Hypoxia in the Androgen-Dependent Shionogi Model for Prostate Cancer at Three Stages<sup>1</sup>
Bibliographic record
Abstract
The objective of this study was to investigate a possible relationship between androgen status and hypoxia in the Shionogi murine prostate tumor model, which is widely used to study the effects of androgen withdrawal on hormone resistance and radiation response. Binding of the nitroimidazole hypoxia marker EF5 was assessed using the Cy3-tagged monoclonal antibody ELK3-51. Three hours after injection of EF5 (30 mg/kg), tumors from the following three stages were excised: androgen-dependent, regressed tumors 7 days after castration, and androgen-independent. Half of each tumor was disaggregated for analysis by flow cytometry and the remainder was flash frozen. Statistically significant differences (P < 0.01) were found between androgen-dependent, regressed and androgen-dependent tumors: approximately 30, approximately 2 and approximately 50% hypoxic cells, respectively. Frozen sections from androgen-dependent tumors exhibited highly variable EF5 binding; regressed tumors showed very little or no binding; each section from androgen-dependent tumors showed high levels and uniformly distributed binding of EF5. There was no correlation between the degree of hypoxia and tumor weight (P > 0.1). The results from this preliminary study indicate that hypoxia may play an important role with respect to the timing of irradiation in prostate cancer treatments and possibly may be a useful prognostic tool. In addition, hypoxia may also be relevant to progression in this disease after androgen ablation.
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 | 0.000 | 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) | 0.001 | 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".