Development of an in vitro protein digestibility assay mimicking the chicken digestive tract
Bibliographic record
Abstract
It is difficult to obtain in vivo digestion kinetics data of high protein ingredients using chickens. Collecting kinetics data requires repeated sampling of digesta from the small intestine during the digestion process, which is not easily accomplished due to the anatomical structure of chicken digestive tract. An in vitro technique is proposed for measuring the digestion kinetics of protein sources fed to chickens. The method has a 30 min gastric and 3 h intestinal phase. Five hundred milligram crude protein (CP) equivalent of each meal sample (CP = % N × 6.25) was digested with pepsin (28,260 units) in 50 mL polyethylene centrifuge tubes for 30 min in a shaking water bath (150 strokes/min; 30 mm stroke length) at 41 °C. The 6.5 mL pancreatin was selected as the enzyme concentration for the intestinal phase, during which time 500 μL aliquots were collected at 0, 15, 30, 45, 60, 90, 120, 150, 180 and 240 min. Samples were diluted 1:820 with HCl and sodium acetate buffer, and then mixed with ninhydrin reagent (2:1) at 100 ± 2 °C for 15 min and spectrometric readings taken at 568 nm. To validate the assay, 5 replications of soybean meal (SBM), corn gluten meal (CGM), corn distillers dried grains with solubles (CDDGS), porcine meal (PCM), fish meal (FM) and casein (CA) were digested. The digestion data were modeled with PROC NLIN procedure, and the intra coefficient of variation (CV) assessed using PROC MEANS of SAS 9.4. The digestion values at 180 min were SBM 95 ± 4, FM 93 ± 3, PCM 68 ± 4, CGM 82 ± 3 and CDDGS 70 ± 2. Intra CV for SBM, CGM, CDDGS, PCM and FM were 5%, 5%, 12%, 10% and 2%, respectively. The estimated fractional digestion rates for SBM, CGM, CDDGS, FM and PCM were 0.023, 0.013, 0.009, 0.024 and 0.013, respectively. In conclusion, the proposed in vitro technique estimated the rate and extent of the digestion of CP for the meals with low intra CV.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".