PSXIV-13 Novel DI/LC-MS/MS-based urinary metabolite signatures for monitoring dairy cows for occurrence of retained placenta.
Bibliographic record
Abstract
The objective of this study was to determine presence of alterations in the urinary metabolite signatures related to amino acids (AAs), acylcarnitines (ACs), biogenic amines (BAs), glycerophospholipids, sphingolipids (SM) and hexose metabolism in cows that expelled fetal membranes normally and those with retained placenta (RP). Six cows that were diagnosed with RP and 20 healthy control cows (CON), similar in parity and body condition score were selected. Urine samples were collected at -8 and -4 wks prior to parturition, the week of RP as well as at +4 and +8 wks postpartum in Holstein dairy cows. AbsoluteIDQ 180 kit (BIOCRATES, Austria) was used to determine urinary metabolite signatures in RP and CON cows. Univariate analysis was performed using R (version 3.0.3; 2008). Metabolomic data were analyzed by MetaboAnalyst. Statistical significance was declared at P < 0.05. At -8 and -4 wks prepartum and the week of RP diagnosis, the urine of cows with RP was characterized by higher concentrations of 19 species of ACs, aspartate, asymmetric dimethylarginine (SDMA) and carnosine (PPPP<0.05). In conclusion, pre-RP and RP cows were characterized by higher excretion of ACs, ADMA, aspartate, and carnosine in the urine. Moreover, RP was preceded by lower concentrations of multiple species of phosphatidylcholines in the urine starting from -8 wks prior to parturition.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".