EFFECT OF PULSED MAGNETIC FIELDS ON THE EXPRESSION LEVELS OF TUMOR SUPPRESSOR GENES IN HUMAN T98G GLYOBLASTOMA CELL LINE
Bibliographic record
Abstract
Aim: to study the effect of a pulsed magnetic field (PMF) on the expression of key tumor suppressor genes, such as aPc, MLH, and MGMt in human t98G glioblastoma cell line. material and methods . the PMF with the intensity of 15 and 300 mt was used alone and in combination with ionizing radiation at a single dose of 10 Gy. to perform ionizing radiation, theratron Equinox 60 co unit Best theratronics Ltd., Ottawa, canada) was used. the source of the pulsed magnetic field was Neuro-Ms / D therapeutic advanced device of the Neurosoft company. Live and dead cells were determined in NanoEntekJuliFl cell counter (Korea) using a 0.4 % trypan blue solution to stain dead cells. total RNa was extracted according to the protocol of the manufacturer trizol with changes: the aqueous phase was separated with trizol reagent twice. the quantitative measurement of the isolated RNa was carried out on a Qubit 2.0 fluorimeter using a kit of reagents with the Quant-it RNa assayKit RNa intercalating dye (Life technologies, usa). the expression of MLH, aPc, and MGMt genes was evaluated by Rt-PcR using a cFx96 amplifier (BioRad, usa). Data were analyzed using the cycle threshold (ct) method with normalization for tBP gene expression in each sample. Relative expression of the genetic locus (Exp) was calculated by the 2-Δct method. statistical analysis of the results was carried out using the statictica v10 software package. Results . One day after exposure to PMF, significant differences in the MGMt expression level compared to the control were found (p<0.05). a significant decrease in the transcriptional activity of the MGMt gene in glioblastoma cells was observed with PMF intensity of 15 mt, and correlated with the cell mortality rate. No changes in the mortality rate were observed after radiation exposure combined with 15 mt PMF. However, the mortality rate decreased from 18.7 % to 15 % after radiation exposure combined with 300 mt PMF. Conclusion . the effect of reduction in the transcriptional activity of MGMt in t98G glioblastoma cells and the effect of PMF as a monofactor on their viability characterize the magnetic susceptibility of tumor cell mechanisms. Given the multidirectional nature of the combined interaction of ionizing radiation and PMF, it is necessary to emphasize the importance of choosing and justifying the role of biotropic parameters of PMF in order to exclude a negative effect on the 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 | 0.000 | 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".