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Record W4406821644 · doi:10.1016/j.aninu.2024.11.022

Multi-omics analysis provides new insights into the molecular mechanisms underlying colostral immunoglobulin G absorption in the gut of neonatal goat kids

2025· article· en· W4406821644 on OpenAlexaff
Chao Yang, Yan Cheng, Tianxi Zhang, Kefyalew Gebeyew, A.J. Fischer-Tlustos, Le Luo Guan, M.A. Steele, Zhiliang Tan, Zhixiong He

Bibliographic record

VenueAnimal nutrition · 2025
Typearticle
Languageen
FieldVeterinary
TopicAnimal health and immunology
Canadian institutionsUniversity of British ColumbiaUniversity of Guelph
FundersNatural Science Foundation of Hunan ProvinceChinese Academy of SciencesNational Natural Science Foundation of ChinaInstitute of Subtropical Agriculture, Chinese Academy of Sciences
KeywordsAntibodyBiologyOmicsAbsorption (acoustics)Computational biologyImmunologyBioinformaticsPhysics

Abstract

fetched live from OpenAlex

) in micropinocytosis, which induced differences in serum IgG concentrations. Additionally, 5 differentially expressed miRNAs (miR-2755-3p, miR-10400-5p, miR-71-5p, miR-2944-3p and miR-2411-3p) were predicted to regulate mRNA involved in clathrin-coated vesicles, Fc receptor for IgG (FcRn)-IgG sorting, and macropinosomes formation that may cause the difference in IgG absorption ability. This study provides new insights into the molecular mechanisms controlling IgG absorption of neonatal ruminants and reveals novel mRNA and miRNA markers involved in clathrin-mediated endocytosis and macropinocytosis which may provide the fundamental knowledge related to IgG absorption to support further study in other mammals.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0030.003
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0000.001
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 head0.046
GPT teacher head0.345
Teacher spread0.299 · 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

Citations2
Published2025
Admission routes1
Has abstractyes

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