Blood and Islet Phenotypes Indicate Immunological Heterogeneity in Type 1 Diabetes
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
Studies in type 1 diabetes indicate potential disease heterogeneity, notably in the rate of β-cell loss, responsiveness to immunotherapies, and, in limited studies, islet pathology. We sought evidence for different immunological phenotypes using two approaches. First, we defined blood autoimmune response phenotypes by combinatorial, multiparameter analysis of autoantibodies and autoreactive T-cell responses in 33 children/adolescents with newly diagnosed diabetes. Multidimensional cluster analysis showed two equal-sized patient agglomerations characterized by proinflammatory (interferon-γ-positive, multiautoantibody-positive) and partially regulated (interleukin-10-positive, pauci-autoantibody-positive) responses. Multiautoantibody-positive nondiabetic siblings at high risk of disease progression showed similar clustering. Additionally, pancreas samples obtained post mortem from a separate cohort of 21 children/adolescents with recently diagnosed type 1 diabetes were examined immunohistologically. This revealed two distinct types of insulitic lesions distinguishable by the degree of cellular infiltrate and presence of B cells that we termed "hyper-immune CD20Hi" and "pauci-immune CD20Lo." Of note, subjects had only one infiltration phenotype and were partitioned by this into two equal-sized groups that differed significantly by age at diagnosis, with hyper-immune CD20Hi subjects being 5 years younger. These data indicate potentially related islet and blood autoimmune response phenotypes that coincide with and precede disease. We conclude that different immunopathological processes (endotypes) may underlie type 1 diabetes, carrying important implications for treatment and prevention strategies.
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) | 0.000 | 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) | 0.000 | 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 it