BACKGROUND Understanding the humoral response pattern of coronavirus disease 2019(COVID-19)is one of the essential factors to better characterize the immune memory of patients,which allows understanding the temporalit...BACKGROUND Understanding the humoral response pattern of coronavirus disease 2019(COVID-19)is one of the essential factors to better characterize the immune memory of patients,which allows understanding the temporality of reinfection,provides answers about the efficacy and durability of protection against severe acute respiratory syndrome coronavirus 2(SARS-CoV-2),and consequently helps in global public health and vaccination strategy.Among the patients who became infected with SARS-CoV-2,the majority who did not progress to death were those who developed the mild COVID-19,so understanding the pattern and temporality of the antibody response of these patients is certainly relevant.AIM To investigate the temporal pattern of humoral response of specific immunoglobulin G(IgG)in mild cases of COVID-19.METHODS Blood samples from 191 COVID-19 real-time reverse transcriptase-polymerase chain reaction(RT-qPCR)-positive volunteers from the municipality of Toledo/Paraná/Brazil,underwent two distinct serological tests,enzyme-linked immunosorbent assay,and detection of anti-nucleocapsid IgG.Blood samples and clinicoepidemiological data of the volunteers were collected between November 2020 and February 2021.All assays were performed in duplicate and the manufacturers'recommendations were strictly followed.The data were statistically analyzed using multiple logistic regression;the variables were selected by applying the P<0.05 criterion.RESULTS Serological tests to detect specific IgG were performed on serum samples from volunteers who were diagnosed as being positive by RT-qPCR for COVID-19 or had disease onset in the time interval from less than 1 mo to 7 mo.The time periods when the highest number of participants with detectable IgG was observed were 1,2 and 3 mo.It was observed that 9.42%of participants no longer had detectable IgG antibodies 1 mo only after being infected with SARS-CoV-2 and 1.57%were also IgG negative at less than 1 mo.At 5 mo,3.14%of volunteers were IgG negative,and at 6 or 7 mo,1 volunteer(0.52%)had no detectable IgG.During the period between diagnosis by RT-qPCR/symptoms onset and the date of collection for the study,no statistical significance was observed for any association analyzed.Moreover,considering the age category between 31 and 59 years as the exposed group,the P value was 0.11 for the category 31 to 59 years and 0.32 for the category 60 years or older,showing that in both age categories there was no association between the pair of variables analyzed.Regarding chronic disease,the exposure group consisted of the participants without any comorbidity,so the P value of 0.07 for the category of those with at least one chronic disease showed no association between the two variables.CONCLUSION A temporal pattern of IgG response was not observed,but it is suggested that immunological memory is weak and there is no association between IgG production and age or chronic disease in mild COVID-19.展开更多
鉴于当前气候变化和人类活动的影响,生物多样性的空间预测对其保护和修复至关重要。本文将不同堆叠物种分布模型(stacked species distribution models,S-SDMs)的预测结果与森林清查数据进行了比较,以评估这些S-SDMs模型能否捕获生物多...鉴于当前气候变化和人类活动的影响,生物多样性的空间预测对其保护和修复至关重要。本文将不同堆叠物种分布模型(stacked species distribution models,S-SDMs)的预测结果与森林清查数据进行了比较,以评估这些S-SDMs模型能否捕获生物多样性热点地区物种丰富度的新特性和地理分布及局部群落的组成。我们选取大西洋沿岸森林151处地点的1499个树种进行SDM模型构建,并利用4种模型堆叠方法重建植物群落。这43种方法分别为二进制SDM模型(bS-SDM)、由最小凸多边形裁剪得到的二进制SDM模型(bS-SDM-CROP)、受物种丰富度观测结果约束的堆叠SDM模型(cS-SDM)以及物种出现点的最小凸多边形(MCP)。我们从物种丰富度、组成、群落预测指标以及β多样性组分(物种嵌套和物种周转)等方面将各堆叠方法与局部群落进行对比。研究结果表明,所有S-SDM模型均捕获到了一般分布格局,其中bS-SDM-CROP模型最为简约。各堆叠模型预测得到的物种组成与局部群落的实际情况存在一定的差异,其中bS-SDM、bS-SDM-CROP和MCP模型呈现出嵌套格局,而物种周转在cS-SDM模型中最为显著。这些S-SDM模型在性能、遗漏率和记账错率方面的表现各不相同,对一些脆弱、濒危和极度濒危物种给出了错误预测。尽管与森林清查数据有差别,但这些S-SDM模型均捕获了与局部群落数据的部分差异,可以表征物种的潜在分布区。本研究的结论有助于S-SDM模型在粗尺度生物多样性整合与保护规划中的应用,但在生物高度多样性地区局部尺度上可能会得出错误的预测结果。展开更多
文摘BACKGROUND Understanding the humoral response pattern of coronavirus disease 2019(COVID-19)is one of the essential factors to better characterize the immune memory of patients,which allows understanding the temporality of reinfection,provides answers about the efficacy and durability of protection against severe acute respiratory syndrome coronavirus 2(SARS-CoV-2),and consequently helps in global public health and vaccination strategy.Among the patients who became infected with SARS-CoV-2,the majority who did not progress to death were those who developed the mild COVID-19,so understanding the pattern and temporality of the antibody response of these patients is certainly relevant.AIM To investigate the temporal pattern of humoral response of specific immunoglobulin G(IgG)in mild cases of COVID-19.METHODS Blood samples from 191 COVID-19 real-time reverse transcriptase-polymerase chain reaction(RT-qPCR)-positive volunteers from the municipality of Toledo/Paraná/Brazil,underwent two distinct serological tests,enzyme-linked immunosorbent assay,and detection of anti-nucleocapsid IgG.Blood samples and clinicoepidemiological data of the volunteers were collected between November 2020 and February 2021.All assays were performed in duplicate and the manufacturers'recommendations were strictly followed.The data were statistically analyzed using multiple logistic regression;the variables were selected by applying the P<0.05 criterion.RESULTS Serological tests to detect specific IgG were performed on serum samples from volunteers who were diagnosed as being positive by RT-qPCR for COVID-19 or had disease onset in the time interval from less than 1 mo to 7 mo.The time periods when the highest number of participants with detectable IgG was observed were 1,2 and 3 mo.It was observed that 9.42%of participants no longer had detectable IgG antibodies 1 mo only after being infected with SARS-CoV-2 and 1.57%were also IgG negative at less than 1 mo.At 5 mo,3.14%of volunteers were IgG negative,and at 6 or 7 mo,1 volunteer(0.52%)had no detectable IgG.During the period between diagnosis by RT-qPCR/symptoms onset and the date of collection for the study,no statistical significance was observed for any association analyzed.Moreover,considering the age category between 31 and 59 years as the exposed group,the P value was 0.11 for the category 31 to 59 years and 0.32 for the category 60 years or older,showing that in both age categories there was no association between the pair of variables analyzed.Regarding chronic disease,the exposure group consisted of the participants without any comorbidity,so the P value of 0.07 for the category of those with at least one chronic disease showed no association between the two variables.CONCLUSION A temporal pattern of IgG response was not observed,but it is suggested that immunological memory is weak and there is no association between IgG production and age or chronic disease in mild COVID-19.
基金financed in part by the Coordenagao de Aperfeicoamento de Pessoal de Nivel Superior-Brasil(CAPES)with a scholarship to VAA-Finance Code ool.
文摘鉴于当前气候变化和人类活动的影响,生物多样性的空间预测对其保护和修复至关重要。本文将不同堆叠物种分布模型(stacked species distribution models,S-SDMs)的预测结果与森林清查数据进行了比较,以评估这些S-SDMs模型能否捕获生物多样性热点地区物种丰富度的新特性和地理分布及局部群落的组成。我们选取大西洋沿岸森林151处地点的1499个树种进行SDM模型构建,并利用4种模型堆叠方法重建植物群落。这43种方法分别为二进制SDM模型(bS-SDM)、由最小凸多边形裁剪得到的二进制SDM模型(bS-SDM-CROP)、受物种丰富度观测结果约束的堆叠SDM模型(cS-SDM)以及物种出现点的最小凸多边形(MCP)。我们从物种丰富度、组成、群落预测指标以及β多样性组分(物种嵌套和物种周转)等方面将各堆叠方法与局部群落进行对比。研究结果表明,所有S-SDM模型均捕获到了一般分布格局,其中bS-SDM-CROP模型最为简约。各堆叠模型预测得到的物种组成与局部群落的实际情况存在一定的差异,其中bS-SDM、bS-SDM-CROP和MCP模型呈现出嵌套格局,而物种周转在cS-SDM模型中最为显著。这些S-SDM模型在性能、遗漏率和记账错率方面的表现各不相同,对一些脆弱、濒危和极度濒危物种给出了错误预测。尽管与森林清查数据有差别,但这些S-SDM模型均捕获了与局部群落数据的部分差异,可以表征物种的潜在分布区。本研究的结论有助于S-SDM模型在粗尺度生物多样性整合与保护规划中的应用,但在生物高度多样性地区局部尺度上可能会得出错误的预测结果。
