Boric acid and Calcium fructoborate effect in ovarian cancer
Bibliographic record
Abstract
A2780 ovarian cancer cell line was used to investigate the effects of Boric Acid (BA) and Calcium Fructoborate (CaF) on the proteomic profile of cells in terms of apoptotic pathways and DNA damage/repair pathways. Cell viability and toxicity were determined by the MTT method. Cells were treated with BA and CaF according to the MTT results and collected for protein isolation. Protein isolation was performed from the cell line. Peptides from each sample were obtained for bottom-up proteomic analysis and run on a LC–MS/MS (DionexUltimate 3000 RSLCnano system/Easy Spray/Q-Exactive Plus, Thermo Scientific, USA) The LC-MSMS raw data were processed with the MaxQuant software and searched with Andromeda search engine against the human UniProt database. Comparison of groups were visualized through heatmaps that were prepared on the pHeatmap, an R function to draw heatmaps. Enriched pathways were determined through inputting the Uniprot codes of each protein on the online mapping tool path DIP. Protein-protein interaction networks were analysed through the Integrated Interactions Database of University of Toronto. As a result, Calcium fructoborate (CFB) may have elicited a strong biological response by markedly reducing the expression of apoptosis-related proteins in some samples and appears to cause a more pronounced change in the expression of DNA repair-related proteins than boric acid. These changes are mostly in the direction of repression (negative values), suggesting that it could potentially suppress DNA repair pathways. The CaF group was found to be associated with apoptosis and DNA repair pathways.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".