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We describe a multi-step high-dimensional (HD) flow cytometry workflow for the deep phenotypic characterization of T cells infiltrating metastatic tumor lesions in the liver, particularly derived from colorectal cancer (CRC-LM). First, we applied a novel flow cytometer setting approach based on single positive cells rather than fluorescent beads, resulting in optimal sensitivity when compared with previously published protocols. Second, we set up a 26-color based antibody panel designed to assess the functional state of both conventional T-cell subsets and unconventional invariant natural killer T, mucosal associated invariant T, and gamma delta T (γδT)-cell populations, which are abundant in the liver. Third, the dissociation of the CRC-LM samples was accurately tuned to preserve both the viability and antigenic integrity of the stained cells. This combined procedure permitted the optimal capturing of the phenotypic complexity of T cells infiltrating CRC-LM. Hence, this study provides a robust tool for high-dimensional flow cytometry analysis of complex T-cell populations, which could be adapted to characterize other relevant pathological tissues.
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http://dx.doi.org/10.26508/lsa.202101316 | DOI Listing |
Am J Physiol Cell Physiol
September 2025
Department of Cancer Biology, Wake Forest University School of Medicine, Winston-Salem, NC.
Cachexia, the loss of skeletal muscle mass and function with cancer, contributes to reduced life quality and worsened survival. Skeletal muscle fibrosis leads to disproportionate muscle weakness; however, the role of infiltrating immune cells and fibro-adipogenic progenitors (FAPs) in cancer-induced muscle fibrosis is not well understood. Using the C26 model of cancer cachexia, we sought to examine the changes to skeletal muscle immune cells and FAPs which contribute to excessive extracellular matrix (ECM) collagen deposition.
View Article and Find Full Text PDFJCI Insight
September 2025
Arthur D. Riggs Diabetes and Metabolism Research Institute, The Beckman Research Institute, and.
Steroid-refractory gut acute graft-versus-host disease (SR-Gut-aGVHD) is the major cause of nonrelapse death after allogeneic hematopoietic cell transplantation. High numbers of donor-type IL-22+ T cells, IL-22-dependent dysbiosis, and loss of antiinflammatory CX3CR1hi mononuclear phagocytes (MNPs) play critical roles in SR-Gut-aGVHD pathogenesis. CEACAM1 on intestinal epithelial cells (IECs) is proposed to regulate bacterial translocation and subsequent immune responses in the intestine.
View Article and Find Full Text PDFJCI Insight
September 2025
Department of Immunology, Tufts University School of Medicine, Boston, United States of America.
Recent findings suggest that the small intestine (SI) is a novel site for B cell lymphopoiesis during fetal and neonatal life. However, the unique and/or conserved features that enable B cell development at this site remain unclear. To investigate the molecular and cellular scaffolds for B cell lymphopoiesis in mouse and human fetal intestines we leveraged single-cell RNA sequencing, in situ immunofluorescence, spatial transcriptomics and high-dimensional spectral flow cytometry.
View Article and Find Full Text PDFEur Heart J
August 2025
Department of Internal Medicine I, University Hospital of Augsburg, University Augsburg, Germany.
Background And Aims: Reticulated platelets (RPs), hyperreactive and RNA-rich, are associated with increased risk of cardiovascular events and suboptimal response to antiplatelet therapy in coronary artery disease (CAD). However, the underlying mechanisms remain poorly defined. This study aimed to characterise the molecular and functional phenotype of RPs in CAD and assess their potential as therapeutic targets.
View Article and Find Full Text PDFSensors (Basel)
August 2025
School of Innovation, Design and Engineering, Mälardalen University, 722 20 Västerås, Sweden.
In cyber-physical systems governed by nonlinear partial differential equations (PDEs), real-time control is often limited by sparse sensor data and high-dimensional system dynamics. Deep reinforcement learning (DRL) has shown promise for controlling such systems, but training DRL agents directly on full-order simulations is computationally intensive. This paper presents a sensor-driven, non-intrusive reduced-order modeling (NIROM) framework called FAE-CAE-LSTM, which combines convolutional and fully connected autoencoders with a long short-term memory (LSTM) network.
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