Molecular omics最新文献

{"title":"Multi-omics data integration for topology-based pathway activation assessment and personalized drug ranking.","authors":"Nicolas Borisov, Yaroslav Ilnytsky, Boseon Byeon, Olga Kovalchuk, Igor Kovalchuk","doi":"10.1039/d5mo00151j","DOIUrl":"https://doi.org/10.1039/d5mo00151j","url":null,"abstract":"<p><p>Although multi-omics analysis is popular for revealing diverse physiological effects and biomarkers in many branches of state-of-the-art molecular and cell biology and bioinformatics, there is still no consensus on a gold standard protocol for the integration of various multi-omics profiles into a uniformly shaped system bioinformatics platform. In the current study, we performed the integration of data on DNA methylation, and the expression of coding RNA (mRNA), micro-RNA (miRNA), and long non-coding RNA into a joint platform for calculation of signaling pathway impact analysis (SPIA) and drug efficiency index (DEI). We found that the mirrored and balanced DEI values fitted the DNA methylome data better than the original DEI. Additionally, the protein-coding mRNA-based values correlated more strongly with antisense lncRNA-based values than with miRNA-based values. The whole correlation between the mRNA-based and antisense lncRNA-based values was generally positive. This platform allowed integrative analysis of several levels of gene expression regulation of protein-coding genes and their regulators, including methylation and noncoding RNAs.</p>","PeriodicalId":19065,"journal":{"name":"Molecular omics","volume":" ","pages":""},"PeriodicalIF":2.4,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145200260","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}

{"title":"MOFNet: a deep learning framework for multi-omics data fusion in cancer subtype classification.","authors":"Guangji Zhang, Chunxiao Zhang, Pengpai Li, Duanchen Sun, Zhixia Yang, Zhi-Ping Liu","doi":"10.1039/d5mo00221d","DOIUrl":"https://doi.org/10.1039/d5mo00221d","url":null,"abstract":"<p><strong>Background: </strong>cancer exhibits high molecular and clinical heterogeneity, making accurate subtyping essential for personalized treatment. Traditional single-omics approaches often fail to capture this complexity. Multi-omics integration offers a more holistic understanding, but many existing methods either lack interpretability or fail to model cross-omics correlations effectively.</p><p><strong>Methods: </strong>we developed MOFNet, a novel supervised deep learning framework for multi-omics integration, incorporating a similarity graph pooling (SGO) module and a view correlation discovery network (VCDN). MOFNet processes omics data-including mRNA expression, DNA methylation, and miRNA expression-<i>via</i> omics-specific graph learning and cross-omics label space fusion. Three cancer types-breast cancer (BRCA), low-grade glioma (LGG), and stomach adenocarcinoma (STAD)-were analyzed using datasets from the cancer genome atlas (TCGA). Statistical evaluation was performed using accuracy, weighted F1 score, and macro F1 score across stratified training/testing splits.</p><p><strong>Results: </strong>MOFNet achieved superior performance across all datasets. For BRCA, it obtained an accuracy of 85.17%, F1_weighted of 85.36%, and macro F1 of 80.93%, outperforming all baseline models by up to 18.25%. In LGG and STAD, MOFNet also showed robust gains, with maximum improvements of 23.72% and 21.56%, respectively. Omics ablation studies demonstrated enhanced performance with multi-omics integration. Functional enrichment analysis revealed that MOFNet-identified key features were involved in biologically relevant pathways such as cell cycle regulation, synaptic signaling, and ion transport.</p><p><strong>Conclusions: </strong>MOFNet enables scalable and interpretable multi-omics data fusion for cancer subtype classification, significantly improving predictive accuracy while retaining only 25% of input features. The integration of SGO and VCDN modules offers both biological interpretability and computational efficiency. These results suggest MOFNet's promising application in precision oncology and biomarker discovery.</p>","PeriodicalId":19065,"journal":{"name":"Molecular omics","volume":" ","pages":""},"PeriodicalIF":2.4,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145200191","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}

{"title":"MALDI mass spectrometry imaging in plant and food lipidomics: advances, challenges, and future perspectives.","authors":"G Ventura, M Bianco, I Losito, T R I Cataldi, C D Calvano","doi":"10.1039/d5mo00116a","DOIUrl":"https://doi.org/10.1039/d5mo00116a","url":null,"abstract":"<p><p>Matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) has established itself as a powerful analytical technique for spatially resolved lipidomics, offering unique insights into lipid distribution and metabolism directly within plant and food matrices. Recent methodological and technological advances have markedly improved the spatial resolution, sensitivity, and selectivity of MALDI-MSI, enabling high-definition mapping of complex lipidomes down to the cellular level. This review presents the current state of MALDI-MSI applications in plant and food lipidomics, with a focus on studies that have advanced our understanding of lipid heterogeneity, metabolic pathways, and spatial lipid organization. Special attention is given to the analytical challenges associated with lipid structural diversity, particularly isomerism and isobarism, and to the strategies developed to address these limitations. Emerging applications involving stable isotope labelling, advanced ion mobility spectrometry, and chemical derivatization are also discussed, highlighting their potential to enhance lipid identification and spatial localization. Finally, the review outlines future perspectives, emphasizing the integration of MALDI-MSI with complementary omics approaches and advanced computational tools to accelerate discoveries in plant biology, food quality assessment, and nutritional science.</p>","PeriodicalId":19065,"journal":{"name":"Molecular omics","volume":" ","pages":""},"PeriodicalIF":2.4,"publicationDate":"2025-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145149842","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}

{"title":"Network-driven identification of indisulam neo-substrates for targeted protein degradation.","authors":"Andrew F Jarnuczak, Orli Yogev, Angelo Andres, Stephanie K Ashenden, Cheng Ye, Fiona Pachl, Andrew Zhang, Maria Emanuela Cuomo, Meizhong Jin","doi":"10.1039/d5mo00053j","DOIUrl":"https://doi.org/10.1039/d5mo00053j","url":null,"abstract":"<p><p>Indisulam, a DCAF15-based molecular glue degrader, induces widespread proteome changes with implications for cell division and chromosome segregation. While RBM39 and RBM23 are two well-characterized indisulam neo-substrates, additional targets likely exist. To identify those degradation targets, we applied a network-based approach to prioritize novel neo-substrates from large-scale omics data. Our approach integrates proteome-wide expression measurements with information from publicly accessible databases into a multilayer heterogeneous network. Utilizing a Random Walk with Restart algorithm, we identified a preliminary list of 30 neo-substrates. These proteins are likely interactors with DCAF15 in the presence of indisulam and are subject to subsequent degradation. Experimental validation of hits from the shortlisted candidates confirmed their degradation in a proteasome-dependent manner, supporting their identification as potential novel indisulam neo-substrates. Our work employs established network resources and analytical methods to effectively identify direct targets of the indisulam molecular glue degrader. This approach is readily adaptable for exploring novel targets across other molecular glue systems, enhancing its applicability and value to the drug discovery community.</p>","PeriodicalId":19065,"journal":{"name":"Molecular omics","volume":" ","pages":""},"PeriodicalIF":2.4,"publicationDate":"2025-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145125361","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}

{"title":"<i>Prunus mongolica</i> oil attenuates hepatic fibrosis <i>via</i> a lncRNA-mediated ceRNA network targeting dual PGC-1α/PPARγ and TGF-β/Smad3 pathways.","authors":"YiJie Hou, HongBing Zhou, XiaoGang Li, JiaXing Gao, Hong Chang, Jia Wang, YingChun Bai, ShuYuan Jiang, ShuFang Niu, WanFu Bai, SongLi Shi","doi":"10.1039/d5mo00083a","DOIUrl":"https://doi.org/10.1039/d5mo00083a","url":null,"abstract":"<p><p>Hepatic fibrosis (HF), a reversible yet critical pathological stage in chronic liver disease progression, represents a major global public health challenge. This study systematically investigated the antifibrotic mechanism of <i>Prunus mongolica</i> oil (OIL), an active component derived from traditional medicinal plants, through an integrated approach combining pharmacodynamics, transcriptomics, and molecular biology in carbon tetrachloride (CCl₄)-induced Sprague-Dawley rat models. Dose-response evaluation revealed optimal antifibrotic efficacy at the medium dosage (5 g kg^-1) compared with other concentrations (2.5 and 7.5 g kg^-1). Transcriptomic profiling identified 1734 differentially expressed mRNAs, 121 lncRNAs, and 82 miRNAs among model (MOD), control (CON), and OIL-treated groups. Construction of competing endogenous RNA (ceRNA) networks and functional enrichment analysis highlighted the potential association of the PPAR signaling pathway (<i>P</i> = 0.012, FDR = 0.27). Topological assessment using Cytoscape (v3.9.1) and the STRING database identified the Gck/rno-miR-667-5p/Cyp8b1 axis as the central regulatory node. Mechanistically, OIL exerted dual therapeutic effects: (1) upregulating PGC-1α/PPARγ expression to enhance metabolic reprogramming, and (2) suppressing TGF-β/Smad3 phosphorylation activation, thereby inhibiting hepatic stellate cell (HSC) activation and extracellular matrix (ECM) deposition. Immunohistochemical and western blot analyses validated these protein-level modulations. Our findings revealed a novel ceRNA-network-mediated mechanism wherein OIL attenuates hepatic fibrosis through coordinated regulation of PPAR and TGF-β/Smad3 pathways <i>via</i> the Gck/rno-miR-667-5p/Cyp8b1 axis, providing a theoretical foundation for developing multitarget phytopharmaceuticals against liver fibrosis.</p>","PeriodicalId":19065,"journal":{"name":"Molecular omics","volume":" ","pages":""},"PeriodicalIF":2.4,"publicationDate":"2025-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145125408","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}

{"title":"Mammary gland metabolism and its relevance to the fetoplacental expression of cytokine signaling in caveolin-1 null mice","authors":"Shankar P. Poudel, Maliha Islam, Thomas B. McFadden and Susanta K. Behura","doi":"10.1039/D5MO00059A","DOIUrl":"10.1039/D5MO00059A","url":null,"abstract":"<p >Mice lacking caveolin-1 (<em>Cav1</em>), a major protein of the lipid raft of plasma membrane, show deregulated cellular proliferation of the mammary gland and an abnormal fetoplacental communication during pregnancy. This study leverages a multi-omics approach to test the hypothesis that the absence of <em>Cav1</em> elicits a coordinated crosstalk of genes among the mammary gland, placenta and fetal brain in pregnant mice. Integrative analysis of metabolomics and transcriptomics data of mammary glands showed that the loss of <em>Cav1</em> significantly impacted specific metabolites and metabolic pathways in the pregnant mice. Next, gene expression changes of the deregulated metabolic pathways of the mammary gland were compared with the gene expression changes of the placenta and fetus. The analysis showed that genes associated with specific metabolic and signaling pathways changed in a coordinated manner in the placenta, mammary gland and fetal brain of <em>Cav1</em>-null mice. The cytokine signaling pathway emerged as a key player of the molecular crosstalk among these tissues. By interrogating the single-nuclei gene expression data of placenta and fetal brain previously generated from <em>Cav1</em>-null mice, the study further revealed that these metabolic and signaling genes were differentially regulated in specific cell types of the placenta and fetal brain. Though a causal effect of the mammary gland on the placenta and/or fetal brain can’t be inferred from this study, the findings show that the mammary gland, placenta and fetal brain show a coordinated molecular crosstalk in response to the absence of <em>Cav1</em> in mice.</p>","PeriodicalId":19065,"journal":{"name":"Molecular omics","volume":" 5","pages":" 512-523"},"PeriodicalIF":2.4,"publicationDate":"2025-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145030246","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}

{"title":"Deep learning methods and applications in single-cell multimodal data integration.","authors":"Franklin Vinny Medina Nunes, Luiza Marques Prates Behrens, Rafael Diogo Weimer, Gabriela Flores Gonçalves, Guilherme da Silva Fernandes, Márcio Dorn","doi":"10.1039/d5mo00062a","DOIUrl":"https://doi.org/10.1039/d5mo00062a","url":null,"abstract":"<p><p>The integration of multimodal single-cell omics data is a state-of-art strategy for deciphering cellular heterogeneity and gene regulatory mechanisms. Recent advances in single-cell technologies have enabled the comprehensive characterization of cellular states and their interactions. However, integrating these high-dimensional and heterogeneous datasets poses significant computational challenges, including batch effects, sparsity, and modality alignment. Deep learning has shown great promise in addressing these issues through neural network-based frameworks, including variational autoencoders (VAEs) and graph neural networks (GNNs). In this Review, we examine cutting-edge deep learning methodologies for integrating single-cell multimodal data, discussing their architectures, applications, and limitations. We highlight key tools such as sciCAN, scJoint, and scMaui, which use deep learning techniques to harmonize various omics layers, improve feature extraction, and improve downstream biological analyses. Despite significant advancements, it remains challenging to ensure model interpretability, scalability, and generalizability across different datasets. Future directions of research in this field include the development of self-supervised learning strategies, transformer-based architectures, and federated learning frameworks to enhance the robustness and reproducibility of single-cell multi-omics integration.</p>","PeriodicalId":19065,"journal":{"name":"Molecular omics","volume":" ","pages":""},"PeriodicalIF":2.4,"publicationDate":"2025-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145033747","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}

{"title":"Differentially regulated saliva proteome and metabolome: a way forward for risk-assessment of oral cancer among tobacco abusers.","authors":"Bolaji Fatai Oyeyemi, Shruti Dabral, Amit Paramaraj, Sandhya Srinivasan, Gagan Deep Jhingan, Dhiraj Kumar, Chintamani, Abhinav Kumar, Néel Sarovar Bhavesh","doi":"10.1039/d5mo00058k","DOIUrl":"10.1039/d5mo00058k","url":null,"abstract":"<p><p>Oral cancer (OC) is a malignant tumour with high morbidity and mortality. Significant contributory factors include alcohol and tobacco abuse that dysregulate the proteome and metabolome. We assessed saliva as a noninvasive bio-sample to understand the changes in proteome and metabolome in OC, tobacco abusers (TA), and controls. OC, TA, and control samples (<i>n</i> = 22, 21, and 21, respectively) were subjected to LFQ-proteomics and NMR-based metabolomics analyses individually and integrated using systems biology; 292 out of 758 proteins with two or more unique peptides were significantly differently regulated. Functional annotation revealed that differentially expressed proteins are involved in important cellular metabolic processes. PLS-DA in metabolomics separated OC from the control and TA, and <i>K</i>-means clustering of proteomics and metabolomics profiles revealed distinguishing proteins and metabolites in OC, TA, and the control. Integrated analysis revealed convergence on molecules like transketolase (TKTT), transaldolase (TALDO), kallikrein 1 (KLK1), enolase A (ENOA), glucose-6-phosphate isomerase (G6PI), and aldolase A and C (ALDOA and ALDOC). Finally, the characteristic discriminatory features of several clusters between OC, TA, and the control remain valid only among high tobacco abusers. The results reveal metabolites that could serve as early indicators for OC, especially among chewing tobacco abusers, and therefore establish the basis for larger cohort studies to develop them as predictive OC biomarkers.</p>","PeriodicalId":19065,"journal":{"name":"Molecular omics","volume":" ","pages":""},"PeriodicalIF":2.4,"publicationDate":"2025-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144962312","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}

{"title":"Comparative glycomic analysis of hawk (<i>Rupornis magnirostris</i>), caiman (<i>Caiman latirostris</i>) and sea turtle (<i>Caretta caretta</i>) tear films.","authors":"Ana Cláudia Raposo, Sheryl Joyce B Grijaldo-Alvarez, Gege Xu, Michael Russelle S Alvarez, Carlito B Lebrilla, Ricardo Wagner Portela, Arianne Oriá","doi":"10.1039/d4mo00255e","DOIUrl":"https://doi.org/10.1039/d4mo00255e","url":null,"abstract":"<p><p>Glycans are recognized as biomarkers and therapeutic targets. However, these molecules remain a critical blind spot in understanding post-translational modifications, particularly in vertebrate species inhabiting diverse habitats. The glycans present in tears play a crucial role in eye protection and may be one of the key factors in adapting to direct environmental contact. This study aimed to describe and compare the glycomic profiles of roadside hawk (<i>Rupornis magnirostris</i>), broad-snouted caiman (<i>Caiman latirostris</i>), and loggerhead sea turtle (<i>Caretta caretta</i>) tears, thereby one avian and two reptilian species. Samples were collected from 10 healthy roadside hawks, 70 broad-snouted caimans, and 10 loggerhead sea turtles to determine <i>N</i>- and <i>O</i>-glycan compounds. The compounds were released from tear glycoproteins and enriched by solid-phase extraction (SPE). Then, the glycans were eluted based on size and polarity. SPE fractions were analyzed using high-resolution mass spectrometry. 155 <i>N</i>-glycans (56% sialylated) and 259 <i>O</i>-glycans (37% sialylated) were detected in roadside hawk tears; 127 <i>N</i>-glycans (55% sialylated) and 263 <i>O</i>-glycans (35% sialofucosylated) in broad-snouted caiman tears; and 85 <i>N</i>-glycans (36% fucosylated) and 84 <i>O</i>-glycans (89% fucosylated) in loggerhead sea turtle tears. The marine habitat has a significant impact on the tear's glycans. The high presence of fucosylated glycans can represent a shield mechanism potentially related to its adhesion to glycocalyx, and interaction with the immune system, also serving as an environmental biomarker. Tears are composed of various biologically active substances, and this description can help in further studies on the identification of novel ocular surface biomarkers and in the differentiation of glycan profiles in healthy and non-healthy animals.</p>","PeriodicalId":19065,"journal":{"name":"Molecular omics","volume":" ","pages":""},"PeriodicalIF":2.4,"publicationDate":"2025-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144962380","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}

{"title":"Thioridazine induces phospholipid accumulation and necroptosis in parental and tamoxifen-resistant breast cancer cells†","authors":"Chandrasekaran Mythri, Sachin B Jorvekar, Nirawane Suraj, Nethaji Pruthiviraj, Roshan M Borkar and Sudhagar Selvaraju","doi":"10.1039/D5MO00039D","DOIUrl":"10.1039/D5MO00039D","url":null,"abstract":"<p >The development of acquired resistance to tamoxifen poses a significant clinical challenge in breast cancer treatment. Tumour heterogeneity has emerged as a primary reason for the clinical implications of resistance, yet we still lack actionable targets to address this issue. Repurposing existing drugs has become an emerging trend to tackle demanding medical indications. Therefore, we aim to study the efficacy of the antipsychotic drug Thioridazine against both parental and tamoxifen-resistant breast cancer cells. In this study, we have demonstrated that Thioridazine induces phospholipid accumulation, followed by necroptosis in both parental and tamoxifen-resistant breast cancer cell lines. We have shown thioridazine-mediated cytostatic effects through analyses of cell viability, cell count, caspase activation, cell cycle, and p21 expression levels. Moreover, employing a pharmacometabolomics approach, we identified that Thioridazine induces phospholipid accumulation in breast cancer cells. We established that Thioridazine promotes the accumulation of phospholipids rather than neutral lipids in cells <em>via</em> lipid-specific fluorescent quantification and imaging analysis. The phospholipid accumulation triggers necroptosis, which was evaluated through a propidium iodide uptake assay. Thioridazine activates RIP signalling, facilitating the subsequent translocation of pore-forming MLKL to the plasma membrane to initiate necroptosis. The formation of MLKL-induced membrane pores was confirmed using scanning electron microscopy for cell surface visualisation. Furthermore, thioridazine co-treatment enhances the efficacy of tamoxifen in resistant breast cancer cells, augmenting its potential for combinatorial treatment. Altogether, Thioridazine induces phospholipid accumulation followed by necroptosis in both parental and tamoxifen-resistant breast cancer cell lines, highlighting its potential application in breast cancer treatment.</p>","PeriodicalId":19065,"journal":{"name":"Molecular omics","volume":" 5","pages":" 496-511"},"PeriodicalIF":2.4,"publicationDate":"2025-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144732417","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}