Unlabelled: Complement-mediated hemolytic uremic syndrome (CM-HUS) is a thrombotic microangiopathy characterized by germline variants or acquired antibodies to complement proteins and regulators. Building upon our prior experience with the modified Ham (mHam) assay for ex vivo diagnosis of complementopathies, we have developed an array of cell-based complement "biosensors'' by selective removal of complement regulatory proteins (CD55 and CD59, CD46, or a combination thereof) in an autonomously bioluminescent HEK293 cell line. These biosensors can be used as a sensitive method for diagnosing CM-HUS and monitoring therapeutic complement blockade. Using specific complement pathway inhibitors, this model identifies IgM-driven classical pathway stimulus during both acute disease and in many patients during clinical remission. This provides a potential explanation for ~50% of CM-HUS patients who lack an alternative pathway "driving" variant and suggests at least a subset of CM-HUS is characterized by a breakdown of IgM immunologic tolerance.
Key Points: CM-HUS has a CP stimulus driven by polyreactive IgM, addressing the mystery of why 40% of CM-HUS lack complement specific variantsComplement biosensors and the bioluminescent mHam can be used to aid in diagnosis of CM-HUS and monitor complement inhibitor therapy.
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http://dx.doi.org/10.1101/2024.05.29.596475 | DOI Listing |
Front Psychol
December 2024
Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN, United States.
Introduction: While the fact that visual stimuli synthesized by Artificial Neural Networks (ANN) may evoke emotional reactions is documented, the precise mechanisms that connect the strength and type of such reactions with the ways of how ANNs are used to synthesize visual stimuli are yet to be discovered. Understanding these mechanisms allows for designing methods that synthesize images attenuating or enhancing selected emotional states, which may provide unobtrusive and widely-applicable treatment of mental dysfunctions and disorders.
Methods: The Convolutional Neural Network (CNN), a type of ANN used in computer vision tasks which models the ways humans solve visual tasks, was applied to synthesize ("dream" or "hallucinate") images with no semantic content to maximize activations of neurons in precisely-selected layers in the CNN.
Front Immunol
December 2024
Department of Medical Oncology, The First Hospital of China Medical University, Shenyang, Liaoning, China.
Background: Triple-negative breast cancer (TNBC) is the most aggressive subtype of breast cancer, with the worst prognosis among all subtypes. The impact of distinct cell subpopulations within the tumor microenvironment (TME) on TNBC patient prognosis has yet to be clarified.
Methods: Utilizing single-cell RNA sequencing (scRNA-seq) integrated with bulk RNA sequencing (bulk RNA-seq), we applied Cox regression models to compute hazard ratios, and cross-validated prognostic scoring using a GLMNET-based Cox model.
Front Immunol
December 2024
Division of Rheumatology, University of Washington, Seattle, WA, United States.
Introduction: Neutrophil activation is important in systemic lupus erythematosus (SLE). We previously demonstrated that ribonucleoprotein (RNP) immune complexes (ICs) promoted neutrophil activation in a TLR7/8-dependent manner. However, it remains unclear if this mechanism occurs in patients.
View Article and Find Full Text PDFJ Gen Fam Med
January 2025
Background: Deprescribing is a critical component of clinical practice, especially in geriatric medicine. Nevertheless, the attributes of patients who are prepared for, interested in, and could potentially benefit from deprescribing have not been well examined. The Patient Perceptions of Deprescribing (PPoD) evaluates patients' overall readiness for deprescribing and is complemented by an 11-item validated short form (SF-PPoD).
View Article and Find Full Text PDFJ Extracell Vesicles
January 2025
Cell-Tech HUB and Institute for Research and Biomedical Innovation (IRIB), National Research Council of Italy (CNR), Palermo, Italy.
The application of extracellular vesicles (EVs) as therapeutics or nanocarriers in cell-free therapies necessitates meticulous evaluations of different features, including their identity, bioactivity, batch-to-batch reproducibility, and stability. Given the inherent heterogeneity in EV preparations, this assessment demands sensitive functional assays to provide key quality control metrics, complementing established methods to ensure that EV preparations meet the required functionality and quality standards. Here, we introduce the detectEV assay, an enzymatic-based approach for assessing EV luminal cargo bioactivity and membrane integrity.
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