Report From the 1st International NOD Mouse T-Cell Workshop and the Follow-Up Mini-Workshop
Bibliographic record
Abstract
A workshop on autoreactive T-cell responses in NOD mice was held to optimize autoreactive T-cell detection methodologies. Using different proliferation assay protocols, 1 of the 11 participating laboratories detected spontaneous T-cell responses to GAD(524-543) and insulin(9-23) in their NOD mice. Two other laboratories were able to detect autoreactive responses when using enzyme-linked immunospot assay (ELISPOT) and enzyme-linked immunosorbent assay (ELISA) analysis of cytokines in culture supernatants, suggesting that these assays provided greater sensitivity. To address the divergent findings, a follow-up mini-workshop tested NOD mice from four different colonies side-by-side for T-cell proliferative responses to an expanded panel of autoantigens, using the protocol that had enabled detection of responses in the 1st International NOD Mouse T-Cell Workshop. Under these assay conditions, 16 of 16 NOD mice displayed proliferative responses to whole GAD65, 13 of 16 to GAD(524-543), 9 of 16 to GAD(217-236), 7 of 16 to insulin(9-23), and 5 of 16 to HSP277. Thus, spontaneous proliferative T-cell responses can be consistently detected to some beta-cell autoantigens and peptides thereof. Overall, the results suggest that more sensitive assays (e.g., ELISPOT, ELISA analysis of cytokines in supernatants, or tetramer staining) may be preferred for the detection of autoreactive T-cells.
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.
How this classification was reachedexpand
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".