Bioluminescence Imaging of the Response of Rat Gliosarcoma to ALA‐PpIX‐mediated Photodynamic Therapy<sup>¶</sup>
Bibliographic record
Abstract
Photodynamic therapy (PDT) is a promising modality for the treatment of solid tumors that combines a photosensitizing agent and light to produce cytotoxic reactive oxygen species that lead to tumor cell death. The recent introduction of bioluminescence imaging (BLI), involving the use of the luciferase gene (luc) transferred into target tumor cells, followed by systemic administration of luciferin and detection of the emitted visible chemiluminescence photons, offers the potential for longitudinal imaging of tumor growth and therapeutic response in single animals. We demonstrate in this study the first results of the use of BLI to assess the response of an intracranial brain tumor model (9L rat gliosarcoma) to aminolevulinic acid (ALA)-mediated PDT. Complementary in vitro experiments with the luciferase-transfected 9L cells show that the decrease in the luminescent signal after PDT correlates with cell kill. In vivo imaging shows a decrease in the BLI signal from the tumor after ALA-PDT treatment, followed by tumor regrowth. Furthermore, preliminary studies using cells transfected with a hypoxia-responsive vector show an increase in bioluminescence within 4 h after Photofrin-mediated PDT, demonstrating the ability to observe stress-gene responses. These results suggest that BLI can be used to provide spatiotemporal information of intracranial brain tumor responses after PDT and may serve as a valuable response-endpoint measure.
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.
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 | 0.000 | 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 | 0.001 |
| 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".