Analytical Chemistry最新文献

{"title":"Near-Infrared Light-Activated DNA Nanodevice for Spatiotemporal In Vivo Fluorescence Imaging of Messenger RNA","authors":"Lei Li, Xiaotong He, Yang Zhang, Dashan Qi, Meixing Li, Hui Zhang, Qingming Shen, Quli Fan","doi":"10.1021/acs.analchem.4c05292","DOIUrl":"https://doi.org/10.1021/acs.analchem.4c05292","url":null,"abstract":"Real-time visualization of messenger RNA (mRNA) is essential for tumor classification, grading, and staging. However, the low signal-to-background ratios and nonspatiotemporal specific signal amplification restricted the in vivo imaging of mRNA. In this study, a near-infrared (NIR) light-activated DNA nanodevice (DND) was developed for spatiotemporal in vivo fluorescence imaging of mRNA. The DND was fabricated by encapsulating indocyanine green (ICG) and DNA fluorescent probes within thermosensitive liposomes and subsequently functionalizing the liposomes with aptamers. The ICG offers the “always-on” fluorescence signal, offering a feasible strategy for monitoring DND distribution. The fluorescence signal of DNA probes remains inactive (“off” state) during the delivery process. Upon targeted delivery of the DNDs to tumor cells via aptamer recognition, the thermosensitive liposomes could be dissociated by the photothermal effect induced by ICG under near-infrared irradiation, thereby facilitating the release of DNA probes. The DNA probes were activated (“turn on”) by tumor-specific thymidine kinase 1 (TK1) mRNA through toehold-mediated strand displacement cascades, enabling the signal-amplified fluorescence imaging of mRNA. This study reveals the distinctive light-activated merit and remarkable fluorescence imaging of DNDs, highlighting their great potential to promote progress in spatiotemporal resolution imaging of other disease-relevant RNAs in vivo.","PeriodicalId":27,"journal":{"name":"Analytical Chemistry","volume":"27 1","pages":""},"PeriodicalIF":7.4,"publicationDate":"2024-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142867376","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Measurement of Bacterial Headspaces by FT-IR Spectroscopy Reveals Distinct Volatile Organic Compound Signatures","authors":"Christian Zenner, Lindsay J. Hall, Susmita Roy, Jürgen Hauer, Ronald Sroka, Kiran Sankar Maiti","doi":"10.1021/acs.analchem.4c02899","DOIUrl":"https://doi.org/10.1021/acs.analchem.4c02899","url":null,"abstract":"Ensuring prompt and precise identification of bacterial pathogens is essential for initiating appropriate antibiotic therapy and combating severe bacterial infections effectively. Traditional microbiological diagnostics, involving initial culturing and subsequent pathogen detection, are often laborious and time-consuming. Even though modern techniques such as Raman spectroscopy, MALDI-TOF, and 16S rRNA PCR have significantly expedited this process, new methods are required for the accurate and fast detection of bacterial pathogens. In this context, using bacterial metabolites for detection is promising as a future diagnostic approach. Fourier-transform infrared spectroscopy was employed in our study to analyze the biochemical composition of gas phases of bacterial isolates. We can characterize individual bacterial strains and identify specific bacteria within mixtures by utilizing volatile-metabolite-based infrared detection techniques. This approach enables rapid identification by discerning distinctive spectral features and intensities for different bacteria, offering new perspectives for bacterial pathogen diagnostics. This technique holds innovative potential to accelerate progress in the field, providing a faster and potentially more precise alternative to conventional diagnostic methods.","PeriodicalId":27,"journal":{"name":"Analytical Chemistry","volume":"19 1","pages":""},"PeriodicalIF":7.4,"publicationDate":"2024-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142867351","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Microneedle-Based Electrochemical Array Patch for Ultra-Antifouling and Ultra-Anti-Interference Monitoring of Subcutaneous Oxygen","authors":"Jiaxi Liu, Jiang Liu, Yanyan Liang, Jiao Yang, Yongping Lin, Yingchun Li","doi":"10.1021/acs.analchem.4c04345","DOIUrl":"https://doi.org/10.1021/acs.analchem.4c04345","url":null,"abstract":"Oxygen saturation is a crucial indicator in the management of various diseases and in preoperative diagnosis, and the detection of oxygen content is valuable in guiding clinical treatment. However, as the classical and dominant oxygen detection strategies, current photoelectric oximeters and electrochemical-based blood gas analyzers often suffer from significant interindividual variation and poor compliance, respectively. In recent years, wearable microneedles (MNs) for analyzing biomarkers in interstitial fluid (ISF) have received great attention and recognition mainly for the reason that the content of the substances distributed in ISF has a better correlation with that in blood circulation compared with other body fluids such as sweat and saliva. Herein, an MN-based electrochemical array system was developed for continuous subcutaneous oxygen sensing, in which gold-modified commercial acupuncture MNs were used as the sensing units, and a tailored mini-workstation, a nonwoven fabric, and a water and air isolation membrane were integrated to fabricate a wearable array patch. Notably, a multifunctional swelling resin with good biocompatibility was adopted to decorate the MN surface as a protective layer and as an electrolyte gel. The swelling resin featured the ability to reduce epidermis secretions during the sensor array penetrating the skin and to decrease the interference of other biomolecules in ISF for oxygen assay during measurement. This proposed array patch can perform the subcutaneous oxygen analysis in the physiological range of 6–150 mmHg with high sensitivity (0.3817 μA/mmHg) and low theoretical limit of detection (5.06 mmHg). It also showed decent stability and selectivity in the presence of several kinds of exogenous and endogenous substances. Finally, the patch accomplished continual monitoring of the subcutaneous oxygen content during long-term physical exercise, showing great potential in providing warning about the hypoxia status of the human body. It could be foreseen that this high-performance patch will play an active role in respiratory disease evaluation, surgical monitoring, and public health care.","PeriodicalId":27,"journal":{"name":"Analytical Chemistry","volume":"15 1","pages":""},"PeriodicalIF":7.4,"publicationDate":"2024-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142857944","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Raman Spectral Feature Enhancement Framework for Complex Multiclassification Tasks","authors":"Jiaqi Hu, Chenlong Xue, Ken Xiaokeng Chi, Junyu Wei, Zhicheng Su, Qiuyue Chen, Ziyu Ou, Shuxin Chen, Zhe Huang, Yilin Xu, Haoyun Wei, Yanjun Liu, Perry Ping Shum, Gina Jinna Chen","doi":"10.1021/acs.analchem.4c03261","DOIUrl":"https://doi.org/10.1021/acs.analchem.4c03261","url":null,"abstract":"Raman spectroscopy enables label-free clinical diagnosis in a single step. However, identifying an individual carrying a specific disease from people with a multi-disease background is challenging. To address this, we developed a Raman spectral implicit feature augmentation with a Raman Intersection, Union, and Subtraction augmentation strategy (RIUS). RIUS expands the data set without requiring additional labeled data by leveraging set operations at the feature level, significantly enhancing model performance across various applications. On a challenging 30-class bacterial classification task, RIUS demonstrated a substantial improvement, increasing the accuracy of ResNet by 2.1% and that of SE-ResNet by 1.4%, achieving accuracies of 85.7% and 87.1%, respectively, on the Bacteria-ID-4 Data set, where RIUS improved ResNet and SE-ResNet accuracies by 13.6% and 14.5%, respectively, with only ten samples per category. When the sample size was reduced, accuracy gains increased to 31.7% and 38.3%, demonstrating the method’s robustness across different sample volumes. Compared to basic augmentation, our method exhibited superior performance across various sample volumes and demonstrated exceptional adaptability to different levels of complexity. RIUS exhibited superior performance, particularly in complex settings. Moreover, cluster analysis validated the effectiveness of the implicit feature augmentation module and the consistency between theoretical design and experimental results. We further validated our approach using clinical serum samples from 70 breast cancer patients and 70 controls, achieving an AUC of 0.94 and a sensitivity of 92.9%. Our approach enhances the potential for precisely identifying diseases in complex settings and offers plug-and-play enhancement for existing classification models.","PeriodicalId":27,"journal":{"name":"Analytical Chemistry","volume":"55 1","pages":""},"PeriodicalIF":7.4,"publicationDate":"2024-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142857900","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Single-Cell Mass Spectrometry Studies of Secondary Drug Resistance of Tumor Cells","authors":"Guizhen Zhu, Wenmei Zhang, Yaoyao Zhao, Guangyun Wang, Hanyu Yuan, Guangsheng Guo, Xiayan Wang","doi":"10.1021/acs.analchem.4c04263","DOIUrl":"https://doi.org/10.1021/acs.analchem.4c04263","url":null,"abstract":"Patients with epidermal growth factor receptor mutant nonsmall cell lung cancer (NSCLC) often fail to treat gefitinib because of secondary drug resistance. The development of tumor drug resistance is closely related to variations in cancer cell metabolism. Single-cell metabolomics analysis can provide unique information about tumor drug resistance. Herein, we constructed a platform to study the secondary resistance of tumor cells based on single-cell metabolomics (sSRTC-scM). A gefitinib-resistant NSCLC cell line (PC9GR) was constructed by increasing the dose step by step. The metabolic profiles of parental PC9 cells and PC9GR cells with different drug resistance levels were detected by intact living-cell electrolaunching ionization mass spectrometry at the single-cell level. The data were analyzed by statistical methods such as t-SNE, variance, volcano plot, heat map, and metabolic pathway analysis. Using this platform, we found that the metabolic fingerprints of PC9GR cells can evaluate drug resistance degrees. The metabolic fingerprints continue to be altered with the increase of drug resistance. We revealed 19 metabolic markers of secondary resistance by variance analysis and clarified that the glycerophospholipid metabolic pathway of PC9GR cells changed significantly. In addition, we found that with the increase in drug resistance levels, the heterogeneity of single-cell metabolism became greater and the number of cells with weak drug resistance gradually decreased. This phenomenon can be utilized to illustrate the drug resistance degrees of PC9GR cells. This study provides diagnostic markers for evaluating the drug resistance of tumors and gives new insight into overcoming the secondary resistance of tumors.","PeriodicalId":27,"journal":{"name":"Analytical Chemistry","volume":"112 1","pages":""},"PeriodicalIF":7.4,"publicationDate":"2024-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142867378","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"In Situ and In Vivo Evaluation of Multiplex Protein-Specific Glycosylation of Tumors with a Dual-SERS Encoding Strategy","authors":"Shan Wu, Yuru Wang, Yuhui Yang, Chaoyi Yang, Ayidana Jiensi, Chengyao Geng, Huangxian Ju, Yunlong Chen","doi":"10.1021/acs.analchem.4c05695","DOIUrl":"https://doi.org/10.1021/acs.analchem.4c05695","url":null,"abstract":"A dual-SERS encoding strategy was designed for in situ and in vivo evaluation of multiplex protein-specific glycosylation of tumors. The dual-SERS encoding strategy consisted of two pairs of dual gold nanoprobes with different diameters of 10 and 30 nm, which were encoded with four different and distinguishable Raman signal molecules. The 10 and 30 nm gold nanoprobes (Au10 and Au30 probes, respectively) were further modified with lectins and aptamers to recognize the target glycans and proteins, respectively. After sequential binding to the target glycans and proteins, the adjacent Au10 and Au30 probes could emit strong surface-enhanced Raman scattering (SERS) signals to indicate the multiplex protein-specific glycosylation information on cells and in vivo, which can reveal in situ the distribution differences of different tumor markers in the central and marginal regions of tumors. This strategy has been successfully applied for in situ imaging and evaluation of the MUC1 and EpCAM-specific Sia and Gal/GalNAc information on cell surfaces and tumor xenografted mice, providing a convenient and powerful tool to study protein-specific glycosylation-related physiological and pathological mechanisms.","PeriodicalId":27,"journal":{"name":"Analytical Chemistry","volume":"31 1","pages":""},"PeriodicalIF":7.4,"publicationDate":"2024-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142867377","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Top-Down Computational Design of Molecule Recognition Peptides (MRPs) for Enzyme-Peptide Self-Assembly and Chemiluminescent Biosensing","authors":"Lihong Yu, Chenglin Yang, Shuting Cheng, Qianqian Jiang, Yuehong Pang, Xiaofang Shen","doi":"10.1021/acs.analchem.4c04295","DOIUrl":"https://doi.org/10.1021/acs.analchem.4c04295","url":null,"abstract":"The recognition of small molecules plays a crucial role in disease diagnosis, environmental assessment, and food safety. Currently, their recognition elements predominantly rely on antibodies and aptamers while suffering from a limitation of the complex screening process due to the low immunogenicity of small molecules. Herein, we present a top-down computational design strategy for molecule recognition peptides (MRPs) for enzyme-peptide self-assembly and chemiluminescence biosensing. Taking ochratoxin A (OTA) as an illustrative example, human serum albumin (HSA) was selected as the parental protein due to its high affinity for OTA binding. Through iterative computational simulations involving the binding domain of the HSA-OTA complex, our strategy identified a specific 15-mer MRP (RLKCASLKFGERAFK), which possesses excellent binding affinity (38.02 ± 1.24 nM) against OTA. Molecular dynamics simulations revealed that the 15-mer MRP unfolds into a flexible short chain with high affinity for OTA, but exhibits weak or no binding affinity with five structurally similar mycotoxins. Furthermore, we developed a novel enzyme-peptide self-assembly approach mediated by calcium(II) to obtain nanoflowers, which integrates both the recognition element (MRP) and the signal translator (enzyme) for chemiluminescence biosensing. The assembled nanoflowers allow MRPs to be directly utilized as a tracer for OTA biosensing without labeling or secondary antibodies. This computational-to-application approach offers a new route for small-molecule recognition.","PeriodicalId":27,"journal":{"name":"Analytical Chemistry","volume":"20 1","pages":""},"PeriodicalIF":7.4,"publicationDate":"2024-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142867374","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"TG-MS Analysis for Elemental Composition of Organic Matters and Their Structural Properties","authors":"Lin Lin, Sasha Yang, Fuhong Zhang, Muxin Liu, Dong Liu, Lei Shi","doi":"10.1021/acs.analchem.4c05453","DOIUrl":"https://doi.org/10.1021/acs.analchem.4c05453","url":null,"abstract":"A novel approach for determining the elemental content of organic matter through thermal gravimetric analysis coupled online with a mass spectrometer (TG-MS) is disclosed. This method not only yields results equivalent to ASTM analysis but also provides insight into the covalent bond structure within the sample. The principle of this technique consists of the combustion of organic matter in an oxygen-enriched environment within the thermogravimetric (TG) system. The gases generated during combustion, including carbon-containing gases such as CO₂ and CO, hydrogen-containing gases such as H₂O, nitrogen-containing gases such as NO₂ and NO, and sulfur-containing gases such as SO₂, are then analyzed using online MS. Quantitative analysis of these gases is accomplished via an external standard method, facilitating the determination of the elemental content of the organic matters. The experiment employed a temperature-programmed heating rate of 10 °C/min, a carrier gas flow rate of 100 mL/min, and an oxygen concentration of 50% by volume. We conducted tests on a range of 23 samples, including coal, heavy oil, oil shale, and biomass. The results for coal, oil shale, and biomass samples were consistent with ASTM standards, while the heavy oil samples demonstrated slightly lower values compared with ASTM methods. Furthermore, we probed into the mass loss and gas generation processes that occur during the combustion of samples, and these results enhance the understanding of the mechanism of organic matter combustion as well as that of the covalent bond structure of organic matters.","PeriodicalId":27,"journal":{"name":"Analytical Chemistry","volume":"147 1","pages":""},"PeriodicalIF":7.4,"publicationDate":"2024-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142857946","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Umbrella Sampling MD Simulations for Retention Prediction in Peptide Reversed-phase Liquid Chromatography","authors":"Pablo M. Scrosati, Evelyn H. MacKay-Barr, Lars Konermann","doi":"10.1021/acs.analchem.4c05428","DOIUrl":"https://doi.org/10.1021/acs.analchem.4c05428","url":null,"abstract":"Reversed-phase liquid chromatography (RPLC) is an essential tool for separating complex mixtures such as proteolytic digests in bottom-up proteomics. There is growing interest in methods that can predict the RPLC retention behavior of peptides and other analytes. Already, existing algorithms provide excellent performance based on empirical rules or large sets of RPLC training data. Here we explored a new type of retention prediction strategy that relies on first-principles modeling of peptide interactions with a C18 stationary phase. We recently demonstrated that molecular dynamics (MD) simulations can provide atomistic insights into the behavior of peptides under RPLC conditions (<i>Anal</i>. <i>Chem</i>. <b>2023</b>, 95, 3892). However, the current work found that it is problematic to use conventional MD data for retention prediction, evident from a poor correlation between experimental retention times and MD-generated “fraction bound” values. We thus turned to umbrella sampling MD, a complementary technique that has previously been applied to probe noncovalent contacts in other types of systems. By restraining the peptide dynamic motions at various positions inside a C18-lined pore, we determined the free energy of the system as a function of peptide-stationary phase distance. Δ<i>G</i>_binding values determined in this way under various mobile phase conditions were linearly correlated with experimental retention times of tryptic test peptides. This work opens retention prediction avenues for novel types of stationary and mobile phases, and for peptides (or other analytes) having arbitrary chemical properties, without the need for RPLC reference data. Umbrella sampling can be used as a stand-alone tool, or it may serve to enhance existing retention prediction algorithms.","PeriodicalId":27,"journal":{"name":"Analytical Chemistry","volume":"13 1","pages":""},"PeriodicalIF":7.4,"publicationDate":"2024-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142867383","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Advanced Mass-Spectra-Based Machine Learning for Predicting the Toxicity of Traditional Chinese Medicines","authors":"Chen Jia, Xiaofang Li, Song Hu, Guohong Liu, Jiansong Fang, Xiaoxia Zhou, Xiliang Yan, Bing Yan","doi":"10.1021/acs.analchem.4c05311","DOIUrl":"https://doi.org/10.1021/acs.analchem.4c05311","url":null,"abstract":"Traditional Chinese medicine (TCM) has been a cornerstone of health care for centuries, valued for its preventive and therapeutic properties. However, recent decades have revealed significant toxicological concerns associated with TCMs due to their complex chemical compositions. Traditional QSAR (quantitative structure–activity relationships) models, which predict toxicity based on chemical structures, face challenges with the intricate nature of TCM compounds. In this study, we effectively resolved this issue by correlating the toxicity of TCMs with advanced analytical descriptors from electron ionization mass spectra (EI-MS) data. The optimal classification model achieved a balanced accuracy of over 0.74. Through interpretable machine learning models, we identified specific toxic components, such as 13-hexyloxacyclotridec-10-en-2-one and loliolide. We applied molecular dynamics (MD) simulations to explore the interactions of identified toxic components with crucial protein targets, using hepatic cytochrome P450 3A4 as an example. This novel approach not only enhances our understanding of the toxicological profiles of TCMs but also maximizes their therapeutic benefits while minimizing adverse effects. More importantly, our findings support the application of analytical descriptor-based machine learning in predicting the toxicity of unknown mixtures in the real environment.","PeriodicalId":27,"journal":{"name":"Analytical Chemistry","volume":"114 1","pages":""},"PeriodicalIF":7.4,"publicationDate":"2024-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142858071","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}