Bibliographic record
Abstract
Abstract Low levels of physical activity and being overweight or obese are associated with an increased risk of several types of cancer, particularly colorectal and postmenopausal breast cancer. The proposed biological mechanisms underlying these associations include inflammatory factors, steroid hormones, insulin-like growth factors or insulin resistance. Adipose tissue may play a key role in the association between energy balance and proposed biomarkers of cancer risk, via increased production of inflammatory factors, steroid hormones, and altered adipokines. Therefore, the impact of weight loss and physical activity interventions on adipose tissue gene expression may provide insights into pathways linking obesity/physical activity with cancer risk in human models. Our group previously established the feasibility and acceptability of obtaining subcutaneous abdominal adipose tissue samples in women who were screened to participate in a breast cancer prevention study. We then conducted an ancillary study within a randomized trial of diet, exercise, or combined diet+exercise vs. control among inactive, overweight/obese postmenopausal women. Subcutaneous adipose tissue biopsies were performed at baseline and after 6 months. Changes in adipose tissue gene expression were determined by microarray. The analytical approach had an emphasis on pre-specified candidate genes and candidate pathways, but also included a gene discovery approach. Furthermore, we examined the correlation of gene expression with serum blood markers. Analysis was conducted both by intervention group and also by degree of weight loss. A change in expression of sex hormone-related genes and LEP were noted with weight change, and the unsupervised clustering of >37,000 transcripts revealed new signaling pathways that require further follow-up. Citation Format: Kristin L. Campbell. Adipose tissue as a rich information source. [abstract]. In: Proceedings of the AACR Special Conference on Post-GWAS Horizons in Molecular Epidemiology: Digging Deeper into the Environment; 2012 Nov 11-14; Hollywood, FL. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2012;21(11 Suppl):Abstract nr IA14.
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 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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.326 | 0.168 |
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".