Optimization of Preservation Methods Allows Deeper Insights into Changes of Raw Milk Microbiota
Bibliographic record
Abstract
The temporal instability of raw milk microbiota drastically affects the reliability of microbiome studies. However, little is known about the microbial integrity in preserved samples. Raw cow milk samples were preserved with azidiol or bronopol and stored at 4 °C, or with dimethyl sulfoxide (DMSO) or a mixture of azidiol and DMSO and stored at −20 °C for up to 30 days. Aliquots of 5-, 10-, and 30-day post-storage were treated with propidium monoazide (PMA), then analyzed by sequencing the 16S rRNA gene V3-V4 and V6-V8 regions. The V6-V8 gave a higher richness and lower diversity than the V3-V4 region. After 5-day storage at 4 °C, the microbiota of unpreserved samples was characterized by a drastic decrease in diversity, and a significant shift in community structure. The treatment with azidiol and DMSO conferred the best community stabilization in preserved raw milk. Interestingly, the azidiol treatment performed as well for up to 10 days, thus appearing as a suitable alternative. However, neither azidiol nor bronopol could minimize fungal proliferation as revealed by PMA-qPCR assays. This study demonstrates the preservative ability of a mixture of azidiol and DMSO and provides deeper insights into the microbial changes occurring during the cold storage of preserved raw milk.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".