Enhancing alkylating agent resistance through ERCC2 gene transfection in human glioma cell line.
Bibliographic record
Abstract
OBJECTIVE: To confirm the enhancing effect of excision repair cross complementing rodent repair deficiency gene 2 (ERCC2) on alkylating agents resistance. METHODS: The authors constructed a pcDNA3-ERCC2 plasmid. The pcDNA3-ERCC2 was transfected into a selected ERCC2 negative human glioma cell line, SKMG-4, using liposome-mediated transfection. After G418 selection, a stable transfected cell line was obtained and tested for cytotoxicity of several alkylating agents. RESULTS: The stable transfectant was obtained and confirmed by RT-PCR as well as Western blot analysis to be strongly expressing ERCC2 at both mRNA and protein levels. The IC(90) ( micro mol/L) of two alkylating agents, cisplatin and melphalan, increased from 1.0 to 1.75 (75%) and 5.6 to 9.0 (61%), respectively, compared with control cell line. CONCLUSION: The present data provided evidences and confirmed the authors' previous results that ERCC2 contributes, at least partially, to alkylating agent resistance in human glioma cell line.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".