Development Of Sporobeads Coated With Hecad1/2 For Rapid Detection And Capturing Of Pathogenic Listeria Monocytogenes
Bibliographic record
Abstract
Internalin proteins localized at the surface of pathogenic Listeria monocytogenes interfere with E-cadherin to adhere and internalize into mammalian cells.E-cadherin has five extracellular, immunoglobulin-like domains (EC1 to EC5), of which the first domain is sufficient to mediate L. monocytogenes invasion.Immunomagnetic beads employ antibodies that react either with pathogenic or non-pathogenic Listeria.To obtain cost-effective and easy-to-produce beads for detecting pathogenic L. monocytogenes, we cloned and efficiently expressed human E-cadherin domains 1 and 2 (hEcad1/2) in the Bacillus subtilis spore coat.The cDNA sequence encoding hEC1/2 protein 23.7 kDa (MH511517.1)was inserted in pET22b and expressed and purified from Escherichia coli BL21.We used the CotY as a significant structural component of the B. subtilis spore coat to express hEcad1/2.We constructed a recombinant plasmid p1CSV-CotY-N-hEcad1/2 incorporating the cotY-hEcad1/2 gene under the control of the cotY promoter.The constructed plasmid was transformed into B. subtilis KO7 by double cross-over method and an amylase-inactivated mutant was generated.After spore induction, the developed sporobeads showed a high binding affinity for L. monocytogenes 4b.This result demonstrated the potential of human Ecadherin ectodomain 1 and 2 in a practical application involving the detection and capture of pathogenic L. monocytogenes.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".