Possible target‐related proteins and signal network of bufalin in A549 cells suggested by both iTRAQ‐based and label‐free proteomic analysis
Bibliographic record
Abstract
Bufalin (BF) exhibited antiproliferation and antimigration effects on human A549 lung cancer cells. To search its target-related proteins, protein expression profiles of BF-treated and control cells were compared using two quantitative proteomic methods, iTRAQ-based and label-free proteomic analysis. A total of 5428 proteins were identified in iTRAQ-based analysis while 6632 proteins were identified in label-free analysis. The number of common identified proteins of both methods was 4799 proteins. By application of 1.20-fold for upregulated and 0.83-fold for downregulated cutoff values, 273 and 802 differentially expressed proteins were found in iTRAQ-based and label-free analysis, respectively. The number of common differentially expressed proteins of both methods was 45 proteins. Results of bioinformational analysis using Metacore(TM) showed that the two proteomic methods were complementary and both suggested the involvement of oxidative stress and regulation of gene expression in the effects of BF, and fibronectin-related pathway was suggested to be an important pathway affected by BF. Western blotting assay results confirmed BF-induced change in levels of fibronectin and other related proteins. Overexpression of fibronectin by plasmid transfection ameliorated antimigration effects of BF. Results of the present study provided information about possible target-related proteins and signal network of BF.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".