Bibliographic record
Abstract
Interleukins serve as communicating molecules between cells, mediating key interactions in the tumor microenvironment (TME) between immune cells and non-immune cells. Interleukin-10 (IL-10), a multifunctional cytokine with multiple properties, has been extensively studied in various aspects of immunology and cancer biology. IL-10 is pleiotropic, promotes cytotoxicity, yet inhibits antitumor-responses. In recent years, the role of IL-10 in ovarian cancer (OC) progression and treatment has gained significant scientific attention, elucidating the signaling pathways triggered by IL-10 action. OC, the leading cause of gynecologic cancer-related deaths, is characterized by ascites, which hosts an intricate TME that is not responsive to treatment by immune checkpoint inhibition. IL-10, known for its immunosuppressive and anti-inflammatory properties, plays a complex role in OC progression, immune modulation, and therapeutic response and has a potential therapeutic property as a target and as an effector. As the literature of basic science research studying the role of IL-10 in the TME of OC scopes a few decades and some data is contrasting, it is important to review the literature and provide concise input derived from it. This review aims to provide a comprehensive overview of the current understanding of IL-10 in OC, highlighting its influence on tumor growth, immune evasion, and potential as a therapeutic target.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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; both teacher heads agree on what is shown here.
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".