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Influence of starch and casein administered postruminally on small intestinal sodium-glucose cotransport activity and expression

2007· article· en· W2116311741 on OpenAlexaff
Kátia Cylene Guimarães, Sarah Rodrigues Hazelton, J. C. Matthews, Kendall C Swanson, D. L. Harmon, Antônio Ferriani Branco

Bibliographic record

VenueBrazilian Archives of Biology and Technology · 2007
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicRuminant Nutrition and Digestive Physiology
Canadian institutionsUniversity of Guelph
FundersUniversity of California, Los Angeles
KeywordsJejunumIleumCaseinBrush borderDuodenumStarchMaltaseChemistryVesicleSmall intestineAnimal scienceInternal medicineBiologyBiochemistryEndocrinologyMembraneEnzymeMedicine

Abstract

fetched live from OpenAlex

Twenty-four Holstein steer calves (88 ± 3kg) with abomasal catheters were randomly assigned within blocks to one of four treatments. The treatments consisted of four abomasal infusions: water (control), 4 g/kg BW.d-1 of partially hydrolyzed starch (SH), 0.6 g/kg BW.d-1 of casein, and a mix of SH + casein. The small intestine was collected and five equidistan, 1m sites were identified (duodenum, jejunum 1, jejunum 2 jejunum 3 and ileum). Maltase specific activity in mucosal homogenate and brush border membrane vesicles, SGLT1 protein abundance, and sodium-dependent glucose uptake in brush border membrane vesicles did not differ between the calves receiving different abomasal infusion treatments. However, maltase specific activity in homogenates and brush border membrane vesicles increased four-fold from the duodenum to the first jejunal site before declining steadily towards the ileum (p=0.0145 p=0.0020, respectively). The SGLT1 abundance differed by intestinal sampling site (p=0.0162). These data indicated that cattle might not have the ability to alter the capacity for glucose uptake when challenged with different substrates and that the regulation of SGLT1 expression could differ between bovine and other species.

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)0.000
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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.487
Threshold uncertainty score0.726

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.012
GPT teacher head0.246
Teacher spread0.234 · 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 designBench or experimental
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

Citations11
Published2007
Admission routes1
Has abstractyes

Explore more

Same venueBrazilian Archives of Biology and TechnologySame topicRuminant Nutrition and Digestive PhysiologyFrench-language works237,207