Rapid quantification of the surface overflow and underground infiltration in sewer pipes based on computer vision and continuous optimization.

The overloading of the sewer network caused by unwarranted infiltration of stormwater may lead to waterlogging and environmental pollution. The accurate identification of infiltration and surface overflow is essential to predict and reduce these risks. To retrieve the limitations of infiltration estimation and the failure of surface overflow perception using the common stormwater management model (SWMM), a surface overflow and underground infiltration (SOUI) model is proposed to estimate the infiltration and overflow. First, the precipitation, water level of the manhole, surface water depth and images of the overflowing point, and volume at the outfall are collected. Then, the surface waterlogging area is identified based on computer vision to reconstruct the local digital elevation model (DEM) by spatial interpolation, and the relationship between the waterlogging depth, area and volume is established to identify the real-time overflow. Next, a continuous genetic algorithm optimization (CT-GA) model is proposed for the underground sewer system to determine the inflow rapidly. Finally, surface and underground flow estimations are combined to perceive the state of the urban sewer network accurately. The results show that, compared with the common SWMM simulation, the accuracy of the water level simulation is improved by 43.5% during the rainfall period, and the time cost of the computational optimization is reduced by 67.5%. The proposed method can effectively diagnose the operation state and overflow risk of the sewer networks in real time during rainfall seasons.

Combinatorial screening of a panel of FDA-approved drugs identifies several candidates with anti-Ebola activities.

Ebola virus (EBOV), pathogen of Ebola hemorrhagic fever (EHF), is an enveloped filamental RNA virus. Recently, the EHF crisis occurred in the Democratic Republic of the Congo again highlights the urgency for its clinical treatments. However, no Food and Drug Administration (FDA)-approved therapeutics are currently available. Drug repurposing screening is a time- and cost-effective approach for identifying anti-EBOV therapeutics. Here, by combinatorial screening using pseudovirion and minigenome replicon systems we have identified several FDA-approved drugs with significant anti-EBOV activities. These potential candidates include azithromycin, clomiphene, chloroquine, digitoxin, epigallocatechin-gallate, fluvastatin, tetrandrine and tamoxifen. Mechanistic studies revealed that fluvastatin inhibited EBOV pseudovirion entry by blocking the pathway of mevalonate biosynthesis, while the inhibitory effect of azithromycin on EBOV maybe due to its intrinsic cationic amphiphilic structure altering the homeostasis of later endosomal vesicle similar as tamoxifen. Moreover, based on structure and pathway analyses, the anti-EBOV activity has been extended to other family members of statins, such as simvastatin, and multiple other cardiac glycoside drugs, some of which exhibited even stronger activities. More importantly, in searching for drug interaction, we found various synergy between several anti-EBOV drug combinations, showing substantial and powerful synergistic against EBOV infection. In conclusion, our work illustrates a successful and productive approach to identify new mechanisms and targets for treating EBOV infection by combinatorial screening of FDA-approved drugs.

A novel multi-strategy hydrological feature extraction (MHFE) method to improve urban waterlogging risk prediction, a case study of Fuzhou City in China.

Reliable hydrological data ensure the precision of the urban waterlogging simulation. To reduce the simulation error caused by insufficient basic data, a multi-strategy method (MHFE) for extracting hydrological features is proposed, which includes land use/land cover (LULC) extraction (LE) and digital elevation model (DEM) reconstruction (DR). First, the high-resolution remote image, satellite DEM, precipitation, flood points and depth, and planned LULC were collected. Second, the buildings, roads, and other areas of the satellite image were segmented using the U-Net model, and the LULC data with drainage features were extracted by combining the segmentation result with the planned LULC and drainage data. Then, the terrain features of the road were enhanced to construct high-precision DEM based on the fusion of multi-source data, such as elevation points, LULC, and satellite DEM. Finally, the waterlogging model was implemented under different return periods of rainfalls and typhoon rainfall to obtain the waterlogging distribution and water depth. The simulation results were compared with historical waterlogging event data and water depth observations. The results indicated that the proposed method significantly improved the accuracy of the simulation. In terms of identifying the waterlogging points, the average F1 score increased by 0.36, 0.20, and 0.07 compared to the raw model and the single LE and DR methods, respectively. In terms of water depth simulation, the average Nash-Sutcliffe efficiency (NSE) was increased from -0.24 to 0.86, with DR and LE contributing to 79.1 % and 20.9 %, respectively. The principal contribution and novelty of this paper is to explore the generic method that enhance the hydrological data, and the findings of this study improved the performance of urban waterlogging simulation.

Guanylate-binding protein 1 participates in cellular antiviral response to dengue virus.

BACKGROUND: Dengue virus (DENV), the causative agent of human Dengue hemorrhagic fever, is a mosquito-borne virus found in tropical and sub-tropical regions around the world. Vaccines against DENV are currently unavailable. Guanylate-binding protein 1 (GBP1) is one of the Interferon (IFN) stimulated genes (ISGs) and has been shown important for host immune defense against various pathogens. However, the role of GBP1 during DENV infection remains unclarified. In this study, we evaluated the relevance of GBP1 to DENV infection in in vitro model. FINDINGS: Quantitative RT-PCR (qRT-PCR) and Western blot showed that the expression of mouse Gbp1 was dramatically upregulated in DENV-infected RAW264.7 cells. The intracellular DENV loads were significantly higher in Gbp1 silenced cells compared with controls. The expression levels of selective anti-viral cytokines were decreased in Gbp1 siRNA treated cells, while the transcription factor activity of NF-κB was impaired upon GBP1 silencing during infection. CONCLUSIONS: Our data suggested that GBP1 plays an antiviral role during DENV infection.

Direct inhibitory effect on viral entry of influenza A and SARS-CoV-2 viruses by azithromycin.

OBJECTIVES: Using strategy of drug repurposing, antiviral agents against influenza A virus (IAV) and newly emerging SARS-coronavirus 2 (SARS-CoV-2, also as 2019-nCoV) could be quickly screened out. MATERIALS AND METHODS: A previously reported engineered replication-competent PR8 strain carrying luciferase reporter gene (IAV-luc) and multiple pseudotyped IAV and SARS-CoV-2 virus was used. To specifically evaluate the pH change of vesicles containing IAV, we constructed an A549 cell line with endosomal and lysosomal expression of pHluorin2. RESULTS: Here, we identified azithromycin (AZ) as an effective inhibitor against multiple IAV and SARS-CoV-2 strains. We found that AZ treatment could potently inhibit IAV infection in vitro. Moreover, using pseudotyped virus model, AZ could also markedly block the entry of SARS-CoV-2 in HEK293T-ACE2 and Caco2 cells. Mechanistic studies further revealed that such effect was independent of interferon signalling. AZ treatment neither impaired the binding and internalization of IAV virions, nor the viral replication, but rather inhibited the fusion between viral and vacuolar membranes. Using a NPC1-pHluorin2 reporter cell line, we confirmed that AZ treatment could alkalize the vesicles containing IAV virions, thereby preventing pH-dependent membrane fusion. CONCLUSIONS: Overall, our findings demonstrate that AZ can exert broad-spectrum antiviral effects against IAV and SARS-CoV-2, and could be served as a potential clinical anti-SARS-CoV-2 drug in emergency as well as a promising lead compound for the development of next-generation anti-IAV drugs.

A human programmed death-ligand 1-expressing mouse tumor model for evaluating the therapeutic efficacy of anti-human PD-L1 antibodies.

Huge efforts have been devoted to develop therapeutic monoclonal antibodies targeting human Programmed death-ligand 1 (hPD-L1) for treating various types of human cancers. However, thus far there is no suitable animal model for evaluating the anti-tumor efficacy of such antibodies against hPD-L1. Here we report the generation of a robust and effective system utilizing hPD-L1-expressing mouse tumor cells to study the therapeutic activity and mode of action of anti-human PD-L1 in mice. The model has been validated by using a clinically proven hPD-L1 blocking antibody. The anti-hPD-L1 antibody treatment resulted in potent dose-dependent rejection of the human PD-L1-expressing tumors in mice. Consistent with what have observed in autochthonous mouse tumor models and cancer patients, the hPD-L1 tumor bearing mice treated by anti-hPD-L1 antibody showed rapid activation, proliferation and reinvigoration of the cytolytic effector function of CD8+T cells inside tumor tissues. Moreover, anti-hPD-L1 treatment also led to profound inhibition of Treg expansion and shifting of myeloid cell profiles, showing bona fide induction of multilateral anti-tumor responses by anti-hPD-L1 blockade. Thus, this hPD-L1 mouse model system would facilitate the pre-clinical investigation of therapeutic efficacy and immune modulatory function of various forms of anti-hPD-L1 antibodies.

Chloroquine, a FDA-approved Drug, Prevents Zika Virus Infection and its Associated Congenital Microcephaly in Mice.

Zika virus (ZIKV) has become a global public health emergency due to its rapidly expanding range and its ability to cause severe congenital defects such as microcephaly. However, there are no FDA-approved therapies or vaccines against ZIKV infection. Through our screening of viral entry inhibitors, we found that chloroquine (CQ), a commonly used antimalarial and a FDA-approved drug that has also been repurposed against other pathogens, could significantly inhibit ZIKV infection in vitro, by blocking virus internalization. We also demonstrated that CQ attenuates ZIKV-associated morbidity and mortality in mice. Finally, we proved that CQ protects fetal mice from microcephaly caused by ZIKV infection. Our methodology of focusing on previously identified antivirals in screens for effectiveness against ZIKV proved to be a rapid and efficient means of discovering new ZIKV therapeutics. Selecting drugs that were previously FDA-approved, such as CQ, also improves the likelihood that they may more quickly reach stages of clinical testing and use by the public.

Matrix metalloproteinase 3 promotes cellular anti-dengue virus response via interaction with transcription factor NFκB in cell nucleus.

Dengue virus (DENV), the causative agent of human Dengue hemorrhagic fever, is a mosquito-borne virus of immense global health importance. Characterization of cellular factors promoting or inhibiting DENV infection is important for understanding the mechanism of DENV infection. In this report, MMP3 (stromelysin-1), a secretory endopeptidase that degrades extracellular matrices, has been shown promoting cellular antiviral response against DENV infection. Quantitative RT-PCR and Western Blot showed that the expression of MMP3 was upregulated in DENV-infected RAW264.7 cells. The intracellular viral loads were significantly higher in MMP3 silenced cells compared with controls. The expression level of selective anti-viral cytokines were decreased in MMP3 siRNA treated cells, and the transcription factor activity of NFκB was significantly impaired upon MMP3 silencing during DENV infection. Further, we found that MMP3 moved to cell nucleus upon DENV infection and colocalized with NFκB P65 in nucleus. Co-immunoprecipitation analysis suggested that MMP3 directly interacted with NFκB in nucleus during DENV infection and the C-terminal hemopexin-like domain of MMP3 was required for the interaction. This study suggested a novel role of MMP3 in nucleus during viral infection and provided new evidence for MMPs in immunomodulation.