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Record W4409838709 · doi:10.1016/j.ajcnut.2025.04.024

Single-cell transcriptomics reveals that human milk feeding shapes neonatal immune cell interleukin signaling pathways in a nonrandomized clinical trial

2025· article· en· W4409838709 on OpenAlexfundno aff
Michael L. Salinas, Bharath Kumar Mulakala, Laurie A. Davidson, James J. Cai, Sharon M. Donovan, Robert S. Chapkin, Laxmi Yeruva

Bibliographic record

VenueAmerican Journal of Clinical Nutrition · 2025
Typearticle
Languageen
FieldNursing
TopicInfant Nutrition and Health
Canadian institutionsnot available
FundersAgricultural Research ServiceRoyal Society of CanadaTexas A and M UniversityCancer Prevention and Research Institute of Texas
KeywordsImmune systemBiologyTranscriptomeCellSignal transductionCell biologyInterleukinComputational biologyBioinformaticsImmunologyCytokineGeneticsGeneGene expression

Abstract

fetched live from OpenAlex

BACKGROUND: Several studies have indicated the benefits of human milk feeding to infants however, mechanisms behind positive health outcomes have not been investigated. OBJECTIVES: The study aimed to characterize circulating immune cell subpopulation gene expression in human milk-fed (HMF) compared with cow milk formula-fed (FF) infants using single-cell transcriptomics. METHODS: Peripheral blood mononuclear cells (PBMCs) were isolated from healthy HMF (n = 6), and FF (n = 3) infants who were 3-3.5 mo old and enrolled in a nonrandomized clinical trial. Single-cell RNA sequencing was used to generate a PBMC atlas and evaluate gene expression in immune cell subsets. Differential expression analysis was performed on each cell type independently after clustering the cells by similar marker gene expression using the scGEAToolbox. Differentially expressed genes were subjected to pathway analyses using an online functional enrichment analysis program. RESULTS: The relative abundance (%) of T and B lymphocytes, natural killer (NK) cells, and plasmacytoid dendritic cells were similar, whereas monocytes were higher in FF infants than in HMF infants (22.6 ± 10.7 compared with 8.3 ± 5.6; P = 0.0314). In addition, innate and adaptive immune cells from FF infants exhibited a higher activation state compared with HMF infants. We identified 16 distinct cell subsets from the major immune cell types: 3 monocyte subsets, 4 NK subsets, 2 B cell subsets, and 7 T cell subsets. Transcriptional profiles of each peripheral innate and adaptive immune cell subtype varied between HMF and FF infants. Pathway enrichment analysis of cell-specific transcriptional changes within subsets of major cell types revealed that the interleukin (IL)-4/IL-13 signaling pathways were upregulated in FF infants relative to HMF infants. CONCLUSIONS: These findings suggest that human milk downregulates peripheral immune cell cytokine transcriptional signatures linked to allergic inflammation and infection relative to formula feeding.

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)0.003
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.085
GPT teacher head0.390
Teacher spread0.305 · 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 designNon-randomized trial
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

Citations7
Published2025
Admission routes1
Has abstractyes

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