Detection of Cardiotrophin-like Cytokine Factor 1 (CLCF1) by flow cytometry
Bibliographic record
Abstract
Abstract Cardiotrophin-like Cytokine Factor 1 (CLCF1) belongs to the IL6 family of cytokines and possesses pro-neurotrophic and immuno-modulating functions. Coding mRNA for CLCF1 has been detected in primary and secondary lymphoid organs (i.e. lymph nodes, spleen and bone marrow), as well as in the lungs and feminine reproductive organs. Modulation of CLCF1’s mRNA levels has been associated with the Th17 polarization in CD4+ T cells. However, little information is available regarding CLCF1 protein levels in these tissues or the nature of the immune cells responsible for its production. This can be explained by a lack of in situ detection options for CLCF1. We have therefore developed a methodology for the detection of human and murine CLCF1 by flow cytometry in permeabilized cells. This technique has been validated using derivatives of the Ba/F3 cell line in which cDNAs coding for human and murine CLCF1 were introduced by transduction with recombinant retroviruses. We are currently using this approach to study CLCF1 production by human and murine immune cells. Preliminary results indicate a production of CLCF1 by Th17 T cells. The development of a method to detect CLCF1 by flow cytometry will be beneficial for the study of CLCF1’s functions in the regulation of the immune response.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".