Use of EPO as an adjuvant in PDT of brain tumors to reduce damage to normal brain
Bibliographic record
Abstract
The potential for the use of photodynamic therapy (PDT) after resection of brain tumors is currently limited by the ensuing side effects. These include direct non-specific tissue damage due to the photodynamic action and elevated intracranial pressure as a result of edema and subsequent indirect tissue damage. Erythropoietin (EPO) has been recognized to confer resistance to apoptosis of neurons and endothelial cells in the brain. Here we present preliminary results of the combination of Photofrin – PDT and EPO in the treatment of rat brain astrocytomas in vivo and its ability to increase the therapeutic ratio versus stand alone PDT. The effects of the combination treatment are characterized in normal rat brain based on tissue damage (using TTC as a live cell stain) and monitoring intracranial pressure (ICP) for 24 hours following surgery, using a piezoelectric transducer. To access tumor cell kill, EGFP transduced astrocytoma cell line, CNS-1_gfp, is implanted in the cortex of Lewis rats through a craniotomy, allowed to grow to a diameter of 3mm. Immediately after PDT tumors are excised with the aid of a fluorescence microscope, desaggregated, counted under fluorescence and plated for colony forming assays. Tumor cell kill due to PDT is compared in the presence and absence of EPO.
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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".