1H NMR metabonomics and immune cell signature of milk may reveal insights into subclinical mastitis and quarter interdependence
Bibliographic record
Abstract
Milk metabolome depends on a plethora of factors and on the presence of different cell types and could help understanding the biology of the mammary gland and, possibly, identifying biomarkers for mastitis, tissue repairing and milk quality. To fulfill these expectations, metabolome changes need an accurate characterization under several well-characterized physiological and pathophysiological conditions. The aim of the present work is to study mammary quarters of dairy cows affected by subclinical mastitis (SCM) and acute inflammation compared to healthy animals. The milk metabolome was investigated by 1 H-NMR spectroscopy and by the assessment of somatic cell populations by flow cytometry using a panel of leukocyte markers (CD11b, CD44, CD14, CD4, CD8, CD21). The study was integrated by microbiological evaluations and oxidized proteins (AOPP) determination and results were analyzed by multivariate model. Mammary quarters with the highest CD11b positive cells, suggestive of acute inflammation, were present in SCM-affected cows only, and were characterized by significantly higher AOPP, where the microbiological analysis revealed the presence of minor pathogens. A good PCA separation between healthy and SCM-infected animals was observed (overall error rate: 0.177±0.056) confirming that SCC are associated with modifications of milk metabolome. The classification accuracy was lower (overall error rate: 0.343±0.029) when the mammary quarters were classified on the fraction of CD11b positive cells of quarters from healthy and SCM-affected cows. Interestingly, low-CD11b-SCM samples tended to be misclassified (error rate: 0.460), suggesting the influence of infected neighboring quarters. The results of this work underlay the importance of studying the functional interdependence of mammary quarters in animals affected by SCM. Simple summary This study explored how subclinical mastitis—a mild, often hidden udder infection in dairy cows—affects the metabolites in milk. Nuclear magnetic resonance spectroscopy was used for comparing milk from healthy cows to that produced by cows with subclinical mastitis caused by bacterial infections. We found that the metabolic profile (metabolome) of analyzed milk changed noticeably in infected cows. These changes were linked to both immune cell activity and possible damage to udder tissue. Surprisingly, even parts of the udder that seemed healthy in infected cows sometimes showed altered milk composition. This suggests that infections in one part of the udder can influence nearby quarters or cause broader changes in the cow’s immune and metabolic systems. The findings support the suggestion that milk metabolites could be used to detect early stages of udder infections. The study also highlights how different quarters of the udder are connected, and how even the “healthy” ones can be affected when a cow suffers from mastitis.
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How this classification was reachedexpand
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 | 0.001 | 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 | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".