Bibliographic record
Abstract
The immunoglobulin superfamily molecule RAGE (receptor for advanced glycation end product) transduces the effects of multiple ligands, including AGEs (advanced glycation end products), advanced oxidation protein products, S100/calgranulins, high-mobility group box-1, amyloid-beta peptide, and beta-sheet fibrils. In diabetes, hyperglycemia likely stimulates the initial burst of production of ligands that interact with RAGE and activate signaling mechanisms. Consequently, increased generation of proinflammatory and prothrombotic molecules and reactive oxygen species trigger further cycles of oxidative stress via RAGE, thus setting the stage for augmented damage to diabetic tissues in the face of further insults. Many of the ligand families of RAGE have been identified in atherosclerotic plaques and in the infarcted heart. Together with increased expression of RAGE in diabetic settings, we propose that release and accumulation of RAGE ligands contribute to exaggerated cellular damage. Stopping the vicious cycle of AGE-RAGE and RAGE axis signaling in the vulnerable heart and great vessels may be essential in controlling and preventing the consequences of diabetes.
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 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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.004 |
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".