<i>In Vitro</i> Raman Thermometry Using Gold Nanorod-Decorated Carbon Nanotubes
Bibliographic record
Abstract
Anti-Stokes Raman thermometry, a rapidly evolving field in Raman spectroscopy, was investigated for in situ cellular temperature measurements─a critical aspect in photothermal cancer therapy. In this study, multiwalled carbon nanotubes decorated with gold nanorods (MWCNTs-GNRs) were employed as nanothermometer probes. Characterization involved the analysis of individual Raman spectra acquired at various powers and initial temperatures. The changes observed in the Raman spectra of MWCNTs-GNRs, particularly in response to variations in temperature and excitation power, provide the necessary information to develop a reliable Raman thermometry. This methodology facilitated the extraction of the intrinsic photothermal heating coefficient of MWCNTs-GNRs, offering essential insights into their thermometric properties. An evaluation was extended to incubating MWCNTs-GNRs with prostate cancer PC3 cell lines, where anti-Stokes and Stokes signals were measured at different laser powers to assess in situ cellular temperatures. Temperature maps for a selected area were generated for MWCNTs-GNRs and a single PC3 cell incubated with MWCNTs-GNRs with data standard error analysis performed to indicate a certain level of reliability in temperature measurement accuracy. Cell viability was determined through trypan blue assays, and the obtained temperatures were correlated with viability outcomes at different laser powers. Our investigation encompassed a temperature range spanning 60–100 °C, transcending the critical temperature threshold of 50 °C, which is associated with inducing cell demise. The study highlights the potential of MWCNTs-GNRs as nanothermometer probes for targeted photothermal therapies.
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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 | 0.000 | 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 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".