EVALUATION OF FPA‐FTIR SPECTROSCOPY AS A TOOL IN THE DIFFERENTIATION OF<i>CAMPYLOBACTER JEJUNI</i>FROM<i>CAMPYLOBACTER COLI</i>ISOLATED FROM RETAIL CHICKEN SAMPLES
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
ABSTRACT A method for differentiation of Campylobacter jejuni and Campylobacter coli based on focal‐plane‐array Fourier transform infrared (FPA‐FTIR) spectroscopy was evaluated as an alternative to the current cumbersome methodology. Two types of reference data banks were constructed, one containing FTIR spectra of C. jejuni and C. coli strains, and the other containing FTIR spectra of 11 Campylobacter species. The FPA–FTIR method was tested by identifying 40 C. jejuni and 16 C. coli isolates from poultry, previously identified biochemically and by a multiplex polymerase chain reaction, through comparison of their spectra against the data banks. Employing the C. jejuni and C. coli data bank produced high sensitivity toward C. jejuni (95%) and C. coli (94%) and high overall specificity (95%). With the Campylobacter spp. data bank, the corresponding values were 82, 88 and 84%, respectively. We conclude that FPA‐FTIR spectroscopy is a valuable tool for the differentiation of C. jejuni and C. coli, particularly when C. jejuni and C. coli data banks are used. PRACTICAL APPLICATIONS Foodborne Campylobacter infections are highly prevalent, and therefore proper detection and identification of Campylobacter strains are of paramount importance. Accurate and fast methods for the identification of Campylobacter jejuni and Campylobacter coli are pressing needs. This study presents a rapid, accurate method for differentiation between C. jejuni and C. coli based on Fourier transform infrared (FTIR) spectroscopy. By employing FTIR imaging instrumentation equipped with an infrared microscope and a focal‐plane‐array detector, thousands of spectra are recorded from each isolate in the amount of time a traditional FTIR spectrometer records a single spectrum. In turn, rich biochemical characterizations of bacterial strains, often termed “whole‐organism fingerprints,” are rapidly produced. Comparison of the FTIR spectra of unknown microorganisms against spectral databases of reference strains through the use of principal component analysis allows quick and accurate identification of C. jejuni and C. coli strains, offering an invaluable tool for food safety assurance and surveillance.
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.
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 | 0.002 | 0.001 |
| 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 it