Increasing Levels of Dietary Hempseed Products Leads to Differential Responses in the Fatty Acid Profiles of Egg Yolk, Liver and Plasma of Laying Hens
Bibliographic record
Abstract
The limited efficiency with which dietary alpha-linolenic acid (ALA) is converted by hens into docosahexaenoic acid (DHA) for egg deposition is not clearly understood. In this study, dietary ALA levels were increased via the inclusion of hempseed (HS) and hempseed oil (HO) in hen diets, with the goal of assessing the effects on the fatty acid (FA) profiles of total lipids and lipid classes in yolk, liver and plasma. Forty-eight hens were individually caged and fed one of six diets containing either HS:10, 20 or 30, HO:4.5 or 9.0 (%, diet) or a control (containing corn oil), providing a range (0.1-1.28 %, diet) of ALA. Fatty acid methyl esters of total lipids and lipid classes, including phosphatidyl choline (PtdCho) and ethanolamine (PtdEtn) in yolk, plasma and liver were then determined. Levels of n-3 FAs in both total lipids and lipid classes increased in all tissues. ALA and eicosapentaenoic acid (EPA) increased linearly, while docosapentaenoic acid and DHA increased quadratically. The FA profiles of yolk closely reflected levels in both plasma and liver. While ALA was highly concentrated in the triacylglycerol, it was low but equally distributed between PtdCho and PtdEtn in all tissues; however, the net accumulation was lower (P < 0.0001) in liver compared to yolk and plasma. Levels of EPA and ALA in yolk-PtdEtn were linearly (P < 0.0001; R (2) = 0.93) associated, and reflected those in liver-PtdEtn (P < 0.0001; R (2) = 0.90). In the liver, a strong inverse correlation (P < 0.0001; r = -0.94) between PL-DHA and ALA-to-EPA ratio in PtdEtn supports theories of low substrate availability, possibly limiting the conversion of ALA into DHA for egg enrichment.
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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 | 0.000 | 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) | 0.000 | 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".