Receptor for Advanced Glycation End Products (RAGEs) and Experimental Diabetic Neuropathy
Post-publication record
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Bibliographic record
Abstract
OBJECTIVE: Heightened expression of the receptor for advanced glycation end products (RAGE) contributes to development of systemic diabetic complications, but its contribution to diabetic neuropathy is uncertain. We studied experimental diabetic neuropathy and its relationship with RAGE expression using streptozotocin-induced diabetic mice including a RAGE(-/-) cohort exposed to long-term diabetes compared with littermates without diabetes. RESEARCH DESIGN AND METHODS: Structural indexes of neuropathy were addressed with serial (1, 3, 5, and 9 months of experimental diabetes) electrophysiological and quantitative morphometric analysis of dorsal root ganglia (DRG), peripheral nerve, and epidermal innervation. RAGE protein and mRNA levels in DRG, peripheral nerve, and epidermal terminals were assessed in WT and RAGE(-/-) mice, with and without diabetes. The correlation of RAGE activation with nuclear factor (NF)-kappaB and protein kinase C beta II (PKC beta II) protein and mRNA expression was also determined. RESULTS: Diabetic peripheral epidermal axons, sural axons, Schwann cells, and sensory neurons within ganglia developed dramatic and cumulative rises in RAGE mRNA and protein along with progressive electrophysiological and structural abnormalities. RAGE(-/-) mice had attenuated structural features of neuropathy after 5 months of diabetes. RAGE-mediated signaling pathway activation for NF-kappaB and PKC beta II pathways was most evident among Schwann cells in the DRG and peripheral nerve. CONCLUSIONS: In a long-term model of experimental diabetes resembling human diabetic peripheral neuropathy, RAGE expression in the peripheral nervous system rises cumulatively and relates to progressive pathological changes. Mice lacking RAGE have attenuated features of neuropathy and limited activation of potentially detrimental signaling pathways.
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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 | 0.000 |
| 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) | 0.001 | 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".