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Record W1847184053 · doi:10.4049/jimmunol.178.2.936

Cigarette Smoke Impairs NK Cell-Dependent Tumor Immune Surveillance

2007· article· en· W1847184053 on OpenAlexaff
Л. Лу, Caleb C. J. Zavitz, Biao Chen, Sussan Kianpour, Yonghong Wan, Martin R. Stämpfli

Bibliographic record

VenueThe Journal of Immunology · 2007
Typearticle
Languageen
FieldImmunology and Microbiology
TopicImmune Cell Function and Interaction
Canadian institutionsMcMaster UniversityMcMaster University Medical Centre
Fundersnot available
KeywordsImmune surveillanceImmune systemImmunologySmokeCigarette smokeCancer researchMedicineChemistryEnvironmental health

Abstract

fetched live from OpenAlex

In this study, we investigated the impact of cigarette smoke on tumor immune surveillance and its consequences to lung tumor burden in a murine lung metastasis model. Cigarette smoke exposure significantly increased the numbers of lung metastases following B16-MO5 melanoma challenge. This effect was reversible; we observed significantly fewer tumor nodules following smoking cessation. Using RAG2(-/-) and RAG2(-/-)gamma(c)(-/-) mice, we provide strong evidence that increased tumor incidence was NK cell dependent. Furthermore, we show that cigarette smoke suppressed NK activation and attenuated NK CTL activity, without apparent effect on activating or inhibitory receptor expression. Finally, activation of NK cells through bone marrow-derived dendritic cells conferred protection against lung metastases in smoke-exposed mice; however, protection was not as efficacious as in sham-exposed mice. To our knowledge, this is the first experimental evidence showing that cigarette smoke impairs NK cell-dependent tumor immune surveillance and that altered immunity is associated with increased tumor burden. Our findings suggest that altered innate immunity may contribute to the increased risk of cancer in smokers.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
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 score0.158
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
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 science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.009
GPT teacher head0.229
Teacher spread0.220 · 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.

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

Citations101
Published2007
Admission routes1
Has abstractyes

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