Changes in Rumen Microbial Profiles and Subcutaneous Fat Composition When Feeding Extruded Flaxseed Mixed With or Before Hay
Bibliographic record
Abstract
Extruded flaxseed (25%) and ground hay (75%) were each fed (DM basis) either together in a total mixed ration (TMR) or as flaxseed first followed by hay (non-TMR) to three pens of eight crossbred steers (n = 24 per diet) for 240 days. Compared to TMR, feeding non-TMR enriched subcutaneous fat with α-linolenic acid (ALA, 18:3n-3) and its biohydrogenation intermediates including vaccenic acid (trans(t)11-18:1), rumenic acid (cis(c)9,t11-conjugated linoleic acid) and conjugated linolenic acid (CLnA). Rumen microbial analysis using QIIME indicated that fourteen genera differed (P ≤ 0.05) between TMR and the non-TMR. Azoarcus and Streptococcus were the only genera which increased in relative abundance in the TMR fed steers, whereas Methanimicrococcus, Moryella, Prevotella, Succiniclasticum, Succinivibrio, Suttenella, and TG5 decreased as compared to steers fed the non-TMR. Among these, Moryella, Succiniclasticum and Succinivibrio, spp. were correlated with fatty acid profiles, specifically intermediates believed to be components of the major biohydrogenation pathway for ALA (i.e.t11,c15-18:2, c9,t11,c15-18:3, and total CLnA). In addition, negative correlations were found between the less abundant Ruminoccocus-like OTU60 and major ALA biohydrogenation intermediates, as well as positive correlations with several intermediates from alternative pathways that did not involve the formation of trans 11 double bonds. The present results suggest a number of pathways for ALA biohydrogenation are operating concurrently in the rumen, with their balance being influenced by diet and driven by less abundant species rather than members of the core bacterial population.
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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) | 0.000 | 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) | 0.001 | 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".