Analytical biochemistry最新文献_第9页

Isolation and characterization of ssDNA aptamers against BipD antigen of Burkholderia pseudomallei 针对假丝酵母伯克霍尔德氏菌 BipD 抗原的 ssDNA 短肽的分离与表征

IF 2.6 4区生物学

Analytical biochemistry Pub Date : 2024-08-28 DOI: 10.1016/j.ab.2024.115655

Kasturi Selvam , Mohamad Ahmad Najib , Muhammad Fazli Khalid , Muhammad Hafiznur Yunus , Habibah A. Wahab , Azian Harun , Ummu Afeera Zainulabid , Khairul Mohd Fadzli Mustaffa , Ismail Aziah

{"title":"Isolation and characterization of ssDNA aptamers against BipD antigen of Burkholderia pseudomallei","authors":"Kasturi Selvam , Mohamad Ahmad Najib , Muhammad Fazli Khalid , Muhammad Hafiznur Yunus , Habibah A. Wahab , Azian Harun , Ummu Afeera Zainulabid , Khairul Mohd Fadzli Mustaffa , Ismail Aziah","doi":"10.1016/j.ab.2024.115655","DOIUrl":"10.1016/j.ab.2024.115655","url":null,"abstract":"<div><h3>Background</h3><p>Melioidosis is difficult to diagnose due to its wide range of clinical symptoms. The culture method is time-consuming and less sensitive, emphasizing the importance of rapid and accurate diagnostic tests for melioidosis. <em>Burkholderia</em> invasion protein D (BipD) of <em>Burkholderia pseudomallei</em> is a potential diagnostic biomarker. This study aimed to isolate and characterize single-stranded DNA aptamers that specifically target BipD.</p></div><div><h3>Methods</h3><p>The recombinant BipD protein was produced, followed by isolation of BipD-specific aptamers using Systematic Evolution of Ligands by EXponential enrichment. The binding affinity and specificity of the selected aptamers were evaluated using Enzyme-Linked Oligonucleotide Assay.</p></div><div><h3>Results</h3><p>The fifth SELEX cycle showed a notable enrichment of recombinant BipD protein-specific aptamers. Sequencing analysis identified two clusters with a total of seventeen distinct aptamers. AptBipD1, AptBipD13, and AptBipD50 were chosen based on their frequency. Among them, AptBipD1 exhibited the highest binding affinity with a <em>K</em><sub>d</sub> value of 1.0 μM for the recombinant BipD protein. Furthermore, AptBipD1 showed significant specificity for <em>B. pseudomallei</em> compared to other tested bacteria.</p></div><div><h3>Conclusion</h3><p>AptBipD1 is a promising candidate for further development of reliable, affordable, and efficient point-of-care diagnostic tests for melioidosis.</p></div>","PeriodicalId":7830,"journal":{"name":"Analytical biochemistry","volume":"695 ","pages":"Article 115655"},"PeriodicalIF":2.6,"publicationDate":"2024-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142103680","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Erratum to “Prediction of lysine HMGylation sites using multiple feature extraction and fuzzy support vector machine” [Anal. Biochem. 663 (2023), 115032] 对 "利用多重特征提取和模糊支持向量机预测赖氨酸 HMGylation 位点 "的勘误 [Anal. Biochem.

IF 2.6 4区生物学

Analytical biochemistry Pub Date : 2024-08-26 DOI: 10.1016/j.ab.2024.115652

Zhe Ju, Shi-Yun Wang

引用次数: 0

Erratum to “Predicting lysine lipoylation sites using bi-profile bayes feature extraction and fuzzy support vector machine algorithm” [Anal. Biochem. 561 (2018), 11–17] 对 "利用双轮廓贝叶斯特征提取和模糊支持向量机算法预测赖氨酸脂酰化位点 "的勘误 [Anal. Biochem. 561 (2018), 11-17].

IF 2.6 4区生物学

Analytical biochemistry Pub Date : 2024-08-26 DOI: 10.1016/j.ab.2024.115653

Zhe Ju, Shi-Yun Wang

引用次数: 0

The development of machine learning approaches in two-dimensional NMR data interpretation for metabolomics applications 开发用于代谢组学应用的二维核磁共振数据解读的机器学习方法。

IF 2.6 4区生物学

Analytical biochemistry Pub Date : 2024-08-24 DOI: 10.1016/j.ab.2024.115654

Julie Pollak , Moses Mayonu , Lin Jiang , Bo Wang

{"title":"The development of machine learning approaches in two-dimensional NMR data interpretation for metabolomics applications","authors":"Julie Pollak , Moses Mayonu , Lin Jiang , Bo Wang","doi":"10.1016/j.ab.2024.115654","DOIUrl":"10.1016/j.ab.2024.115654","url":null,"abstract":"<div><p>Metabolomics has been widely applied in human diseases and environmental science to study the systematic changes of metabolites over diverse types of stimuli. NMR-based metabolomics has been widely used, but the peak overlap problems in the one-dimensional (1D) NMR spectrum could limit the accuracy of quantitative analysis for metabolomics applications. Two-dimensional (2D) NMR has been applied to solve the 1D NMR overlap problem, but the data processing is still challenging. In this study, we built an automatic approach to process the 2D NMR data for quantitative applications using machine learning approaches. Partial least square discriminant analysis (PLS-DA), artificial neural network classification (ANN-DA), gradient boosted trees classification (XGBoost-DA), and artificial deep learning neural network classification (ANNDL-DA) were applied in combination with an automatic peak selection approach. Standard mixtures, sea anemone extracts, and mouse fecal samples were tested to demonstrate the approach. Our results showed that ANN-DA and ANNDL-DA have high accuracy in selecting 2D NMR peaks (around 90 %), which have a high potential application in 2D NMR-based metabolomics quantitively study, while PLS-DA and XGBoost-DA showed limitations in either data variation or overfitting. Our study built an automatic approach to applying 2D NMR data to routine quantitative analysis in metabolomics.</p></div>","PeriodicalId":7830,"journal":{"name":"Analytical biochemistry","volume":"695 ","pages":"Article 115654"},"PeriodicalIF":2.6,"publicationDate":"2024-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142071781","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Spectrofluorometric determination of ascorbic acid in the plasma matrix: Exploring correlation with autism spectrum disorder 分光荧光测定血浆基质中的抗坏血酸：探索与自闭症谱系障碍的相关性。

IF 2.6 4区生物学

Analytical biochemistry Pub Date : 2024-08-21 DOI: 10.1016/j.ab.2024.115649

Adnan Alharbi , Ahmed K. Bamaga , Majed A. Algarni , Maram H. Abduljabbar , Reem M. Alnemari , Yusuf S. Althobaiti , Faisal Alsenani , Ahmed H. Abdelazim , Atiah H. Almalki

{"title":"Spectrofluorometric determination of ascorbic acid in the plasma matrix: Exploring correlation with autism spectrum disorder","authors":"Adnan Alharbi , Ahmed K. Bamaga , Majed A. Algarni , Maram H. Abduljabbar , Reem M. Alnemari , Yusuf S. Althobaiti , Faisal Alsenani , Ahmed H. Abdelazim , Atiah H. Almalki","doi":"10.1016/j.ab.2024.115649","DOIUrl":"10.1016/j.ab.2024.115649","url":null,"abstract":"<div><p>Ascorbic acid (Vitamin C) is crucial for bodily functions, including collagen synthesis, immune system support and antioxidant defense. Despite autism spectrum disorder's multifactorial nature involving genetic, environmental and neurological factors, robust evidence exploring the association between ascorbic acid and this disorder is notably lacking. This study introduces an innovative spectrofluorometric method to quantify ascorbic acid in the plasma of healthy children and those with autism spectrum disorder. The method relies on the interaction of ascorbic acid with the fluorescent dye propidium iodide. In acidic conditions, propidium iodide undergoes protonation and selectively binds to the negatively charged ascorbic acid forming an ion-pair complex. This complex alters the molecular structure of propidium iodide inducing chemical fluorescence quenching, that can be utilized for ascorbic acid quantification. The developed method undergoes rigorous validation following ICH guidelines, demonstrating a linear relationship within a concentration range of 4–40 μg/mL, with high precision and accuracy metrics. Analysis of real plasma samples from autistic and healthy children reveals clinically and statistically elevated levels of ascorbic acid in those with autism spectrum disorder.</p></div>","PeriodicalId":7830,"journal":{"name":"Analytical biochemistry","volume":"695 ","pages":"Article 115649"},"PeriodicalIF":2.6,"publicationDate":"2024-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141999302","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

NeuroPred-ResSE: Predicting neuropeptides by integrating residual block and squeeze-excitation attention mechanism NeuroPred-ResSE：通过整合残余阻滞和挤压激发注意机制预测神经肽。

IF 2.6 4区生物学

Analytical biochemistry Pub Date : 2024-08-16 DOI: 10.1016/j.ab.2024.115648

Yunyun Liang , Mengyi Cao , Shengli Zhang

{"title":"NeuroPred-ResSE: Predicting neuropeptides by integrating residual block and squeeze-excitation attention mechanism","authors":"Yunyun Liang , Mengyi Cao , Shengli Zhang","doi":"10.1016/j.ab.2024.115648","DOIUrl":"10.1016/j.ab.2024.115648","url":null,"abstract":"<div><p>Neuropeptides play crucial roles in regulating neurological function acting as signaling molecules, which provide new opportunity for developing drugs for the treatment of neurological diseases. Therefore, it is very necessary to develop a rapid and accurate prediction model for neuropeptides. Although a few prediction tools have been developed, there is room for improvement in prediction accuracy by using deep learning approach. In this paper, we establish the NeuroPred-ResSE model based on residual block and squeeze-excitation attention mechanism. Firstly, we extract multi-features by using one-hot coding based on the NT5CT5 sequence, dipeptide deviation from expected mean and natural vector. Then, we integrate residual block and squeeze-excitation attention mechanism, which can capture and identify the most relevant attribute features. Finally, the accuracies of the training set and test set are 97.16 % and 96.60 % based on the 5-fold cross-validation and independent test, respectively, and other evaluation metrics have also obtained satisfactory results. The experimental results show that the performance of the NeuroPred-ResSE model outperforms those of existing state-of-the-art models, and our model is an effective, intelligent and robust prediction tool. The datasets and source codes are available at <span><span>https://github.com/yunyunliang88/NeuroPred-ResSE</span><svg><path></path></svg></span>.</p></div>","PeriodicalId":7830,"journal":{"name":"Analytical biochemistry","volume":"695 ","pages":"Article 115648"},"PeriodicalIF":2.6,"publicationDate":"2024-08-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141999301","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A multifunctional N-GO/PtCo nanocomposite bridged carbon fiber interface for the electrochemical aptasensing of CA15-3 oncomarker 桥接碳纤维界面的多功能 N-GO/PtCo 纳米复合材料，用于 CA15-3 标志物的电化学敏感。

IF 2.6 4区生物学

Analytical biochemistry Pub Date : 2024-08-12 DOI: 10.1016/j.ab.2024.115640

Aqsa Tariq , Sehrish Bilal , Iram Naz , Mian Hasnain Nawaz , Silvana Andreescu , Farhat Jubeen , Amina Arif , Akhtar Hayat

{"title":"A multifunctional N-GO/PtCo nanocomposite bridged carbon fiber interface for the electrochemical aptasensing of CA15-3 oncomarker","authors":"Aqsa Tariq , Sehrish Bilal , Iram Naz , Mian Hasnain Nawaz , Silvana Andreescu , Farhat Jubeen , Amina Arif , Akhtar Hayat","doi":"10.1016/j.ab.2024.115640","DOIUrl":"10.1016/j.ab.2024.115640","url":null,"abstract":"<div><p>The development of integrated analytical devices is crucial for advancing next-generation point-of-care platforms. Herein, we describe a facile synthesis of a strongly catalytic and durable Nitrogen-doped graphene oxide decorated platinum cobalt (NGO-PtCo) nanocomposite that is conjugated with target-specific DNA aptamer (i-e. MUC1) and grown on carbon fiber. Benefitting from the combined features of the high electrochemical surface area of N-doped GO, high capacitance and stabilization by Co, and high kinetic performance by Pt, a robust, multifunctional, and flexible nanotransducer surface was created. The designed platform was applied for the specific detection of a blood-based oncomarker, CA15-3. The electrochemical characterization proved that nanosurface provides a highly conductive and proficient immobilization support with a strong bio-affinity towards MUC1 aptamer. The specific interaction between CA15-3 and the aptamer alters the surface properties of the aptasensor and the electroactive signal probe generated a remarkable increase in signal intensity. The sensor exhibited a wide dynamic range of 5.0 × 10<sup>−2</sup> -200 U mL<sup>−1</sup>, a low limit of detection (LOD) of 4.1 × 10<sup>−2</sup> U mL<sup>−1</sup>, and good reproducibility. The analysis of spiked serum samples revealed outstanding recoveries of up to 100.03 %, by the proposed aptasensor. The aptasensor design opens new revelations in the reliable detection of tumor biomarkers for timely cancer diagnosis.</p></div>","PeriodicalId":7830,"journal":{"name":"Analytical biochemistry","volume":"695 ","pages":"Article 115640"},"PeriodicalIF":2.6,"publicationDate":"2024-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141981533","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Evaluation of simplified ester-linked fatty acid analysis (ELFA) for phospholipid fatty acid (PLFA) analysis of bacterial population 评估用于细菌群体磷脂脂肪酸 (PLFA) 分析的简化酯联脂肪酸分析法 (ELFA)。

IF 2.6 4区生物学

Analytical biochemistry Pub Date : 2024-08-08 DOI: 10.1016/j.ab.2024.115638

Jeong Hyeon Hwang , Tae-Rim Choi , Suwon Kim , Yeda Lee , Yuni Shin , Suhye Choi , Jinok Oh , Sang-Hyoun Kim , Jeong-Hoon Park , Shashi Kant Bhatia , Yung-Hun Yang

{"title":"Evaluation of simplified ester-linked fatty acid analysis (ELFA) for phospholipid fatty acid (PLFA) analysis of bacterial population","authors":"Jeong Hyeon Hwang , Tae-Rim Choi , Suwon Kim , Yeda Lee , Yuni Shin , Suhye Choi , Jinok Oh , Sang-Hyoun Kim , Jeong-Hoon Park , Shashi Kant Bhatia , Yung-Hun Yang","doi":"10.1016/j.ab.2024.115638","DOIUrl":"10.1016/j.ab.2024.115638","url":null,"abstract":"<div><p>Phospholipid fatty acid (PLFA) analysis is used for characterizing microbial communities based on their lipid profiles. This method avoids biases from PCR or culture, allowing data collection in a natural state. However, PLFA is labor-intensive due to lipid fractionation. Simplified ester-linked fatty acid analysis (ELFA), which skips lipid fractionation, offers an alternative. It utilizes base-catalyzed methylation to derivatize only lipids, not free fatty acids, and found glycolipid and neutral lipid fractions are scarcely present in most bacteria, allowing lipid fractionation to be skipped. ELFA method showed a high correlation to PLFA data (r = 0.99) and higher sensitivity than the PLFA method by 1.5–2.57-fold, mainly due to the higher recovery of lipids, which was 1.5–1.9 times higher than with PLFA. The theoretical limit of detection (LOD) and limit of quantification (LOQ) for the ELFA method indicated that 1.54-fold less sample was needed for analysis than with the PLFA method. Our analysis of three bacterial cultures and a simulated consortium revealed the effectiveness of the ELFA method by its simple procedure and enhanced sensitivity for detecting strain-specific markers, which were not detected in PLFA analysis. Overall, this method could be easily used for the population analysis of synthetic consortia.</p></div>","PeriodicalId":7830,"journal":{"name":"Analytical biochemistry","volume":"695 ","pages":"Article 115638"},"PeriodicalIF":2.6,"publicationDate":"2024-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141911373","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Protein-peptide binding residue prediction based on protein language models and cross-attention mechanism 基于蛋白质语言模型和交叉注意力机制的蛋白质-肽结合残基预测

IF 2.6 4区生物学

Analytical biochemistry Pub Date : 2024-08-08 DOI: 10.1016/j.ab.2024.115637

Jun Hu , Kai-Xin Chen , Bing Rao , Jing-Yuan Ni , Maha A. Thafar , Somayah Albaradei , Muhammad Arif

{"title":"Protein-peptide binding residue prediction based on protein language models and cross-attention mechanism","authors":"Jun Hu , Kai-Xin Chen , Bing Rao , Jing-Yuan Ni , Maha A. Thafar , Somayah Albaradei , Muhammad Arif","doi":"10.1016/j.ab.2024.115637","DOIUrl":"10.1016/j.ab.2024.115637","url":null,"abstract":"<div><p>Accurate identifications of protein-peptide binding residues are essential for protein-peptide interactions and advancing drug discovery. To address this problem, extensive research efforts have been made to design more discriminative feature representations. However, extracting these explicit features usually depend on third-party tools, resulting in low computational efficacy and suffering from low predictive performance. In this study, we design an end-to-end deep learning-based method, E2EPep, for protein-peptide binding residue prediction using protein sequence only. E2EPep first employs and fine-tunes two state-of-the-art pre-trained protein language models that can extract two different high-latent feature representations from protein sequences relevant for protein structures and functions. A novel feature fusion module is then designed in E2EPep to fuse and optimize the above two feature representations of binding residues. In addition, we have also design E2EPep+, which integrates E2EPep and PepBCL models, to improve the prediction performance. Experimental results on two independent testing data sets demonstrate that E2EPep and E2EPep + could achieve the average AUC values of 0.846 and 0.842 while achieving an average Matthew's correlation coefficient value that is significantly higher than that of existing most of sequence-based methods and comparable to that of the state-of-the-art structure-based predictors. Detailed data analysis shows that the primary strength of E2EPep lies in the effectiveness of feature representation using cross-attention mechanism to fuse the embeddings generated by two fine-tuned protein language models. The standalone package of E2EPep and E2EPep + can be obtained at <span><span>https://github.com/ckx259/E2EPep.git</span><svg><path></path></svg></span> for academic use only.</p></div>","PeriodicalId":7830,"journal":{"name":"Analytical biochemistry","volume":"694 ","pages":"Article 115637"},"PeriodicalIF":2.6,"publicationDate":"2024-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141911374","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Carbon nanomaterial-based aptasensors for rapid detection of foodborne pathogenic bacteria 基于碳纳米材料的快速检测食源性致病菌的灵敏传感器。

IF 2.6 4区生物学

Analytical biochemistry Pub Date : 2024-08-08 DOI: 10.1016/j.ab.2024.115639

Kiyana Fatemi , Sie Yon Lau , Kehinde Shola Obayomi , Siaw Fui Kiew , Ranil Coorey , Lip Yong Chung , Reza Fatemi , Zoheir Heshmatipour , K.S.D. Premarathna

{"title":"Carbon nanomaterial-based aptasensors for rapid detection of foodborne pathogenic bacteria","authors":"Kiyana Fatemi , Sie Yon Lau , Kehinde Shola Obayomi , Siaw Fui Kiew , Ranil Coorey , Lip Yong Chung , Reza Fatemi , Zoheir Heshmatipour , K.S.D. Premarathna","doi":"10.1016/j.ab.2024.115639","DOIUrl":"10.1016/j.ab.2024.115639","url":null,"abstract":"<div><p>Each year, millions of people suffer from foodborne illness due to the consumption of food contaminated with pathogenic bacteria, which severely challenges global health. Therefore, it is essential to recognize foodborne pathogens swiftly and correctly. However, conventional detection techniques for bacterial pathogens are labor-intensive, low selectivity, and time-consuming, highlighting a notable knowledge gap. A novel approach, aptamer-based biosensors (aptasensors) linked to carbon nanomaterials (CNs), has shown the potential to overcome these limitations and provide a more reliable method for detecting bacterial pathogens. Aptamers, short single-stranded DNA (ssDNA)/RNA molecules, serve as bio-recognition elements (BRE) due to their exceptionally high affinity and specificity in identifying foodborne pathogens such as <em>Salmonella</em> spp., <em>Escherichia coli (E. coli</em>), <em>Listeria monocytogenes</em>, <em>Campylobacter jejuni</em>, and other relevant pathogens commonly associated with foodborne illnesses. Carbon nanomaterials' high surface area-to-volume ratio contributes unique characteristics crucial for bacterial sensing, as it improves the binding capacity and signal amplification in the design of aptasensors. Furthermore, aptamers can bind to CNs and create aptasensors with improved signal specificity and sensitivity. Hence, this review intends to critically review the current literature on developing aptamer functionalized CN-based biosensors by transducer optical and electrochemical for detecting foodborne pathogens and explore the advantages and challenges associated with these biosensors. Aptasensors conjugated with CNs offers an efficient tool for identifying foodborne pathogenic bacteria that is both precise and sensitive to potentially replacing complex current techniques that are time-consuming.</p></div>","PeriodicalId":7830,"journal":{"name":"Analytical biochemistry","volume":"695 ","pages":"Article 115639"},"PeriodicalIF":2.6,"publicationDate":"2024-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141911372","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0