Factors Of Chemotherapy From Different Classes Combined With USMB Effect Drug Efficacy In Breast Cancer Cells
Bibliographic record
Abstract
Ultrasound microbubble therapy (USMB) has shown to increase cell membrane permeability, minimize interaction between normal tissue and cytotoxic agents from the requirement of lower chemotherapy dosages, and permits the localized delivery of chemotherapy. The drug efficacy from combined treatment of chemotherapy and USMB is dependent on many variables including the chemotherapy agent, USMB parameters, and tumour cell type. This study treated a human breast cancer cell line with USMB and agents from two different chemotherapy classes, alkylating agents (oxaliplatin and carboplatin) and metabolic inhibitors (gemcitabine and 5-fluorouracil). Colony assays were used to measure cell viability of cells treated with chemotherapy alone, and chemotherapy combined with USMB over increasing concentrations of chemotherapy. The cell viability results showed that the alkylating agents performed better than the metabolic inhibitors when combined with USMB. This study suggests that chemotherapy's internalization method and mechanism of action contribute to the efficacy of combined 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) | 0.000 | 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) | 0.002 | 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".