Bmc Med
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Endometriosis is well known as a chronic inflammatory disease. The development of endometriosis is heavily influenced by the estrogen receptor β (ERβ), while NOD-like receptors (NLRs) family CARD domain-containing 5 (NLRC5) exhibits anti-inflammatory properties during endometriosis. However, whether NLRC5-mediated anti-inflammation is involved in the ERβ-mediated endometriosis is still uncertain. This study aimed to assess that relation. ⋯ Our results suggest that the innate immune molecule NLRC5-mediated anti-inflammation participates in ERβ-mediated endometriosis development, and partly clarifies the pathological mechanism of endometriosis, expanding our knowledge of the specific molecules related to the inflammatory response involved in endometriosis and potentially providing a new therapeutic target for endometriosis.
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The integration of machine learning (ML) and artificial intelligence (AI) techniques in life-course epidemiology offers remarkable opportunities to advance our understanding of the complex interplay between biological, social, and environmental factors that shape health trajectories across the lifespan. This perspective summarizes the current applications, discusses future potential and challenges, and provides recommendations for harnessing ML and AI technologies to develop innovative public health solutions. ML and AI have been increasingly applied in epidemiological studies, demonstrating their ability to handle large, complex datasets, identify intricate patterns and associations, integrate multiple and multimodal data types, improve predictive accuracy, and enhance causal inference methods. ⋯ However, the successful integration of these technologies faces challenges related to data quality, model interpretability, bias, privacy, and equity. To fully realize the potential of ML and AI in life-course epidemiology, fostering interdisciplinary collaborations, developing standardized guidelines, advocating for their integration in public health decision-making, prioritizing fairness, and investing in training and capacity building are essential. By responsibly harnessing the power of ML and AI, we can take significant steps towards creating healthier and more equitable futures across the life course.
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Multicenter Study Observational Study
Gender-affirming hormonal therapy induces a gender-concordant fecal metagenome transition in transgender individuals.
Limited data exists regarding gender-specific microbial alterations during gender-affirming hormonal therapy (GAHT) in transgender individuals. This study aimed to investigate the nuanced impact of sex steroids on gut microbiota taxonomy and function, addressing this gap. We prospectively analyzed gut metagenome changes associated with 12 weeks of GAHT in trans women and trans men, examining both taxonomic and functional shifts. ⋯ This study provides compelling evidence of distinct taxonomic and functional profiles in the gut microbiota between trans men and women. GAHT induces androgenization in trans men and feminization in trans women, potentially impacting physiological and health-related outcomes.
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Randomized Controlled Trial
Cruciferous vegetables lower blood pressure in adults with mildly elevated blood pressure in a randomized, controlled, crossover trial: the VEgetableS for vaScular hEaLth (VESSEL) study.
Higher cruciferous vegetable intake is associated with lower cardiovascular disease risk in observational studies. The pathways involved remain uncertain. We aimed to determine whether cruciferous vegetable intake (active) lowers 24-h brachial systolic blood pressure (SBP; primary outcome) compared to root and squash vegetables (control) in Australian adults with mildly elevated BP (SBP 120-160 mmHg inclusive). ⋯ Increased intake of cruciferous vegetables resulted in reduced SBP compared to root and squash vegetables. Future research is needed to determine whether targeted recommendations for increasing cruciferous vegetable intake benefits population health.
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Sex disparity between metabolic-obesity (defined by body mass index, BMI) phenotypes and obesity-related cancer (ORC) remains unknown. Considering BMI reflecting overall obesity but not fat distribution, we aimed to systematically assess the association of our newly proposed metabolic-anthropometric phenotypes with risk of overall and site-specific ORC by sex. ⋯ There was a significant sex disparity between metabolic-anthropometric phenotypes and ORC risk. We advised future ORC prevention and control worth taking body shape and sex disparity into account.