Starvation after Cobalt-60 γ-Ray Radiation Enhances Metastasis in U251 Glioma Cells by Regulating the Transcription Factor SP1
Bibliographic record
Abstract
Radiation is of clinical importance during glioma therapy; however, vasculature damage is observed over the treatment course. This type of tissue damage might lead to starvation conditions, affecting tumor metastasis. To test this possibility, we compared starvation conditions in conjunction with radiation treatment to monitor metastatic ability in the U251 glioma cell line. Transcriptome, western blot, and immunofluorescence analyses were used to measure the RNA and protein expression changes of the U251 cells after various treatments. We found that starvation combined with radiation treatment yielded the most significant expression changes in metastasis-related factors compared to that in the control groups. In addition, a metastasis assay was used to directly measure the metastatic ability of the treated cells, which confirmed that the U251 cells treated with starvation combined with radiation possessed the highest metastatic ability. Furthermore, bioinformatics analysis demonstrated that SP1 represented a common transcription factor associated with changes in metastasis-related factors. Blocking SP1 activity by an inhibitor suppressed the starvation-plus-radiation treatment-mediated enhancement of U251 cell metastasis. Our study provides the first evidence that starvation caused by radiation might play a significant role in enhancing the ability of the glioma cell line U251 to metastasize via regulation of the transcription factor SP1.
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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".