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Record W1979762673 · doi:10.4137/lpi.s10871

Diet, Obesity, and Cancer Progression: Are Adipocytes the Link?

2013· review· en· W1979762673 on OpenAlexaff
Paul Toren, Benjamin C. Mora, Vasundara Venkateswaran

Bibliographic record

VenueLipid Insights · 2013
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer, Lipids, and Metabolism
Canadian institutionsUniversity of TorontoSunnybrook Health Science CentreHealth Sciences CentreUniversity of British Columbia
Fundersnot available
KeywordsAdipokineParacrine signallingTumor microenvironmentAdipose tissueCancerAdipocyteProstate cancerBiologyCancer researchInternal medicineTumor progressionEndocrinologyBreast cancerObesityMedicineInsulin resistanceReceptor

Abstract

fetched live from OpenAlex

Obesity has been linked to more aggressive characteristics of several cancers, including breast and prostate cancer. Adipose tissue appears to contribute to paracrine interactions in the tumor microenvironment. In particular, cancer-associated adipocytes interact reciprocally with cancer cells and influence cancer progression. Adipokines secreted from adipocytes likely form a key component of the paracrine signaling in the tumor microenvironment. In vitro coculture models allow for the assessment of specific adipokines in this interaction. Furthermore, micronutrients and macronutrients present in the diet may alter the secretion of adipokines from adipocytes. The effect of dietary fat and specific fatty acids on cancer progression in several in vivo model systems and cancer types is reviewed. The more common approaches of caloric restriction or diet-induced obesity in animal models establish that such dietary changes modulate tumor biology. This review seeks to explore available evidence regarding how diet may modulate tumor characteristics through changes in the role of adipocytes in the tumor microenvironment.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.921
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
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 head0.028
GPT teacher head0.311
Teacher spread0.283 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations20
Published2013
Admission routes1
Has abstractyes

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