In vitro studies of the efficiency of two-photon activation of photodynamic therapy agents
Bibliographic record
Abstract
Age related macular degeneration (AMD) is a major cause of severe vision loss in the older population, due to ingrowth of new leaky blood vessels (neovasculature) from the choriocapillaris, which results in destruction of photoreceptors in the fovea and loss of central vision. "Standard" one-photon (1-γ) photodynamic therapy (PDT) using Visudyne<sup>(R)</sup> is an approved method of AMD treatment but has the potential to damage healthy tissues lying above and below the neovasculature due to photosensitizer accumulation and its wide-beam 1-γ excitation. Highly-targeted two-photon (2-γ) excitation may avoid this, since, due to its non-linear intensity dependence, the probability of 2-γ excitation is greatest in the focal plane, which intrinsically avoids out-of-focus damage to healthy tissues. The aim of the present study is to evaluate the 2-γ efficiency of Visudyne and to compare it to the archetypal photosensitizer Photofrin<sup>(R)</sup>. Since neovascular endothelium is targeted in AMD, an endothelial cell line (YPEN-1) was selected as the in vitro model. 2-γ PDT was delivered using tightly focused ~300 fs laser pulses from a Ti:sapphire laser operating at 850 nm with 90 MHz pulse repetition rate. An assay was developed for quantification of the cellular damage using the permeability stain Hoechst 33258 and the viability stain SYTOX. Visudyne (LD<sub>50</sub>= dose to kill 50% of cells: 500 J/cm<sup>2</sup>, 10 M, 7.2 μg/ml) was about an order of magnitude more effective than Photofrin (LD50 : 7500 J/cm<sup>2</sup>, ~42 μM, 25 μg/ml). We also demonstrate for the first time the quadratic dependence of the cellular response to 2-γ PDT. This in vitro work will lead to the design of optimized in vivo studies in animal models of AMD.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".