Comparison of volumetric dynamic optical coherence tomography with biological methods for evaluation of radiation effects in prostate tumor spheroids
Bibliographic record
Abstract
Abstract Significance 3D tumor spheroids are more physiologically representative of in vivo patient tumors compared to 2D monolayer culture. However, their 3D nature challenges the use of conventional biological techniques like proliferation assays, fluorescence microscopy, and the clonogenic assay, which is the gold standard method for assessing cell survival following radiation. However, clonogenic assay requires spheroid disaggregation. Aim Non-invasive volumetric imaging with dynamic optical coherence tomography (dOCT) enables cellular activity to be visualized with spatial resolution within 3D tumor spheroids. Cellular activity observed via dOCT in irradiated prostate tumor spheroids was quantified for comparison with conventional biological techniques. Approach A Varian TrueBeam linear accelerator was used to irradiate spheroid and monolayer cultures with a 6 MV beam. Cellular activity was estimated from dOCT images generated via frequency banding and compared to clonogenic assay, proliferation assay, fluorescence microscopy, and 3D cell simulation. Results Prostate cancer cells cultured as spheroids demonstrated improved radio-resistance via clonogenic assay compared to monolayer culture. The dOCT method demonstrated quantitative and qualitative agreement with proliferation assay and fluorescence microscopy, respectively. Conclusions A longer duration of repeated dOCT measurement in tumor spheroids following radiation treatment could offer a non-invasive alternative to the clonogenic assay.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".