Kisameet Clay Exhibits Potent Antibacterial Activity against the ESKAPE Pathogens
Bibliographic record
Abstract
UNLABELLED: The ESKAPE (Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, and Enterobacter species) pathogens cause an increasing number of nosocomial infections worldwide since they escape the inhibitory effect of the available antibiotics and the immune response. Here, we report the broad-spectrum and potent antibacterial activity of Kisameet clay, a natural clay mineral from British Columbia, Canada, against a group of multidrug-resistant ESKAPE strains. The results suggest that this natural clay might be developed as a therapeutic option for the treatment of serious infections caused by these important pathogens. IMPORTANCE: More than 50 years of misuse and overuse of antibiotics has led to a plague of antibiotic resistance that threatens to reduce the efficacy of antimicrobial agents available for the treatment of infections due to resistant organisms. The main threat is nosocomial infections in which certain pathogens, notably the ESKAPE organisms, are essentially untreatable and contribute to increasing mortality and morbidity in surgical wards. The pipeline of novel antimicrobials in the pharmaceutical industry is essentially empty. Thus, there is a great need to seek for new sources for the treatment of recalcitrant infectious diseases. We describe experiments that demonstrate the efficacy of a "natural" medicine, Kisameet clay, against all of the ESKAPE strains. We suggest that this material is worthy of clinical investigation for the treatment of infections due to multidrug-resistant organisms.
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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) | 0.001 | 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 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".