Heterogeneous activation of peroxymonosulfate by a biochar-supported Co3O4 composite for efficient degradation of chloramphenicols

Herein, a new peroxymonosulfate (PMS) activation system was established using a biochar (BC)-supported Co3O4 composite (Co3O4-BC) as a catalyst to enhance chloramphenicols degradation. The effects of the amount of Co3O4 load on the BC, Co3O4-BC amount, PMS dose and solution pH on the degradation of chloramphenicol (CAP) were investigated. The results showed that the BC support could well disperse Co3O4 particles. The degradation of CAP (30 mg/L) was enhanced in the Co3O4-BC/PMS system with the apparent degradation rate constant increased to 5.1, 19.4 and 7.2 times of that in the Co3O4/PMS, BC/PMS and PMS-alone control systems, respectively. Nearly complete removal of CAP was achieved in the Co3O4-BC/PMS system under the optimum conditions of 10 wt% Co3O4 loading on BC, 0.2 g/L. Co3O4-BC, 10 mM PMS and pH 7 within 10 min. The Co3O4/BC composites had a synergistic effect on the catalytic activity possibly because the conducting BC promoted electron transfer between the Co species and HSO5- and thus accelerated the Co3+/Co(2+)redox cycle. Additionally, over 85.0 +/- 1.5% of CAP was still removed in the 10th run. Although both SO4 center dot- and OH center dot were identified as the main active species, SO4 center dot- played a dominant role in CAP degradation. In addition, two other chloramphenicols, i.e., florfenicol (FF) and thiamphenicol (TAP), were also effectively degraded with percentages of 86.4 +/- 13% and 71.8 +/- 1.0%, respectively. This study provides a promising catalyst Co3O4-BC to activate PMS for efficient and persistent antibiotics degradation. (C) 2019 Elsevier Ltd. All rights reserved

Brain structural covariance networks in obsessive-compulsive disorder: a graph analysis from the ENIGMA Consortium.

Brain structural covariance networks reflect covariation in morphology of different brain areas and are thought to reflect common trajectories in brain development and maturation. Large-scale investigation of structural covariance networks in obsessive-compulsive disorder (OCD) may provide clues to the pathophysiology of this neurodevelopmental disorder. Using T1-weighted MRI scans acquired from 1616 individuals with OCD and 1463 healthy controls across 37 datasets participating in the ENIGMA-OCD Working Group, we calculated intra-individual brain structural covariance networks (using the bilaterally-averaged values of 33 cortical surface areas, 33 cortical thickness values, and six subcortical volumes), in which edge weights were proportional to the similarity between two brain morphological features in terms of deviation from healthy controls (i.e. z-score transformed). Global networks were characterized using measures of network segregation (clustering and modularity), network integration (global efficiency), and their balance (small-worldness), and their community membership was assessed. Hub profiling of regional networks was undertaken using measures of betweenness, closeness, and eigenvector centrality. Individually calculated network measures were integrated across the 37 datasets using a meta-analytical approach. These network measures were summated across the network density range of K = 0.10-0.25 per participant, and were integrated across the 37 datasets using a meta-analytical approach. Compared with healthy controls, at a global level, the structural covariance networks of OCD showed lower clustering (P < 0.0001), lower modularity (P < 0.0001), and lower small-worldness (P = 0.017). Detection of community membership emphasized lower network segregation in OCD compared to healthy controls. At the regional level, there were lower (rank-transformed) centrality values in OCD for volume of caudate nucleus and thalamus, and surface area of paracentral cortex, indicative of altered distribution of brain hubs. Centrality of cingulate and orbito-frontal as well as other brain areas was associated with OCD illness duration, suggesting greater involvement of these brain areas with illness chronicity. In summary, the findings of this study, the largest brain structural covariance study of OCD to date, point to a less segregated organization of structural covariance networks in OCD, and reorganization of brain hubs. The segregation findings suggest a possible signature of altered brain morphometry in OCD, while the hub findings point to OCD-related alterations in trajectories of brain development and maturation, particularly in cingulate and orbitofrontal regions

Hepatocyte Growth Factor Increases Osteopontin Expression in Human Osteoblasts through PI3K, Akt, c-Src, and AP-1 Signaling Pathway

BACKGROUND: Hepatocyte growth factor (HGF) has been demonstrated to stimulate osteoblast proliferation and participated bone remodeling. Osteopontin (OPN) is a secreted phosphoglycoprotein that belongs to the SIBLING family and is present during bone mineralization. However, the effects of HGF on OPN expression in human osteoblasts are large unknown. METHODOLOGY/PRINCIPAL FINDINGS: Here we found that HGF induced OPN expression in human osteoblasts dose-dependently. HGF-mediated OPN production was attenuated by c-Met inhibitor and siRNA. Pretreatment of osteoblasts with PI3K inhibitor (Ly294002), Akt inhibitor, c-Src inhibitor (PP2), or AP-1 inhibitor (curcumin) blocked the potentiating action of HGF. Stimulation of osteoblasts with HGF enhanced PI3K, Akt, and c-Src activation. In addition, incubation of cells with HGF also increased c-Jun phosphorylation, AP-1-luciferase activity, and c-Jun binding to the AP-1 element on the OPN promoter. HGF-mediated AP-1-luciferase activity and c-Jun binding to the AP-1 element was reduced by c-Met inhibitor, Ly294002, Akt inhibitor, and PP2. CONCLUSIONS/SIGNIFICANCE: Our results suggest that the interaction between HGF and c-Met increases OPN expression in human osteoblasts via the PI3K, Akt, c-Src, c-Jun, and AP-1 signaling pathway

Identification of Antifreeze Proteins and Their Functional Residues by Support Vector Machine and Genetic Algorithms based on n-Peptide Compositions

For the first time, multiple sets of n-peptide compositions from antifreeze protein (AFP) sequences of various cold-adapted fish and insects were analyzed using support vector machine and genetic algorithms. The identification of AFPs is difficult because they exist as evolutionarily divergent types, and because their sequences and structures are present in limited numbers in currently available databases. Our results reveal that it is feasible to identify the shared sequential features among the various structural types of AFPs. Moreover, we were able to identify residues involved in ice binding without requiring knowledge of the three-dimensional structures of these AFPs. This approach should be useful for genomic and proteomic studies involving cold-adapted organisms

Bayesian Spatio-Temporal Modeling of Schistosoma japonicum Prevalence Data in the Absence of a Diagnostic ‘Gold’ Standard

Schistosomiasis is a serious public health problem in the People's Republic of China and elsewhere, and mapping of risk areas is important for guiding control interventions. Here, a 10-year surveillance database from Dangtu County in the southeastern part of the People's Republic of China was utilized for modeling the spatial and temporal distribution of infections in relation to environmental features and socioeconomic factors. Disease surveillance was done on the basis of a serological test, and we explicitly considered the imperfect sensitivity and specificity of the test when modeling the ‘true’ infection prevalence of Schistosoma japonicum. We then produced a risk map for S. japonicum transmission, which can assist decision making for local control interventions. Our work emphasizes the importance of accounting for the uncertainty in the diagnosis of schistosomiasis, and the potential of predicting the spatial and temporal distribution of the disease when using a Bayesian modeling framework. Our study can therefore serve as a template for future risk profiling of neglected tropical diseases studies, particularly when exploring spatial and temporal disease patterns in relation to environmental and socioeconomic factors, and how to account for the influence of diagnostic uncertainty

Hf-based high-k materials for Si nanocrystal floating gate memories

Pure and Si-rich HfO2 layers fabricated by radio frequency sputtering were utilized as alternative tunnel oxide layers for high-k/Si-nanocrystals-SiO2/SiO2 memory structures. The effect of Si incorporation on the properties of Hf-based tunnel layer was investigated. The Si-rich SiO2 active layers were used as charge storage layers, and their properties were studied versus deposition conditions and annealing treatment. The capacitance-voltage measurements were performed to study the charge trapping characteristics of these structures. It was shown that with specific deposition conditions and annealing treatment, a large memory window of about 6.8 V is achievable at a sweeping voltage of ± 6 V, indicating the utility of these stack structures for low-operating-voltage nonvolatile memory devices

Behavior and Impact of Zirconium in the Soil–Plant System: Plant Uptake and Phytotoxicity

Because of the large number of sites they pollute, toxic metals that contaminate terrestrial ecosystems are increasingly of environmental and sanitary concern (Uzu et al. 2010, 2011; Shahid et al. 2011a, b, 2012a). Among such metals is zirconium (Zr), which has the atomic number 40 and is a transition metal that resembles titanium in physical and chemical properties (Zaccone et al. 2008). Zr is widely used in many chemical industry processes and in nuclear reactors (Sandoval et al. 2011; Kamal et al. 2011), owing to its useful properties like hardness, corrosion-resistance and permeable to neutrons (Mushtaq 2012). Hence, the recent increased use of Zr by industry, and the occurrence of the Chernobyl and Fukashima catastrophe have enhanced environmental levels in soil and waters (Yirchenko and Agapkina 1993; Mosulishvili et al. 1994 ; Kruglov et al. 1996)