Sci—Fri PM: Delivery — 09: Response of a tumor xenograft model to radiation therapy using magnetic resonance spectroscopy
Bibliographic record
Abstract
9.4T 1H magnetic resonance spectroscopy (MRS) was utilized to track the response of mouse xenograft glioblastoma multiform (GBM) brain tumors to single fraction radiation therapy. Six metabolites were analyzed with LCModel: alanine (Ala), myo‐inositol (Ins), taurine (Tau), creatine and phosphocreatine (Cr + PCr), glutamine and glutamate (Glu + Gln), and total choline (glycerophosphocholine + phosphocholine) (GPC + PCh). 11 mice received 800 cGy of 200 kVp x‐rays, 5 were untreated controls. PRESS spectra (27 μL volumes) were acquired at multiple time points for treated and control animals. In treated animals, all metabolite : water ratios decreased 3 days post‐treatment, with further decreases at day 7, and then increases at day 14 relative to the 7 day mark. Concentrations on day 7 relative to pre‐treatment were as follows: 0.42 (Ala), 0.43 (Ins), 0.68 (Tau), 0.52 (GPC+PCh), 0.49 (Cr + PCr) and 0.78 (Glu + Gln). Metabolite ratios did not correlate with tumor volume in control animals, suggesting a real therapeutic response was observed. Our 1H MRS data suggests that perturbations in the metabolic signature of GBM cancers occur in response to irradiation. Such changes in the metabolite : water concentration ratios could potentially be exploited for the improvement of radiotherapy.
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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.015 | 0.005 |
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".