90: Combined Salicylate (SAL) - Metformin (MET) Treatment Induces Increased Tumour Suppression and Radiosensitization in Preclinical Models of Prostate Cancer (PRCA)
Bibliographic record
Abstract
assurance, to limit the required resources, and to reduce the effect of differences in patient positioning between the planning CT and treatment.The patient is treated both prone and supine under a 1 cm clear plastic sheet positioned 20 cm from their surface used to increase skin dose.The first patient treated using this technique at the TBCC was a 16-year-old male with sicklecell anemia.As gonadal shielding was desirable for this patient, our extended SSD lateral field technique was not an option.Our optimized VMAT technique allowed us to provide a reasonable amount of gonadal shielding using MLCs.Results: Dose to the gonads was further reduced using a physical shield made of coated lead positioned above the gonads using an in-house designed device.The combined effect of these two types of shielding allowed us to reduce dose to testis from the prescription of 300 cGy to approximately 100 cGy, without overmodulating the treatment fields or compromising dose uniformity to the rest of the body.Conclusions: In conclusion, a new TBI technique has been developed using VMAT delivery that is optimized to patient anatomy.In addition to a safe and more comfortable patient environment, this technique allows for shielding of organs at risk, if desired by the physician, as was the case for a recent patient at the TBCC -a pediatric sickle-cell anemia patient requiring scrotal shielding. COMBINED SALICYLATE (SAL) -METFORMIN (MET) TREATMENT
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".