Label-free Gram-negative bacteria detection using bacteriophage-adhesin-coated long-period gratings
Bibliographic record
Abstract
This paper presents a novel application of a highly sensitive sensor based on long-period gratings (LPGs) coated with T4 bacteriophage adhesin for Gram-negative bacteria detection. We show here, that the sensor evidently recognizes Escherichia coli K-12 (PCM2560), whereas in the reference tests - ELISA and BIAcore - the results are questionable. For LPGs sensor the resonant wavelength shift observed for E. coli K-12 was approximately half of that measured for E.coli B (positive control). The BIAcore readings (RU) for E. coli K-12 were at 10% level of the signal obtained for E .coli B. These results confirm the improved sensitivity of the LPGs sensor. Moreover, we also show that application of adhesin may allow for efficient detection of E. coli O111 (PCM418), Klebsiella pneumoniae O1 (PCM1) and Yersinia enterocolitica O1 (PCM1879). The specificity of binding bacteria by the adhesin is discussed and it is determined by a distinct region of lipopolysaccharide receptors and/or by the presence of outer-membrane protein C in an outer membrane of Gram-negative bacteria.
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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) | 0.000 | 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 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".