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Introduction Stroke disrupts functional brain connectivity, yet how this relates to lower limb motor and sensory abilities is not well understood. Greater knowledge of movement‐related brain connectivity can aide in the development of better interventions for recovery after stroke. Our objective was to evaluate the relationship between lower limb performance and resting‐state functional connectivity (rsFC) of large‐scale brain networks for individuals with chronic motor deficits (> 6 months) after stroke. Methods Resting‐state functional magnetic resonance imaging and lower limb clinical measures were collected for 37 individuals. Regions of interest (ROI)‐to‐ROI connectivity analysis was conducted for cortical sensorimotor network (SMN) (cortical SMN), SMN with both cortical and subcortical ROIs (SMN), and default mode network (DMN). Relationship of ROI–ROI connectivity and clinical measures or lesion load was assessed using general linear models. Graph theory metrics (global efficiency, clustering coefficient, and betweenness centrality) were related to clinical measures using elastic nets analysis. Results Greater connectivity between several SMN and DMN ROI pairs was associated with better gait speed, Timed‐Up‐and‐Go score, and monofilament perception. The majority of ROI pairs showing statistically significant relationship with clinical measures were interhemispheric, non‐homologous, and cortical‐to‐subcortical. Elastic net analysis for graph theory metrics revealed complexity and multi‐directionality of the relationship of the individual ROIs to clinical outcomes and lesion load. There were unique sets of ROIs associated with each clinical measure for different graph metrics. Conclusions rsFC between specific ROIs within SMN and DMN are related to lower limb performance. Non‐homologous interhemispheric ROI‐to‐ROI connectivity was featured in the analysis. Graph theory analysis demonstrates the complex role that an individual ROI has in relation to sensorimotor function of lower extremity. Trial Registration Clinicialtrials.gov registration number NCT03666533 Resting‐state connectivity between specific regions of interest (ROI) within SMN and DMN is related to lower limb performance. Interhemispheric connectivity of non‐homologous ROIs was associated with better function. Graph theory analysis demonstrated the complex role that an individual ROI has in relation to sensorimotor function of lower extremity.

Crohn’s disease (CD) is a debilitating inflammatory bowel condition of unknown aetiology that is growing in prevalence globally. Large-scale studies have determined associations between female obesity or low body mass index (BMI) with risk of CD at all ages or 8– < 40 years, respectively. For males, low BMI entering adult life is associated with increased incidence of CD or ulcerative colitis up to 40 years later. Body composition analysis has shown that combinations of lean tissue loss and high visceral fat predict poor CD outcomes. Here, we assessed dietary intake, physical activity and whole or regional body composition of patients with CD relapse or remission. This anthropometric approach found people with CD, irrespective of relapse or remission, differed from a large representative healthy population sample in exhibiting elevated gynoid fat and reduced android fat. CD is associated with mesenteric adipose tissue, or “creeping fat”, that envelops affected intestine exclusive of other tissue; that fat is localised to the android region of the body. In this context, CD mesenteric adiposity represents a stark juxtaposition of organ-specific and regional adiposity. Although our study population was relatively small, we suggest tentatively that there is a rationale to refer to Crohn’s disease as a fatty intestine condition, akin to fatty liver conditions. We suggest that our data provide early insight into a subject that potentially warrants further investigation across a larger patient cohort.

Inflammatory processes have been implicated in the cascade of events that lead to nerve cell death. In the nervous system, a number of genes involved in inflammation pathways are regulated post-transcriptionally via the interaction of their mRNAs with specific RNA-binding Hu proteins, the vertebrate homologues of the Drosophila ELAV (for embryonic lethal abnormal vision). The gene encoding ELAVL4, a member of the Hu family of proteins, is located 2 Mb from the chromosome 1p linkage region peak for age-at-onset (AAO) of Parkinson disease (PD) (LOD = 3.41). Nine single-nucleotide polymorphisms (SNPs) in ELAVL4 were genotyped for 266 multiplex families (1,223 samples). Additional genotyping in 377 singleton families was performed for a subset of five SNPs (SNPs 1-5) that were not in linkage disequilibrium. SNP 2 (located in the first intron of ELAVL4) showed a strong significant association with AAO of PD (P = 0.006), and SNP 5 (a coding SNP in ELAVL4) showed a moderately significant association (P = 0.035). Haplotype analysis revealed that the A-C haplotype at SNPs 2 and 3 has the strongest significant association with AAO (P = 0.0001) among all combinations of two or three loci. The A-C haplotype remained significant for AAO after the inclusion of the C allele at SNP 5 to this haplotype (A-C-C haplotype, P = 0.00018). Although SNP 5 was found to associate with PD risk in the early-onset subset of PD families (at least one affected with AAO <40 years, 60 families), we believe that it is a by-product of its association with AAO. Taken together, these results suggest a potential role for ELAVL4 as a modifier gene for AAO of PD.

The lack of effective child obesity intervention and intervention prevention programmes is an increasing concern for public health professionals. Since eating and physical activity habits become established in the early years, these efforts should start as early as possible. A pilot programme, Fighting Fit Tots, was developed within a local Sure Start area. It consiste, of 11 weekly parent and toddler physical activity sessions, followed by a parent/carer healthy lifestyle workshop. Fighting Fit Tots was modelled on The MEND Programme, a successful community-based obesity intervention for school-aged children. Toddle recruitment criteria were based on the children's age, body mass index and parental obesity status. It was noticed that uptake and attendance were unsatisfac tory due to poor parental perception of child weight status, commitment issues, and limited staff capacity for outreach work. Therefore, the group was extended to all families with a toddler and this proved more successful. The pilot was a promising experience, an more community practitioners should be encourager to adopt and improve a public health approach to obesity prevention in the early years.

Model organisms have provided critical insights into the basic biology of metabolic disorders, however, one of the greatest limitations to translation has been the absence of the genetic heterogeneity that is characteristic of human populations. We examined metabolic health across three genetically diverse mouse strains fed control (low fat, no sucrose) or unhealthy (high fat, high sucrose) diets and observed a wide range of metabolic responses from overt type 2 diabetes in NZO/HlLtJ mice, to obesity and glucose intolerance in C57BL/6J mice, to complete resilience in CAST/EiJ mice. Analysis of multi-tissue gene expression revealed strain- and tissue-specific responses to diet, with strongest responses in white adipose tissue and pancreatic islets. In pancreatic islets, diet response was limited to just NZO mice, which showed high levels of inflammation and associated β cell dysfunction. Adipose tissue was responsive to diet across all three strains and revealed both common and strain-specific changes in inflammatory and metabolic pathways. Using a complementary outbred mouse resource, we mapped genetic loci associated with strain-specific diet responses, including a monocyte regulatory locus on mChr19. This multi-strain approach to modeling metabolic disease revealed a prominent role of white adipose tissue and lipid-associated inflammation in the determination of individual disease risk in response to unhealthy diets.Competing Interest StatementThe authors have declared no competing interest.