Fast and easy immunomagnetic isolation of untouched human naïve T cells in less than 15 minutes
Bibliographic record
Abstract
Abstract Peripheral blood circulating T cells can be subdivided into either antigen experienced effector and memory T cells or naïve T cells that have not yet encountered their cognate antigen. Naïve T cells are valuable tools when studying mechanisms of T cell activation and are required for foundational research into infectious diseases, cancer and transplantation. We describe here a simple immunomagnetic cell isolation protocol for the isolation of untouched human naïve T cells from fresh or previously frozen PBMC or leukapheresis samples. The column-free, negative selection procedure involves labelling and removing unwanted cells using bispecific antibody complexes that crosslink cell surface antigens to magnetic particles. The labelling cocktail is composed of antibodies that target non-T cells, memory T cells, and an optional cocktail for depleting gamma delta T cells. Briefly, the procedure involves a five minute incubation with the antibody cocktail followed by the addition of magnetic particles and two three minute magnetic separations in a hand-held EasySep™ magnet. Following the second magnetic separation, the untouched naïve T cells are simply poured off into a new tube and are ready for use. We define naïve T cells phenotypically as CD3+CD45RA+CD45RO-CD197+. Starting from fresh PBMC, we were able to obtain purities of 96.1 ± 2.3% (mean ± SD, n=14) and recoveries of 62.6% ± 24.5% (mean ± SD, n=14). Additionally, isolated naïve T cells are functional and respond by upregulating the expression of CD25 and CD69 upon stimulation. Our EasySep™ Human Naïve Pan T Cell Isolation Kit offers a fast and easy isolation method for naïve T cells that is suitable for downstream applications such as flow cytometry, cell culture or DNA/RNA extraction.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.004 |
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".