Glioma Stem-like Cells are Less Susceptible than Glioma Cells to Sonodynamic Therapy with Photofrin
Bibliographic record
Abstract
Despite remarkable progress in diagnosis and treatment, malignant glioma, a highly lethal cancer of the central nervous system, remains incurable. Although glioma stem-like cells (GSCs) represent a relatively small fraction of the cells in malignant glioma, they can proliferate and self renew extensively, being crucial for tumor recurrence. Cancer treatment by sonodynamic therapy (SDT) chiefly depends on antitumor effects of reactive oxygen species (ROS) generated from a sonosensitizer activated by ultrasound. Although SDT effectively kills glioma cells, its efficiency against GSCs is not established. We attempted to compare the susceptibility of GSCs to SDT, using Photofrin, a porphyrin-derivative photosensitizer, with that of glioma cells. Cell viability and apoptosis assays showed that SDT damaged both GSCs and U251 glioma cells, but GSCs were significantly less susceptible to SDT (p < 0.01). To elucidate the mechanism of the antitumor effects of SDT, we evaluated intracellular ROS production and Photofrin uptake: ROS production and Photofrin content were significantly lower (p < 0.01) in GSCs than in U251 glioma cells. Thus, cellular differences in sonosensitizer uptake and ROS production influence the antitumor effects of SDT. Furthermore, the resistance of GSCs may be caused by decreased sonosensitizer uptake due to ABCG2 overexpression.
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 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".