Investigation of interaction between human hemoglobin A<sub>0</sub> and platinum anticancer drugs by capillary isoelectric focusing with whole column imaging detection
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
CIEF with whole column imaging detection (WCID) was used to investigate the interaction of platinum-based anticancer drugs, cis-platinum(II) diamine dichloride (cisplatin) and [SP-4-2-{1R-trans)]-(1,2-cyclohexanediamine-N,N')[ethanedioata(2-)-O,O']platinum (oxaliplatin), with human hemoglobin A(0) (Hb). This technique facilitates the investigation and characterization of the formation of adducts between drugs and proteins. Cisplatin and oxaliplatin were mixed with the target protein at different concentrations (0:1, 1:1, 1:10, 1:50, and 1:100), and the reaction mixtures were incubated for 0, 0.5, 1, 12, 24, 48, and 72 h at 37 degrees C in a water-bath. The focused Hb-drug adduct profiles were imaged by WCID. At higher drug to protein molar ratios (for both oxaliplatin and cisplatin), the results exhibit significant changes in the peak shapes and heights, which may indicate the destabilization of the protein. However, the conformational change was less evident at lower molar ratios. In addition, a major pI shift was observed for the oxaliplatin reaction mixtures (for 1:10, 1:50, and 1:100 ratios). In comparison with previously reported findings obtained by other analytical methods, conclusions were drawn about the validity of CIEF as a simple and convenient method for the investigation of protein-drug interactions. These results may provide useful information for further understanding the activity and toxicity of these chemotherapeutic drugs and improving their clinical performance.
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.
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) | 0.000 | 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) | 0.000 | 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 it