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Record W2787190452 · doi:10.1139/cjpp-2017-0252

Triiodothyronine attenuates the progression of renal injury in a rat model of chronic kidney disease

2018· article· en· W2787190452 on OpenAlexvenueno aff
Sahar M. El Agaty

Bibliographic record

VenueCanadian Journal of Physiology and Pharmacology · 2018
Typearticle
Languageen
FieldMedicine
TopicBiochemical effects in animals
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineRenal injuryKidney diseaseTriiodothyronineInternal medicineEndocrinologyKidneyRat modelChronic renal diseaseDiseaseAnimal modelThyroid

Abstract

fetched live from OpenAlex

This study was designed to investigate whether and how triiodothyronine (T 3 ) affects renal function in an experimental model of chronic kidney disease. Twenty-four female rats were divided into the following groups: sham-operated control group (n = 8), 5/6 nephrectomized group (Nx, n = 8), and 5/6 nephrectomized group treated with T 3 for 2 weeks (T 3 -Nx, n = 8). T 3 administration significantly decreased serum levels of urea, creatinine, tumour necrosis factorα, and interleukin-6 compared with serum levels in the Nx group. The levels of malondialdehyde, transforming growth factor β, fibronectin, and collagen IV, as well as the expression of inducible nitric oxide synthase, nuclear factor κB, poly(ADP-ribose) polymerase, caspase-3, and Bax were all significantly decreased, though not normalized, in the remnant kidney of rats in the T 3 -Nx group compared with Nx rats. Glutathione, heme oxygenase-1 levels, as well as endothelial nitric oxide synthase expression were increased in the remnant kidney of the T 3 -Nx group. Histological studies revealed focal necrosis of renal tubules associated with inflammatory cell infiltration and fibrosis in the Nx group. These changes were alleviated in T 3 -Nx rats. This study showed that T 3 administration attenuated the clinical and histological signs of renal injury in 5/6 nephrectomized rats by mitigating renal oxidative stress, inflammation, apoptosis, and fibrosis.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.008
Threshold uncertainty score0.470

Codex and Gemma teacher scores by category

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

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 head0.015
GPT teacher head0.320
Teacher spread0.305 · 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 teacher head, 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

Citations5
Published2018
Admission routes1
Has abstractyes

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