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Record W3043035865 · doi:10.1186/s40104-020-00478-7

Shifts in the Holstein dairy cow milk fat globule membrane proteome that occur during the first week of lactation are affected by parity

2020· article· en· W3043035865 on OpenAlexafffund
Mallory C. Honan, Megan J. Fahey, A.J. Fischer-Tlustos, M.A. Steele, S.L. Greenwood

Bibliographic record

VenueJournal of Animal Science and Biotechnology/Journal of animal science and biotechnology · 2020
Typearticle
Languageen
FieldVeterinary
TopicAnimal health and immunology
Canadian institutionsUniversity of AlbertaUniversity of Guelph
FundersNational Center for Research ResourcesNational Institute of General Medical SciencesNational Institutes of HealthLallemandU.S. Department of Agriculture
KeywordsMilkingColostrumLactationProteomeAnimal scienceAutomatic milkingBiologyChemistryFood scienceBiochemistryImmunologyPregnancyAntibodyGeneticsIce calving

Abstract

fetched live from OpenAlex

Abstract Background The milk fat globule membrane (MFGM) proteomes of colostrum and transition milk are rich sources of proteins that are likely important for neonatal calf health. In addition, characterization of these proteomes could also yield valuable information regarding mammary gland physiology of the early postpartum lactating cow. The objectives of this research were to characterize the MFGM proteomes of colostrum and transition milk through sample collections at four timepoints postpartum, including the first milking (M1, colostrum), second milking (M2, transition milk), fourth milking (M4, transition milk), and fourteenth milking (M14, mature milk), and compare these proteomes between multiparous (MP; n = 10) and primiparous (PP; n = 10) Holstein dairy cows. Isolated MFGM proteins were labeled using Tandem Mass tagging and analyzed using liquid chromatography-tandem mass spectrometry (LC-MS/MS). Protein identification was completed using MASCOT and Sequest in Proteome Discoverer 2.2. The scaled abundance values were analyzed using PROC MIXED in SAS to determine the effects of milking (MIL), parity (PAR), and MIL × PAR. The adaptive false-discovery rate (FDR)-adjusted P values were determined using PROC MULTTEST. Protein characterization and bioinformatic analysis were completed using a combination of PANTHER, Blast, and Uniprot. Results A total of 104 common proteins were identified in each of the MFGM samples. Statistical analysis revealed that 70.2% of identified proteins were affected by MIL. Of these, 78.1% were lower in M14 compared with M1, including immune-related proteins lactotransferrin, lactadherin and hemopexin. Parity affected 44.2% of proteins. Of the proteins affected by PAR, 84.8% were higher in MP cows compared with PP cows, including apolipoprotein E and histones 2A, 2B, 3, and 4 b. Butyrophilin subfamily 1 member 1A and annexin 5 were higher in samples from PP cows. Milking × parity affected 32.7% of identified proteins, including lactotransferrin, gelsolin, vitamin D binding protein, and S100 proteins. Conclusions This research supports previous findings that the Holstein MFGM proteome changes rapidly during the first week of lactation. In addition, this research identifies the impact of parity on the colostrum and transition milk MFGM proteomes, which may be important for milk-fed calf health or for the identification of protein biomarkers for mammary functionality.

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)0.004
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
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 score0.488
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.004
Science and technology studies0.0010.008
Scholarly communication0.0000.001
Open science0.0030.001
Research integrity0.0010.002
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 head0.038
GPT teacher head0.290
Teacher spread0.252 · 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.

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

Citations17
Published2020
Admission routes2
Has abstractyes

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