Pub Date : 2025-05-28DOI: 10.1016/j.vibspec.2025.103815
Larissa F. Torres , Marilia R. Oliveira , Thales C.S. Barbalho , Cláudio Dariva , Gustavo R. Borges , Papa M. Ndiaye , Frederico W. Tavares
The use of Near Infrared Spectroscopy (NIRS) has a significant potential to enable the detection and quantification of natural gas components (e.g., CH4, CO2, moisture). It offers a quick, non-invasive, and non-destructive approach, eliminating the challenges associated with traditional sampling methods. Here, we investigated the applicability of the NIR technique to perform accurate quantification of water content and compositional analysis regarding CH4 and CO2 in compressed systems. The system’s pressure is also considered a response variable. The spectra collection was made at room temperature (298.15 K), with pressures up to 120 bar and CO2 concentrations varying from 0 % to 50 % of the total composition. The Partial Least Squares (PLS) was used as the regression method, and the Quartz Crystal Microbalance (QCM) as the reference technique for water content. The PLS models yielded high accuracy, with R² values of 0.990 for CH₄, 0.993 for CO₂, and 0.947 for H₂O, with RMSEP values of 4.43 %, 3.55 %, and 8.35 %, respectively. Although water estimation showed slightly higher deviation, it remained within the experimental uncertainty range of the QCM reference. These results confirm the feasibility of applying NIRS for real-time, multi-component gas analysis in industrial settings
{"title":"The use of NIR spectroscopy for the quantification of water content and compositional analysis in compressed gas-systems","authors":"Larissa F. Torres , Marilia R. Oliveira , Thales C.S. Barbalho , Cláudio Dariva , Gustavo R. Borges , Papa M. Ndiaye , Frederico W. Tavares","doi":"10.1016/j.vibspec.2025.103815","DOIUrl":"10.1016/j.vibspec.2025.103815","url":null,"abstract":"<div><div>The use of Near Infrared Spectroscopy (NIRS) has a significant potential to enable the detection and quantification of natural gas components (e.g., CH<sub>4</sub>, CO<sub>2</sub>, moisture). It offers a quick, non-invasive, and non-destructive approach, eliminating the challenges associated with traditional sampling methods. Here, we investigated the applicability of the NIR technique to perform accurate quantification of water content and compositional analysis regarding CH<sub>4</sub> and CO<sub>2</sub> in compressed systems. The system’s pressure is also considered a response variable. The spectra collection was made at room temperature (298.15 K), with pressures up to 120 bar and CO<sub>2</sub> concentrations varying from 0 % to 50 % of the total composition. The Partial Least Squares (PLS) was used as the regression method, and the Quartz Crystal Microbalance (QCM) as the reference technique for water content. The PLS models yielded high accuracy, with R² values of 0.990 for CH₄, 0.993 for CO₂, and 0.947 for H₂O, with RMSEP values of 4.43 %, 3.55 %, and 8.35 %, respectively. Although water estimation showed slightly higher deviation, it remained within the experimental uncertainty range of the QCM reference. These results confirm the feasibility of applying NIRS for real-time, multi-component gas analysis in industrial settings</div></div>","PeriodicalId":23656,"journal":{"name":"Vibrational Spectroscopy","volume":"139 ","pages":"Article 103815"},"PeriodicalIF":2.7,"publicationDate":"2025-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144169254","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-05-28DOI: 10.1016/j.vibspec.2025.103816
Seung-Hyun Im , Mohammad Akbar Faqeerzada , Byoung-Kwan Cho , Geonwoo Kim , Hoonsoo Lee
Soil volumetric water content (SVWC) is a critical factor in plant health, influencing water uptake, nutrient transport, and overall physiological performance. Adverse environmental conditions like drought and high temperatures challenge crop growth and reduce yields. Accurate monitoring of SVWC is essential for optimizing growing conditions, preventing water stress, and promoting sustainable agriculture. This study explores a non-destructive method for predicting SVWC in Chinese cabbage seedlings using short-wave infrared (SWIR, 894–2504 nm) hyperspectral imaging coupled with machine learning. Daily hyperspectral images and corresponding SVWC measurements were collected over three days following irrigation cessation, resulting in a dataset of 2700 spectra. Gaussian process regression (GPR) and support vector regression (SVR) models were applied, with Lasso and Ridge regression used for feature selection. The models were evaluated using all spectral bands (E164) and 30 selected bands (L30 and R30). The GPR model with Lasso-selected bands and smoothing preprocessing achieved the highest accuracy (R² = 0.87, RMSE = 1.33). The SVR model with smoothing preprocessing and the entire spectral range demonstrated R² = 0.82 and RMSE = 1.52. Multivariate regression models using 14 shared bands selected by Lasso and Ridge regression yielded moderate performance (R² = 0.67, RMSE = 2.07). These findings highlight the potential of hyperspectral imaging combined with machine learning for non-destructive SVWC prediction, enabling early crop detection of water stress.
{"title":"Optimized feature selection and machine learning for non-destructive estimation of soil volumetric water content in Chinese cabbage using hyperspectral imaging","authors":"Seung-Hyun Im , Mohammad Akbar Faqeerzada , Byoung-Kwan Cho , Geonwoo Kim , Hoonsoo Lee","doi":"10.1016/j.vibspec.2025.103816","DOIUrl":"10.1016/j.vibspec.2025.103816","url":null,"abstract":"<div><div>Soil volumetric water content (SVWC) is a critical factor in plant health, influencing water uptake, nutrient transport, and overall physiological performance. Adverse environmental conditions like drought and high temperatures challenge crop growth and reduce yields. Accurate monitoring of SVWC is essential for optimizing growing conditions, preventing water stress, and promoting sustainable agriculture. This study explores a non-destructive method for predicting SVWC in Chinese cabbage seedlings using short-wave infrared (SWIR, 894–2504 nm) hyperspectral imaging coupled with machine learning. Daily hyperspectral images and corresponding SVWC measurements were collected over three days following irrigation cessation, resulting in a dataset of 2700 spectra. Gaussian process regression (GPR) and support vector regression (SVR) models were applied, with Lasso and Ridge regression used for feature selection. The models were evaluated using all spectral bands (E164) and 30 selected bands (L30 and R30). The GPR model with Lasso-selected bands and smoothing preprocessing achieved the highest accuracy (R² = 0.87, RMSE = 1.33). The SVR model with smoothing preprocessing and the entire spectral range demonstrated R² = 0.82 and RMSE = 1.52. Multivariate regression models using 14 shared bands selected by Lasso and Ridge regression yielded moderate performance (R² = 0.67, RMSE = 2.07). These findings highlight the potential of hyperspectral imaging combined with machine learning for non-destructive SVWC prediction, enabling early crop detection of water stress.</div></div>","PeriodicalId":23656,"journal":{"name":"Vibrational Spectroscopy","volume":"139 ","pages":"Article 103816"},"PeriodicalIF":2.7,"publicationDate":"2025-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144190377","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-05-21DOI: 10.1016/j.vibspec.2025.103812
Zhonghai He , Haoxiang Zhang , Yi Zhang , Xiaofang Zhang
Spectroscopy are widely used in routine concentration measurement. However, when spectral measurement is carried out in process industry, the measurement environment often changes thus the prediction accuracy of the regression model is spoiled. Existing studies regard the measurement environment change as noise, but in fact, the measurement environment also contains useful information. In this paper, a modeling method is proposed to augment the measured environmental parameters (physical quantities) into the calibration modeling to improve the prediction accuracy. To solve the problem of physical quantity parameters being overridden caused by direct variable extension method, we use the data fusion method based on sample similarity. Gaussian kernel function is used to calculate the similarity matrix of spectral and physical quantities respectively. Then fusion matrix is obtained by weighting combination. Finally, the regression model of fusion matrix and concentration is established by standard PLS modeling method. A regression model is established for the data collected during the fermentation process. The results showed that the prediction performance of the model could be improved by nearly 10 % by adding physical quantity information.
{"title":"Similarity based spectral data fusion physical parameter regression modeling method","authors":"Zhonghai He , Haoxiang Zhang , Yi Zhang , Xiaofang Zhang","doi":"10.1016/j.vibspec.2025.103812","DOIUrl":"10.1016/j.vibspec.2025.103812","url":null,"abstract":"<div><div>Spectroscopy are widely used in routine concentration measurement. However, when spectral measurement is carried out in process industry, the measurement environment often changes thus the prediction accuracy of the regression model is spoiled. Existing studies regard the measurement environment change as noise, but in fact, the measurement environment also contains useful information. In this paper, a modeling method is proposed to augment the measured environmental parameters (physical quantities) into the calibration modeling to improve the prediction accuracy. To solve the problem of physical quantity parameters being overridden caused by direct variable extension method, we use the data fusion method based on sample similarity. Gaussian kernel function is used to calculate the similarity matrix of spectral and physical quantities respectively. Then fusion matrix is obtained by weighting combination. Finally, the regression model of fusion matrix and concentration is established by standard PLS modeling method. A regression model is established for the data collected during the fermentation process. The results showed that the prediction performance of the model could be improved by nearly 10 % by adding physical quantity information.</div></div>","PeriodicalId":23656,"journal":{"name":"Vibrational Spectroscopy","volume":"139 ","pages":"Article 103812"},"PeriodicalIF":2.7,"publicationDate":"2025-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144139599","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-05-20DOI: 10.1016/j.vibspec.2025.103811
Jiawei Ma , Shizheng Zhang , Rui Cheng , Chang Zhao , Xiaoli Zhu , Peng Du , Xiaolei Wang , Huinan Yang
Ulcerative colitis (UC) is a type of inflammatory bowel disease (IBD), which can be diagnosed by a combination of invasive endoscopy, clinical examination and histopathology. However, Crohn's disease (CD), as another subtype of IBD, exhibits similar clinical and pathological manifestations to UC. This usually leads to delayed diagnosis of UC and increases the possibility of conversion to colorectal cancer. Moreover, it is difficult to distinguish patients with UC from healthy controls (HC) in early diagnosis. Therefore, it is very important to accurately distinguish IBD subtypes and early identification of UC patients and HC in clinical practice. In this work, surface-enhanced Raman spectroscopy (SERS) was used to measure urine samples from 166 IBD patients (including 83 UC and 83 CD) and 83 HC, totaling 249 samples. It shows that there are significant differences in the intensities at several main Raman peaks between UC and CD, as well as between UC and HC. Then, classification models based on principal component analysis (PCA) were constructed for UC/CD and UC/HC to reduce the dimensionality of the dataset, followed by analysis of the reduced-dimension samples using the constructed support vector machine (SVM) models. After the leave-one-out cross-validation (LOOCV), the UC/CD classification model achieved an accuracy of 72.89 %, sensitivity of 67.47 %, and specificity of 78.31 %, while the UC/HC classification model achieved 82.53 %, 90.36 %, and 74.70 % respectively for these metrics. Therefore, this indicates that SERS, based on urine samples combined with PCA and SVM analysis techniques, can effectively identify IBD subtypes and accurately diagnose UC patients from HC patients, greatly facilitating the clinical diagnosis process. The application of this method has great potential to achieve non-invasive early diagnosis of UC, thereby providing more timely and effective treatment strategies for patients.
{"title":"Early diagnosis of ulcerative colitis based on urine SERS and multivariate analysis","authors":"Jiawei Ma , Shizheng Zhang , Rui Cheng , Chang Zhao , Xiaoli Zhu , Peng Du , Xiaolei Wang , Huinan Yang","doi":"10.1016/j.vibspec.2025.103811","DOIUrl":"10.1016/j.vibspec.2025.103811","url":null,"abstract":"<div><div>Ulcerative colitis (UC) is a type of inflammatory bowel disease (IBD), which can be diagnosed by a combination of invasive endoscopy, clinical examination and histopathology. However, Crohn's disease (CD), as another subtype of IBD, exhibits similar clinical and pathological manifestations to UC. This usually leads to delayed diagnosis of UC and increases the possibility of conversion to colorectal cancer. Moreover, it is difficult to distinguish patients with UC from healthy controls (HC) in early diagnosis. Therefore, it is very important to accurately distinguish IBD subtypes and early identification of UC patients and HC in clinical practice. In this work, surface-enhanced Raman spectroscopy (SERS) was used to measure urine samples from 166 IBD patients (including 83 UC and 83 CD) and 83 HC, totaling 249 samples. It shows that there are significant differences in the intensities at several main Raman peaks between UC and CD, as well as between UC and HC. Then, classification models based on principal component analysis (PCA) were constructed for UC/CD and UC/HC to reduce the dimensionality of the dataset, followed by analysis of the reduced-dimension samples using the constructed support vector machine (SVM) models. After the leave-one-out cross-validation (LOOCV), the UC/CD classification model achieved an accuracy of 72.89 %, sensitivity of 67.47 %, and specificity of 78.31 %, while the UC/HC classification model achieved 82.53 %, 90.36 %, and 74.70 % respectively for these metrics. Therefore, this indicates that SERS, based on urine samples combined with PCA and SVM analysis techniques, can effectively identify IBD subtypes and accurately diagnose UC patients from HC patients, greatly facilitating the clinical diagnosis process. The application of this method has great potential to achieve non-invasive early diagnosis of UC, thereby providing more timely and effective treatment strategies for patients.</div></div>","PeriodicalId":23656,"journal":{"name":"Vibrational Spectroscopy","volume":"139 ","pages":"Article 103811"},"PeriodicalIF":2.7,"publicationDate":"2025-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144124309","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This study evaluates the accuracy and convergence of 12 DFT quadrature grid combinations for computing potential energy surfaces (PESs) to address quantum anharmonic vibrational spectra. The grids, ranging from 23 to 300 radial and 170 to 1202 angular points, are tested with widely used six DFT functionals (B3LYP-D, PBE0-D, B3PW91-D, B98-D, ωB97X-D, M06–2X) using def2-type triple-ξ basis sets. The computed anharmonic transitions for fundamentals and overtones along with the intensities are benchmarked using vibrational self-consistent field (VSCF) and its second-order perturbative corrected (VSCF-PT2) algorithms across different molecules, against the reference/largest grid (300,1202). While the smallest grid (23,170) had significant deviations, the largest grid is accurate but computationally expensive. Moderate grids like 75,302 achieved excellent accuracy with lower CPU demands, making them ideal for large molecules, while 75,590 is preferred for flexible systems. Furthermore, the angular grid has a greater impact on the accuracy of computed spectra than the radial grid.
{"title":"Accuracy of DFT quadrature grids for the computation of quantum anharmonic vibrational spectroscopy","authors":"Dhiksha Sharma , Jyoti Devi , Avantika Sharma , Mokshi Sharma , Meenakshi Raina , Akriti Jamwal , Tapta Kanchan Roy","doi":"10.1016/j.vibspec.2025.103810","DOIUrl":"10.1016/j.vibspec.2025.103810","url":null,"abstract":"<div><div>This study evaluates the accuracy and convergence of 12 DFT quadrature grid combinations for computing potential energy surfaces (PESs) to address quantum anharmonic vibrational spectra. The grids, ranging from 23 to 300 radial and 170 to 1202 angular points, are tested with widely used six DFT functionals (B3LYP-D, PBE0-D, B3PW91-D, B98-D, ωB97X-D, M06–2X) using def2-type triple-ξ basis sets. The computed anharmonic transitions for fundamentals and overtones along with the intensities are benchmarked using vibrational self-consistent field (VSCF) and its second-order perturbative corrected (VSCF-PT2) algorithms across different molecules, against the reference/largest grid (300,1202). While the smallest grid (23,170) had significant deviations, the largest grid is accurate but computationally expensive. Moderate grids like 75,302 achieved excellent accuracy with lower CPU demands, making them ideal for large molecules, while 75,590 is preferred for flexible systems. Furthermore, the angular grid has a greater impact on the accuracy of computed spectra than the radial grid.</div></div>","PeriodicalId":23656,"journal":{"name":"Vibrational Spectroscopy","volume":"139 ","pages":"Article 103810"},"PeriodicalIF":2.7,"publicationDate":"2025-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144068182","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-05-01DOI: 10.1016/j.vibspec.2025.103807
Chun Li , Yanan Lu , Shengzhu Fu, Yulong Guo, Zhengwei Huang, Lei Wen, Ling Jiang
With the increased awareness of food safety, rapid, accurate, and non-destructive detection of pesticide residues on fruit peels has attracted widespread attention. In this work, we utilize the attenuated total reflectance-Fourier transform infrared spectroscopy (ATR-FTIR) to directly detect multiple pesticide residues (including carbendazim, thiophanate-methyl, and thiabendazole) on the surface of the apple peels. To further improve the efficiency of detection and meet the practical application needs, a multi-task learning (MTL) model based on multi-task neural networks is introduced to perform qualitative and quantitative analysis of three pesticides, simultaneously. The optimal results in the testing set demonstrate an average accuracy of 100 % for the qualitative task, while the average R2 of 0.9415 and root mean square error (RMSE) of 2.567 μg/cm2 can be achieved in the quantitative task. The limit of detection (LOD) of carbendazim, thiophanate-methyl, and thiabendazole were determined as 7.308 μg/cm2, 1.595 μg/cm2 and 0.159 μg/cm2, respectively. Compared with the traditional single-task model, our work greatly simplifies the complexity of pesticide detection while ensuring prediction accuracy, which offers an alternative approach for further deployment and operation of the on-site system.
{"title":"Simultaneous qualitative and quantitative analyses of pesticide residues on fruit peels with ATR-FTIR spectroscopy and multi-task learning","authors":"Chun Li , Yanan Lu , Shengzhu Fu, Yulong Guo, Zhengwei Huang, Lei Wen, Ling Jiang","doi":"10.1016/j.vibspec.2025.103807","DOIUrl":"10.1016/j.vibspec.2025.103807","url":null,"abstract":"<div><div>With the increased awareness of food safety, rapid, accurate, and non-destructive detection of pesticide residues on fruit peels has attracted widespread attention. In this work, we utilize the attenuated total reflectance-Fourier transform infrared spectroscopy (ATR-FTIR) to directly detect multiple pesticide residues (including carbendazim, thiophanate-methyl, and thiabendazole) on the surface of the apple peels. To further improve the efficiency of detection and meet the practical application needs, a multi-task learning (MTL) model based on multi-task neural networks is introduced to perform qualitative and quantitative analysis of three pesticides, simultaneously. The optimal results in the testing set demonstrate an average accuracy of 100 % for the qualitative task, while the average R<sup>2</sup> of 0.9415 and root mean square error (RMSE) of 2.567 μg/cm<sup>2</sup> can be achieved in the quantitative task. The limit of detection (LOD) of carbendazim, thiophanate-methyl, and thiabendazole were determined as 7.308 μg/cm<sup>2</sup>, 1.595 μg/cm<sup>2</sup> and 0.159 μg/cm<sup>2</sup>, respectively. Compared with the traditional single-task model, our work greatly simplifies the complexity of pesticide detection while ensuring prediction accuracy, which offers an alternative approach for further deployment and operation of the on-site system.</div></div>","PeriodicalId":23656,"journal":{"name":"Vibrational Spectroscopy","volume":"138 ","pages":"Article 103807"},"PeriodicalIF":2.7,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143916361","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-05-01DOI: 10.1016/j.vibspec.2025.103808
Ying Wang , Shouqi Zhang , Xiaowen Kong , Zhengren Xu , Zhiqiang Wang , Ruiting Zhang , Lin Ma , Ke Lin
Isoprenol has important applications in both biological and medical fields, and the measurement of its structure in living organisms is very important to understand the mechanism of its role at the molecular level. We synthesized five kinds of deuterated isoprenols, and optimized structure of the deuterated rotational isomers by quantum chemical calculations, and calculated and record the Raman spectra of all the deuterated isoprenols. These experimental and theoretical results suggest that the stretching vibrational spectra of individual C-D bonds in deuterated methylene and methanediyl group can be used to identify the conformers of isoprenol. This work not only analyzed the correlation between the structure of isoprenol and the spectra of this particular deuterated molecule, but also demonstrates the potential of combining this novel method with other techniques, such as X-ray diffraction, to obtain more precise molecular structures in complex environments.
{"title":"Identification of the isoprenols conformers by the Raman spectra of the deuterated compounds in the C-D stretching region","authors":"Ying Wang , Shouqi Zhang , Xiaowen Kong , Zhengren Xu , Zhiqiang Wang , Ruiting Zhang , Lin Ma , Ke Lin","doi":"10.1016/j.vibspec.2025.103808","DOIUrl":"10.1016/j.vibspec.2025.103808","url":null,"abstract":"<div><div>Isoprenol has important applications in both biological and medical fields, and the measurement of its structure in living organisms is very important to understand the mechanism of its role at the molecular level. We synthesized five kinds of deuterated isoprenols, and optimized structure of the deuterated rotational isomers by quantum chemical calculations, and calculated and record the Raman spectra of all the deuterated isoprenols. These experimental and theoretical results suggest that the stretching vibrational spectra of individual C-D bonds in deuterated methylene and methanediyl group can be used to identify the conformers of isoprenol. This work not only analyzed the correlation between the structure of isoprenol and the spectra of this particular deuterated molecule, but also demonstrates the potential of combining this novel method with other techniques, such as X-ray diffraction, to obtain more precise molecular structures in complex environments.</div></div>","PeriodicalId":23656,"journal":{"name":"Vibrational Spectroscopy","volume":"138 ","pages":"Article 103808"},"PeriodicalIF":2.7,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143904232","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-05-01DOI: 10.1016/j.vibspec.2025.103809
Xubo Wang , Hongjun Yin , Jingwen Zhu , Yong Huang , Zhenguang Wang , Xinmei Zheng , Xiaowei Cao , Wei Wei
MicroRNA (miRNA) is a potential biomarker for tumor diagnosis. Therefore, it is important to investigate a method for accurate analysis of miRNA. In this study, we developed a novel and cost-effective surface-enhanced Raman scattering (SERS)-lateral flow assay(LFA) dual detection line test strip for quantitatively detecting miR-19a-3p and miR-4491, respectively. These two miRNAs are closely associated with the development of gastric cancer (GC) and their significant overexpression in patients gives them great potential as innovative tumor markers for GC detection. During the detection process, miR-19a-3p and miR-4491 would compete for binding to the corresponding SERS tags. The presence of concentrations of miR-19a-3p and miR-4491 in the sample solution reduces the binding of the SERS tags to the ssDNAs, thereby reducing the SERS intensity. The test strips were designed to be highly specific and reproducible, and the entire assay was completed in 15 minutes. The test strips we designed were simpler, more sensitive, and more efficient than other detection methods. The detection limit in serum were 21.14 fM for miR-19a-3p and 10.34 fM for miR-4491. In addition, the results of SERS-based LFA test strip and quantitative real-time polymerase chain reaction (qRT-PCR) were consistent for serum testing of healthy individuals, patients with mild intraepithelial neoplasia (IE), patients with severe IE, and patients with gastric cancer. Therefore, SERS-based LFA test strip has great potential for the clinical diagnosis of gastric cancer.
{"title":"SERS and lateral flow assay-based test strips for rapid and efficient detection of GC-associated miR-19a-3p and miR-4491","authors":"Xubo Wang , Hongjun Yin , Jingwen Zhu , Yong Huang , Zhenguang Wang , Xinmei Zheng , Xiaowei Cao , Wei Wei","doi":"10.1016/j.vibspec.2025.103809","DOIUrl":"10.1016/j.vibspec.2025.103809","url":null,"abstract":"<div><div>MicroRNA (miRNA) is a potential biomarker for tumor diagnosis. Therefore, it is important to investigate a method for accurate analysis of miRNA. In this study, we developed a novel and cost-effective surface-enhanced Raman scattering (SERS)-lateral flow assay(LFA) dual detection line test strip for quantitatively detecting miR-19a-3p and miR-4491, respectively. These two miRNAs are closely associated with the development of gastric cancer (GC) and their significant overexpression in patients gives them great potential as innovative tumor markers for GC detection. During the detection process, miR-19a-3p and miR-4491 would compete for binding to the corresponding SERS tags. The presence of concentrations of miR-19a-3p and miR-4491 in the sample solution reduces the binding of the SERS tags to the ssDNAs, thereby reducing the SERS intensity. The test strips were designed to be highly specific and reproducible, and the entire assay was completed in 15 minutes. The test strips we designed were simpler, more sensitive, and more efficient than other detection methods. The detection limit in serum were 21.14 fM for miR-19a-3p and 10.34 fM for miR-4491. In addition, the results of SERS-based LFA test strip and quantitative real-time polymerase chain reaction (qRT-PCR) were consistent for serum testing of healthy individuals, patients with mild intraepithelial neoplasia (IE), patients with severe IE, and patients with gastric cancer. Therefore, SERS-based LFA test strip has great potential for the clinical diagnosis of gastric cancer.</div></div>","PeriodicalId":23656,"journal":{"name":"Vibrational Spectroscopy","volume":"138 ","pages":"Article 103809"},"PeriodicalIF":2.7,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143899326","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-04-15DOI: 10.1016/j.vibspec.2025.103806
Feng Zhang, Yang Yang, Dingyue Lian, Lin Li, Suping Zhao, Chaobo Chen
Baseline drift is a key problem in spectral analysis. The resolution of the baseline drift problem sets the stage for future spectral analyses. The baseline correction algorithm previously proposed by scholars may result in inaccurate correction in the presence of spectral overlap peak areas and noise interference, and they all have one or more parameters that need to be optimized by the user. Therefore, an Automatic baseline correction algorithm based on reweighted penalised least squares method for non-sensitive areas(NasPLS) was proposed. First, according to the High solution Transmission Molecular Absorption Database (HITRAN) and actual measurements of hydrocarbon gases, several non-sensitive areas appeared between 400 and 4000 wavenumbers. Then, based on the root mean square error(RMSE) values of the original baseline and the fitted baseline in the non-sensitive areas, the minimum RMSE is found to adapt to updating the smoothing parameters and select the optimal . Finally, the proposed NasPLS method was validated using simulated data and actual measured spectra of methane and ethane, the NasPLS achieves precise baseline correction in the presence of noise interference in simulated data. The results of experimental measurements show that the proposed method can accurately perform baseline corrections in complex situations.
{"title":"An automatic baseline correction method based on reweighted penalised least squares method for non-sensitive areas","authors":"Feng Zhang, Yang Yang, Dingyue Lian, Lin Li, Suping Zhao, Chaobo Chen","doi":"10.1016/j.vibspec.2025.103806","DOIUrl":"10.1016/j.vibspec.2025.103806","url":null,"abstract":"<div><div>Baseline drift is a key problem in spectral analysis. The resolution of the baseline drift problem sets the stage for future spectral analyses. The baseline correction algorithm previously proposed by scholars may result in inaccurate correction in the presence of spectral overlap peak areas and noise interference, and they all have one or more parameters that need to be optimized by the user. Therefore, an Automatic baseline correction algorithm based on reweighted penalised least squares method for non-sensitive areas(NasPLS) was proposed. First, according to the High solution Transmission Molecular Absorption Database (HITRAN) and actual measurements of hydrocarbon gases, several non-sensitive areas appeared between 400 and 4000 wavenumbers. Then, based on the root mean square error(RMSE) values of the original baseline and the fitted baseline in the non-sensitive areas, the minimum RMSE is found to adapt to updating the smoothing parameters and select the optimal <span><math><mi>λ</mi></math></span>. Finally, the proposed NasPLS method was validated using simulated data and actual measured spectra of methane and ethane, the NasPLS achieves precise baseline correction in the presence of noise interference in simulated data. The results of experimental measurements show that the proposed method can accurately perform baseline corrections in complex situations.</div></div>","PeriodicalId":23656,"journal":{"name":"Vibrational Spectroscopy","volume":"138 ","pages":"Article 103806"},"PeriodicalIF":2.7,"publicationDate":"2025-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143847646","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-04-13DOI: 10.1016/j.vibspec.2025.103805
Ali I. Al-Mosawi, Shaymaa Abbas Abdulsada
For polymers, including flexible polyvinyl chloride, aging processes play a crucial role in determining their long-term performance and function in various applications, especially those exposed to harsh environmental conditions. Aging effects are analyzed using several tools, including Raman spectroscopy, which is an effective tool for detecting molecular and structural changes in the polymer structure, providing a detailed analytical picture of the degradation behavior as a result of aging. The present study investigates the effect of aging on the structural properties of flexible PVC, taking into account the effect of sample thickness on the results of Raman spectroscopy. The results of 2 and 4 mm thick flexible PVC samples produced by extrusion, immediately after production and after one year of production, after being stored at room temperature without being exposed to harsh external conditions were analyzed to study natural aging. The characteristic Raman peaks associated with plasticizer leaching, chain splitting, and oxidation, as well as the SEM images, were analyzed and the obtained results correlated with the sample thickness. Thicker samples showed a lower rate of detectable chemical changes in the polymer structure, attributed to slower oxygen diffusion and lower chlorine release rate compared to thinner samples exposed to the same environmental conditions. Therefore, it is essential to consider the sample thickness factor in Raman spectroscopy analyses, as it greatly affects the sensitivity and interpretation of the results.
{"title":"Effect of aging on Raman spectroscopy analyses for flexible polyvinyl chloride","authors":"Ali I. Al-Mosawi, Shaymaa Abbas Abdulsada","doi":"10.1016/j.vibspec.2025.103805","DOIUrl":"10.1016/j.vibspec.2025.103805","url":null,"abstract":"<div><div>For polymers, including flexible polyvinyl chloride, aging processes play a crucial role in determining their long-term performance and function in various applications, especially those exposed to harsh environmental conditions. Aging effects are analyzed using several tools, including Raman spectroscopy, which is an effective tool for detecting molecular and structural changes in the polymer structure, providing a detailed analytical picture of the degradation behavior as a result of aging. The present study investigates the effect of aging on the structural properties of flexible PVC, taking into account the effect of sample thickness on the results of Raman spectroscopy. The results of 2 and 4 mm thick flexible PVC samples produced by extrusion, immediately after production and after one year of production, after being stored at room temperature without being exposed to harsh external conditions were analyzed to study natural aging. The characteristic Raman peaks associated with plasticizer leaching, chain splitting, and oxidation, as well as the SEM images, were analyzed and the obtained results correlated with the sample thickness. Thicker samples showed a lower rate of detectable chemical changes in the polymer structure, attributed to slower oxygen diffusion and lower chlorine release rate compared to thinner samples exposed to the same environmental conditions. Therefore, it is essential to consider the sample thickness factor in Raman spectroscopy analyses, as it greatly affects the sensitivity and interpretation of the results.</div></div>","PeriodicalId":23656,"journal":{"name":"Vibrational Spectroscopy","volume":"138 ","pages":"Article 103805"},"PeriodicalIF":2.7,"publicationDate":"2025-04-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143843339","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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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