The Influence of Oxygen Depletion and Photosensitizer Triplet‐state Dynamics During Photodynamic Therapy on Accurate Singlet Oxygen Luminescence Monitoring and Analysis of Treatment Dose Response
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
To date, singlet oxygen ((1)O(2)) luminescence (SOL) detection was predictive of photodynamic therapy (PDT) treatment responses both in vitro and in vivo, but accurate quantification is challenging. In particular, the early and strongest part of the time-resolved signal (500-2000ns) is difficult to separate from confounding sources of luminescence and system noise, and so is normally gated out. However, the signal dynamics change with oxygen depletion during PDT, so that this time gating biases the (1)O(2) measurements. Here, the impact of gating was investigated in detail, determining the rate constants from SOL and direct pO(2) measurements during meso-tetra(hydroxyphenyl)chlorin (mTHPC)-mediated PDT of cells in vitro under well-controlled conditions. With these data as input, numerical simulations were used to examine PDT and SOL dynamics, and the influence of various time gates on cumulative SOL signals. It is shown that gating can underestimate the SOL at early treatment time points by ∼40% and underestimate the cumulative SOL signal by 20-25%, representing significant errors. In vitro studies with both mTHPC and aminolevulinic acid-photosensitizer protoporphyrin IX demonstrate that rigorous analysis of SOL signal kinetics is then crucial in order to use SOL as an accurate and quantitative PDT dose metric.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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 it