Development of analytical methods for the quantification of amoxicillin in human plasma and for the determination of Minimal Biofilm Eradication Concentration and Biofilm Prevention Concentration
Bibliographic record
Abstract
High doses (>4g/day) of amoxicillin for a long time period (>2 weeks) is currently indicated in the treatment of Bone and Joint Infections (BJI) and Infective Endocarditis (IE) caused by susceptible bacteria in order to be active on planktonic bacteria and biofilm. We performed an observational study in the University Hospital of Grenoble to determine if the plasma concentrations were active on planktonic bacteria and if they could eradicate or prevent the biofilm formation. Between July 2017 and February 2019, 20 patients for whom 22 amoxicillin susceptible bacteria were isolated, were included. LC-MS/MS amoxicillin dosage method was developed according to ISO 15189 standard. Minimal Inhibitory Concentration (MIC), Minimal Biofilm Eradication Concentration (MBEC) and Biofilm Prevention Concentration (BPC) were determined thanks to the “Calgary Biofilm Device”. Plasma concentrations measured were highly variable (<5mg/L to 126,4 mg/L). Based on determined MBEC, amoxicillin concentrations are not sufficient in monotherapy to eradicate E. faecalis biofilm but can eradicate C. acnes biofilm. These in vitro results seem relevant as 5/5 C. acnes infections were cured and 2/5 E. faecalis infections were not. Regarding Streptococci, results depend on the species. Six patients underwent surgery before starting treatment. So, it seems interesting to correlated patients’ outcome with BPC (in process of determination).
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 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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.002 |
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".