AIMC Topic: B-Lymphocytes
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Artificial intelligence and deep learning to map immune cell types in inflamed human tissue.
Journal of immunological methods
Feb 4, 2022
Biopsies of inflammatory tissue contain a complex network of interacting cells, orchestrating the immune or autoimmune response. While standard histological examination can identify relationships, it is clear that a great amount of data on each slide...
Single B cell technologies for monoclonal antibody discovery.
Trends in immunology
Nov 4, 2021
Monoclonal antibodies (mAbs) are often selected from antigen-specific single B cells derived from different hosts, which are notably short-lived in ex vivo culture conditions and hence, arduous to interrogate. The development of several new technique...
Pseudocell Tracer-A method for inferring dynamic trajectories using scRNAseq and its application to B cells undergoing immunoglobulin class switch recombination.
PLoS computational biology
May 3, 2021
Single cell RNA sequencing (scRNAseq) can be used to infer a temporal ordering of cellular states. Current methods for the inference of cellular trajectories rely on unbiased dimensionality reduction techniques. However, such biologically agnostic or...
Interleukin-4
Immunoglobulin G
Computer Simulation
Animals
Neural Networks, Computer
Immunoglobulin Class Switching
NF-kappa B p50 Subunit
STAT6 Transcription Factor
B-Lymphocytes
Supervised Machine Learning
Databases, Nucleic Acid
Computational Biology
Recombination, Genetic
Single-Cell Analysis
Mice, Inbred C57BL
Signal Transduction
RNA-Seq
Basic-Leucine Zipper Transcription Factors
Models, Immunological
Gene Expression
Mice
Receptors, Cytokine
Machine learning-assisted immune profiling stratifies peri-implantitis patients with unique microbial colonization and clinical outcomes.
Theranostics
May 3, 2021
The endemic of peri-implantitis affects over 25% of dental implants. Current treatment depends on empirical patient and site-based stratifications and lacks a consistent risk grading system. We investigated a unique cohort of peri-implantitis patie...
Machine Learning Analysis of Naïve B-Cell Receptor Repertoires Stratifies Celiac Disease Patients and Controls.
Frontiers in immunology
Mar 10, 2021
Celiac disease (CeD) is a common autoimmune disorder caused by an abnormal immune response to dietary gluten proteins. The disease has high heritability. HLA is the major susceptibility factor, and the HLA effect is mediated via presentation of deami...
Machine Learning to Quantify Humoral Selection in Human Lupus Tubulointerstitial Inflammation.
Frontiers in immunology
Nov 27, 2020
In human lupus nephritis, tubulointerstitial inflammation (TII) is associated with expansion of B cells expressing anti-vimentin antibodies (AVAs). The mechanism by which AVAs are selected is unclear. Herein, we demonstrate that AVA somatic hypermut...
Identification and Staging of B-Cell Acute Lymphoblastic Leukemia Using Quantitative Phase Imaging and Machine Learning.
ACS sensors
Oct 14, 2020
Identification and classification of leukemia cells in a rapid and label-free fashion is clinically challenging and thus presents a prime arena for implementing new diagnostic tools. Quantitative phase imaging, which maps optical path length delays i...
On Its Way to Primetime: Artificial Intelligence in Flow Cytometry Diagnostics.
Cytometry. Part A : the journal of the International Society for Analytical Cytology
Jul 28, 2020
Hematologist-Level Classification of Mature B-Cell Neoplasm Using Deep Learning on Multiparameter Flow Cytometry Data.
Cytometry. Part A : the journal of the International Society for Analytical Cytology
Jun 9, 2020
The wealth of information captured by multiparameter flow cytometry (MFC) can be analyzed by recent methods of computer vision when represented as a single image file. We therefore transformed MFC raw data into a multicolor 2D image by a self-organiz...
Discriminant analysis and machine learning approach for evaluating and improving the performance of immunohistochemical algorithms for COO classification of DLBCL.
Journal of translational medicine
Jun 11, 2019
BACKGROUND: Diffuse large B-cell lymphoma (DLBCL) is classified into germinal center-like (GCB) and non-germinal center-like (non-GCB) cell-of-origin groups, entities driven by different oncogenic pathways with different clinical outcomes. DLBCL clas...
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