The emergence of multidrug-resistant bacteria presents a severe threat to public health and causes extensive losses in livestock husbandry and aquaculture. Effective strategies to control such infections are in high demand. Enhancing host immunity is an ideal strategy with fewer side effects than antibiotics. To explore metabolite candidates, we applied a metabolomics approach to investigate the metabolic profiles of mice after Klebsiella pneumoniae infection. Compared with the mice that died from K. pneumoniae infection, mice that survived the infection displayed elevated levels of l-valine. Our analysis showed that l-valine increased macrophage phagocytosis, thereby reducing the load of pathogens; this effect was not only limited to K. pneumoniae but also included Escherichia coli clinical isolates in infected tissues. Two mechanisms are involved in this process: l-valine activating the PI3K/Akt1 pathway and promoting NO production through the inhibition of arginase activity. The NO precursor l-arginine is necessary for l-valine-stimulated macrophage phagocytosis. The valine-arginine combination therapy effectively killed K. pneumoniae and exerted similar effects in other Gram-negative (E. coli and Pseudomonas aeruginosa) and Gram-positive (Staphylococcus aureus) bacteria. Our study extends the role of metabolism in innate immunity and develops the possibility of employing the metabolic modulator-mediated innate immunity as a therapy for bacterial infections.
The efficiency of direct methanol fuel cell (DMFC) is largely determined by the activity and durability of methanol oxidation reaction (MOR) catalysts. Herein, we present a CO-resilient MOR catalyst of palladium-tin nano-alloy anchored on Se-doped MXene (PdSn 0.5 /SeÀ Ti 3 C 2 ) via a progressive one-step electrochemical deposition strategy. MOR mass activity resulting from Pd/SeÀ Ti 3 C 2 catalyst (1046.2 mA mg À 1 ) is over 2-fold larger than that of Pd/Ti 3 C 2 , suggesting that the introduction of Se atoms on MXene might accelerate the reaction kinetics. PdSn 0.5 /SeÀ Ti 3 C 2 with Se-doping progress of MXene and the cooperated PdÀ Sn sites has a superior MOR mass activity (4762.8 mA mg À 1 ), outperforming many other reported Pd-based catalysts. Both experimental results and theoretical calculation reveal that boosted electron interaction of metal crystals with Se-doped MXene and optimized distribution of PdÀ Sn sites can modulate the d band center, reduce adsorption energies of CO* at Pd site and enhance OH* generation at Sn site, resulting in highly efficient removal of CO intermediates by reaction with neighboring OH species on adjacent Sn sites.
The internet is an abundant source of news every day. Thus, efficient algorithms to extract keywords from the text are important to obtain information quickly. However, the precision and recall of mature keyword extraction algorithms need improvement. TextRank, which is derived from the PageRank algorithm, uses word graphs to spread the weight of words. The keyword weight propagation in TextRank focuses only on word frequency. To improve the performance of the algorithm, we propose Semantic Clustering TextRank (SCTR), a semantic clustering news keyword extraction algorithm based on TextRank. Firstly, the word vectors generated by the Bidirectional Encoder Representation from Transformers (BERT) model are used to perform k-means clustering to represent semantic clustering. Then, the clustering results are used to construct a TextRank weight transfer probability matrix. Finally, iterative calculation of word graphs and extraction of keywords are performed. The test target of this experiment is a Chinese news library. The results of the experiment conducted on this text set show that the SCTR algorithm has greater precision, recall, and F1 value than the traditional TextRank and Term Frequency-Inverse Document Frequency (TF-IDF) algorithms.
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