ReviewFrontiers in medicine2026
The recent advancements of single-cell RNA sequencing in pre-eclampsia.
Review in Frontiers in medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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
1 citing paper in PubMed.
- Artificial Intelligence for the Prediction of Preeclampsia: Current Evidence, Comparison with Conventional Screening Models, and Future Perspectives.Diagnostics (Basel, Switzerland) · 2026Review
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Preeclampsia (PE) is a multisystem syndrome that manifests after 20 weeks of gestation, with a global incidence of 2%-8%, and is one of the leading causes of maternal and perinatal mortality. Its etiology is complex, involving multiple mechanisms such as abnormal placentation, immune dysregulation, and angiogenic imbalance, with early-onset PE (EOPE) and late-onset PE (LOPE) exhibiting distinct pathological foundations. In recent years, the application of single-cell RNA sequencing (scRNA-seq) has provided a novel perspective for deciphering the cellular heterogeneity and molecular mechanisms of PE. This review systematically summarizes the latest advances in scRNA-seq applications in PE research, focusing on how this technology reveals: (1) Dysfunction of trophoblast subpopulations and its association with defective spiral artery remodeling; (2) Dynamic changes in the immune microenvironment, including macrophage polarization, functional subsets of uNK cells, and T cell regulatory networks; (3) Cell-specific dysregulation of key signaling pathways; (4) The distinct cytopathological features of early-onset versus late-onset PE. Furthermore, scRNA-seq has facilitated the discovery of multi-gene-based early diagnostic models and potential therapeutic targets. Compared to traditional bulk sequencing, scRNA-seq enables the resolution of cellular heterogeneity, identification of rare cell subpopulations, and elucidation of intercellular communication networks. However, its limitations include difficulties in sample acquisition, high technical costs, complex data analysis, and challenges in capturing multinucleated syncytial structures. In the future, scRNA-seq is expected to provide highly promising therapeutic strategies for PE patients.
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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 Socratic graph.