NPJ Systems Biology and Applications最新文献_第9页

The complexome contextualizes proteomics data to fingerprint biological states and highlight perturbed functional modules in disease. 复杂组将蛋白质组学数据置于背景中，以识别生物状态并突出疾病中受干扰的功能模块。

IF 4.4 2区生物学

NPJ Systems Biology and Applications Pub Date : 2026-04-25 DOI: 10.1038/s41540-026-00716-0

Mainak Guharoy, Isabelle Adant, Matthew Bird, Alexander Botzki, James Collier, Jonas Dehairs, Stefaan Derveaux, Simon Devos, Geert Goeminne, Francis Impens, Andrea Jáñez Pedrayes, Rekin's Janky, Ruth Maes, Pedro Magalhães, Teresa M Maia, Wouter Meersseman, Daisy Rymen, Johannes V Swinnen, Delphi Van Haver, Dries Verdegem, Peter Witters, David Cassiman, Bart Ghesquiere

{"title":"The complexome contextualizes proteomics data to fingerprint biological states and highlight perturbed functional modules in disease.","authors":"Mainak Guharoy, Isabelle Adant, Matthew Bird, Alexander Botzki, James Collier, Jonas Dehairs, Stefaan Derveaux, Simon Devos, Geert Goeminne, Francis Impens, Andrea Jáñez Pedrayes, Rekin's Janky, Ruth Maes, Pedro Magalhães, Teresa M Maia, Wouter Meersseman, Daisy Rymen, Johannes V Swinnen, Delphi Van Haver, Dries Verdegem, Peter Witters, David Cassiman, Bart Ghesquiere","doi":"10.1038/s41540-026-00716-0","DOIUrl":"10.1038/s41540-026-00716-0","url":null,"abstract":"Analyzing single omics and integrating multimodal omics datasets to capture functional dysregulation in disease remains challenging. Here, we propose a bioinformatics framework that leverages curated datasets of protein complexes ('complexome') as a foundation for proteomics data integration. Available for human and other model organisms, the complexome provides a global view of cellular function, enabling queries with proteomics datasets. We first benchmarked how protein abundances across human tissues shape distinct complexomic profiles, serving to fingerprint biological activity. Next, we analyzed complexome remodeling using disease versus control proteomics quantifications. Using proteomics data from fibroblasts of patients with genetically confirmed metabolic defects, we identified significant perturbations in mitochondrial oxidative phosphorylation complexes and additional complexes involved in wider mitochondrial functions. The complexome provides a systems-wide approach to dissect mechanisms underlying disease-related functional and phenotypic changes by mapping measured protein-level perturbations to specific molecular complexes. The software is available as a Python notebook at https://github.com/mguharoy/Complexome .","PeriodicalId":19345,"journal":{"name":"NPJ Systems Biology and Applications","volume":" ","pages":""},"PeriodicalIF":4.4,"publicationDate":"2026-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13462548/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147777273","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

Context-aware multi-property antibody predictor: a novel framework integrating text and protein language models. 上下文感知多属性抗体预测器：一个整合文本和蛋白质语言模型的新框架。

IF 4.4 2区生物学

NPJ Systems Biology and Applications Pub Date : 2026-04-25 DOI: 10.1038/s41540-026-00723-1

Luca Giancardo, Melih Yilmaz, Edward Lee, Ke Ren, Yue Zhao, Gordon Trang, Kemal Sonmez, Lan Guo, Nina Cheng

{"title":"Context-aware multi-property antibody predictor: a novel framework integrating text and protein language models.","authors":"Luca Giancardo, Melih Yilmaz, Edward Lee, Ke Ren, Yue Zhao, Gordon Trang, Kemal Sonmez, Lan Guo, Nina Cheng","doi":"10.1038/s41540-026-00723-1","DOIUrl":"10.1038/s41540-026-00723-1","url":null,"abstract":"Recent advances in Machine Learning have transformed antibody development through in silico models, accelerating therapeutic candidate identification. However, challenges persist: rapid adaptation of property predictors to laboratory-specific assays with incomplete datasets; batch effects introducing systematic bias; assay costs necessitating efficient unseen property prediction. We introduce a novel multimodal architecture featuring specialized tokenization and embedding projection that integrates text and protein language models (pLM) and a learning strategy to enable context-conditioned multi-property prediction without learning shortcuts. Our framework enables prompting without dictionary merging across modalities, creating a compact model capable of context-conditioned learning for multi-property prediction. The orchestrating model avoids pLM-to-text projection while enabling inference-time adaptation without retraining. Using 876,898 antibody heavy chain sequences with batch effect simulation, our architecture achieved Spearman's ρ > 0.8 across multiple developability properties, significantly outperforming fine-tuned multimodal LLMs and showed the ability to leverage correlation between properties for prediction. This approach has the potential to address critical antibody development challenges.","PeriodicalId":19345,"journal":{"name":"NPJ Systems Biology and Applications","volume":" ","pages":""},"PeriodicalIF":4.4,"publicationDate":"2026-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13324834/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147777226","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

Creating an engine of scientific discovery, an Indo-Japan perspective: learnings from IJNTC 2025 workshop. 创造科学发现的引擎，印日视角：从IJNTC 2025研讨会的学习。

IF 4.4 2区生物学

NPJ Systems Biology and Applications Pub Date : 2026-04-22 DOI: 10.1038/s41540-026-00714-2

Sucheendra K Palaniappan, Moreno Zolfo, Satish Kottapalli, Ajay Sethi, Johan Nyström-Persson, Daniel Evans-Yamamoto, Jihun Choi, Anton Kratz, Srinivas Padmanabhan, Ryota Yamada, Yosuke Ozawa, Natalia Polouliakh, Ashwini Patil, Manas Kala, Tavpritesh Sethi, Ganesh Bagler, Jun Seita, Samik Ghosh, Ravindranath Kancherla, Hiroaki Kitano

引用次数: 0

When normalization induces correlation: shared and unstable references can create hidden dependencies. 当规范化引起相关性时：共享的和不稳定的引用可能会创建隐藏的依赖关系。

IF 4.4 2区生物学

NPJ Systems Biology and Applications Pub Date : 2026-04-21 DOI: 10.1038/s41540-026-00722-2

Kiyoshi F Fukutani, Thomas H Hampton, Mattheus Luís Alves Santiago, Eddy José Francisco de Oliveira, Todd A MacKenzie

{"title":"When normalization induces correlation: shared and unstable references can create hidden dependencies.","authors":"Kiyoshi F Fukutani, Thomas H Hampton, Mattheus Luís Alves Santiago, Eddy José Francisco de Oliveira, Todd A MacKenzie","doi":"10.1038/s41540-026-00722-2","DOIUrl":"10.1038/s41540-026-00722-2","url":null,"abstract":"Correlation analyses are widely used to infer biological relationships, yet preprocessing can introduce structural dependencies that inflate correlation estimates. Here, we examine an under-recognized mechanism: shared-reference transformations, in which multiple variables are centered or scaled using the same reference before correlation-based inference. We derive analytically that, even when two variables are independent, subtracting a shared reference induces nonzero covariance and yields an expected correlation that increases with the variance of the reference. Simulations show that this artifact is systematic, strengthens as the reference becomes more variable, and does not disappear with increasing sample size. We further show that sequential shared transformations of the form (X-Z)/W can become unstable when denominators fluctuate or approach zero, producing highly dispersed correlations consistent with heavy-tailed ratio effects. As an illustrative count-based example,we introduce a simulation with sample-level scaling showing that downstream shared-reference steps can reintroduce dependence after an initial correction step. Finally, real-data analysis across multiple preprocessing pipelines confirms that shared-reference transformations can inflate correlation estimates in practice. These results highlight shared-reference preprocessing as a potential source of artificial dependence that should be explicitly considered when interpreting correlation-based findings.","PeriodicalId":19345,"journal":{"name":"NPJ Systems Biology and Applications","volume":" ","pages":""},"PeriodicalIF":4.4,"publicationDate":"2026-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13287743/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147777330","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

Modeling epithelial deformation and cell rearrangement in response to external forces during Zebrafish epiboly. 模拟斑马鱼上皮变形和细胞重排对外力的反应。

IF 4.4 2区生物学

NPJ Systems Biology and Applications Pub Date : 2026-04-21 DOI: 10.1038/s41540-026-00708-0

Sharon B Minsuk, T J Sego, David M Umulis, Mary C Mullins, James A Glazier

{"title":"Modeling epithelial deformation and cell rearrangement in response to external forces during Zebrafish epiboly.","authors":"Sharon B Minsuk, T J Sego, David M Umulis, Mary C Mullins, James A Glazier","doi":"10.1038/s41540-026-00708-0","DOIUrl":"10.1038/s41540-026-00708-0","url":null,"abstract":"Morphogenesis in early development involves complex and extreme deformations in response to intra- and intercellular forces. Zebrafish epiboly, the spreading of the blastoderm to cover and engulf the large yolk cell, is a key early event that sets the stage for the establishment of the body plan, but the way the forces driving expansion are generated and mediated is poorly understood. The enveloping layer (EVL), the thin squamous outer epithelium of the blastoderm, plays a central role. Forces generated in the yolk cell are transmitted through tight junctions to the marginal EVL cells, and then propagate through the rest of the EVL. To understand mechanisms of force generation and transduction during epiboly, we first need a mechanical model of the EVL capable of responding to such forces and undergoing the drastic deformation of epiboly. The expanding EVL more than doubles its surface area and experiences significant shear as it deforms from a thin cap at one pole to become a complete sphere, necessarily requiring extensive internal rearrangement. We constructed an agent-based model of the EVL and its response to exogenous forces using the center-based simulation framework, Tissue Forge. Our model captures the large viscoelastoplastic deformation of the EVL by cell rearrangement, and accommodates the required cell neighbor exchanges without losing mechanical integration. Features observed in living embryos, such as the straightening of the initially ragged leading edge, also emerge in the model. We identified two key components required for realistic epiboly in the model: first, a mechanism to enable tissue remodeling by cell rearrangement without tearing the tissue, and second, a negative feedback on the forces driving EVL expansion, to regulate and synchronize the advancement of the EVL margin. We discuss the implications of these findings for the behavior of living EVL and the mechanisms that drive epiboly.","PeriodicalId":19345,"journal":{"name":"NPJ Systems Biology and Applications","volume":" ","pages":""},"PeriodicalIF":4.4,"publicationDate":"2026-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13139408/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147777260","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

Matters of life and death in computational cell biology. 计算细胞生物学中的生死问题。

IF 4.4 2区生物学

NPJ Systems Biology and Applications Pub Date : 2026-04-20 DOI: 10.1038/s41540-026-00718-y

Connor McShaffrey, Eran Agmon, Randall D Beer

引用次数: 0

Succession-diagram-based Markov chains reveal the attractor landscape of asynchronous Boolean networks. 基于序列图的马尔可夫链揭示了异步布尔网络的吸引子景观。

IF 4.4 2区生物学

NPJ Systems Biology and Applications Pub Date : 2026-04-17 DOI: 10.1038/s41540-026-00717-z

Kyu Hyong Park, Réka Albert

{"title":"Succession-diagram-based Markov chains reveal the attractor landscape of asynchronous Boolean networks.","authors":"Kyu Hyong Park, Réka Albert","doi":"10.1038/s41540-026-00717-z","DOIUrl":"10.1038/s41540-026-00717-z","url":null,"abstract":"Comprehensive analysis of the dynamics of Boolean models of biological systems is hampered by the exponentially large state space. Here we introduce the succession-diagram-based Markov chain (SD Markov chain), a coarse-grained representation that uses trap spaces (unescapable state subspaces) of the Boolean model as the states of a Markov chain. These trap spaces and their succession diagram can be efficiently identified, and constitute a dramatic reduction compared to the full state space. The SD Markov chain preserves the decisions that trap the system's dynamics while making the state space computationally tractable. Using an ensemble of random Boolean networks with known state transition matrices, we show that the SD Markov chain accurately reproduces attractors, basins of attraction, convergence probabilities, decision transitions, and sequences of events. We illustrate the insights and predictions that arise from the SD Markov chain by analyzing a published model of cancer cell metastasis. By combining the interpretability of the succession diagram with the probabilistic rigor of Markov analysis, the SD Markov chain offers a compact quantitative description of the attractor landscape and provides a new avenue for studying control and stability in complex biological systems.","PeriodicalId":19345,"journal":{"name":"NPJ Systems Biology and Applications","volume":" ","pages":""},"PeriodicalIF":4.4,"publicationDate":"2026-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13273057/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147717614","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

Multiscale modeling reveals synergy between CCL19 and PD-1 blockade in reshaping the TNBC microenvironment. 多尺度模型揭示了CCL19和PD-1阻断在重塑TNBC微环境中的协同作用。

IF 4.4 2区生物学

NPJ Systems Biology and Applications Pub Date : 2026-04-16 DOI: 10.1038/s41540-026-00695-2

Chunjie Gao, Chenghang Li, Lei Du, Jing Liu, Jinzhi Lei, Lei Wang

{"title":"Multiscale modeling reveals synergy between CCL19 and PD-1 blockade in reshaping the TNBC microenvironment.","authors":"Chunjie Gao, Chenghang Li, Lei Du, Jing Liu, Jinzhi Lei, Lei Wang","doi":"10.1038/s41540-026-00695-2","DOIUrl":"10.1038/s41540-026-00695-2","url":null,"abstract":"Triple-negative breast cancer (TNBC) presents a major clinical challenge owing to its immunosuppressive tumor microenvironment, target scarcity, and poor therapeutic response. Recently, the combination therapy of immune checkpoint blockade and CCL19 has shown significant efficacy in TNBC. To systematically unravel the synergistic mechanisms between CCL19 and anti-PD-1, we developed a mathematical model by integrating cellular and molecular scales to capture essential tumor-immune interactions and predict the dynamics of tumor evolution under various therapies. In this study, we proposed three quantitative indicators: (1) the tumor relative volume index (TRVI), (2) the therapeutic efficacy discrepancy index (TEDI), and (3) the immune heterogeneity treatment response index (IHTRI). Our model validated that the immunostimulatory effect of CCL19 in synergizing with anti-PD-1, and revealed that this synergy is highly modulated by individual baseline immune heterogeneity. Notably, our analysis identified (CTLs × CCL19)/PD-L1 as a novel dynamic biomarker combination with significant predictive (AUC = 0.86) and prognostic value (log-rank p= 0.019). Finally, virtual clinical trials revealed that administering anti-PD-1 therapy prior to CCL19 injection draws more significant clinical benefits in TNBC. Collectively, this study provides a theoretical foundation for elucidating the synergistic mechanism between CCL19-mediated immunostimulation and anti-PD-1 therapy.","PeriodicalId":19345,"journal":{"name":"NPJ Systems Biology and Applications","volume":" ","pages":""},"PeriodicalIF":4.4,"publicationDate":"2026-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13269484/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147699391","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

AI-enhanced approaches for personalized cardiac treatment: insights from ECG data. 个性化心脏治疗的人工智能增强方法：来自ECG数据的见解。

IF 4.4 2区生物学

NPJ Systems Biology and Applications Pub Date : 2026-04-16 DOI: 10.1038/s41540-026-00702-6

Vibha Tiwari, Rohit Gupta, Akshada Telang, Akshra Tiwari, Rebakah Geddam, Muhammad Awais, Muhammad Ahmed Khan, Hemant Ghayvat

{"title":"AI-enhanced approaches for personalized cardiac treatment: insights from ECG data.","authors":"Vibha Tiwari, Rohit Gupta, Akshada Telang, Akshra Tiwari, Rebakah Geddam, Muhammad Awais, Muhammad Ahmed Khan, Hemant Ghayvat","doi":"10.1038/s41540-026-00702-6","DOIUrl":"10.1038/s41540-026-00702-6","url":null,"abstract":"The analysis of drug-induced alterations in the electrocardiogram (ECG) is essential in measuring cardiac safety, but manual analysis is not always accurate enough to identify subtle but important effects. This paper examines how machine learning (ML) models can be used to categorize various pharmacological treatments according to their distinct ECG patterns to establish a platform of individualized therapeutic evaluation. Using the public ECG Effects of Dofetilide, Moxifloxacin, Dofetilide+Mexiletine, Dofetilide+Lidocaine and Moxifloxacin+Diltiazem (ECGDMMLD) database, key electrophysiological features were extracted-including heart rate variability (HRV) and standard cardiac intervals (RR, PR, QT, QRS) to train and compare three different classifiers: XGBoost, Random Forest, and a Support Vector Machine (SVM). The analysis showed that tree-based ensemble techniques were very useful in this task. The XGBoost model had a better classification accuracy of 98.1%, which was closely followed by the random forest at 97.3%. Conversely, the SVM had much lower accuracy, implying that it was not as well adapted to the complexity of the high-dimensional ECG data. These results establish that ML models, particularly XGBoost, can accurately decode complex drug-induced cardiac signatures from ECG data. This work is a powerful demonstration of the proof-of-concept of automated and data-driven analytics integration into clinical processes to enhance drug safety and promote personalized medicine.","PeriodicalId":19345,"journal":{"name":"NPJ Systems Biology and Applications","volume":" ","pages":""},"PeriodicalIF":4.4,"publicationDate":"2026-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13198540/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147699398","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

Revealing novel subtypes of synovial sarcoma through single cell transcriptomics. 通过单细胞转录组学揭示滑膜肉瘤的新亚型。

IF 4.4 2区生物学

NPJ Systems Biology and Applications Pub Date : 2026-04-15 DOI: 10.1038/s41540-026-00711-5

Artem L Toropov, Elena E Kopantseva, Alexander V Ikonnikov, Maxim E Menyailo, Timur I Fetisov, Anna M Stroganova, Daria A Meshkova, Nikolay A Kozlov, Polina A Shtompel, Sofya A Khazanova, Ekaterina A Trapeznikova, Kirill I Kirsanov, Anastasia A Tararykova, Marianna G Yakubovskaya, Evgeny V Denisov

{"title":"Revealing novel subtypes of synovial sarcoma through single cell transcriptomics.","authors":"Artem L Toropov, Elena E Kopantseva, Alexander V Ikonnikov, Maxim E Menyailo, Timur I Fetisov, Anna M Stroganova, Daria A Meshkova, Nikolay A Kozlov, Polina A Shtompel, Sofya A Khazanova, Ekaterina A Trapeznikova, Kirill I Kirsanov, Anastasia A Tararykova, Marianna G Yakubovskaya, Evgeny V Denisov","doi":"10.1038/s41540-026-00711-5","DOIUrl":"10.1038/s41540-026-00711-5","url":null,"abstract":"Synovial sarcoma (SyS) is a common type of soft tissue sarcoma, characterized by slow growth, high rates of metastasis, and diverse clinical symptoms. This malignancy is defined by the presence of the SS18-SSX fusion protein and the corresponding SS18-SSX program that promotes the core oncogenic pathways and a wide spectrum of tumor cell phenotypes. In this study, we used single-cell RNA sequencing to explore SyS diversity, highlighting four molecular subtypes. The mesenchymal NKD2+ SyS is characterized by the increased BMP signaling in tumor cells and the most severe immune escape and chemoresistance profile. The poorly differentiated HOXD11+ SyS displays the highest expression of the core oncogenic program and the likely suppression of the immune response through CXCL and MIF signaling. The fibroblast-like DCN+ SyS demonstrates high levels of mesenchymal differentiation, a surprising drop in the SS18-SSX program expression, and the angiogenesis-oriented cell-cell interactions. The biphasic EPCAM+ SyS has the highest levels of differentiation and lowest levels of the core oncogenic program. Our data complements the traditional classification of SyS and suggests that the monophasic mesenchymal SyS might consist of two molecular subtypes.","PeriodicalId":19345,"journal":{"name":"NPJ Systems Biology and Applications","volume":" ","pages":""},"PeriodicalIF":4.4,"publicationDate":"2026-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13442865/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147691227","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