ReviewBiomolecules2025
Molecular Biomarkers for Timely and Personalized Prediction of Maternal-Fetal Health Risk.
Review in Biomolecules, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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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
6 citing papers in PubMed.
- Longitudinal patterns of urinary biomarkers of placental and renal function in pregnancy and associations with early pregnancy exposure to phthalates and replacements.Reproductive toxicology (Elmsford, N.Y.) · 2026Article
- Association of maternal IL-2, IL-4, and IL-13 with intrauterine growth restriction and umbilical artery doppler: a case-control study.Revista brasileira de ginecologia e obstetricia : revista da Federacao Brasileira das Sociedades de Ginecologia e Obstetricia · 2026Article
- Emerging biomarkers for gestational diabetes mellitus and related pediatric outcomes.World journal of clinical pediatrics · 2025Review
- The Prognostic Value and Perioperative Dynamics of the HALP Score in Placenta Accreta Spectrum Surgeries.Journal of clinical medicine · 2025Article
- Molecular Insights into Human Placentation: From Villous Morphogenesis to Pathological Pathways and Translational Biomarkers.International journal of molecular sciences · 2025Review
- Maternal Telomere Length and Its Influence on Neonatal Parameters: A Potential Tool for Prenatal Screening.Medicina (Kaunas, Lithuania) · 2025Observational
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
Molecular biomarker profiling is an emerging field in maternal-fetal health with the potential to transform early detection and prediction of placental dysfunction. By analysing a range of biomarkers in maternal blood, researchers and clinicians can gain crucial insights into placental health, enabling timely interventions to enhance fetal and maternal outcomes. Placental structural function is vital for fetal growth and development, and disruptions can lead to serious pregnancy complications like preeclampsia. While conventional methods such as ultrasound and Doppler velocimetry offer valuable information on fetal growth and blood flow, they have limitations in predicting placental dysfunction before clinical signs manifest. In contrast, molecular biomarker profiling can provide a more comprehensive assessment by measuring proteins, metabolites, and microRNAs (miRNAs) in maternal blood, reflecting the placenta's endocrine and metabolic functions. This approach offers a deeper understanding of placental health and function, aiding in early detection and prediction of complications. Challenges in developing molecular biomarker profiling include pinpointing specific molecular changes in the placenta linked to pathologies, timing predictions of conditions before clinical onset, and understanding how placental dysfunction affects maternal metabolism. Validating specific biomarkers and integrating them effectively into clinical practice requires further research. This review underscores the significance of molecular biomarker profiling as a powerful tool for early detection and prediction of placental dysfunction in maternal-fetal health. Through an exploration of biomarker analysis, we delve into how a deeper understanding of placental health can potentially improve outcomes for both mother and baby. Furthermore, we address the critical need to validate the utility of biomarkers and effectively integrate them into clinical practice.
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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.