Upregulation of NUAK2: A novel prognostic marker in breast cancer

Background. Breast cancer is the most commonly diagnosed neoplasm in women worldwide. New molecular biomarkers and effective prognostic models are being developed. This study aimed to investigate the clinical and prognostic significance of NUAK2 expression in patients with breast cancer. Methods. The expression of NUAK 2 was examined in breast cancer cells and tissues by real-time PCR, western blotting, and immunohistochemical staining. CCK-8 and colony formation assays were performed to verify the effect of NUAK2 on the proliferation and tumor progression of breast cancer cells. A tumor formation assay in nude mice was performed to analyze the effect of NUAK2 on the tumorigenicity of breast cancer cells. Results. The expression of NUAK2 in breast cancer tissues was higher than that in paracarcinoma and normal breast tissues. The overall survival of patients with high NUAK2 expression was significantly lower than that of patients with low NUAK2 expression. Multivariate analyses indicated that NUAK2 was an independent prognostic indicator of survival in breast cancer. In vitro experiments demonstrated that knocking down NUAK2 in breast cancer cells inhibited cell proliferation and tumor-forming ability, and overexpression of NUAK2 showed the opposite effects. NUAK2 overexpression promoted the tumorigenicity of breast cancer cells in vivo. Conclusion. These findings suggest that NUAK2 is involved in breast cancer development and progression. NUAK2 may be a valuable prognostic indicator in patients with breast cancer

Environmental-Friendly Catalytic Oxidation Processes Based on Hierarchical Titanium Silicate Zeolites at SINOPEC

Since it was claimed by EniChem in 1983 for the first time, titanium silicate‐1 (TS‐1) zeolite presented the most delightful catalytic performance in the area of selective organic oxidation reactions. To enhance the mass diffusion property, hierarchical titanium silicate with hollow cavities within crystal was prepared by using a post‐synthesis treatment in the presence of organic template, and then, it was commercially produced and employed in many industrial catalytic oxidation processes, such as propylene epoxidation, phenol hydroxylation, and cyclohexanone ammoximation. Moreover, we also developed several totally novel oxidation reactions on hollow titanium silicate (HTS) zeolite, i.e., Baeyer‐Villiger oxidation of cyclohexanone and chlorohydrination of allyl chloride with HCl and H2O2. In all cases, HTS shows much better catalytic performance than TS‐1, attributing to the mass diffusion intensification by introducing hollow cavities. On the other hand, enormous works on synthesizing hierarchical TS‐1 zeolites with open intracrystalline mesopores have been done via silanization treatment and recrystallization. Based on them, several bulk molecule oxidation processes with tert‐butyl hydroperoxide, such as epoxidation of fatty acid methyl ester (FAME) and large olefins, have been carried out. As a consequence, hierarchical TS‐1 zeolites supply a platform for developing environmental‐friendly catalytic oxidation processes to remarkably overcome the drawbacks of traditional routes

Oscillation-specific nodal alterations in early to middle stages Parkinsons disease.

Background: Different oscillations of brain networks could carry different dimensions of brain integration. We aimed to investigate oscillation-specific nodal alterations in patients with Parkinsons disease (PD) across early stage to middle stage by using graph theory-based analysis. Methods: Eighty-eight PD patients including 39 PD patients in the early stage (EPD) and 49 patients in the middle stage (MPD) and 36 controls were recruited in the present study. Graph theory-based network analyses from three oscillation frequencies (slow-5: 0.01-0.027 Hz; slow-4: 0.027-0.073 Hz; slow-3: 0.073-0.198 Hz) were analyzed. Nodal metrics (e.g. nodal degree centrality, betweenness centrality and nodal efficiency) were calculated. Results: Our results showed that (1) a divergent effect of oscillation frequencies on nodal metrics, especially on nodal degree centrality and nodal efficiency, that the anteroventral neocortex and subcortex had high nodal metrics within low oscillation frequencies while the posterolateral neocortex had high values within the relative high oscillation frequency was observed, which visually showed that network was perturbed in PD; (2) PD patients in early stage relatively preserved nodal properties while MPD patients showed widespread abnormalities, which was consistently detected within all three oscillation frequencies; (3) the involvement of basal ganglia could be specifically observed within slow-5 oscillation frequency in MPD patients; (4) logistic regression and receiver operating characteristic curve analyses demonstrated that some of those oscillation-specific nodal alterations had the ability to well discriminate PD patients from controls or MPD from EPD patients at the individual level; (5) occipital disruption within high frequency (slow-3) made a significant influence on motor impairment which was dominated by akinesia and rigidity. Conclusions: Coupling various oscillations could provide potentially useful information for large-scale network and progressive oscillation-specific nodal alterations were observed in PD patients across early to middle stages

Novel KRIT1/CCM1 and MGC4607/CCM2 Gene Variants in Chinese Families With Cerebral Cavernous Malformations

Familial cerebral cavernous malformations (CCMs) are autosomal dominant disorders characterized by hemorrhagic strokes, recurrent headache, epilepsy, and focal neurological deficits. Genetic variants in KRIT1/CCM1, MGC4607/CCM2, and PDCD10/CCM3 genes contribute to CCMs. The clinical information of two Chinese families with CCMs was collected. MRI and video-electroencephalography were performed. Genetic variants of CCM1, CCM2, and CCM3 genes were investigated by exome sequencing. The patients were presented with recurrent epilepsy or headache. Susceptibility-weighted images of brains showed many dark dots, while video-electroencephalography revealed many spikes from multiple brain regions of patients. Exome sequencing revealed a novel CCM1 genetic variant (c.1599_1601TGAdel, p.Asp533del) and a novel CCM2 genetic variant (c.773delA, p.K258fsX34) in Family one and Family two, respectively; cosegregation existed in these two families. The two family members presented typical CCMs symptoms. These two novel genetic variants in CCM1 and CCM2 genes were the causation of CCM in the two Chinese families, and our data enriched the genetic variant spectrum of CCM genes

IL-33 ameliorates Alzheimer’s disease-like pathology and cognitive decline

Alzheimer’s disease (AD) is a devastating condition with no known effective treatment. AD is characterized by memory loss as well as impaired locomotor ability, reasoning, and judgment. Emerging evidence suggests that the innate immune response plays a major role in the pathogenesis of AD. In AD, the accumulation of β-amyloid (Aβ) in the brain perturbs physiological functions of the brain, including synaptic and neuronal dysfunction, microglial activation, and neuronal loss. Serum levels of soluble ST2 (sST2), a decoy receptor for interleukin (IL)-33, increase in patients with mild cognitive impairment, suggesting that impaired IL-33/ST2 signaling may contribute to the pathogenesis of AD. Therefore, we investigated the potential therapeutic role of IL-33 in AD, using transgenic mouse models. Here we report that IL-33 administration reverses synaptic plasticity impairment and memory deficits in APP/PS1 mice. IL-33 administration reduces soluble Aβ levels and amyloid plaque deposition by promoting the recruitment and Aβ phagocytic activity of microglia; this is mediated by ST2/p38 signaling activation. Furthermore, IL-33 injection modulates the innate immune response by polarizing microglia/macrophages toward an antiinflammatory phenotype and reducing the expression of proinflammatory genes, including IL-1β, IL-6, and NLRP3, in the cortices of APP/PS1 mice. Collectively, our results demonstrate a potential therapeutic role for IL-33 in AD

Exploring the mechanistic role of alloying elements in copper-based electrocatalysts for the reduction of carbon dioxide to methane

The promise of electrochemically reducing excess anthropogenic carbon dioxide into useful chemicals and fuels has gained significant interest. Recently, indium–copper (In–Cu) alloys have been recognized as prospective catalysts for the carbon dioxide reduction reaction (CO2RR), although they chiefly yield carbon monoxide. Generating further reduced C1 species such as methane remains elusive due to a limited understanding of how In–Cu alloying impacts electrocatalysis. In this work, we investigated the effect of alloying In with Cu for CO2RR to form methane through first-principles simulations. Compared with pure copper, In–Cu alloys suppress the hydrogen evolution reaction while demonstrating superior initial CO2RR selectivity. Among the alloys studied, In7Cu10 exhibited the most promising catalytic potential, with a limiting potential of −0.54 V versus the reversible hydrogen electrode. Analyses of adsorbed geometries and electronic structures suggest that this decreased overpotential arises primarily from electronic perturbations around copper and indium ions and carbon–oxygen bond stability. This study outlines a rational strategy to modulate metal alloy compositions and design synergistic CO2RR catalysts possessing appreciable activity and selectivity

Constraints on modified Chaplygin gas from recent observations and a comparison of its status with other models

In this Letter, a modified Chaplygin gas (MCG) model of unifying dark energy and dark matter with the exotic equation of state $p_{MCG}=B\rho_{MCG} -\frac A{\rho_{MCG}^\alpha}$ is constrained from recently observed data: the 182 Gold SNe Ia, the 3-year WMAP and the SDSS baryon acoustic peak. It is shown that the best fit value of the three parameters ($B$,$B_{s}$,$\alpha$) in MCG model are (-0.085,0.822,1.724). Furthermore, we find the best fit $w(z)$ crosses -1 in the past and the present best fit value $w(0)=-1.114<-1$, and the $1\sigma$ confidence level of $w(0)$ is $-0.946\leq w(0)\leq-1.282$. Finally, we find that the MCG model has the smallest $\chi^{2}_{min}$ value in all eight given models. According to the Alaike Information Criterion (AIC) of model selection, we conclude that recent observational data support the MCG model as well as other popular models.Comment: 8 pages, 1 figur

HCV core protein inhibits polarization and activity of both M1 and M2 macrophages through the TLR2 signaling pathway

Hepatitis C virus (HCV) establishes persistent infection in most infected patients, and eventually causes chronic hepatitis, cirrhosis, and hepatocellular carcinoma in some patients. Monocytes and macrophages provide the first line of defense against pathogens, but their roles in HCV infection remains unclear. We have reported that HCV core protein (HCVc) manipulates human blood-derived dendritic cell development. In the present study, we tested whether HCVc affects human blood-derived monocyte differentiating into macrophages. Results showed that HCVc inhibits monocyte differentiation to either M1 or M2 macrophages through TLR2, associated with impaired STATs signaling pathway. Moreover, HCVc inhibits phagocytosis activity of M1 and M2 macrophages, M1 macrophage-induced autologous and allogeneic CD4+ T cell activation, but promotes M2 macrophage-induced autologous and allogeneic CD4+ T cell activation. In conclusion, HCVc inhibits monocyte-derived macrophage polarization via TLR2 signaling, leading to dysfunctions of both M1 and M2 macrophages in chronic HCV infected patients. This may contribute to the mechanism of HCV persistent infection, and suggest that blockade of HCVc might be a novel therapeutic approach to treating HCV infection

Research on dynamic robust planning method for active distribution network considering correlation

The universality of load subjects in distribution network brings challenges to the reliability of distribution network planning results. In this paper, a two-stage dynamic robust distribution network planning method considering correlation is proposed. The method evaluates the correlation between random variables using the Spearman rank correlation coefficient, and converts the correlated random variables into mutually independent random variables by Cholesky decomposition and independent transformation; expresses the source-load uncertainty by a bounded interval without distribution, and describes the active distribution network planning as a dynamic zero-sum game problem by combining with the two-phase dynamic robust planning; use the Benders decomposition approach to tackle the issue; mathematical simulation is used to confirm the accuracy and efficacy of the method. The results show that the dynamic robustness planning method of active distribution network taking into account the correlation can accurately simulate the operation of active distribution network with uncertain boundaries, which enhances the reliability and economy of the active distribution network planning results