XF-70 and XF-73, novel antibacterial agents active against slow-growing and non-dividing cultures of Staphylococcus aureus including biofilms
Bibliographic record
Abstract
OBJECTIVES: Slow-growing and non-dividing bacteria exhibit tolerance to many antibiotics. However, membrane-active agents may act against bacteria in all growth phases. We sought to examine whether the novel porphyrin antibacterial agents XF-70 and XF-73, which have rapid membrane-perturbing activity against Staphylococcus aureus, retained antistaphylococcal activity against growth-attenuated cells. METHODS: The killing kinetics of XF-70, XF-73 and various comparator agents against exponential phase cultures of S. aureus SH1000 were compared with effects on cells held at 4 degrees C, non-growing cultures expressing the stringent response induced by mupirocin and bacteria in the stationary phase. Biofilms of S. aureus SH1000 were generated with the Calgary device to examine the activities of XF-70 and XF-73 under a further system exhibiting diminished bacterial growth. RESULTS: Cold culture, stringent response and stationary phase cultures remained susceptible to XF-70 and XF-73, which caused > or =5 log reductions in viability over 2 h. During this period the most active comparator agents (chlorhexidine and cetyltrimethylammonium bromide) only promoted a 3 log drop in viability. XF-70 and XF-73 were also highly active against biofilms, with both agents exhibiting low biofilm MICs (1 mg/L) and minimum biofilm eradication concentrations (2 mg/L). CONCLUSIONS: XF-70 and XF-73 remained highly active against various forms of slow-growing or non-dividing S. aureus. The results support the hypothesis that membrane-active agents may be particularly effective in eradicating slow- or non-growing bacteria and suggest that XF-70 and XF-73 could be utilized to treat staphylococcal infections where the organisms are only dividing slowly, such as biofilm-associated infections of prosthetic devices.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".