Non‐invasive evaluation of tumour hypoxia in the Shionogi tumour model for prostate cancer with <sup>18</sup> F‐EF5 and positron emission tomography
Bibliographic record
Abstract
OBJECTIVE: To evaluate hypoxia non-invasively in androgen-dependent (AD), regressing (6-days after castration, RG) and androgen-independent (AI) Shionogi tumours, using the radiolabelled tracer for hypoxia, 18F-EF5, and positron emission tomography (PET). MATERIALS AND METHODS: Groups of mice bearing AD, RG and AI Shionogi tumours were co-injected with 18F-EF5 and unlabelled EF5. The mice were imaged non-invasively with PET to examine the accumulation of 18F-EF5 in hypoxic regions of the tumour. The tumours were subsequently placed in a gamma-counter, or disaggregated for flow cytometry, to determine the levels of 18F-EF5 and the percentage of hypoxic cells present in the tumour, respectively. RESULTS: The mean (sd) levels of hypoxia in AD Shionogi tumours decreased significantly 6 days after androgen ablation as measured by flow cytometry, from 17.1 (4.77) to 1.74 (0.46)% (P=0.003). There were no significant differences in the levels of 18F-EF5 in the tissue between AD and RG tumours using region-of-interest analysis of PET images or gamma-counting, although the differences were significant when measured by flow cytometry. However, mean (sd) levels of hypoxia in AI Shionogi tumours were significantly higher than in AD tumours regardless of the analysis method; PET, 10.5 (4.93)x10(-5)) Bq/cm2 (P=0.017), flow cytometry, 42.98 (3.35)% (P<0.001), well count, 6.81 (1.17)x10(4) and 13.1 (1.99)x10(4) cpm/g, for AD and AI tumours, respectively (P<0.001). CONCLUSIONS: Differences in hypoxia between AD and AI, but not RG, Shionogi tumours can be detected non-invasively with 18F-EF5 and PET. As prostate tumours are hypoxic and the oxygen levels can change with androgen ablation, noninvasive imaging of hypoxia with PET and 18F-EF5 might ultimately have a prognostic and/or diagnostic role in the clinical management of the disease.
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) | 0.001 | 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".