Carbon dioxide reactivity of computed tomography functional parameters in rabbit VX2 soft tissue tumour
Bibliographic record
Abstract
Tumour blood flow is one of the important factors limiting the efficacy of radiation therapy (hypoxic radioresistance), chemotherapy (drug delivery) and thermal therapy (heat dissipation) in treating cancer. The modification of tumour blood flow has been an area of intense investigation. In the current study, the arterial carbon dioxide tension (PaCO2) was changed in order to investigate the tumour vascular response to carbon dioxide. Functional maps of blood flow, blood volume and mean transit time were generated at four PaCO2 levels in VX2 tumour in the rabbit thigh and normal soft tissue. The PaCO2 levels investigated were normocapnia (PaCO2 = 40.9 +/- 1.2 mmHg), hypocapnia (27.2 +/- 2.3 and 33.5 +/- 2.3 mmHg) and hypercapnia (54.9 +/- 4.4 mmHg). The carbon dioxide reactivity of the global tumour blood flow and mean transit time showed significant differences between normocapnia and the two levels of hypocapnia, but not between normocapnia and hypercapnia. The average fractional change of blood flow from normocapnia for the two levels of hypocapnia was -0.41 +/- 0.06 and -0.29 +/- 0.08, respectively (P < 0.05). In the case of mean transit time the fractional change was +0.39 +/- 0.30 and +0.23 +/- 0.24, respectively (P < 0.05). The fractional change of blood volume from normocapnia, however, was not significantly different at any capnic level, as was the case with respect to each of the functional parameters in normal tissue. The ability to reduce blood flow and increase mean transit time through hypocapnia has significant implications in thermal therapy, since heat dissipation is a major factor in limiting the effectiveness of 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) | 0.000 | 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) | 0.001 | 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".