Co‐localization of nodal in hypoxic regions of tumours as seen using confocal microscopy and stereoscopic 3D reconstruction methods
Bibliographic record
Abstract
Metastatic breast cancer is associated with a poor clinical prognosis. Understanding the factors that promote metastasis is required so that new treatments can be derived. Studies have shown that low oxygen levels (hypoxia) characterize the microenvironment of many tumours and that tumour hypoxia is correlated with increased metastatic potential. Nodal, an embryonic growth factor, is associated with tumour progression in breast cancer. Previous work indicates that Nodal is up‐regulated in response to hypoxia. The aim of this study was to investigate the co‐localization of Nodal with areas of hypoxia within three‐dimensional (3D) tumour spheroids. A poorly metastatic, well differentiated, human breast cancer cell line (MCF‐7) was grown as mammospheres and fixed using paraformaldahyde. Nuclei, hypoxia, and Nodal were simultaneously detected using immunofluorescence. Stained mammospheres were whole mounted for optical sectioning using a confocal microscope. Images were obtained at a slice thickness of 1‐2µm. Images were compiled and rendered into a 3D image using digital segmentation software. The co‐localization of Nodal and areas of hypoxia within the mammospheres were observed. Early results indicate that there may be pockets of hypoxic regions within the mammospheres and it is anticipated that Nodal will be up‐regulated in these areas. Research support: Canadian Institute of Health Research. Grant Funding Source Internal
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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 | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".