Expressions of some vital molecules: glioblastoma multiforme versus normal tissues
Bibliographic record
Abstract
OBJECTIVE: The aim of this study was to assess plasma and/or tissue levels of adhesion and apoptotic molecules, cytokines, nitric oxide metabolites, levels of lipid peroxidation, myeloperoxidase and superoxide dismutase in patients with glioblastoma multiforme and controls. METHODS: All the molecules were evaluated in 25 tumors and 30 controls: 15 were normal healthy subjects for plasma and 15 were normal brain tissues that were collected during autopsy. Commercially available kits for measurements were used. RESULTS: Superoxide dismutase was significantly lower in tumors, while all other molecules were significantly elevated compared to the controls (p=0.0001). Superoxide dismutase negatively correlated with plasma interleukin-1beta (p=0.04) and plasma Fas (p=0.016). Plasma intercellular adhesion molecule-1 and vascular cell adhesion molecule-1 correlated positively with plasma 3-nitrotyrosine (p=0.019) and nitrite/nitrate (p=0.019), respectively. Furthermore, plasma interleukin-1beta also positively correlated with plasma nitrite/nitrate (p=0.003). DISCUSSION: These results suggest that there is a complex relationship between pro- and anti-apoptotic molecules in glioblastoma multiforme pathogenesis. Thus, targeting multiple pathways with advanced chemotherapeutic agents or radiotheraupetic regimens following total resections might be helpful in patients with glioblastoma multiforme since preventing a single pathway does not seem to be reasonable.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".