Cytokine Expression in Unstimulated PBMC of Children with Type 1 Diabetes and Subjects Positive for Diabetes‐Associated Autoantibodies
Bibliographic record
Abstract
The aim of this study was to evaluate possible changes in the circulating levels of interferon (IFN)-gamma, interleukin (IL)-4 and transforming growth factor (TGF)-beta in association with the autoimmune process leading to type 1 diabetes. Expression levels of mRNAs specific for each cytokine were determined in peripheral blood mononuclear cells (PBMC) by a multiplex reverse transcription-polymerase chain reaction (RT-PCR) followed by hybridization reactions with lanthanide-labelled probes and detection by time-resolved fluorometry. Newly diagnosed diabetic children had lower levels of IFN-gamma, IL-4 and TGF-beta 1 signals compared to their age- and sex-matched controls (P < 0.02, P < 0.005 and P < 0.005, respectively) and also the autoantibody-positive subjects had significantly lower levels of IL-4 and TGF-beta 1 in comparison with their matched controls (P = 0.0013 and P = 0.012). No significant differences were observed when comparing matched pairs of diabetic children and autoantibody-positive subjects. Our results suggest a systemic bias towards reduced production of T-helper cell type 2 cytokines (IL-4 and TGF-beta 1) during the autoimmune process, but there was also a reduced level of IFN-gamma expression in the periphery at the onset of clinical diabetes.
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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 | 0.001 |
| 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) | 0.001 | 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 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".