14 research outputs found

    Intelligent cholinergic white matter pathways algorithm based on U-net reflects cognitive impairment in patients with silent cerebrovascular disease

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    Background and objective The injury of the cholinergic white matter pathway underlies cognition decline in patients with silent cerebrovascular disease (SCD) with white matter hyperintensities (WMH) of vascular origin. However, the evaluation of the cholinergic white matter pathway is complex with poor consistency. We established an intelligent algorithm to evaluate WMH in the cholinergic pathway.Methods Patients with SCD with WMH of vascular origin were enrolled. The Cholinergic Pathways Hyperintensities Scale (CHIPS) was used to measure cholinergic white matter pathway impairment. The intelligent algorithm used a deep learning model based on convolutional neural networks to achieve WMH segmentation and CHIPS scoring. The diagnostic value of the intelligent algorithm for moderate-to-severe cholinergic pathway injury was calculated. The correlation between the WMH in the cholinergic pathway and cognitive function was analysed.Results A number of 464 patients with SCD were enrolled in internal training and test set. The algorithm was validated using data from an external cohort comprising 100 patients with SCD. The sensitivity, specificity and area under the curve of the intelligent algorithm to assess moderate and severe cholinergic white matter pathway injury were 91.7%, 87.3%, 0.903 (95% CI 0.861 to 0.952) and 86.5%, 81.3%, 0.868 (95% CI 0.819 to 0.921) for the internal test set and external validation set. for the. The general cognitive function, execution function and attention showed significant differences among the three groups of different CHIPS score (all p<0.05).Discussion We have established the first intelligent algorithm to evaluate the cholinergic white matter pathway with good accuracy compared with the gold standard. It helps more easily assess the cognitive function in patients with SCD

    Monosodium urate crystals regulate a unique JNK-dependent macrophage metabolic and inflammatory response

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    Monosodium urate crystals (MSUc) induce inflammation in vivo without prior priming, raising the possibility of an initial cell-autonomous phase. Here, using genome-wide transcriptomic analysis and biochemical assays, we demonstrate that MSUc alone induce a metabolic-inflammatory transcriptional program in non-primed human and murine macrophages that is markedly distinct to that induced by LPS. Genes uniquely upregulated in response to MSUc belong to lipid and amino acid metabolism, glycolysis, and SLC transporters. This upregulation leads to a metabolic rewiring in sera from individuals and mice with acute gouty arthritis. Mechanistically, the initiating inflammatory-metabolic changes in acute gout flares are regulated through a persistent expression and increased binding of JUN to the promoter of target genes through JNK signaling-but not P38-in a process that is different than after LPS stimulation and independent of inflammasome activation. Finally, pharmacological JNK inhibition limits MSUc-induced inflammation in animal models of acute gouty inflammation
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