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Effects of high salt diet on NF‐KB and CREB DNA binding activity in heart, kidney and hypothalamus of SHR

2009· article· en· W345113607 on OpenAlexaff
Qianhui Shang, Hongwei Wang, Alexandre F.R. Stewart, Frans H. H. Leenen

Bibliographic record

VenueThe FASEB Journal · 2009
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenomics, phytochemicals, and oxidative stress
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsCREBEndocrinologyInternal medicineKidneyChemistryHypothalamusMedicineTranscription factorBiochemistry

Abstract

fetched live from OpenAlex

In Dahl S or SHR on high salt diet, activation of NF‐κB contributes to cardiac hypertrophy and renal damage, which may be offset by activation of CREB. The brain RAAS mediates the salt‐induced hypertension, possibly by NF‐κB in the PVN. We assessed effects of high salt diet on DNA‐binding activity of NF‐κB and CREB in the heart, kidney and PVN of WKY rats and SHR on high (8%) or reg (0.6%) salt diet for 2 or 4 weeks (n=6). NF‐κB and CREB DNA binding activity were studied by electrophoretic mobility shift assay. In WKY, high salt only increased CREB DNA binding activity in the LV and NFκB in the PVN. In SHR, high salt increased NF‐κB DNA‐binding activity in the heart and kidney, but decreased CREB binding activity in the heart, kidney, and the PVN. Conclusion High salt causes an inverse relationship between NF‐κB and CREB in the LV, kidney and PVN which may contribute to salt induced sympathetic hyperactivity, LV and renal hypertrophy in SHR.

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 score0.002
Threshold uncertainty score0.006

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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.007
GPT teacher head0.228
Teacher spread0.221 · 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
Published2009
Admission routes1
Has abstractyes

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