Easy, column-free procedure for the enrichment of human Th1 cells from peripheral blood (P3239)
Bibliographic record
Abstract
Abstract Upon activation naïve T helper (Th) precursor cells are polarized toward various cell subtypes and can be distinguished from each other based on effector function and chemokine expression. Th1 cells regulate cellular immunity via IL-2 plus IFN-γ, activating macrophages, cytotoxic T, NK and B cells in an effort to eliminate intracellular pathogens. Th1 cells preferentially express the chemokine receptors CXCR3 and CCR5 and can be further characterized by intracellular staining for IFN-γ. We have developed a 2-step EasySepTM immunomagnetic column-free method for the enrichment of CD4+CXCR3+ T cells from fresh peripheral blood nucleated cells. First, non-CD4 T cells are targeted for depletion using dextran-coated magnetic particles and a cocktail of antibody complexes. Labeled cells are separated using an EasySepTM magnet, and pre-enriched CD4 T cells are poured off. CXCR3+ cells are then positively selected from the pre-enriched fraction. The procedure can be automated using RoboSepTM. With an initial frequency of 10 ± 3% CD4+CXCR3+ cells, purities of 90 ± 4% (n=12) can be obtained. When stimulated, a high proportion of these cells produce IFN-γ (68 ± 12%) compared with total CD4 T cells and pre-enriched CD4 T cells. Less than 1% of isolated cells produce cytokines associated with other Th cell subtypes (IL-4, IL-17). Enrichment of unstimulated human Th1 cells enables the investigation of chronic inflammation responses and mechanisms of regulation in human models of 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.021 | 0.031 |
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".