Progress in photodynamic method of tumor diagnosis and treatment
Bibliographic record
Abstract
Development of photodymanic method for tumors diagnosis and therapy (PDT) was observed in the early 70's. The third stage of clinical investigations in the USA, Canada, Japan, and in European countries has begun since 1988. Tumors treatment consists in selective oxidation of biological material of a tumor tissue by a singlet oxygen or radical forms. Such forms are generated due to molecular oxygen, soluted in cells, exogeneously introduced photosensitiser which is better accumulated in the diseased tissues than in healthy ones and delivered light of adequate power and wavelength. Such therapeutic method allows selective destruction of tumor tissues, simultaneously protecting the healthy ones. Tumors diagnostics relies on localisation of photosensitisers, absorbed in tumor tissues, by means of fluorometric methods. Investigations with PDT method are carried out in several direction, i.e., synthesis and application of new photosensitisers, design of new light sources, radiation dosimetry in tissues, mechanisms of photochemical reaction, and clinical applications of PDT method. PDT method for tumors treatment compared to traditional ones (surgery, irradiation, chemotherapy) is much more selective but is constrained by many factors limiting its intensive development and clinical applications. In Poland the PDT method is applied in several clinics for treatment of skin tumors, lungs, gynaecological sphere, and urinary bladder. The paper presents current status and perspectives of development of this method. Technology for production of our own photosensitisers (aminoacid complexes and protoporphyrines) is implemented and adequate diagnostic and therapeutic systems have been constructed. Investigations required for specimens admission to clinical application were carried out.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 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".