SPECTROCHIMICA ACTA PART A-MOLECULAR AND BIOMOLECULAR SPECTROSCOPY
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2020
·
IF 3.232
Zijun Xu,Zhaokun Wang,Mingyang Liu,Binwei Yan,Xueqin Ren,Zideng Gao
The detection and differentiation of tetracyclines (TCs) has received increasing attention due to the severe threat they pose to human health and the ecological balance. A dual-channel fluorescence sensor array based on two carbon quantum dots (CDs) was fabricated to distinguish between four TCs, including tetracycline (TC), oxytetracycline (OTC), doxycycline (DOX), and metacycline (MTC). A distinct fluorescence variation pattern (I/I 0 ) was produced when CDs interacted with the four TCs. This pattern was analyzed by LDA and SVM. This was the first time that SVM was used for data processing of fluorescence sensor arrays. LDA and SVM showed that the array has the capacity for parallel and accurate determination of TCs at concentrations between 1.0 μM and 150 μM. In addition, the interference experiment using metal ions and antibiotics as possible coexisting interference substances proves that the sensor array has excellent selectivity and anti-interference ability. The array was also used for the accurate detection and identification of TCs in binary mixtures, and furthermore, the four TCs were successfully identified in river water and milk samples. Besides, the sensor array successfully identified the four TCs in 72 unknown samples with a 100% accuracy. The results proved that SVM can achieve the same accurate classification and prediction as LDA, and considering its additional advantages, it can be used as an optional supplementary method for data processing, thereby expanding the data processing field.
研究领域:
分析化学
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环境科学
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生物医学工程
✓ 已验证
DOI
高影响因子
FOOD RESEARCH INTERNATIONAL
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2022
·
IF 7.425
Yaodi Zhu,Weijia Liu,Shijie Liu,Miaoyun Li,Lijun Zhao,Lina Xu,Na Wang,Gaiming Zhao,Qiuying Yu
In this study, we developed a novel and sensitive AgNPs self-assembled solid-phase (AgNPs-SASP) SERS substrate platform using seed-mediated and liquid interface self-assembly methods and applied the platform for the detection of three bacterial spores. Multivariate statistical analysis (HCA and LDA) were employed for identification and categorization of the obtained data. The results illustrated that AgNPs-SASP exhibited high reproducibility and Raman enhancement effect (1.43 × 10 4 ). The Raman shift bands of the three bacterial spores ranged from 400 to 1800 cm −1 demonstrating the difference in reigon and intensity. And the intensities of their Ca 2+ -DPA Raman bands are significantly different. HCA results revealed that the spectra for the three bacterial spores were statistically different while LDA completely differentiated the spectra for the three bacterial spores with 100 % sensitivity and specificity. Overall, the novel SERS platform based on AgNPs-SASP provides an effective tool for food safety risk control and detection.
研究领域:
食品科学
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分析化学
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生物技术
✓ 已验证
产品关联
DOI
PubMed
高影响因子
Analytical Methods
·
2016
·Vol. 9
·期 1
·141-148
·
IF 1.915
Li Jia-wei,Hou Chang-jun,Huo Dan-qun,Yang Mei,Zhang Su-yi,Ma Yi,Lin Yang
The components of Chinese liquor are influenced by geographical origins and raw materials. Currently, Chinese liquor identification systems are limited and have a single application that can distinguish only one nature of flavor type and production area. Four chemical reagents were successfully used to build this 3 × 1 simple colorimetric sensor array. This is the first time that a highly accurate colorimetric Chinese liquor sensor array was fabricated using only a few array points. It could distinguish four types of Chinese base liquors from Luzhou Laojiao, nine types of Chinese liquors with different flavor types, and seven types of Chinese liquors from different geographical origins. In order to ensure the accuracy, seven parallel samples were analyzed with water used as a control. PCA proved this sensor array to be effective. In LDA and HCA, every group was clearly classified. The “leave-one-out” cross-validation method was applied with 100% prediction ability in the three experiments. According to the results of the PCA, HCA, LDA, and the “leave-one-out” method, we can deduce that this colorimetric sensor array with multiple applications has great performance in discriminating Chinese liquors.
研究领域:
分析化学
·
食品科学
✓ 已验证
产品关联
DOI
高影响因子
ANALYTICA CHIMICA ACTA
·
2025
·
IF 6
Ruiying Lin,Zhangying Jiang,Jinyong Lin,Feifei Tong,Yangmin Wu,Jinquan Hong,Sufang Qiu,Qiong Wu
Background In recent years, significant progress has been made in the treatment of nasopharyngeal carcinoma (NPC). The application of immunotherapy, especially the use of Programmed Cell Death Protein 1 inhibitors, has demonstrated excellent therapeutic effects. However, inconsistent immunotherapy outcomes due to individual differences in patients remain a major challenge, making the search for specific biomarkers to screen for the population who may benefit from immunotherapy a priority. Surface-enhanced Raman spectroscopy (SERS) has shown great potential as a highly sensitive and specific optical analytical tool for identifying and monitoring tumor-related markers in NPC. Results In this study, plasma samples from Nasopharyngeal cancer patients before and after immunotherapy, along with those from healthy volunteers, were tested using label-free SERS combined with plasmapheresis. Especially, the components with varying molecular weight sizes were analyzed via the separation process, thereby preventing the potential loss of diagnostic information that could result from competitive adsorption. Subsequently, a robust machine learning algorithm based on principal component analysis and linear discriminant analysis (PCA-LDA) was used to extract features from plasma SERS data and establish an effective discriminant model. The results showed that in the upper plasma layer, the most optimal discrimination was found between normal patients and those post-treatment, with sensitivity and specificity of 88.5% and 92.3%, respectively. In the lower plasma layer, the most optimal discrimination was found between the pre-treatment and post-treatment patients, with sensitivity and specificity of 84.6% and 80.8%, respectively. Significance and novelty Plasmapheresis can reveal latent diagnostic information in the plasma and holds promise for treating NPC, the screening of the population who may benefit from immunotherapy, and the postoperative evaluation of immunotherapy. Further exploration of the feasibility of using SERS to detect tumor markers in the population who may benefit from immunotherapy for NPC will help improve the therapeutic efficacy, optimize clinical practice, and promote the development of individualized treatment strategies.
研究领域:
肿瘤学
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医学诊断
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生物信息学
✓ 已验证
产品关联
DOI
PubMed
高影响因子
JOURNAL OF RAMAN SPECTROSCOPY
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2022
·Vol. 53
·期 8
·1371-1379
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IF 2.727
Xueliang Lin,Xianggang Jia,Jin Yong Lin,Ping Hui Wu,Youliang Weng,Shangyuan Feng
Human blood contains a variety of biomolecules that are highly related to the occurrence, progression, and prognosis of diseases, including cancer. The development of rapid and accurate methods for the detection of these biomarkers with extremely low concentration is vital for improving cancer screening. Herein, a label-free surface-enhanced Raman scattering (SERS) technology was employed to detect human serum samples from healthy volunteers ( n = 51) and breast cancer patients ( n = 58) with the aim of exploring the differences in bio-components between them. Moreover, the influence of measurement location during SERS assay was evaluated due to the occurrence of “coffee-ring (CR)” effect associated with this work. Results showed that the SERS spectra obtained from the CR area can better reflect the overall biochemical information of serum samples and exhibited excellent diagnostic sensitivity (94.8%) and specificity (98%) for identifying breast cancer from healthy groups using principal component analysis and linear discriminant analysis (PCA-LDA) algorithm. This work showed a preliminary study of the serum SERS method for breast cancer detection, providing a potential rapid and accurate liquid biopsy strategy for clinical cancer screening.
研究领域:
医学诊断
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光谱学
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癌症研究
✓ 已验证
产品关联
DOI
高影响因子
JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY
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2014
·
IF 3.107
Quan-Jin Wu,Qing-Hua Dong,Wei-Jiang Sun,Yan Huang,Qiong-Qiong Wang,Wei-Long Zhou
This study aimed to construct objective and accurate analytical models of tea categories based on their polyphenols and caffeine. A total of 522 tea samples of 4 commonly consumed teas with different fermentation degrees (green tea, white tea, oolong tea, and black tea) were analyzed by high-performance liquid chromatography (HPLC) coupled with spectrophotometry, utilizing ISO 14502, as analytical tools. The content of polyphenols and caffeine varied significantly according to differently fermented teas, indicating that these active constituents may discriminate fermentation degrees effectively. By principal component analysis (PCA) and stepwise linear discriminant analysis (S-LDA), the vast majority of tea samples could be successfully differentiated according to their chemical markers. This study yielded three discriminant functions with the capacity to simultaneously discriminate the four tea categories with a 97.8% correct rate. In classification of oolong and other teas, there were one discriminant function and two equations with best discriminant capacity. Furthermore, the classification of different degrees of fermentation of oolong and external validation achieved the desired results. It is suggested that polyphenols and caffeine are the distinct variables to establish internationally recognized models of teas.
研究领域:
食品科学
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分析化学
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植物学
✓ 已验证
DOI
PubMed
高影响因子
DYES AND PIGMENTS
·
2019
·
IF 4.018
Linfeng Chen,Xike Tian,Yong Li,Chao Yang,Liqiang Lu,Zhaoxin Zhou,Yulun Nie
Portable, rapid, accurate and on-site detection of analysis target has always been the goal of continuous efforts in the field of analysis. In this work, a novel intelligent and rapid detection system based on an AIE dye (TPA-DCV) was established for portable and on-site detection of trace water in organic solvents and CN − in water by integrating the smartphone and linear discriminant analysis (LDA). The TPA-DCV displayed remarkable solvatochromism effect and showed different fluorescence colors to different water contents of different solvents, with the minimum detection limit of 54 ppm. In addition, TPA-DCV also exhibited specific response to CN − , and showed significant fluorescence changes to different amounts of CN − . With the assist of this detection system, these different fluorescence color signals could be accurately classified in canonical score plot. What's more, the classification and distribution of fluorescence color in canonical score plot showed regular change with the target concentration, which could be used to quantify the trace water and CN − . The rationality and practicability of this detection system were preliminary verified by a large number of real sample analyses. This detection system greatly simplifies the analysis process, which is in the proof of intelligent and rapid detection just using a simple color analysis without any instrument test, which may be a big step forward.
研究领域:
分析化学
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环境科学
·
生物医学工程
✓ 已验证
产品关联
DOI
高影响因子
Materials Chemistry Frontiers
·
2024
·
IF 6
Yujiao Xie,Xue Li,Lei Xu,Chenguang Zhang,Yong Ren,Xiaofeng Shi,Liyun Fu,Jing Wang,Xiawei Xu,Yue Liu,Yue Hu,Zhouxu Zhang,Jiahao Zhang,Ting Yao,Wenzhi Ren,Tianxiang Chen,Xiaoyu Qian,Xiaotian Wang,Jie Lin,Aiguo Wu
Early diagnosis and treatment of liver fibrosis can effectively prevent chronic liver disease from developing into hepatocellular carcinoma (HCC). Conventional techniques to detect liver fibrosis are complex and expensive. The development of non-invasive and sensitive surface-enhanced Raman scattering (SERS) can significantly reduce the time and cost, which is important for improving the efficiency of diagnosis and detection of liver disease. In this study, we developed a cubic core–shell Cu2O@Ag SERS bioprobe for label-free identification of HCC and hepatic fibrosis. The constructed composite substrate has shown impressive SERS sensitivity and good stability. Trace molecules (alizarin red and rhodamine 6G) with concentrations as low as 10−10 mol L−1 could be detected. Cubic Cu2O@Ag also exhibited good SERS stability, since the smallest relative standard deviation (RSD) of Cu2O@Ag-MB (methylene blue) was only 8.80%. Then, the spectral analysis of these three molecules (AR, MB, and R6G) was carried out by applying a machine learning-assisted LDA model, and the classification accuracy reached 100%. Subsequently, four different types of hepatocytes were identified and classified by using the established model and label-free SERS detection with a desirable accuracy of 91.38%. This innovative technology will further facilitate the early diagnosis of HCC and liver disease and assist in the rationalization of clinical treatment.
研究领域:
生物医学工程
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分析化学
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医学诊断
·
机器学习
✓ 已验证
产品关联
DOI
高影响因子
Advanced Optical Materials
·
2024
·
IF 8
Yuhan Jiang,Zixuan Zhou,Weile Kong,Ying Zhang,Lei Wang,Yaguang Sun,Mingchang Zhu,Shuangyan Wu
Development of new multi-ratiometric fluorescence probes has been a popular research field. This approach provides richer and more accurate information for the recognition of different substances which have similar chemical and physical properties. In this work, a ratiometric fluorescence sensor UIO-66⊃FL/RhB is successfully constructed by incorporating fluorescein (FL) and rhodamine B (RhB) to the UIO-66. With the addition of fluoroquinolones (FQs), the prepared UIO-66⊃FL/RhB sensor can be used for the 2D emission-fingerprint map, the linear discriminant analysis (LDA) and hierarchical clustering analysis (HCA) in recognition the presence of each FQs. The fluorescence probe offers a broad linear range (0-8 µM) and a low detection limit (3.7 nM) in sensing ofloxacin. In addition, a smartphone-assisted portable sensing platform and a portable UIO-66⊃FL/RhB hydrogel test material are constructed successfully for screening before fluorescence detection. This study proposes a novel multi-ratiometric fluorescence probe, which can recognize different FQs. Besides, the UIO-66⊃FL/RhB-based hydrogel beads are construction for screening before the detection of FQs, which established a promising strategy for the simple and accurate discrimination of FQs.
研究领域:
分析化学
·
材料科学
·
环境科学
·
传感器与执行器
✓ 已验证
产品关联
DOI
高影响因子
TALANTA
·
2023
·
IF 6.1
Qiong Wu,Jing Yu,Mingjin Zhang,Yinran Xiong,Lijia Zhu,Bo Wei,Ting Wu,Yiping Du
The liver is a major organ in metabolism, and alterations in serum lipids are associated with liver disorders. Here, a rapid, easy, and reliable screening technique based on lipidomic profiling was developed using machine learning and surface-assisted laser desorption ionization mass spectrometry (SALDI MS) for liver cancer diagnosis. A graphitized carbon matrix (GCM) was created for serum lipid profiling in SALDI MS and demonstrated a better performance for neutral lipids analysis than conventional organic matrices. The fingerprint of serum lipids, including triacylglycerols (TGs), diacylglycerols (DGs), cholesteryl esters (CEs), glycerophospholipids (GPs), and other components, could be directly obtained by GCM-assisted LDI MS without extraction. Five machine learning methods were applied to distinguish liver cancer (LC) patients from healthy controls (HC) and chronic hepatitis B (CHB) patients. The best diagnostic performance was attained by linear discriminant analysis (LDA), which has a confusion matrix accuracy of 98.3 %. The receiver operating characteristic (ROC) curve for liver cancer exhibited an area under the curve (AUC) of 0.99, indicating a high degree of prediction accuracy. One-way ANOVA analysis revealed that numerous TGs were down-regulated in LC group. The results demonstrated the viability of GCM-assisted LDI MS as a valuable diagnostic tool for liver cancer.
研究领域:
医学诊断
·
质谱技术
·
机器学习
·
癌症研究
·
脂质组学
✓ 已验证
产品关联
DOI
PubMed
高影响因子
危险品化学品经营许可证（带存储）