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Record W2777173335 · doi:10.1139/cjpp-2018-0072

Retraction: Mitigation of azathioprine-induced testicular atrophy by taurine; an impact on inflammation, oxidative perturbations and apoptosis

2018· retraction· en· W2777173335 on OpenAlexvenueno aff
Salwa A. Mohammad, Basma K. Ramadan, Mona F. Schaalan

Post-publication record

OpenAlex flags this work as retracted, but it carries no matching Retraction Watch record in this frame.

Bibliographic record

VenueCanadian Journal of Physiology and Pharmacology · 2018
Typeretraction
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAldose Reductase and Taurine
Canadian institutionsnot available
Fundersnot available
KeywordsOxidative stressSuperoxide dismutaseEndocrinologyGlutathioneInternal medicineAntioxidantCatalaseTesticular atrophySpermAndrologyBiologyMedicineEnzymeBiochemistry

Abstract

fetched live from OpenAlex

Azathioprine (AZA) is an effective anticancer drug, but some cases of testicular toxicity have been reported. The aim of this work was to investigate the protective effects of taurine (TAU), a reported antioxidant and antiinflammtory peptide, against AZA-induced testicular dysfunction in male rats and ascertain the contributing mechanisms. Forty adult male rats were allocated into four equal groups; (i) normal control rats, (ii) TAU group (100 mg/kg b.w/ day for ten weeks, (iii) AZA group (10 mg/day for four weeks); (iv) TAU/AZA group. As expected, AZA caused increased DNA damage in the testes, and alterations in sex hormones and sperm quality, including sperm count, viability, and motility. Moreover, testicular tissue from the AZA-treated group had increased levels of oxidative stress indicators, MDA, and reduced glutathione (GSH) levels, and decreased activity of the antioxidant enzymes superoxide dismutase (SOD) and catalase (CAT). These deleterious events were accompanied by upregulated levels of the ...

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Other
About the Canadian research system: no · About a Canadian topic: no
Not applicablelow
gptResearch integrity
Domain: not available · Genre: Other
About the Canadian research system: no · About a Canadian topic: no
Not applicablehigh
models splitAgreement compares identical category sets and study designs across arms.

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)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesResearch integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.997
Threshold uncertainty score0.041

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0120.008

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 head0.012
GPT teacher head0.290
Teacher spread0.278 · 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

Labeled directly by 2 models reading the full record.

Research integrity

The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.

Study designNot applicable
Domainnot available
GenreOther

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

Citations1
Published2018
Admission routes1
Has abstractyes

Explore more

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