Platinum-Based Agents for Individualized Cancer Treatment
Bibliographic record
Abstract
Platinum-based agents are important drugs or drug candidates for cancer chemotherapy. Traditional platinum drugs including the globally approved cisplatin, carboplatin and oxaliplatin are neutral platinum (II) complexes with two amine ligands and two additional ligands that can be aquated for further binding with DNA. The platinum-DNA adducts can impede cellular process and lead to cellular apoptosis. Tumor resistance to platinum drugs has become a very challenging problem to overcome. Individualized cancer treatment using different strategies to circumvent the platinum-drug resistance in cancer patients is of great importance. Structural modification of traditional platinum drugs, combination therapy using platinum drugs with other agents and improved delivery of platinum drug to tumor sites are major strategies developed to overcome existed problems in chemotherapy using traditional platinum drugs. Platinum-based agents with respect to their structure, mechanism of action and strategies developed for improved efficacy in cancer treatment have been summarized in this paper with the perspective of developing new platinum drugs or platinum-based therapy for individualized cancer 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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.003 |
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".