Single-Domain Antibody-Nanoparticles: Promising Architectures for Increased <i>Staphylococcus aureus</i> Detection Specificity and Sensitivity
Bibliographic record
Abstract
Because antibodies are highly target-specific and nanoparticles possess diverse, material-dependent properties that can be exploited in order to label and potentially identify biomolecules, the development of antibody-nanoparticle conjugates (nanoconjugates) has huge potential in biodiagnostics. Here, we describe a novel superparamagnetic nanoconjugate, one whose recognition component is a single-domain antibody. It is highly active toward its target Staphylococcus aureus, displays long shelf life, lacks cross-reactivity inherent to traditional homologue whole antibodies, and captures a few dozen S. aureus cells in a mixed cell population with ~100% efficiency and specificity. We ascribe the excellent performance of our nanoconjugate to its single-domain antibody component and recommend it as a general purpose recognition element.
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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 | 0.000 | 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".