Self-monitored and optically powered fiber-optic device for localized hyperthermia and controlled cell death in vitro
Bibliographic record
Abstract
Localized hyperthermia therapy involves heating a small volume of tissue in order to kill cancerous cells selectively and with limited damage to healthy cells and surrounding tissue. However, these features are only achievable through real-time control of the tissue temperature and heated volume, both of which are difficult to obtain with current heating systems and techniques. This work introduces an optical fiber-based active heater that acts both as a miniature heat source and as a thermometer. The heat-induced damage in the tissue is caused by the conductive heat transfer from the surface of the device, while the heat is generated in an absorptive coating on the fiber by near-infrared light redirected from the fiber core to the surface by a tilted fiber Bragg grating inscribed in the fiber core. Simultaneous monitoring of the reflection spectrum of the grating provides a measure of the local temperature. Localized temperature increases between 0°C and 100°C in 10 mm-long/5 mm-diameter cylindrical volumes are obtained with continuous-wave pump power levels up to 1.8 W. Computational and experimental results further indicate that the temperature rise and dimensions of the heated volume can be maintained at a nearly stable level determined by the input optical power.
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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".