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Biology subjects

Pei, B.

Publications and source records attributed to Pei, B..

2 recordsLinked to original sources

A Germinal Center Checkpoint of AIRE in B Cells LimitsAntibody Diversification

In response to antigens, B cells undergo antibody diversification, including affinity maturation and class switching, mediated by activation-induced cytidine deaminase (AID) in secondary lymphoid organs, but uncontrolled AID activity can precipitate autoimmunity and cancer. The regulation of antibody diversification is of fundamental importance, though the mechanisms underlying these pathways are not well understood. We found that autoimmune regulator (AIRE), the molecule essential for T cell tolerance, is expressed in germinal center (GC) B cells in a CD40-dependent manner, interacts with AID and negatively regulates antibody affinity maturation and class switching by inhibiting AID function. AIRE deficiency in B cells caused altered antibody repertoire, increased somatic hypermutations, elevated autoantibodies to T helper 17 effector cytokines and defective control of skin Candida albicans. These results define a GC B cell checkpoint of humoral immunity and illuminate new approaches of generating high-affinity neutralizing antibodies for immunotherapy.

immunology↗

AN ARTIFICIAL INTELLIGENCE FOR RAPID IN-LINE LABEL-FREE HUMAN PLURIPOTENT STEM CELL COUNTING AND QUALITY ASSESSMENT

The current state-of-the-art in hPSC culture is a bespoke and user-dependent process limiting the scale and complexity of the experiments performed and introducing operator-to-operator and day-to-day variation. Artificial intelligence (AI) offers the speed and flexibility to bridge the gap between a human-dependent process and industrial-scale automation. We evaluated an AI approach for counting exact cell numbers of undifferentiated human induced pluripotent stem cells in brightfield images for automating hPSC culture. The neural network generates a topological density map for accurate cell counts. We found that the image-based AI algorithm can determine a precise number of hPSCs and is superior to fluorescence-labeled object detection; the algorithm can ignore well edges, meniscus effects, and dust, achieving an average error of 5.6%. We have built a prototype capable of making a go/no go decision for stem cell passaging to perform 26,400 individual well-level counts from 422,400 images in 12 hours at low cost.

cell biology↗