Pub Date : 2022-10-05DOI: 10.30744/brjac.2179-3425.interview.srath
S. Rath
Susanne Rath is an associate professor in the Institute of Chemistry at the University of Campinas (Unicamp), where she coordinates the “Laboratório de Bioanalítica Paracelsus”. She graduated with a Bachelor's degree in Chemistry (1983) from the University of Brasília (UnB), a Master’s degree in Chemistry (1986) from Unicamp, and a Ph.D in Pharmaceutical Chemistry (1990) from the Johann Wolfgang Goethe Universität Frankfurt am Main, Germany. So far, she has published 110 articles and seven book chapters, had four patents granted, and she has presented over 230 papers at scientific conferences. She supervised 17 master's students, 20 doctorate students and 10 post-docs. In addition, she coordinated 23 research projects supported by Brazilian funding agencies. Prof. Dr. Rath’s primary research is focused on toxic compounds in food, residue depletion studies of veterinary drugs in food-producing animals, development and validation of analytical methods, application of bidimensional chromatography and mass spectrometry, environmental impact assessment of veterinary drugs, antimicrobial resistance and N-nitrosamines in food, cosmetics and drugs. Since 2007, Prof. Rath has been a member of the Joint Expert Committee on Food Additives (JECFA) of the Food and Agriculture Organization of the United Nations (FAO) and the World Health Organization (WHO). Since 2011, Prof. Rath has been a member of the Technical Group on Maximum Residue Limits for Veterinary Drugs in Food of the National Health Surveillance Agency (Anvisa) of the Ministry of Health of Brazil.
Susanne Rath是坎皮纳斯大学(Unicamp)化学研究所的副教授，负责协调“Laboratório de Bioanalítica Paracelsus”项目。她毕业于University of Brasília (UnB)的化学学士学位(1983年)，Unicamp的化学硕士学位(1986年)，以及德国法兰克福的Johann Wolfgang Goethe Universität的药物化学博士学位(1990年)。到目前为止，她已经发表了110篇文章和7本书章节，获得了4项专利，并在科学会议上发表了230多篇论文。硕士生17人，博士生20人，博士后10人。此外，她还协调了23个由巴西资助机构支持的研究项目。Rath教授的主要研究领域包括食品中的有毒化合物、兽药在食用动物体内的残留去除研究、分析方法的开发和验证、二维色谱和质谱的应用、兽药的环境影响评估、抗微生物药物耐药性和食品、化妆品和药物中的n -亚硝胺。自2007年以来，Rath教授一直是联合国粮食及农业组织(粮农组织)和世界卫生组织(世卫组织)食品添加剂联合专家委员会(JECFA)的成员。自2011年以来，Rath教授一直是巴西卫生部国家卫生监督局(Anvisa)食品中兽药最大残留限量技术小组的成员。
{"title":"Professor Susanne Rath, a researcher who has bravely faced challenges since childhood, kindly granted BrJAC an interview","authors":"S. Rath","doi":"10.30744/brjac.2179-3425.interview.srath","DOIUrl":"https://doi.org/10.30744/brjac.2179-3425.interview.srath","url":null,"abstract":"Susanne Rath is an associate professor in the Institute of Chemistry at the University of Campinas (Unicamp), where she coordinates the “Laboratório de Bioanalítica Paracelsus”. She graduated with a Bachelor's degree in Chemistry (1983) from the University of Brasília (UnB), a Master’s degree in Chemistry (1986) from Unicamp, and a Ph.D in Pharmaceutical Chemistry (1990) from the Johann Wolfgang Goethe Universität Frankfurt am Main, Germany. So far, she has published 110 articles and seven book chapters, had four patents granted, and she has presented over 230 papers at scientific conferences. She supervised 17 master's students, 20 doctorate students and 10 post-docs. In addition, she coordinated 23 research projects supported by Brazilian funding agencies. Prof. Dr. Rath’s primary research is focused on toxic compounds in food, residue depletion studies of veterinary drugs in food-producing animals, development and validation of analytical methods, application of bidimensional chromatography and mass spectrometry, environmental impact assessment of veterinary drugs, antimicrobial resistance and N-nitrosamines in food, cosmetics and drugs. Since 2007, Prof. Rath has been a member of the Joint Expert Committee on Food Additives (JECFA) of the Food and Agriculture Organization of the United Nations (FAO) and the World Health Organization (WHO). Since 2011, Prof. Rath has been a member of the Technical Group on Maximum Residue Limits for Veterinary Drugs in Food of the National Health Surveillance Agency (Anvisa) of the Ministry of Health of Brazil.","PeriodicalId":9115,"journal":{"name":"Brazilian Journal of Analytical Chemistry","volume":null,"pages":null},"PeriodicalIF":0.7,"publicationDate":"2022-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44148232","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-10-05DOI: 10.30744/brjac.2179-3425.point-of-view-wktcoltro.n37
W. Coltro
In the last three decades, the scientific community has observed exponential growth in the development of microfluidic platforms and their use for applications in different fields. The noticeable advances are attributed to the advantages provided by miniaturization.1 In summary, the downscaling of analytical devices has offered attractive features, including reduced consumption of samples and reagents, short analysis time, and minimal waste generation. In addition, the possibility to perform multiplexed assays in portable devices without bulky instrumentation is another attractive feature that boosted the investigation of miniaturized devices with the capability to be tested directly in the point-of-care (POC). Due to the sample volume required to proceed with a chemical analysis on a microscale (typically in the µL range), a complete understanding of the fluid control and handle on channels defined in micrometric dimensions was necessary, giving rise to the science known as microfluidics.2 Many platforms including rigid and flexible materials can be explored for manufacturing microfluidic networks. Among all the substrates reported in the literature, the “paper” is by far the simplest and cheapest material currently employed for the development of microfluidic devices dedicated to analytical, bioanalytical, biomedical, environmental, food, and forensics applications.3 For many readers, the first question is why paper is used instead of other materials such as glass. Well, glass is a rigid material, and microchannel engraving requires cleanroom facilities, photolithographic patterning, developing steps, and thermal sealing. This standard protocol makes use of sophisticated instrumentation, and it is not readily available to most researchers. In this way, paper emerges as a simple and alternative material to be used for microfluidics. One of the major benefits of microfluidics refers to the sample-in-answer-out capability, which requires a fully automated fluid control to allow sample preparation, analytical separation, and detection stages. The fluid-controlled handling inside microchannels opens the possibility to integrate multiple analytical tasks in parallel into a high-throughput device. Considering these possibilities, it is worthwhile reflecting on how paper can be used to transport and handle a fluid. Paper is currently one of the most widely used raw materials in research laboratories. Its use has been explored for over a century. In 1949, a paper containing barriers made of paraffin was exploited to successfully demonstrate the elution of pigments within a channel based on the sample diffusion process.4 In 2007, paper was reinvented by the Whitesides group as a globally affordable substrate material for the development of miniaturized analytical platforms.5 Since this period, paper has become an increasingly popular platform for multipurpose applications. Probably, its broad use is associated with advantages over other conventional subs
{"title":"Paper-based microfluidics: What can we expect?","authors":"W. Coltro","doi":"10.30744/brjac.2179-3425.point-of-view-wktcoltro.n37","DOIUrl":"https://doi.org/10.30744/brjac.2179-3425.point-of-view-wktcoltro.n37","url":null,"abstract":"In the last three decades, the scientific community has observed exponential growth in the development of microfluidic platforms and their use for applications in different fields. The noticeable advances are attributed to the advantages provided by miniaturization.1 In summary, the downscaling of analytical devices has offered attractive features, including reduced consumption of samples and reagents, short analysis time, and minimal waste generation. In addition, the possibility to perform multiplexed assays in portable devices without bulky instrumentation is another attractive feature that boosted the investigation of miniaturized devices with the capability to be tested directly in the point-of-care (POC). Due to the sample volume required to proceed with a chemical analysis on a microscale (typically in the µL range), a complete understanding of the fluid control and handle on channels defined in micrometric dimensions was necessary, giving rise to the science known as microfluidics.2 Many platforms including rigid and flexible materials can be explored for manufacturing microfluidic networks. Among all the substrates reported in the literature, the “paper” is by far the simplest and cheapest material currently employed for the development of microfluidic devices dedicated to analytical, bioanalytical, biomedical, environmental, food, and forensics applications.3 For many readers, the first question is why paper is used instead of other materials such as glass. Well, glass is a rigid material, and microchannel engraving requires cleanroom facilities, photolithographic patterning, developing steps, and thermal sealing. This standard protocol makes use of sophisticated instrumentation, and it is not readily available to most researchers. In this way, paper emerges as a simple and alternative material to be used for microfluidics. One of the major benefits of microfluidics refers to the sample-in-answer-out capability, which requires a fully automated fluid control to allow sample preparation, analytical separation, and detection stages. The fluid-controlled handling inside microchannels opens the possibility to integrate multiple analytical tasks in parallel into a high-throughput device. Considering these possibilities, it is worthwhile reflecting on how paper can be used to transport and handle a fluid. Paper is currently one of the most widely used raw materials in research laboratories. Its use has been explored for over a century. In 1949, a paper containing barriers made of paraffin was exploited to successfully demonstrate the elution of pigments within a channel based on the sample diffusion process.4 In 2007, paper was reinvented by the Whitesides group as a globally affordable substrate material for the development of miniaturized analytical platforms.5 Since this period, paper has become an increasingly popular platform for multipurpose applications. Probably, its broad use is associated with advantages over other conventional subs","PeriodicalId":9115,"journal":{"name":"Brazilian Journal of Analytical Chemistry","volume":null,"pages":null},"PeriodicalIF":0.7,"publicationDate":"2022-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49113364","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-10-05DOI: 10.30744/brjac.2179-3425.inmemoriam.carol-collins
C. Bottoli
Professor Carol Collins graduated in Chemistry from Bates College (1952) and obtained her PhD in Organic Physical Chemistry from Iowa State University of Science and Technology (1958), when she was introduced to the recently developed gas–liquid chromatography. She conducted postdoctoral research at the University of Wisconsin and later worked on radiochemistry and nuclear medicine at the Brookhaven National Laboratory and the Western New York Nuclear Research Center in Louvain (Belgium) and Southwest Asia. Professor Collins came to the State University of Campinas (Unicamp) with her husband, Kenneth Collins, in July 1974, during the university’s first decade, and played a leading role in consolidation of the Institute of Chemistry at Unicamp and in the growth of chemistry and analytical chemistry in Brazil. Her first line of research in Brazil was radioanalytical chemistry, later focusing on chromatographic techniques, initially applied to the products of radiochemical reactions and radiation chemistry. Subsequently, her attention was directed to the preparation of stationary phases for liquid chromatography. She gained remarkable achievement in the area of chromatography that allowed her to publish two books that are very popular in Brazil: "Introduction to Chromatographic Methods" (1987) and "Fundamentals of Chromatography" (2006). Her scientific and technological contributions have been recognized through several awards, including the “Marie Curie Award” from the American Association of University Women and the “Simão Mathias Medal” from the Brazilian Chemical Society (SBQ). She also received honors in recognition of the contributions of Unicamp's 40th anniversary, SBQ's 30th anniversary, a tribute from the Journal of the Brazilian Chemical Society, the National Meeting of Analytical Chemistry, the School of Separations and the Brazilian Symposium on Chromatography and Related Techniques (SIMCRO) Medal. For her outstanding performance and leadership in the creation and consolidation of the Analytical Chemistry Division of the Brazilian Chemical Society, her name was recognized in the Carol Collins Medal given to each National Meeting of Analytical Chemistry since the 2018 edition. Professor Collins was also a full member of the Brazilian Academy of Sciences and the Academy of Sciences of São Paulo, and received the title of Professor Emerita of Unicamp on 14 May 2012, in addition to being Emeritus Researcher at the National Council for Scientific and Technological Development (CNPq). Apart from her scientific competence, some characteristics shaped her personality and made her very popular among her colleagues and students: her vast gourmet knowledge, keen taste for caipirinha and coffee, infallible memory, great love for her work and for Brazil, dedication to science, analytical chemistry/chromatography, kindness as a person and her incessant search for justice. She was always receptive to clarifying the doubts of students, teachers and inte
Carol Collins教授1952年毕业于贝茨学院化学专业，1958年在爱荷华州立科技大学获得有机物理化学博士学位，当时她接触了最近发展起来的气液色谱法。她在威斯康星大学进行博士后研究，后来在布鲁克海文国家实验室和位于比利时鲁汶和西南亚的西纽约核研究中心从事放射化学和核医学工作。1974年7月，在坎皮纳斯州立大学(Unicamp)成立的第一个十年期间，柯林斯教授与丈夫肯尼斯·柯林斯(Kenneth Collins)来到坎皮纳斯州立大学(Unicamp)，并在坎皮纳斯州立大学化学研究所的整合以及巴西化学和分析化学的发展中发挥了主导作用。她在巴西的第一个研究方向是放射分析化学，后来专注于色谱技术，最初应用于放射化学反应和辐射化学的产物。随后，她的注意力转向了液相色谱固定相的制备。她在色谱学领域取得了显著成就，出版了两本在巴西非常受欢迎的书:《色谱方法入门》(1987年)和《色谱学基础》(2006年)。她的科学和技术贡献获得了多个奖项的认可，包括美国大学妇女协会的“玛丽居里奖”和巴西化学学会(SBQ)的“sim o Mathias奖章”。她还获得了Unicamp成立40周年、SBQ成立30周年、巴西化学学会杂志、全国分析化学会议、分离学院和巴西色谱及相关技术研讨会(SIMCRO)奖章等荣誉。由于她在巴西化学会分析化学部门的创建和巩固方面的杰出表现和领导作用，自2018年以来，她的名字被授予每个国家分析化学会议的卡罗尔·柯林斯奖章。Collins教授还是巴西科学院和圣保罗科学院的正式成员，并于2012年5月14日获得Unicamp的荣誉教授头衔，此外他还是国家科学和技术发展委员会(CNPq)的荣誉研究员。除了她的科学能力之外，她的一些特点塑造了她的个性，并使她在同事和学生中非常受欢迎:她丰富的美食知识，对凯皮林纳酒和咖啡的敏锐品味，准确的记忆力，对她的工作和巴西的热爱，对科学的奉献，分析化学/色谱，为人善良，以及对正义的不断追求。她总是乐于澄清学生、老师和有关各方的疑问，她做得非常愉快，这是一个喜欢教授和传播知识的人的特点。柯林斯教授对人力资源培训、Unicamp化学研究所的巩固和发展以及巴西和国外分析化学/色谱部门的贡献是不可估量的。她辉煌的人生轨迹将留下难以估量的巨大遗产，她将永远留在那些有幸与她生活在一起的人的记忆中。
{"title":"In Memoriam - BrJAC mourns the death of Prof. Dr. Carol Hollingworth Collins and recognizes her great contribution to the Analytical Chemistry in Brazil","authors":"C. Bottoli","doi":"10.30744/brjac.2179-3425.inmemoriam.carol-collins","DOIUrl":"https://doi.org/10.30744/brjac.2179-3425.inmemoriam.carol-collins","url":null,"abstract":"Professor Carol Collins graduated in Chemistry from Bates College (1952) and obtained her PhD in Organic Physical Chemistry from Iowa State University of Science and Technology (1958), when she was introduced to the recently developed gas–liquid chromatography. She conducted postdoctoral research at the University of Wisconsin and later worked on radiochemistry and nuclear medicine at the Brookhaven National Laboratory and the Western New York Nuclear Research Center in Louvain (Belgium) and Southwest Asia. Professor Collins came to the State University of Campinas (Unicamp) with her husband, Kenneth Collins, in July 1974, during the university’s first decade, and played a leading role in consolidation of the Institute of Chemistry at Unicamp and in the growth of chemistry and analytical chemistry in Brazil. Her first line of research in Brazil was radioanalytical chemistry, later focusing on chromatographic techniques, initially applied to the products of radiochemical reactions and radiation chemistry. Subsequently, her attention was directed to the preparation of stationary phases for liquid chromatography. She gained remarkable achievement in the area of chromatography that allowed her to publish two books that are very popular in Brazil: \"Introduction to Chromatographic Methods\" (1987) and \"Fundamentals of Chromatography\" (2006). Her scientific and technological contributions have been recognized through several awards, including the “Marie Curie Award” from the American Association of University Women and the “Simão Mathias Medal” from the Brazilian Chemical Society (SBQ). She also received honors in recognition of the contributions of Unicamp's 40th anniversary, SBQ's 30th anniversary, a tribute from the Journal of the Brazilian Chemical Society, the National Meeting of Analytical Chemistry, the School of Separations and the Brazilian Symposium on Chromatography and Related Techniques (SIMCRO) Medal. For her outstanding performance and leadership in the creation and consolidation of the Analytical Chemistry Division of the Brazilian Chemical Society, her name was recognized in the Carol Collins Medal given to each National Meeting of Analytical Chemistry since the 2018 edition. Professor Collins was also a full member of the Brazilian Academy of Sciences and the Academy of Sciences of São Paulo, and received the title of Professor Emerita of Unicamp on 14 May 2012, in addition to being Emeritus Researcher at the National Council for Scientific and Technological Development (CNPq). Apart from her scientific competence, some characteristics shaped her personality and made her very popular among her colleagues and students: her vast gourmet knowledge, keen taste for caipirinha and coffee, infallible memory, great love for her work and for Brazil, dedication to science, analytical chemistry/chromatography, kindness as a person and her incessant search for justice. She was always receptive to clarifying the doubts of students, teachers and inte","PeriodicalId":9115,"journal":{"name":"Brazilian Journal of Analytical Chemistry","volume":null,"pages":null},"PeriodicalIF":0.7,"publicationDate":"2022-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48791165","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-10-05DOI: 10.30744/brjac.2179-3425.letter-fabiolaverbi.n37
F. Pereira
The application of chemometric tools in analytical chemistry or other areas of chemistry has become essential. This is mainly due to the large amount and nature of the generated data1,2 and the need to extract useful information from these and optimize steps throughout a process. It allows the quick decision-making visualization of interactions among variables, such as synergism or antagonism between parameters, during the development of a method,3 as shown in Figure 1. Classical chemometric techniques have been disseminated and can be divided according to the study approach, among which exploratory data analysis stands out. Principal component analysis (PCA) is one of the most accessible and well-established ways to perform an initial exploration and extract relevant information from a given dataset and has been used quite successfully in various spectroscopic techniques.4 Principal component analysis consists of projecting the data in a smaller dimension, enabling the detection of anomalous samples (outliers), the selection of essential variables in a given system, and unsupervised classification.1,2,4 Another branch of chemometrics involves the design of experiments (DoE). The primary purpose of the factorial design is to study the influence or effect of a given variable and its interactions in a specific system.5-9 Multivariate calibration is another aspect of chemometrics, where several variables are used to calibrate one (or more) property or the concentration of a given chemical analyte.10,11 Since the first publications of chemometric tools, numerous variations of these techniques, proposals for data fusion strategies, and applications using hyphenated instrumental techniques have been proposed.12-14 Industrial quality control and development (R&D) laboratories require an approach addressing adequate quality by design (QbD). The QbD strategies consider four steps that include an analytical target profile (ATP), a risk assessment, a design space (DS), and control strategy and validation based on figures of merit, for instance.9 Principal component analysis is the most widely multivariate technique used for data analysis. Jolliffe wrote a review reporting his wonderful experience with PCA in the last 50 years.15 Indeed, PCA is an invaluable method for data, and I agree with it. PCA is the algorithm of choice for numerous chemometric techniques.16 Other computational languages, such as Python, are currently experiencing a rise in popularity in the field of chemistry. The R language has also become more popular than it was ten years ago. The scripts, functions, or codes are easily written with fewer lines and specific commands that minimize steps and help speed up calculations. The dissemination of free software has also become popular, and the sharing of codes through publications, social media, communities, or websites has become relatively easy. From my point of view, chemometrics is no longer faced as a giant monster or a way to become sc
{"title":"Chemometrics reveals not-so-obvious analytical information","authors":"F. Pereira","doi":"10.30744/brjac.2179-3425.letter-fabiolaverbi.n37","DOIUrl":"https://doi.org/10.30744/brjac.2179-3425.letter-fabiolaverbi.n37","url":null,"abstract":"The application of chemometric tools in analytical chemistry or other areas of chemistry has become essential. This is mainly due to the large amount and nature of the generated data1,2 and the need to extract useful information from these and optimize steps throughout a process. It allows the quick decision-making visualization of interactions among variables, such as synergism or antagonism between parameters, during the development of a method,3 as shown in Figure 1. Classical chemometric techniques have been disseminated and can be divided according to the study approach, among which exploratory data analysis stands out. Principal component analysis (PCA) is one of the most accessible and well-established ways to perform an initial exploration and extract relevant information from a given dataset and has been used quite successfully in various spectroscopic techniques.4 Principal component analysis consists of projecting the data in a smaller dimension, enabling the detection of anomalous samples (outliers), the selection of essential variables in a given system, and unsupervised classification.1,2,4 Another branch of chemometrics involves the design of experiments (DoE). The primary purpose of the factorial design is to study the influence or effect of a given variable and its interactions in a specific system.5-9 Multivariate calibration is another aspect of chemometrics, where several variables are used to calibrate one (or more) property or the concentration of a given chemical analyte.10,11 Since the first publications of chemometric tools, numerous variations of these techniques, proposals for data fusion strategies, and applications using hyphenated instrumental techniques have been proposed.12-14 Industrial quality control and development (R&D) laboratories require an approach addressing adequate quality by design (QbD). The QbD strategies consider four steps that include an analytical target profile (ATP), a risk assessment, a design space (DS), and control strategy and validation based on figures of merit, for instance.9 Principal component analysis is the most widely multivariate technique used for data analysis. Jolliffe wrote a review reporting his wonderful experience with PCA in the last 50 years.15 Indeed, PCA is an invaluable method for data, and I agree with it. PCA is the algorithm of choice for numerous chemometric techniques.16 Other computational languages, such as Python, are currently experiencing a rise in popularity in the field of chemistry. The R language has also become more popular than it was ten years ago. The scripts, functions, or codes are easily written with fewer lines and specific commands that minimize steps and help speed up calculations. The dissemination of free software has also become popular, and the sharing of codes through publications, social media, communities, or websites has become relatively easy. From my point of view, chemometrics is no longer faced as a giant monster or a way to become sc","PeriodicalId":9115,"journal":{"name":"Brazilian Journal of Analytical Chemistry","volume":null,"pages":null},"PeriodicalIF":0.7,"publicationDate":"2022-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46525004","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-09-26DOI: 10.30744/brjac.2179-3425.ar-50-2022
khadeejah alyasiri, F. Al-Zubaidi, Layla Mohammed
A new, sensitive, and accurate spectrophotometric method for determining lead (II) ion in vegetables samples, using laboratory prepared reagent (6-MBTAMP) is developed. The reagent and pb+2 complex characterization included infrared spectroscopy, ultraviolet-visible spectrophotometry, elemental analysis (CHN), energy dispersive X-ray spectroscopy (EDX), and nuclear magnetic resonance spectroscopy (1HNMR & 13CNMR) techniques. The method depends on the reaction of lead (II) with the 6-MBTAMP reagent in a neutral medium to form a green-red complex which showed a maximum absorbance at 670 nm. The optimum conditions such as pH of the medium, reagent volume, reagent concentration, and time effect were also investigated carefully. Limit of detection (LOD), limit of quantification (LOQ) and Sandell’s sensitivity were calculated to be 0.181 mg L-1, 0.604 mg L-1 and 0.03 µg cm-2 respectively. The proposed method obeyed Beer’s law at range of 0.6-10 mg L-1 and the recovery percentage of the vegetable samples ranged from 71% to 106.6%. The suggested spectrophotometric technique is proved to be simple, fast and sensitive for determination of Pb (II) ion in vegetables samples.
{"title":"A New Spectrophotometric Method to Determinate Lead (II) Ion in Vegetables with 2-[(6-Methoxy-2-benzothiazolyl) azo]-4-methoxy phenol as a New Reagent","authors":"khadeejah alyasiri, F. Al-Zubaidi, Layla Mohammed","doi":"10.30744/brjac.2179-3425.ar-50-2022","DOIUrl":"https://doi.org/10.30744/brjac.2179-3425.ar-50-2022","url":null,"abstract":"A new, sensitive, and accurate spectrophotometric method for determining lead (II) ion in vegetables samples, using laboratory prepared reagent (6-MBTAMP) is developed. The reagent and pb+2 complex characterization included infrared spectroscopy, ultraviolet-visible spectrophotometry, elemental analysis (CHN), energy dispersive X-ray spectroscopy (EDX), and nuclear magnetic resonance spectroscopy (1HNMR & 13CNMR) techniques. The method depends on the reaction of lead (II) with the 6-MBTAMP reagent in a neutral medium to form a green-red complex which showed a maximum absorbance at 670 nm. The optimum conditions such as pH of the medium, reagent volume, reagent concentration, and time effect were also investigated carefully. Limit of detection (LOD), limit of quantification (LOQ) and Sandell’s sensitivity were calculated to be 0.181 mg L-1, 0.604 mg L-1 and 0.03 µg cm-2 respectively. The proposed method obeyed Beer’s law at range of 0.6-10 mg L-1 and the recovery percentage of the vegetable samples ranged from 71% to 106.6%. The suggested spectrophotometric technique is proved to be simple, fast and sensitive for determination of Pb (II) ion in vegetables samples.","PeriodicalId":9115,"journal":{"name":"Brazilian Journal of Analytical Chemistry","volume":null,"pages":null},"PeriodicalIF":0.7,"publicationDate":"2022-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42759317","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-09-26DOI: 10.30744/brjac.2179-3425.ar-44-2022
Tallyta Teixeira, Jorge Rodrigues Neto, Elias Silva, A. Conceição, Felix Siqueira, P. Abdelnur
Fungi can produce many bioactive metabolites, which are enhanced when challenged in co-culture competition. For a better evaluation of these metabolites, Mass Spectrometry Imaging (MSI) can be used to provide complementary information about the metabolite spatial localization. However, some adaptations are required on available methodologies in MSI for applications in microorganisms, particularly on sample preparation, due to the characteristics of each type of cell that has to be analyzed. The imprinting method has been shown to be a robust method when applied to sample preparation, but to our knowledge it has never been tested for microbial MALDI-MSI. Herein we applied both Classic and Imprinting MALDI-MSI to compare and analyze metabolites produced by Aspergillus terreus (ATCC® 20542TM) and Pleurotus pulmonarius fungi. For the classic method, the fungi were inoculated for 8 days with PDA medium in a MALDI glass slide. For the imprinting method, fungi were also inoculated for 8 days in a MALDI glass slide and then transferred to a filter paper by manual pressure using a homemade apparatus. Samples were then dehydrated and submitted to HCCA matrix application by sublimation. The chemical images were acquired by MALDI-MSI, and the metabolites were identified by UHPLC-ESI-MS/MS. Twelve ions were detected by MALDI-MSI, using classic (m/z 210.54, 276.99, 307.45, 321.04, 329.70, 346.12, 351.12, 462.41 and 484.02) and imprinting (m/z 313.64, 379.66 and 404.36) methods. Some ions presented a higher intensity in the interaction zone between fungi areas, especially the ions m/z 329.70, 351.12 and 484.02. These ions may be related to metabolites involved in communication between microorganisms, because these fungi formed a mutualistic interaction. All ions were investigated by UHPLC-ESI-MS/MS, and two were identified: adenosine monophosphate (C10H14N5O7P, m/z 346.12, [M-H]-) visualized in the Classic Method, and rubrophen (C22H20O6, m/z 379.66, [M-H]-) visualized in the Imprinting Method. The metabolites from microorganisms are rarely reported in MS/MS databases, which explains the difficulty in the identification of these compounds. Our MSI analysis using the classic method provided a higher number of detected ions. However, both classic and imprinting methods resulted in a complementary information, leading to the detection of ions that were not previously observed on the classic approach. Despite of the challenges encountered on the sample preparation and metabolite identification, using both classic and imprinting MALDI-MSI for bioprospection of fungi metabolites is a promising approach on the analytical field of mass spectrometry which can be later used in biotechnological applications.
{"title":"Mass Spectrometry Imaging for fungal interaction analysis: Classic versus Imprinting Methods","authors":"Tallyta Teixeira, Jorge Rodrigues Neto, Elias Silva, A. Conceição, Felix Siqueira, P. Abdelnur","doi":"10.30744/brjac.2179-3425.ar-44-2022","DOIUrl":"https://doi.org/10.30744/brjac.2179-3425.ar-44-2022","url":null,"abstract":"Fungi can produce many bioactive metabolites, which are enhanced when challenged in co-culture competition. For a better evaluation of these metabolites, Mass Spectrometry Imaging (MSI) can be used to provide complementary information about the metabolite spatial localization. However, some adaptations are required on available methodologies in MSI for applications in microorganisms, particularly on sample preparation, due to the characteristics of each type of cell that has to be analyzed. The imprinting method has been shown to be a robust method when applied to sample preparation, but to our knowledge it has never been tested for microbial MALDI-MSI. Herein we applied both Classic and Imprinting MALDI-MSI to compare and analyze metabolites produced by Aspergillus terreus (ATCC® 20542TM) and Pleurotus pulmonarius fungi. For the classic method, the fungi were inoculated for 8 days with PDA medium in a MALDI glass slide. For the imprinting method, fungi were also inoculated for 8 days in a MALDI glass slide and then transferred to a filter paper by manual pressure using a homemade apparatus. Samples were then dehydrated and submitted to HCCA matrix application by sublimation. The chemical images were acquired by MALDI-MSI, and the metabolites were identified by UHPLC-ESI-MS/MS. Twelve ions were detected by MALDI-MSI, using classic (m/z 210.54, 276.99, 307.45, 321.04, 329.70, 346.12, 351.12, 462.41 and 484.02) and imprinting (m/z 313.64, 379.66 and 404.36) methods. Some ions presented a higher intensity in the interaction zone between fungi areas, especially the ions m/z 329.70, 351.12 and 484.02. These ions may be related to metabolites involved in communication between microorganisms, because these fungi formed a mutualistic interaction. All ions were investigated by UHPLC-ESI-MS/MS, and two were identified: adenosine monophosphate (C10H14N5O7P, m/z 346.12, [M-H]-) visualized in the Classic Method, and rubrophen (C22H20O6, m/z 379.66, [M-H]-) visualized in the Imprinting Method. The metabolites from microorganisms are rarely reported in MS/MS databases, which explains the difficulty in the identification of these compounds. Our MSI analysis using the classic method provided a higher number of detected ions. However, both classic and imprinting methods resulted in a complementary information, leading to the detection of ions that were not previously observed on the classic approach. Despite of the challenges encountered on the sample preparation and metabolite identification, using both classic and imprinting MALDI-MSI for bioprospection of fungi metabolites is a promising approach on the analytical field of mass spectrometry which can be later used in biotechnological applications.","PeriodicalId":9115,"journal":{"name":"Brazilian Journal of Analytical Chemistry","volume":null,"pages":null},"PeriodicalIF":0.7,"publicationDate":"2022-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42658632","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-08-31DOI: 10.30744/brjac.2179-3425.ar-30-2022
A. Luna, A. Torres, Camilla L Cunha, I. Lima, Luis Nonato
This work aims to develop an auto-machine learning method using Mid-Infrared (MIR) spectroscopy data to determine the cold filter plugging point (CFPP) and kinematic viscosity at 40 ºC of biodiesel, diesel, and mixtures samples. The biodiesel was obtained by the transesterification reaction and later purified. The first dataset was composed of 108 blends (biodiesel obtained from different biomass such as soy, corn, sunflower, and canola) with binary, ternary and quaternary mixtures. The second dataset was composed of 227 blends of diesel-biodiesel and diesel-biodiesel-ethanol, respectively. The physical properties of the samples were obtained according to ABNT NBR 14747 and ABNT NBR 10441, respectively. The MIR Spectroscopy data were acquired from 7,800 to 450 cm-1, with a 4 cm-1 resolution and 20 scans. The spectra' baseline alignment was carried out using the asymmetric least squares method. A Savitzky–Golay filter was applied to a set of digital data points to smooth the data. This work used a first-order polynomial and a zero derivative function to smooth the spectra. The dataset was split into training and test sets using the function CreateDataPartition from the caret package. It was adopted 70% for training and 30% for test sets. In this work, the model training process was carried out using the open-source Python library LazyPredict. The LazyPredict returns the trained models and their performance metrics. The kinematic viscosity at 40 ºC of the biodiesel samples and their blends could be modeled using the MIR Spectroscopy dataset using different auto-machine learning algorithms. The RMSEP (Root Mean Square Error of Prediction) (≤ 0.02 mm2 s-1) was similar to the experimental error obtained after log transformation. The CFPP of the biodiesel samples and their blends could be modeled using the MIR Spectroscopy dataset by different auto-machine learning algorithms with an RMSEP (≤ 1.6 ºC) similar to the experimental error obtained by traditional methodology. Based on the lower computational time and the same performance observed by the RMSEP and R2 (coefficient of determination) values from different algorithms, it is recommended to use Ridge or Ridge Cross-Validation Regression models for both physical properties using MIR Spectroscopy data.
{"title":"Employing Auto-Machine Learning Algorithms for Predicting the Cold Filter Plugging and Kinematic Viscosity at 40 ºC in Biodiesel Blends using Vibrational Spectroscopy Data","authors":"A. Luna, A. Torres, Camilla L Cunha, I. Lima, Luis Nonato","doi":"10.30744/brjac.2179-3425.ar-30-2022","DOIUrl":"https://doi.org/10.30744/brjac.2179-3425.ar-30-2022","url":null,"abstract":"This work aims to develop an auto-machine learning method using Mid-Infrared (MIR) spectroscopy data to determine the cold filter plugging point (CFPP) and kinematic viscosity at 40 ºC of biodiesel, diesel, and mixtures samples. The biodiesel was obtained by the transesterification reaction and later purified. The first dataset was composed of 108 blends (biodiesel obtained from different biomass such as soy, corn, sunflower, and canola) with binary, ternary and quaternary mixtures. The second dataset was composed of 227 blends of diesel-biodiesel and diesel-biodiesel-ethanol, respectively. The physical properties of the samples were obtained according to ABNT NBR 14747 and ABNT NBR 10441, respectively. The MIR Spectroscopy data were acquired from 7,800 to 450 cm-1, with a 4 cm-1 resolution and 20 scans. The spectra' baseline alignment was carried out using the asymmetric least squares method. A Savitzky–Golay filter was applied to a set of digital data points to smooth the data. This work used a first-order polynomial and a zero derivative function to smooth the spectra. The dataset was split into training and test sets using the function CreateDataPartition from the caret package. It was adopted 70% for training and 30% for test sets. In this work, the model training process was carried out using the open-source Python library LazyPredict. The LazyPredict returns the trained models and their performance metrics. The kinematic viscosity at 40 ºC of the biodiesel samples and their blends could be modeled using the MIR Spectroscopy dataset using different auto-machine learning algorithms. The RMSEP (Root Mean Square Error of Prediction) (≤ 0.02 mm2 s-1) was similar to the experimental error obtained after log transformation. The CFPP of the biodiesel samples and their blends could be modeled using the MIR Spectroscopy dataset by different auto-machine learning algorithms with an RMSEP (≤ 1.6 ºC) similar to the experimental error obtained by traditional methodology. Based on the lower computational time and the same performance observed by the RMSEP and R2 (coefficient of determination) values from different algorithms, it is recommended to use Ridge or Ridge Cross-Validation Regression models for both physical properties using MIR Spectroscopy data.","PeriodicalId":9115,"journal":{"name":"Brazilian Journal of Analytical Chemistry","volume":null,"pages":null},"PeriodicalIF":0.7,"publicationDate":"2022-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45706617","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-08-31DOI: 10.30744/brjac.2179-3425.ar-35-2022
Razan Alkassab, Yumen Hilal, Amin Swed
In this study, a rapid, simple, economical and accurate spectrophotometric process was developed for the determination of sodium diclofenac in modified release tablets using ethanol 96% as an available and non-toxic solvent. Sodium diclofenac standard solution was scanned under UV (200-400 nm) in a 1 cm quartz cell to determine the maximum absorption wavelength which was 285 nm. This method was validated in accordance with the requirements of the International Conference on Harmonization (ICH), where the calibration curve showed linearity in the studied concentration range (5-30 μg mL-1) with correlation coefficient R² = 0.9993. The relative standard deviation of the accuracy studies was within the acceptable range (<2%). This method also achieved an excellent recovery ratio (Mean recovery ± S.D. = 100.44% ± 0.81) with high sensitivity (limit of detection 1.10 μg mL-1 and quantitation limit of 3.34 μg mL-1). The developed process applied successfully to determine sodium diclofenac in four commercial pharmaceuticals products (A, B, C and D) marketed locally as modified-release tablets. The product C showed the highest assay value 106% and product B showed the lowest value 98%. Hence, we recommend using this method to quantitatively determine of sodium diclofenac in pharmaceutical dosage forms.
{"title":"Development and Validation of a Simple Spectrophotometric Method for Quantitative Determination of Sodium Diclofenac in Modified-Release Tablets","authors":"Razan Alkassab, Yumen Hilal, Amin Swed","doi":"10.30744/brjac.2179-3425.ar-35-2022","DOIUrl":"https://doi.org/10.30744/brjac.2179-3425.ar-35-2022","url":null,"abstract":"In this study, a rapid, simple, economical and accurate spectrophotometric process was developed for the determination of sodium diclofenac in modified release tablets using ethanol 96% as an available and non-toxic solvent. Sodium diclofenac standard solution was scanned under UV (200-400 nm) in a 1 cm quartz cell to determine the maximum absorption wavelength which was 285 nm. This method was validated in accordance with the requirements of the International Conference on Harmonization (ICH), where the calibration curve showed linearity in the studied concentration range (5-30 μg mL-1) with correlation coefficient R² = 0.9993. The relative standard deviation of the accuracy studies was within the acceptable range (<2%). This method also achieved an excellent recovery ratio (Mean recovery ± S.D. = 100.44% ± 0.81) with high sensitivity (limit of detection 1.10 μg mL-1 and quantitation limit of 3.34 μg mL-1). The developed process applied successfully to determine sodium diclofenac in four commercial pharmaceuticals products (A, B, C and D) marketed locally as modified-release tablets. The product C showed the highest assay value 106% and product B showed the lowest value 98%. Hence, we recommend using this method to quantitatively determine of sodium diclofenac in pharmaceutical dosage forms.","PeriodicalId":9115,"journal":{"name":"Brazilian Journal of Analytical Chemistry","volume":null,"pages":null},"PeriodicalIF":0.7,"publicationDate":"2022-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46707693","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-08-03DOI: 10.30744/brjac.2179-3425.rv-42-2022
Lanaia Maciel, R. Martins, D. Gondim, João V A Oliveira, Julia Pereira, Gustavo Pereira, Leonardo Ferreira, A. Chaves, B. Vaz
Parkinson's disease (PD) is globally known as the most common movement disorder and the second most common neurodegenerative disease. The disease includes the symptoms of involuntary limb tremors, stiffness, or inflexibility of limbs and joints, among others. Due to this, scientific reports on analytical methodologies to evaluate the progression of neurodegenerative diseases are extremely necessary. Traditional methods include histochemical, immunohistochemical, and ligand-based approaches, however, these approaches still suffer from selectivity limitations of association, leading to a wrong evaluation. In this context, mass spectrometry imaging methods, such as desorption electrospray ionization (DESI), are potential approaches to visualize the distribution of biomarkers that can lead to the information on the progress of PD. This review aims to bring a discussion of some DESI methodologies reported in the literature for the assessment of neurotransmitters associated with PD.
{"title":"Desorption Electrospray Ionization Imaging for Neurotransmitters Evaluation: A Potential Approach to Parkinson’s Disease Monitoring","authors":"Lanaia Maciel, R. Martins, D. Gondim, João V A Oliveira, Julia Pereira, Gustavo Pereira, Leonardo Ferreira, A. Chaves, B. Vaz","doi":"10.30744/brjac.2179-3425.rv-42-2022","DOIUrl":"https://doi.org/10.30744/brjac.2179-3425.rv-42-2022","url":null,"abstract":"Parkinson's disease (PD) is globally known as the most common movement disorder and the second most common neurodegenerative disease. The disease includes the symptoms of involuntary limb tremors, stiffness, or inflexibility of limbs and joints, among others. Due to this, scientific reports on analytical methodologies to evaluate the progression of neurodegenerative diseases are extremely necessary. Traditional methods include histochemical, immunohistochemical, and ligand-based approaches, however, these approaches still suffer from selectivity limitations of association, leading to a wrong evaluation. In this context, mass spectrometry imaging methods, such as desorption electrospray ionization (DESI), are potential approaches to visualize the distribution of biomarkers that can lead to the information on the progress of PD. This review aims to bring a discussion of some DESI methodologies reported in the literature for the assessment of neurotransmitters associated with PD.","PeriodicalId":9115,"journal":{"name":"Brazilian Journal of Analytical Chemistry","volume":null,"pages":null},"PeriodicalIF":0.7,"publicationDate":"2022-08-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42242162","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-08-03DOI: 10.30744/brjac.2179-3425.ar-38-2022
Fiorella Iaquinta, J. Santander, M. Pistón, I. Machado
Four methods for the efficient extraction of copper from bovine and ovine liver were optimized. Sample preparation consisted of extractions with dilute nitric acid or dilute tetramethyl ammonium hydroxide, assisted by an ultrasonic bath or an ultrasonic probe. Copper was determined by flame atomic absorption spectrometry. The experimental conditions were optimized using multivariate experiments. All methods were considered adequate for copper extraction, however, the two methods involving the probe turned out to be more efficient and faster, so they were selected for subsequent validation. Trueness was verified after the analysis of a certified reference material and the performance of a microwave-assisted extraction. Results were statistically equivalent, at the 95% significance level, to the values declared on the certificate. Precision (expressed as relative standard deviation) was better than 5% for all methods. Samples obtained from Uruguayan animals were analyzed. Obtained results agreed with previous results from sheep and cattle abroad. The proposed methods are simple alternatives for food surveillance and animal status monitoring, being straightforward and aligned with Green Chemistry principles, as it was demonstrated by performing the analytical Eco-Scale comprehensive approach. A discussion related to the particle size distribution obtained during the multivariate experiments was also included, to give some deeper insight into ultrasound effect on the biological tissue in different media. In addition, ultrasound-assisted extraction was compared to magnetic stirring to prove the effect of ultrasound.
{"title":"Comparison of Ultrasound-assisted Methods for Copper Determination in Bovine and Ovine Liver as Strategies for Food Surveillance and Animal Status Monitoring","authors":"Fiorella Iaquinta, J. Santander, M. Pistón, I. Machado","doi":"10.30744/brjac.2179-3425.ar-38-2022","DOIUrl":"https://doi.org/10.30744/brjac.2179-3425.ar-38-2022","url":null,"abstract":"Four methods for the efficient extraction of copper from bovine and ovine liver were optimized. Sample preparation consisted of extractions with dilute nitric acid or dilute tetramethyl ammonium hydroxide, assisted by an ultrasonic bath or an ultrasonic probe. Copper was determined by flame atomic absorption spectrometry. The experimental conditions were optimized using multivariate experiments. All methods were considered adequate for copper extraction, however, the two methods involving the probe turned out to be more efficient and faster, so they were selected for subsequent validation. Trueness was verified after the analysis of a certified reference material and the performance of a microwave-assisted extraction. Results were statistically equivalent, at the 95% significance level, to the values declared on the certificate. Precision (expressed as relative standard deviation) was better than 5% for all methods. Samples obtained from Uruguayan animals were analyzed. Obtained results agreed with previous results from sheep and cattle abroad. The proposed methods are simple alternatives for food surveillance and animal status monitoring, being straightforward and aligned with Green Chemistry principles, as it was demonstrated by performing the analytical Eco-Scale comprehensive approach. A discussion related to the particle size distribution obtained during the multivariate experiments was also included, to give some deeper insight into ultrasound effect on the biological tissue in different media. In addition, ultrasound-assisted extraction was compared to magnetic stirring to prove the effect of ultrasound.","PeriodicalId":9115,"journal":{"name":"Brazilian Journal of Analytical Chemistry","volume":null,"pages":null},"PeriodicalIF":0.7,"publicationDate":"2022-08-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44318803","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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