Antibacterial Activity of a Natural Clay Mineral against Burkholderia cepacia Complex and Other Bacterial Pathogens Isolated from People with Cystic Fibrosis
Bibliographic record
Abstract
There is an impending crisis in healthcare brought about by a new era of untreatable infections caused by bacteria resistant to all available antibiotics. Thus, there is an urgent need to identify novel antimicrobial agents to counter the continuing threat posed by formerly treatable infections. We previously reported that a natural mineral clay known as Kisameet clay (KC) is a potent inhibitor of the organisms responsible for acute infections. Chronic bacterial infections present another major challenge to treatment by antimicrobials, due to their prolonged nature, which results in repeated exposure to antibiotics and a constant selection for antimicrobial resistance. A prime example is bacteria belonging to the Burkholderia cepacia complex (Bcc), which particularly causes some of the most serious chronic lung infections in patients with cystic fibrosis (CF) associated with unpredictable clinical outcomes, poor prognosis, and high mortality rates. Eradication of these organisms from CF patients with limited effective antimicrobial options is a major challenge. Novel therapeutic approaches are urgently required. Here, we report the in vitro antibacterial activity of KC aqueous suspensions (1–10% w/v) and its aqueous extract (L100) against a collection of extensively and multi-drug resistant clinical isolates of Bcc, Pseudomonas aeruginosa, and Stenotrophomonas maltophilia isolated from patients with CF. These findings present a potential novel therapy for further investigation in the clinic.
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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".