Vaginal microbiome and inflammation cytokines among Chinese women.

Network science has significantly advanced our understanding of brain structure. Magnetic resonance imaging (MRI) has been a key driver of this progress because it has enabled the collection of whole brain images at the millimetre scale in vivo. Analysis of MRI images allows quantification of brain structure both at the macro-scale, through metrics such as cortical thickness, surface area, and mean curvature; and at the micro-scale, below the minimal resolution of single voxels, using sequences such as diffusion imaging and magnetisation transfer. Recent technical advances in structural similarity have permitted the integration of these MRI-derived structural features into a single network representation, with edges between nodes defined by the statistical relationships between the MRI features measured in pairs of regional nodes. Similarity networks therefore represent spatially patterned structural variation across the cortex (the architectome), rather than directly measuring connectivity (the connectome), as is the case in diffusion tensor imaging (DTI) tractography. However, areas that are structurally similar are more likely to be axonally connected due to the network formation principle of homophilic attachment, or “like attracts like”. Accordingly, the architectome represented by MRI-derived structural similarity networks has been correlated empirically with the connectome represented by axonal tract tracing data in the macaque and rat cortex. A recently developed method for estimating structural similarity networks from MRI data is morphometric inverse divergence (MIND), which uses Kullback-Leibler divergence to quantify the similarity between a pair of cortical areas in terms of their voxel- or vertex-wise distributions of one or more structural MRI features. MIND and adjacent methods are technically robust and reliable estimators of heritable phenotypes, associated with similarity in gene expression, developmentally sensitive, and altered in psychiatric disorders. Animal models can enhance our understanding of the biological underpinnings of structural similarity networks and how they are reorganised during development and disease. The common marmoset (), a New World primate, represents a key rung on the translational ladder between rodent and human neuroscience, combining the tractability of rodent research with the translational relevance of primate research. Like rodents, marmosets have an accelerated lifespan compared to humans, reaching adulthood at 18-20 months, which facilitates longitudinal MRI studies that collect repeated measures over the lifespan. Like humans, marmosets show prolonged postnatal development in the context of familial nurturing, and protracted development of association cortex, particularly those areas involved in social cognition.