Observational studyFrontiers in public health2025
Cohort protocol: risk assessment of maternal inflammation and early brain development in infants and young children based on multi-source data modeling.
Observational study in Frontiers in public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05040542 (A Cohort Study on the Brain Mechanism of Social Emotion and Communication in Infants Aged 0 to 6 Years), which is not on this map. Not yet cited in PubMed.
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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.
A Cohort Study on the Brain Mechanism of Social Emotion and Communication in Infants Aged 0 to 6 Years
Who cites it
0 citing papers in PubMed.
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Corrections and comments
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Authors and funding
16 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Introduction: Infancy and early childhood are the key stage for the rapid development of brain structure and function, and brain development at this stage has a profound impact on the future intelligence, behavior and health of individuals. A growing body of research suggests that maternal inflammation, as a potential environmental factor, may affect brain development in infants and young children through a variety of mechanisms. Therefore, it is of great significance to evaluate the risk of maternal inflammation to early brain development in infants and young children based on multi-source data modeling to understand the mechanism of early development and prevent brain development disorders. Methods and analysis: Between December 2021 and May 2024, 360 pairs of pregnant women and their offspring were recruited into the Xiamen Children's Brain Development Cohort. Pregnant women's exposure during pregnancy was collected through standardized and structured questionnaires and medical records. All children were followed up to 3 years of age. We administered questionnaires, behavioral assessments, and performed neuroimaging. Environmental exposures during infancy and early childhood were collected. Children's cognitive, emotional, and linguistic development was evaluated, and blood samples were obtained for whole-exome sequencing and exposure-related biomarker analysis. Conclusion: In this study, we used deep learning artificial intelligence to construct an early risk assessment model for infant brain development based on the developmental trajectory and developmental results of early brain structure, function, and connections under the complex interaction of "gene-image-environment-behavior" multi-factors, which can improve the early identification and precise intervention of problems in this period, and improve infants cognitive learning and work performance in childhood, adolescence and even adulthood. Clinical trial registration: https://www.clinicaltrials.gov/; identifier [NCT05040542].
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