Temporal changes in biochemical indices of sulphur amino acid (SAA) metabolism in the vitamin B‐6 deficient piglet
Bibliographic record
Abstract
The impact of vitamin B‐6 deficiency on temporal changes in markers of SAA metabolism was determined in weanling pigs. Pigs (5.3 kg; n=6 per group) were fed a semi‐purified diet (20.5% casein; 3474 kcal ME/kg) containing either 0 or 3 mg pyridoxine HCl/kg diet, using a pair‐feeding design. Feed intake was measured continuously, and growth data and blood samples were collected weekly for 6 weeks. Animals were killed at the end of 6 weeks, and tissue samples harvested. Plasma pyridoxal‐5‐phosphate (PLP) was quantified by radioenzymatic assay. Total homocysteine (Hcy) and cysteine (Cys) were measured by reverse‐phase HPLC. From the 4 th week until the end of trial, vitamin B‐6 deficiency decreased average daily gain and feed efficiency (p<0.05), despite the pair‐feeding. In B‐6 deficient pigs, plasma PLP decreased substantially after the first week (37 vs.14 nM). At 6 weeks, plasma PLP was significantly higher in control vs. B‐6 deficient pigs (36 vs 5 nM; p<0.0001). Significant decreases in plasma Cys and increases in plasma Hcy, due to B‐6 deficiency, were detected from the 3 rd week (p<0.0001). From the 3 rd to 6 th week, plasma Hcy in controls was 17.70, 13.51, 11.48, and 13.28 μ M, respectively. Plasma Hcy in deficient pigs, however, was 332.48, 403.19, 337.94, and 479.91 μM, respectively. Similarly, vitamin B‐6 deficiency decreased hepatic Cys (164.03 vs. 86.31 nmol/g liver, p=0.04) but increased hepatic Hcy (16.06 vs. 307.41 nmol/g liver, p=0.001). These results provide justification for a 4 week period to establish a vitamin B‐6 deficiency in piglets. This data is critical to the implementation of studies designed to quantify the impact of vitamin B‐6 status on rates of transsulphuration in pigs. Supported by NSERC
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".