A generalized simplicial model and its application.

Higher-order structures, consisting of more than two individuals, provide a new perspective to reveal the missed non-trivial characteristics under pairwise networks. Prior works have researched various higher-order networks, but research for evaluating the effects of higher-order structures on network functions is still scarce. In this paper, we propose a framework to quantify the effects of higher-order structures (e.g., 2-simplex) and vital functions of complex networks by comparing the original network with its simplicial model. We provide a simplicial model that can regulate the quantity of 2-simplices and simultaneously fix the degree sequence. Although the algorithm is proposed to control the quantity of 2-simplices, results indicate it can also indirectly control simplexes more than 2-order. Experiments on spreading dynamics, pinning control, network robustness, and community detection have shown that regulating the quantity of 2-simplices changes network performance significantly. In conclusion, the proposed framework is a general and effective tool for linking higher-order structures with network functions. It can be regarded as a reference object in other applications and can deepen our understanding of the correlation between micro-level network structures and global network functions.

Higher-order link prediction via local information.

Link prediction has been widely studied as an important research direction. Higher-order link prediction has gained, in particular, significant attention since higher-order networks provide a more accurate description of real-world complex systems. However, higher-order networks contain more complex information than traditional pairwise networks, making the prediction of higher-order links a formidable challenging task. Recently, researchers have discovered that local features have advantages over long-range features in higher-order link prediction. Therefore, it is necessary to develop more efficient and concise higher-order link prediction algorithms based on local features. In this paper, we proposed two similarity metrics via local information, simplicial decomposition weight and closed ratio weight, to predict possible future higher-order interactions (simplices) in simplicial networks. These two algorithms capture local higher-order information at two aspects: simplex decomposition and cliques' state (closed or open). We tested their performance in eight empirical simplicial networks, and the results show that our proposed metrics outperform other benchmarks in predicting third-order and fourth-order interactions (simplices) in most cases. In addition, we explore the robustness of the proposed algorithms, and the results suggest that the performance of these novel algorithms is advanced under different sizes of training sets.

IL-6, IL-8 and IL-10 polymorphisms may impact predisposition of Alzheimer's disease: a meta-analysis.

Gene polymorphisms in interleukin-6 (IL-6), interleukin-8 (IL-8), and interleukin-10 (IL-10) may affect the predisposition of Alzheimer's disease (AD), but the results of the so far published studies remain controversial. The authors conducted this meta-analysis to assess relationships between IL-6/IL-8/IL-10 polymorphisms and predisposition of AD by pooling the findings of so far published studies. A comprehensive search of Pubmed, Embase, Web of Science, and CNKI was endorsed by the authors to identify the already published studies. Forty-five studies were found to be eligible for meta-analyses. The pooled meta-analyses results showed that genotypic frequencies of IL-6 - 174 G/C, IL-6 - 572 G/C and IL-10 - 1082 A/G polymorphisms among patients with AD and controls differed significantly. Moreover, genotypic frequencies of IL-6 - 174 G/C, IL-6 - 572 G/C, and IL-8 - 251 A/T polymorphisms among patients with AD and controls in Asians also differed significantly. But no such genotypic frequencies' differences were observed for IL-10 - 819 C/T and 592 C/A polymorphisms. This meta-analysis suggests that IL-6 - 174 G/C, IL-6 - 572 G/C, and IL-10 - 1082 A/G polymorphisms may affect the predisposition of AD in overall population. Moreover, IL-6 - 174 G/C, IL-6 - 572 G/C, and IL-8 - 251 A/T polymorphisms may affect the predisposition of AD in Asians.

Exploring the role and mechanism of sodium benzoate in CUMS-induced depression model of rats.

AIM: This study was aimed to investigate the effects of sodium benzoate in chronic unpredictable mild stress (CUMS)-induced depression model in rats. MATERIAL AND METHOD: Male rats were exposed to CUMS stress for 6 weeks which includes with multiple unpredictable stressors to induce depression related symptoms and the treatment with sodium benzoate was started at the 4th week of stress protocol (i.e. on the 22nd day) for 21 days during stress protocol . RESULTS: CUMS significantly increased the immobility period in the forced swimming test and decrease sucrose consumption in the sucrose preference test in rats. In the prefrontal cortex region (PFC) of the brain, a significant decline in the Brain-derived neurotrophic factor (BDNF) levels and Protein kinase A (PKA) was observed in rats. However, sodium benzoate (400 and 800 mg/kg i.p.) significantly restored sucrose preference behavior as well as reduced immobility in CUMS-subjected rats in a dose-dependent manner, suggesting the antidepressant potential of sodium benzoate. Also, sodium benzoate treatment significantly increased BDNF levels and PKA activity in the PFC region of the stress subjected rat brain. Moreover, co-administration of H-89, PKA inhibitor (1 and 5 mg/kg) along with sodium benzoate (800 mg/kg) in CUMS subjected rats notably attenuated antidepressant effects of sodium benzoate. H-89 also abolished sodium benzoate-mediated increase in BDNF levels and PKA activity in stress-subjected rats. CONCLUSION: Sodium benzoate mediated antidepressant actions may be due to a decrease in the d-amino oxidase activity, an increase in BDNF, and PKA levels in PFC region of the brain. Sodium benzoate-mediated modulation of BDNF/PKA signaling may contribute to attenuating depressive-symptoms in unpredictable stress-subjected rats.

Comorbid Bipolar Disorder and Migraine: From Mechanisms to Treatment.

Bipolar disorder (BD) is a severe psychiatric disorder characterized by recurrent episodes of manic/hypomanic or depressive symptoms and euthymic periods, with some patients suffering a gradual deterioration of illness and consequent cognitive deficits during the late stage. Migraine is a disease generally without abnormal medical examinations, neurological examinations or laboratory studies, and the diagnosis is made based on the retrospective demonstration of headache features and groupings of disease-associated symptoms. The epidemiology of comorbid BD and migraine is high and it is obligatory to find effective treatments to improve the prognosis. Recent investigations demonstrated that the close relationship between BD and migraine significantly increased the rapid cycling rates of both BD and migraine in patients. Although the detailed mechanism is complex and largely unclear in comorbid BD and migrain, genetic factors, neurotransmitters, altered signaling pathways, disturbances of inflammatory cytokines, and mitochondrial dysfunction are risk factors of BD and migraine. Particularly these two diseases share some overlapping mechanisms according to previous studies. To this end, we call for further investigations of the potential mechanisms, and more efforts are underway to improve the treatment of people with comorbid BD and migraine. In this review, we provide an overview of the potential mechanisms in patients with BD or migraine and we further discuss the treatment strategies for comorbid BD and migraine and it is obligatory to find effective treatments to improve the prognosis. This work will provide insights for us to know more about the mechanisms of comorbid BD and migraine, provides new therapeutic targets for the treatment and give clinicians some guidance for more appropriate and beneficial treatment.