A rapid and efficient method for the isolation of distinct human regulatory T cell populations using combinations of antibody mediated buoyant density centrifugation and/or column-free immunomagnetic cell separation (143.41)
Bibliographic record
Abstract
Abstract Regulatory T cells (Tregs) are a specialized subset of T cells that play a key role in immune regulation. Harnessing the suppressive function of Tregs is a major area of interest as they hold great potential for the treatment of autoimmune disorders. The first step towards quality Treg research is the isolation of highly purified, functional Tregs. With unique cell isolation platforms, STEMCELL has developed a full range of products for the rapid and efficient isolation of highly functional Tregs from virtually any peripheral blood sample. RosetteSep is an antibody mediated buoyant density centrifugation method used to isolate unlabelled cells specifically from whole blood or buffy coat samples. EasySep is an immunomagnetic cell separation method used to isolate cells from fresh or previously frozen PBMCs. Treg pre-enrichment is achieved by antibody mediated crosslinking of unwanted cells to either red blood cells (RosetteSep) or magnetic particles (EasySep) allowing their removal by Ficoll centrifugation or magnetic separation, respectively. RosetteSep or EasySep pre-enriched Treg populations consist of CD4+, CD4+CD127low or CD4+CD127lowCD49d- T cells. Pre-enriched Tregs can be further purified using EasySep positive selection to isolate Tregs expressing high levels of cell surface CD25. Purities of 85% +/- 10% CD4+CD25highFOXP3+ human Tregs can be achieved depending on the Treg population. From start to finish, Treg isolations can be completed in less than 3 hours.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".