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Record W2018009078 · doi:10.2527/jas.2008-0939

Empirical prediction of net portal appearance of volatile fatty acids, glucose, and their secondary metabolites (β-hydroxybutyrate, lactate) from dietary characteristics in ruminants: A meta-analysis approach1

2008· review· en· W2018009078 on OpenAlexaff
Christelle Loncke, Isabelle Ortigues Marty, J. Vernet, H. Lapierre, D. Sauvant, Pierre Nozière

Bibliographic record

VenueJournal of Animal Science · 2008
Typereview
Languageen
FieldAgricultural and Biological Sciences
TopicRuminant Nutrition and Digestive Physiology
Canadian institutionsAgriculture and Agri-Food Canada
Fundersnot available
KeywordsPropionateNutrientAnimal scienceRumenChemistryNet energyFood scienceFermentationBiologyBiochemistry

Abstract

fetched live from OpenAlex

The current trend in energy feeding systems for ruminants toward a nutrient-based system requires dietary energy supply to be determined in terms of amount and nature of absorbed energy-yielding nutrients. The objective of this study was to establish response equations on the net portal appearance (NPA) of VFA and glucose, and their secondary metabolites beta-hydroxybutyrate (BHBA) and lactate, to changes in intake level and chemical dietary characteristics based on the Institut National de la Recherche Agronomique Feed Evaluation System for Ruminants. Meta-analyses were applied on published data compiled from the FLORA database, which pools the results on net splanchnic nutrient fluxes in multi-catheterized ruminants from international publications. For each nutrient, several prediction variables were tested. We obtained robust models for intakes up to 30 g of DM x d(-1) x kg of BW(-1) and diets containing less than 70 g of concentrate per 100 g of DM. These models were designed to predict the NPA (mmol x h(-1) x kg of BW(-1)) of total VFA based on the amount of ruminally fermented OM (RfOM) intake [adjusted R(2) (R(2)(adj)) = 0.95; residual means square errors (RMSE) = 0.24], to predict VFA profile (mol/100 mol of total VFA) based on type of RfOM intake (acetate: R(2)(adj) = 0.85, RMSE = 2.2; propionate: R(2)(adj) = 0.76, RMSE = 2.2; butyrate: R(2)(adj) = 0.76, RMSE = 1.09), and to predict the NPA (mmol x h(-1) x kg of BW(-1)) of glucose based on the starch digested in the small intestine independent of ruminant species, and while presenting no interfering factors on the residuals and individual slopes. The model predicting the NPA (mmol x h(-1) x kg of BW(-1)) of BHBA based on the amount of RfOM intake (R(2)(adj) = 0.91; RMSE = 0.036) was species-dependent, and the model predicting NPA (mmol x h(-1) x kg of BW(-1)) of lactate based on starch digested in the rumen (R(2)(adj) = 0.77; RMSE = 0.042) presented a wide dispersion. However, the NPA (mmol x h(-1) x kg of BW(-1)) of BHBA was related to the NPA of both butyrate (R(2)(adj) = 0.85; RMSE = 0.054) and acetate (R(2)(adj) = 0.85; RMSE = 0.052), and the NPA (mmol x h(-1) x kg of BW (-1)) of lactate was related to the NPA of propionate (R(2)(adj) = 0.51; RMSE = 0.096). This research showed that it is possible to accurately predict the amount and nature of absorbed nutrient fluxes based on dietary characteristics in both sheep and cattle. This work aims to quantify the consequences of digestion and portal-drained viscera metabolism on nutrient availability. These results can provide deeper insight into biological processes and help develop improved tools for dietary formulation.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.897
Threshold uncertainty score0.514

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0000.002
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.097
GPT teacher head0.301
Teacher spread0.203 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreReview

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".

Quick stats

Citations50
Published2008
Admission routes1
Has abstractyes

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