Column-free isolation of untouched CD4+CD127lowCD49d- human regulatory T cells in 45 minutes (168.4)
Bibliographic record
Abstract
Abstract Regulatory T cells (Tregs) are a subset of lymphocytes that play a key role in maintaining immune homeostasis. The isolation of highly purified Tregs is essential for advancing this exciting field of research. FOXP3 remains the best marker for the identification of Tregs, but its intracellular localization currently precludes its use for the isolation of viable human Tregs. To overcome these technical difficulties, researchers have exploited the expression of other surface markers to isolate Treg populations. Typically, the expression of CD127 inversely correlates with FOXP3 expression, while CD49d, is expressed on the majority of pro-inflammatory effector cells but is absent on Tregs. Removal of CD127high cells from the CD4+ T-cell population enriches for Tregs with high levels of FOXP3 expression. Additional depletion of CD49d expressing cells further removes contaminating IFNγ and IL-17 secreting cells. Together this strategy permits selective isolation of highly enriched Tregs. We have developed a new kit for the negative enrichment of highly purified human Tregs. Our new EasySep™ CD4+CD127lowCD49d- kit isolates untouched Tregs by by column-free magnetic separation in only 45 minutes. Mean CD4+ T-cell purity is 94.3% +/- 5.5% of which 65.5% +/- 11.7% express high levels of FOXP3 (n=7). This new product will add to the array of powerful yet convenient tools available for the isolation of functional highly purified human Tregs.
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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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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".