025
Center for Reproductive Medicine, The First Affiliated Hospital of Jinzhou Medical University, Jinzhou, Liaoning, China.
Objective: Polycystic ovary syndrome (PCOS) is a diverse condition with an unknown cause. The precise mechanism underlying ovulatory abnormalities in PCOS remains unclear. It is widely believed that malfunction of granulosa cells is the primary factor contributing to aberrant follicular formation in PCOS.
View Article and Find Full Text PDFEur J Nucl Med Mol Imaging
January 2025
Department of Nuclear Medicine, Xiangya Hospital, Central South University, No. 87 Xiangya Road, Changsha, Hunan, 410008, P.R. China.
Purpose: To develop and validate a prostate-specific membrane antigen (PSMA) PET/CT based multimodal deep learning model for predicting pathological lymph node invasion (LNI) in prostate cancer (PCa) patients identified as candidates for extended pelvic lymph node dissection (ePLND) by preoperative nomograms.
Methods: [Ga]Ga-PSMA-617 PET/CT scan of 116 eligible PCa patients (82 in the training cohort and 34 in the test cohort) who underwent radical prostatectomy with ePLND were analyzed in our study. The Med3D deep learning network was utilized to extract discriminative features from the entire prostate volume of interest on the PET/CT images.
Sci Rep
January 2025
Department of Oncology, The First Affiliated Hospital of Yangtze University, Jingzhou, Hubei, China.
Exploring the potential of advanced artificial intelligence technology in predicting microsatellite instability (MSI) and Ki-67 expression of endometrial cancer (EC) is highly significant. This study aimed to develop a novel hybrid radiomics approach integrating multiparametric magnetic resonance imaging (MRI), deep learning, and multichannel image analysis for predicting MSI and Ki-67 status. A retrospective study included 156 EC patients who were subsequently categorized into MSI and Ki-67 groups.
View Article and Find Full Text PDFLab Anim
January 2025
Department of Physiology, Faculty of Medicine, University of Colombo, Sri Lanka.
The immunogenicity of rabies vaccines is commonly measured by serological testing, which includes measuring rabies virus-neutralising antibody titre levels in the serum. Apart from humoral immunity, cellular immunity measurements are also helpful in assessing the immunogenicity and efficacy of rabies vaccinations. Recently, there has been an increased emphasis on cellular immunity measurements against rabies in humans and animals.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!