Third Prize: Effects of Subinhibitory Concentrations of Ciprofloxacin on <i>Staphylococcus Saprophyticus</i> Adherence and Virulence in Urinary Tract Infections
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Staphylococcus saprophyticus is a frequent cause of both uncomplicated and complicated urinary tract infections (UTI) in young females and has recently been established as the most prominent gram-positive uropathogen. Although the effects of subinhibitory concentrations of antimicrobials on numerous other pathogenic bacteria have been studied, little is known regarding how S saprophyticus responds under such conditions. MATERIALS AND METHODS: In this study, we investigated the effects of subminimum inhibitory concentrations (MIC) of ciprofloxacin (CIP) on S saprophyticus attachment to glass microscope slides, ureteral stent material, and T24 bladder cells, as well as its effects on S saprophyticus-induced proinflammatory cytokine expression in bladder cells. RESULTS: Adherence to glass microscope slides, ureteral stent material, and bladder cell monolayers were all significantly increased in the presence of sub-MIC levels of CIP. While the S saprophyticus challenge of T24 bladder cell monolayers significantly upregulated both interleukin (IL)-6 and IL-8 expression, sub-MIC CIP abrogated these effects, returning their secretion to control levels. CONCLUSIONS: Our results demonstrate that exposure to sub-MIC CIP increases S saprophyticus adherence to both abiotic and biotic surfaces including urinary device material and cultured bladder cells. In addition, low levels of this antimicrobial downregulate S saprophyticus-stimulated proinflammatory cytokine secretion in the bladder. These changes may make S saprophyticus more effective at colonizing the urinary tract and highlights the need for clinicians to consider the impact of subinhibitory concentrations of antimicrobials on bacteria when designing treatment strategies to manage UTI.
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 | 0.001 |
| 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".