Deregulated Expression of the <i>Per1</i> and <i>Per2</i> in Human Gliomas
Bibliographic record
Abstract
BACKGROUND: Growing evidence shows that the deregulation of the circadian clock plays an important role in the development of malignant tumors, including gliomas. However, the molecular mechanisms of genes controlling circadian rhythm in glioma cells have not been explored. METHODS: Using reverse transcription polymerase chain reaction and immunohistochemistry techniques, we examined the expression of two important clock genes, Per1 and Per2, in 33 gliomas. RESULTS: In this study, out of 33 gliomas, 28 were Per1-positive, and 23 were Per2-positive. The expression levels of Per1 and Per2 in glioma cells were significantly different from the surrounding non-glioma cells (P<0.01). The difference in the expression rate of Per1 and Per2 in high-grade (grade III and IV) and low-grade (grade 1 and II) gliomas was insignificant (P>0.05). While there was no difference in the intensity of immunoactivity for Per2 between high-grade gliomas and low-grade gliomas (r=-0.330, P=0.061), the expression level of Per1 in high-grade gliomas was significantly lower than that in low-grade gliomas(r=-0.433, P=0.012). CONCLUSIONS: In this study, we found that the expression of Per1 and Per2 in glioma cells was much lower than in the surrounding non-glioma cells. Therefore, we suggest that disturbances in Per1 and Per2 expression may result in the disruption of the control of normal circadian rhythm, thus benefiting the survival of glioma cells. Differential expression of circadian clock genes in glioma and non-glioma cells may provide a molecular basis for the chemotherapy of gliomas.
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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".