The COVID-19 pandemic,which was caused by severe acute respiratory syndrome coronavirus 2(SARS-CoV-2),has become a worldwide health crisis due to its transmissibility.SARS-CoV-2 infection results in severe respiratory...The COVID-19 pandemic,which was caused by severe acute respiratory syndrome coronavirus 2(SARS-CoV-2),has become a worldwide health crisis due to its transmissibility.SARS-CoV-2 infection results in severe respiratory illness and can lead to significant complications in affected individuals.These complications encompass symptoms such as coughing,respiratory distress,fever,infectious shock,acute respiratory distress syndrome(ARDS),and even multiple-organ failure.Animal models serve as crucial tools for investigating pathogenic mechanisms,immune responses,immune escape mechanisms,antiviral drug development,and vaccines against SARS-CoV-2.Currently,various animal models for SARS-CoV-2 infection,such as nonhuman primates(NHPs),ferrets,hamsters,and many different mouse models,have been developed.Each model possesses distinctive features and applications.In this review,we elucidate the immune response elicited by SARS-CoV-2 infection in patients and provide an overview of the characteristics of various animal models mainly used for SARS-CoV-2 infection,as well as the corresponding immune responses and applications of these models.A comparative analysis of transcriptomic alterations in the lungs from different animal models revealed that the K18-hACE2 and mouse-adapted virus mouse models exhibited the highest similarity with the deceased COVID-19 patients.Finally,we highlighted the current gaps in related research between animal model studies and clinical investigations,underscoring lingering scientific questions that demand further clarification.展开更多
Small cell lung cancer(SCLC)is a highly malignant and heterogeneous cancer with limited therapeutic options and prognosis prediction models.Here,we analyzed formalin-fixed,paraffin-embedded(FFPE)samples of surgical re...Small cell lung cancer(SCLC)is a highly malignant and heterogeneous cancer with limited therapeutic options and prognosis prediction models.Here,we analyzed formalin-fixed,paraffin-embedded(FFPE)samples of surgical resections by proteomic profiling,and stratified SCLC into three proteomic subtypes(S-I,S-II,and S-III)with distinct clinical outcomes and chemotherapy responses.The proteomic subtyping was an independent prognostic factor and performed better than current tumor–node–metastasis or Veterans Administration Lung Study Group staging methods.The subtyping results could be further validated using FFPE biopsy samples from an independent cohort,extending the analysis to both surgical and biopsy samples.The signatures of the S-II subtype in particular suggested potential benefits from immunotherapy.Differentially overexpressed proteins in S-III,the worst prognostic subtype,allowed us to nominate potential therapeutic targets,indicating that patient selection may bring new hope for previously failed clinical trials.Finally,analysis of an independent cohort of SCLC patients who had received immunotherapy validated the prediction that the S-II patients had better progression-free survival and overall survival after first-line immunotherapy.Collectively,our study provides the rationale for future clinical investigations to validate the current findings for more accurate prognosis prediction and precise treatments.展开更多
Severe acute respiratory syndrome coronavirus 2(SARS-CoV-2),the causative agent of COVID-19,encodes several accessory proteins that have been shown to play crucial roles in regulating the innate immune response.Howeve...Severe acute respiratory syndrome coronavirus 2(SARS-CoV-2),the causative agent of COVID-19,encodes several accessory proteins that have been shown to play crucial roles in regulating the innate immune response.However,their expressions in infected cells and immunogenicity in infected humans and mice are still not fully understood.This study utilized various techniques such as luciferase immunoprecipitation system(LIPS),immunofluorescence assay(IFA),and western blot(WB)to detect accessory protein-specific antibodies in sera of COVID-19 patients.Specific antibodies to proteins 3a,3b,7b,8 and 9c can be detected by LIPS,but only protein 3a antibody was detected by IFA or WB.Antibodies against proteins 3a and 7b were only detected in ICU patients,which may serve as a marker for predicting disease progression.Further,we investigated the expression of accessory proteins in SARS-CoV-2-infected cells and identified the expressions of proteins 3a,6,7a,8,and 9b.We also analyzed their ability to induce antibodies in immunized mice and found that only proteins 3a,6,7a,8,9b and 9c were able to induce measurable antibody productions,but these antibodies lacked neutralizing activities and did not protect mice from SARS-CoV-2 infection.Our findings validate the expression of SARS-CoV-2 accessory proteins and elucidate their humoral immune response,providing a basis for protein detection assays and their role in pathogenesis.展开更多
Currently,decarbonization has become an emerging trend in the power system arena.However,the increasing number of photovoltaic units distributed into a distribution network may result in voltage issues,providing chall...Currently,decarbonization has become an emerging trend in the power system arena.However,the increasing number of photovoltaic units distributed into a distribution network may result in voltage issues,providing challenges for voltage regulation across a large-scale power grid network.Reinforcement learning based intelligent control of smart inverters and other smart building energy management(EM)systems can be leveraged to alleviate these issues.To achieve the best EM strategy for building microgrids in a power system,this paper presents two large-scale multi-agent strategy evaluation methods to preserve building occupants’comfort while pursuing systemlevel objectives.The EM problem is formulated as a general-sum game to optimize the benefits at both the system and building levels.Theα-rank algorithm can solve the general-sum game and guarantee the ranking theoretically,but it is limited by the interaction complexity and hardly applies to the practical power system.A new evaluation algorithm(TcEval)is proposed by practically scaling theα-rank algorithm through a tensor complement to reduce the interaction complexity.Then,considering the noise prevalent in practice,a noise processing model with domain knowledge is built to calculate the strategy payoffs,and thus the TcEval-AS algorithm is proposed when noise exists.Both evaluation algorithms developed in this paper greatly reduce the interaction complexity compared with existing approaches,including ResponseGraphUCB(RG-UCB)andαInformationGain(α-IG).Finally,the effectiveness of the proposed algorithms is verified in the EM case with realistic data.展开更多
To the Editor:Systemic sclerosis(SSc)is an autoimmune disease characterized by,progressive skin and visceral fibrosis,microvasculopathy,and autoimmunity.Circulating auto-antibodies(AAbs)are detectable in 90%to 95%of p...To the Editor:Systemic sclerosis(SSc)is an autoimmune disease characterized by,progressive skin and visceral fibrosis,microvasculopathy,and autoimmunity.Circulating auto-antibodies(AAbs)are detectable in 90%to 95%of patients with SSc.展开更多
基金supported by a grant from the National Key R&D Program of China(No.2021YFC2301700 JS,2022YFC2604102 JS)Major Project of Guangzhou National Laboratory(GZNL2023A01003)+3 种基金the National Natural Science Foundation of China(82025001 JCZ,81971500 JXZ,2022YFC2303700 ARZ)the Guangdong Basic and Applied Basic Research Foundation(2022B1515020059 JS,2021B15150005 JXZ)the State Key Laboratory of Respiratory Disease(SKLRD-Z-202304,QTH)the ZHONGNANSHAN MEDICAIFOUNDATION OF GUANGDONG PROVINCE(No.ZNSA2020013 JCZ).
文摘The COVID-19 pandemic,which was caused by severe acute respiratory syndrome coronavirus 2(SARS-CoV-2),has become a worldwide health crisis due to its transmissibility.SARS-CoV-2 infection results in severe respiratory illness and can lead to significant complications in affected individuals.These complications encompass symptoms such as coughing,respiratory distress,fever,infectious shock,acute respiratory distress syndrome(ARDS),and even multiple-organ failure.Animal models serve as crucial tools for investigating pathogenic mechanisms,immune responses,immune escape mechanisms,antiviral drug development,and vaccines against SARS-CoV-2.Currently,various animal models for SARS-CoV-2 infection,such as nonhuman primates(NHPs),ferrets,hamsters,and many different mouse models,have been developed.Each model possesses distinctive features and applications.In this review,we elucidate the immune response elicited by SARS-CoV-2 infection in patients and provide an overview of the characteristics of various animal models mainly used for SARS-CoV-2 infection,as well as the corresponding immune responses and applications of these models.A comparative analysis of transcriptomic alterations in the lungs from different animal models revealed that the K18-hACE2 and mouse-adapted virus mouse models exhibited the highest similarity with the deceased COVID-19 patients.Finally,we highlighted the current gaps in related research between animal model studies and clinical investigations,underscoring lingering scientific questions that demand further clarification.
基金supported by the National Key R&D Program of China(Grant Nos.2018YFA0507503,2017YFA0505102,2017YFA0505103,and 2017YFA0505104)the National Natural Science Foundation of China(Grant Nos.82072597,62131009,31770892,31970725,31870828,81874237,and 81974016)+2 种基金the Beijing Municipal Natural Science Foundation(Grant No.7192199)the State Key Laboratory of Proteomics(Grant No.SKLP-K202002)the Kaifeng Science and Technology Development Plan Project(Grant No.1806005),China.
文摘Small cell lung cancer(SCLC)is a highly malignant and heterogeneous cancer with limited therapeutic options and prognosis prediction models.Here,we analyzed formalin-fixed,paraffin-embedded(FFPE)samples of surgical resections by proteomic profiling,and stratified SCLC into three proteomic subtypes(S-I,S-II,and S-III)with distinct clinical outcomes and chemotherapy responses.The proteomic subtyping was an independent prognostic factor and performed better than current tumor–node–metastasis or Veterans Administration Lung Study Group staging methods.The subtyping results could be further validated using FFPE biopsy samples from an independent cohort,extending the analysis to both surgical and biopsy samples.The signatures of the S-II subtype in particular suggested potential benefits from immunotherapy.Differentially overexpressed proteins in S-III,the worst prognostic subtype,allowed us to nominate potential therapeutic targets,indicating that patient selection may bring new hope for previously failed clinical trials.Finally,analysis of an independent cohort of SCLC patients who had received immunotherapy validated the prediction that the S-II patients had better progression-free survival and overall survival after first-line immunotherapy.Collectively,our study provides the rationale for future clinical investigations to validate the current findings for more accurate prognosis prediction and precise treatments.
基金supported by grants from the National Natural Science Foundation of China(82002127,81971500,82025001,82172240)National Key R&D Program of China(2021YFC2301700,2022YFC2604100)+1 种基金Guangdong Basic and Applied Basic Research Foundation(2022B1515020059,2021B1515130005)R&D Program of Guangzhou Laboratory(EKPG21-30-2).
文摘Severe acute respiratory syndrome coronavirus 2(SARS-CoV-2),the causative agent of COVID-19,encodes several accessory proteins that have been shown to play crucial roles in regulating the innate immune response.However,their expressions in infected cells and immunogenicity in infected humans and mice are still not fully understood.This study utilized various techniques such as luciferase immunoprecipitation system(LIPS),immunofluorescence assay(IFA),and western blot(WB)to detect accessory protein-specific antibodies in sera of COVID-19 patients.Specific antibodies to proteins 3a,3b,7b,8 and 9c can be detected by LIPS,but only protein 3a antibody was detected by IFA or WB.Antibodies against proteins 3a and 7b were only detected in ICU patients,which may serve as a marker for predicting disease progression.Further,we investigated the expression of accessory proteins in SARS-CoV-2-infected cells and identified the expressions of proteins 3a,6,7a,8,and 9b.We also analyzed their ability to induce antibodies in immunized mice and found that only proteins 3a,6,7a,8,9b and 9c were able to induce measurable antibody productions,but these antibodies lacked neutralizing activities and did not protect mice from SARS-CoV-2 infection.Our findings validate the expression of SARS-CoV-2 accessory proteins and elucidate their humoral immune response,providing a basis for protein detection assays and their role in pathogenesis.
基金the National Key R&D Program of China(No.2021ZD0112700)the Zhejiang Provincial Natural Science Foundation of China(No.LZ22F030006)the Fundamental Research Funds for the Central Universities,China(No.xtr072022001)。
文摘Currently,decarbonization has become an emerging trend in the power system arena.However,the increasing number of photovoltaic units distributed into a distribution network may result in voltage issues,providing challenges for voltage regulation across a large-scale power grid network.Reinforcement learning based intelligent control of smart inverters and other smart building energy management(EM)systems can be leveraged to alleviate these issues.To achieve the best EM strategy for building microgrids in a power system,this paper presents two large-scale multi-agent strategy evaluation methods to preserve building occupants’comfort while pursuing systemlevel objectives.The EM problem is formulated as a general-sum game to optimize the benefits at both the system and building levels.Theα-rank algorithm can solve the general-sum game and guarantee the ranking theoretically,but it is limited by the interaction complexity and hardly applies to the practical power system.A new evaluation algorithm(TcEval)is proposed by practically scaling theα-rank algorithm through a tensor complement to reduce the interaction complexity.Then,considering the noise prevalent in practice,a noise processing model with domain knowledge is built to calculate the strategy payoffs,and thus the TcEval-AS algorithm is proposed when noise exists.Both evaluation algorithms developed in this paper greatly reduce the interaction complexity compared with existing approaches,including ResponseGraphUCB(RG-UCB)andαInformationGain(α-IG).Finally,the effectiveness of the proposed algorithms is verified in the EM case with realistic data.
基金Youth Program of National Natural Science Foundation of China(No. 81501391)medical and health research projects from Shanghai Baoshan Science and Technology Commission(No. 20-E-3)。
文摘To the Editor:Systemic sclerosis(SSc)is an autoimmune disease characterized by,progressive skin and visceral fibrosis,microvasculopathy,and autoimmunity.Circulating auto-antibodies(AAbs)are detectable in 90%to 95%of patients with SSc.
