Nickel allergy is associated with a broad spectrum cytokine response
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
BACKGROUND: Nickel-induced proliferation or cytokine release by peripheral blood mononuclear cells may be used for in vitro diagnosis of nickel allergy. OBJECTIVES: Aim of this study was to explore the nickel-specific cytokine profile to further elucidate the pathogenesis of nickel allergic contact dermatitis (ACD) and to identify potential new biomarkers for nickel ACD. METHODS: Peripheral blood mononuclear cells from patients and controls were cultured with T-cell skewing cytokine cocktails and/or nickel. Cytokine and chemokine concentrations were assessed in culture supernatants using validated multiplex assays. Specific cytokine production was related to history of nickel allergy and patch-test results. RESULTS: Twenty-one of the 33 analytes included in the analysis were associated with nickel allergy and included type1 (TNF-α, IFN-γ, TNF-β), type 2 (IL-3, IL-4, IL-5, IL-13), type 1/2 (IL-2, IL-10), type 9 (IL-9), type 17/1 (IL-17A[F], GM-CSF, IL-21) and type 22 (IL-22) derived cytokines as well as the T-cell/antigen presentation cell derived factors Thymus and activation regulated chemokine (TARC), IL-27 and IP-10. Receiver operator characteristics (ROC) analysis showed that IL-5 was the strongest biomarker for nickel allergy. CONCLUSIONS: A broad spectrum of 33 cytokines and chemokines is involved in the allergen-specific immune response in nickel allergic patients. IL-5 remains, next to the lymphocyte proliferation test, the strongest biomarker for nickel allergy.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 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 it