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Record W2767968368 · doi:10.1155/2017/2032697

Protective Effects of Genistein against Mono-(2-ethylhexyl) Phthalate-Induced Oxidative Damage in Prepubertal Sertoli Cells

2017· article· en· W2767968368 on OpenAlexfundno aff
Liandong Zhang, Ming Gao, Tong-Dian Zhang, Tie Chong, Ziming Wang, Xiaoqiang Zhai, Zhi‐Zhong Wu, Hecheng Li

Bibliographic record

VenueBioMed Research International · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicEffects and risks of endocrine disrupting chemicals
Canadian institutionsnot available
FundersMcGill University Health CentreNational Natural Science Foundation of ChinaMcGill University
KeywordsGenisteinSertoli cellApoptosisEndocrinologyInternal medicineOxidative stressPhthalateChemistryFenretinideBiologyAndrologyCell cultureSpermatogenesisBiochemistryMedicine

Abstract

fetched live from OpenAlex

Mono-(2-ethylhexyl) phthalate (MEHP) and genistein are two of the most prevalent endocrine-disrupting chemicals (EDCs) that present in the environment and food. However, how these two EDCs would affect prepubertal Sertoli cells development was rarely studied. In this study, primary prepubertal Sertoli cells were isolated from 22-day-old Sprague Dawley rats and exposed to MEHP at 1 μ mol/L, 10 μ mol/L, and 100 μ mol/L (M1, M10, and M100), genistein at 10 μ mol/L (G), and their combination (G + M1, G + M10, and G + M100). Cell proliferation inhibition rate, apoptosis and necrosis rate, and cellular redox state were evaluated. Our results revealed that MEHP could significantly increase cell proliferation inhibition rate, apoptosis rate, necrosis rate, and intracellular reactive oxidative species level. However, coadministration of genistein could partially alleviate MEHP-induced prepubertal Sertoli cells oxidative injuries via enhancement of testicular antioxidative enzymes activities and upregulation of Nrf2 and HO-1, indicating that genistein could partially attenuate MEHP-induced prepubertal Sertoli cells damage through antioxidative action and may have promising future on its curative role for attenuating other EDCs-induced reproductive disorders.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.111
Threshold uncertainty score0.535

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 science0.0010.001
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 head0.035
GPT teacher head0.428
Teacher spread0.393 · 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

Citations34
Published2017
Admission routes1
Has abstractyes

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