Analog of H2 relaxin exhibits antagonistic properties and impairs prostate tumor growth
Bibliographic record
Abstract
Hormone antagonists can be effective tools to delineate receptor signaling pathways and their resulting downstream physiological actions. Mutation of the receptor binding domain (RBD) of human H2 relaxin (deltaH2) impaired its biological function as measured by cAMP signaling. In a competition assay, deltaH2 exhibited antagonistic activity by blocking recombinant H2 relaxin from binding to receptors on THP-1 cells. In a flow cytometry-based binding assay, deltaH2 demonstrated weak binding to 293T cells expressing the LGR7 receptor in the presence of biotinylated H2 relaxin. When human prostate cancer cell lines (PC-3 and LNCaP) were engineered to overexpress eGFP, wild-type (WT) H2, or deltaH2, and subsequently implanted into NOD/SCID mice, tumor xenografts overexpressing deltaH2 displayed smaller volumes compared to H2 and eGFP controls. Plasma osmolality readings and microvessel density and area assessment suggest that deltaH2 modulates physiological parameters in vivo. In a second murine model, intratumoral injections of lentivectors engineered to express deltaH2/eGFP led to suppressed tumor growth compared to controls. This study provides further evidence supporting a role for H2 relaxin in prostate tumor growth. More importantly, we report how mutation of the H2 relaxin RBD confers the hormone derivative with antagonistic properties, offering a novel reagent for relaxin research.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".