Changes in Brain Energy and Membrane Metabolism in Glioblastoma following Chemoradiation
Bibliographic record
Abstract
Brain parenchyma infiltration with glioblastoma (GB) cannot be entirely visualized by conventional magnetic resonance imaging (MRI). The aim of this study was to investigate changes in the energy and membrane metabolism measured with phosphorous MR spectroscopy (31P-MRS) in the presumably "normal-appearing" brain following chemoradiation therapy (CRT) in GB patients in comparison to healthy controls. Twenty (seven female, thirteen male) GB patients underwent a 31P-MRS scan prior to surgery (baseline) and after three months of standard CRT (follow-up examination. The regions of interest "contrast-enhancing (CE) tumor" (if present), "adjacent to the (former) tumor", "ipsilateral distant" hemisphere, and "contralateral" hemisphere were compared, differentiating between patients with stable (SD) and progressive disease (PD). Metabolite ratios PCr/ATP, Pi/ATP, PCr/Pi, PME/PDE, PME/PCr, and PDE/ATP were investigated. In PD, energy and membrane metabolism in CE tumor areas have a tendency to "normalize" under therapy. In different "normal-appearing" brain areas of GB patients, the energy and membrane metabolism either "normalized" or were "disturbed", in comparison to baseline or controls. Differences were also detected between patients with SD and PD. 31P-MRS might contribute as an additional imaging biomarker for outcome measurement, which remains to be investigated in a larger cohort.
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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) | 0.000 | 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 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".