The Expressions of Wnt/β-catenin Pathway-Related Components in Brainstem Gliomas
Bibliographic record
Abstract
BACKGROUND: The overall prognosis of brainstem gliomas is very poor, and the current treatment cannot significantly prolong the overall survival of these patients; therefore, studying the molecular biological mechanisms of the occurrence and development of brainstem gliomas has important significance for their treatment. The Wnt/β-catenin signaling pathway is closely associated with the occurrence and development of tumors, but its relationship with brainstem gliomas remains unclear. METHODS: This study used Western blot and immunohistochemistry methods to detect the expressions of Wnt/β-catenin signaling pathway-related components such as Wnt-1, Wnt-2, β-catenin and C-myc in six cases of normal brain tissues and 24 cases of brainstem gliomas and analyzed the relationship between their expressions and clinicopathological characteristics. RESULTS: Wnt-1 had no obvious expression in normal brain tissues and did not show any significant difference between high- and low-grade brainstem gliomas; the expressions of Wnt-2, β-catenin and C-myc in high-grade brainstem gliomas were significantly higher than that in low-grade brainstem gliomas and normal brain tissues and were positively correlated with the expression of Ki-67. Moreover, the expressions of Wnt-2 and C-myc were significantly associated with the prognosis of brainstem glioma patients; additionally, there was a trend toward increased β-catenin expression with shorter survival, but there was no statistical difference. CONCLUSIONS: Wnt/β-catenin signaling pathway might be abnormally activated and plays an important role in the occurrence and development of brainstem gliomas. Wnt-2, β-catenin and C-myc may be potential targets for brainstem glioma treatment.
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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".