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Chemoprevention of Lung Squamous Cell Carcinoma in Mice by a Mixture of Chinese Herbs

2009· article· en· W2161711994 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueCancer Prevention Research · 2009
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBioactive natural compounds
Canadian institutionsSimon Fraser University
FundersNational Center for Complementary and Integrative HealthWashington University in St. LouisNational Cancer InstituteNational Institutes of HealthAlvin J. Siteman Cancer CenterU.S. Public Health Service
KeywordsLungHyperplasiaMedicinePathologyLung cancerAnimal modelCellCancer researchInternal medicineChemistry

Abstract

fetched live from OpenAlex

Antitumor B (ATB) is a Chinese herbal mixture of six plants. Previous studies have shown significant chemopreventive efficacy of ATB against human esophageal and lung cancers. We have recently developed a new mouse model for lung squamous cell carcinomas (SCC). In this study, lung SCC mouse model was characterized using small-animal imaging techniques (magnetic resonance imaging and computed tomography). ATB decreased lung SCC significantly (3.1-fold; P < 0.05) and increased lung hyperplastic lesions by 2.4-fold (P < 0.05). This observation suggests that ATB can block hyperplasia from progression to SCC. ATB tissue distribution was determined using matrine as a marker chemical. We found that ATB is rapidly absorbed and then distributes to various tissues including the lung. These results indicate that ATB is a potent chemopreventive agent against the development of mouse lung SCCs.

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.

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)0.000
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 score0.062
Threshold uncertainty score0.413

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0000.000

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 head0.015
GPT teacher head0.361
Teacher spread0.346 · 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