SIRT1 in B[a]P-induced lung tumorigenesis
Bibliographic record
Abstract
// Jianyi Lu 1, * , Min Zhang 1, * , Zhiyong Huang 2, * , Sufang Sun 1 , Yongliang Zhang 1 , Lei Zhang 1 , Lirong Peng 1 , Ailing Ma 1 , Pan Ji 1 , Jia Dai 1 , Tong Cui 1 , Heping Liu 1 , Jimin Gao 1 1 Zhejiang Provincial Key Laboratory for Technology & Application of Model Organisms, School of Life Sciences, Wenzhou Medical University, Wenzhou, Zhejiang, 325035, China 2 Department of Cardiothoracic Surgery, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong, 510515, China * These authors have contributed equally to this work Correspondence to: Jimin Gao, e-mail: jimingao@yahoo.com Heping Liu, e-mail: hl691296@hotmail.com Keywords: B[a]P, SIRT1, TNF-α, β-catenin, lung cancer Received: February 04, 2015 Accepted: July 16, 2015 Published: July 28, 2015 ABSTRACT Benzo[a]pyrene (B[a]P) is a carcinogen in cigarette smoke. We found that B[a]P induced SIRT1 in human bronchial epithelial BEAS-2B cell. SIRT1 was overexpressed in the lung of B[a]P-exposed mice and in human lung cancer biopsies. SIRT1 up-regulated TNF-α and β-catenin and down-regulated the membrane fraction of E-cadherin. In addition, SIRT1 promoted invasion, migration and tumorigenesis of BEAS-2B cells in nude mice upon B[a]P exposure. Thus, SIRT1 is involved in B[a]P-induced transformation associated with activation of the TNF-α/β-catenin axis and is as a potential therapeutic target for lung cancer.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".