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Record W2738066453 · doi:10.1139/cjpp-2016-0744

Ablation of toll-like receptor 4 mitigates cardiac mitochondrial dysfunction in hyperhomocysteinemia

2017· article· en· W2738066453 on OpenAlexvenueno aff
Nevena Jeremić, Gregory J. Weber, Suresh C. Tyagi

Bibliographic record

VenueCanadian Journal of Physiology and Pharmacology · 2017
Typearticle
Languageen
FieldMedicine
TopicFolate and B Vitamins Research
Canadian institutionsnot available
Fundersnot available
KeywordsOxidative stressHyperhomocysteinemiaInternal medicineReceptorEndocrinologyEndothelial dysfunctionBiologyMitochondrionmitochondrial fusionTLR4Mitochondrial fissionEndotheliumHomocysteineMedicineCell biologyMitochondrial DNAGeneBiochemistry

Abstract

fetched live from OpenAlex

Hyperhomocysteinemia (HHcy) is a risk factor for adverse cardiovascular events; however, the mechanism for development of this disease is still unknown. Toll-like receptor 4 (TRL4) is a molecule involved in the immune response pathway and is quickly becoming a receptor of interest in the field of hypertension. In this study, we hypothesized that ablation of TLR4 mitigates cardiac mitochondrial dysfunction in a model of HHcy. Five strains of mice (C57BL/6J, CBS+/−, C3H, CBS+/−/C3H, and C3H/HeOuJ) 10–12 weeks old were utilized. We found that HHcy causes heart hypertrophy and promotes oxidative stress while mice with HHcy and inactivated TLR4 showed significant improvement in examined parameters. A dominance of endothelial cell mitochondrial fission over mitochondrial fusion in HHcy and oxidative stress was observed, which may explain the endothelial cell loss and dysfunction that contributes to inward cardiac remodeling.

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)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.018
GPT teacher head0.301
Teacher spread0.283 · 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

Citations9
Published2017
Admission routes1
Has abstractyes

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