659 research outputs found

    Sequential Wnt Agonist then Antagonist Treatment Accelerates Tissue Repair and Minimizes Fibrosis

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    Tissue fibrosis compromises organ function and occurs as a potential long-term outcome in response to acute tissue injuries. Currently, lack of mechanistic understanding prevents effective prevention and treatment of the progression from acute injury to fibrosis. Here, we combined quantitative experimental studies with a mouse kidney injury model and a computational approach to determine how the physiological consequences are determined by the severity of ischemia injury, and to identify how to manipulate Wnt signaling to accelerate repair of ischemic tissue damage while minimizing fibrosis. The study reveals that Wnt-mediated memory of prior injury contributes to fibrosis progression, and ischemic preconditioning reduces the risk of death but increases the risk of fibrosis. Furthermore, we validated the prediction that sequential combination therapy of initial treatment with a Wnt agonist followed by treatment with a Wnt antagonist can reduce both the risk of death and fibrosis in response to acute injuries

    Spatial representativeness and uncertainty of eddy covariance carbon flux measurements for upscaling net ecosystem productivity to the grid scale

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    Eddy covariance (EC) measurements are often used to validate net ecosystem productivity (NEP) estimated from satellite remote sensing data and biogeochemical models. However, EC measurements represent an integrated flux over their footprint area, which usually differs from respective model grids or remote sensing pixels. Quantifying the uncertainties of scale mismatch associated with gridded flux estimates by upscaling single EC tower NEP measurements to the grid scale is an important but not yet fully investigated issue due to limited data availability as well as knowledge of flux variability at the grid scale. The Heihe Watershed Allied Telemetry Experimental Research (HiWATER) Multi-Scale Observation Experiment on Evapotranspiration (MUSOEXE) built a flux observation matrix that includes 17 EC towers within a 5 km × 5 km area in a heterogeneous agricultural landscape in northwestern China, providing an unprecedented opportunity to evaluate the uncertainty of upscaling due to spatial representative differences at the grid scale. Based on the HiWATER-MUSOEXE data, this study evaluated the spatial representativeness and uncertainty of EC CO2 flux measurements for upscaling to the grid scale using a scheme that combines a footprint model and a model-data fusion method. The results revealed the large spatial variability of gross primary productivity (GPP), ecosystem respiration (Re), and NEP within the study site during the growing season from 10 June to 14 September 2012. The variability of fluxes led to high variability in the representativeness of single EC towers for grid-scale NEP. The systematic underestimations of a single EC tower may reach 92(±11)%, 30(±11)%, and 165(±150)% and the overestimations may reach 25(±14)%, 20(±13)%, and 40(±33)% for GPP, Re, and NEP, respectively. This finding suggests that remotely sensed NEP at the global scale (e.g., MODIS products) should not be validated against single EC tower data in the case of heterogeneous surfaces. Any systematic bias should be addressed before upscaling EC data to grid scale. Otherwise, most of the systematic bias may be propagated to grid scale due to the scale dependence of model parameters. A systematic bias greater than 20% of the EC measurements can be corrected effectively using four indicators proposed in this study. These results will contribute to the understanding of spatial representativeness of EC towers within a heterogeneous landscape, to upscaling carbon fluxes from the footprint to the grid scale, to the selection of the location of EC towers, and to the reduction in the bias of NEP products by using an improved parameterization scheme of remote-sensing driven models, such as VPRM

    A virus-like particle of the hepatitis B virus preS antigen elicits robust neutralizing antibodies and T cell responses in mice

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    The preS antigen of hepatitis B virus (HBV) corresponds to the N-terminal polypeptide in the large (L) antigen in addition to the small (S) antigen. The virus-like particle (VLP) of the S antigen is widely used as a vaccine to protect the population from HBV infection. The presence of the S antigen and its antibodies in patient blood has been used as markers to monitor hepatitis B. However, there is very limited knowledge about the preS antigen. We generated a preS VLP that is formed by a chimeric protein between preS and hemagglutinin (HA), and the matrix protein M1 of influenza virus. The HBV preS antigen is displayed on the surface of preS VLP. Asn112 and Ser98 of preS in VLP were found to be glycosylated and O-glycosylation of Ser98 has not been reported previously. The preS VLP shows a significantly higher immunogenicity than recombinant preS, eliciting robust anti-preS neutralizing antibodies. In addition, preS VLP is also capable of stimulating preS-specific CD8+ and CD4+ T cell responses in Balb/c mice and HBV transgenic mice. Furthermore, preS VLP immunization provided protection against hydrodynamic transfection of HBV DNA in mice. The data clearly suggest that this novel preS VLP could elicit robust immune responses to the HBV antigen, and can be potentially developed into prophylactic and therapeutic vaccines

    NineRec: A Benchmark Dataset Suite for Evaluating Transferable Recommendation

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    Learning a recommender system model from an item's raw modality features (such as image, text, audio, etc.), called MoRec, has attracted growing interest recently. One key advantage of MoRec is that it can easily benefit from advances in other fields, such as natural language processing (NLP) and computer vision (CV). Moreover, it naturally supports transfer learning across different systems through modality features, known as transferable recommender systems, or TransRec. However, so far, TransRec has made little progress, compared to groundbreaking foundation models in the fields of NLP and CV. The lack of large-scale, high-quality recommendation datasets poses a major obstacle. To this end, we introduce NineRec, a TransRec dataset suite that includes a large-scale source domain recommendation dataset and nine diverse target domain recommendation datasets. Each item in NineRec is represented by a text description and a high-resolution cover image. With NineRec, we can implement TransRec models in an end-to-end training manner instead of using pre-extracted invariant features. We conduct a benchmark study and empirical analysis of TransRec using NineRec, and our findings provide several valuable insights. To support further research, we make our code, datasets, benchmarks, and leaderboards publicly available at https://github.com/westlake-repl/NineRec

    CRISPR-Cas technology opens a new era for the creation of novel maize germplasms

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    Maize (Zea mays) is one of the most important food crops in the world with the greatest global production, and contributes to satiating the demands for human food, animal feed, and biofuels. With population growth and deteriorating environment, efficient and innovative breeding strategies to develop maize varieties with high yield and stress resistance are urgently needed to augment global food security and sustainable agriculture. CRISPR-Cas-mediated genome-editing technology (clustered regularly interspaced short palindromic repeats (CRISPR)-Cas (CRISPR-associated)) has emerged as an effective and powerful tool for plant science and crop improvement, and is likely to accelerate crop breeding in ways dissimilar to crossbreeding and transgenic technologies. In this review, we summarize the current applications and prospects of CRISPR-Cas technology in maize gene-function studies and the generation of new germplasm for increased yield, specialty corns, plant architecture, stress response, haploid induction, and male sterility. Optimization of gene editing and genetic transformation systems for maize is also briefly reviewed. Lastly, the challenges and new opportunities that arise with the use of the CRISPR-Cas technology for maize genetic improvement are discussed

    Relationship between Non-Pathogenic Bacteria from Eggs of Healthy Laying Ducks and Flora Structure in the Genital Tract and Cecum

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    Objective: The aim was to investigate whether a bacterial flora exists in the eggs of healthy laying ducks (Ma breed), and if yes, whether the bacterial flora could be associated with those in the genital tract and cecum. Methods: Healthy laying ducks were dissected to collect genital tract and cecum tissues, as well as soft- and hard-shelled duck eggs, and cultivable bacteria were counted by plate count method, and the diversity and correlation of uncultured bacterial flora were analyzed by MiSeq high-throughput sequencing. Results: The decreasing order of the total bacterial counts in the samples was cecum > genital tract > hard-shelled egg > soft-shelled egg. The bacterial gene sequences belonged to 56 phyla and 1 319 genera. The abundance and species evenness of bacteria in the cecum and genital tract were higher. The dominant genera included Bacteroides, Megamonas and Campylobacter. Species abundance and dominant concentration were higher in soft- and hard-shell eggs. Pseudomonas and Acinetobacter accounted for 19.01% and 10.01% of the total abundance, respectively. Gene function prediction showed that all samples had high abundance of metabolic and glycolytic functions. The gram-positive and anaerobic phenotypes in the cecum and genital tract were abundant. The pathogenicity and oxidative stress of bacteria in soft and hard shell eggs were significant. The dominant bacterial genera in the four samples were overlapped, and the overlap rates of egg content with the cecum and genital tract were 13.96% and 24.35%, respectively. In addition, the phylogenetic tree analysis showed that the genera in all samples were closely related to each other and shared homology with the significantly contributing genus Bacteroides in the cecum. Conclusion: Duck eggs are not formed in a sterile environment, the bacteria residing in the cecum and reproductive tract of healthy laying ducks can infect different egg structures during its formation and become a part of the internal flora in duck eggs. These results can provide a reference for further research on the characteristics and control of non-pathogenic bacteria in egg contents

    Current climate overrides past climate change in explaining multi-site beta diversity of Lauraceae species in China

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    Background: We aimed to characterise the geographical distribution of Sorensen-based multi-site dissimilarity (beta(sor)) and its underlying true turnover (beta(sim)) and nestedness (beta(sne)) components for Chinese Lauraceae and to analyse their relationships to current climate and past climate change. Methods: We used ensembles of small models (ESMs) to map the current distributions of 353 Lauraceae species in China and calculated beta(sor) and its beta(sim) and beta(sne) components. We tested the relationship between beta(sor), beta s(ne) and beta(sim) with current climate and past climate change related predictors using a series of simultaneous autoregressive (SAR(err)) models. Results: Spatial distribution of beta(sor) of Lauraceae is positively correlated with latitude, showing an inverse relationship to the latitudinal alpha-diversity (species richness) gradient. High beta(sor) occurs at the boundaries of the warm temperate and subtropical zones and at the Qinghai-Tibet Plateau due to high beta(sne). The optimized SAR(err) model explains beta(sor) and beta(sne) well, but not beta(sim). Current mean annual temperature determines beta(sor) and beta(sne) of Lauraceae more than anomalies and velocities of temperature or precipitation since the Last Glacial Maximum. Conclusions: Current low temperatures and high climatic heterogeneity are the main factors explaining the high multi-site beta-diversity of Lauraceae. In contrast to analyses of the beta-diversity of entire species assemblages, studies of single plant families can provide complementary insights into the drivers of beta-diversity of evolutionarily more narrowly defined entities.Peer reviewe
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