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Record W2807968719 · doi:10.1093/jas/skaa098

Influence of forage level and corn grain processing on whole-body urea kinetics, and serosal-to-mucosal urea flux and expression of urea transporters and aquaporins in the ovine ruminal, duodenal, and cecal epithelia

2020· article· en· W2807968719 on OpenAlexafffund
Karen A. Scott, G.B. Penner, T. Mutsvangwa

Bibliographic record

VenueJournal of Animal Science · 2020
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicRuminant Nutrition and Digestive Physiology
Canadian institutionsUniversity of Saskatchewan
FundersGovernment of SaskatchewanNatural Sciences and Engineering Research Council of Canada
KeywordsUreaForageLatin squareAnimal scienceDry matterExcretionRumenChemistryInternal medicineFecesEndocrinologyBiologyBiochemistryFermentationAgronomyMedicineEcology

Abstract

fetched live from OpenAlex

The objectives were to determine the effects of forage level and grain processing on whole-body urea kinetics, N balance, serosal-to-mucosal urea flux (Jsm-urea), and messenger ribonucleic acid (mRNA) abundance of urea transporter-B (UT-B; SLC14a1) and aquaporins (AQP) in ovine ruminal, duodenal, and cecal epithelia. Thirty-two wether lambs were blocked by body weight into groups of four and assigned to one of four diets (n = 8) in a 2 × 2 factorial design. Dietary factors were forage level (30% [LF] vs. 70% [HF]) and corn grain processing (whole-shelled [WS] vs. steam-flaked [SF]). Four blocks of lambs (n = 4) were used to determine urea kinetics and N balance using 4-d [15N15N]-urea infusions with concurrent fecal and urine collections. Lambs were killed after 23 d of dietary adaptation. Ruminal, duodenal, and cecal epithelia were collected to determine Jsm-urea and mRNA abundance of UT-B and AQP. Lambs fed LF had greater intakes of dry matter (DMI; 1.20 vs. 0.86 kg/d) and N (NI; 20.1 vs. 15.0 g/d) than those fed HF (P < 0.01). Lambs fed SF had greater DMI (1.20 vs. 0.86 kg/d) and NI (20.6 vs. 14.5 g/d) than those fed WS (P < 0.01). As a percentage of NI, total N excretion was greater in lambs fed HF compared with those fed LF (103% vs. 63.0%; P < 0.01) and was also greater in lambs fed WS compared with those fed SF (93.6% vs. 72.1%; P = 0.02). Retained N (% of NI) was greater in lambs fed LF compared with those fed HF (37.0% vs. -2.55%; P < 0.01). Lambs fed SF had a greater (P = 0.02) retained N (% of NI; 28.0% vs. 6.50%) compared with those fed WS. Endogenous urea production (UER) tended (P = 0.09) to be greater in lambs fed HF compared with those fed LF. As a proportion of UER, lambs fed HF had a greater urinary urea-N loss (0.38 vs. 0.22) and lower urea-N transferred to the gastrointestinal tract (GIT; 0.62 vs. 0.78) or urea-N used for anabolism (as a proportion of urea-N transferred to the GIT; 0.12 vs. 0.26) compared with lambs fed LF (P < 0.01). Ruminal Jsm-urea was unaffected by diet. Duodenal Jsm-urea was greater (P < 0.01) in lambs fed HF compared with LF (77.5 vs. 57.2 nmol/[cm2 × h]). Lambs fed LF had greater (P = 0.03) mRNA expression of AQP3 in ruminal epithelia and tended (P = 0.06) to have greater mRNA expression of AQP3 in duodenal epithelia compared with lambs fed HF. Expression of UT-B mRNA was unaffected by diet. Our results showed that feeding more ruminally available energy improved N utilization, partly through a greater proportion of UER being transferred to the GIT and being used for anabolic purposes.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.034
GPT teacher head0.260
Teacher spread0.226 · 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 source (direct Gemma or distilled Codex), not a consensus.

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

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

Citations9
Published2020
Admission routes2
Has abstractyes

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