Preterm birth remains a significant global health challenge and is strongly associated with heightened risks of long-term neurodevelopmental impairments, including cognitive delays, behavioural disorders, and emotional dysregulation. In recent years, accumulating evidence has underscored the critical role of the gut microbiota in early brain development through the gut–brain axis. In preterm infants, microbial colonisation is frequently delayed or disrupted due to caesarean delivery, perinatal antibiotic exposure, formula feeding, and prolonged stays in neonatal intensive care units (NICUs), all of which contribute to gut dysbiosis during critical periods of neurodevelopment. This review synthesises current knowledge on the sources, temporal patterns, and determinants of gut microbiota colonisation in preterm infants. This review focuses on the gut bacteriome and uses faecal-sample bacteriome sequencing as its primary method of characterisation. We detail five mechanistic pathways that link microbial disturbances to adverse neurodevelopmental outcomes: immune activation and white matter injury, short-chain fatty acids (SCFAs)-mediated neuroprotection, tryptophan–serotonin metabolic signalling, hypothalamic–pituitary–adrenal (HPA) axis modulation, and the integrity of intestinal and blood–brain barriers (BBB). We also critically examine emerging microbiota-targeted interventions—including probiotics, prebiotics, human milk oligosaccharides (HMOs), antibiotic stewardship strategies, skin-to-skin contact (SSC), and faecal microbiota transplantation (FMT)—focusing on their mechanisms of action, translational potential, and associated ethical concerns. Finally, we identify key research gaps, including the scarcity of longitudinal studies, limited functional modelling, and the absence of standardised protocols across clinical settings. A comprehensive understanding of microbial–neurodevelopmental interactions may provide a foundation for the development of targeted, timing-sensitive, and ethically sound interventions aimed at improving neurodevelopmental outcomes in this vulnerable population.

Background: Premenopausal women typically exhibit superior glucose metabolism compared to males, but this metabolic advantage is lost after menopause. The primary cause is the sharp decline in estrogen levels post-menopause. Genistein, a natural compound predominantly derived from leguminous plants, possesses structural similarity to estrogen. This enables specific binding to estrogen receptors, allowing genistein to exert estrogen-mimicking effects under conditions of estrogen deficiency. The aim of this study was to investigate the effects and potential mechanisms of genistein on glucose metabolism in the liver and skeletal muscle of ovariectomized (OVX) mice fed a high-fat diet (HFD). Methods: Animal experiments were performed using 8-week-old mice that were OVX to construct a model of estrogen deficiency and impaired their glucose metabolism by a continuous HFD. Genistein was administered by gavage (50 mg/kg-day) for 10 weeks and 17β-estradiol was administered subcutaneously (50 μg/kg) every 4 days for 10 weeks as a positive control. Results: Genistein significantly improved glucose metabolism (including fasting glucose, postprandial glucose, serum glucose levels, and HOMA-IR index) but did not affect serum estrogen levels and uterine weights in OVX mice. Genistein promoted increased expression and translocation of glucose transporter 4 (GLUT4) in the gastrocnemius muscle, enhanced phosphorylation of the PI3K/AKT pathway, and upregulated expression of the G protein-coupled estrogen receptor (GPER). Concurrently, it stimulates hepatic glycogen accumulation and upregulates GLUT2 expression in the liver. Conclusions: GEN improves glucose metabolism in ovariectomized mice, and this improvement is primarily attributed to increased expression and membrane translocation of GLUT4 in the gastrocnemius muscle mediated by the GPER-PI3K/AKT pathway.

Preterm infants face higher neurodevelopmental risks than term infants due to immature brain development, including delays, cognitive impairments, and poor

Objectives: Developmental delay in preterm infants is a critical clinical issue, and early risk identification and prediction are essential. This study aims to develop and validate a predictive model for developmental delay, providing a scientific basis for clinical risk assessment and early intervention. Methods: This study included preterm infants and their primary caregivers who were followed up at our center from May 2023 to September 2024. The samples were randomly divided into a training cohort, an internal validation cohort, and an external validation cohort. Independent risk factors for stunting were identified through univariate and multivariate logistic regression analyses, and predictive models and calibration were constructed accordingly. Results: The five standardized indicators at 3, 6, 9, and 12 months for 507 preterm infants were analyzed using principal component analysis, and their developmental outcomes were grouped accordingly. Logistic regression analyses showed that gestational age, high-risk factors, knowledge of caregiving, caregiving experience, and the presence of other caregivers in the home were independent risk factors for the risk of preterm infants with stunted growth at 3, 6, 9, and 12 months. The nomogram showed the area under the receiver operating characteristic curve values of 0.743, 0.735, 0.752, and 0.774 in the training cohort; 0.855, 0.771, 0.870, and 0.786 in the internal validation cohort; 0.822, 0.804, 0.717, and 0.678 in the external validation cohort, respectively. The calibration curves, consistency index, and decision curve analysis all showed that the model was significantly better than a single indicator in predicting the risk of stunting in preterm infants. Conclusions: The stunting risk prediction model constructed in this study shows good predictive ability, which can help clinicians assess the risk of stunting in preterm infants and support the development of early intervention strategies.