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Record W2590279378 · doi:10.3390/ijms18030480

Intracellular Accumulation of Methylglyoxal by Glyoxalase 1 Knock Down Alters Collagen Homoeostasis in L6 Myoblasts

2017· article· en· W2590279378 on OpenAlexfundno aff
Bernd Stratmann, Bernhard Goldstein, Paul J. Thornalley, Naila Rabbani, Diethelm Tschoepe

Bibliographic record

VenueInternational Journal of Molecular Sciences · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAdvanced Glycation End Products research
Canadian institutionsnot available
FundersUniversity of Toronto
KeywordsMethylglyoxalLactoylglutathione lyaseExtracellular matrixChemistryGene knockdownMyocyteExtracellularIntracellularBiochemistryInternal medicineEndocrinologyCell biologyBiologyEnzymeMedicine

Abstract

fetched live from OpenAlex

Hyperglycemia results in accumulation of the reactive dicarbonyl methylglyoxal (MG). Methylglyoxal is detoxified by the glyoxalase system (glyoxalase 1 and 2). The influence of glyoxalase 1 knockdown on expression of collagens 1, 3, 4, and 5 in L6 myoblasts under hyperglycemic conditions was investigated. Increased biosynthesis of collagens 1, 3, 4, and 5 was detected at mRNA-level following knockdown of glyoxalase 1 (GLO1). At the protein level a significant elevation of the concentration of collagen 1 and 4 was shown, whereas no increase of collagen 5 and a non-significant increase in collagen 3 were detectable. These results could partially explain MG-induced changes in the extracellular matrix (ECM) which account for increased fibrosis and impaired function in myocytes. The mechanisms by which reactive glucose metabolites influence ECM composition deserve further investigation.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.040
GPT teacher head0.392
Teacher spread0.352 · 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 designBench or experimental
Domainnot available
GenreEmpirical

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

Citations38
Published2017
Admission routes1
Has abstractyes

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