AEB-071 has minimal impact on onset of autoimmune diabetes in NOD mice
Bibliographic record
Abstract
Protein kinase C (PKC) is an important signaling enzyme in the activation and regulation of T lymphocytes. T-cell-mediated destruction of beta-cells is a characteristic feature of autoimmune (Type 1) diabetes. Here we explore the ability of PKC inhibition, using the PKC inhibitor AEB-071 (AEB), to reduce disease in two animal models of spontaneous autoimmune diabetes (non-obese diabetic (NOD) mouse and biobreeding rat (BB)). NOD mice were treated with AEB for 4 weeks, starting at either 4 weeks of age (prior to the development of insulitis) or at 8 weeks of age, once insulitis is present. Animals treated with AEB during the effector phase of the disease (treatment onset at 8 weeks of age), showed a 2-week delay in diabetes onset (p < 0.05). In these animals, the extent of insulitis was lower than in vehicle-treated controls; however, neither serum autoimmune anti-GAD65 antibody levels nor pancreatic insulin content were different between experimental groups. Overall, inhibition of PKC can mildly reduce lymphocytic infiltrate of pancreatic islets and modestly delay onset of autoimmune diabetes in NOD mice. AEB, a T-cell-targeted immunosuppressive strategy, is only sufficient as a monothereapy to modestly delay onset of autoimmune disease in the NOD mouse.
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 | 0.000 |
| 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 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".