Confocal Raman microspectral analysis and imaging of the drug response of osteosarcoma to cisplatin
Why this work is in the frame
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Bibliographic record
Abstract
Confocal Raman microspectral analysis and imaging were used to elucidate the drug response of osteosarcoma (OS) to cisplatin. Raman spectral data were obtained from OS cells that were untreated (UT group) and treated with 20 µM (20T group) and 40 µM (40T group) cisplatin for 24 hours. Statistical analysis of the changes in specific Raman signals was performed using a one-way ANOVA and multiple Tukey's honest significant difference (HSD) post hoc tests. Principal component analysis-linear discriminant analysis (PCA-LDA) was used to highlight the featured cellular drug responses based on the obtained spectral information. For spectral imaging analysis, k-means cluster analysis (KCA) was adopted to clarify the effect of cisplatin dose changes on the subcellular structure and its biochemical composition. The results suggest that the major biochemical changes induced by cisplatin in OS cells undergoing apoptosis are reduced protein and nucleic acid content. Through univariate analysis, the changes in the distribution of nucleic acids in OS cells induced by different doses of cisplatin were obtained. The combination of Raman spectroscopy and multivariate analysis shows that cisplatin mainly acts on the nucleus and causes changes in the secondary structure of proteins. These results indicate that Raman imaging technology has the potential to offer the basis of dose optimization for personalized cancer treatment by helping to understand in vitro cellular drug interactions.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 it