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Record W6993005288

Negative regulation of PGC-1α by NF-κB

2014· dissertation· en· W6993005288 on OpenAlexaff

Bibliographic record

VenueMspace (University of Manitoba) · 2014
Typedissertation
Languageen
FieldMedicine
TopicMedicinal Plant Extracts Effects
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsTranscription factorHomeostasisEnergy homeostasisInflammationEndogenyGlucose homeostasisSignallingFetusSignal transduction
DOInot available

Abstract

fetched live from OpenAlex

The normal adult heart prefers fatty acids as an energy substrate. In the case of heart failure, the heart switches its preference from fatty acids to glucose, adopting a pattern similar to fetal metabolism. PGC-1α is heavily involved in the shift towards glucose oxidation. p65, which belongs to the NF-κB transcription factor family is another crucial molecule involved in maintaining cardiac homeostasis. There is a substantial amount of evidence suggesting that PGC-1α and NF-κB directly interact, thereby connecting metabolic and inflammatory processes. Dysregulation of either PGC-1α or NF-κB signalling correlates to many diseases including heart disease. In this study, we provide further evidence that the NF-κB family has the ability to repress PGC-1α. We also show that the PGC-1α promoter contains a p65 binding site through which p65 imparts control on the PGC-1α gene. Metabolic homeostasis and inflammation pathways are closely linked and play crucial roles in heart dysfunction.

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 score0.005
Threshold uncertainty score0.016

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)0.0050.001

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 head0.009
GPT teacher head0.217
Teacher spread0.207 · 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

Citations0
Published2014
Admission routes1
Has abstractyes

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