In vitro elution of amikacin and <scp>Dispersin B</scp> from a polymer hydrogel
Bibliographic record
Abstract
OBJECTIVE: To characterize the in vitro elution of amikacin and Dispersin B (β-N-acetylglucosaminidase) in a degradable hydrogel. STUDY DESIGN: In vitro, prospective study. METHODS: Amikacin (group A; 40 mg/mL), Dispersin B (group D; 70 μg/mL), or combined amikacin and Dispersin B (group AD; 40 mg/mL and 70 μg/mL, respectively) were added to a hydrogel. Ten aliquots per group were incubated in phosphate-buffered saline that was exchanged at 1, 4, 8, 12, and 24 hours and then once daily for 10 days. Eluted amikacin and Dispersin B were quantitated by using an amikacin reagent kit and a Dispersin B enzyme-linked immunosorbent assay kit, respectively. Time point drug concentrations were compared between groups by using repeated-measures analysis of variance, and total drug elution was compared by using an area under the curve calculation. RESULTS: Amikacin alone, Dispersin B alone, and amikacin and Dispersin B combined together underwent rapid elution in the first 24 hours, followed by a gradual decrease over 10 days. The concentration of Dispersin B eluted in group D was higher at 1 day and lower from day 5 to day 10 compared with that in group AD. The concentration of amikacin eluted in group A was higher at 1, 4, and 8 hours and on day 10 and lower on day 1 compared with that in group AD. The total elution of amikacin was greater from group AD compared with that from group A (P = .02). CONCLUSION: Combining amikacin and Dispersin B had an affect on the total elution of amikacin but not Dispersin B. CLINICAL SIGNIFICANCE: The combination of amikacin and Dispersin B in a degradable hydrogel could allow local treatment of complex infections without the requirement for multiple invasive procedures.
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".