Screening sourdough samples for gliadin-degrading activity revealed <i>Lactobacillus casei</i> strains able to individually metabolize the coeliac-disease-related 33-mer peptide
Bibliographic record
Abstract
A selective culture medium containing acid-hydrolyzed gliadins as the sole nitrogen source was used in the search for sourdough-indigenous lactic acid bacteria (LAB) with gliadin-metabolizing activity. Twenty gliadin-degrading LAB strains were isolated from 10 sourdoughs made in different ways and from different geographical regions. Fifteen of the 20 isolated strains were identified as Lactobacillus casei, a species usually reported as subdominant in sourdough populations. The other 5 gliadin-degrading strains belonged to the more commonly encountered sourdough species Leuconostoc mesenteroides and Lactobacillus plantarum. All these strains were shown to be safe in terms of their resistance to antimicrobial agents. When individually incubated with the α2-gliadin-derived immunotoxic 33-mer peptide (97.5 ppm), half of the L. casei strains metabolized at least 50% of it within 24 h. One strain metabolized 82% of the 33-mer peptide within 8 h and made it fully disappear within 12 h. These results reveal for the first time the presence in sourdough of proteolytic L. casei strains with the capacity to individually metabolize the coeliac-disease-related 33-mer peptide.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".