Exploring Protein-Inorganic Hybrid Nanoflowers and Immune Magnetic Nanobeads to Detect Salmonella Typhimurium
Bibliographic record
Abstract
Early screening of pathogenic bacteria is key to preventing and controlling outbreaks of foodborne diseases. In this study, protein-inorganic hybrid nanoflowers were synthesized for signal amplification and used with a calcium ion selective electrode (Ca-ISE) to establish a new enzyme-free assay for rapid and sensitive detection of Salmonella. Calcium hydrophosphate crystals were first conjugated with polyclonal antibodies against Salmonella to synthesize immune calcium nanoflowers (CaNFs), and streptavidin modified magnetic nanobeads (MNBs) were conjugated with biotinylated monoclonal antibodies against Salmonella to form immune MNBs. After target bacteria were separated using immune MNBs to form magnetic bacteria, immune CaNFs were conjugated with magnetic bacteria to form nanoflower conjugated bacteria. Then, hydrogen chloride was used to release calcium ions from nanoflower conjugated bacteria. After magnetic separation, the supernatant was finally injected as a continuous-flow to fluidic chip with Ca-ISE for specific detection of calcium ions. The supernatant’s potential had a good linear relationship with bacteria concentration, and this assay was able to detect the S. Typhimurium cells as low as 28 colony forming units/mL within two hours. The mean recovery of target bacteria in spiked chicken samples was 95.0%. This proposed assay shows the potential for rapid, sensitive, and on-line detection of foodborne pathogens.
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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".