Fabrication and Characteristics of Macroporous TiO

Macroporous TiO2 photocatalyst was synthesized by a facile nanocasting method using polystyrene (PS) spherical particles as the hard template. The synthesized photocatalyst was characterized by transmission electron microscope (TEM), scanning electron microscopy (SEM), thermogravimetry-differential thermogravimetry (TG-DTG), X-ray diffraction (XRD), and N2-sorption. TEM, SEM, and XRD characterizations confirmed that the macroporous TiO2 photocatalyst is composed of anatase phase. The high specific surface area of 87.85 m2/g can be achieved according to the N2-sorption analysis. Rhodamine B (RhB) was chosen as probe molecule to evaluate the photocatalytic activity of the TiO2 catalysts. Compared with the TiO2 materials synthesized in the absence of PS spherical template, the macroporous TiO2 photocatalyst sintered at 500°C exhibits much higher activity on the degradation of RhB under the UV irradiation, which can be assigned to the well-structured macroporosity. The macroporous TiO2 material presents great potential in the fields of environmental remediation and energy conversion and storage

Evaluation of Analgesic and Anti-Inflammatory Activities of Water Extract of Galla Chinensis In Vivo

Aim. Pain and inflammation are associated with many diseases in humans and animals. Galla Chinensis, a traditional Chinese medicine, has a variety of pharmacological properties. The purpose of this study was to evaluate analgesic and anti-inflammatory activities of Galla Chinensis through different animal models. Method. The analgesic activities were evaluated by hot-plate and writhing tests. The anti-inflammatory effects were assessed by ear edema, capillary permeability, and paw edema tests. The contents of cytokines (NO, iNOS, PGE2, and IL-10) in serum of rats in paw edema test were inspected by ELISA assays. Results. In the hot-plate test, Galla Chinensis could significantly extend pain threshold when compared to control group. The inhibitory rates of writhes ranged from 36.62% to 68.57% in Galla Chinensis-treated mice. Treatment with Galla Chinensis (1 and 0.5 g/kg) could significantly inhibit ear edema (47.45 and 36.91%, resp.; P < 0.01). Galla Chinensis (1 g/kg) had significant (P < 0.05) anti-inflammatory activity in capillary permeability test (29.04%). In carrageenan-induced edema test, the inhibitory rates were 43.71% and 44.07% (P < 0.01) at 1 h and 2 h after administration of Galla Chinensis (1 g/kg), respectively, and the levels of proinflammatory cytokines were significantly reduced. Conclusion. These results suggest that Galla Chinensis has analgesic and anti-inflammatory effects, which may be a candidate drug for the treatment of inflammation and pain

Evidence for a Monolayer Excitonic Insulator

The interplay between topology and correlations can generate a variety of unusual quantum phases, many of which remain to be explored. Recent advances have identified monolayer WTe2 as a promising material for exploring such interplay in a highly tunable fashion. The ground state of this two-dimensional (2D) crystal can be electrostatically tuned from a quantum spin Hall insulator (QSHI) to a superconductor. However, much remains unknown about the nature of these ground states, including the gap-opening mechanism of the insulating state. Here we report systematic studies of the insulating phase in WTe2 monolayer and uncover evidence supporting that the QSHI is also an excitonic insulator (EI). An EI, arising from the spontaneous formation of electron-hole bound states (excitons), is a largely unexplored quantum phase to date, especially when it is topological. Our experiments on high-quality transport devices reveal the presence of an intrinsic insulating state at the charge neutrality point (CNP) in clean samples. The state exhibits both a strong sensitivity to the electric displacement field and a Hall anomaly that are consistent with the excitonic pairing. We further confirm the correlated nature of this charge-neutral insulator by tunneling spectroscopy. Our results support the existence of an EI phase in the clean limit and rule out alternative scenarios of a band insulator or a localized insulator. These observations lay the foundation for understanding a new class of correlated insulators with nontrivial topology and identify monolayer WTe2 as a promising candidate for exploring quantum phases of ground-state excitons.Comment: 37 pages, 4 Main Figures + 15 SI Figur

In Vivo

Aim. Dermatophytosis is one of the main fungal diseases in humans and animals all over the world. Galla chinensis, a traditional medicine, has various pharmacological effects. The goal of this study was to evaluate the treatment effect of Galla chinensis solution (GCS) on dermatophytosis-infected dogs (Microsporum canis, Microsporum gypseum, and Trichophyton mentagrophytes, resp.). Methods. The treatment effects of GCS were evaluated by mycological cure rates and clinical score comprised of three indices, including inflammation, hair loss, and lesion scale. Results. The results showed that, in the three models of dermatophytosis, GCS significantly (P<0.05) improved skin lesions and fungal eradication. GCS (10% and 5%) had higher efficacy compared to the positive control (Tujingpi Tincture). The fungal eradication efficacy exceeds 85% after treatment with GCS (10%, 5%, and 2.5%) on day 14. Conclusion. The GCS has antidermatophytosis effect in dogs, which may be a candidate drug for the treatment of dermatophytosis

The Medical Segmentation Decathlon

International challenges have become the de facto standard for comparative assessment of image analysis algorithms given a specific task. Segmentation is so far the most widely investigated medical image processing task, but the various segmentation challenges have typically been organized in isolation, such that algorithm development was driven by the need to tackle a single specific clinical problem. We hypothesized that a method capable of performing well on multiple tasks will generalize well to a previously unseen task and potentially outperform a custom-designed solution. To investigate the hypothesis, we organized the Medical Segmentation Decathlon (MSD) - a biomedical image analysis challenge, in which algorithms compete in a multitude of both tasks and modalities. The underlying data set was designed to explore the axis of difficulties typically encountered when dealing with medical images, such as small data sets, unbalanced labels, multi-site data and small objects. The MSD challenge confirmed that algorithms with a consistent good performance on a set of tasks preserved their good average performance on a different set of previously unseen tasks. Moreover, by monitoring the MSD winner for two years, we found that this algorithm continued generalizing well to a wide range of other clinical problems, further confirming our hypothesis. Three main conclusions can be drawn from this study: (1) state-of-the-art image segmentation algorithms are mature, accurate, and generalize well when retrained on unseen tasks; (2) consistent algorithmic performance across multiple tasks is a strong surrogate of algorithmic generalizability; (3) the training of accurate AI segmentation models is now commoditized to non AI experts

Phylogeny and Metabolic Potential of the Methanotrophic Lineage MO3 in Beijerinckiaceae from the Paddy Soil through Metagenome-Assembled Genome Reconstruction

Although the study of aerobic methane-oxidizing bacteria (MOB, methanotrophs) has been carried out for more than a hundred years, there are many uncultivated methanotrophic lineages whose metabolism is largely unknown. Here, we reconstructed a nearly complete genome of a Beijerinckiaceae methanotroph from the enrichment of paddy soil by using nitrogen-free M2 medium. The methanotroph labeled as MO3_YZ.1 had a size of 3.83 Mb, GC content of 65.6%, and 3442 gene-coding regions. Based on phylogeny of pmoA gene and genome and the genomic average nucleotide identity, we confirmed its affiliation to the MO3 lineage and a close relationship to Methylocapsa. MO3_YZ.1 contained mxaF- and xoxF-type methanol dehydrogenase. MO3_YZ.1 used the serine cycle to assimilate carbon and regenerated glyoxylate through the glyoxylate shunt as it contained isocitrate lyase and complete tricarboxylic acid cycle-coding genes. The ethylmalonyl-CoA pathway and Calvin&ndash;Benson&ndash;Bassham cycle were incomplete in MO3_YZ.1. Three acetate utilization enzyme-coding genes were identified, suggesting its potential ability to utilize acetate. The presence of genes for N2 fixation, sulfur transformation, and poly-&beta;-hydroxybutyrate synthesis enable its survival in heterogeneous habitats with fluctuating supplies of carbon, nitrogen, and sulfur

Conventional methanotrophs are responsible for atmospheric methane oxidation in paddy soils

Soils serve as the biological sink of the potent greenhouse gas methane with exceptionally low concentrations of ~1.84 p.p.m.v. in the atmosphere. The as-yet-uncultivated methane-consuming bacteria have long been proposed to be responsible for this ‘high-affinity’ methane oxidation (HAMO). Here we show an emerging HAMO activity arising from conventional methanotrophs in paddy soil. HAMO activity was quickly induced during the low-affinity oxidation of high-concentration methane. Activity was lost gradually over 2 weeks, but could be repeatedly regained by flush-feeding the soil with elevated methane. The induction of HAMO activity occurred only after the rapid growth of methanotrophic populations, and a metatranscriptome-wide association study suggests that the concurrent high- and low-affinity methane oxidation was catalysed by known methanotrophs rather than by the proposed novel atmospheric methane oxidizers. These results provide evidence of atmospheric methane uptake in periodically drained ecosystems that are typically considered to be a source of atmospheric methane

Resource Allocation in V2X Communications Based on Multi-Agent Reinforcement Learning with Attention Mechanism

In this paper, we study the joint optimization problem of the spectrum and power allocation for multiple vehicle-to-infrastructure (V2I) and vehicle-to-vehicle (V2V) users in cellular vehicle-to-everything (C-V2X) communication, aiming to maximize the sum rate of V2I links while satisfying the low latency requirements of V2V links. However, channel state information (CSI) is hard to obtain accurately due to the mobility of vehicles. In addition, the effective sensing of state information among vehicles becomes difficult in an environment with complex and diverse information, which is detrimental to vehicles collaborating for resource allocation. Thus, we propose a framework of multi-agent deep reinforcement learning based on attention mechanism (AMARL) to improve the V2X communication performance. Specifically, for vehicle mobility, we model the problem as a multi-agent reinforcement learning process, where each V2V link is regarded an agent and all agents jointly intercommunicate with the environment. Each agent allocates spectrum and power through its deep Q network (DQN). To enhance effective intercommunication and the sense of collaboration among vehicles, we introduce an attention mechanism to focus on more relevant information, which in turn reduces the signaling overhead and optimizes their communication performance more explicitly. Experimental results show that the proposed AMARL-based approach can satisfy the requirements of a high rate for V2I links and low latency for V2V links. It also has an excellent adaptability to environmental change