The nuclear-localized GHR is involved in the cell proliferation of gastric cancer, and pegvisomant may be an important potential drug to inhibit the proliferation of gastric cancer cells
Bibliographic record
Abstract
Under normal physiological conditions, growth hormones (GH) play an important role in body growth and metabolism. A recent study showed that GH has important biological effects on gastric cancer (GC) both in vitro and in vivo. However, the biological properties of GH/GHR (GHR, growth hormone receptor) in GC cells have not been fully elucidated. To this end, we systemically studied the biological properties of GH in GC cells and found that GH/GHR was transported into the nuclei of GC cells. Furthermore, we investigated the functions of nuclear GHR and its potential mechanisms of action. We found that nuclear-localized GHR was closely related to the proliferation of GC cells. In addition, we systematically studied the effect of a GHR inhibitor (pegvisomant) on GC in vivo and in vitro, and the results showed that pegvisomant can not only inhibit the proliferation of GC cells but also inhibit the nuclear localization of GHR, suggesting that pegvisomant may be a dual-effect antagonist. Current research indicates that GHR may be a potential target for the treatment of GC.
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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 | 0.001 |
| 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".