A simple and rapid method for the isolation of untouched human memory CD8 T cells (124.9)
Bibliographic record
Abstract
Abstract Memory CD8 T cells are long-lived antigen-specific cells that persist after clearance of infection. Functionally, they are distinguished from naïve CD8 T cells by their less extensive signal requirement for activation and their ability to respond quickly to recall antigens and secrete a broad repertoire of cytokines. In addition, the two populations are phenotypically distinct, with naïve cells expressing CD45RA, and memory cells expressing CD45RO, a marker indicative of previous activation. Current protocols for the isolation of memory CD8 T cells are time-consuming and require the use of columns. We have developed a new kit for easy and rapid isolation of memory CD8 T cells from PBMCs by immunomagnetic, column-free cell separation (EasySep™). Non-CD8 T cells and CD45RA positive CD8 T cell subsets are targeted for depletion by bispecific tetrameric antibody complexes crosslinked to dextran-coated magnetic particles. The labeled cells are separated using an EasySep™ magnet and the desired fraction is poured off. The procedure is performed in 30 minutes and can be fully automated using RoboSep™. The mean enrichment purity and recovery of CD45RO+ CD45RA- CD8+ T cells is 86 ± 4, and 23 ± 11, respectively. The kit provides a simple and efficient means of isolating untouched human memory CD8 T cells that are ideal for studies in signal transduction, activation, cytokine expression, and response to infectious disease.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.007 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".