NPJ Systems Biology and Applications最新文献_第2页

Cell populations simulated in silico within SimulCell accurately reproduce the behaviour of experimental cell cultures. 在SimulCell内用硅模拟的细胞群准确地再现了实验细胞培养的行为。

IF 3.5 2区生物学

NPJ Systems Biology and Applications Pub Date : 2025-05-17 DOI: 10.1038/s41540-025-00518-w

Elvira Toscano, Elena Cimmino, Angelo Boccia, Leandra Sepe, Giovanni Paolella

{"title":"Cell populations simulated in silico within SimulCell accurately reproduce the behaviour of experimental cell cultures.","authors":"Elvira Toscano, Elena Cimmino, Angelo Boccia, Leandra Sepe, Giovanni Paolella","doi":"10.1038/s41540-025-00518-w","DOIUrl":"10.1038/s41540-025-00518-w","url":null,"abstract":"In silico simulations are used to understand cell behaviour by means of different approaches and tools, which range from reproducing average population trends to building lattice-based models to, more recently, creating populations of individual cell agents whose mass, volume and morphology behave according to more or less precise rules and models. In this work, a new agent-based simulator, SimulCell, was conceived, developed and used to predict the behaviour of eukaryotic cell cultures while growing attached to a flat surface. The system, starting from time-lapse microscopy experiments, uses growth, proliferation and migration models to create synthetic populations closely resembling original cultures. Support for cell-cell and cell-environment interaction makes cell agents able to react to changes in medium composition and other events, such as physical damage or chemical modifications occurring in the culture plate. The simulator is accessible through a web application and generates data that can be shown as tables and graphs or exported for further analyses.","PeriodicalId":19345,"journal":{"name":"NPJ Systems Biology and Applications","volume":"11 1","pages":"48"},"PeriodicalIF":3.5,"publicationDate":"2025-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12084383/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144086634","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Assessing the impact of sampling bias on node centralities in synthetic and biological networks. 评估采样偏差对合成和生物网络中节点中心性的影响。

IF 3.5 2区生物学

NPJ Systems Biology and Applications Pub Date : 2025-05-15 DOI: 10.1038/s41540-025-00526-w

Ali Salehzadeh-Yazdi, Marc-Thorsten Hütt

{"title":"Assessing the impact of sampling bias on node centralities in synthetic and biological networks.","authors":"Ali Salehzadeh-Yazdi, Marc-Thorsten Hütt","doi":"10.1038/s41540-025-00526-w","DOIUrl":"10.1038/s41540-025-00526-w","url":null,"abstract":"Centrality measures are crucial for network analysis, offering insights into node importance within complex networks. However, their accuracy is often affected by observational errors and incomplete data. This study investigates how sampling biases systematically impact centrality measures. We simulate six types of biased down-sampling, transitioning networks from dense to sparse states, using the initial network as the 'ground truth.' Changes in centrality values reveal the robustness of these measures under various sampling scenarios across synthetic and biological networks. Our results show that in synthetic networks, some sampling methods consistently exhibit higher robustness, particularly in scale-free networks. For biological networks, protein interaction networks are the most robust, followed by metabolite, gene regulatory, and reaction networks. Local centrality measures generally show greater robustness, while global measures are more heterogeneous and less reliable. This study highlights the limitations of centrality measures under sampling biases and informs the development of more robust methodologies.","PeriodicalId":19345,"journal":{"name":"NPJ Systems Biology and Applications","volume":"11 1","pages":"47"},"PeriodicalIF":3.5,"publicationDate":"2025-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12081662/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144079162","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Computational modeling of cancer cell metabolism along the catabolic-anabolic axes. 癌细胞代谢沿分解代谢-合成代谢轴的计算模型。

IF 3.5 2区生物学

NPJ Systems Biology and Applications Pub Date : 2025-05-10 DOI: 10.1038/s41540-025-00525-x

Javier Villela-Castrejon, Herbert Levine, Benny A Kaipparettu, José N Onuchic, Jason T George, Dongya Jia

{"title":"Computational modeling of cancer cell metabolism along the catabolic-anabolic axes.","authors":"Javier Villela-Castrejon, Herbert Levine, Benny A Kaipparettu, José N Onuchic, Jason T George, Dongya Jia","doi":"10.1038/s41540-025-00525-x","DOIUrl":"https://doi.org/10.1038/s41540-025-00525-x","url":null,"abstract":"Abnormal metabolism is a hallmark of cancer, this was initially recognized nearly a century ago through the observation of aerobic glycolysis in cancer cells. Mitochondrial respiration can also drive tumor progression and metastasis. However, it remains largely unclear the mechanisms by which cancer cells mix and match different metabolic modalities (oxidative/reductive) and leverage various metabolic ingredients (glucose, fatty acids, glutamine) to meet their bioenergetic and biosynthetic needs. Here, we formulate a phenotypic model for cancer metabolism by coupling master gene regulators (AMPK, HIF-1, MYC) with key metabolic substrates (glucose, fatty acids, and glutamine). The model predicts that cancer cells can acquire four metabolic phenotypes: a catabolic phenotype characterized by vigorous oxidative processes-O, an anabolic phenotype characterized by pronounced reductive activities-W, and two complementary hybrid metabolic states-one exhibiting both high catabolic and high anabolic activity-W/O, and the other relying mainly on glutamine oxidation-Q. Using this framework, we quantified gene and metabolic pathway activity by developing scoring metrics based on gene expression. We validated the model-predicted gene-metabolic pathway association and the characterization of the four metabolic phenotypes by analyzing RNA-seq data of tumor samples from TCGA. Strikingly, carcinoma samples exhibiting hybrid metabolic phenotypes are often associated with the worst survival outcomes relative to other metabolic phenotypes. Our mathematical model and scoring metrics serve as a platform to quantify cancer metabolism and study how cancer cells adapt their metabolism upon perturbations, which ultimately could facilitate an effective treatment targeting cancer metabolic plasticity.","PeriodicalId":19345,"journal":{"name":"NPJ Systems Biology and Applications","volume":"11 1","pages":"46"},"PeriodicalIF":3.5,"publicationDate":"2025-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12065808/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144023683","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Patient-specific gene co-expression networks reveal novel subtypes and predictive biomarkers in lung adenocarcinoma. 患者特异性基因共表达网络揭示肺腺癌的新亚型和预测性生物标志物。

IF 3.5 2区生物学

NPJ Systems Biology and Applications Pub Date : 2025-05-09 DOI: 10.1038/s41540-025-00522-0

Patricio López-Sánchez, Federico Ávila-Moreno, Enrique Hernández-Lemus, Marieke L Kuijjer, Jesús Espinal-Enríquez

{"title":"Patient-specific gene co-expression networks reveal novel subtypes and predictive biomarkers in lung adenocarcinoma.","authors":"Patricio López-Sánchez, Federico Ávila-Moreno, Enrique Hernández-Lemus, Marieke L Kuijjer, Jesús Espinal-Enríquez","doi":"10.1038/s41540-025-00522-0","DOIUrl":"https://doi.org/10.1038/s41540-025-00522-0","url":null,"abstract":"Lung adenocarcinoma (LUAD) is a highly heterogenous and aggressive form of non-small cell lung cancer (NSCLC). The use of genome-wide gene co-expression networks (GCNs) has been paramount to describe changes in the transcriptional regulatory programs found between diseased and healthy states of LUAD. Recently, studies have shown that multiple cancerous phenotypes share a distinct GCN architecture, suggesting that network topology holds promise for understanding disease pathology. However, conventional GCN inference methods struggle to capture the inherent context-specificity within a patient population, thus flattening its heterogeneity. To address this issue, the use of single-sample network (SSN) modelling has emerged as a promising solution into studying heterogeneous traits of cancer through network-based approaches. Here, we reconstructed patient-specific GCNs (n=334) using the LIONESS equation and mutual information as the network inference method. Unsupervised analysis revealed six novel LUAD subtypes based on inter-patient network similarity, each with distinct network motifs reflecting unique biological programs. Supervised analysis, employing regularized Cox regression, identified 12 genes (CHRDL2, SPP2, VAC14, IRF5, GUCY1B1, NCS1, RRM2B, EIF5A2, CCDC62, CTCFL, XG, and TP53INP2) whose weighted degree in SSNs is predictive of patient survival in LUAD. These findings suggest that topological features of SSNs offer valuable insights into the context-specific nature of LUAD malignancy, highlighting the potential of SSN-based approaches for further research.","PeriodicalId":19345,"journal":{"name":"NPJ Systems Biology and Applications","volume":"11 1","pages":"44"},"PeriodicalIF":3.5,"publicationDate":"2025-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12064794/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144029704","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Python toolbox for neural circuit parameter inference. 神经电路参数推理的Python工具箱。

IF 3.5 2区生物学

NPJ Systems Biology and Applications Pub Date : 2025-05-09 DOI: 10.1038/s41540-025-00527-9

Alejandro Orozco Valero, Víctor Rodríguez-González, Noemi Montobbio, Miguel A Casal, Alejandro Tlaie, Francisco Pelayo, Christian Morillas, Jesús Poza, Carlos Gómez, Pablo Martínez-Cañada

{"title":"A Python toolbox for neural circuit parameter inference.","authors":"Alejandro Orozco Valero, Víctor Rodríguez-González, Noemi Montobbio, Miguel A Casal, Alejandro Tlaie, Francisco Pelayo, Christian Morillas, Jesús Poza, Carlos Gómez, Pablo Martínez-Cañada","doi":"10.1038/s41540-025-00527-9","DOIUrl":"https://doi.org/10.1038/s41540-025-00527-9","url":null,"abstract":"Computational research tools have reached a level of maturity that enables efficient simulation of neural activity across diverse scales. Concurrently, experimental neuroscience is experiencing an unprecedented scale of data generation. Despite these advancements, our understanding of the precise mechanistic relationship between neural recordings and key aspects of neural activity remains insufficient, including which specific features of electrophysiological population dynamics (i.e., putative biomarkers) best reflect properties of the underlying microcircuit configuration. We present ncpi, an open-source Python toolbox that serves as an all-in-one solution, effectively integrating well-established methods for both forward and inverse modeling of extracellular signals based on single-neuron network model simulations. Our tool serves as a benchmarking resource for model-driven interpretation of electrophysiological data and the evaluation of candidate biomarkers that plausibly index changes in neural circuit parameters. Using mouse LFP data and human EEG recordings, we demonstrate the potential of ncpi to uncover imbalances in neural circuit parameters during brain development and in Alzheimer's Disease.","PeriodicalId":19345,"journal":{"name":"NPJ Systems Biology and Applications","volume":"11 1","pages":"45"},"PeriodicalIF":3.5,"publicationDate":"2025-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12064716/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144047179","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Effective integration of multi-omics with prior knowledge to identify biomarkers via explainable graph neural networks. 多组学与先验知识的有效整合，通过可解释的图神经网络识别生物标志物。

IF 3.5 2区生物学

NPJ Systems Biology and Applications Pub Date : 2025-05-08 DOI: 10.1038/s41540-025-00519-9

Rohit K Tripathy, Zachary Frohock, Hong Wang, Gregory A Cary, Stephen Keegan, Gregory W Carter, Yi Li

{"title":"Effective integration of multi-omics with prior knowledge to identify biomarkers via explainable graph neural networks.","authors":"Rohit K Tripathy, Zachary Frohock, Hong Wang, Gregory A Cary, Stephen Keegan, Gregory W Carter, Yi Li","doi":"10.1038/s41540-025-00519-9","DOIUrl":"https://doi.org/10.1038/s41540-025-00519-9","url":null,"abstract":"The rapid growth of multi-omics datasets and the wealth of biological knowledge necessitates the development of effective methods for their integration. Such methods are essential for building predictive models and identifying drug targets based on a limited number of samples. We propose a framework called GNNRAI for the supervised integration of multi-omics data with biological priors represented as knowledge graphs. Our framework leverages graph neural networks (GNNs) to model the correlation structures among features from high-dimensional 'omics data, which reduces the effective dimensions in data and enables us to analyze thousands of genes simultaneously using hundreds of samples. Furthermore, our framework incorporates explainability methods to elucidate informative biomarkers. We apply our framework to Alzheimer's disease (AD) multi-omics data, showing that the integration of transcriptomics and proteomics data with prior AD knowledge is effective, improving the prediction accuracy of AD status over single-omics analyses and highlighting both known and novel AD-predictive biomarkers.","PeriodicalId":19345,"journal":{"name":"NPJ Systems Biology and Applications","volume":"11 1","pages":"43"},"PeriodicalIF":3.5,"publicationDate":"2025-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12062277/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144012929","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

An in silico approach deciphering the commensal dynamics in the cutaneous milieu. 一种破译皮肤环境中共生动力学的计算机方法。

IF 3.5 2区生物学

NPJ Systems Biology and Applications Pub Date : 2025-05-07 DOI: 10.1038/s41540-025-00524-y

Sumathi Kalankariyan, Anjana Thottapillil, Abha Saxena, Manoj Srivatsn S, Vinitha Kadamkode, Renu Kapoor, Rupak Mitra, Janhavi Raut, K V Venkatesh

{"title":"An in silico approach deciphering the commensal dynamics in the cutaneous milieu.","authors":"Sumathi Kalankariyan, Anjana Thottapillil, Abha Saxena, Manoj Srivatsn S, Vinitha Kadamkode, Renu Kapoor, Rupak Mitra, Janhavi Raut, K V Venkatesh","doi":"10.1038/s41540-025-00524-y","DOIUrl":"https://doi.org/10.1038/s41540-025-00524-y","url":null,"abstract":"The skin microbiota, particularly coagulase-negative staphylococci (CoNS) such as S. epidermidis, plays a crucial role in maintaining skin health and immunity. S. epidermidis, a predominant commensal species, interacts intimately with keratinocytes to regulate immune responses and antimicrobial defence mechanisms. Metabolic byproducts like short-chain fatty acids (SCFAs) influence keratinocyte activation, while cell wall components engage Toll-like receptors (TLRs) to modulate inflammation. These interactions are fundamental for preserving skin homeostasis and combating pathogenic invaders. Our comprehensive mathematical model, integrating commensal dynamics, immune responses, and skin microenvironment variables, provides insights into these intricate interactions. The model delves into the complexities of skin scenarios and perturbations, aiming to understand the colonization dynamics of S. epidermidis and its influence on skin barrier functions. It examines how disruptions in key factors such as AMP, growth factor-mediated repair pathways, and filaggrin mutations influence the behaviour of the system. The study depicts the skin microenvironment as a highly dynamic one, highlighting the critical role of S. epidermidis and capturing its role in barrier dysfunction caused by internal and external factors. By offering insights into skin barrier function and immune responses, the model illuminates key interactions of commensals within the skin microenvironment which can ultimately benefit skin health.","PeriodicalId":19345,"journal":{"name":"NPJ Systems Biology and Applications","volume":"11 1","pages":"42"},"PeriodicalIF":3.5,"publicationDate":"2025-05-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12058978/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144034185","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Neural mechanisms balancing accuracy and flexibility in working memory and decision tasks. 平衡工作记忆和决策任务的准确性和灵活性的神经机制。

IF 3.5 2区生物学

NPJ Systems Biology and Applications Pub Date : 2025-05-07 DOI: 10.1038/s41540-025-00520-2

Han Yan, Jin Wang

{"title":"Neural mechanisms balancing accuracy and flexibility in working memory and decision tasks.","authors":"Han Yan, Jin Wang","doi":"10.1038/s41540-025-00520-2","DOIUrl":"https://doi.org/10.1038/s41540-025-00520-2","url":null,"abstract":"The living system follows the principles of physics, yet distinctive features, such as adaptability, differentiate it from conventional systems. The cognitive functions of decision-making (DM) and working memory (WM) are crucial for animal adaptation, but the underlying mechanisms are still unclear. To explore the mechanism underlying DM and WM functions, here we applied a general non-equilibrium landscape and flux approach to a biophysically based model that can perform decision-making and working memory functions. Our findings reveal that DM accuracy improved with stronger resting states in the circuit architecture with selective inhibition. However, the robustness of working memory against distractors was weakened. To address this, an additional non-selective input during the delay period of decision-making tasks was proposed as a mechanism to gate distractors with minimal increase in thermodynamic cost. This temporal gating mechanism, combined with the selective-inhibition circuit architecture, supports a dynamical modulation that emphasizes the robustness or flexibility to incoming stimuli in working memory tasks according to the cognitive task demands. Our approach offers a quantitative framework to uncover mechanisms underlying cognitive functions grounded in non-equilibrium physics.","PeriodicalId":19345,"journal":{"name":"NPJ Systems Biology and Applications","volume":"11 1","pages":"41"},"PeriodicalIF":3.5,"publicationDate":"2025-05-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12059158/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144037551","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Biochemical implementation of acceleration sensing and PIDA control. 生化实现加速度传感和PIDA控制。

IF 3.5 2区生物学

NPJ Systems Biology and Applications Pub Date : 2025-04-26 DOI: 10.1038/s41540-025-00514-0

Emmanouil Alexis, Sebastián Espinel-Ríos, Ioannis G Kevrekidis, José L Avalos

引用次数: 0

The Virtual Parkinsonian patient. 虚拟帕金森病人。

IF 3.5 2区生物学

NPJ Systems Biology and Applications Pub Date : 2025-04-26 DOI: 10.1038/s41540-025-00516-y

Marianna Angiolelli, Damien Depannemaecker, Hasnae Agouram, Jean Régis, Romain Carron, Marmaduke Woodman, Letizia Chiodo, Paul Triebkorn, Abolfazl Ziaeemehr, Meysam Hashemi, Alexandre Eusebio, Viktor Jirsa, Pierpaolo Sorrentino

{"title":"The Virtual Parkinsonian patient.","authors":"Marianna Angiolelli, Damien Depannemaecker, Hasnae Agouram, Jean Régis, Romain Carron, Marmaduke Woodman, Letizia Chiodo, Paul Triebkorn, Abolfazl Ziaeemehr, Meysam Hashemi, Alexandre Eusebio, Viktor Jirsa, Pierpaolo Sorrentino","doi":"10.1038/s41540-025-00516-y","DOIUrl":"https://doi.org/10.1038/s41540-025-00516-y","url":null,"abstract":"This study investigates the influence of the pharmacological nigrostriatal dopaminergic stimulation on the entire brain by analyzing EEG and deep electrodes, placed near the subthalamic nuclei, from 10 Parkinsonian patients before (OFF) and after (ON) L-Dopa administration. We characterize large-scale brain dynamics as the spatio-temporal spreading of aperiodic bursts. We then simulate the effects of L-Dopa utilizing a novel neural-mass model that includes the local dopamine concentration. Whole-brain dynamics are simulated for different dopaminergic tones, generating predictions for the expected dynamics, to be compared with empirical EEG and deep electrode data. To this end, we invert the model and infer the most likely dopaminergic tone from empirical data, correctly identifying a higher Dopaminergic tone in the ON-state, and a lower dopaminergic tone in the OFF-state, for each patient. In conclusion, we successfully infer the dopaminergic tone by integrating anatomical and functional knowledge into physiological predictions, using solid ground truth to validate our findings.","PeriodicalId":19345,"journal":{"name":"NPJ Systems Biology and Applications","volume":"11 1","pages":"40"},"PeriodicalIF":3.5,"publicationDate":"2025-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12033322/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144029743","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0