Live E. coli bacteria label-free sensing using a microcavity in-line Mach-Zehnder interferometer
Bibliographic record
Abstract
The paper presents the first study to date on selective label-free biosensing with a microcavity in-line Mach-Zehnder interferometer induced in an optical fiber. The sensing structures were fabricated in a single-mode fiber by femtosecond laser micromachining. In contrast to other studies of this sensing scheme, where only the sensitivity to refractive index changes in the cavity was investigated, this research used chemical surface treatment of the sensor to ensure detection specificity. Immobilized MS2 bacteriophages were applied as recognition elements specifically targeting live E. coli C3000 bacteria. It is shown that the sensor allows for real-time monitoring of biological phenomena taking place on the surface of the microcavity. The developed biosensor exhibits ultrahigh refractive index sensitivity of 15,000 nm/RIU and is capable of detecting live E. coli bacteria concentrations as low as 100 colony forming units (CFU)/mL in liquid volume as low as picoliters.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".