Inosine:A broad-spectrum anti-inflammatory against SARS-CoV-2 infection-induced acute lung injury via suppressing TBK1 phosphorylation

Severe acute respiratory syndrome coronavirus 2(SARS-CoV-2)-induced cytokine storms constitute the primary cause of coronavirus disease 19(COVID-19)progression,severity,criticality,and death.Glucocorticoid and anti-cytokine therapies are frequently administered to treat COVID-19,but have limited clinical efficacy in severe and critical cases.Nevertheless,the weaknesses of these treatment modalities have prompted the development of anti-inflammatory therapy against this infection.We found that the broad-spectrum anti-inflammatory agent inosine downregulated proinflammatory interleukin(IL)-6,upregulated anti-inflammatory IL-10,and ameliorated acute inflammatory lung injury caused by multiple infectious agents.Inosine significantly improved survival in mice infected with SARS-CoV-2.It indirectly impeded TANK-binding kinase 1(TBK1)phosphorylation by binding stimulator of interferon genes(STING)and glycogen synthase kinase-3β(GSK3β),inhibited the activation and nuclear translocation of the downstream transcription factors interferon regulatory factor(IRF3)and nuclear factor kappa B(NF-κB),and downregulated IL-6 in the sera and lung tissues of mice infected with lipopolysaccharide(LPS),H1N1,or SARS-CoV-2.Thus,inosine administration is feasible for clinical anti-inflammatory therapy against severe and critical COVID-19.Moreover,targeting TBK1 is a promising strategy for inhibiting cytokine storms and mitigating acute inflammatory lung injury induced by SARS-CoV-2 and other infectious agents.

Improving sentence simplification model with ordered neurons network

Sentence simplification is an essential task in natural language processing and aims to simplify complex sentences while retaining their primary meanings.To date,the main research works on sentence simplification models have been based on sequence-to-sequence(Seq2Seq)models.However,these Seq2Seq models are incapable of analysing the hierarchical structure of sentences,which is of great significance for sentence simplification.The problem can be addressed with an ON-MULTI-STAGE model constructed based on the improved MULTI-STAGE encoder model.In this model,an ordered neurons network is introduced and can provide sentence-level structural infor-mation for the encoder and decoder.A weak attention connection method is then employed to make the decoder use the sentence-level structural details.Experimental results on two open data sets demonstrated that the constructed model outperforms the state-of-the-art baseline models in sentence simplification.

Effects of an immunosuppressive active component of Periplocae Cortex (Periploca sepium Bge.) on positive selection of thymocytes in vitro

Objective:To determine the effect of an immunosuppressive active component (periploside A) isolated from the stem bark of Periplocae Cortex (Periploca sepium Bge.),a Chinese medicinal herb used in the treatment of rheumatoid arthritis for centuries in China,on positive selection of thymocytes in vitro.Methods:Female C57BL/6 mice at 6 weeks of age were housed in specific pathogen-free conditions.Double-positive thymocytes from C57BL/6 mice were induced into positive selection in vitro with or without periploside A treatment.Cell viability and expression of CD69,CD4,and CD8 were analyzed by flow cytometry.Results:Flow cytometric examination of thymocyte populations revealed that the percentage of CD8+ single-positive thymocytes was decreased by periploside A upon differentiation induced by an anti-CD3 antibody.However,the percentage of CD4+ single-positive thymocytes was decreased by periploside A upon differentiation induced by phorbol 12-myristate 13-acetate/ionomycin.Expression of CD69 plays a major role in prohibiting differentiation of thymocytes.Treatment with periploside A decreased CD69 expression in thymocytes.Conclusion:These results demonstrate that periploside A influences positive selection of thymocytes in vitro.

Joint Toxicity Determination of Clopyralid,Picloram and Benazolin Mixtures on Broad-leaved Weed Lapsana apogonoides Maxim.in Rape Fields

[Objectives]This study was conducted to investigate the compounding of three herbicides:clopyralid,picloram and benazolin,so as to improve the effectiveness of herbicides.[Methods]With Lapsana apogonoides Maxim.as the target and clopyralid,picloram and benazolin as the test agents,seven gradient concentrations were set up to determine the joint toxicity of the three agents.[Results]When the compounding ratio of picloram,clopyralid and benazolin was 2∶1∶6,the maximum co-toxicity coefficient was 290.0.[Conclusions]The compounding of picloram,clopyralid and benazolin has a significant synergistic effect on L.apogonoides,which reduces production costs and environmental pressure,providing technical support for the effective control of broad-leaved weeds such as L.apogonoides.

Improving word vector model with part-of-speech and dependency grammar information

Part-of-speech(POS)and dependency grammar(DG)are the basic components of natural language processing.However,current word vector models have not made full use of both POS information and DG information,and hence the models’performances are limited to some extent.The authors first put forward the concept of POS vector,and then,based on continuous bag-of-words(CBOW),constructed four models:CBOW+P,CBOW+PW,CBOW+G,and CBOW+G+P to incorporate POS information and DG information into word vectors.The CBOW+P and CBOW+PW models are based on POS tagging,the CBOW+G model is based on DG parsing,and the CBOW+G+P model is based on POS tagging and DG parsing.POS information is integrated into the training process of word vectors through the POS vector to solve the problem of the POS similarity being difficult to measure.The POS vector correlation coefficient and distance weighting function are used to train the POS vector as well as the word vector.DG information is used to correct the information loss caused by fixed context windows.Dependency relations weight is used to measure the difference of dependency relations.Experiments demonstrated the superior performance of their models while the time complexity is still kept the same as the base model of CBOW.

A circular single-stranded DNA mycovirus infects plants and confers broad-spectrum fungal resistance

Circular single-stranded DNA(ssDNA)viruses have been rarely found in fungi,and the evolutionary and ecological relationships among ssDNA viruses infecting fungi and other organisms remain unclear.In this study,a novel circular ssDNA virus,tentatively named Diaporthe sojae circular DNA virus 1(DsCDV1),was identified in the phytopathogenic fungus Diaporthe sojae isolated from pear trees.DsCDV1 has a monopartite genome(3185 nt in size)encapsidated in isometric virions(21-26 nm in diameter).The genome comprises seven putative open reading frames encoding a discrete replicase(Rep)split by an intergenic region,a putative capsid protein(CP),several proteins of unknown function(P1-P4),and a long intergenic region.Notably,the two split parts of DsCDV1 Rep share high identities with the Reps of Geminiviridae and Genomoviridae,respectively,indicating an evolutionary linkage with both families.Phylogenetic analysis based on Rep or CP sequences placed DsCDV1 in a unique cluster,supporting the establishment of a new family,tentatively named Gegemycoviridae,intermediate to both families.DsCDV1 significantly attenuates fungal growth and nearly erases fungal virulence when transfected into the host fungus.Remarkably,DsCDV1 can systematically infect tobacco and pear seedlings,providing broad-spectrum resistance to fungal diseases.Subcellular localization analysis revealed that DsCDV1 P3 is systematically localized in the plasmodesmata,while its expression in trans-complementation experiments could restore systematic infection of a movement-deficient plant virus,suggesting that P3 is a movement protein.DsCDV1 exhibits unique molecular and biological traits not observed in other ssDNA viruses,serving as a link between fungal and plant ssDNA viruses and presenting an evolutionary connection between ssDNA viruses and fungi.These findings contribute to expanding our understanding of ssDNA virus diversity and evolution,offering potential biocontrol applications for managing crucial plant diseases.