Collagen and hyaluronan at wound sites influence early polymicrobial biofilm adhesive events
Bibliographic record
Abstract
BACKGROUND: Wounds can easily become chronically infected, leading to secondary health complications, which occur more frequently in individuals with diabetes, compromised immune systems, and those that have suffered severe burns. When wounds become chronically infected, biofilm producing microbes are often isolated from these sites. The presence of a biofilm at a wound site has significant negative impact on the treatment outcomes, as biofilms are characteristically recalcitrant to removal, in part due to the formation of a protective matrix that shield residents organisms from inimical forces. Pseudomonas aeruginosa and methicillin-resistant Staphylococcus aureus (MRSA) are two of the organisms most prevalently isolated from wound sites, and are of particular concern due to their elevated levels of antibiotic resistance, rapid growth, and exotoxin production. In order to understand the biofilm forming abilities of these microbes in a simulated wound environment we used a microtiter plate assay to assess the ability of these two organisms to bind to proteins that are typically found at wound sites: collagen and hyaluronan. RESULTS: Collagen and hyaluronan were used to coat the wells of 96-well plates in collagen:hyaluronan ratios of 0:1, 3:1, 1:1, 1:3, and 1:0 . P. aeruginosa and MRSA were inoculated as mono- and co-cultures (1:1 and a 3:1 MRSA: P. aeruginosa). We determined that coating the wells with collagen and/or hyaluronan significantly increased the biofilm biomass of attached cells compared to an uncoated control, although no one coating formulation showed a significant increase compared to any other combination. We also noted that the fold-change increase for MRSA upon coating was greater than for P. aeruginosa. CONCLUSIONS: Our study suggests that the presence of collagen and/or hyaluronan at wound sites may be an important factor that influences the attachment and subsequent biofilm formation of notorious biofilm-formers, such as MRSA and P. aeruginosa. Understanding the kinetics of binding may aid in our comprehension of recalcitrant wound infection development, better enabling our ability to design therapies that would prevent or mitigate the negative outcomes associated with such infections.
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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".