Tegillarca granosa(T.granosa)is susceptible to heavy metals,which may pose a threat to consumer health.Thus,healthy and polluted T.granosa should be distinguished quickly.This study aimed to rapidly identify heavy met...Tegillarca granosa(T.granosa)is susceptible to heavy metals,which may pose a threat to consumer health.Thus,healthy and polluted T.granosa should be distinguished quickly.This study aimed to rapidly identify heavy metal pollution by using laser-induced breakdown spectroscopy(LIBS)coupled with linear regression classification(LRC).Five types of T.granosa were studied,namely,Cd-,Zn-,Pb-contaminated,mixed contaminated,and control samples.Threshold method was applied to extract the significant variables from LIBS spectra.Then,LRC was used to classify the different types of T.granosa.Other classification models and feature selection methods were used for comparison.LRC was the best model,achieving an accuracy of 90.67%.Results indicated that LIBS combined with LRC is effective and feasible for T.granosa heavy metal detection.展开更多
Coke powder is expected to be an excellent raw material to produce activated carbon because of its high carbon content. Potassium hydroxide(KOH), as an effective activation agent, was reported to be effective in activ...Coke powder is expected to be an excellent raw material to produce activated carbon because of its high carbon content. Potassium hydroxide(KOH), as an effective activation agent, was reported to be effective in activating coke powder. However, the microstructures development in the coke powder and its mechanisms when KOH was applied were still unclear. In this study, effects of KOH on the microstructure activation of coke powder were investigated using the surface area and pore structure analyzer, scanning electron microscope(SEM) and thermogravimetry-differential scanning calorimetry-mass spectrometry(TG-DSC-MS), etc. Results revealed that the addition KOH at its lower ratio(mass ratios of KOH and coke powder in a range of 0.5 and 1) decreased the specific surface area and average lateral sizes, but sharply increased of the specific surface area to 132 m^2·g^-1 and 355 m^2·g^-1 and decreased of the space size of aromatic crystallites upon the further increase of the KOH addition amounts(ratios of KOH and coke powder in a range of 3 and 7), generating a number of new micropores and mesopores. The mechanisms study implied surface reactions between KOH and aliphatic hydrocarbon side chain and other carbon functional groups of the coke powder to destruct aromatic crystallites in one dimension and broaden pores at lower KOH addition. In the activation process, KOH was decomposed to be more active components, which can be rapidly destruct the aromatic layers in spatial scope to form developed porous carbon structures within coke powder at higher KOH addition.展开更多
Tegillarca granosa,as a popular seafood among consumers,is easily susceptible to pollution from heavy metals.Thus,it is essential to develop a rapid detection method for Tegillarca granosa.For this issue,five categori...Tegillarca granosa,as a popular seafood among consumers,is easily susceptible to pollution from heavy metals.Thus,it is essential to develop a rapid detection method for Tegillarca granosa.For this issue,five categories of Tegillarca granosa samples consisting of a healthy group;Zn,Pb,and Cd polluted groups;and a mixed pollution group of all three metals were used to detect heavy metal pollution by combining laser-induced breakdown spectrometry(LIBS)and the newly proposed linear regression classification-sum of rank difference(LRC-SRD)algorithm.As the comparison models,least regression classification(LRC),support vector machine(SVM),and k-nearest neighbor(KNN)and linear discriminant analysis were also utilized.Satisfactory accuracy(0.93)was obtained by LRC-SRD model and which performs better than other models.This demonstrated that LIBS coupled with LRC-SRD is an efficient framework for Tegillarca granosa heavy metal detection and provides an alternative to replace traditional methods.展开更多
Primary liver cancer(PLC) is one of the most common malignant tumors in China. PLC is characterized by insidious onset, rapid progress, poor quality of life, and short survival time. Notably, current treatment strateg...Primary liver cancer(PLC) is one of the most common malignant tumors in China. PLC is characterized by insidious onset, rapid progress, poor quality of life, and short survival time. Notably, current treatment strategies remain unsatisfactory. Traditional Chinese medicines(TCM) have been used to treat a variety of diseases, including liver diseases, for more than 2000 years. In this study, we performed a review of the use frequency and clinical efficacy of TCM in treating PLC. Relevant literature from January 1, 2009, to January 1, 2021 was retrieved from network databases of China National Knowledge Infrastructure(CNKI), Chongqing VIP, Wanfang, PubMed, and SinoMed. The most frequently used TCM and their efficacy in PLC treatment were summarized. Based on the inclusion and exclusion criteria, 33 articles were selected. Overall, the efficacy of the combination of TCM and Western medicines in the treatment of PLC was higher than that in the control groups(i.e. treatment with Western medicines alone)(65.11% vs.44.31%, P <.05). Among the 33 selected articles, 11 were investigated for TCM preparation(marketed drugs) and 22 for TCM formulas. In total, 102 types of TCM(single herbs) were used to treat PLC. The top five most frequently used TCM were Poria(14.71%), Astragali radix(13.73%), Atractylodis Macrocephalae Rhizoma(12.75%), Bupleuri radix(12.75%), and Glycyrrhizae radix et Rhizoma(11.76%). Of the 102 types of TCM, tonics were the most frequently used categories, followed by heat-clearing medicines, blood-invigorating medicines, and stasis-resolving medicines. Of 207 papers, 174(84.06%) could not be subjected to statistical analysis due to research quality. Further high-quality research on herb sources, formula components and dosage, toxicology, and ethics of TCM is necessary. In conclusion, TCM play a promising role in the treatment and management of PLC, although further investigations are warranted.展开更多
Objectives:This study presents a method combining a one-class classifier and laser-induced breakdown spectrometry(LIBS)to quickly identify healthy Tegillarca granosa(T.granosa).Materials and Methods:The sum of ranking...Objectives:This study presents a method combining a one-class classifier and laser-induced breakdown spectrometry(LIBS)to quickly identify healthy Tegillarca granosa(T.granosa).Materials and Methods:The sum of ranking differences(SRD)was used to fuse multiple anomaly detection metrics to build the one-class classifier,which was only trained with healthy T.granosa.The one-class classifier can identify healthy T.granosa to exclude non-healthy T.granosa.The proposed method calculated multiple anomaly detection metrics and standardized them to obtain a fusion matrix.Based on the fusion matrix,the samples were ranked by SRD and those ranked lowest and below the threshold were considered to be unhealthy.Results:Multiple anomaly detection metrics were fused by the SRD algorithm and tested on each band,and the final fusion model achieved an accuracy rate of 98.46%,a sensitivity of 100%,and a specificity of 80%.The remaining three single classification models obtained the following results:the SVDD model achieved an accuracy rate of 87.69%,a sensitivity of 90%,and a specificity of 60%;the OCSVM model achieved an accuracy rate of 80%,a sensitivity of 76.67%,and a specificity of 60%;and the DD-SIMCA model achieved an accuracy rate of 95.38%,a sensitivity of 98.33%,and a specificity of 60%.Conclusions:The experimental results showed that the proposed method achieved better results than the traditional one-class classification methods with a single metric.Therefore,the fusion method effectively improves the performance of traditional one-class classifiers when using LIBS to quickly identify healthy substances(healthy T.granosa).展开更多
Detection of fruit traits by using near-infrared(NIR)spectroscopy may encounter out-of-distribution samples that exceed the generalization ability of a constructed calibration model.Therefore,confidence analysis for a...Detection of fruit traits by using near-infrared(NIR)spectroscopy may encounter out-of-distribution samples that exceed the generalization ability of a constructed calibration model.Therefore,confidence analysis for a given prediction is required,but this cannot be done using common calibration models of NIR spectroscopy.To address this issue,this paper studied the Gaussian process regression(GPR)for fruit traits detection using NIR spectroscopy.The mean and variance of the GPR were used as the predicted value and confidence,respectively.To show this,a real NIR data set related to dry matter content measurements in mango was used.Compared to partial least squares regression(PLSR),GPR showed approximately 14%lower root mean squared error(RMSE)for the in-distribution test set.Compared with no confidence analysis,using the variance of GPR to remove abnormal samples made GPR and PLSR showed approximately 58%and 10%lower RMSE on the mixed distribution test set,respectively(when the type 1 error rate was set to 0.1).Compared with traditional one-class classification methods,the variance of the GPR can be used to effectively eliminate poorly predicted samples.展开更多
Laser-induced breakdown spectroscopy(LIBS)can be used for the rapid detection of heavy metal contamination of Tegillarca granosa(T.granosa),but an appropriate classification model needs to be constructed.In the one-cl...Laser-induced breakdown spectroscopy(LIBS)can be used for the rapid detection of heavy metal contamination of Tegillarca granosa(T.granosa),but an appropriate classification model needs to be constructed.In the one-class classification method,only target samples are needed in training process to achieve the recognition of abnormal samples,which is suitable for rapid identification of healthy T.granosa from those contaminated with uncertain heavy metals.The construction of a one-class classification model for heavy metal detection in T.granosa by LIBS has faced the problem of high-dimension and small samples.To solve this problem,a novel one-class classification method was proposed in this study.Here,the principal component scores and the intensity of the residual spectrum were combined as extracted features.Then,a one-class classifier based on Mahalanobis distance using the extracted features was constructed and its threshold was set by leave-one-out crossvalidation.The sensitivity,specificity and accuracy of the proposed method were reached to 1,0.9333 and 0.9667 respectively,which are superior to the previously reported methods.展开更多
Dendrimer,such as dendrigraft poly-L-lysine(DGL)polymers,with high surface charge density,well-defined structure,and narrow poly-dispersity is often employed as a gene vector,but its transfection efficiency is still p...Dendrimer,such as dendrigraft poly-L-lysine(DGL)polymers,with high surface charge density,well-defined structure,and narrow poly-dispersity is often employed as a gene vector,but its transfection efficiency is still partially inhibited due to poor endosomal escape ability.Herein,we used a surface modification strategy to enhance the endosomal escape ability of DGL polymers,and thus improved its gene transfection efficiency.A library of phenylboronic acid(PBA)modified DGL polymers(PBA-DGLs)was designed to screen efficient small interfering RNA(siRNA)vectors.The lead candidate screened from the library shown a capability of inducing nearly 90% gene silencing in MDA-MB-231 cells.The study of the transfection mechanism revealed that PBA modification not only improves siRNA cellular uptake,but,more importantly,endows DGL polymers the ability of endosomal escape.One of the top candidates from polyplexes was further shielded with hyaluronic acid to construct targeted nanoparticles,and the yielding nanoparticles significantly suppressed the tumor growth in a breast cancer model by effective siRNA delivery.This research provides a general and effective strategy to enhance the endosomal escape and transfection efficiency of dendrimer.展开更多
Multi-drug resistance(MDR)has become the largest obstacle to the success of cancer patients receiving traditional chemotherapeutics or novel targeted drugs.Here,we developed a targeted nanoplatform based on biodegrada...Multi-drug resistance(MDR)has become the largest obstacle to the success of cancer patients receiving traditional chemotherapeutics or novel targeted drugs.Here,we developed a targeted nanoplatform based on biodegradable boronic acid modifiedε-polylysine to co-deliver P-gp siRNA,Bcl-2 siRNA,and doxorubicin for overcoming the challenge.The targeted nanoplatform showed a robust suppressing efficiency for the invasion,proliferation,and colony formation of adriamycin(ADR)resistant breast cancer cell line(MCF-7/ADR)cells in vitro.The ATP responsiveness of the nanoplatform was also proved in the research.In the in vivo antitumor experiment,the targeted nanoplatform showed a significant inhibition of tumor growth with good biocompatibility.The goal of this study is to develop a novel and facile strategy to prepare a highly efficient and safe gene and drug delivery system for MDR breast cancer based on biocompatibleε-polylysine polymers.展开更多
To the Editor:Left ventricular diastolic dysfunction(LVDD)is an unrecognized subclinical presentation of autoimmune diseases(AD)andcarries a worse prognosis.Elevated serum uric acid(SUA),as a_proinflammatory factor,is...To the Editor:Left ventricular diastolic dysfunction(LVDD)is an unrecognized subclinical presentation of autoimmune diseases(AD)andcarries a worse prognosis.Elevated serum uric acid(SUA),as a_proinflammatory factor,is associatedwithchanges in cardiacfunction in the general population as,well as in those with cardiac diseases.展开更多
基金This research was funded by National Natural Science Foundation of China(Nos.31571920,61671378)。
文摘Tegillarca granosa(T.granosa)is susceptible to heavy metals,which may pose a threat to consumer health.Thus,healthy and polluted T.granosa should be distinguished quickly.This study aimed to rapidly identify heavy metal pollution by using laser-induced breakdown spectroscopy(LIBS)coupled with linear regression classification(LRC).Five types of T.granosa were studied,namely,Cd-,Zn-,Pb-contaminated,mixed contaminated,and control samples.Threshold method was applied to extract the significant variables from LIBS spectra.Then,LRC was used to classify the different types of T.granosa.Other classification models and feature selection methods were used for comparison.LRC was the best model,achieving an accuracy of 90.67%.Results indicated that LIBS combined with LRC is effective and feasible for T.granosa heavy metal detection.
基金Supported by the National Key R&D Plan(2016YFE0131100,2017YFB0603101)the Program for Sanjin Scholars of Shanxi Provincethe Talent Training Program of Shanxi Joint Postgraduate Training Base(2016JD07).
文摘Coke powder is expected to be an excellent raw material to produce activated carbon because of its high carbon content. Potassium hydroxide(KOH), as an effective activation agent, was reported to be effective in activating coke powder. However, the microstructures development in the coke powder and its mechanisms when KOH was applied were still unclear. In this study, effects of KOH on the microstructure activation of coke powder were investigated using the surface area and pore structure analyzer, scanning electron microscope(SEM) and thermogravimetry-differential scanning calorimetry-mass spectrometry(TG-DSC-MS), etc. Results revealed that the addition KOH at its lower ratio(mass ratios of KOH and coke powder in a range of 0.5 and 1) decreased the specific surface area and average lateral sizes, but sharply increased of the specific surface area to 132 m^2·g^-1 and 355 m^2·g^-1 and decreased of the space size of aromatic crystallites upon the further increase of the KOH addition amounts(ratios of KOH and coke powder in a range of 3 and 7), generating a number of new micropores and mesopores. The mechanisms study implied surface reactions between KOH and aliphatic hydrocarbon side chain and other carbon functional groups of the coke powder to destruct aromatic crystallites in one dimension and broaden pores at lower KOH addition. In the activation process, KOH was decomposed to be more active components, which can be rapidly destruct the aromatic layers in spatial scope to form developed porous carbon structures within coke powder at higher KOH addition.
基金supported by the Natural Science Foundation of Zhejiang Province(No.LY21C200001)National Natural Science Foundation of China(No.31571920)+1 种基金Wenzhou Science and Technology Project(No.N20160004)Wenzhou Basic Public Welfare Project(No.N20190017)。
文摘Tegillarca granosa,as a popular seafood among consumers,is easily susceptible to pollution from heavy metals.Thus,it is essential to develop a rapid detection method for Tegillarca granosa.For this issue,five categories of Tegillarca granosa samples consisting of a healthy group;Zn,Pb,and Cd polluted groups;and a mixed pollution group of all three metals were used to detect heavy metal pollution by combining laser-induced breakdown spectrometry(LIBS)and the newly proposed linear regression classification-sum of rank difference(LRC-SRD)algorithm.As the comparison models,least regression classification(LRC),support vector machine(SVM),and k-nearest neighbor(KNN)and linear discriminant analysis were also utilized.Satisfactory accuracy(0.93)was obtained by LRC-SRD model and which performs better than other models.This demonstrated that LIBS coupled with LRC-SRD is an efficient framework for Tegillarca granosa heavy metal detection and provides an alternative to replace traditional methods.
基金financially supported by the National Natural Science Foundation of China(81874356)the Open Project of Hubei Key Laboratory of Wudang Local Chinese Medicine Research from Hubei University of Medicine(WDCM2018002,WDCM201917,WDCM201918)+1 种基金the Chinese Medicine Project of Health Commission of Hubei Province(ZY2021010)the Foundation for Innovative Research Team of Hubei University of Medicine(2018YHKT01)。
文摘Primary liver cancer(PLC) is one of the most common malignant tumors in China. PLC is characterized by insidious onset, rapid progress, poor quality of life, and short survival time. Notably, current treatment strategies remain unsatisfactory. Traditional Chinese medicines(TCM) have been used to treat a variety of diseases, including liver diseases, for more than 2000 years. In this study, we performed a review of the use frequency and clinical efficacy of TCM in treating PLC. Relevant literature from January 1, 2009, to January 1, 2021 was retrieved from network databases of China National Knowledge Infrastructure(CNKI), Chongqing VIP, Wanfang, PubMed, and SinoMed. The most frequently used TCM and their efficacy in PLC treatment were summarized. Based on the inclusion and exclusion criteria, 33 articles were selected. Overall, the efficacy of the combination of TCM and Western medicines in the treatment of PLC was higher than that in the control groups(i.e. treatment with Western medicines alone)(65.11% vs.44.31%, P <.05). Among the 33 selected articles, 11 were investigated for TCM preparation(marketed drugs) and 22 for TCM formulas. In total, 102 types of TCM(single herbs) were used to treat PLC. The top five most frequently used TCM were Poria(14.71%), Astragali radix(13.73%), Atractylodis Macrocephalae Rhizoma(12.75%), Bupleuri radix(12.75%), and Glycyrrhizae radix et Rhizoma(11.76%). Of the 102 types of TCM, tonics were the most frequently used categories, followed by heat-clearing medicines, blood-invigorating medicines, and stasis-resolving medicines. Of 207 papers, 174(84.06%) could not be subjected to statistical analysis due to research quality. Further high-quality research on herb sources, formula components and dosage, toxicology, and ethics of TCM is necessary. In conclusion, TCM play a promising role in the treatment and management of PLC, although further investigations are warranted.
基金The authors would like to acknowledge the financial support provided by the Natural Science Foundation of Zhejiang(No.LY21C200001)China,the National Natural Science Foundation of China(Nos.62105245 and 61805180)the Wenzhou Science and Technology Bureau General Project(Nos.S2020011 and G20200044),China。
文摘Objectives:This study presents a method combining a one-class classifier and laser-induced breakdown spectrometry(LIBS)to quickly identify healthy Tegillarca granosa(T.granosa).Materials and Methods:The sum of ranking differences(SRD)was used to fuse multiple anomaly detection metrics to build the one-class classifier,which was only trained with healthy T.granosa.The one-class classifier can identify healthy T.granosa to exclude non-healthy T.granosa.The proposed method calculated multiple anomaly detection metrics and standardized them to obtain a fusion matrix.Based on the fusion matrix,the samples were ranked by SRD and those ranked lowest and below the threshold were considered to be unhealthy.Results:Multiple anomaly detection metrics were fused by the SRD algorithm and tested on each band,and the final fusion model achieved an accuracy rate of 98.46%,a sensitivity of 100%,and a specificity of 80%.The remaining three single classification models obtained the following results:the SVDD model achieved an accuracy rate of 87.69%,a sensitivity of 90%,and a specificity of 60%;the OCSVM model achieved an accuracy rate of 80%,a sensitivity of 76.67%,and a specificity of 60%;and the DD-SIMCA model achieved an accuracy rate of 95.38%,a sensitivity of 98.33%,and a specificity of 60%.Conclusions:The experimental results showed that the proposed method achieved better results than the traditional one-class classification methods with a single metric.Therefore,the fusion method effectively improves the performance of traditional one-class classifiers when using LIBS to quickly identify healthy substances(healthy T.granosa).
基金the National Natural Science Foundation of China(62105245)the Zhejiang Natural Science Foundation of China(LQ20F030059,and LY21C200001)the Wenzhou Science and Technology Bureau General Project(S2020011),China.
文摘Detection of fruit traits by using near-infrared(NIR)spectroscopy may encounter out-of-distribution samples that exceed the generalization ability of a constructed calibration model.Therefore,confidence analysis for a given prediction is required,but this cannot be done using common calibration models of NIR spectroscopy.To address this issue,this paper studied the Gaussian process regression(GPR)for fruit traits detection using NIR spectroscopy.The mean and variance of the GPR were used as the predicted value and confidence,respectively.To show this,a real NIR data set related to dry matter content measurements in mango was used.Compared to partial least squares regression(PLSR),GPR showed approximately 14%lower root mean squared error(RMSE)for the in-distribution test set.Compared with no confidence analysis,using the variance of GPR to remove abnormal samples made GPR and PLSR showed approximately 58%and 10%lower RMSE on the mixed distribution test set,respectively(when the type 1 error rate was set to 0.1).Compared with traditional one-class classification methods,the variance of the GPR can be used to effectively eliminate poorly predicted samples.
基金supported by the Zhejiang Natural Science Foundation of China(Grant No.LY21C200001,LY20F030019)National Natural Science Foundation of China(Grant No.62105245,62071386)+1 种基金Wenzhou Major Scientific and Technological Innovation Projects of China(Grant No.ZG2021029,ZY2021027)the Wenzhou Science and Technology Bureau General Project(Grant No.S2020011).
文摘Laser-induced breakdown spectroscopy(LIBS)can be used for the rapid detection of heavy metal contamination of Tegillarca granosa(T.granosa),but an appropriate classification model needs to be constructed.In the one-class classification method,only target samples are needed in training process to achieve the recognition of abnormal samples,which is suitable for rapid identification of healthy T.granosa from those contaminated with uncertain heavy metals.The construction of a one-class classification model for heavy metal detection in T.granosa by LIBS has faced the problem of high-dimension and small samples.To solve this problem,a novel one-class classification method was proposed in this study.Here,the principal component scores and the intensity of the residual spectrum were combined as extracted features.Then,a one-class classifier based on Mahalanobis distance using the extracted features was constructed and its threshold was set by leave-one-out crossvalidation.The sensitivity,specificity and accuracy of the proposed method were reached to 1,0.9333 and 0.9667 respectively,which are superior to the previously reported methods.
基金the National Natural Science Foundation of China(Nos.81771968,21704061,and 82003166)Natural Science Foundation of Shanghai(No.21ZR1439200)+3 种基金Shanghai Sailing Program(No.17YF1411000)Shanghai Municipal Education Commission-Gaofeng Clinical Grant Support(No.20181705)Shanghai Municipal Commission of Health and Family Planning(No.201840020)the Medical-Engineering Joint Funds from the Shanghai Jiao Tong University(Nos.ZH2018ZDA05 and YG2016QN54).
文摘Dendrimer,such as dendrigraft poly-L-lysine(DGL)polymers,with high surface charge density,well-defined structure,and narrow poly-dispersity is often employed as a gene vector,but its transfection efficiency is still partially inhibited due to poor endosomal escape ability.Herein,we used a surface modification strategy to enhance the endosomal escape ability of DGL polymers,and thus improved its gene transfection efficiency.A library of phenylboronic acid(PBA)modified DGL polymers(PBA-DGLs)was designed to screen efficient small interfering RNA(siRNA)vectors.The lead candidate screened from the library shown a capability of inducing nearly 90% gene silencing in MDA-MB-231 cells.The study of the transfection mechanism revealed that PBA modification not only improves siRNA cellular uptake,but,more importantly,endows DGL polymers the ability of endosomal escape.One of the top candidates from polyplexes was further shielded with hyaluronic acid to construct targeted nanoparticles,and the yielding nanoparticles significantly suppressed the tumor growth in a breast cancer model by effective siRNA delivery.This research provides a general and effective strategy to enhance the endosomal escape and transfection efficiency of dendrimer.
基金the National Natural Science Foundation of China(Nos.81771968,82003166,and 21704061)the Natural Science Foundation of Shanghai(No.21ZR1439200)+3 种基金Shanghai Sailing Program(No.17YF1411000)Shanghai Municipal Education Commission-Gaofeng Clinical Grant Support(No.20181705)Shanghai Municipal Commission of Health and Family Planning(No.201840020)the Medical-Engineering Joint Funds from the Shanghai Jiao Tong University(Nos.ZH2018ZDA05 and YG2016QN54)on this work.
文摘Multi-drug resistance(MDR)has become the largest obstacle to the success of cancer patients receiving traditional chemotherapeutics or novel targeted drugs.Here,we developed a targeted nanoplatform based on biodegradable boronic acid modifiedε-polylysine to co-deliver P-gp siRNA,Bcl-2 siRNA,and doxorubicin for overcoming the challenge.The targeted nanoplatform showed a robust suppressing efficiency for the invasion,proliferation,and colony formation of adriamycin(ADR)resistant breast cancer cell line(MCF-7/ADR)cells in vitro.The ATP responsiveness of the nanoplatform was also proved in the research.In the in vivo antitumor experiment,the targeted nanoplatform showed a significant inhibition of tumor growth with good biocompatibility.The goal of this study is to develop a novel and facile strategy to prepare a highly efficient and safe gene and drug delivery system for MDR breast cancer based on biocompatibleε-polylysine polymers.
基金Science Technology Support Plan Projects of Sichuan Province(No. 2020YFS0241)135 project for disciplines of excellence–Clinical Research Incubation Project, West China Hospital, Sichuan University(No. 2020HXFH045)。
文摘To the Editor:Left ventricular diastolic dysfunction(LVDD)is an unrecognized subclinical presentation of autoimmune diseases(AD)andcarries a worse prognosis.Elevated serum uric acid(SUA),as a_proinflammatory factor,is associatedwithchanges in cardiacfunction in the general population as,well as in those with cardiac diseases.