Adipocyte-Derived Adipokines and Other Obesity-Associated Molecules in Feline Mammary Cancer
Bibliographic record
Abstract
Obesity has been identified as a serious health concern in domestic cats. Feline mammary cancer (FMC) is also a concern, as it is highly prevalent and aggressive. Considering the identified connection between obesity and breast cancer, it is worthwhile to investigate the potential obesity-cancer relationship in FMC. This review investigated the association between adipokines and other obesity-associated molecules and FMC, with the aim of identifying gaps in the current literature for future research. Based on the reports to date, it was found that tissue concentrations of leptin, serum concentrations of leptin receptor, serum amyloid A, and estrogen correlate positively with FMC, and serum concentrations of leptin correlate negatively with FMC. The roles of adiponectin and prolactin in FMC development were also investigated, but the reports are either lacking or insufficient to suggest an association. Numerous research gaps were identified and could be used as opportunities for future research. These include the need for studies on additional cohorts to confirm the association of leptin/leptin receptor and serum amyloid A with FMC, and to address the role of adiponectin and prolactin in FMC. It is also important to investigate the genetic determinants of FMC, evaluate the use of molecular-targeted therapies in FMC, and exploit the enrichment of the triple-negative immunophenotype in FMC to address current clinical needs for both human triple-negative breast cancer and FMC. Finally, mechanistic studies with any of the molecules reviewed are scarce and are important to generate hypotheses and ultimately advance our knowledge and the outcome of FMC.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".