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Record W1999402143 · doi:10.1371/journal.pone.0099824

Milk Oligosaccharides over Time of Lactation from Different Dog Breeds

2014· article· en· W1999402143 on OpenAlexaboutno aff
Shirin Macias Rostami, Thierry Bénet, Julie Spears, Arleigh J. Reynolds, Ebenezer Satyaraj, Norbert Sprenger, Sean Austin

Bibliographic record

VenuePLoS ONE · 2014
Typearticle
Languageen
FieldNursing
TopicInfant Nutrition and Health
Canadian institutionsnot available
FundersNestec
KeywordsTetrasaccharideLactoseLactationAnimal scienceOligosaccharideFood scienceMilkingBiologyChemistryBiochemistryPolysaccharideGenetics

Abstract

fetched live from OpenAlex

The partnership of humans and dogs goes back to over 10'000 years, yet relatively little is known about a dog's first extra-uterine nutrition particularly when it comes to milk oligosaccharides. We set out to identify and quantify milk oligosaccharides over the course of lactation from different dog breeds (Labrador retriever, Schnauzer and 3 Alaskan husky crossbreeds). To this end, 2 different chromatographic methods with fluorescence and mass spectrometry detection were developed and one was validated for quantification. Besides lactose and lactose-sulphate, we identified 2 different trisaccharides composed of 3 hexose units, 3'sialyllactose (3'SL), 6'sialyllactose (6'SL), 2'fucosyllactose (2'FL), and a tetrasaccharide composed of 2 hexoses, an N-acetylhexosamine and a deoxyhexose. 3'SL was present at the highest levels in milk of all dog breeds starting at around 7.5 g/L and dropping to about 1.5 g/L in the first 10 days of lactation. 6'SL was about 10 times less abundant and 2'FL and the tetrasaccharide had rather varying levels in the milk of the different breeds with the tetrasaccharide only detectable in the Alaskan husky crossbreeds. The longitudinal and quantitative data of milk oligosaccharides from different dog breeds are an important basis to further our understanding on their specific biological roles and also on the specific nutritional requirements of lactating puppies.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.298
Threshold uncertainty score0.828

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 studies0.0000.000
Scholarly communication0.0000.000
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 head0.030
GPT teacher head0.250
Teacher spread0.221 · 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

Citations25
Published2014
Admission routes1
Has abstractyes

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