Selective radiation-enhancing effects of a muscle-derived dipeptide in an orthotopic non-small cell lung cancer (NSCLC) xenograft mouse model
Bibliographic record
Abstract
PURPOSE: Radiotherapy (RT) is a standard treatment for non-small cell lung cancer (NSCLC). Radiosensitizers enhance radiation-mediated cancer cell elimination but lack selectivity and therefore also enhance normal tissue damage. L-carnosine (CAR) shows promise, having selective radiation-enhancing properties in vitro. This study validates CAR's selective radiation-enhancing properties in vivo, resulting in reduced tumor volume without causing damage to normal lung tissues. METHODS: An orthotopic NSCLC model was established by implanting NCI-H1299 cells into male and female athymic nude mice. Mice were randomly divided into four treatment groups: (1) Control, (2) RT-only, (3) CAR-only and (4) CAR+RT. Control and RT-only received 8 days of intraperitoneal vehicle, while CAR-only and CAR+RT received 1 M CAR (500 μL/day) intraperitoneally for 8 days. A single 20 Gy RT dose was delivered to RT-only and CAR+RT treated mice after 4-days of CAR treatment. The response of tumors to treatment was evaluated using CT imaging and immunohistochemistry (IHC), and the effects on normal lung tissue were evaluated using IHC. RESULTS: CAR+RT significantly reduced tumor volumes and reduced expression of tumor aggressiveness markers without increasing damage to the normal lung tissue when compared to RT-only group in both sexes. CONCLUSION: Treatment with CAR in combination with RT significantly reduces tumor volume and cancer cell proliferation in vivo without affecting normal lung tissue. Our study supports CAR's potential as a safe and selective radiation-enhancer that could widen the therapeutic window of RT.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.000 | 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 teacher head, 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".