Disease diagnosis through breath analysis has attracted significant attention in recent years due to its noninvasive nature, rapid testing ability, and applicability for patients of all ages. More than 1000 volatile organic components (VOCs) exist in human breath, but only selected VOCs are associated with specific diseases. Selective identification of those disease marker VOCs using an array of multiple sensors are highly desirable in the current scenario. The use of efficient sensors and the use of suitable classification algorithms is essential for the selective and reliable detection of those disease markers in complex breath. In the current study, we fabricated a noble metal (Au, Pd and Pt) nanoparticle-functionalized MoS2 (Chalcogenides, Sigma Aldrich, St. Louis, MO, USA)-based sensor array for the selective identification of different VOCs. Four sensors, i.e., pure MoS2, Au/MoS2, Pd/MoS2, and Pt/MoS2 were tested under exposure to different VOCs, such as acetone, benzene, ethanol, xylene, 2-propenol, methanol and toluene, at 50 °C. Initially, principal component analysis (PCA) and linear discriminant analysis (LDA) were used to discriminate those seven VOCs. As compared to the PCA, LDA was able to discriminate well between the seven VOCs. Four different machine learning algorithms such as k-nearest neighbors (kNN), decision tree, random forest, and multinomial logistic regression were used to further identify those VOCs. The classification accuracy of those seven VOCs using KNN, decision tree, random forest, and multinomial logistic regression was 97.14%, 92.43%, 84.1%, and 98.97%, respectively. These results authenticated that multinomial logistic regression performed best between the four machine learning algorithms to discriminate and differentiate the multiple VOCs that generally exist in human breath.
近年来，通过呼吸分析进行疾病诊断因其无创性、快速检测能力和适用于所有年龄的患者而备受关注。人体呼吸中存在1000多种挥发性有机成分(VOCs)，但只有特定的VOCs与特定的疾病有关。在目前的情况下，使用多个传感器阵列选择性地识别这些疾病标志物VOCs是非常可取的。使用高效的传感器和使用合适的分类算法对于选择性和可靠地检测复杂呼吸中的这些疾病标志物至关重要。在本研究中，我们制作了一种贵金属(Au, Pd和Pt)纳米粒子功能化的MoS2 (Chalcogenides, Sigma Aldrich, St. Louis, MO, USA)传感器阵列，用于选择性识别不同的VOCs。在50℃的条件下，测试了纯MoS2、Au/MoS2、Pd/MoS2和Pt/MoS2四种传感器暴露于丙酮、苯、乙醇、二甲苯、2-丙烯醇、甲醇和甲苯等不同挥发性有机化合物下的性能。首先，采用主成分分析(PCA)和线性判别分析(LDA)对这7种VOCs进行了判别。与PCA相比，LDA能够很好地区分七种挥发性有机化合物。采用k近邻(kNN)、决策树、随机森林和多项逻辑回归等四种不同的机器学习算法进一步识别这些挥发性有机化合物。采用KNN、决策树、随机森林和多项逻辑回归对这7种VOCs的分类准确率分别为97.14%、92.43%、84.1%和98.97%。这些结果验证了多项逻辑回归在四种机器学习算法中表现最好，以区分和区分人类呼吸中普遍存在的多种挥发性有机化合物。
{"title":"Statistical Analysis for Selective Identifications of VOCs by Using Surface Functionalized MoS2 Based Sensor Array","authors":"U. N. Thakur, Radha Bhardwaj, A. Hazra","doi":"10.3390/csac2021-10451","DOIUrl":"https://doi.org/10.3390/csac2021-10451","url":null,"abstract":"Disease diagnosis through breath analysis has attracted significant attention in recent years due to its noninvasive nature, rapid testing ability, and applicability for patients of all ages. More than 1000 volatile organic components (VOCs) exist in human breath, but only selected VOCs are associated with specific diseases. Selective identification of those disease marker VOCs using an array of multiple sensors are highly desirable in the current scenario. The use of efficient sensors and the use of suitable classification algorithms is essential for the selective and reliable detection of those disease markers in complex breath. In the current study, we fabricated a noble metal (Au, Pd and Pt) nanoparticle-functionalized MoS2 (Chalcogenides, Sigma Aldrich, St. Louis, MO, USA)-based sensor array for the selective identification of different VOCs. Four sensors, i.e., pure MoS2, Au/MoS2, Pd/MoS2, and Pt/MoS2 were tested under exposure to different VOCs, such as acetone, benzene, ethanol, xylene, 2-propenol, methanol and toluene, at 50 °C. Initially, principal component analysis (PCA) and linear discriminant analysis (LDA) were used to discriminate those seven VOCs. As compared to the PCA, LDA was able to discriminate well between the seven VOCs. Four different machine learning algorithms such as k-nearest neighbors (kNN), decision tree, random forest, and multinomial logistic regression were used to further identify those VOCs. The classification accuracy of those seven VOCs using KNN, decision tree, random forest, and multinomial logistic regression was 97.14%, 92.43%, 84.1%, and 98.97%, respectively. These results authenticated that multinomial logistic regression performed best between the four machine learning algorithms to discriminate and differentiate the multiple VOCs that generally exist in human breath.","PeriodicalId":9815,"journal":{"name":"Chemistry Proceedings","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88815593","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}
A. Kalinowska, P. Matusiak, Sandra Skorupska, I. Grabowska-Jadach, P. Ciosek-Skibińska
Working parameters of chemical sensors, such as selectivity and sensitivity, can be adjusted by optimizing components of chemosensitive layers, including type and amount of plasticizer in the case of PVC membranes in optodes. Plasticizers are also used in the process of creating micro/nanospheres that are incorporated with chemical indicators to form micro/nano-scale optodes. This study investigated the influence of the type of plasticizer (polar o-NPOE and non-polar DOS) on the optical response of microspheres that are sensitive to lipophilic ions. Moreover, the amount of plasticizer was also adjusted in order to obtain satisfactory sensitivity in the widest linear range. The chemosensory response of the developed microspheres was studied with the use of spectrophotometry and spectrofluorimetry, while size of the optodes was estimated by confocal microscopy.
{"title":"Influence of the Type and Amount of Plasticizer on the Sensory Properties of Microspheres Sensitive to Lipophilic Ions","authors":"A. Kalinowska, P. Matusiak, Sandra Skorupska, I. Grabowska-Jadach, P. Ciosek-Skibińska","doi":"10.3390/csac2021-10487","DOIUrl":"https://doi.org/10.3390/csac2021-10487","url":null,"abstract":"Working parameters of chemical sensors, such as selectivity and sensitivity, can be adjusted by optimizing components of chemosensitive layers, including type and amount of plasticizer in the case of PVC membranes in optodes. Plasticizers are also used in the process of creating micro/nanospheres that are incorporated with chemical indicators to form micro/nano-scale optodes. This study investigated the influence of the type of plasticizer (polar o-NPOE and non-polar DOS) on the optical response of microspheres that are sensitive to lipophilic ions. Moreover, the amount of plasticizer was also adjusted in order to obtain satisfactory sensitivity in the widest linear range. The chemosensory response of the developed microspheres was studied with the use of spectrophotometry and spectrofluorimetry, while size of the optodes was estimated by confocal microscopy.","PeriodicalId":9815,"journal":{"name":"Chemistry Proceedings","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87288775","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}
Alcohol abuse is the dominant cause of fatal car accidents (about 25% of all road deaths in Europe). The large-scale implementation of systems aimed at the realization of in-vehicle driver breath ethanol detection is therefore in high demand. For this reason, we devoted our attention to the design of an inexpensive and reliable breath alcohol sensor for use in an Advanced Driver Assistance System (ADAS). The main challenge in the development of this sensor is related to the complexity of breath composition and its high humidity content, coupled with the high dilution of breath reaching the sensor. In this work, a simple α-Fe2O3 film-based sensor was developed and validated in laboratory tests. Tests were also performed by placing the ethanol sensor within the casing of the upper steering column of a car to simulate real driving conditions. Using an array provided with the developed ethanol sensor and humidity, temperature and CO2 sensors, it was possible to differentiate the signal of a driver’s breath before and after alcohol consumption.
{"title":"Development of an Integrated In-Vehicle Driver Breath Ethanol System Based on α-Fe2O3 Sensing Material","authors":"R. Di Chio, Monica Galtieri, N. Donato, G. Neri","doi":"10.3390/csac2021-10476","DOIUrl":"https://doi.org/10.3390/csac2021-10476","url":null,"abstract":"Alcohol abuse is the dominant cause of fatal car accidents (about 25% of all road deaths in Europe). The large-scale implementation of systems aimed at the realization of in-vehicle driver breath ethanol detection is therefore in high demand. For this reason, we devoted our attention to the design of an inexpensive and reliable breath alcohol sensor for use in an Advanced Driver Assistance System (ADAS). The main challenge in the development of this sensor is related to the complexity of breath composition and its high humidity content, coupled with the high dilution of breath reaching the sensor. In this work, a simple α-Fe2O3 film-based sensor was developed and validated in laboratory tests. Tests were also performed by placing the ethanol sensor within the casing of the upper steering column of a car to simulate real driving conditions. Using an array provided with the developed ethanol sensor and humidity, temperature and CO2 sensors, it was possible to differentiate the signal of a driver’s breath before and after alcohol consumption.","PeriodicalId":9815,"journal":{"name":"Chemistry Proceedings","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87351692","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}
E. Sánchez-Tirado, S. Guerrero, A. González-Cortés, L. Agüí, P. Yáñez‐Sedeño, J. Pingarrón
Rheumatoid arthritis is an autoimmune disorder characterized by persistent erosive synovitis, systemic inflammation and the presence of autoantibodies, which play an important role in inducing inflammation and joint damage, releasing pro-inflammatory cytokines from monocytes and macrophages [1,2]. Likewise, neutrophil activating protein-2 (CXCL7) is a platelet-derived growth factor belonging to the CXC chemokine subfamily, which is expressed in serum, synovial fluid and synovial tissue of patients developing rheumatoid arthritis during the first twelve weeks, being useful to reflect local pathological changes [3]. Besides, matrix metalloproteinase-3 (MMP-3), which is induced by inflammatory cytokines such as interleukin-1 (IL-1) and tumor necrosis factor alpha (TNF-α) in rheumatoid synovium, degrades several extracellular matrix components of cartilage and plays central roles in rheumatoid joint destruction [4]. Therefore, monitoring serum CXCL7 and MMP-3 levels is useful for predicting the disease activity in rheumatoid arthritis. In this work, the construction and analytical performance of a dual electrochemical platform for the simultaneous determination of CXCL7 and MMP-3 is described. After the optimization of experimental variables involved in the preparation and implementation of the biosensor, the analytical usefulness of the developed configuration was demonstrated by its application to the determination of these biomarkers in serum samples from healthy individuals and patients with rheumatoid arthritis. To carry out the simultaneous determination of CXCL7 and MMP3 in human serum, just a fifty-fold sample dilution in PBS of pH 7.4 was required. In addition, the results obtained using the dual immunosensor were compared with those provided by the respective ELISA immunoassays, yielding no significant differences between the two methods. It is important to highlight that reagents consumption, four times smaller using the dual immunosensor than that required in the ELISA protocol, and an assay time of 2 h 50 min versus almost 5 h, counted in both cases after incubation of the capture antibody, are advantageous features of the dual immunosensor [5].
{"title":"Electrochemical Immunosensor for Simultaneous Determination of Emerging Autoimmune Disease Biomarkers in Human Serum","authors":"E. Sánchez-Tirado, S. Guerrero, A. González-Cortés, L. Agüí, P. Yáñez‐Sedeño, J. Pingarrón","doi":"10.3390/csac2021-10437","DOIUrl":"https://doi.org/10.3390/csac2021-10437","url":null,"abstract":"Rheumatoid arthritis is an autoimmune disorder characterized by persistent erosive synovitis, systemic inflammation and the presence of autoantibodies, which play an important role in inducing inflammation and joint damage, releasing pro-inflammatory cytokines from monocytes and macrophages [1,2]. Likewise, neutrophil activating protein-2 (CXCL7) is a platelet-derived growth factor belonging to the CXC chemokine subfamily, which is expressed in serum, synovial fluid and synovial tissue of patients developing rheumatoid arthritis during the first twelve weeks, being useful to reflect local pathological changes [3]. Besides, matrix metalloproteinase-3 (MMP-3), which is induced by inflammatory cytokines such as interleukin-1 (IL-1) and tumor necrosis factor alpha (TNF-α) in rheumatoid synovium, degrades several extracellular matrix components of cartilage and plays central roles in rheumatoid joint destruction [4]. Therefore, monitoring serum CXCL7 and MMP-3 levels is useful for predicting the disease activity in rheumatoid arthritis. In this work, the construction and analytical performance of a dual electrochemical platform for the simultaneous determination of CXCL7 and MMP-3 is described. After the optimization of experimental variables involved in the preparation and implementation of the biosensor, the analytical usefulness of the developed configuration was demonstrated by its application to the determination of these biomarkers in serum samples from healthy individuals and patients with rheumatoid arthritis. To carry out the simultaneous determination of CXCL7 and MMP3 in human serum, just a fifty-fold sample dilution in PBS of pH 7.4 was required. In addition, the results obtained using the dual immunosensor were compared with those provided by the respective ELISA immunoassays, yielding no significant differences between the two methods. It is important to highlight that reagents consumption, four times smaller using the dual immunosensor than that required in the ELISA protocol, and an assay time of 2 h 50 min versus almost 5 h, counted in both cases after incubation of the capture antibody, are advantageous features of the dual immunosensor [5].","PeriodicalId":9815,"journal":{"name":"Chemistry Proceedings","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79638117","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}
Ekaterina Yuskina, K. Tugashov, V. Shur, I. A. Tikhonova, V. Babain, D. Kirsanov
In this work, we explore the possibility of using anti-crown ether (C6HgF4)3 as a membrane-active component for potentiometric cross-sensitive sensors. Anti-crown ligands have already been employed as ionophores in plasticized polymeric membranes; however, the results of these studies are contradictory. In order to clarify the electrochemical sensitivity patterns of anti-crown-based sensors, we have studied plasticized polymeric membranes containing cation and anion-exchanging additives and various solvent-plasticizers. We explored the electrochemical sensitivity of these membranes in a wide variety of aqueous solutions of inorganic salts. Alkaline, alkaline-earth, and d-element salts with different anions were studied. It was found that the sensors based on anti-crown (C6HgF4)3 exhibit cationic sensitivity, and no considerable anionic responses were observed.
{"title":"Cross-Sensitive Potentiometric Sensors Based on Anti-Crown (C6HgF4)3","authors":"Ekaterina Yuskina, K. Tugashov, V. Shur, I. A. Tikhonova, V. Babain, D. Kirsanov","doi":"10.3390/csac2021-10424","DOIUrl":"https://doi.org/10.3390/csac2021-10424","url":null,"abstract":"In this work, we explore the possibility of using anti-crown ether (C6HgF4)3 as a membrane-active component for potentiometric cross-sensitive sensors. Anti-crown ligands have already been employed as ionophores in plasticized polymeric membranes; however, the results of these studies are contradictory. In order to clarify the electrochemical sensitivity patterns of anti-crown-based sensors, we have studied plasticized polymeric membranes containing cation and anion-exchanging additives and various solvent-plasticizers. We explored the electrochemical sensitivity of these membranes in a wide variety of aqueous solutions of inorganic salts. Alkaline, alkaline-earth, and d-element salts with different anions were studied. It was found that the sensors based on anti-crown (C6HgF4)3 exhibit cationic sensitivity, and no considerable anionic responses were observed.","PeriodicalId":9815,"journal":{"name":"Chemistry Proceedings","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73665749","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}
G. Y. Aguilar-Lira, Prisciliano Hernandez, G. Álvarez-Romero, J. M. Gutiérrez
This work describes the development of a novel and low-cost methodology for the simultaneous quantification of four main nonsteroidal anti-inflammatory drugs (NSAIDs) in pharmaceutical samples using differential pulse voltammetry coupled with an artificial neural network model (ANN). The working electrode used as a detector was a carbon paste electrode (CPE) modified with multi-wall carbon nanotubes (MWCNT-CPE). The specific voltammetric determination of the drugs was performed by cyclic voltammetry (CV). Some characteristic anodic peaks were found at potentials of 0.446, 0.629, 0.883 V related to paracetamol, diclofenac, and aspirin. For naproxen, two anodic peaks were found at 0.888 and 1.14 V and for ibuprofen, an anodic peak was not observed at an optimum pH of 10 in 0.1 mol L−1 Britton–Robinson buffer. Since these drug’s oxidation process turned out to be irreversible and diffusion-controlled, drug quantification was carried out by differential pulse voltammetry (DPV). The Box Behnken design technique’s optimal parameters were: step potential of 5.85 mV, the amplitude of 50 mV, period of 750 ms, and a pulse width of 50 ms. A data pretreatment was carried out using the Discrete Wavelet Transform using the db4 wavelet at the fourth decomposition level applied to the voltammetric records obtained. An ANN was built to interpret the obtained approximation coefficients of voltammograms generated at different drug concentrations to calibrate the system. The ANN model’s architecture is based on a Multilayer Perceptron Network (MLP) that employed a Bayesian regularization training algorithm. The trained MLP achieves significant R values for the test data to simultaneous quantification of the four drugs in the presence of aspirin.
{"title":"Simultaneous Quantification of Four Principal NSAIDs through Voltammetry and Artificial Neural Networks Using a Modified Carbon Paste Electrode in Pharmaceutical Samples","authors":"G. Y. Aguilar-Lira, Prisciliano Hernandez, G. Álvarez-Romero, J. M. Gutiérrez","doi":"10.3390/csac2021-10450","DOIUrl":"https://doi.org/10.3390/csac2021-10450","url":null,"abstract":"This work describes the development of a novel and low-cost methodology for the simultaneous quantification of four main nonsteroidal anti-inflammatory drugs (NSAIDs) in pharmaceutical samples using differential pulse voltammetry coupled with an artificial neural network model (ANN). The working electrode used as a detector was a carbon paste electrode (CPE) modified with multi-wall carbon nanotubes (MWCNT-CPE). The specific voltammetric determination of the drugs was performed by cyclic voltammetry (CV). Some characteristic anodic peaks were found at potentials of 0.446, 0.629, 0.883 V related to paracetamol, diclofenac, and aspirin. For naproxen, two anodic peaks were found at 0.888 and 1.14 V and for ibuprofen, an anodic peak was not observed at an optimum pH of 10 in 0.1 mol L−1 Britton–Robinson buffer. Since these drug’s oxidation process turned out to be irreversible and diffusion-controlled, drug quantification was carried out by differential pulse voltammetry (DPV). The Box Behnken design technique’s optimal parameters were: step potential of 5.85 mV, the amplitude of 50 mV, period of 750 ms, and a pulse width of 50 ms. A data pretreatment was carried out using the Discrete Wavelet Transform using the db4 wavelet at the fourth decomposition level applied to the voltammetric records obtained. An ANN was built to interpret the obtained approximation coefficients of voltammograms generated at different drug concentrations to calibrate the system. The ANN model’s architecture is based on a Multilayer Perceptron Network (MLP) that employed a Bayesian regularization training algorithm. The trained MLP achieves significant R values for the test data to simultaneous quantification of the four drugs in the presence of aspirin.","PeriodicalId":9815,"journal":{"name":"Chemistry Proceedings","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88859303","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}
M. Barral-Martinez, P. García-Oliveira, Bernabé Nuñez-Estevez, Aurora Silva, T. Finimundy, R. Calhelha, Marija Nenadić, M. Soković, F. Barroso, J. Simal-Gándara, I. Ferreira, L. Barros, M. Prieto
The present study focused on the biological analysis of five plants: Achillea millefolium, Arnica montana, Calendula officinalis, Chamaemelum nobile and Taraxacum officinale. The results indicated that A. montana extracts showed the highest content of phenolic compounds. Regarding the biological properties, A. millefolium had outstanding antioxidant activity, while C. officinalis had the highest rate of antimicrobial and antifungal activity. The anti-inflammatory and cytotoxic activities reflected that C. nobile showed the highest effect. In enzyme assays, C. nobile and C. officinalis extracts showed the highest inhibitory effects on acetylcholinesterase and butyrylcholinesterase enzymes. Overall, this study provides scientific evidence for the evaluation of the potential of medicinal plant extracts for the development of new products.
{"title":"Plants of the Family Asteraceae: Evaluation of Biological Properties and Identification of Phenolic Compounds","authors":"M. Barral-Martinez, P. García-Oliveira, Bernabé Nuñez-Estevez, Aurora Silva, T. Finimundy, R. Calhelha, Marija Nenadić, M. Soković, F. Barroso, J. Simal-Gándara, I. Ferreira, L. Barros, M. Prieto","doi":"10.3390/csac2021-10486","DOIUrl":"https://doi.org/10.3390/csac2021-10486","url":null,"abstract":"The present study focused on the biological analysis of five plants: Achillea millefolium, Arnica montana, Calendula officinalis, Chamaemelum nobile and Taraxacum officinale. The results indicated that A. montana extracts showed the highest content of phenolic compounds. Regarding the biological properties, A. millefolium had outstanding antioxidant activity, while C. officinalis had the highest rate of antimicrobial and antifungal activity. The anti-inflammatory and cytotoxic activities reflected that C. nobile showed the highest effect. In enzyme assays, C. nobile and C. officinalis extracts showed the highest inhibitory effects on acetylcholinesterase and butyrylcholinesterase enzymes. Overall, this study provides scientific evidence for the evaluation of the potential of medicinal plant extracts for the development of new products.","PeriodicalId":9815,"journal":{"name":"Chemistry Proceedings","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84710512","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}
H. Tyagi, E. Daulton, A. Bannaga, R. Arasaradnam, J. Covington
This study outlines the use of an electronic nose as a method for the detection of VOCs as biomarkers of bladder cancer. Here, an AlphaMOS FOX 4000 electronic nose was used for the analysis of urine samples from 15 bladder cancer and 41 non-cancerous patients. The FOX 4000 consists of 18 MOS sensors that were used to differentiate the two groups. The results obtained were analysed using s MultiSens Analyzer and RStudio. The results showed a high separation with sensitivity and specificity of 0.93 and 0.88, respectively, using a Sparse Logistic Regression and 0.93 and 0.76 using a Random Forest classifier. We conclude that the electronic nose shows potential for discriminating bladder cancer from non-cancer subjects using urine samples.
本研究概述了使用电子鼻作为一种方法来检测挥发性有机化合物作为膀胱癌的生物标志物。本文使用AlphaMOS FOX 4000电子鼻对15例膀胱癌患者和41例非膀胱癌患者的尿液样本进行了分析。FOX 4000由18个MOS传感器组成，用于区分两组。使用MultiSens Analyzer和RStudio对所得结果进行分析。结果表明，使用稀疏逻辑回归和随机森林分类器分别具有0.93和0.88和0.93和0.76的高分离度和特异性。我们的结论是，电子鼻显示出利用尿液样本区分膀胱癌和非膀胱癌受试者的潜力。
{"title":"Electronic Nose for Bladder Cancer Detection","authors":"H. Tyagi, E. Daulton, A. Bannaga, R. Arasaradnam, J. Covington","doi":"10.3390/csac2021-10438","DOIUrl":"https://doi.org/10.3390/csac2021-10438","url":null,"abstract":"This study outlines the use of an electronic nose as a method for the detection of VOCs as biomarkers of bladder cancer. Here, an AlphaMOS FOX 4000 electronic nose was used for the analysis of urine samples from 15 bladder cancer and 41 non-cancerous patients. The FOX 4000 consists of 18 MOS sensors that were used to differentiate the two groups. The results obtained were analysed using s MultiSens Analyzer and RStudio. The results showed a high separation with sensitivity and specificity of 0.93 and 0.88, respectively, using a Sparse Logistic Regression and 0.93 and 0.76 using a Random Forest classifier. We conclude that the electronic nose shows potential for discriminating bladder cancer from non-cancer subjects using urine samples.","PeriodicalId":9815,"journal":{"name":"Chemistry Proceedings","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85343320","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}
The growing human population and the discovery of new diseases and emerging pandemics have increased the need for healthcare treatments and medications with innovative designs. The emergence of nanotechnology provides a platform for novel diagnostic and therapeutic in vivo non-invasive detection and treatment of ailments. It is now the era of the Internet of things (IoT), and data acquisition and interpretation from various parts of the human body in real time is possible with interconnected sensors and information transfer devices. Miniaturization, low power consumption and price with compatibility to existing network circuits are essential requirements in the IoT. Biosensors made of nanostructured materials are the ideal choice due to the unique structural, chemical and electronic properties of these materials with the advantage of a large surface-to-volume ratio, which makes them very successful for use as sensors for the detection of diseases, drug carriers, filters, fillers and reaction catalysts in healthcare applications. In this paper, we reviewed the recent progress made in the research and applications of biosensors in health and preventive medicine. The focus of the paper is biosensors made of nanostructured layered materials such as graphene and its structural analogs molybdenum disulphide (MoS2) and boron nitride (BN). We discussed and highlighted the present capabilities of the different nano-forms of these materials in the detection and analysis of diseases. Their efficiencies in terms of the detection limit, the sensitivity and the adaptability to different environments were be discussed. In addition, the challenges and future perspectives of using nano-biosensors to develop efficient diagnostic, therapeutic and cost-effective monitoring devices with smart technologies were explored.
{"title":"Review of the Recent Advances in Nano-Biosensors and Technologies for Healthcare Applications","authors":"M. Aqra, A. Ramanathan","doi":"10.3390/csac2021-10473","DOIUrl":"https://doi.org/10.3390/csac2021-10473","url":null,"abstract":"The growing human population and the discovery of new diseases and emerging pandemics have increased the need for healthcare treatments and medications with innovative designs. The emergence of nanotechnology provides a platform for novel diagnostic and therapeutic in vivo non-invasive detection and treatment of ailments. It is now the era of the Internet of things (IoT), and data acquisition and interpretation from various parts of the human body in real time is possible with interconnected sensors and information transfer devices. Miniaturization, low power consumption and price with compatibility to existing network circuits are essential requirements in the IoT. Biosensors made of nanostructured materials are the ideal choice due to the unique structural, chemical and electronic properties of these materials with the advantage of a large surface-to-volume ratio, which makes them very successful for use as sensors for the detection of diseases, drug carriers, filters, fillers and reaction catalysts in healthcare applications. In this paper, we reviewed the recent progress made in the research and applications of biosensors in health and preventive medicine. The focus of the paper is biosensors made of nanostructured layered materials such as graphene and its structural analogs molybdenum disulphide (MoS2) and boron nitride (BN). We discussed and highlighted the present capabilities of the different nano-forms of these materials in the detection and analysis of diseases. Their efficiencies in terms of the detection limit, the sensitivity and the adaptability to different environments were be discussed. In addition, the challenges and future perspectives of using nano-biosensors to develop efficient diagnostic, therapeutic and cost-effective monitoring devices with smart technologies were explored.","PeriodicalId":9815,"journal":{"name":"Chemistry Proceedings","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85101415","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}
Ricarda Torre, M. Freitas, E. Costa-Rama, H. Nouws, C. Delerue-Matos
A screen-printed carbon electrode was used as the transducer for the development of an electrochemical immunosensor for the determination of tropomyosin (a major shrimp allergen) in food samples. Monoclonal and polyclonal antibodies were used in a sandwich-type immunoassay. The analytical signal was electrochemically obtained using an alkaline phosphatase-labelled secondary antibody and a 3-indoxyl phosphate/silver nitrate substrate. The total assay time was 2 h 50 min and allowed the quantification of tropomyosin between 2.5 and 20 ng mL−1, with a limit of detection of 1.7 ng mL−1 The immunosensor was successfully applied to the analysis of commercial food products.
采用丝网印刷碳电极作为传感器，研制了一种测定食品样品中原肌球蛋白(一种主要的虾类过敏原)的电化学免疫传感器。单克隆抗体和多克隆抗体用于三明治型免疫分析。分析信号采用碱性磷酸酶标记的二抗和3-吲哚基磷酸/硝酸银底物电化学获得。总检测时间为2 h 50 min，原肌球蛋白的定量范围为2.5 ~ 20 ng mL−1，检测限为1.7 ng mL−1。该免疫传感器成功应用于商业食品的分析。
{"title":"Tropomyosin Analysis in Foods Using an Electrochemical Immunosensing Approach","authors":"Ricarda Torre, M. Freitas, E. Costa-Rama, H. Nouws, C. Delerue-Matos","doi":"10.3390/csac2021-10471","DOIUrl":"https://doi.org/10.3390/csac2021-10471","url":null,"abstract":"A screen-printed carbon electrode was used as the transducer for the development of an electrochemical immunosensor for the determination of tropomyosin (a major shrimp allergen) in food samples. Monoclonal and polyclonal antibodies were used in a sandwich-type immunoassay. The analytical signal was electrochemically obtained using an alkaline phosphatase-labelled secondary antibody and a 3-indoxyl phosphate/silver nitrate substrate. The total assay time was 2 h 50 min and allowed the quantification of tropomyosin between 2.5 and 20 ng mL−1, with a limit of detection of 1.7 ng mL−1 The immunosensor was successfully applied to the analysis of commercial food products.","PeriodicalId":9815,"journal":{"name":"Chemistry Proceedings","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88956325","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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