UV‐induced DNA damage response in blood cells for cancer detection
Bibliographic record
Abstract
Abstract Detection and diagnosis of cancer often require a combination of tests that are inconvenient and invasive for patients. There is therefore a need for new simple non‐invasive tests able to detect cancer at various stages. Here, a novel photochemical assay for cancer detection in liquid biopsies is described. This proof of concept study shows that the response of peripheral blood mononuclear cells (PBMCs) to light‐emitting diode (LED)‐transmitted UV radiation can be used as an indicator of malignant disease. When exposed to UVB/C radiation, isolated PBMCs from prostate cancer patients presented with an acute dose‐dependent DNA damage response that is distinct from that of PBMCs from healthy individuals. Importantly, this assay achieves sensitivity and specificity comparable to standard methods currently in clinical use. In summary, this work demonstrates that photochemical interrogation of PBMCs from cancer patients can be utilized for detection of malignant diseases. As such, the assay could potentially complement current gold standard cancer detection strategies for the benefit of patients and healthcare economy.
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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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".