NPJ Systems Biology and Applications最新文献

Combining in vitro and in silico approaches to model neural tube patterning and isthmic organizer formation. 结合体外和计算机方法模拟神经管模式和峡部组织体形成。

IF 4.4 2区生物学

NPJ Systems Biology and Applications Pub Date : 2026-08-21 DOI: 10.1038/s41540-026-00813-0

Fredrik Bertilsson, Alexander Degener, Paulina Ibek, Gaurav Singh Rathore, Emil Andersson, Pedro Rifes, Agnete Kirkeby, Victor Olariu

引用次数: 0

Bulk transcriptomics of peripheral blood mononuclear cells delineates systems-level immune dysregulation in pediatric dengue infection. 外周血单个核细胞的大量转录组学描述了儿童登革热感染中系统水平的免疫失调。

IF 4.4 2区生物学

NPJ Systems Biology and Applications Pub Date : 2026-08-14 DOI: 10.1038/s41540-026-00796-y

Abdul R Anshad, Muthuvel Atchaya, Amudhan Murugesan, Suvaiyarasan Suvaithenamudhan, Shanmugam Saravanan, Sivadoss Raju, Cecilia Svanberg, Marie Larsson, Esaki M Shankar

{"title":"Bulk transcriptomics of peripheral blood mononuclear cells delineates systems-level immune dysregulation in pediatric dengue infection.","authors":"Abdul R Anshad, Muthuvel Atchaya, Amudhan Murugesan, Suvaiyarasan Suvaithenamudhan, Shanmugam Saravanan, Sivadoss Raju, Cecilia Svanberg, Marie Larsson, Esaki M Shankar","doi":"10.1038/s41540-026-00796-y","DOIUrl":"10.1038/s41540-026-00796-y","url":null,"abstract":"Children are disproportionately at a greater risk of developing severe dengue disease, yet the molecular mechanisms driving the heightened susceptibility remains poorly understood. To elucidate the immune determinants of pediatric dengue pathogenesis, we profiled the transcriptomic landscape by performing RNA sequencing (RNA-Seq) on peripheral blood mononuclear cells (PBMCs) from laboratory-confirmed cases of primary and secondary pediatric dengue, as well as pediatric healthy controls. Differential gene expression (DEG) and pathway analyses were performed to delineate the transcriptional alterations. Pediatric dengue was marked by extensive transcriptional changes with altered expression of genes associated with the complement cascade macrophage-associated genes as well as immune checkpoint molecules. Notably, secondary infection had significant alterations in immune checkpoint molecules and genes associated with macrophage activation, suggesting the onset of immune exhaustion during reinfection. Differences between the primary and secondary dengue cohorts were modest relative to the transcriptional differences observed between either of the groups and healthy controls, with immune checkpoint genes showing the most consistent divergence between the two dengue cohorts. While our initial findings provide early insights into the transcriptional patterns potentially associated with disease outcomes, the dysregulated transcriptomic signatures reported here are preliminary requiring systemic functional validation to determine their biologic role in the immunopathogenesis of pediatric dengue infection.","PeriodicalId":19345,"journal":{"name":"NPJ Systems Biology and Applications","volume":"12 1","pages":""},"PeriodicalIF":4.4,"publicationDate":"2026-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13477468/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148761932","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

Wrapshap a high dimension feature selection framework to explore biological systems through machine learning explanations. 包装一个高维特征选择框架，通过机器学习解释来探索生物系统。

IF 4.4 2区生物学

NPJ Systems Biology and Applications Pub Date : 2026-07-21 DOI: 10.1038/s41540-026-00779-z

Félix Furger, Miguel Thomas, Colas Foulon, Haomio Wang, Julien Aligon, Emmanuel Doumard, Chantal Soulé-Dupuy, Cyrille Delpierre, Louis Casteilla, Paul Monsarrat

{"title":"Wrapshap a high dimension feature selection framework to explore biological systems through machine learning explanations.","authors":"Félix Furger, Miguel Thomas, Colas Foulon, Haomio Wang, Julien Aligon, Emmanuel Doumard, Chantal Soulé-Dupuy, Cyrille Delpierre, Louis Casteilla, Paul Monsarrat","doi":"10.1038/s41540-026-00779-z","DOIUrl":"https://doi.org/10.1038/s41540-026-00779-z","url":null,"abstract":"Among the existing feature selection (FS) methods in machine learning (ML), those known as wrapper methods often produce the most effective subset of features. However, their high computational cost and tendency to overfit make them impractical for high-dimensional data, as is frequently encountered in biological research. The Wrapshap framework presents a novel FS method tailored for high-dimensional biological data, addressing challenges such as redundancy, multicollinearity, and interaction effects. By leveraging the local accuracy property of Additive Local Explanation methods of SHAP, Wrapshap translates complex biological data into interpretable insights. The framework, integrating a trained ML model, allows explanations to be viewed as a new exploratory data space containing a comprehensive understanding of the underlying complexity of the raw data structure. Benchmarks against 84 regression and 106 classification datasets demonstrate its superiority in computational speed, feature ranking quality, and predictive performance compared to state-of-the-art methods like Recursive Feature Elimination. The method's adaptability extends to various ML models, explanation methods and tasks. By requiring only a single training of the complex model, Wrapshap mitigates the computational inefficiencies of traditional wrapper methods while maintaining performance monitoring thus opening new possibilities for real-time, interactive FS with user involvement. This innovative approach addresses a notable gap in existing methods, and promotes informed biological hypothesis generation, enhancing the interpretability and usability of ML in biomedical research.","PeriodicalId":19345,"journal":{"name":"NPJ Systems Biology and Applications","volume":" ","pages":""},"PeriodicalIF":4.4,"publicationDate":"2026-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148550030","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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

Artificial intelligence perceives marginal gains from MHC class I haplotype data in antigen presentation predictions. 人工智能在抗原呈递预测中从MHC I类单倍型数据中获得边际收益。

IF 4.4 2区生物学

NPJ Systems Biology and Applications Pub Date : 2026-07-21 DOI: 10.1038/s41540-026-00776-2

Fabio Massimo Zanzotto, Michele Mastromattei, Aleksander Palkowski, Aria Nourbakhsh, Piyush Borole, Ashwin Adrian Kallor, Emilia Daghir-Wojtkowiak, Michał Waleron, Davide Venditti, Elena Sofia Ruzzetti, Roberta Bernadini, Maksym Zoziuk, Maurizio Mattei, Dimitri Koroliouk, Ajitha Rajan, Christophe Battail, Javier Antonio Alfaro

{"title":"Artificial intelligence perceives marginal gains from MHC class I haplotype data in antigen presentation predictions.","authors":"Fabio Massimo Zanzotto, Michele Mastromattei, Aleksander Palkowski, Aria Nourbakhsh, Piyush Borole, Ashwin Adrian Kallor, Emilia Daghir-Wojtkowiak, Michał Waleron, Davide Venditti, Elena Sofia Ruzzetti, Roberta Bernadini, Maksym Zoziuk, Maurizio Mattei, Dimitri Koroliouk, Ajitha Rajan, Christophe Battail, Javier Antonio Alfaro","doi":"10.1038/s41540-026-00776-2","DOIUrl":"https://doi.org/10.1038/s41540-026-00776-2","url":null,"abstract":"Artificial Intelligence offers valuable tools for scientific discovery, but when used improperly, it can cause blunders. In this paper, we report findings related to the role of Major Histocompatibility Complexes (MHCs) in epitope prediction. Through a serendipitous programmatic error, we observed that methods like TransPHLA yield similar results on both training and testing datasets when only peptides are used, without knowing the specifics of MHC alleles. To further investigate, we developed a new dataset free of the artifacts present in the original. Results from experiments on this new dataset would suggest a field led astray by AI hype, as understanding the MHC allele may not be as critical for epitope prediction as previously thought. Yet, further experiments with synthetic datasets reveal the limitations of current AI applications in biology, paving the way for a stricter multidisciplinary approach.","PeriodicalId":19345,"journal":{"name":"NPJ Systems Biology and Applications","volume":" ","pages":""},"PeriodicalIF":4.4,"publicationDate":"2026-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148550084","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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

Study of wrap mode impact on Pseudomonas aeruginosa motion in the chemotactic field of fungi. 真菌趋化领域中包裹方式对铜绿假单胞菌运动影响的研究。

IF 4.4 2区生物学

NPJ Systems Biology and Applications Pub Date : 2026-07-20 DOI: 10.1038/s41540-026-00789-x

Austin Hansen, Alireza Ramezani, Dale A Pelletier, Tomás A Rush, Roya Zandi, Yi-Syuan Guo, Huijing Du, William Cannon, Mark Alber

{"title":"Study of wrap mode impact on Pseudomonas aeruginosa motion in the chemotactic field of fungi.","authors":"Austin Hansen, Alireza Ramezani, Dale A Pelletier, Tomás A Rush, Roya Zandi, Yi-Syuan Guo, Huijing Du, William Cannon, Mark Alber","doi":"10.1038/s41540-026-00789-x","DOIUrl":"https://doi.org/10.1038/s41540-026-00789-x","url":null,"abstract":"An agent-based discrete computational model biologically calibrated to Pseudomonas aeruginosa migration is used to explore the impacts of bacterial reversals and wrap mode on the efficiency of motion in different environments, both with and without chemotaxis. It is first shown that wrap mode increases the exploration of continuous multimodal chemotactic profiles such as those produced by biologically relevant fungal networks. For cells undergoing a run-reverse pattern, it is shown that the bacteria are likely to remain at the first local chemoattractant maximal production site on a hypha they find. However, with wrap mode, the bacteria can more easily escape these local sites to further explore their neighboring environment along the fungi, suggesting that wrap mode may be beneficial for migration along the fungi in liquid. In a different set of simulations of bacterial motion close to an isolated chemotactic source, wrap mode is shown to increase the ability of a bacterium to reorient toward the source while reducing the overall motion required for similar chemotactic efficiency as a run-reverse strategy, suggesting a potential metabolic benefit. In contrast, model simulations show that wrap mode can increase the rate of dispersal of P. aeruginosa in a nonchemotactic environment.","PeriodicalId":19345,"journal":{"name":"NPJ Systems Biology and Applications","volume":" ","pages":""},"PeriodicalIF":4.4,"publicationDate":"2026-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148536433","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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

MoCaPS: a machine learning model for stratification of cancer-associated cachexia based on blood biomarkers. MoCaPS：基于血液生物标志物的癌症相关恶病质分层的机器学习模型。

IF 4.4 2区生物学

NPJ Systems Biology and Applications Pub Date : 2026-07-16 DOI: 10.1038/s41540-026-00791-3

Kayode D Olumoyin, Magaret Park, Evan W Davis, Jennifer B Permuth, Katarzyna A Rejniak

{"title":"MoCaPS: a machine learning model for stratification of cancer-associated cachexia based on blood biomarkers.","authors":"Kayode D Olumoyin, Magaret Park, Evan W Davis, Jennifer B Permuth, Katarzyna A Rejniak","doi":"10.1038/s41540-026-00791-3","DOIUrl":"10.1038/s41540-026-00791-3","url":null,"abstract":"Identification of minimally invasive biomarkers of cancer-associated cachexia may help to recognize high risk patients for progression to more severe cachectic stages. We developed a machine learning-based Model for Cachectic Patients Stratification (MoCaPS) to determine the sets of blood biomarkers that differentiate between noncachectic (NCa), precachectic (PCa), or cachectic (Ca) patients. The model was applied to data collected from treatment-naïve patients with pancreatic ductal adenocarcinoma through the Florida Pancreas Collaborative multi-institutional cohort study and biobanking initiative. Cachexia status of all participants was classified according to modified criteria by Vigano and colleagues. The MoCaPS model pipeline was designed to work effectively with datasets of moderate size to robustly select predictive data features, and to efficiently handle data imbalance. MoCaPS identified between 4 and 5 biomarkers out of 37 candidates that distinguished precachectic and cachectic stages, and demonstrated accuracies near or greater than 75% for predictors of NCa, PCa, and Ca.","PeriodicalId":19345,"journal":{"name":"NPJ Systems Biology and Applications","volume":" ","pages":""},"PeriodicalIF":4.4,"publicationDate":"2026-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148472037","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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

Multiscale Modeling of Embryonic Morphogenesis from Fertilization to Organogenesis. 从受精到器官发生的胚胎形态发生的多尺度建模。

IF 4.4 2区生物学

NPJ Systems Biology and Applications Pub Date : 2026-07-15 DOI: 10.1038/s41540-026-00788-y

Debanik Deb, Orishma Parida, Laasya Naduthota, Bandan Chakrabortty

引用次数: 0

Sleep restriction reprograms systemic immunity through NK and T cell crosstalk. 睡眠限制通过NK和T细胞串扰重编程系统免疫。

IF 4.4 2区生物学

NPJ Systems Biology and Applications Pub Date : 2026-07-14 DOI: 10.1038/s41540-026-00787-z

Zhengyang Qiu, Jichen Jin, Pengqi Zhang, Chen Li, Yongmei Xi

{"title":"Sleep restriction reprograms systemic immunity through NK and T cell crosstalk.","authors":"Zhengyang Qiu, Jichen Jin, Pengqi Zhang, Chen Li, Yongmei Xi","doi":"10.1038/s41540-026-00787-z","DOIUrl":"https://doi.org/10.1038/s41540-026-00787-z","url":null,"abstract":"Insufficient sleep is a recognized risk factor for inflammatory diseases, yet how sleep loss functionally perturbs immune regulation remains unclear. Here, we apply a multi-omics framework combining two-sample Mendelian randomization, sleep-restriction intervention microarray, and PBMC single-cell profiling to dissect immune consequences of sleep loss. Mendelian randomization associated genetically proxied sleeplessness/insomnia symptoms with alterations in 162 plasma proteins and increased risk across 94 clinical diagnosis traits. Gene expression microarray after sleep restriction confirmed immune activation and stress-response programs. Single-cell RNA sequencing revealed PBMC remodeling with increased NK/NKT cells and decreased γδ T cells and dendritic cells, alongside pro-inflammatory pathway activity. Ligand-receptor analysis identified altered intercellular communication patterns, characterized by increasing signals to NK cells and enhancing NK-T cell-associated interfaces. These findings nominate dysregulated NK cell-T cell crosstalk as a putative mechanism underlying sleep-related inflammation and provide prioritized targets for future validation.","PeriodicalId":19345,"journal":{"name":"NPJ Systems Biology and Applications","volume":" ","pages":""},"PeriodicalIF":4.4,"publicationDate":"2026-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148448386","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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

The unreasonable likelihood of being: origin of life, terraforming, and AI. 不合理的存在可能性：生命的起源、地球化和人工智能。

IF 4.4 2区生物学

NPJ Systems Biology and Applications Pub Date : 2026-07-13 DOI: 10.1038/s41540-026-00785-1

Robert G Endres

引用次数: 0

Drug-tolerant persisters to TRAIL emerge from a dose-dependent surface in a cell-state continuum of sensitivity. 对TRAIL的耐药持久性在细胞状态敏感性连续体中从剂量依赖的表面出现。

IF 4.4 2区生物学

NPJ Systems Biology and Applications Pub Date : 2026-07-13 DOI: 10.1038/s41540-026-00782-4

Giada Fiandaca, Marielle Péré, Kelian Bonhomme, Madalena Chaves, Jérémie Roux

{"title":"Drug-tolerant persisters to TRAIL emerge from a dose-dependent surface in a cell-state continuum of sensitivity.","authors":"Giada Fiandaca, Marielle Péré, Kelian Bonhomme, Madalena Chaves, Jérémie Roux","doi":"10.1038/s41540-026-00782-4","DOIUrl":"https://doi.org/10.1038/s41540-026-00782-4","url":null,"abstract":"Clonal cancer cells show heterogeneous responses to cytotoxic drugs, raising the question of whether this variability reflects discrete phenotypes or a continuum of underlying cell states. We address this by quantifying single-cell caspase-8 activation dynamics after TRAIL treatment and developing an extended mechanistic model of the extrinsic apoptosis pathway that incorporates c-FLIP-mediated control of initiator caspase activation. Fitting this model to individual trajectories across multiple doses recovers cell-specific procaspase-8 and c-FLIP abundances, together with three kinetic parameters, and reproduces the full diversity of observed responses. Embedding these inferred parameters into a shared state space reveals that sensitive and tolerant outcomes do not correspond to discrete subpopulations. Instead, a single biochemical pathway generates a continuous distribution of cell states whose position at treatment determines fate. Linking each trajectory to its early activation rate identifies a dose-dependent hyperplane that partitions this landscape into apoptotic and tolerant regions. Increasing drug dose translates this decision surface predictably, altering the outcome only for cells positioned near the boundary. This geometric perspective explains fractional killing in clonal populations and shows how drug-tolerant persister cells can arise from reversible variation in cell state. It further suggests that shifting state-space distributions relative to the decision surface may offer new strategies to limit persistence.","PeriodicalId":19345,"journal":{"name":"NPJ Systems Biology and Applications","volume":" ","pages":""},"PeriodicalIF":4.4,"publicationDate":"2026-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148437567","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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