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Record W2166705808 · doi:10.1158/0008-5472.can-09-3231

Activation of Murine Double Minute 2 by Akt in Mammary Epithelium Delays Mammary Involution and Accelerates Mammary Tumorigenesis

2010· article· en· W2166705808 on OpenAlexaff
Xiaoyun Cheng, Weiya Xia, Jer-Yen Yang, Jennifer L. Hsu, Jing-Yu Lang, Chao‐Kai Chou, Yi Du, Hui-Lung Sun, Shannon L. Wyszomierski, Gordon B. Mills, William J. Muller, Dihua Yu, Mien‐Chie Hung

Bibliographic record

VenueCancer Research · 2010
Typearticle
Languageen
FieldMedicine
TopicCancer-related Molecular Pathways
Canadian institutionsMcGill University
FundersNational Cancer InstituteKræftens Bekæmpelse
KeywordsProtein kinase BMdm2Mammary glandCarcinogenesisInvolution (esoterism)Mammary tumorCancer researchBiologyApoptosisTransgeneGenetically modified mousePhosphorylationIn vivoInternal medicineEndocrinologyCancerCell biologyMedicineBreast cancerGeneGenetics

Abstract

fetched live from OpenAlex

Amplification or overexpression of murine double minute 2 (MDM2) promotes a variety of human tumors by degrading tumor suppressor proteins such as p53. Phosphorylation of MDM2 on Ser(166) and Ser(186) by the survival kinase Akt inhibits p53-mediated apoptosis. However, it is unclear whether this pathway contributes to normal or malignant pathophysiology in vivo. To address these questions, we generated transgenic mice expressing the Akt-phosphorylated form of MDM2 (MDM2DDS166D/S186D) in the mammary epithelium. Activation of MDM2 delayed mammary gland involution and accelerated tumor progression in mouse mammary tumor virus/neu transgenic mice by inhibiting apoptosis in a manner associated with decreased p53 expression. Our findings offer in vivo evidence that activation of MDM2 by Akt contributes to mammary development and tumorigenesis.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.046
GPT teacher head0.346
Teacher spread0.299 · 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 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

Citations21
Published2010
Admission routes1
Has abstractyes

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