Pub Date : 2022-01-01DOI: 10.4236/ajac.2022.1311032
Mohamed Samara, A. Nasser, U. Mingelgrin
{"title":"Critical Examination of the Suitability of the Folin-Ciocalteu Reagent Assay for Quantitative Analysis of Polyphenols—The Case of Olive-Mill Wastewater","authors":"Mohamed Samara, A. Nasser, U. Mingelgrin","doi":"10.4236/ajac.2022.1311032","DOIUrl":"https://doi.org/10.4236/ajac.2022.1311032","url":null,"abstract":"","PeriodicalId":63216,"journal":{"name":"美国分析化学(英文)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70500473","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 : 2022-01-01DOI: 10.4236/ajac.2022.131001
Niara A. Nichols, I. Lednev
Two critical issues in forensic science are identifying body fluid traces found at crime scenes and preserving them for DNA analysis. However, the majority of current biochemical tests for body fluid identification, which are applicable at the crime scene, are presumptive and destructive to the sample. Raman Spectroscopy provides a suitable alternative to current methods as a nonde-structive, confirmatory, and potentially in field method. Our laboratory has developed a chemometric model for the identification of five main body fluids using Raman spectroscopy. This model was developed using samples obtained from healthy donors. Thus, it is of most importance for the forensic application of the method to validate its performance for donors with diseases that might affect the biochemical composition of body fluids. In this study, the developed method was validated using peripheral blood samples acquired from donors with Celiac Disease, Sickle Cell Anemia, and Type 2 Diabetes. It was shown that the method correctly identified all samples as peripheral blood indicating that no false positives could occur because the blood traces were originated from donors suffering from the diseases.
{"title":"Raman Spectroscopy for Forensic Identification of Body Fluid Traces: Method Validation for Potential False Negatives Caused by Blood-Affecting Diseases","authors":"Niara A. Nichols, I. Lednev","doi":"10.4236/ajac.2022.131001","DOIUrl":"https://doi.org/10.4236/ajac.2022.131001","url":null,"abstract":"Two critical issues in forensic science are identifying body fluid traces found at crime scenes and preserving them for DNA analysis. However, the majority of current biochemical tests for body fluid identification, which are applicable at the crime scene, are presumptive and destructive to the sample. Raman Spectroscopy provides a suitable alternative to current methods as a nonde-structive, confirmatory, and potentially in field method. Our laboratory has developed a chemometric model for the identification of five main body fluids using Raman spectroscopy. This model was developed using samples obtained from healthy donors. Thus, it is of most importance for the forensic application of the method to validate its performance for donors with diseases that might affect the biochemical composition of body fluids. In this study, the developed method was validated using peripheral blood samples acquired from donors with Celiac Disease, Sickle Cell Anemia, and Type 2 Diabetes. It was shown that the method correctly identified all samples as peripheral blood indicating that no false positives could occur because the blood traces were originated from donors suffering from the diseases.","PeriodicalId":63216,"journal":{"name":"美国分析化学(英文)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70500233","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 : 2022-01-01DOI: 10.4236/ajac.2022.1311030
Y. Achille, Agbokponto Janvier Engelbert, Assanhou Assogba Gabin, Adetona Pauline, Doffon Parfait, Ganfon Habib, Roland Marini Djang’eing’a
{"title":"Quality Control of Paracetamol Generic Tablets Marketed in Benin and Search of Its Two Impurities P-Aminophenol and P-Nitrophenol by HPLC-UV/Visible","authors":"Y. Achille, Agbokponto Janvier Engelbert, Assanhou Assogba Gabin, Adetona Pauline, Doffon Parfait, Ganfon Habib, Roland Marini Djang’eing’a","doi":"10.4236/ajac.2022.1311030","DOIUrl":"https://doi.org/10.4236/ajac.2022.1311030","url":null,"abstract":"","PeriodicalId":63216,"journal":{"name":"美国分析化学(英文)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70500425","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 : 2022-01-01DOI: 10.4236/ajac.2022.132006
Feng Yu, Jinfang Ma, Yi Qi, Han Song, Guiliang Tan, Furong Huang, Maoxun Yang
In this study, a seed origin discrimination model for Clinacanthus nutans was developed. First, 81 C. nutans samples from three seed origin locations were collected, and their Near-Infrared (NIR) spectra were obtained. Next, Principal Component Analysis (PCA) was performed on the NIR spectra of the 81 C. nutans samples. Then, MSC (multiplicative scatter correction), SNV (stand-ard normal variate), first derivative, and second derivative pre-treatments of the C. nutans spectra were performed and combined with the Support Vector Machine (SVM) algorithm for modelling and analysis. Among these methods, first-order derivative pre-treatment achieved the best SVM model effectiveness, with a training set accuracy of 93.44% (57/61) and a test set accuracy of 85.00% (17/20). In order to further improve the discrimination accuracy of the model, three optimization algorithms Grid Search (GS), Genetic Algorithm (GA), and Particle Swarm Optimization (PSO) were employed to identify the best c and g parameters for the SVM model. The results demonstrated that the PSO optimization algorithm yielded the best parameters of c = 0.8343, g = 57.8741, with corresponding model training set the accuracy of 96.36% (60/61) and test set the accuracy of 95.00% (20/21). Therefore, developing a seed origin classification model for C. nutans based on NIR spectroscopy combined with chemometrics is feasible and has the advantages of being simple, rapid, and green.
在此基础上，建立了山核桃种子来源鉴别模型。首先，从3个种子产地采集了81份核桃样品，获得了其近红外光谱。接下来，对81份核桃样品的近红外光谱进行主成分分析(PCA)。然后，对C. nutans光谱进行乘法散点校正(MSC)、标准正态变量(SNV)、一阶导数和二阶导数预处理，并结合支持向量机(SVM)算法进行建模和分析。其中，一阶导数预处理的SVM模型效果最好，训练集准确率为93.44%(57/61)，测试集准确率为85.00%(17/20)。为了进一步提高模型的识别精度，采用网格搜索(GS)、遗传算法(GA)和粒子群优化(PSO)三种优化算法对SVM模型进行最佳c和g参数的识别。结果表明，PSO优化算法得到的最佳参数为c = 0.8343, g = 57.8741，相应的模型训练集准确率为96.36%(60/61)，测试集准确率为95.00%(20/21)。因此，建立基于近红外光谱与化学计量学相结合的核桃种子来源分类模型是可行的，且具有简单、快速、绿色的优点。
{"title":"Geographical Traceability of <i>Clinacanthus nutans</i> with Near-Infrared Pectroscopy and Chemometrics","authors":"Feng Yu, Jinfang Ma, Yi Qi, Han Song, Guiliang Tan, Furong Huang, Maoxun Yang","doi":"10.4236/ajac.2022.132006","DOIUrl":"https://doi.org/10.4236/ajac.2022.132006","url":null,"abstract":"In this study, a seed origin discrimination model for Clinacanthus nutans was developed. First, 81 C. nutans samples from three seed origin locations were collected, and their Near-Infrared (NIR) spectra were obtained. Next, Principal Component Analysis (PCA) was performed on the NIR spectra of the 81 C. nutans samples. Then, MSC (multiplicative scatter correction), SNV (stand-ard normal variate), first derivative, and second derivative pre-treatments of the C. nutans spectra were performed and combined with the Support Vector Machine (SVM) algorithm for modelling and analysis. Among these methods, first-order derivative pre-treatment achieved the best SVM model effectiveness, with a training set accuracy of 93.44% (57/61) and a test set accuracy of 85.00% (17/20). In order to further improve the discrimination accuracy of the model, three optimization algorithms Grid Search (GS), Genetic Algorithm (GA), and Particle Swarm Optimization (PSO) were employed to identify the best c and g parameters for the SVM model. The results demonstrated that the PSO optimization algorithm yielded the best parameters of c = 0.8343, g = 57.8741, with corresponding model training set the accuracy of 96.36% (60/61) and test set the accuracy of 95.00% (20/21). Therefore, developing a seed origin classification model for C. nutans based on NIR spectroscopy combined with chemometrics is feasible and has the advantages of being simple, rapid, and green.","PeriodicalId":63216,"journal":{"name":"美国分析化学(英文)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70500443","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 : 2022-01-01DOI: 10.4236/ajac.2022.1310025
B. Kaboré, Moumouni Koala, Mathieu Nitiema, Windingoudi Rimwagna Christian Ouedraogo, Souleymane Compaoré, L. Belemnaba, S. Ouedraogo, Sylvain Ilboudo, N. Ouedraogo, Constantin M. Dabiré, F. Kini, S. Ouédraogo, E. Palé
{"title":"Phytochemical Screening by High-Performance Thin-Layer Chromatography, Antioxidant Activities and Acute Toxicity of Trunk Barks Extracts of <i>Lannea velutina</i> A. Rich","authors":"B. Kaboré, Moumouni Koala, Mathieu Nitiema, Windingoudi Rimwagna Christian Ouedraogo, Souleymane Compaoré, L. Belemnaba, S. Ouedraogo, Sylvain Ilboudo, N. Ouedraogo, Constantin M. Dabiré, F. Kini, S. Ouédraogo, E. Palé","doi":"10.4236/ajac.2022.1310025","DOIUrl":"https://doi.org/10.4236/ajac.2022.1310025","url":null,"abstract":"","PeriodicalId":63216,"journal":{"name":"美国分析化学(英文)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70500280","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 : 2022-01-01DOI: 10.4236/ajac.2022.1311029
T. S. A. Jeevan, G. Tadele, Liyew Yizengaw, M. F. L. Johnson
{"title":"Review on Recent Progress of Nanostructured Anode Materials for Li-Ion Batteries","authors":"T. S. A. Jeevan, G. Tadele, Liyew Yizengaw, M. F. L. Johnson","doi":"10.4236/ajac.2022.1311029","DOIUrl":"https://doi.org/10.4236/ajac.2022.1311029","url":null,"abstract":"","PeriodicalId":63216,"journal":{"name":"美国分析化学(英文)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70500375","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 : 2022-01-01DOI: 10.4236/ajac.2022.132004
Christina R. Perez, M. Rani, T. Phan
{"title":"Optimization of High-Performance Liquid Chromatography Parameters for Purification of Oligonucleotide-A","authors":"Christina R. Perez, M. Rani, T. Phan","doi":"10.4236/ajac.2022.132004","DOIUrl":"https://doi.org/10.4236/ajac.2022.132004","url":null,"abstract":"","PeriodicalId":63216,"journal":{"name":"美国分析化学(英文)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70500392","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 : 2022-01-01DOI: 10.4236/ajac.2022.1312033
Jean-Kisito Kouamé, M. D. Yéhé, Carine Nina Ablé, Vincent De Paul Ovi, Hervé Tazoh Broh, C. B. N. Ngantchouko, G. Gbassi
{"title":"Influence of Some Physico-Chemical Exposure Factors on the Carbocysteine Content of an Opened Pharmaceutical Product","authors":"Jean-Kisito Kouamé, M. D. Yéhé, Carine Nina Ablé, Vincent De Paul Ovi, Hervé Tazoh Broh, C. B. N. Ngantchouko, G. Gbassi","doi":"10.4236/ajac.2022.1312033","DOIUrl":"https://doi.org/10.4236/ajac.2022.1312033","url":null,"abstract":"","PeriodicalId":63216,"journal":{"name":"美国分析化学(英文)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70500490","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}
{"title":"Stabilization of Spent Grains by Composting: Case of the BB Brewery in Lomé (Togo)","authors":"Bodjona Bassai Magnoudewa, Kadena Somyé-Abalo Mèhèssa, Kolani Lankondjoa, Bafai Diyakadola Dihéénane","doi":"10.4236/ajac.2022.135012","DOIUrl":"https://doi.org/10.4236/ajac.2022.135012","url":null,"abstract":"","PeriodicalId":63216,"journal":{"name":"美国分析化学(英文)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70500561","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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