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Record W4394260991 · doi:10.6084/m9.figshare.12851522

BMI1 promotes steroidogenesis through maintaining redox homeostasis in mouse MLTC-1 and primary Leydig cells

2023· dataset· en· W4394260991 on OpenAlexaff
Tingting Gao, Meng Lin, Binbin Shao, Qiao Zhou, Yufeng Wang, Xia Chen, Dan Zhao, Xiuliang Dai, Cong Shen, Hongbo Cheng, Shenmin Yang, Hong Li, Bo Zheng, Xingming Zhong, Jun Yu, Li Chen, Xiaoyan Huang

Bibliographic record

VenueFigshare · 2023
Typedataset
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicFOXO transcription factor regulation
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsLeydig cellRedoxCell biologyHomeostasisPrimary (astronomy)BMI1ChemistryBiologyStem cellEndocrinologyPhysics

Abstract

fetched live from OpenAlex

In males, aging is accompanied by decline in serum testosterone levels due to impairment of testicular Leydig cells. The polycomb protein BMI1 has recently been identified as an anti-aging factor. In our previous study, BMI1 null mice showed decreased serum testosterone and Leydig cell population, excessive oxidative stress and p16/p19 signaling activation. However, a cause-and-effect relationship between phenotypes and pathways was not investigated. Here, we used the rescue approach to study the role of oxidative stress or p16/p19 in BMI1-mediated steroidogenesis. Our results revealed that treatment with antioxidant NAC, but not down-regulation of p16/p19, largely rescued cell senescence, DNA damage and steroidogenesis in BMI1-deficient mouse MLTC-1 and primary Leydig cells. Collectively, our study demonstrates that BMI1 orchestrates steroidogenesis mainly through maintaining redox homeostasis, and thus, BMI1 may be a novel and potential therapeutic target for treatment of hypogonadism.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.032
Threshold uncertainty score0.105

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0320.014

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 head0.032
GPT teacher head0.258
Teacher spread0.227 · 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 designNot applicable
Domainnot available
GenreDataset

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
Published2023
Admission routes1
Has abstractyes

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