Patients with obesity are susceptible to hypertension and diabetes. Over-activation of cannabinoid receptor 1 (CB1R) in adipose tissue is proposed in the pathophysiology of metabolic disorders, which led to the metabolic dysfunction of adipose tissue and deregulated production and secretion of adipokines. In the current study, we determined the impact of LH-21, a representative peripheral CB1R antagonist, on the obesity-accompanied hypertension and explored the modulatory action of LH-21 on the adipose tissue in genetically obese and diabetic KKAy mice. 3-week LH-21 treatment significantly decreased blood pressure with a concomitant reduction in body weight, white adipose tissue (WAT) mass, and a slight loss on food intake in KKAy mice. Meanwhile, glucose handling and dyslipidemia were also markedly ameliorated after treatment. Gene expression of pro-inflammatory cytokines in WAT and the aortae were both attenuated apparently by LH-21, as well the mRNA expression of adipokines (lipocalin-2, leptin) in WAT. Concomitant amelioration on the accumulation of lipocalin-2 was observed in both WAT and aortae. In corresponding with this, serum inflammatory related cytokines (tumor necrosis factor α, IL-6, and CXCL1), and lipocalin-2 and leptin were lowered notably. Thus according to current results, it can be concluded that the peripheral CB1R antagonist LH-21 is effective in managing the obesity-accompanied hypertension in KKAy mice. These metabolic benefits are closely associated with the regulation on the production and secretion of inflammatory cytokines and adipokines in the WAT, particularly alleviated circulating lipocalin-2 and its accumulation in aortae.

PurposeTreatment of epithelial ovarian cancer is evolving towards personalization and precision, which require patient-specific estimates of overall survival (OS) and progression-free survival (PFS).Patients and MethodsMedical records of 1173 patients who underwent debulking surgery in our center were comprehensively reviewed and randomly allocated into a derivation cohort of 879 patients and an internal validation cohort of 294 patients. Five hundred and seventy-seven patients from the other three cancer centers served as the external validation cohort. A novel nomogram model for PFS and OS was constructed based on independent predictors identified by multivariable Cox regression analysis. The predictive accuracy and discriminative ability of the model were measured using Harrell’s concordance index (C-index) and calibration curve.ResultsThe C-index values were 0.82 (95% CI: 0.76–0.88) and 0.84 (95% CI: 0.78–0.90) for the PFS and OS models, respectively, substantially higher than those obtained with the FIGO staging system and most nomograms reported for use in epithelial ovarian cancer. The nomogram score could clearly classify the patients into subgroups with different risks of recurrence or postoperative mortality. The online versions of our nomograms are available at https://eocnomogram.shinyapps.io/eocpfs/ and https://eocnomogram.shinyapps.io/eocos/.ConclusionA externally validated nomogram predicting OS and PFS in patients after R0 reduction surgery was established using a propensity score matching model. This nomogram may be useful in estimating individual recurrence risk and guiding personalized surveillance programs for patients after surgery, and it could potentially aid clinical decision-making or stratification for clinical trials.