RESUMEN
Chronic migraine is a common central nervous system disorder characterized by recurrent, pulsating headaches. However, the extent and mechanisms of hypothalamic involvement in disease progression have not been thoroughly investigated. Herein, we created a chronic migraine mouse model using repeated intraperitoneal injections of nitroglycerin. We performed transcriptomic sequencing on the hypothalamus of mice with chronic migraine and control mice under normal physiological conditions, followed by differential gene set enrichment and functional analysis of the data. Additionally, we examined the intrinsic connection between chronic migraine and sleep disorders using transcriptomic sequencing data from sleep-deprived mice available in public databases. We identified 39 differentially expressed genes (DEGs) in the hypothalamus of a mouse model of chronic migraine. Functional analysis of DEGs revealed enrichment primarily in signaling transduction, immune-inflammatory responses, and the cellular microenvironment. A comparison of the transcriptomic data of sleep-deprived mice revealed two commonly expressed DEGs. Our findings indicate that the hypothalamic DEGs are primarily enriched in the PI3K/AKT/mTOR pathway and associated with the NF-κB/NLRP3/IL-1 ß pathway activation to maintain the central sensitization of the chronic migraine. Chronic migraine-induced gene expression changes in the hypothalamus may help better understand the underlying mechanisms and identify therapeutic targets.
RESUMEN
Objective: This study aims to determine the clinical significance of the advanced lung cancer inflammation index (ALI) in predicting prognosis, chemotherapy response, and infection risk in newly diagnosed multiple myeloma (MM) patients receiving induction therapy. Methods: A retrospective analysis of the clinical characteristics and laboratory data of 111 newly diagnosed MM patients from the Haematology Department of the Third Xiangya Hospital of Central South University from January 2014 to March 2020 was performed. We first determined the relationship between ALI and overall survival (OS), as well as clinical and laboratory parameters. Second, predictive factors for chemotherapy response were analysed by univariate and multivariate regression analyses. Third, univariate regression analysis of risk factors was performed using infection as the evaluable outcome. Results: Of the 111 evaluable patients, the low ALI group (<32.7) exhibited significantly poorer survival than the high ALI group (51 months versus 77 months). Multivariable analysis showed that advanced age, chemotherapy response and serum calcium level were independent prognostic factors for OS. Better chemotherapy efficacy in the high ALI group (89.3%) than in the low ALI group (42.2%) (p < 0.001) was noted. Multivariate analysis suggested that only ALI [HR: 0.110, 95% CI (0.035-0.350), p = 0.000] is an independent predictive factor in evaluating the efficiency of induction chemotherapy. Forty patients (36.04%) presented with infection after induction chemotherapy. Univariate analysis suggested that low ALI and abnormal renal function increase risk of infection in newly diagnosed MM patients. Conclusion: Our study confirmed that ALI is not only a prognostic biomarker for newly diagnosed patients, but also predicts chemotherapy efficacy in newly diagnosed MM patients receiving induction therapy.