A multi-epitope vaccine GILE against Echinococcus Multilocularis infection in mice

IntroductionThe objective of this study is to construct a multi-epitope vaccine GILE containing B-cell and T-cell epitopes against Echinococcus Multilocularis (E. multilocularis) infection based on the dominant epitopes of E. multilocularis EMY162, LAP, and GLUT1.MethodsThe structure and hydrophobicity of GILE were predicted by SWISSMODEL, pyMOL, SOPMA and VMD, and its sequence was optimized by Optimum™ Codon. The GILE gene was inserted into pCzn1 and transformed into Escherichia coli Arctic express competent cells. IPTG was added to induce the expression of recombinant proteins. High-purity GILE recombinant protein was obtained by Ni-NTA Resin. BALB/c mice were immunized with GILE mixed with Freund’s adjuvant, and the antibody levels and dynamic changes in the serum were detected by ELISA. Lymphocyte proliferation was detected by MTS. The levels of IFN-g and IL-4 were detected by ELISpot and flow cytometry (FCM). T cells were detected by FCM. The growth of hepatic cysts was evaluated by Ultrasound and their weights were measured to evaluate the immune protective effect of GILE.ResultsThe SWISS-MODEL analysis showed that the optimal model was EMY162 95-104―LAP464-479―LAP495-510―LAP396-410―LAP504-518―EMY162112-126. The SOPMA results showed that there were Alpha helix (14.88%), Extended strand (26.25%), Beta turn (3.73%) and Random coil (45.82%) in the secondary structure of GILE. The restriction enzyme digestion and sequencing results suggested that the plasmid pCzn1-GILE was successfully constructed. The SDSPAGE results indicated that the recombinant protein was 44.68 KD. The ELISA results indicated that mice immunized with GILE showed higher levels of serum antibodies compared to the PBS group. The FCM and ELISpot results indicated that mice immunized with GILE secreted more IFN-g and IL-4. Immunization with GILE also led to a significant decrease in the maximum diameter and weight of cysts and stimulated the production of CD4+ and CD8+ T Cell.DiscussionA multi-epitope vaccine GILE with good immunogenicity and antigenicity has been successfully constructed in this study, which may provide important theoretical and experimental bases for the prevention and treatment of E. multilocularis infection

Cell transcriptomic atlas of the non-human primate Macaca fascicularis.

Studying tissue composition and function in non-human primates (NHPs) is crucial to understand the nature of our own species. Here we present a large-scale cell transcriptomic atlas that encompasses over 1 million cells from 45 tissues of the adult NHP Macaca fascicularis. This dataset provides a vast annotated resource to study a species phylogenetically close to humans. To demonstrate the utility of the atlas, we have reconstructed the cell-cell interaction networks that drive Wnt signalling across the body, mapped the distribution of receptors and co-receptors for viruses causing human infectious diseases, and intersected our data with human genetic disease orthologues to establish potential clinical associations. Our M. fascicularis cell atlas constitutes an essential reference for future studies in humans and NHPs.We thank W. Liu and L. Xu from the Huazhen Laboratory Animal Breeding Centre for helping in the collection of monkey tissues, D. Zhu and H. Li from the Bioland Laboratory (Guangzhou Regenerative Medicine and Health Guangdong Laboratory) for technical help, G. Guo and H. Sun from Zhejiang University for providing HCL and MCA gene expression data matrices, G. Dong and C. Liu from BGI Research, and X. Zhang, P. Li and C. Qi from the Guangzhou Institutes of Biomedicine and Health for experimental advice or providing reagents. This work was supported by the Shenzhen Basic Research Project for Excellent Young Scholars (RCYX20200714114644191), Shenzhen Key Laboratory of Single-Cell Omics (ZDSYS20190902093613831), Shenzhen Bay Laboratory (SZBL2019062801012) and Guangdong Provincial Key Laboratory of Genome Read and Write (2017B030301011). In addition, L.L. was supported by the National Natural Science Foundation of China (31900466), Y. Hou was supported by the Natural Science Foundation of Guangdong Province (2018A030313379) and M.A.E. was supported by a Changbai Mountain Scholar award (419020201252), the Strategic Priority Research Program of the Chinese Academy of Sciences (XDA16030502), a Chinese Academy of Sciences–Japan Society for the Promotion of Science joint research project (GJHZ2093), the National Natural Science Foundation of China (92068106, U20A2015) and the Guangdong Basic and Applied Basic Research Foundation (2021B1515120075). M.L. was supported by the National Key Research and Development Program of China (2021YFC2600200).S

Proton-transfer-induced 3D/2D hybrid perovskites suppress ion migration and reduce luminance overshoot

Abstract: Perovskite light-emitting diodes (PeLEDs) based on three-dimensional (3D) polycrystalline perovskites suffer from ion migration, which causes overshoot of luminance over time during operation and reduces its operational lifetime. Here, we demonstrate 3D/2D hybrid PeLEDs with extremely reduced luminance overshoot and 21 times longer operational lifetime than 3D PeLEDs. The luminance overshoot ratio of 3D/2D hybrid PeLED is only 7.4% which is greatly lower than that of 3D PeLED (150.4%). The 3D/2D hybrid perovskite is obtained by adding a small amount of neutral benzylamine to methylammonium lead bromide, which induces a proton transfer from methylammonium to benzylamine and enables crystallization of 2D perovskite without destroying the 3D phase. Benzylammonium in the perovskite lattice suppresses formation of deep-trap states and ion migration, thereby enhances both operating stability and luminous efficiency based on its retardation effect in reorientation

Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States

Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models provide specific, quantitative, and evaluable predictions that inform short-term decisions such as healthcare staffing needs, school closures, and allocation of medical supplies. Starting in April 2020, the US COVID-19 Forecast Hub (https://covid19forecasthub.org/) collected, disseminated, and synthesized tens of millions of specific predictions from more than 90 different academic, industry, and independent research groups. A multimodel ensemble forecast that combined predictions from dozens of groups every week provided the most consistently accurate probabilistic forecasts of incident deaths due to COVID-19 at the state and national level from April 2020 through October 2021. The performance of 27 individual models that submitted complete forecasts of COVID-19 deaths consistently throughout this year showed high variability in forecast skill across time, geospatial units, and forecast horizons. Two-thirds of the models evaluated showed better accuracy than a naïve baseline model. Forecast accuracy degraded as models made predictions further into the future, with probabilistic error at a 20-wk horizon three to five times larger than when predicting at a 1-wk horizon. This project underscores the role that collaboration and active coordination between governmental public-health agencies, academic modeling teams, and industry partners can play in developing modern modeling capabilities to support local, state, and federal response to outbreaks

The United States COVID-19 Forecast Hub dataset

Academic researchers, government agencies, industry groups, and individuals have produced forecasts at an unprecedented scale during the COVID-19 pandemic. To leverage these forecasts, the United States Centers for Disease Control and Prevention (CDC) partnered with an academic research lab at the University of Massachusetts Amherst to create the US COVID-19 Forecast Hub. Launched in April 2020, the Forecast Hub is a dataset with point and probabilistic forecasts of incident cases, incident hospitalizations, incident deaths, and cumulative deaths due to COVID-19 at county, state, and national, levels in the United States. Included forecasts represent a variety of modeling approaches, data sources, and assumptions regarding the spread of COVID-19. The goal of this dataset is to establish a standardized and comparable set of short-term forecasts from modeling teams. These data can be used to develop ensemble models, communicate forecasts to the public, create visualizations, compare models, and inform policies regarding COVID-19 mitigation. These open-source data are available via download from GitHub, through an online API, and through R packages

Enhanced Efficiency and Stability of an Aqueous Lead-Nitrate-Based Organometallic Perovskite Solar Cell

We investigate the stability of an active organometallic perovskite layer prepared from a two-step solution procedure, including spin coating of aqueous lead nitrate (Pb(NO3)(2)) as a Pb2+ source and sequential dipping into a methylammonium iodide (CH3NH3I) solution. The conversion of CH3NH3PbI3 from a uniform Pb(NO3)2 layer generates PbI2-free and large-grain perovskite crystallites owing to an intermediate ion exchange reaction step, resulting in improved humidity resistance and, thereby, improved long-term stability with 93% of the initial power conversion efficiency (PCE) after a period of 20 days. The conventional fast-converted PbI2-dimethylformamide solution system leaves small amounts of intrinsic PbI2 residue on the resulting perovskite and MAPbI(3) crystallites with uncontrollable sizes. This accelerates the generation of PbI2 and the decomposition of the perovskite layer, resulting in poor stability with less than 60% of the initial PCE after a period of 20 days.1142sciescopu