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Record W2160339712 · doi:10.1902/annals.2001.6.1.113

Receptor for Advanced Glycation End Products, Inflammation, and Accelerated Periodontal Disease in Diabetes: Mechanisms and Insights Into Therapeutic Modalities

2001· review· en· W2160339712 on OpenAlexaff
Evanthia Lalla, Ira B. Lamster, David M. Stern, Ann Marie Schmidt

Bibliographic record

VenueAnnals of Periodontology · 2001
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAdvanced Glycation End Products research
Canadian institutionsColumbia College
Fundersnot available
KeywordsGlycationRage (emotion)MedicineInflammationImmunoglobulin superfamilyDiabetes mellitusReceptorImmunologyAdvanced glycation end-productDiseaseBioinformaticsInternal medicineEndocrinologyBiology

Abstract

fetched live from OpenAlex

In hyperglycemic states found in diabetics, a nonenzymatic glycation and oxidation of proteins and lipids occurs. As a result, advanced glycation end products (AGEs), particularly N epsilon-(carboxymethyl)lysine, accumulate in the plasma and tissues of diabetic subjects. This accumulation has been linked to the development of pathogenic complications of diabetes. Many of the effects of AGEs are receptor-dependent and involve a multi-ligand member of the immunoglobulin superfamily of cell surface molecules. The best characterized of these is the receptor for advanced glycation end products (RAGE), which is expressed by multiple cell types including endothelium and mononuclear phagocytes. Based on data from a variety of sources, including studies of RAGE-deficient mice, it appears that RAGE plays a central role in oral infection, exaggerated inflammatory host responses, and destruction of alveolar bone in diabetes. It is possible that antagonists of RAGE might have a valuable adjunctive therapeutic role for the management of periodontal disease found in diabetics.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.005
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.004

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.

Opus teacher head0.067
GPT teacher head0.369
Teacher spread0.302 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations178
Published2001
Admission routes1
Has abstractyes

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