Altered brain morphometry has been widely acknowledged in chronic pain, and recent studies have implicated altered network dynamics, as opposed to properties of individual brain regions, in supporting persistent pain. Structural covariance analysis determines the inter-regional association in morphological metrics, such as gray matter volume, and such structural associations may be altered in chronic pain. In this study, voxel-based morphometry structural covariance networks were compared between fibromyalgia patients (N = 42) and age- and sex-matched pain-free adults (N = 63). We investigated network topology using spectral partitioning, which can delineate local network submodules with consistent structural covariance. We also explored white matter connectivity between regions comprising these submodules and evaluated the association between probabilistic white matter tractography and pain-relevant clinical metrics. Our structural covariance network analysis noted more connections within the cerebellum for fibromyalgia patients, and more connections in the frontal lobe for healthy controls. For fibromyalgia patients, spectral partitioning identified a distinct submodule with cerebellar connections to medial prefrontal and temporal and right inferior parietal lobes, whose gray matter volume was associated with the severity of depression in these patients. Volume for a submodule encompassing lateral orbitofrontal, inferior frontal, postcentral, lateral temporal, and insular cortices was correlated with evoked pain sensitivity. Additionally, the number of white matter fibers between specific submodule regions was also associated with measures of evoked pain sensitivity and clinical pain interference. Hence, altered gray and white matter morphometry in cerebellar and frontal cortical regions may contribute to, or result from, pain-relevant dysfunction in chronic pain patients.
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http://dx.doi.org/10.1016/j.nicl.2015.02.022 | DOI Listing |
SSM Popul Health
March 2025
Department of Health and Social Behavior, School of Public Health, The University of Tokyo, Tokyo, Japan.
Recent discussions in epidemiology have emphasised the need to estimate the heterogeneous effects of risk factors across the distribution of health outcomes for better aetiological understanding of the determinants of population health. We propose using quantile regression-based decomposition to expand the empirical discussion on population health intervention strategies for health equity by incorporating population homogeneity/heterogeneity in the risk-outcome association. We theorised that the 'proportionate universalism' approach presumes population homogeneity in the risk-outcome association with varying risk intensities, which decomposition analysis shows as the 'covariates part' between groups.
View Article and Find Full Text PDFInt J Hyg Environ Health
January 2025
RECETOX, Faculty of Science, Masaryk University, Brno, Czech Republic; Institute of Epidemiology & Health Care, University College London, London, United Kingdom. Electronic address:
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Methods: Cross-sectional data of the Czech arm of the HAPIEE cohort study examined 4,178 participants (55.
Genet Sel Evol
January 2025
GenPhySE, Université de Toulouse, INRAE, ENVT, 31326, Castanet-Tolosan, France.
Background: The magnitude of inbreeding depression depends on the recessive burden of the individual, which can be traced back to the hidden (recessive) inbreeding load among ancestors. However, these ancestors carry different alleles at potentially deleterious loci and therefore there is individual variability of this inbreeding load. Estimation of the additive genetic value for inbreeding load is possible using a decomposition of inbreeding in partial inbreeding components due to ancestors.
View Article and Find Full Text PDFBiological memory networks are thought to store information by experience-dependent changes in the synaptic connectivity between assemblies of neurons. Recent models suggest that these assemblies contain both excitatory and inhibitory neurons (E/I assemblies), resulting in co-tuning and precise balance of excitation and inhibition. To understand computational consequences of E/I assemblies under biologically realistic constraints we built a spiking network model based on experimental data from telencephalic area Dp of adult zebrafish, a precisely balanced recurrent network homologous to piriform cortex.
View Article and Find Full Text PDFInt J Equity Health
January 2025
Center for Health Equity in Latin America, Celia Scott Weatherhead School of Public Health and Tropical Medicine, Tulane University, Louisiana, USA.
Background: Ethnic and racial discrimination in maternal health care has been overlooked in academic literature and yet it is critical for achieving universal health coverage (UHC). There is a lack of empirical evidence on its impact on the effective coverage of maternal health interventions (ECMH) for Indigenous women in Mexico. Documenting progress in reducing maternal health inequities, particularly given the disproportionate impact of the Covid-19 pandemic on ethnic minorities, is essential to improving equity in health systems.
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