Antibacterial activity of chemotherapeutic drugs against <i>Escherichia coli</i> and <i>Staphylococcus pseudintermedius</i>
Bibliographic record
Abstract
The ability of chemotherapeutic agents to affect the growth of common bacterial pathogens and the relationship between the effects of chemotherapeutics and antimicrobials is largely unknown. The purpose of this study was to describe the susceptibility of canine bacterial isolates to chemotherapeutic agents and to compare these results to their antimicrobial susceptibility. The effects of bleomycin, doxorubicin, cytarabine, cyclophosphamide, methotrexate, 5-fluorouracil and gemcitabine on the growth of 33 Staphylococcus pseudintermedius isolates and 32 Escherichia coli isolates from dogs was determined by agar dilution. In addition to MICs, the lowest drug concentration associated with a decreased colony size was recorded. Results were compared to the MICs of a panel of antimicrobial agents. Bleomycin consistently inhibited bacterial growth of S. pseudintermedius and E. coli. Doxorubicin inhibited S. pseudintermedius but not E. coli while the opposite was seen for gemcitabine. Reduction in colony size on exposure to 5-fluorouracil for both organisms, and methotrexate for S. pseudintermedius was seen. No observable effect of cyclophosphamide or cytarabine was observed. Associations between elevated MICs to chemotherapeutic drugs and antimicrobial resistance were not found. These results indicate that chemotherapeutic agents affect the growth of bacteria, but do not support a role in the selection of antimicrobial resistance. SIGNIFICANCE AND IMPACT OF THE STUDY: This study shows that chemotherapy drugs commonly used in veterinary oncology have an effect of the growth of canine isolates of Escherichia coli and Staphylococcus pseudintermedius. No associations between susceptibility to chemotherapeutic drugs and antibiotics were found, which does not support selection of antimicrobial resistance by chemotherapy drugs.
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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) | 0.000 | 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 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".