ArticleMolecular medicine (Cambridge, Mass.)2026
Preterm birth skews the developmental trajectory of myeloid-derived suppressor cells in the first 48 hours of life: single-cell transcriptomics and inferred intercellular communication.
Article in Molecular medicine (Cambridge, Mass.), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
16 authors.
Funding
Abstract
backgroundPrematurity is a leading cause of neonatal and childhood mortality, with infections driving early deaths. Innate immunity provides frontline defense after birth and is shaped in part by myeloid-derived suppressor cells (MDSCs). The role of MDSCs in regulation of neonatal immunity, especially in the context of prematurity, remains elusive. We sought to understand the transcriptional landscape of neonatal immune myeloid regulators, specifically differences between preterm and full-term neonates. Insight into specific cellular networks could help understand how to skew preterm MDSCs’ development towards classical immunotolerant and anti-microbial mechanisms.
methodsThis cross-sectional study used single-cell RNA sequencing to characterize the neonatal MDSC transcriptional landscape, developmental trajectories, and predicted signaling networks within 48 h after birth. Peripheral blood mononuclear cells were isolated from 7 preterm neonates (< 36 weeks gestational age), 6 full-term neonates (> 37 weeks), and 6 healthy adult (21–45 years old, control). Primary exposure was premature birth and neonatal intensive care hospitalization from a single-center, academic tertiary care hospital between 2023 – 2024.
resultsAmong ~ 339,000 cells, preterm neonates exhibited enrichment of polymorphonuclear MDSCs (10.6% ± 5.3%) vs full-term (2.6% ± 1.3%) and adults (0.4% ± 1.3%). Trajectory analysis identified a prematurity-associated differentiation branch characterized by inflammatory signaling, mitochondrial stress, and heightened protein-translation programs, distinct from a conserved, tolerogenic MDSC trajectory present across ages. Cell-communication modeling showed intensified outgoing and incoming signaling via ADGRE, RESISTIN, TGF-β, ANNEXIN, and ICAM networks. Antigen presentation signatures suggested preserved MHC-I output and diminished MHC-II interactions in neonates, with increased MHC-I input to preterm polymorphonuclear MDSCs.
conclusionsPrematurity is associated with early divergence of MDSC maturation toward an inflammatory and metabolically stressed PMN-MDSC state with altered immune communication. These findings identify cellular mechanisms that may contribute to the heightened tissue damage and infection susceptibility of preterm neonates and highlight MDSC signaling as a potential target for early-life immunomodulatory interventions.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.