Background: Epidemiological evidence indicates a high correlation and comorbidity between Attention Deficit Hyperactivity Disorder (ADHD) and Restless Legs Syndrome (RLS). Objective: We aimed to investigate the causal relationship and shared genetic architecture between ADHD and RLS, as well as explore potential causal associations between both disorders and peripheral iron status. Methods: We performed two-sample Mendelian randomization (MR) analyses using summary statistics from genome-wide meta-analyses of ADHD, RLS, and peripheral iron status (serum iron, ferritin, transferrin saturation, and total iron binding capacity). Additionally, we employed linkage disequilibrium score regression (LDSC) to assess genetic correlations between ADHD and RLS using genetic data. Results: Our MR results supports a causal effect from ADHD (as exposure) to RLS (as outcome) (inverse variance weighted OR = 1.20, 95% CI: 1.08-1.34, p = 0.001). Conversely, we found no a causal association from RLS to ADHD (inverse variance weighted OR = 1.04, 95% CI: 0.99-1.09, p = 0.11). LDSC analysis did not detect a significant genetic correlation between RLS and ADHD (Rg = 0.3, SE = 0.16, p = 0.068). Furthermore, no evidence supported a causal relationship between peripheral iron deficiency and the RLS or ADHD onset. However, RLS may have been associated with a genetic predisposition to reduced serum ferritin levels (OR = 1.20, 95% CI: 1.00-1.04, p = 0.047). Conclusion: This study suggests that ADHD is an independent risk factor for RLS, while RLS may confer a genetic predisposition to reduced serum ferritin levels. Limitations: The GWAS summary data utilized originated from populations of European ancestry, limiting the generalizability of conclusions to other populations. Clinical implications: The potential co-occurrence of RLS in individuals with ADHD should be considered during diagnosis and treatment. Moreover, iron supplementation may be beneficial for alleviating RLS symptoms.
Background and Purpose: Futile recanalization (FRC) is common among large artery occlusion (LAO) patients after endovascular therapy (EVT). We developed nomogram models to identify LAO patients at a high risk of FRC pre- and post-EVT to help neurologists select the optimal candidates for EVT. Methods: From April 2020 to July 2022, EVT and mTICI score ≥2b LAO patients were recruited. Nomogram models was developed by two-step approach for predicting the outcomes of LAO patients. First, the least absolute shrinkage and selection operator (LASSO) regression analysis was to optimize variable selection. Then, a multivariable analysis was to construct an estimation model with significant indicators from the LASSO. The accuracy of the model was verified using receiver operating characteristic (ROC), calibration curve, and decision curve analyses (DCA), along with validation cohort (VC). Results: Using LASSO, age, sex, hypertension history, baseline NIHSS, ASPECTS and baseline SBP upon admission were identified from the pre-EVT variables. Model 1 (pre-EVT) showed good predictive performance, with an area under the ROC curve (AUC) of 0.815 in the training cohort (TrC) and 0.904 in VC. Under the DCA, the generated nomogram was clinically applicable where risk cut-off was between 15%-85% in the TrC and 5%-100% in the VC. Moreover, age, ASPECTS upon admission, onset duration, puncture-to-recanalization (PTR) duration, and lymphocyte-to-monocyte ratio (LMR) were screened by LASSO. Model 2 (post-EVT) also demonstrated good predictive performance with AUCs of 0.888 and 0.814 for TrC and VC, respectively. Under the DCA, the generated nomogram was clinically applicable if the risk cut-off was between 13-100% in the TrC and 22-85% of VC. Conclusion: In this study, two nomogram models were generated that showed good discriminative performance, improved calibration, and clinical benefits. These nomograms can potentially accurately predict the risk of FRC in LAO patients pre- and post-EVT and help to select appropriate candidates for EVT.
INTRODUCTION: NLRP3 inflammasome responses and gut microbiota have been shown an important role in lung cancer, however, the relationship between gut microbiota and NLRP3 inflammasome responses in lung cancer with Qi-yin deficiency remains elusive. METHODS: To investigate the effect of the traditional Chinese medicine BuFeiXiaoJiYin (BFXJY) on NLRP3 inflammasome responses and dysbiosis in lung cancer with Qi-yin deficiency, the female BALB/cA-nu mice were treated with LPS and ATP to induce inflammation, and were intragastrically treated with warm Chinese medicine and smoked with shavings to induce Qi-yin deficiency, as well as were injected with 1 × 107/ml A549 cells to simulate lung cancer. Then the three different doses of BuFeiXiaoJiYin (BFXJY) and positive control (CRID3) were used for intervention in mice for 27 consecutive days. Then, we estimated the protection effect of BFXJY on lung cancer mice with Qi-yin deficiency, through deterring tumor growth, NLRP3 inflammasome, PKC signaling, and homeostasis of gut microbiota. RESULTS: In this study, we found that BFXJY could inhibit the tumor growth in lung cancer with Qi-yin deficiency by reducing the production of IL-1ß and IL-18 and inhibiting NLRP3 inflammasome activation, which might be associated with the inhibition of PKC signaling. Furthermore, BFXJY could promote microbial diversity and balance the microbial composition changes induced by inflammation and Qi-yin deficiency in lung cancer. CONCLUSION: BuFeiXiaoJiYin ameliorates the NLRP3 inflammation response and gut microbiota in mice with lung cancer companied with Qi-yin deficiency. Our study provides a theoretical basis for the clinical development of therapeutic drugs targeting to treat lung cancer.
