Analytical and Bioanalytical Chemistry最新文献

{"title":"Regulating the surface chemistry of covalent organic frameworks for enhancement cationic dye removal and identification.","authors":"Xiaoli Zhou, Wenjuan Lei, Xiaohuan Qin, Xiaofen Lai, Kun Hu, Shulin Zhao","doi":"10.1007/s00216-024-05687-x","DOIUrl":"10.1007/s00216-024-05687-x","url":null,"abstract":"<p><p>Simultaneous removal and identification of trace-level cationic dye pollutants from water is both important and challenging owing to their highly polar and complex sample matrices. In this study, three covalent organic frameworks (COFs) were synthesized using 2, 4, 6-triformylphloroglucinol with ethidium bromide (EB) containing positively charged groups, 3, 5-diaminobenzoic acid (DABA) containing negatively charged groups, and p-phenylenediamine (Pa) lacking charged groups. These were named EB-COFs, TpPa-1, and DP-COFs, respectively, and were employed as adsorbents for the extraction and identification of cationic dyes. The adsorption performance of the three COFs toward methylene blue (MB) and crystal violet (CV) was investigated. By incorporating carboxyl groups into DP-COFs, the surface chemistry of the adsorbent was effectively tailored, enabling complete exploitation of selective cationic sites. This facilitated dynamic interactions with cationic dyes through multiple adsorption mechanisms, including electrostatic, π-π, and H-bonding interactions. DP-COFs exhibited high adsorption capacities for MB and CV, achieving 383 and 326 mg g^-1, respectively. The adsorption behavior was further analyzed using adsorption isothermals, kinetics, and thermodynamics. Moreover, DP-COFs were employed as a matrix in laser desorption/ionization time-of-flight mass spectrometry (LDI-TOF MS) to adsorb and directly identify both cationic dyes without the need for an elution process. This approach demonstrated high sensitivity, high reproducibility, low background interference, and excellent salt tolerance. The limits of detection for MB and CV were 0.12 and 0.04 ng mL^-1, respectively, representing improvements of 166-fold and 225-fold compared with using DP-COFs solely as a matrix. Recovery rates of both dyes in spiked industrial wastewater and lake water samples ranged from 81.4 to111.1% with RSDs of 1.9-6.3%. These results highlight the high reliability of the proposed method.</p>","PeriodicalId":462,"journal":{"name":"Analytical and Bioanalytical Chemistry","volume":" ","pages":"675-685"},"PeriodicalIF":3.8,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142793916","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}

{"title":"Inter-tissue glycan heterogeneity: site-specific glycoform analysis of mouse tissue N-glycoproteomes using MS1-based glycopeptide detection method assisted by lectin microarray.","authors":"Chiaki Nagai-Okatani, Azusa Tomioka, Daisuke Tominaga, Hiroaki Sakaue, Atsushi Kuno, Hiroyuki Kaji","doi":"10.1007/s00216-024-05686-y","DOIUrl":"10.1007/s00216-024-05686-y","url":null,"abstract":"<p><p>To understand the biological and pathological functions of protein glycosylation, the glycan heterogeneities for each glycosite in a single glycoprotein need to be elucidated depending on the type and status of cells. For this aim, a reliable strategy is needed to compare site-specific glycoforms of multiple glycoprotein samples in a comprehensive manner. To analyze this \"inter-heterogeneity\" of samples, we previously introduced an MS1-based glycopeptide detection method, \"Glyco-RIDGE.\" Here, to elucidate inter-tissue glycan heterogeneities, this estimation method was applied to site-specific N-glycoforms of glycoproteins from six normal mouse tissues (liver, kidney, spleen, pancreas, stomach, and testis). The analyses of desialylated glycopeptides estimated 11,325 site-specific N-glycoforms with 239 glycan compositions at 1260 sites (1122 non-redundant core peptides) in 800 glycoproteins, revealing inter-tissue differences in macro-, micro-, and meta-glycan heterogeneities. To obtain detailed information on their glycan features and tissue distribution, the Glyco-RIDGE results were compared with laser microdissection-assisted lectin microarray (LMD-LMA)-based mouse tissue glycome mapping data deposited on LM-GlycomeAtlas, as well as MS-based mouse tissue glycome data deposited on GlycomeAtlas. This integrated approach supported the certainty of Glyco-RIDGE results and suggested that inter-tissue differences exist in glycan motifs, such as alpha-galactose and bisecting N-acetylglucosamine, in both whole tissue glycomes and specific glycoproteins, Anpep and Lamc1. In addition, the comparison with LMD-LMA-based tissue glycome mapping data suggested the possibility of estimating the tissue distribution of the assigned glycans and glycopeptides. Taken together, these findings demonstrate the utility of an integrated approach using MS assisted by LMA for large-scale analyses.</p>","PeriodicalId":462,"journal":{"name":"Analytical and Bioanalytical Chemistry","volume":" ","pages":"973-988"},"PeriodicalIF":3.8,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142826783","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}

{"title":"Toward integration of glycan chemical databases: an algorithm and software tool for extracting sugars from chemical structures.","authors":"Masaaki Matsubara, Evan E Bolton, Kiyoko F Aoki-Kinoshita, Issaku Yamada","doi":"10.1007/s00216-024-05508-1","DOIUrl":"10.1007/s00216-024-05508-1","url":null,"abstract":"<p><p>Integration of glycan-related databases between different research fields is essential in glycoscience. It requires knowledge across the breadth of science because most glycans exist as glycoconjugates. On the other hand, especially between chemistry and biology, glycan data has not been easy to integrate due to the huge variety of glycan structure representations. We have developed WURCS (Web 3.0 Unique Representation of Carbohydrate Structures) as a notation for representing all glycan structures uniquely for the purpose of integrating data across scientific data resources. While the integration of glycan data in the field of biology has been greatly advanced, in the field of chemistry, progress has been hampered due to the lack of appropriate rules to extract sugars from chemical structures. Thus, we developed a unique algorithm to determine the range of structures allowed to be considered as sugars from the structural formulae of compounds, and we developed software to extract sugars in WURCS format according to this algorithm. In this manuscript, we show that our algorithm can extract sugars from glycoconjugate molecules represented at the molecular level and can distinguish them from other biomolecules, such as amino acids, nucleic acids, and lipids. Available as software, MolWURCS is freely available and downloadable ( https://gitlab.com/glycoinfo/molwurcs ).</p>","PeriodicalId":462,"journal":{"name":"Analytical and Bioanalytical Chemistry","volume":" ","pages":"945-956"},"PeriodicalIF":3.8,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142103057","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}

{"title":"Cooperation of GlycoPOST and UniCarb-DR towards a comprehensive glycomics data repository workflow.","authors":"Yushi Takahashi, Niclas G Karlsson, Shujiro Okuda, Kiyoko F Aoki-Kinoshita","doi":"10.1007/s00216-024-05673-3","DOIUrl":"10.1007/s00216-024-05673-3","url":null,"abstract":"<p><p>In glycomics, two data repositories, GlycoPOST and UniCarb-DR, have been developed to accumulate experimental data generated by glycomics and glycoproteomics mass spectrometry experiments. In order to enhance the interrelation between these two data repositories, we have upgraded the framework for both of them; we have unified their respective data submission systems and constructed a mechanism that can automatically cross-reference corresponding entries. In addition to this integration, the metadata registration system was also extended so that liquid chromatography experiments can be reported according to standard reporting guidelines specified by MIRAGE (Minimum Information Required for A Glycomics Experiment). Furthermore, by augmenting the visualization software used in UniCarb-DR, we have been able to introduce new functionality into GlycoPOST to enable the visualization of unpublished experimental identification result files during an embargo period defined by the data provider. As a result, this work introduces a new framework by which glycomics researchers can take advantage of GlycoPOST and UniCarb-DR in an integrated manner.</p>","PeriodicalId":462,"journal":{"name":"Analytical and Bioanalytical Chemistry","volume":" ","pages":"1015-1023"},"PeriodicalIF":3.8,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142749761","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}

{"title":"GlyCompute: towards the automated analysis of protein N-linked glycosylation kinetics via an open-source computational framework.","authors":"Konstantinos Flevaris, Pavlos Kotidis, Cleo Kontoravdi","doi":"10.1007/s00216-024-05522-3","DOIUrl":"10.1007/s00216-024-05522-3","url":null,"abstract":"<p><p>Understanding the complex biosynthetic pathways of glycosylation is crucial for the expanding field of glycosciences. Computer-aided glycosylation analysis has greatly benefited in recent years from the development of tools found in web-based portals and open-source libraries. However, the in silico analysis of cellular glycosylation kinetics is underrepresented in current glycoscience-related tools and databases. This could be partly attributed to the limited accessibility of kinetic models developed using proprietary software and the difficulty in reliably parameterising such models. This work aims to address these challenges by proposing GlyCompute, an open-source framework demonstrating a novel, streamlined approach for the assembly, simulation, and parameterisation of kinetic models of protein N-linked glycosylation. Specifically, given one or more sets of experimentally observed N-glycan structures and their relative abundances, minimum representations of a glycosylation reaction network are generated. The topology of the resulting networks is then used to automatically assemble the material balances and kinetic mechanisms underpinning the mathematical model. To match the experimentally observed relative abundances, a sequential parameter estimation strategy using Bayesian inference is proposed, with stages determined automatically based on the underlying network topology. The proposed framework was tested on a case study involving the simultaneous fitting of the kinetic model to two protein N-linked glycoprofiles produced by the same CHO cell culture, showing good agreement with experimental observations. We envision that GlyCompute could help glycoscientists gain quantitative insights into the effect of enzyme kinetics and their perturbations on experimentally observed glycoprofiles in biomanufacturing and clinical settings.</p>","PeriodicalId":462,"journal":{"name":"Analytical and Bioanalytical Chemistry","volume":" ","pages":"957-972"},"PeriodicalIF":3.8,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142338695","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}

{"title":"Deep structure-level N-glycan identification using feature-induced structure diagnosis integrated with a deep learning model.","authors":"Suideng Qin, Zhixin Tian","doi":"10.1007/s00216-024-05505-4","DOIUrl":"10.1007/s00216-024-05505-4","url":null,"abstract":"<p><p>Being a widely occurring protein post-translational modification, N-glycosylation features unique multi-dimensional structures including sequence and linkage isomers. There have been successful bioinformatics efforts in N-glycan structure identification using N-glycoproteomics data; however, symmetric \"mirror\" branch isomers and linkage isomers are largely unresolved. Here, we report deep structure-level N-glycan identification using feature-induced structure diagnosis (FISD) integrated with a deep learning model. A neural network model is integrated to conduct the identification of featured N-glycan motifs and boosts the process of structure diagnosis and distinction for linkage isomers. By adopting publicly available N-glycoproteomics datasets of five mouse tissues (17,136 intact N-glycopeptide spectrum matches) and a consideration of 23 motif features, a deep learning model integrated with a convolutional autoencoder and a multilayer perceptron was trained to be capable of predicting N-glycan featured motifs in the MS/MS spectra with previously identified compositions. In the test of the trained model, a prediction accuracy of 0.8 and AUC value of 0.95 were achieved; 5701 previously unresolved N-glycan structures were assigned by matched structure-diagnostic ions; and by using an explainable learning algorithm, two new fragmentation features of m/z = 674.25 and m/z = 835.28 were found to be significant to three N-glycan structure motifs with fucose, NeuAc, and NeuGc, proving the capability of FISD to discover new features in the MS/MS spectra.</p>","PeriodicalId":462,"journal":{"name":"Analytical and Bioanalytical Chemistry","volume":" ","pages":"1001-1014"},"PeriodicalIF":3.8,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142103041","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}

{"title":"Evaluation of combined workflows for multimodal mass spectrometry imaging of elements and lipids from the same tissue section.","authors":"Tassiani Sarretto, Mika T Westerhausen, Jayden C Mckinnon, David P Bishop, Shane R Ellis","doi":"10.1007/s00216-024-05696-w","DOIUrl":"10.1007/s00216-024-05696-w","url":null,"abstract":"<p><p>The wide range of mass spectrometry imaging (MSI) technologies enables the spatial distributions of many analyte classes to be investigated. However, as each approach is best suited to certain analytes, combinations of different MSI techniques are increasingly being explored to obtain more chemical information from a sample. In many cases, performing a sequential analysis of the same tissue section is ideal to enable a direct correlation of multimodal data. In this work, we explored different workflows that allow sequential lipid and elemental imaging on the same tissue section using atmospheric pressure laser desorption/ionisation-plasma post-ionisation-MSI (AP-MALDI-PPI-MSI) and laser ablation-inductively coupled plasma-MSI (LA-ICP-MSI), respectively. It is found that performing lipid imaging first using matrix-coated samples, followed by elemental imaging on matrix-coated samples, provides high-quality MSI datasets for both lipids and elements, with the resulting distributions being similar to those obtained when each is performed in isolation. The effect of matrix removal prior to elemental imaging, and of performing elemental imaging first were also investigated but found to generally yield lower quality elemental imaging data but comparable lipid imaging data. Finally, we used the ability to acquire both elemental and lipid imaging data from the same section to investigate the spatial correlations between different lipids (including ceramides, phosphatidylethanolamine, and hexosylceramides) and elements within mouse brain tissue.</p>","PeriodicalId":462,"journal":{"name":"Analytical and Bioanalytical Chemistry","volume":" ","pages":"705-719"},"PeriodicalIF":3.8,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11772510/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142998157","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Glycoscience data content in the NCBI Glycans and PubChem.","authors":"Sunghwan Kim, Jian Zhang, Tiejun Cheng, Qingliang Li, Evan E Bolton","doi":"10.1007/s00216-024-05459-7","DOIUrl":"10.1007/s00216-024-05459-7","url":null,"abstract":"<p><p>Studying glycans and their functions in the body aids in the understanding of disease mechanisms and developing new treatments. This necessitates resources that provide comprehensive glycan data integrated with relevant information from other scientific fields such as genomics, genetics, proteomics, metabolomics, and chemistry. The present paper describes two resources at the U.S. National Center for Biotechnology Information (NCBI), the NCBI Glycans and PubChem, which provide glycan-related information useful for the glycoscience research community. The NCBI Glycans ( https://www.ncbi.nlm.nih.gov/glycans/ ) is a dedicated website for glycobiology data content at NCBI and provides quick access to glycan-related information scattered across multiple NCBI databases as well as other information resources external to NCBI. Importantly, the NCBI Glycans hosts the official web page for the symbol nomenclature for glycans (SNFG), which is the standard graphical representation of glycan structures recommended for scientific publication. On the other hand, PubChem ( https://pubchem.ncbi.nlm.nih.gov ) is a research-focused, large-scale public chemical database, containing a substantial number of glycan-containing records and is integrated with important glycoscience resources like GlyTouCan, GlyCosmos, and GlyGen. PubChem organizes glycan-related information within multiple data collections (i.e., Substance, Compound, Protein, Gene, Pathway, and Taxonomy) and provides various tools and services that allow users to access them both interactively through a web browser and programmatically through a REST-ful interface, including PUG-View. The NCBI Glycans and PubChem highlight glycan-related data and improve their accessibility, helping scientists exploit these data in their research.</p>","PeriodicalId":462,"journal":{"name":"Analytical and Bioanalytical Chemistry","volume":" ","pages":"865-878"},"PeriodicalIF":3.8,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141970323","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}

{"title":"Updates implemented in version 4 of the GlyCosmos Glycoscience Portal.","authors":"Sunmyoung Lee, Tamiko Ono, Shiota Masaaki, Akihiro Fujita, Masaaki Matsubara, Achille Zappa, Issaku Yamada, Kiyoko F Aoki-Kinoshita","doi":"10.1007/s00216-024-05692-0","DOIUrl":"10.1007/s00216-024-05692-0","url":null,"abstract":"<p><p>Glycosylation, characterized by its complexity and diversity, is a common system across all domains of life. The glycosylation of proteins or lipids imparts them with structural and functional roles, ranging from development to infectious or Mendelian disease. The high-throughput-based omics data has revealed that glycans are involved in important cellular processes. Comprehensive knowledge of glycosylation has contributed not only to the fundamental concepts in glycoscience but also to its applications, including the development of molecular markers for diagnosis and therapeutic tools for treating diseases. The GlyCosmos Glycoscience Portal (GlyCosmos) has undergone significant updates to better support the scientific community in studying glycosylation-related phenomena. Key enhancements include the integration of expanded datasets linking glycans to other omics fields, improved tools for glycan structure prediction and analysis, and upgraded visualization capabilities to streamline data interpretation. A strengthened focus on data standardization has also been introduced, fostering interoperability between glycoscience resources and external databases. Since its release in 2019, the portal has seen a fivefold increase in user engagement, reflecting its growing relevance. These recent advancements aim to provide researchers with a more comprehensive and user-friendly platform, enabling deeper insights into glycan roles in cellular processes and disease mechanisms. GlyCosmos will continue to evolve, prioritizing community needs and advancing the integration of glycoscience with broader biological and biomedical research.</p>","PeriodicalId":462,"journal":{"name":"Analytical and Bioanalytical Chemistry","volume":" ","pages":"907-919"},"PeriodicalIF":3.8,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142845463","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}

{"title":"Role of membrane porosity in passive sampling of aquatic contaminants for stable isotope analysis: enhancement of analyte accumulation rates and selectivity.","authors":"Armela Tafa, Anat Bernstein, Martin Elsner, Rani Bakkour","doi":"10.1007/s00216-025-05756-9","DOIUrl":"https://doi.org/10.1007/s00216-025-05756-9","url":null,"abstract":"<p><p>Compound-specific isotope analysis (CSIA) is a potent method for illustrating the in situ degradation of aquatic contaminants. However, its application to surface and groundwater is hindered by low contaminant concentrations, typically in the nanogram-per-litre range, requiring the processing of large water volumes. Polar organic chemical integrative samplers (POCIS) have shown promising results when combined with CSIA, yet their extended deployment time to accumulate sufficient analyte mass remains a major limitation. In our study, we addressed this issue by increasing the pore size of the polyethersulfone membrane (PES) from 0.1 to 8 <math><mi>μ</mi></math> m. This resulted in significant increases in the mass accumulation rates of atrazine (3.5-fold), S-metolachlor (3.4-fold), and boscalid (3.0-fold). Importantly, the larger pore sizes did not compromise isotopic integrity, with <math><mrow><mi>Δ</mi> <msup><mi>δ</mi> <mn>13</mn></msup> </mrow> </math> C <math><mrow><mo>≤</mo> <mo>+</mo> <mn>0.4</mn> <mo>±</mo> <mn>0.1</mn></mrow> </math> ‰ and <math><mrow><mi>Δ</mi> <msup><mi>δ</mi> <mn>15</mn></msup> </mrow> </math> N <math><mrow><mo>≤</mo> <mo>-</mo> <mn>0.6</mn> <mo>±</mo> <mn>0.4</mn></mrow> </math> ‰, both within accepted uncertainties. Additionally, we observed an enhanced selectivity of the larger pores towards the target analytes over humic acids, whereas no significant increase in (bio)fouling potential was detected for the 8 <math><mi>μ</mi></math> m membrane, as demonstrated by gravimetric analysis, SEM measurements, mass accumulation rates, and isotope ratios of fouled and unfouled POCIS. Our findings show that increasing the membrane pore size from 0.1 to 8 <math><mi>μ</mi></math> m reduces deployment time and expedites the accumulation of analyte mass required for gas chromatography isotope ratio mass spectrometry, offering a promising method to expand CSIA for low-concentration pesticide analysis in the field.</p>","PeriodicalId":462,"journal":{"name":"Analytical and Bioanalytical Chemistry","volume":" ","pages":""},"PeriodicalIF":3.8,"publicationDate":"2025-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143062907","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}