Quantitative Lateral Flow Assay for Meropenem Determination: A Proof-of-Concept Study
Bibliographic record
Abstract
High Resolution Image Download MS PowerPoint Slide Therapeutic drug monitoring (TDM) is essential for optimizing antibiotic dosing, particularly in critically ill patients. However, conventional methods, such as LC/MS, have long turnaround times, limiting timely dose adjustment. We developed a novel competitive lateral flow assay (LFA) format with dual test lines previously validated for vancomycin and adapted it for Meropenem quantification. Using BlaR-CTD, a beta-lactam receptor protein, in place of an antibody and biotinylated BSA–Meropenem conjugated to gold nanoparticles, the LFA produced a concentration-dependent change in test line intensities. A custom image analysis algorithm showed strong correlation with Meropenem concentrations ( R 2 = 0.9537). The platform demonstrates the potential for rapid, point-of-care antibiotic monitoring across diverse healthcare settings. While further optimization is needed for low-concentration accuracy, this proof-of-concept supports broader applicability to other beta-lactams.
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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".