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Record W2112698509 · doi:10.2174/092986707780830989

The Road to Advanced Glycation End Products: A Mechanistic Perspective

2007· review· en· W2112698509 on OpenAlexaff
S.-J. Cho, Gheorghe Roman, Faustinus K. Yeboah, Y. Konishi

Bibliographic record

VenueCurrent Medicinal Chemistry · 2007
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAdvanced Glycation End Products research
Canadian institutionsBiotechnology Research InstituteNational Research Council Canada
FundersDiabetes Action Research and Education Foundation
KeywordsGlycationAmadori rearrangementChemistryPentosidineBiochemistryLysineAdvanced glycation end-productMaillard reactionReactive intermediateAmino acidReceptor

Abstract

fetched live from OpenAlex

Protein glycation is a slow natural process involving the chemical modification of the reactive amino and guanidine functions in amino acids by sugars and carbohydrates-derived reactive carbonyls. Its deleterious consequences are obvious in the case of long-lived proteins in aged people and are exacerbated by the high blood concentration of sugars in diabetic patients. The non-enzymatic glycation of proteins occurs through a wide range of concurrent processes comprising condensation, rearrangement, fragmentation, and oxidation reactions. Using a few well established intermediates such as Schiff base, Amadori product and reactive a-dicarbonyls as milestones and the results of in vitro glycation investigations, an overall detailed mechanistic analysis of protein glycation is presented for the first time. The pathways leading to several advanced glycation end products (AGEs) such as (carboxymethyl)lysine, pentosidine, and glucosepane are outlined, whereas other AGEs useful as potential biomarkers of glycation are only briefly mentioned. The current stage of the development of glycation inhibitors has been reviewed with an emphasis on their mechanism of action.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0020.003
Science and technology studies0.0000.001
Scholarly communication0.0020.005
Open science0.0010.001
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0040.004

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 head0.055
GPT teacher head0.427
Teacher spread0.372 · 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 designTheoretical or conceptual
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

Citations215
Published2007
Admission routes1
Has abstractyes

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