Pub Date : 2024-09-02DOI: 10.1016/j.microc.2024.111546
Zhilong Chen, Yan Guo, Xinyue Gu, Xinyu Liu, Jingjing Zhang, Chunyuan Song, Lianhui Wang
Interstitial fluid (ISF) is a prevalent accessible and information-rich biofluid, and monitoring pH level of interstitial fluid plays a crucial role in the physiological health assessment. However, facile extraction of ISF and sensitive detection of pH is still a great challenge. Herein, a flexible plasmonic microneedle array (PMNA)-based SERS sensor was developed for facile and sensitive pH monitoring of skin ISF. The flexible microneedle arrays were fabricated by norland optical adhesive 65 (NOA65), and coated with pH-sensitive 4-Mercaptobenzoic acid (4-MBA)-labeled silver nanoparticles (Ag NPs) by electrostatic assembly. The proposed flexible PMNA-based SERS sensor has a good linear response in the pH range of 5 to 9 which covers the normal pH level in skin interstitial fluid. The ISF extracted from porcine skin was chosen as the test model, and the pH levels detected by the PMNA-based SERS sensors were well consistent with the theoretical results. Besides, the proposed flexible SERS sensors show good mechanical robustness, sensing stability, and biocompatibility before and after skin insertion, which can be a potential analytical tool for practical detection of pH levels in ISF and provide technical support for SERS-based wearable biosensing.
{"title":"Flexible plasmonic microneedle array-based SERS sensor for pH monitoring of skin interstitial fluid","authors":"Zhilong Chen, Yan Guo, Xinyue Gu, Xinyu Liu, Jingjing Zhang, Chunyuan Song, Lianhui Wang","doi":"10.1016/j.microc.2024.111546","DOIUrl":"https://doi.org/10.1016/j.microc.2024.111546","url":null,"abstract":"Interstitial fluid (ISF) is a prevalent accessible and information-rich biofluid, and monitoring pH level of interstitial fluid plays a crucial role in the physiological health assessment. However, facile extraction of ISF and sensitive detection of pH is still a great challenge. Herein, a flexible plasmonic microneedle array (PMNA)-based SERS sensor was developed for facile and sensitive pH monitoring of skin ISF. The flexible microneedle arrays were fabricated by norland optical adhesive 65 (NOA65), and coated with pH-sensitive 4-Mercaptobenzoic acid (4-MBA)-labeled silver nanoparticles (Ag NPs) by electrostatic assembly. The proposed flexible PMNA-based SERS sensor has a good linear response in the pH range of 5 to 9 which covers the normal pH level in skin interstitial fluid. The ISF extracted from porcine skin was chosen as the test model, and the pH levels detected by the PMNA-based SERS sensors were well consistent with the theoretical results. Besides, the proposed flexible SERS sensors show good mechanical robustness, sensing stability, and biocompatibility before and after skin insertion, which can be a potential analytical tool for practical detection of pH levels in ISF and provide technical support for SERS-based wearable biosensing.","PeriodicalId":391,"journal":{"name":"Microchemical Journal","volume":null,"pages":null},"PeriodicalIF":4.8,"publicationDate":"2024-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142212310","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-02DOI: 10.1016/j.microc.2024.111538
Agustami Sitorus, Ravipat Lapcharoensuk
This work proposes exploring the discrimination model by near-infrared (NIR) spectroscopy (FT-NIR and Micro-NIR) for geographical source areas of coconut milk in tandem with the classical to modern chemometrics classifier. The discrimination model was developed using qualitative chemometrics techniques from classic (Principal Component Analysis-PCA, Partial Least Squares Discriminant Analysis-PLS-DA, Linear Discriminant Analysis-LDA) to modern, including classifiers from machine learning (Support Vector Machine-SVM, k-Nearest Neighbor-KNN, Artificial Neural Network-ANN) and deep learning (Simple Convolutional Neural Networks-S-CNN, S-AlexNET, Residual Networks-ResNET). Three sources as geographical areas of coconut milk originally from Thailand were used, including the south region (Chumphon Province), middle region (Samut Songkhram Province), and east region (Chonburi Province). Our findings showed that a classifier from SVM and ResNET could yield the optimal performance for discriminating the geographical source area of coconut milk using FT-NIR. Furthermore, when using Micro-NIR, the classifier from LDA, SVM, KNN and ResNET delivered the highest accuracy. The performance discrimination models above were excellent when classified based on the kappa coefficient. This study concluded that both FT-NIR and Micro-NIR supported by classical to modern chemometric classifiers could be used to evaluate the geographical area source from coconut milk. Also, the method in this study includes a strategy for discovering feature-important NIR spectra for interpretability purposes, thereby facilitating the qualitative interpretation of results for all types of classifiers.
{"title":"Discrimination model of geographical area from coconut milk by near-infrared spectroscopy: Exploration in tandem with classical chemometrics, machine learning, and deep learning","authors":"Agustami Sitorus, Ravipat Lapcharoensuk","doi":"10.1016/j.microc.2024.111538","DOIUrl":"https://doi.org/10.1016/j.microc.2024.111538","url":null,"abstract":"This work proposes exploring the discrimination model by near-infrared (NIR) spectroscopy (FT-NIR and Micro-NIR) for geographical source areas of coconut milk in tandem with the classical to modern chemometrics classifier. The discrimination model was developed using qualitative chemometrics techniques from classic (Principal Component Analysis-PCA, Partial Least Squares Discriminant Analysis-PLS-DA, Linear Discriminant Analysis-LDA) to modern, including classifiers from machine learning (Support Vector Machine-SVM, k-Nearest Neighbor-KNN, Artificial Neural Network-ANN) and deep learning (Simple Convolutional Neural Networks-S-CNN, S-AlexNET, Residual Networks-ResNET). Three sources as geographical areas of coconut milk originally from Thailand were used, including the south region (Chumphon Province), middle region (Samut Songkhram Province), and east region (Chonburi Province). Our findings showed that a classifier from SVM and ResNET could yield the optimal performance for discriminating the geographical source area of coconut milk using FT-NIR. Furthermore, when using Micro-NIR, the classifier from LDA, SVM, KNN and ResNET delivered the highest accuracy. The performance discrimination models above were excellent when classified based on the kappa coefficient. This study concluded that both FT-NIR and Micro-NIR supported by classical to modern chemometric classifiers could be used to evaluate the geographical area source from coconut milk. Also, the method in this study includes a strategy for discovering feature-important NIR spectra for interpretability purposes, thereby facilitating the qualitative interpretation of results for all types of classifiers.","PeriodicalId":391,"journal":{"name":"Microchemical Journal","volume":null,"pages":null},"PeriodicalIF":4.8,"publicationDate":"2024-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142212309","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-01DOI: 10.1016/j.microc.2024.111552
Glykeria N. Tsompanopoulou, Abuzar Kabir, Kenneth G. Furton, Natasa P. Kalogiouri, Victoria F. Samanidou
In the present study magnet integrated fabric phase sorptive extraction (MI-FPSE) was employed for the selective extraction of seven sulfonamides (i.e., sulfamerazine, sulfamethazine, sulfamethoxypyridazine, sulfamonomethoxine, sulfamethoxazole, sulfisoxazole and sulfadimethoxine) from human urine prior to their determination by high pressure liquid chromatography – diode array detection (HPLC-DAD). The MI-FPSE protocol was optimized after studying the critical parameters that affect extraction, namely: type of sol–gel sorbent, extraction time, desorption time, stirring rate, type and volume of elution solvent, the ionic strength and the pH of the sample matrix using the one-factor-at-a-time method. The developed MI-FPSE-HPLC-DAD method was validated in terms of linearity, sensitivity, selectivity, accuracy, and precision and presented satisfactory results. The limits of detection (LODs) and quantification (LOQs) ranged between 0.02–0.04 ng/μL and 0.06–0.15 ng/μL, respectively. The RSD% values of the intra-day and inter-day assays were found lower than 6.7 % and 9.4 %, respectively, showing good precision. Accuracy was assessed using percentage of relative recovery and varied from 86.3–112.9 % (intra-day study) and 85.5–106.9 % (inter-day study) for all examined analytes. The green character and practicality of the proposed method were investigated using the ComplexGAPI index and Blue Applicability Grade Index (BAGI).
{"title":"Μagnet integrated fabric phase sorptive extraction (MI-FPSE) for the selective isolation of seven sulfonamides from human urine prior to HPLC-DAD analysis","authors":"Glykeria N. Tsompanopoulou, Abuzar Kabir, Kenneth G. Furton, Natasa P. Kalogiouri, Victoria F. Samanidou","doi":"10.1016/j.microc.2024.111552","DOIUrl":"https://doi.org/10.1016/j.microc.2024.111552","url":null,"abstract":"In the present study magnet integrated fabric phase sorptive extraction (MI-FPSE) was employed for the selective extraction of seven sulfonamides (i.e., sulfamerazine, sulfamethazine, sulfamethoxypyridazine, sulfamonomethoxine, sulfamethoxazole, sulfisoxazole and sulfadimethoxine) from human urine prior to their determination by high pressure liquid chromatography – diode array detection (HPLC-DAD). The MI-FPSE protocol was optimized after studying the critical parameters that affect extraction, namely: type of sol–gel sorbent, extraction time, desorption time, stirring rate, type and volume of elution solvent, the ionic strength and the pH of the sample matrix using the one-factor-at-a-time method. The developed MI-FPSE-HPLC-DAD method was validated in terms of linearity, sensitivity, selectivity, accuracy, and precision and presented satisfactory results. The limits of detection (LODs) and quantification (LOQs) ranged between 0.02–0.04 ng/μL and 0.06–0.15 ng/μL, respectively. The RSD% values of the intra-day and inter-day assays were found lower than 6.7 % and 9.4 %, respectively, showing good precision. Accuracy was assessed using percentage of relative recovery and varied from 86.3–112.9 % (intra-day study) and 85.5–106.9 % (inter-day study) for all examined analytes. The green character and practicality of the proposed method were investigated using the ComplexGAPI index and Blue Applicability Grade Index (BAGI).","PeriodicalId":391,"journal":{"name":"Microchemical Journal","volume":null,"pages":null},"PeriodicalIF":4.8,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142226859","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-01DOI: 10.1016/j.microc.2024.111551
Yu Liu, Yawen Liu, Fangfang Wang, Zhigang Zhang, Haiming Hu, Lei Xiong, Junping Zheng, Hongtao Liu
The conventional ELISA lacked sufficient sensitivity and accuracy for analyzing neutrophil gelatinase associated lipocalin (NGAL), a potential biomarker of ulcerative colitis. Here, we developed a dual-readout plasmonic ELISA with cascade amplification of alkaline phosphatase hydrolysis and O-phenylenediamine oxidation. In this novel plasmonic ELISA, alkaline phosphatase-conjugated antibodies capture NGAL from samples, alkaline phosphatase hydrolyzes 2-phospho-L-ascorbic acid into ascorbic acid, and then ascorbic acid blocks silver-catalyzed O-phenylenediamine oxidation by turning silver ions into silver microwires. Therefore, NGAL concentration is proportional to the decrease in chromogenic and fluorescent response. This novel plasmonic ELISA exhibited a linear range of 0.5–80 ng/mL, and the LOD was as low as 0.5 ng/mL. The sensitivity was superior to that of conventional ELISA and previous studies. The plasmonic ELISA exhibited favorable selectivity because of the specific antibody-antigen interaction and the robust cascade amplification. Besides, the dual-readout feature endowed the plasmonic ELISA with advantages in terms of convenience and compatibility. In summary, our study provided a novel and sensitive plasmonic ELISA for the diagnosis of ulcerative colitis.
{"title":"A silver auto-catalyzed plasmonic enzyme-linked immunosorbent assay for colorimetric and fluorescent detection of neutrophil gelatinase associated lipocalin (NGAL)","authors":"Yu Liu, Yawen Liu, Fangfang Wang, Zhigang Zhang, Haiming Hu, Lei Xiong, Junping Zheng, Hongtao Liu","doi":"10.1016/j.microc.2024.111551","DOIUrl":"https://doi.org/10.1016/j.microc.2024.111551","url":null,"abstract":"The conventional ELISA lacked sufficient sensitivity and accuracy for analyzing neutrophil gelatinase associated lipocalin (NGAL), a potential biomarker of ulcerative colitis. Here, we developed a dual-readout plasmonic ELISA with cascade amplification of alkaline phosphatase hydrolysis and O-phenylenediamine oxidation. In this novel plasmonic ELISA, alkaline phosphatase-conjugated antibodies capture NGAL from samples, alkaline phosphatase hydrolyzes 2-phospho-L-ascorbic acid into ascorbic acid, and then ascorbic acid blocks silver-catalyzed O-phenylenediamine oxidation by turning silver ions into silver microwires. Therefore, NGAL concentration is proportional to the decrease in chromogenic and fluorescent response. This novel plasmonic ELISA exhibited a linear range of 0.5–80 ng/mL, and the LOD was as low as 0.5 ng/mL. The sensitivity was superior to that of conventional ELISA and previous studies. The plasmonic ELISA exhibited favorable selectivity because of the specific antibody-antigen interaction and the robust cascade amplification. Besides, the dual-readout feature endowed the plasmonic ELISA with advantages in terms of convenience and compatibility. In summary, our study provided a novel and sensitive plasmonic ELISA for the diagnosis of ulcerative colitis.","PeriodicalId":391,"journal":{"name":"Microchemical Journal","volume":null,"pages":null},"PeriodicalIF":4.8,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142212332","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-01DOI: 10.1016/j.microc.2024.111540
Lingzi Zhong, Haiyi Niu, Yanfei Lin, Tianqing Ye, Shiyan Zheng, Kan Chen, Lei Li, Longhua Guo, Jianbo Wang
Viscosity and peroxynitrite (ONOO) are two crucial elements that influence the operational status of biological processes within living organisms. Their abnormal changes cause metabolic disorders and even diseases. Therefore, it is important to develop a near-infrared (NIR) probe with aggregation-induced emission (AIE) feature that is capable of dual channel detection of both viscosity and ONOO. Here, a new NIR fluorescent probe with large Stokes shift was synthesized in which triphenylamine was conjugated to a pyridinium phenylborate salt. Probe with the distorted intramolecular twisted intramolecular charge transfer (TICT) properties is sensitive to systemic viscosity and exhibits enhanced fluorescence emission with peak at the 704 nm. On the other hand, the probe is also susceptible to peroxynitrite-triggered borate oxidation, providing an AIE fluorescence-enhanced response at the 639 nm peak. Moreover, with excellent photochemical stability, lower cytotoxicity and a precise targeting ability for mitochondria, probe was used to visualize imaging changes in endogenous and exogenous cellular viscosity and peroxynitrite. The imaging results of the probe during ferroptosis confirmed that both the intracellular viscosity microenvironment and peroxynitrite were further overexpressed. Finally, in vivo imaging experiments showed that the occurrence of inflammation was accompanied by an increase in the viscosity and the release in peroxynitrite.
{"title":"Near-infrared multi-functional aggregation-induced emission fluorescent probe for detection of viscosity and peroxynitrite and its imaging application","authors":"Lingzi Zhong, Haiyi Niu, Yanfei Lin, Tianqing Ye, Shiyan Zheng, Kan Chen, Lei Li, Longhua Guo, Jianbo Wang","doi":"10.1016/j.microc.2024.111540","DOIUrl":"https://doi.org/10.1016/j.microc.2024.111540","url":null,"abstract":"Viscosity and peroxynitrite (ONOO) are two crucial elements that influence the operational status of biological processes within living organisms. Their abnormal changes cause metabolic disorders and even diseases. Therefore, it is important to develop a near-infrared (NIR) probe with aggregation-induced emission (AIE) feature that is capable of dual channel detection of both viscosity and ONOO. Here, a new NIR fluorescent probe with large Stokes shift was synthesized in which triphenylamine was conjugated to a pyridinium phenylborate salt. Probe with the distorted intramolecular twisted intramolecular charge transfer (TICT) properties is sensitive to systemic viscosity and exhibits enhanced fluorescence emission with peak at the 704 nm. On the other hand, the probe is also susceptible to peroxynitrite-triggered borate oxidation, providing an AIE fluorescence-enhanced response at the 639 nm peak. Moreover, with excellent photochemical stability, lower cytotoxicity and a precise targeting ability for mitochondria, probe was used to visualize imaging changes in endogenous and exogenous cellular viscosity and peroxynitrite. The imaging results of the probe during ferroptosis confirmed that both the intracellular viscosity microenvironment and peroxynitrite were further overexpressed. Finally, in vivo imaging experiments showed that the occurrence of inflammation was accompanied by an increase in the viscosity and the release in peroxynitrite.","PeriodicalId":391,"journal":{"name":"Microchemical Journal","volume":null,"pages":null},"PeriodicalIF":4.8,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142212331","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this work, quasi-hydrophobic deep eutectic solvents were used for the first time for the efficient extraction of both polar (Sunset Yellow FCF (E 110), Azorubine (E122), Ponceau 4R (E124)) and non-polar (Sudan I, Sudan II, Sudan III) dyes from food products at the same time. These solvents were made from polar and nonpolar components, which made it possible to extract analytes of various natures. To automate the technique, a flow analysis method was used, which increases the speed and reliability of determining analytes in food samples. For a detailed study of extraction mechanisms, various process modeling methods were used. The proposed DES-based method addresses the limitations of traditional extraction methods, offering a more robust and efficient solution for food analysis. Validation of the method has demonstrated high precision, accuracy and extraction efficiency, making it a promising tool for regulatory compliance and consumer safety in the food industry. The following analytical characteristics were achieved: the limits of detection were 0.03–0.13 mg L, limits of quantification were 0.09–0.44 mg L, an extraction recovery exceeding 85 %, a linear range was from 1 to 100 mg L, and a relative standard deviation ranging from 2 % to 10 %. The experiments were confirmed by both Conductor Like Screening Model-Segment Activity Coefficient (COSMO-SAC) and the Non-Covalent Interaction using the Reduced Density Gradient of the DES-dye system in aqueous media.
在这项工作中，我们首次使用了准疏水性深共晶溶剂来同时高效萃取食品中的极性染料（日落黄 FCF (E 110)、偶氮染料 (E122)、胭脂红 4R (E124)）和非极性染料（苏丹一号、苏丹二号、苏丹三号）。这些溶剂由极性和非极性成分制成，因此可以提取各种性质的分析物。为了使这项技术自动化，使用了流动分析方法，从而提高了测定食品样品中分析物的速度和可靠性。为了详细研究萃取机制，使用了各种过程建模方法。所提出的基于 DES 的方法解决了传统萃取方法的局限性，为食品分析提供了一种更稳健、更高效的解决方案。该方法的验证结果表明，其精确度、准确度和萃取效率都很高，是食品行业中符合法规要求和保障消费者安全的一种很有前途的工具。该方法具有以下分析特性：检出限为 0.03-0.13 毫克/升，定量限为 0.09-0.44 毫克/升，萃取回收率超过 85%，线性范围为 1-100 毫克/升，相对标准偏差为 2%-10%。实验结果得到了COSMO-SAC（Conductor Like Screening Model-Segment Activity Coefficient）和水介质中DES-染料体系的还原密度梯度非共价相互作用的证实。
{"title":"Quasi-hydrophobic deep eutectic solvents for simultaneous automated determination of polar and non-polar dyes in food products","authors":"Rifat Muradymov, Nabendu Paul, Nipu Kumar Das, Tamal Banerjee, Andrey Shishov","doi":"10.1016/j.microc.2024.111510","DOIUrl":"https://doi.org/10.1016/j.microc.2024.111510","url":null,"abstract":"In this work, quasi-hydrophobic deep eutectic solvents were used for the first time for the efficient extraction of both polar (Sunset Yellow FCF (E 110), Azorubine (E122), Ponceau 4R (E124)) and non-polar (Sudan I, Sudan II, Sudan III) dyes from food products at the same time. These solvents were made from polar and nonpolar components, which made it possible to extract analytes of various natures. To automate the technique, a flow analysis method was used, which increases the speed and reliability of determining analytes in food samples. For a detailed study of extraction mechanisms, various process modeling methods were used. The proposed DES-based method addresses the limitations of traditional extraction methods, offering a more robust and efficient solution for food analysis. Validation of the method has demonstrated high precision, accuracy and extraction efficiency, making it a promising tool for regulatory compliance and consumer safety in the food industry. The following analytical characteristics were achieved: the limits of detection were 0.03–0.13 mg L, limits of quantification were 0.09–0.44 mg L, an extraction recovery exceeding 85 %, a linear range was from 1 to 100 mg L, and a relative standard deviation ranging from 2 % to 10 %. The experiments were confirmed by both Conductor Like Screening Model-Segment Activity Coefficient (COSMO-SAC) and the Non-Covalent Interaction using the Reduced Density Gradient of the DES-dye system in aqueous media.","PeriodicalId":391,"journal":{"name":"Microchemical Journal","volume":null,"pages":null},"PeriodicalIF":4.8,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142226835","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The development of a real-time online system for rapid and non-destructive identification of seed varieties can significantly improve production efficiency in modern agriculture. Near-infrared spectroscopy technology has become one of the commonly used techniques in seed variety identification due to its fast and non-destructive characteristics. However, existing convolutional neural networks are difficult to reflect the complex nonlinear relationships of the near-infrared (NIR) spectrum, resulting in poor modeling performance, and their high model complexity is not conducive to real-time online identification tasks. Therefore, this study proposes a maize seed variety identification method using near-infrared spectroscopy technology and lightweight deep learning network (BAC-DenseNet). First, a total of 750 samples from 5 different types of maize seeds were taken as the research object. The spectral data were pre-processing using the SGD-SNV, and the identification accuracy was improved by an average of 15.78 %. Then, the attraction–repulsion optimization algorithm combined with Laplacian Eigenmaps (AROA-LE) was used to perform dimension reduction on the pre-processed data, and the dimensionality was reduced from 1845 to 66. Finally, a lightweight deep learning network model (BAC-DenseNet) was constructed based on DenseNet-121 network with layer pruning and the introduction of batch channel normalization (BCN), self-attention and convolution mixed module (ACmix) and convolutional block attention module (CBAM). The experimental results show that the proposed BAC-DenseNet model has an identification accuracy of 99.33 %. Compared with the original network and seven other classical deep learning models, the proposed method has an average improvement of 2.83 %, 3.52 %, and 3.47 % in accuracy, Kappa, and MCC, respectively. Meanwhile, Params, Size, and FLOPs decreased by an average of 9.09 M, 35.08 MB, and 88.66 M, respectively. This method offered high accuracy and reliability in maize seed variety identification, which can provide qualitative indicators for the breeding, planting, and management of maize seed varieties. This study can provide a reference method for variety identification of other agricultural products.
{"title":"A method of maize seed variety identification based on near-infrared spectroscopy combined with improved DenseNet model","authors":"Haichao Zhou, Haiou Guan, Xiaodan Ma, Bingxue Wei, Yifei Zhang, Yuxin Lu","doi":"10.1016/j.microc.2024.111542","DOIUrl":"https://doi.org/10.1016/j.microc.2024.111542","url":null,"abstract":"The development of a real-time online system for rapid and non-destructive identification of seed varieties can significantly improve production efficiency in modern agriculture. Near-infrared spectroscopy technology has become one of the commonly used techniques in seed variety identification due to its fast and non-destructive characteristics. However, existing convolutional neural networks are difficult to reflect the complex nonlinear relationships of the near-infrared (NIR) spectrum, resulting in poor modeling performance, and their high model complexity is not conducive to real-time online identification tasks. Therefore, this study proposes a maize seed variety identification method using near-infrared spectroscopy technology and lightweight deep learning network (BAC-DenseNet). First, a total of 750 samples from 5 different types of maize seeds were taken as the research object. The spectral data were pre-processing using the SGD-SNV, and the identification accuracy was improved by an average of 15.78 %. Then, the attraction–repulsion optimization algorithm combined with Laplacian Eigenmaps (AROA-LE) was used to perform dimension reduction on the pre-processed data, and the dimensionality was reduced from 1845 to 66. Finally, a lightweight deep learning network model (BAC-DenseNet) was constructed based on DenseNet-121 network with layer pruning and the introduction of batch channel normalization (BCN), self-attention and convolution mixed module (ACmix) and convolutional block attention module (CBAM). The experimental results show that the proposed BAC-DenseNet model has an identification accuracy of 99.33 %. Compared with the original network and seven other classical deep learning models, the proposed method has an average improvement of 2.83 %, 3.52 %, and 3.47 % in accuracy, Kappa, and MCC, respectively. Meanwhile, Params, Size, and FLOPs decreased by an average of 9.09 M, 35.08 MB, and 88.66 M, respectively. This method offered high accuracy and reliability in maize seed variety identification, which can provide qualitative indicators for the breeding, planting, and management of maize seed varieties. This study can provide a reference method for variety identification of other agricultural products.","PeriodicalId":391,"journal":{"name":"Microchemical Journal","volume":null,"pages":null},"PeriodicalIF":4.8,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142212330","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-01DOI: 10.1016/j.microc.2024.111535
Belal Muneeb Kanaan, Ayman M. Algohary, Ahmed M. Ibrahim
Vonoprazan fumarate (VPZ), a potent potassium-competitive acid blocker, holds great promise as a therapeutic option for addressing acid-related disorders. This study introduces a refined reversed phase liquid chromatography methodology tailored for the comprehensive analysis of eight related substances, including starting materials, byproducts, and degradants within VPZ. Our approach integrates response surface methodology and tolerance analysis to achieve six sigma quality standards in chromatographic performance. By embedding specifications into the optimization process, we ensure robustness during method development. Chromatographic separation was executed using an XSelect CSH Phenyl-Hexyl column under stepped gradient conditions, employing a mobile phase comprising 0.1 % trifluoroacetic acid aqueous solution and acetonitrile. The flow rate was maintained at 1.3 mL/min, with UV absorbance at 252 nm, and a column temperature set at 25 °C. To evaluate the stability indicating ability of the method, forced degradation studies were conducted. Importantly, identified degradants did not interfere with the accurate quantification of VPZ and its associated impurities. Validation of the method was achieved through accuracy profiles. A greenness assessment was conducted using National Environmental Methods Index (NEMI), carbon footprint analysis, Analytical Greenness Calculator (AGREE), and Complementary Green Analytical Procedure Index (Complex GAPI). Additionally, blueness and whiteness assessments were conducted using the Blue Applicability Grade Index (BAGI) and Red-Green-Blue 12 (RGB 12) algorithms, respectively. The proposed method exhibited a green profile in NEMI and Complex GAPI. The carbon footprint was calculated at 0.055 kg CO equivalent per sample. The AGREE score was 0.67, BAGI was 80.0, and the whiteness score from the RGB12 algorithm was 83.5.This methodological framework holds promise for utilization in process development and quality assurance of VPZ in bulk drug manufacturing, particularly in the absence of official monographs within recognized compendia.
{"title":"Optimized reversed phase liquid chromatography methodology for the determination of vonoprazan fumarate impurities: Towards Six Sigma quality standards and sustainability assessment","authors":"Belal Muneeb Kanaan, Ayman M. Algohary, Ahmed M. Ibrahim","doi":"10.1016/j.microc.2024.111535","DOIUrl":"https://doi.org/10.1016/j.microc.2024.111535","url":null,"abstract":"Vonoprazan fumarate (VPZ), a potent potassium-competitive acid blocker, holds great promise as a therapeutic option for addressing acid-related disorders. This study introduces a refined reversed phase liquid chromatography methodology tailored for the comprehensive analysis of eight related substances, including starting materials, byproducts, and degradants within VPZ. Our approach integrates response surface methodology and tolerance analysis to achieve six sigma quality standards in chromatographic performance. By embedding specifications into the optimization process, we ensure robustness during method development. Chromatographic separation was executed using an XSelect CSH Phenyl-Hexyl column under stepped gradient conditions, employing a mobile phase comprising 0.1 % trifluoroacetic acid aqueous solution and acetonitrile. The flow rate was maintained at 1.3 mL/min, with UV absorbance at 252 nm, and a column temperature set at 25 °C. To evaluate the stability indicating ability of the method, forced degradation studies were conducted. Importantly, identified degradants did not interfere with the accurate quantification of VPZ and its associated impurities. Validation of the method was achieved through accuracy profiles. A greenness assessment was conducted using National Environmental Methods Index (NEMI), carbon footprint analysis, Analytical Greenness Calculator (AGREE), and Complementary Green Analytical Procedure Index (Complex GAPI). Additionally, blueness and whiteness assessments were conducted using the Blue Applicability Grade Index (BAGI) and Red-Green-Blue 12 (RGB 12) algorithms, respectively. The proposed method exhibited a green profile in NEMI and Complex GAPI. The carbon footprint was calculated at 0.055 kg CO equivalent per sample. The AGREE score was 0.67, BAGI was 80.0, and the whiteness score from the RGB12 algorithm was 83.5.This methodological framework holds promise for utilization in process development and quality assurance of VPZ in bulk drug manufacturing, particularly in the absence of official monographs within recognized compendia.","PeriodicalId":391,"journal":{"name":"Microchemical Journal","volume":null,"pages":null},"PeriodicalIF":4.8,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142212334","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-01DOI: 10.1016/j.microc.2024.111515
Linbo Zou, Xiaojun Liu, Lizhu Yang, Wen Yun
MicroRNA is taken as diagnostic tumor markers in clinical diagnosis of various cancers. However, the complexity system and low utilization rate of entropy-driven amplification reaction (EDAR) limit its application. In this work, a product catalysis dual EDAR amplification strategy is developed for miRNA-21 detection. This strategy allows miRNA-21 to simultaneously catalyze two EDARs, greatly increasing the limit of detection to 0.40 pM and enhancing amplification efficiency. The amplification efficiency was also significantly enhanced with a much shorter reaction time by increasing concentration of the catalyzer (EDAR product). The approach was successfully applied in clinical samples, showing potential for early screening and diagnosis.
{"title":"Product catalysis dual entropy-driven amplification reaction strategy for miRNA-21 detection in glioblastoma","authors":"Linbo Zou, Xiaojun Liu, Lizhu Yang, Wen Yun","doi":"10.1016/j.microc.2024.111515","DOIUrl":"https://doi.org/10.1016/j.microc.2024.111515","url":null,"abstract":"MicroRNA is taken as diagnostic tumor markers in clinical diagnosis of various cancers. However, the complexity system and low utilization rate of entropy-driven amplification reaction (EDAR) limit its application. In this work, a product catalysis dual EDAR amplification strategy is developed for miRNA-21 detection. This strategy allows miRNA-21 to simultaneously catalyze two EDARs, greatly increasing the limit of detection to 0.40 pM and enhancing amplification efficiency. The amplification efficiency was also significantly enhanced with a much shorter reaction time by increasing concentration of the catalyzer (EDAR product). The approach was successfully applied in clinical samples, showing potential for early screening and diagnosis.","PeriodicalId":391,"journal":{"name":"Microchemical Journal","volume":null,"pages":null},"PeriodicalIF":4.8,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142212333","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-08-31DOI: 10.1016/j.microc.2024.111536
Yao Wang, Gengping Pan, Chenfang Miao, Minge Xu, Menghan Zhang, Hai Zeng, Shaohuang Weng, Qifeng Zou
As an iron chelation therapy, deferasirox (DEF) is commonly used as the primary treatment drug to prevent intracellular iron overload in patients with thalassemia who require long-term and large blood transfusions. However, due to the toxic side effects of long-term use, building a convenient and sensitive DEF detection method remains an important task. This study developed a simple and effective fluorescence detection strategy for DEF based on the coordination effect of DEF and Cu (DEF-Cu). The high quantum yield N-doped blue emission carbon dots (CDs) synthesized by a simple one-step hydrothermal method were applied as the fluorescent probe. The DEF-Cu exhibited a new absorption peak centered at 334 nm, overlapping with the absorption wavelength of CDs, resulting in an internal filtration effect (IFE) for quenching the fluorescence of CDs. The quenching degrees of CDs caused by DEF-Cu showed a good linear relationship in the range of 0.5–20 μg/mL, with a detection limit (LOD) as low as 0.12 μg/mL. The accurate detections of DEF in dispersible tablets and plasma were also achieved. This strategy not only enriched the understanding of the properties of target drugs but also provided valuable insights for designing CDs with specific luminescent properties and applying them to distinctive methods for drug analysis.
地拉罗司（DEF）作为一种铁螯合疗法，常用于需要长期大量输血的地中海贫血症患者，是防止细胞内铁负荷过重的主要治疗药物。然而，由于长期使用的毒副作用，建立一种方便灵敏的地拉羅司检测方法仍是一项重要任务。本研究基于 DEF 和铜（DEF-Cu）的配位效应，开发了一种简单有效的 DEF 荧光检测策略。采用简单的一步水热法合成了高量子产率的 N 掺杂蓝色发射碳点（CD）作为荧光探针。DEF-Cu 在 334 纳米波长处出现了新的吸收峰，与 CD 的吸收波长重叠，从而产生了淬灭 CD 荧光的内滤效应（IFE）。DEF-Cu 对 CD 的淬灭度在 0.5-20 μg/mL 范围内呈良好的线性关系，检测限低至 0.12 μg/mL。此外，还实现了对分散片和血浆中 DEF 的准确检测。这一策略不仅丰富了对目标药物特性的理解，还为设计具有特定发光特性的 CD 并将其应用于独特的药物分析方法提供了宝贵的见解。
{"title":"Effective synthesis of fluorescent carbon dots and their application in controllable detection of deferasirox","authors":"Yao Wang, Gengping Pan, Chenfang Miao, Minge Xu, Menghan Zhang, Hai Zeng, Shaohuang Weng, Qifeng Zou","doi":"10.1016/j.microc.2024.111536","DOIUrl":"https://doi.org/10.1016/j.microc.2024.111536","url":null,"abstract":"As an iron chelation therapy, deferasirox (DEF) is commonly used as the primary treatment drug to prevent intracellular iron overload in patients with thalassemia who require long-term and large blood transfusions. However, due to the toxic side effects of long-term use, building a convenient and sensitive DEF detection method remains an important task. This study developed a simple and effective fluorescence detection strategy for DEF based on the coordination effect of DEF and Cu (DEF-Cu). The high quantum yield N-doped blue emission carbon dots (CDs) synthesized by a simple one-step hydrothermal method were applied as the fluorescent probe. The DEF-Cu exhibited a new absorption peak centered at 334 nm, overlapping with the absorption wavelength of CDs, resulting in an internal filtration effect (IFE) for quenching the fluorescence of CDs. The quenching degrees of CDs caused by DEF-Cu showed a good linear relationship in the range of 0.5–20 μg/mL, with a detection limit (LOD) as low as 0.12 μg/mL. The accurate detections of DEF in dispersible tablets and plasma were also achieved. This strategy not only enriched the understanding of the properties of target drugs but also provided valuable insights for designing CDs with specific luminescent properties and applying them to distinctive methods for drug analysis.","PeriodicalId":391,"journal":{"name":"Microchemical Journal","volume":null,"pages":null},"PeriodicalIF":4.8,"publicationDate":"2024-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142212335","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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