BiOCl Decorated NaNbO3 Nanocubes: A Novel p-n Heterojunction Photocatalyst With Improved Activity for Ofloxacin Degradation

BiOCl/NaNbO3 p-n heterojunction photocatalysts with significantly improved photocatalytic performance were fabricated by a facile in-situ growth method. The obtained BiOCl/NaNbO3 samples were characterized by UV-vis absorption spectroscopy, scanning electron microscopy (SEM), X-ray diffraction (XRD), photocurrent (PC) and photoluminescence spectroscopy (PL). The photocatalytic activity of the BiOCl/NaNbO3 samples was investigated by the degradation of a typical antibiotic Ofloxacin (OFX). The experimental results showed that BiOCl/NaNbO3 composites exhibited much higher photocatalytic activity for OFX degradation compared to pure NaNbO3 and BiOCl. The degradation percent of OFX reached 90% within 60 min, and the apparent rate constant was about 8 times as that of pure NaNbO3 and BiOCl. The improved activity can be attributed to the formation of p-n junction between NaNbO3 and BiOCl. The formed p-n junction facilitated the separation of photogenerated holes and electrons, thereby enhancing photocatalytic activity. In addition, the composite photocatalyst showed satisfactory stability for the degradation of OFX. Due to the simple synthesis process, high photocatalytic activity, and the good recyclability of these composite photocatalysts, the results of this study would provide a good example for the rational design of other highly efficient heterojunction photocatalytic materials

Stabilization of the Transcription Factors Slug and Twist by the Deubiquitinase Dub3 is a Key Requirement for Tumor Metastasis

The Epithelial-mesenchymal transition (EMT) represents a cellular de-differentiation process that provides cells with the increased plasticity required during embryonic development, tissue remodeling, wound healing and metastasis. Slug and Twist are two key EMT transcription factors (EMT-TFs) that are tightly regulated via ubiquitination and degradation. How Slug and Twist escape degradation and become stabilized in cancer cells remains unclear. One plausible mechanism of Slug and Twist stabilization involves removal of ubiquitin by deubiquitinases (DUBs). In this study, we identified Dub3 as a novel DUB for both Slug and Twist. We further found that Dub3 overexpression increased Slug and Twist protein levels in a dose-dependent manner, whereas Dub3-knockdown decreased their protein levels. Of importance, Dub3 interacted with Slug and Twist and prevented them from degradation, thereby promoting migration, invasion, and cancer stem cell (CSC)-like properties of breast cancer cells. Intriguingly, Dub3 was identified as an early response gene that was upregulated after exposure to inflammatory cytokines such as IL-6, which plays a critical role in the growth and metastasis of breast cancer cells, as well as the maintenance of breast CSCs. We found that Dub3 played an essential role in IL-6 induced EMT through stabilization of Slug and Twist. Our study has uncovered an IL-6-Dub3-Slug/Twist signaling axis during EMT and suggests potential approaches that could target Dub3 to prevent metastatic breast tumor

Nucleocapsid Protein as Early Diagnostic Marker for SARS

Serum samples from 317 patients with patients with severe acute respiratory syndrome (SARS) were tested for the nucleocapsid (N) protein of SARS-associated coronavirus, with sensitivities of 94% and 78% for the first 5 days and 6–10 days after onset, respectively. The specificity was 99.9%. N protein can be used as an early diagnostic maker for SARS

Evidence for e+e−→γχc1,2e^+e^-\to\gamma\chi_{c1, 2} at center-of-mass energies from 4.009 to 4.360 GeV

Using data samples collected at center-of-mass energies of $\sqrt{s}$ = 4.009, 4.230, 4.260, and 4.360 GeV with the BESIII detector operating at the BEPCII collider, we perform a search for the process $e^+e^-\to\gamma\chi_{cJ}$ $(J = 0, 1, 2)$ and find evidence for $e^+e^-\to\gamma\chi_{c1}$ and $e^+e^-\to\gamma\chi_{c2}$ with statistical significances of 3.0$\sigma$ and 3.4$\sigma$, respectively. The Born cross sections $\sigma^{B}(e^+e^-\to\gamma\chi_{cJ})$, as well as their upper limits at the 90% confidence level are determined at each center-of-mass energy.Comment: 8 pages, 7 figures, 3 table

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

Inferring the Economic Attributes of Urban Rail Transit Passengers Based on Individual Mobility Using Multisource Data

Socioeconomic attributes are essential characteristics of people, and many studies on economic attribute inference focus on data that contain user profile information. For data without user profiles, like smart card data, there is no validated method for inferring individual economic attributes. This study aims to bridge this gap by formulating a mobility to attribute framework to infer passengers’ economic attributes based on the relationship between individual mobility and personal attributes. This framework integrates shop consumer prices, house prices, and smart card data using three steps: individual mobility extraction, location feature identification, and economic attribute inference. Each passenger’s individual mobility is extracted by smart card data. Economic features of stations are described using house price and shop consumer price data. Then, each passenger’s comprehensive consumption indicator set is formulated by integrating these data. Finally, individual economic levels are classified. From the case study of Beijing, commuting distance and trip frequency using the metro have a negative correlation with passengers’ income and the results confirm that metro passengers are mainly in the low- and middle-income groups. This study improves on passenger information extracted from data without user profile information and provides a method to integrate multisource big data mining for more information

Spatio-temporal analysis of rail station ridership determinants in the built environment

The development of new routes and stations, as well as changes in land use, can have significant impacts on public transit ridership. Thus, transport departments and governments should seek to determine the level and spatio-temporal dependency of these impacts with the aim of adjusting services or improving planning. However, existing studies primarily focus on predicting ridership, and pay relatively little attention to analyzing the determinants of ridership from temporal and spatial perspectives. Consequently, no comprehensive cognition of the spatio-temporal relationship between station ridership and the built environment can be obtained from previous models, which makes them unable to facilitate the optimization of transportation demands and services. To rectify this problem, we have employed a Bayesian negative binomial regression model to identify the significant impact factors associated with entry/exit ridership at different periods of the day. Based on this model, we formulated geographically weighted models to analyze the spatial dependency of these impacts over different periods. The spatio-temporal relationship between station ridership and the built environment was analyzed using data from Beijing. The results reveal that the temporal impacts of most ridership determinants are related to the passenger trip patterns. Furthermore, the spatial impacts correspond with the determinants’ spatial distribution, and the results give some implications on urban and transportation planning. This analysis gives a common analytical framework analyzing impacts of urban characteristics on ridership, and extending researches on how we capture the impacts of urban and other factors on ridership from a comprehensive perspective

Comparative analysis of biofilm characterization of probiotic Escherichia coli

Biofilms are thought to play a vital role in the beneficial effects of probiotic bacteria. However, the structure and function of probiotic biofilms are poorly understood. In this work, biofilms of Escherichia coli (E. coli) Nissle 1917 were investigated and compared with those of pathogenic and opportunistic strains (E. coli MG1655, O157:H7) using crystal violet assay, confocal laser scanning microscopy, scanning electron microscopy and FTIR microspectroscopy. The study revealed significant differences in the morphological structure, chemical composition, and spatial heterogeneity of the biofilm formed by the probiotic E. coli strain. In particular, the probiotic biofilm can secrete unique phospholipid components into the extracellular matrix. These findings provide new information on the morphology, architecture and chemical heterogeneity of probiotic biofilms. This information may help us to understand the beneficial effects of probiotics for various applications

Phylogenetic supertree reveals detailed evolution of SARS-CoV-2

Corona Virus Disease 2019 (COVID-19) caused by the emerged coronavirus SARS-CoV-2 is spreading globally. The origin of SARS-Cov-2 and its evolutionary relationship is still ambiguous. Several reports attempted to figure out this critical issue by genome-based phylogenetic analysis, yet limited progress was obtained, principally owing to the disability of these methods to reasonably integrate phylogenetic information from all genes of SARS-CoV-2. Supertree method based on multiple trees can produce the overall reasonable phylogenetic tree. However, the supertree method has been barely used for phylogenetic analysis of viruses. Here we applied the matrix representation with parsimony (MRP) pseudo-sequence supertree analysis to study the origin and evolution of SARS-CoV-2. Compared with other phylogenetic analysis methods, the supertree method showed more resolution power for phylogenetic analysis of coronaviruses. In particular, the MRP pseudo-sequence supertree analysis firmly disputes bat coronavirus RaTG13 be the last common ancestor of SARS-CoV-2, which was implied by other phylogenetic tree analysis based on viral genome sequences. Furthermore, the discovery of evolution and mutation in SARS-CoV-2 was achieved by MRP pseudo-sequence supertree analysis. Taken together, the MRP pseudo-sequence supertree provided more information on the SARS-CoV-2 evolution inference relative to the normal phylogenetic tree based on full-length genomic sequences