Detection of Mycobacterium‐specific interferon‐gamma‐producing human T lymphocytes by flow cytometry
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Flow cytometry has proven to be a useful tool for the investigation of cytokine synthesis by selected cell subpopulations. While most reports have used mitogen stimulation or long-term cultures with antigen, we describe here a novel method to allow the detection of rare mycobacterial antigen-specific cytokine synthesizing cells within one day. The most important feature of this method is the use of an FITC-conjugated isotype-matched control antibody to identify and exclude cells which fluoresce non-specifically. With this technique, we demonstrate interferon-gamma (IFN-gamma) staining in 785 cells per 1 x 10(5) T cells counted, in mycobacterial antigen-stimulated peripheral blood mononuclear cells from a BCG-vaccinated subject. In comparison, only 14 IFN-gamma-staining T cells were seen in the cultures not stimulated by mycobacterial antigen. Less than 10 cells per 1 x 10(5) T cells are stained by an irrelevant control antibody. Specific responses are detectable after 12 h of in vitro culture, and peak at 24 h. In volunteer health care workers, IFN-gamma staining correlated with IFN-gamma production using a published ELISPOT assay (r=0.927). IFN-gamma staining was also higher in PBMC from mantoux skin test-positive volunteers, compared to cells from skin test-negative subjects (p=0.0045). Flow cytometry following short-term culture can thus be used for enumeration of antigen-specific IFN-gamma synthesizing cells.
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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 | 0.000 | 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) | 0.019 | 0.002 |
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 it