Phytase dose-dependent response of kidney inositol phosphate levels in poultry
Bibliographic record
Abstract
Phytases, enzymes that degrade phytate present in feedstuffs, are widely added to the diets of monogastric animals. Many studies have correlated phytase addition with improved animal productivity and a subset of these have sought to correlate animal performance with phytase-mediated generation of inositol phosphates in different parts of the gastro-intestinal tract or with release of inositol or of phosphate, the absorbable products of phytate degradation. Remarkably, the effect of dietary phytase on tissue inositol phosphates has not been studied. The objective of this study was to determine effect of phytase supplementation on liver and kidney myo-inositol and myo-inositol phosphates in broiler chickens. For this, methods were developed to measure inositol phosphates in chicken tissues. The study comprised wheat/soy-based diets containing one of three levels of phytase (0, 500 and 6,000 FTU/kg of modified E. coli 6-phytase). Diets were provided to broilers for 21 D and on day 21 digesta were collected from the gizzard and ileum. Liver and kidney tissue were harvested. Myo-inositol and inositol phosphates were measured in diet, digesta, liver and kidney. Gizzard and ileal content inositol was increased progressively, and total inositol phosphates reduced progressively, by phytase supplementation. The predominant higher inositol phosphates detected in tissues, D-and/or L-Ins(3,4,5,6)P4 and Ins(1,3,4,5,6)P5, differed from those (D-and/or L-Ins(1,2,3,4)P4, D-and/or L-Ins(1,2,5,6)P4, Ins(1,2,3,4,6)P5, D-and/or L-Ins(1,2,3,4,5)P5 and D-and/or L-Ins(1,2,4,5,6)P5) generated from phytate (InsP6) degradation by E. coli 6-phytase or endogenous feed phytase, suggesting tissue inositol phosphates are not the result of direct absorption. Kidney inositol phosphates were reduced progressively by phytase supplementation. These data suggest that tissue inositol phosphate concentrations can be influenced by dietary phytase inclusion rate and that such effects are tissue specific, though the consequences for physiology of such changes have yet to be elucidated.
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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 | 0.001 |
| 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".