New Approaches in the Manufacture of Biomaterials for Betalactam Allergic Diagnose
Bibliographic record
Abstract
Betalactams are the most widely utilized drugs against infections but are the primary cause of allergic reactions to antibiotic drugs. REF1 An accurate diagnosis of these allergic reactions to betalactams is crucial to avoid the use of unnecessary alternative antibiotics that may reduce efficacy, lead to prolonged treatments, have a higher toxicity or induce bacterial resistance. The most consensual approach to diagnose betalactam allergy are in vivo tests. However, they are not risky free, require experienced personnel and are both time-consuming and expensive for health-care systems, being so in vitro test more appropriate or complementary to the in vivo tests. In vitro tests are not still widely used on account of their low sensitivity. Current efforts are in progress to improve these assays, thus allowing for better diagnosis of allergic responses within patients. REF 2 We report progress in the preparation of new functional materials for in vitro allergic diagnosis testing. In particular, the application of new approaches employing orthogonally functionalised fluorescent dyes based upon 4-amino-1,8 naphthalimide joined with the multivalence of polyamide dendrimers. REF 3 The in vitro diagnosis capabilities of these functional materials was verified by testing on patient sera samples, with results demonstrating their potential for application within the healthcare industry. Acknowledgments: The present study has been supported by MINECO CTQ2016-75870P; by Andalusian Regional Ministry Health (grants: PI-0250-2016); by the European Regional Development Fund (ERDF) and “Plan Propio Universidad de Málaga” (UMA-Andalucía-TECH).
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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".