Localized thermal tumor destruction using dye‐enhanced photothermal tumor therapy
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVE: In an attempt to develop a new therapeutic approach for highly localized thermal destruction of tissue targets that lack natural pigmentation, the potential of in-vivo dye-enhanced photothermal therapy (PTT) was investigated. PTT involves the application of an exogenous absorber, which accumulates in metabolically active tissues, followed by non-invasive light irradiation, using appropriate wavelengths, exposure durations, and irradiances. The chromophore used, palladium(II) octabutoxynaphthalocyanine (PdNc(OBu)8 ), strongly absorbs in the near infrared wavelength range which thus permits good penetration depth of the exciting light. The predominant de-excitation routes of the chromophore are radiationless thermal processes. MATERIALS AND METHODS: Using a BALB/c mouse model with a subcutaneously implanted syngeneic EMT6 adenocarcinoma, 96-100 hours after intraperitoneal application of PdNc(OBu)8 , tumor, and surrounding tissue were irradiated with a 830 nm continuous wave diode laser applying 30 Wcm(-2) for 10-20 seconds. Treatment parameters were based on theoretical calculations. RESULTS: Histological evaluation of thermal effects on tumor and normal tissue showed that after PdNc(OBu)8 -enhanced photothermal treatment, highly localized and selective thermal damage of the tumors was achieved. The necrotic tumor area was invaded by inflammatory cells, including neutrophils, macrophages, mast cells, and lymphocytes, thus reflecting a prominent host immune response. In tumors treated with PTT for 15 or 20 seconds, respectively, only few surviving tumor cells were detected underneath the epidermis. Adjacent peripheral normal tissue including skin and muscle remained completely unaffected. CONCLUSION: This study highlights the potential of achieving irreversible thermal tissue damage closely localized to the target tissue when PdNc(OBu)8 is used in combination with continuous-wave light.
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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) | 0.001 | 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".