Pub Date : 2022-04-14DOI: 10.3389/frans.2022.872646
Eva Lopez-Fornieles, B. Tisseyre, A. Cheraiet, Belal Gaci, J. Roger
Multispectral image time-series have been promising for some years; yet, the substantial advance of the technology involved, with unprecedented combinations of spatial, temporal, and spectral capabilities for remote sensing applications, raises new challenges, in particular, the need for methodologies that can process the different dimensions of satellite information. Considering that the multi-collinearity problem is present in remote sensing time-series, regression models are widespread tools to model multi-way data. This paper presents the results of the analysis of a high order data of Sentinel-2-time series, conducted in the framework of extreme weather event. A feature extraction method for multi-way data, N-CovSel was used to identify the most relevant features explaining the loss of yield in Mediterranean vineyards during the 2019 heatwave. Different regression models (uni-way and multi-way) from features extracted from the N-CovSel algorithm were calibrated based on available heat wave impact data for 107 vineyard blocks in the Languedoc-Roussillon region and multispectral time-series predictor data for the period May to August. The performance of the models was evaluated by the r 2 and the root mean square of error (RMSE) as follows: for the temporal N-PLS model (r 2 = 0.62—RMSE = 11%), for the spatial N-PLS model (r 2 = 0.61—RMSE = 12%) and the temporal-spectral PLS model (r 2 = 0.63—RMSE = 11%). The results validated the effectiveness of the proposed N-CovSel algorithm in order to reduce the number of total variables and restricting it to the most significant ones. The N-CovSel algorithm seems to be a suitable choice to interpret complex multispectral imagery by temporally discriminating the most appropriate spectral information.
{"title":"Potential of N-CovSel for Variable Selection: A Case Study on Time-Series of Multispectral Images","authors":"Eva Lopez-Fornieles, B. Tisseyre, A. Cheraiet, Belal Gaci, J. Roger","doi":"10.3389/frans.2022.872646","DOIUrl":"https://doi.org/10.3389/frans.2022.872646","url":null,"abstract":"Multispectral image time-series have been promising for some years; yet, the substantial advance of the technology involved, with unprecedented combinations of spatial, temporal, and spectral capabilities for remote sensing applications, raises new challenges, in particular, the need for methodologies that can process the different dimensions of satellite information. Considering that the multi-collinearity problem is present in remote sensing time-series, regression models are widespread tools to model multi-way data. This paper presents the results of the analysis of a high order data of Sentinel-2-time series, conducted in the framework of extreme weather event. A feature extraction method for multi-way data, N-CovSel was used to identify the most relevant features explaining the loss of yield in Mediterranean vineyards during the 2019 heatwave. Different regression models (uni-way and multi-way) from features extracted from the N-CovSel algorithm were calibrated based on available heat wave impact data for 107 vineyard blocks in the Languedoc-Roussillon region and multispectral time-series predictor data for the period May to August. The performance of the models was evaluated by the r 2 and the root mean square of error (RMSE) as follows: for the temporal N-PLS model (r 2 = 0.62—RMSE = 11%), for the spatial N-PLS model (r 2 = 0.61—RMSE = 12%) and the temporal-spectral PLS model (r 2 = 0.63—RMSE = 11%). The results validated the effectiveness of the proposed N-CovSel algorithm in order to reduce the number of total variables and restricting it to the most significant ones. The N-CovSel algorithm seems to be a suitable choice to interpret complex multispectral imagery by temporally discriminating the most appropriate spectral information.","PeriodicalId":73063,"journal":{"name":"Frontiers in analytical science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43806814","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 : 2022-04-04DOI: 10.3389/frans.2022.867527
Lorraine Latchoumane, Karine Alary, J. Minier, F. Davrieux, R. Lugan, M. Chillet, J. Roger
Internal disorder is a major problem in fruit production and is responsible for considerable economical losses. Symptoms are not externally visible, making it difficult to assess the problem. In recent years, 3D fluorescence spectroscopy has been used to reveal features of interest in agronomical field, such as plant stress and plant infection. Such technique could provide useful information regarding changes that occur at the tissue level, in order to distinguish spectral differences between healthy and disordered fruits. This paper introduces the use of the new three-way feature extraction N-CovSel method, compared to the commonly used N-PLS-DA method. These approaches were used upon front-face fluorescence spectra of 27 fruit pulp and skin samples, by analysing excitation wavelengths ranging from 250 to 650 nm, and emission wavelengths varying from 290 to 800 nm. N-CovSel method was applied to identify the most relevant features on: 1) excitation-emission wavelength couples, 2) excitation wavelengths whatever the emission wavelengths and 3) emission wavelengths whatever the excitation wavelengths. Discriminant analysis of the selected features were performed across classes. The constructed models provided key features to differentiate healthy fruits from disordered ones. These results highlighted the capability of N-CovSel method to extract the most fitted features for enhanced fruit classification using front-face fluorescence spectroscopy. They revealed characteristic fluorophores involved in the structural modifications generated by the physiological disorder studied. This paper provides preliminary results concerning the suitability of N-CovSel method for the desired application. Further investigations could be performed on intact fresh fruits in a non-destructive way, allowing an earlier and faster detection of the internal disorder for in-field or industrial applications.
{"title":"Front-Face Fluorescence Spectroscopy and Feature Selection for Fruit Classification Based on N-CovSel Method","authors":"Lorraine Latchoumane, Karine Alary, J. Minier, F. Davrieux, R. Lugan, M. Chillet, J. Roger","doi":"10.3389/frans.2022.867527","DOIUrl":"https://doi.org/10.3389/frans.2022.867527","url":null,"abstract":"Internal disorder is a major problem in fruit production and is responsible for considerable economical losses. Symptoms are not externally visible, making it difficult to assess the problem. In recent years, 3D fluorescence spectroscopy has been used to reveal features of interest in agronomical field, such as plant stress and plant infection. Such technique could provide useful information regarding changes that occur at the tissue level, in order to distinguish spectral differences between healthy and disordered fruits. This paper introduces the use of the new three-way feature extraction N-CovSel method, compared to the commonly used N-PLS-DA method. These approaches were used upon front-face fluorescence spectra of 27 fruit pulp and skin samples, by analysing excitation wavelengths ranging from 250 to 650 nm, and emission wavelengths varying from 290 to 800 nm. N-CovSel method was applied to identify the most relevant features on: 1) excitation-emission wavelength couples, 2) excitation wavelengths whatever the emission wavelengths and 3) emission wavelengths whatever the excitation wavelengths. Discriminant analysis of the selected features were performed across classes. The constructed models provided key features to differentiate healthy fruits from disordered ones. These results highlighted the capability of N-CovSel method to extract the most fitted features for enhanced fruit classification using front-face fluorescence spectroscopy. They revealed characteristic fluorophores involved in the structural modifications generated by the physiological disorder studied. This paper provides preliminary results concerning the suitability of N-CovSel method for the desired application. Further investigations could be performed on intact fresh fruits in a non-destructive way, allowing an earlier and faster detection of the internal disorder for in-field or industrial applications.","PeriodicalId":73063,"journal":{"name":"Frontiers in analytical science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46030005","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 : 2022-03-22DOI: 10.3389/frans.2022.847730
Z. Chaloupková, Zdenka Medříková, M. Král, Veronika Šedajová, V. Ranc
Prostate cancer is one of the compelling types of cancer diagnosed in men. Development of screening analytical methods, which provide fast and reliable results is, thus, demanding. Currently applied methods are usually based on the determination of serum prostate-specific antigen (PSA), where several limitations were identified. However, scientific reports have shown a direct correlation between the percentage of free PSA and prostate volume, and indirect correlation between the unfavorable course of the disease of prostate cancer and the percentage of free PSA in men with elevated PSA levels. Parallel analysis of PSA and free PSA presents an interesting alternative. Here, we present a new analytical method for a parallel analysis of PSA and free PSA in a whole human blood based on MA-SERS. The method is based on magnetic Fe3O4@Ag nanocomposite functionalized using anti-PSA. The method can distinguish between levels of PSA and free PSA within a single analytical run with limits of detection of 0.62 ng/ml for PSA and 0.49 ng/ml for free PSA, respectively.
{"title":"Label-Free Determination of PSA and Free PSA Using MA-SERS","authors":"Z. Chaloupková, Zdenka Medříková, M. Král, Veronika Šedajová, V. Ranc","doi":"10.3389/frans.2022.847730","DOIUrl":"https://doi.org/10.3389/frans.2022.847730","url":null,"abstract":"Prostate cancer is one of the compelling types of cancer diagnosed in men. Development of screening analytical methods, which provide fast and reliable results is, thus, demanding. Currently applied methods are usually based on the determination of serum prostate-specific antigen (PSA), where several limitations were identified. However, scientific reports have shown a direct correlation between the percentage of free PSA and prostate volume, and indirect correlation between the unfavorable course of the disease of prostate cancer and the percentage of free PSA in men with elevated PSA levels. Parallel analysis of PSA and free PSA presents an interesting alternative. Here, we present a new analytical method for a parallel analysis of PSA and free PSA in a whole human blood based on MA-SERS. The method is based on magnetic Fe3O4@Ag nanocomposite functionalized using anti-PSA. The method can distinguish between levels of PSA and free PSA within a single analytical run with limits of detection of 0.62 ng/ml for PSA and 0.49 ng/ml for free PSA, respectively.","PeriodicalId":73063,"journal":{"name":"Frontiers in analytical science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48291377","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 : 2022-03-04DOI: 10.3389/frans.2022.846102
Alfredo J. Ibáñez
Most of us have never faced a pandemic before. The World Health Organization declared the 2019 novel coronavirus infectious disease (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2 virus), a pandemic by March 11th, 2020. Today, this illness has reported more than 5′331,019 fatalities worldwide (December 17th, 2021). The COVID-19 pandemic has posed an unprecedented global challenge and put the academic community on “the spot.” The following mini-review reports how the MS community improved the understanding of the SARS-CoV-2 virus pathophysiology while developing diagnostic procedures to complement the PCR-based approaches. For example, MS researchers identified the interaction sites between the SARS-CoV-2 virus and their hosts; this new knowledge is critical for developing antiviral drugs. MS researchers also realized that COVID-19 should be considered a systemic disease and not just a respiratory illness since its metabolic, lipidomic, and proteomic profile reflects four different clinical disorders: 1) acute inflammatory response, 2) a cardiovascular disease, 3) a prediabetic/diabetes and 4) liver dysfunction. Furthermore, MS researchers put forth the knowledge that the metabolic and lipidomic profile of several patients remained altered after being discharged, thus hinting at the scientific basis for the long COVID syndrome.
{"title":"How Is Mass Spectrometry Tackling the COVID-19 Pandemic?","authors":"Alfredo J. Ibáñez","doi":"10.3389/frans.2022.846102","DOIUrl":"https://doi.org/10.3389/frans.2022.846102","url":null,"abstract":"Most of us have never faced a pandemic before. The World Health Organization declared the 2019 novel coronavirus infectious disease (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2 virus), a pandemic by March 11th, 2020. Today, this illness has reported more than 5′331,019 fatalities worldwide (December 17th, 2021). The COVID-19 pandemic has posed an unprecedented global challenge and put the academic community on “the spot.” The following mini-review reports how the MS community improved the understanding of the SARS-CoV-2 virus pathophysiology while developing diagnostic procedures to complement the PCR-based approaches. For example, MS researchers identified the interaction sites between the SARS-CoV-2 virus and their hosts; this new knowledge is critical for developing antiviral drugs. MS researchers also realized that COVID-19 should be considered a systemic disease and not just a respiratory illness since its metabolic, lipidomic, and proteomic profile reflects four different clinical disorders: 1) acute inflammatory response, 2) a cardiovascular disease, 3) a prediabetic/diabetes and 4) liver dysfunction. Furthermore, MS researchers put forth the knowledge that the metabolic and lipidomic profile of several patients remained altered after being discharged, thus hinting at the scientific basis for the long COVID syndrome.","PeriodicalId":73063,"journal":{"name":"Frontiers in analytical science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49581233","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 : 2022-02-17DOI: 10.3389/frans.2022.857694
J. Stovall, S. Bratton
Most studies of microplastics in freshwater have investigated presence in creeks and rivers below sewage effluents and storm drains. This study examines microplastic distribution in surface waters, including springs and primary streams, located within small, urban Karst watersheds, with and without sources of wastewater treatment discharge. Study locales were in Texas, United States, either in Waco on the Brazos River or in or downstream from San Marcos on the San Marcos River. Research teams collected 800 ml surface water from four different small watersheds and an urban pond (n = 779) and filtered them through 53 μm Nitex mesh. Teams collected samples from springs or primary streams to the lower end of creeks and across stream transects based on distance from the bank and the presence of vegetation and debris. Teams also replicated samples seasonally. Stereo microscopy examined each filter for microplastic particles and subsequently color and type (i.e., fragment, fiber, or sphere). Additionally, we analyzed the influence of urbanization and land use on the origin and transport of the microplastics. Overall, the filters recovered 1,198 microplastic fibers and fragments. On average, 56.7% of all samples at each study locale contained microplastics. Particle abundance was the highest at Proctor Springs ( x ¯ = 3.38 ) and lowest at the pond ( x ¯ = 0.98 ) , both headwaters. Local human use and runoff were thus potentially important factors in microplastic presence, while sewage discharge was not unilaterally the primary determinant of microplastic abundance. Peak pollution events occurred in June, September, and October, indicating seasonality of rainfall and recreation affected microplastic frequency and type.
{"title":"Microplastic Pollution in Surface Waters of Urban Watersheds in Central Texas, United States: A Comparison of Sites With and Without Treated Wastewater Effluent","authors":"J. Stovall, S. Bratton","doi":"10.3389/frans.2022.857694","DOIUrl":"https://doi.org/10.3389/frans.2022.857694","url":null,"abstract":"Most studies of microplastics in freshwater have investigated presence in creeks and rivers below sewage effluents and storm drains. This study examines microplastic distribution in surface waters, including springs and primary streams, located within small, urban Karst watersheds, with and without sources of wastewater treatment discharge. Study locales were in Texas, United States, either in Waco on the Brazos River or in or downstream from San Marcos on the San Marcos River. Research teams collected 800 ml surface water from four different small watersheds and an urban pond (n = 779) and filtered them through 53 μm Nitex mesh. Teams collected samples from springs or primary streams to the lower end of creeks and across stream transects based on distance from the bank and the presence of vegetation and debris. Teams also replicated samples seasonally. Stereo microscopy examined each filter for microplastic particles and subsequently color and type (i.e., fragment, fiber, or sphere). Additionally, we analyzed the influence of urbanization and land use on the origin and transport of the microplastics. Overall, the filters recovered 1,198 microplastic fibers and fragments. On average, 56.7% of all samples at each study locale contained microplastics. Particle abundance was the highest at Proctor Springs ( x ¯ = 3.38 ) and lowest at the pond ( x ¯ = 0.98 ) , both headwaters. Local human use and runoff were thus potentially important factors in microplastic presence, while sewage discharge was not unilaterally the primary determinant of microplastic abundance. Peak pollution events occurred in June, September, and October, indicating seasonality of rainfall and recreation affected microplastic frequency and type.","PeriodicalId":73063,"journal":{"name":"Frontiers in analytical science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-02-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46784069","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 : 2022-02-10DOI: 10.3389/frans.2022.834820
C. Ott, M. Perez-Estebañez, Sheila Hernandez, Kendra Kelly, Kourtney A. Dalzell, M. J. Arcos-Martínez, A. Heras, Á. Colina, Luis E. Arroyo
Reliable identification of fentanyl and fentanyl analogs present in seized drug samples is imperative to the safety of first responders and laboratory personnel and informs the future analysis process and handling procedures. The electrochemical-surface enhanced Raman spectroscopy (EC-SERS) method developed in this work allows the in-situ preparation of the SERS substrate providing a rapid, efficient, and accurate approach to detect fentanyl, even at low percent by weight concentrations common in seized drugs. Optimization of the electrochemical potentials suitable for the SERS substrate preparation and adsorption of the analyte was achieved using multi-pulse amperometric detection. This method demonstrated large enhancement of the SERS response. This method was applied to six fentanyl analogs with substitutions to the amide group, representing small changes in the fentanyl core structure. Identification of these analogs through differences in the EC-SERS spectra was evident. Interference studies incorporating analytes frequently encountered with fentanyl including heroin, cocaine, methamphetamine, naltrexone, and naloxone were assessed and found to offer limited to no interference. The limits of detection of the fentanyl compounds were in the low to mid nanograms per milliliter range, with the most sensitive compound detected at 10 ng/ml. Application of the method to simulated drug mixtures was performed to determine fit-for-purpose. In all mixtures with fentanyl as the minor contributor, fentanyl was correctly identified, including mixture samples comprised of 5 and 1% fentanyl. This approach represents the first in-situ EC-SERS analysis of fentanyl and its analogs and provides accurate and efficient screening for fentanyl in seized drug samples.
{"title":"Forensic Identification of Fentanyl and its Analogs by Electrochemical-Surface Enhanced Raman Spectroscopy (EC-SERS) for the Screening of Seized Drugs of Abuse","authors":"C. Ott, M. Perez-Estebañez, Sheila Hernandez, Kendra Kelly, Kourtney A. Dalzell, M. J. Arcos-Martínez, A. Heras, Á. Colina, Luis E. Arroyo","doi":"10.3389/frans.2022.834820","DOIUrl":"https://doi.org/10.3389/frans.2022.834820","url":null,"abstract":"Reliable identification of fentanyl and fentanyl analogs present in seized drug samples is imperative to the safety of first responders and laboratory personnel and informs the future analysis process and handling procedures. The electrochemical-surface enhanced Raman spectroscopy (EC-SERS) method developed in this work allows the in-situ preparation of the SERS substrate providing a rapid, efficient, and accurate approach to detect fentanyl, even at low percent by weight concentrations common in seized drugs. Optimization of the electrochemical potentials suitable for the SERS substrate preparation and adsorption of the analyte was achieved using multi-pulse amperometric detection. This method demonstrated large enhancement of the SERS response. This method was applied to six fentanyl analogs with substitutions to the amide group, representing small changes in the fentanyl core structure. Identification of these analogs through differences in the EC-SERS spectra was evident. Interference studies incorporating analytes frequently encountered with fentanyl including heroin, cocaine, methamphetamine, naltrexone, and naloxone were assessed and found to offer limited to no interference. The limits of detection of the fentanyl compounds were in the low to mid nanograms per milliliter range, with the most sensitive compound detected at 10 ng/ml. Application of the method to simulated drug mixtures was performed to determine fit-for-purpose. In all mixtures with fentanyl as the minor contributor, fentanyl was correctly identified, including mixture samples comprised of 5 and 1% fentanyl. This approach represents the first in-situ EC-SERS analysis of fentanyl and its analogs and provides accurate and efficient screening for fentanyl in seized drug samples.","PeriodicalId":73063,"journal":{"name":"Frontiers in analytical science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47087904","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}
Medical tests are playing an increasingly important role in the diagnosis and treatment of diseases. Urine tests, blood tests and stool tests together constitute the three major routine examination items of modern medicine and are an important part of medical tests. Urine is a body fluid normally metabolized by the human body. Compared with using blood as a test sample, using urine as a medical test sample has many advantages, such as non-invasiveness and convenient collection. This article discusses the advantages of urine test compared with blood test, the understanding and application of urine in traditional medicine, the application of urine test in social life, the current dilemma and the future urine test may play a greater role The value and advantages are discussed, aiming to increase people’s attention to urine testing by explaining the advantages of urine testing, and to discover more functions of urine testing, thereby optimizing medical testing methods and reducing the pain and fear of patients. Improve inspection efficiency, reduce national and personal medical inspection expenditures, and save medical resources.
{"title":"Urine Analysis has a Very Broad Prospect in the Future","authors":"Zijuan Zhang, Jingnan Liu, Yaxing Chen, Jian Chen, Huihui Zhao, Xiaoqiao Ren","doi":"10.3389/frans.2021.812301","DOIUrl":"https://doi.org/10.3389/frans.2021.812301","url":null,"abstract":"Medical tests are playing an increasingly important role in the diagnosis and treatment of diseases. Urine tests, blood tests and stool tests together constitute the three major routine examination items of modern medicine and are an important part of medical tests. Urine is a body fluid normally metabolized by the human body. Compared with using blood as a test sample, using urine as a medical test sample has many advantages, such as non-invasiveness and convenient collection. This article discusses the advantages of urine test compared with blood test, the understanding and application of urine in traditional medicine, the application of urine test in social life, the current dilemma and the future urine test may play a greater role The value and advantages are discussed, aiming to increase people’s attention to urine testing by explaining the advantages of urine testing, and to discover more functions of urine testing, thereby optimizing medical testing methods and reducing the pain and fear of patients. Improve inspection efficiency, reduce national and personal medical inspection expenditures, and save medical resources.","PeriodicalId":73063,"journal":{"name":"Frontiers in analytical science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45627693","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 : 2022-01-14DOI: 10.3389/frans.2021.772844
Rodrigo Rocha de Oliveira, A. de Juan
Synchronization of variable trajectories from batch process data is a delicate operation that can induce artifacts in the definition of multivariate statistical process control (MSPC) models for real-time monitoring of batch processes. The current paper introduces a new synchronization-free approach for online batch MSPC. This approach is based on the use of local MSPC models that cover a normal operating conditions (NOC) trajectory defined from principal component analysis (PCA) modeling of non-synchronized historical batches. The rationale behind is that, although non-synchronized NOC batches are used, an overall NOC trajectory with a consistent evolution pattern can be described, even if batch-to-batch natural delays and differences between process starting and end points exist. Afterwards, the local MSPC models are used to monitor the evolution of new batches and derive the related MSPC chart. During the real-time monitoring of a new batch, this strategy allows testing whether every new observation is following or not the NOC trajectory. For a NOC observation, an additional indication of the batch process progress is provided based on the identification of the local MSPC model that provides the lowest residuals. When an observation deviates from the NOC behavior, contribution plots based on the projection of the observation to the best local MSPC model identified in the last NOC observation are used to diagnose the variables related to the fault. This methodology is illustrated using two real examples of NIR-monitored batch processes: a fluidized bed drying process and a batch distillation of gasoline blends with ethanol.
{"title":"Synchronization-Free Multivariate Statistical Process Control for Online Monitoring of Batch Process Evolution","authors":"Rodrigo Rocha de Oliveira, A. de Juan","doi":"10.3389/frans.2021.772844","DOIUrl":"https://doi.org/10.3389/frans.2021.772844","url":null,"abstract":"Synchronization of variable trajectories from batch process data is a delicate operation that can induce artifacts in the definition of multivariate statistical process control (MSPC) models for real-time monitoring of batch processes. The current paper introduces a new synchronization-free approach for online batch MSPC. This approach is based on the use of local MSPC models that cover a normal operating conditions (NOC) trajectory defined from principal component analysis (PCA) modeling of non-synchronized historical batches. The rationale behind is that, although non-synchronized NOC batches are used, an overall NOC trajectory with a consistent evolution pattern can be described, even if batch-to-batch natural delays and differences between process starting and end points exist. Afterwards, the local MSPC models are used to monitor the evolution of new batches and derive the related MSPC chart. During the real-time monitoring of a new batch, this strategy allows testing whether every new observation is following or not the NOC trajectory. For a NOC observation, an additional indication of the batch process progress is provided based on the identification of the local MSPC model that provides the lowest residuals. When an observation deviates from the NOC behavior, contribution plots based on the projection of the observation to the best local MSPC model identified in the last NOC observation are used to diagnose the variables related to the fault. This methodology is illustrated using two real examples of NIR-monitored batch processes: a fluidized bed drying process and a batch distillation of gasoline blends with ethanol.","PeriodicalId":73063,"journal":{"name":"Frontiers in analytical science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-01-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48685602","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 : 2022-01-03DOI: 10.3389/frans.2021.785271
Kirsten Nettles, C. Ford, Paola A Prada-Tiedemann
The early detection and location of firearm threats is critical to the success of any law enforcement operation to prevent a mass shooting event or illegal transport of weapons. Prevention tactics such as firearm detection canines have been at the front line of security tools to combat this national security threat. Firearm detection canines go through rigorous training regimens to achieve reliability in the detection of firearms as their target odor source. Currently, there is no scientific foundation as to the chemical odor signature emitted from the actual firearm device that could aid in increased and more efficient canine training and performance protocols or a better understanding of the chemistry of firearm-related odorants for better source identification. This study provides a novel method application of solid phase microextraction-gas chromatography-mass spectrometry (SPME-GC-MS) as a rapid system for the evaluation of odor profiles from firearm devices (loaded and unloaded). Samples included magazines (n = 30) and firearms (n = 15) acquired from the local law enforcement shooting range. Headspace analysis depicted five frequently occurring compounds across sample matrices including aldehydes such as nonanal, decanal, octanal and hydrocarbons tetradecane and tridecane. Statistical analysis via principal component analysis (PCA) highlighted a preliminary clustering differentiating unloaded firearms from both loaded/unloaded magazines and loaded firearm devices. These results highlight potential odor signature differences associated with different firearm components. The understanding of key odorants above a firearm will have an impact on national security efforts, thereby enhancing training regimens to better prepare canine teams for current threats in our communities.
{"title":"Development of Profiling Methods for Contraband Firearm Volatile Odor Signatures","authors":"Kirsten Nettles, C. Ford, Paola A Prada-Tiedemann","doi":"10.3389/frans.2021.785271","DOIUrl":"https://doi.org/10.3389/frans.2021.785271","url":null,"abstract":"The early detection and location of firearm threats is critical to the success of any law enforcement operation to prevent a mass shooting event or illegal transport of weapons. Prevention tactics such as firearm detection canines have been at the front line of security tools to combat this national security threat. Firearm detection canines go through rigorous training regimens to achieve reliability in the detection of firearms as their target odor source. Currently, there is no scientific foundation as to the chemical odor signature emitted from the actual firearm device that could aid in increased and more efficient canine training and performance protocols or a better understanding of the chemistry of firearm-related odorants for better source identification. This study provides a novel method application of solid phase microextraction-gas chromatography-mass spectrometry (SPME-GC-MS) as a rapid system for the evaluation of odor profiles from firearm devices (loaded and unloaded). Samples included magazines (n = 30) and firearms (n = 15) acquired from the local law enforcement shooting range. Headspace analysis depicted five frequently occurring compounds across sample matrices including aldehydes such as nonanal, decanal, octanal and hydrocarbons tetradecane and tridecane. Statistical analysis via principal component analysis (PCA) highlighted a preliminary clustering differentiating unloaded firearms from both loaded/unloaded magazines and loaded firearm devices. These results highlight potential odor signature differences associated with different firearm components. The understanding of key odorants above a firearm will have an impact on national security efforts, thereby enhancing training regimens to better prepare canine teams for current threats in our communities.","PeriodicalId":73063,"journal":{"name":"Frontiers in analytical science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45648563","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 : 2022-01-01Epub Date: 2023-01-06DOI: 10.3389/frans.2022.1091206
Haley A Mulder, Justin L Poklis, Adam C Pearcy, Matthew S Halquist
Tobacco specific nitrosamines (TSNAs) are highly carcinogenic by-products in tobacco samples, and their presence is regulated by the Food and Drug Administration. Molecularly imprinted polymers (MIPs) are synthetic polymers that have been "imprinted" with a template analyte in a co-polymer system, and can selectively extract analytes from complex matrices. MIPs can be incorporated into online systems, replacing traditional high performance liquid chromatography (HPLC) columns. MIP material specific for TSNAs was packed into an empty HPLC column using a slurry packing technique. The developed method with the MIP-packed HPLC column was validated on a LC-MS/MS system for the quantitation of N-nitrosonornicotine (NNN) and 4- (methylnitrosamino)-1-(3-pyridyl)-1-butanone (NNK) in commercial tobacco products. The method was linear over .1-10 ng/ml (.4-10 μg/g) for NNN and NNK. The limit of detection (LOD) was .03 ng/ml (12 μg/g) and the limit of quantitation (LOQ), .1 ng/ml (.4 μg/g). All column uniformity parameters with the exception of theoretical plate number were within the accepted criteria (% RSD values <15%). Theoretical plate number was <250, owing to the large (50 μm) sized MIP particles. Twenty-six tobacco products contained TSNA concentrations that were consistent with reported literature values. The TSNA-MIP based HPLC column effectively replaced a traditional reverse phase HPLC column, and was used for the direct analysis of nicotine and tobacco products without extensive sample preparation prior to instrumental analysis.
{"title":"Direct analysis of tobacco specific nitrosamines in tobacco products using a molecularly imprinted polymer-packed column.","authors":"Haley A Mulder, Justin L Poklis, Adam C Pearcy, Matthew S Halquist","doi":"10.3389/frans.2022.1091206","DOIUrl":"10.3389/frans.2022.1091206","url":null,"abstract":"<p><p>Tobacco specific nitrosamines (TSNAs) are highly carcinogenic by-products in tobacco samples, and their presence is regulated by the Food and Drug Administration. Molecularly imprinted polymers (MIPs) are synthetic polymers that have been \"imprinted\" with a template analyte in a co-polymer system, and can selectively extract analytes from complex matrices. MIPs can be incorporated into online systems, replacing traditional high performance liquid chromatography (HPLC) columns. MIP material specific for TSNAs was packed into an empty HPLC column using a slurry packing technique. The developed method with the MIP-packed HPLC column was validated on a LC-MS/MS system for the quantitation of N-nitrosonornicotine (NNN) and 4- (methylnitrosamino)-1-(3-pyridyl)-1-butanone (NNK) in commercial tobacco products. The method was linear over .1-10 ng/ml (.4-10 μg/g) for NNN and NNK. The limit of detection (LOD) was .03 ng/ml (12 μg/g) and the limit of quantitation (LOQ), .1 ng/ml (.4 μg/g). All column uniformity parameters with the exception of theoretical plate number were within the accepted criteria (% RSD values <15%). Theoretical plate number was <250, owing to the large (50 μm) sized MIP particles. Twenty-six tobacco products contained TSNA concentrations that were consistent with reported literature values. The TSNA-MIP based HPLC column effectively replaced a traditional reverse phase HPLC column, and was used for the direct analysis of nicotine and tobacco products without extensive sample preparation prior to instrumental analysis.</p>","PeriodicalId":73063,"journal":{"name":"Frontiers in analytical science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10540244/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41160603","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：