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        <title>Frontiers in Systems Biology | New and Recent Articles</title>
        <link>https://www.frontiersin.org/journals/systems-biology</link>
        <description>RSS Feed for Frontiers in Systems Biology | New and Recent Articles</description>
        <language>en-us</language>
        <generator>Frontiers Feed Generator,version:1</generator>
        <pubDate>2026-05-14T18:19:24.305+00:00</pubDate>
        <ttl>60</ttl>
        <item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fsysb.2026.1795422</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fsysb.2026.1795422</link>
        <title><![CDATA[Mpox coinfections and clinical manifestation in Africa: a systematic review and meta-analysis]]></title>
        <pubdate>2026-05-07T00:00:00Z</pubdate>
        <category>Systematic Review</category>
        <author>Fabrice Zobel Lekeumo Cheuyem</author><author>Chabeja Achangwa</author><author>Lionel Berthold Keubou Boukeng</author><author>Rick Tchamani</author><author>Jessica Davies</author><author>Christian Noël Malaka</author><author>Armel Evouna Mbarga</author>
        <description><![CDATA[BackgroundMpox remains a significant public health challenge in Africa, where endemic transmission persists alongside a high burden of other infectious diseases. Although the epidemiology and clinical impact of coinfections with human immunodeficiency virus (HIV) and varicella-zoster virus (VZV) remain poorly understood across the continent, these coinfections may influence clinical presentation, disease severity, and diagnostic accuracy. This aimed to describe the coinfections (VZV and HIV) patterns among confirmed mpox cases and characterize the trend of clinical presentation of mpox patients in Africa.MethodsFollowing PRISMA guidelines, we registered our protocol in PROSPERO (CRD420251133960) and conducted a systematic review and meta-analysis. We searched multiple electronic databases and grey literature through 27 February 2025, identifying observational studies from Africa that reported mpox coinfections (VZV and/or HIV) and associated clinical symptoms. Random-effects models were used to calculate pooled prevalence, while subgroup analyses and meta-regression explored sources of heterogeneity across WHO regions, countries, study designs, settings, and participant types.ResultsA total of 23 studies conducted across African countries were included. The pooled prevalence of VZV–mpox coinfection was 8.73% (95% CI: 2.05–30.43; 10 studies; n = 2,681; I2 = 75.7%), while HIV–mpox coinfection prevalence was 4.29% (95% CI: 1.78–9.96; 9 studies; n = 1,939; I2 = 88.4%), both of which had significant heterogeneity. Coinfections were far more prevalent in hospital-based environments than in community-based research. The rash was observed across all clades, but the clinical manifestations varied by viral clades, with clades I and Ia linked to more severe systemic symptoms than clade II.DiscussionsHIV and VZV coinfections with mpox pose a major yet possibly underestimated burden in Africa and are linked to more severe clinical presentations, particularly in hospital environments. The necessity of including clinical, epidemiological, and genomic in mpox monitoring systems is underscored by observed clinical differences across clades. Improving patient management and outbreak preparedness across the continent requires strengthening diagnostic capacity and routinely screening for coinfections.Systematic Review Registrationhttps://www.crd.york.ac.uk/PROSPERO/view/CRD420251133960, identifier CRD420251133960.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fsysb.2026.1819469</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fsysb.2026.1819469</link>
        <title><![CDATA[From empirical vaccinology to predictive systems-based vaccine design: multi-omics integration, artificial intelligence, and global equity challenges]]></title>
        <pubdate>2026-04-30T00:00:00Z</pubdate>
        <category>Review</category>
        <author>Nicole Simone De Lima Coelho</author><author>Viviana Simone De Lima Coelho</author>
        <description><![CDATA[Although vaccination remains one of the most impactful interventions in contemporary public health, with consistent and widely documented reductions in morbidity and mortality, the traditional empirical development of vaccines—largely based on trial-and-error strategies—still reflects an incomplete understanding of the complexity underlying immune responses. With the emergence of systems immunology, supported by multi-omics technologies, mathematical modeling, and computational tools, vaccinology has progressively incorporated the integration of multiple biological layers, addressing critical mechanistic gaps and mitigating limitations of the classical model, thereby transitioning from an empirical framework toward a predictive and integrative paradigm. In this context, the present review critically examines how systems immunology contributes to rational vaccine design by exploring its technological foundations—particularly omics approaches—discussing strategies for data integration, analyzing translational implications, and incorporating considerations related to Artificial Intelligence (AI), regulatory governance, ethics, and global equity. Within this evolving landscape, systems vaccinology has demonstrated promising results and optimistic perspectives, particularly regarding predictive capacity, immunological stratification, vaccine personalization, and potential epidemiological impact. At the same time, challenges including reproducibility concerns, risk of overfitting, the distinction between multi-omic correlation and functional causality, the need for longitudinal and experimental validation, algorithmic bias, excessive reliance on computational models, and regulatory barriers to the approval of data-driven vaccines represent important limitations of this approach. Taken together, these considerations indicate that systems immunology constitutes not merely a technological refinement but a genuine paradigm shift, redefining vaccine development as a predictive, iterative, and integrative process that must be scientifically validated and ethically contextualized, with profound implications for global public health.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fsysb.2026.1734322</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fsysb.2026.1734322</link>
        <title><![CDATA[AI-based methods for the assessment of DNA damage and repair mechanisms]]></title>
        <pubdate>2026-04-29T00:00:00Z</pubdate>
        <category>Review</category>
        <author>Paola Lecca</author><author>Michela Lecca</author><author>Adaoha Elizabeth Ihekwaba-Ndibe</author>
        <description><![CDATA[In recent years, a growing number of artificial intelligence (AI)–driven approaches have been developed to elucidate chemico-biological interactions associated with DNA damage and oxidative stress. Deep learning–based techniques, in particular, have demonstrated substantial potential within molecular biology and toxicology. As a result, researchers and clinicians alike hold high expectations that AI-enabled tools will soon make meaningful contributions to our understanding of the molecular and cellular mechanisms governing DNA damage and repair. In this article, we present a concise yet comprehensive overview of the computational methodologies underpinning contemporary deep learning approaches. We examine their capacity to support DNA damage assessment by revealing mechanistic insights into damage induction and response pathways. Particular emphasis is placed on deep learning techniques designed to enhance the analysis of complex biological data, including the automated detection and quantification of DNA damage from comet assay images and microscopy-based platforms. Furthermore, we critically assess the extent to which a gap exists between the expectations of researchers, biologists, and clinicians and the current practical capabilities of AI technologies in this domain. Finally, we offer a forward-looking perspective on how this gap might be narrowed, outlining key methodological, data-driven, and translational challenges that must be addressed to fully realize the potential of AI in DNA damage and repair research.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fsysb.2026.1708877</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fsysb.2026.1708877</link>
        <title><![CDATA[Structure and multipartite genome architecture of the mitochondrial genome in the endangered medicinal plant Fritillaria taipaiensis P. Y. Li]]></title>
        <pubdate>2026-04-22T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>De Xu</author><author>Jingtao Liu</author><author>Juan Huang</author><author>Qianqian Ma</author><author>Tao Wang</author><author>Zhou Xie</author><author>Xue Liu</author><author>Liang Fu</author>
        <description><![CDATA[Fritillaria taipaiensis: a medicinal plant of the Liliaceae family endemic to the Qinling Mountains and southern regions of China, is renowned for its therapeutic properties in relieving cough and moistening the lungs. Despite growing interest in the organellar genomes of related species, the mitochondrial genome (mitogenome) of F. taipaiensis has remained uncharacterized. In this study, we successfully assembled and annotated the complete mitogenome of F. taipaiensis using a combination of Illumina and Nanopore technologies. The mitogenome consisted of 23 circular chromosomes with a total length of 847,160 bp and contained 49 annotated genes, including 34 protein-coding genes (PCGs), 12 transfer RNA (tRNA) genes, and 3 ribosomal RNA (rRNA) genes. Codon usage analysis revealed a strong bias toward A- and U-ending codons. Additionally, we identified 178 simple sequence repeats (SSRs) and 127 dispersed repeats. We also detected ten chloroplast-derived DNA fragments transferred to the mitogenome, most of which involved tRNA genes. A total of 488 RNA editing events were predicted in PCGs, all involving C-to-U conversions. Phylogenetic analysis based on 21 representative plant mitogenomes placed F. taipaiensis in a position congruent with its traditional taxonomic classification. These findings enhance our understanding of the mitogenome architecture and evolutionary dynamics of F. taipaiensis and provide valuable genomic resources for future studies in conservation biology, population genetics, and comparative genomics within the Fritillaria genus.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fsysb.2026.1686085</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fsysb.2026.1686085</link>
        <title><![CDATA[Design of synthetic selenopeptides with antioxidant activity for the treatment of XP and non-melanoma skin cancer]]></title>
        <pubdate>2026-04-09T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Arthur Alves Coelho</author><author>Eduarda Pereira Soares Dias</author><author>André Kipnis</author>
        <description><![CDATA[IntroductionXeroderma Pigmentosum (XP) is a rare, autosomal recessive disorder characterized by extreme sensitivity to ultraviolet (UV) light. Current treatments primarily focus on symptom management and surgical tumor excisions. Selenopeptides, which possess a modified residue of Cysteine (Selenocysteine), are distinguished for their antioxidant and photoprotective properties. These properties could be beneficial in counteracting the oxidative DNA damage observed in XP lesions.ObjectiveBuilding upon the work initiated by the Brazilian SynBio UFG iGEM Design League team, this study aimed to develop a new approach for designing and expressing synthetic selenopeptides through in silico optimization, to target both XP and non-melanoma skin cancers.MethodsFive novel sequences of selenopeptides, named Selera, were designed and evaluated through bioinformatic tools. Selera-2 was chosen as the best model designed for its physico-chemical and structural properties and was submitted to docking analysis with therapeutic targets.Results and DiscussionDocking models of B-RAF and TrxR1 demonstrated to be the most stable binding sites, considering low-binding energy levels and molecular dynamics profile, suggesting possible targets for anti tumor effect. A new recombinant expression plasmid vector was proposed, p-Sec Reg 1, in order to ensure optimal expression for future trials and production. The in silico validation of this innovative approach allows the creation of novel selenopeptides and their prospective applications in the treatment of XP and other skin cancer conditions.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fsysb.2026.1793501</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fsysb.2026.1793501</link>
        <title><![CDATA[Commentary: GETgene-AI: a framework for prioritizing actionable cancer drug targets]]></title>
        <pubdate>2026-03-30T00:00:00Z</pubdate>
        <category>General Commentary</category>
        <author>Ling Yin</author>
        <description></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fsysb.2026.1818525</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fsysb.2026.1818525</link>
        <title><![CDATA[Systems biology in the era of AI: “winter” or “evolution”?]]></title>
        <pubdate>2026-03-24T00:00:00Z</pubdate>
        <category>Opinion</category>
        <author>Mohamed Helmy</author><author>Kumar Selvarajoo</author>
        <description></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fsysb.2026.1804193</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fsysb.2026.1804193</link>
        <title><![CDATA[Streamlining IRB review of AI human subjects research (AIHSR): the three-stage framework]]></title>
        <pubdate>2026-03-06T00:00:00Z</pubdate>
        <category>Policy Brief</category>
        <author>Tamiko Eto</author><author>Heather Miller</author><author>David Vidal</author><author>Mark Lifson</author>
        <description><![CDATA[Oversight of Artificial Intelligence in Human Subjects Research (AI HSR) presents unique challenges. These challenges arise from both the non-linear and iterative nature of AI development, as well as from the way AI shifts risk from individual research subjects to larger populations affected by AI-driven decisions and data handling. Traditional Institutional Review Boards (IRBs) often struggle to keep pace with these changes, which can lead to gaps in risk assessment and delays in the review process. There is a growing need for transparent, repeatable methods to manage AI risk in healthcare. This paper introduces the Three-Stage Framework, a risk-based oversight model designed to align ethical and regulatory review with an AI project’s stage of maturity and potential human impact. By aligning the level and timing of IRB review with the types of risks present at each stage of AI system development, the framework supports appropriate regulatory pathways and documents expectations while maintaining effective protection of human subjects. Through gradual, stage-appropriate documentation, the approach supports responsible and adaptive innovation while preparing AI systems for safe and ethical use across biomedical, social, behavioral, and educational domains. This approach prepares AI systems for safe and ethical use, accelerates compliant research, and helps IRBs and institutions maintain trustworthiness while protecting human subjects.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fsysb.2025.1659648</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fsysb.2025.1659648</link>
        <title><![CDATA[Avian cecal microbiome response and resilience to Newcastle disease are dictated by breed background]]></title>
        <pubdate>2026-02-12T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Aqsa Ameer</author><author>Farrukh Saleem</author><author>Ciara Keating</author><author>Farhan Afzal</author><author>Hamid Irshad</author><author>Khurshid Ahmed</author><author>Sadia Sattar</author><author>Umer Zeeshan Ijaz</author><author>Sundus Javed</author>
        <description><![CDATA[A wide range of viral infections threaten the long-term sustainability of poultry production. Newcastle disease (ND), caused by Newcastle disease virus (NDV), is endemic in most Asian countries, including Pakistan, causing 50%–100% mortality in young and mature chickens. Some local chicken breeds show resistance to certain diseases and have greater survival probability. The chicken gut microbiome is linked to immune response against infections and to production performance parameters. The present study aims to comprehend disease resistance patterns in multiple chicken breeds with respect to gut microbial communities. Day-old Naked Neck, Black Australorp, Rhode Island Red, white layer, and broiler chicks were raised on an antibiotic-free diet in a semi-controlled setup. Vaccinated and non-vaccinated birds were challenged with NDV. Disease onset was delayed in breeds other than broilers, in which disease symptoms appeared at day 3 post-challenge with maximum severity and mortality. Other breeds, irrespective of vaccination, survived through the challenge period. Naked Neck showed the least variation in clinical features and growth parameters. A lower diversity in broiler groups with a significant decrease after NDV challenge was revealed by 16S rRNA amplicon sequencing of cecal DNA. Furthermore, broiler cecal core microbiome membership was found to be more variable than other breeds. Moreover, differentially abundant genera were observed across treatment groups and breeds with a similar effect on the predicted metabolic pathways, indicating varied energy metabolism responses. Shotgun metagenomics revealed a higher abundance of functional genes, including antimicrobial resistance (AMR) genes, stress genes, virulence genes, and amino acid degradation genes in the broiler NDV-infected group compared to the control group. The gut microbiota in chickens affects immunity to infections, health, and productivity. Compared to broilers, local chicken breeds, specifically Naked Neck, are found to have high immune competence in resisting ND while maintaining most performance metrics. Broilers show lower alpha diversity with an unstable core microbiome. Therefore, stable core microbiome maintenance may help the birds cope with the viral infection. The results support the farming of resistant chicken breeds over broilers to reduce production losses from NDV outbreaks.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fsysb.2026.1729027</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fsysb.2026.1729027</link>
        <title><![CDATA[Mathematical modeling of bone remodeling after surgical menopause]]></title>
        <pubdate>2026-02-11T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Anna C. Nelson</author><author>Edwina F. Yeo</author><author>Yun Zhang</author><author>Carley V. Cook</author><author>Sophie Fischer-Holzhausen</author><author>Lauryn Keeler Bruce</author><author>Pritha Dutta</author><author>Samaneh Gholami</author><author>Brenda J. Smith</author><author>Ashlee N. Ford Versypt</author>
        <description><![CDATA[Osteoporosis is a skeletal pathology characterized by decreased bone mass and structural deterioration resulting from an imbalance in bone metabolic processes. Estrogen deficiency in postmenopausal women leads to an increased risk of osteoporosis, while women who have undergone complete oophorectomies display an even higher risk due to the sudden decrease in estrogen. Some evidence indicates that bone loss slows in the period beyond 15 years after surgery; however, there is substantial uncertainty in clinical data. To explore the effects of surgically induced menopausal transition, here we propose a mathematical model for the bone cell dynamical responses to sudden estrogen deficiency, which extends an existing model for osteoporosis due to aging and natural menopause. Using data on key effects observed in female mice and humans after bilateral oophorectomy, this new model considers the role of osteocytes embedded within the mineralized bone matrix in regulating bone remodeling, which results in net bone loss after surgical menopause. The model parameter values in natural and surgical menopause were estimated from aggregated human clinical data from existing longitudinal studies. The new model effectively captures the previously unmodeled increase in bone loss during the first 15 years post-surgical menopause and the rebound in bone mineral density in the long-term. With this model, effects of treatments on targeting osteocyte dynamics could be explored in the future.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fsysb.2025.1668595</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fsysb.2025.1668595</link>
        <title><![CDATA[A synthetic biology toolkit for rationally designing genetic circuits in Acinetobacter baumannii]]></title>
        <pubdate>2026-01-15T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Sara Letrari</author><author>Lisa Faccincani</author><author>Stefano Intini</author><author>Ilgin Ertan</author><author>Tommaso Varaschin</author><author>Francesca Galiazzo</author><author>Marco Costanzo</author><author>Giorgia D’angelo</author><author>Valentina Del Giudice</author><author>Luca Guarnieri</author><author>Alex Martini</author><author>Asia Picchi</author><author>Chiara Ravazzolo</author><author>Niccolò Venturini Degli Esposti</author><author>Chiara Zanin</author><author>Livio Trainotti</author><author>Cristiano De Pittà</author><author>Claudia Del Vecchio</author><author>Ignazio Castagliuolo</author><author>Massimo Bellato</author>
        <description><![CDATA[IntroductionAntimicrobial resistance (AMR) poses a severe global health threat, with Acinetobacter baumannii among the critical AMR priorities highlighted by World Health Organization (WHO). This Gram-negative pathogen exhibits intrinsic resistance traits, exceptional environmental persistence, and high genomic plasticity, harboring resistance islands.MethodsTo combat AMR through synthetic biology, this study characterizes a library of BioBrick parts to be adopted in A. baumannii engineering and develops a modular CRISPR interference (CRISPRi) platform.ResultsKey components were characterized, including two plasmid vectors, a library of inducible and constitutive promoters, and a CRISPRi-mediated repression system; for the latter, a testbed for biofilm-related genes implicated in the downregulation of antibiotic resistance is also provided.DiscussionBy enabling tunable transcriptional control through the characterized promoters and ensuring the ability to downregulate gene expression via CRISPRi, this synthetic biology toolkit lays the foundation for the rational design of genetic circuits to study and counteract AMR in A. baumannii. The modular platform here characterized provides a valuable resource for the iGEM community to advance functional genomic approaches against this alarming global health challenge.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fsysb.2025.1721019</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fsysb.2025.1721019</link>
        <title><![CDATA[Metagenomics enables the first detection of Trypanosoma sp. in Streblidae (Diptera: Hippoboscoidea) parasitizing bats in São Paulo, Brazil]]></title>
        <pubdate>2026-01-09T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Roberta Marcatti</author><author>Lucas Augusto Moysés Franco</author><author>Esmenia Coelho Rocha</author><author>Marcello Schiavo Nardi</author><author>Juliana Laurito Summa</author><author>Eric Thal Brambilla Cordeiro da Silva</author><author>Adriana Ruckert da Rosa</author><author>Débora Cardoso de Oliveira</author><author>Gustavo Graciolli</author><author>Ester Cerdeira Sabino</author>
        <description><![CDATA[IntroductionBats play important ecological roles but can also harbor a wide diversity of pathogens, including trypanosomatids. Knowledge about the circulation of Trypanosoma spp. in bat ectoparasites remains limited, particularly in peri-urban environments.MethodsIn this study, we used shotgun metagenomic sequencing to investigate the presence of Trypanosoma spp. in streblid flies parasitizing Carollia perspicillata bats collected in a peri-urban fragment of the Atlantic Forest in São Paulo, Brazil. A small, preliminary set of pooled samples was analyzed, followed by phylogenetic reconstruction.ResultsTrypanosoma sequences were detected in flies from the family Streblidae. Phylogenetic analysis showed that these sequences cluster within the Neobat 4 clade, which has previously been reported in Carollia spp. bats. This represents the first detection of Trypanosoma sp. in streblid flies parasitizing bats in São Paulo.DiscussionAlthough the vector competence of streblid flies for Trypanosoma transmission is still unknown, their close ecological association with bats suggests that they may serve as a non-invasive tool for pathogen surveillance when direct bat sampling is limited. This study expands the known geographic distribution of the Neobat 4 clade and contributes to understanding parasite circulation among bats and their ectoparasites.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fsysb.2025.1715692</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fsysb.2025.1715692</link>
        <title><![CDATA[Neural networks and foundation models: two strategies for EEG-to-fMRI prediction]]></title>
        <pubdate>2025-12-17T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Maël Donoso</author>
        <description><![CDATA[Electroencephalography (EEG) and functional Magnetic Resonance Imaging (fMRI) are two widely used neuroimaging techniques, with complementary strengths and weaknesses. Predicting fMRI activity from EEG activity could give us the best of both worlds, and open new horizons for neuroscience research and neurotechnology applications. Here, we formulate this prediction objective both as a classification task (predicting whether the fMRI signal increases or decreases) and a regression task (predicting the value of this signal). We follow two distinct strategies: training classical machine learning and deep learning models (including MLP, CNN, RNN, and transformer) on an EEG-fMRI dataset, or leveraging the capabilities of pre-trained large language models (LLMs) and large multimodal models. We show that predicting fMRI activity from EEG activity is possible for the brain regions defined by the Harvard-Oxford cortical atlas, in the context of subjects performing a neurofeedback task. Interestingly, both strategies yield promising results, possibly highlighting two complementary paths for our prediction objective. Furthermore, a Chain-of-Thought approach demonstrates that LLMs can infer the cognitive functions associated with EEG data, and subsequently predict the fMRI data from these cognitive functions. The natural combination of the two strategies, i.e., fine-tuning an LLM on an EEG-fMRI dataset, is not straightforward and would certainly require further study. These findings could provide important insights for enhancing neural interfaces and advancing toward a multimodal foundation model for neuroscience, integrating EEG, fMRI, and possibly other neuroimaging modalities.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fsysb.2025.1651930</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fsysb.2025.1651930</link>
        <title><![CDATA[BioMedKG: multimodal contrastive representation learning in augmented BioMedical knowledge graphs]]></title>
        <pubdate>2025-12-08T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Tien Dang</author><author>Viet Thanh Duy Nguyen</author><author>Minh Tuan Le</author><author>Truong-Son Hy</author>
        <description><![CDATA[Biomedical Knowledge Graphs (BKGs) integrate diverse datasets to elucidate complex relationships within the biomedical field. Effective link prediction on these graphs can uncover valuable connections, such as potential new drug-disease relations. We introduce a novel multimodal approach that unifies embeddings from specialized Language Models (LMs) with Graph Contrastive Learning (GCL) to enhance intra-entity relationships while employing a Knowledge Graph Embedding (KGE) model to capture inter-entity relationships for effective link prediction. To address limitations in existing BKGs, we present PrimeKG++, an enriched knowledge graph incorporating multimodal data, including biological sequences and textual descriptions for each entity type. By combining semantic and relational information in a unified representation, our approach demonstrates strong generalizability, enabling accurate link predictions even for unseen nodes. Experimental results in PrimeKG++ and the DrugBank drug-target interaction dataset demonstrate the effectiveness and robustness of our method in diverse biomedical datasets. Our source code, pre-trained models, and data are publicly available at https://github.com/HySonLab/BioMedKG.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fsysb.2025.1603749</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fsysb.2025.1603749</link>
        <title><![CDATA[Towards effective cystic fibrosis gene therapy by optimizing prime editing and pulmonary-targeted LNPs]]></title>
        <pubdate>2025-12-03T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Kaya Sophie Lange</author><author>Lisa Marie Wiesner</author><author>Kathleen Susat</author><author>Vera Köhler</author><author>Malte Lenger</author><author>Christian Alexander Michalek</author><author>Anna-Lena Baack</author><author>Philip Frederic Mundt</author><author>Kai Kanthak</author><author>Isabell Alexandra Guckes</author><author>Liliana Sanfilippo</author><author>Lucas Haverkamp</author><author>Utkarsh Anil Mahajan</author><author>Felicitas Helena Zimmer</author><author>Sinan Zimmermann</author><author>Marco Tobias Radukic</author><author>Levin Joe Klages</author><author>Jörn Kalinowski</author><author>Kristian Mark Müller</author>
        <description><![CDATA[Cystic fibrosis (CF) is the most prevalent inherited disease. Inactivating mutations in the Cystic Fibrosis Transmembrane Conductance Regulator (CFTR) gene lead to the accumulation of viscous mucus and subsequent respiratory complications. This study optimized a prime editing (PE) approach to correct CFTR mutations focusing on the F508del mutation. Prime editing allowed to introduce missing bases without double-strand breaks using a Cas9-nickase fused with a reverse transcriptase in combination with a prime editing guide RNA (pegRNA). Various self-designed pegRNAs were compared. For delivery, various lipid nanoparticles (LNP) were tested, which were optimized for stability and lung cells targeting based on lipid selection or chitosan complexion. A fluorescence reporter system, pPEAR_CFTR, was developed mimicking F508del for validation. The five pegRNAs yielding the highest efficiency were used for genomic CFTR correction in a CF bronchial cell line. Nanopore sequencing of genomic DNA revealed approximate 5% edited reads. These results highlight the promise of prime editing-LNP systems for precise and lung-specific gene correction, paving the way for novel therapies in cystic fibrosis and other pulmonary genetic disorders.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fsysb.2025.1710604</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fsysb.2025.1710604</link>
        <title><![CDATA[Correction: MicrobiomeKG: bridging microbiome research and host health through knowledge graphs]]></title>
        <pubdate>2025-10-27T00:00:00Z</pubdate>
        <category>Correction</category>
        <author>Frontiers Production Office </author>
        <description></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fsysb.2025.1656683</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fsysb.2025.1656683</link>
        <title><![CDATA[The role of neutrophil-to-lymphocyte ratio in the prognosis of chronic kidney disease: insights from the NHANES cohort study]]></title>
        <pubdate>2025-10-27T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Ying Liu</author><author>Ru Wang</author><author>Jinguo Yuan</author><author>Jin Zhao</author>
        <description><![CDATA[ObjectiveTo investigate the association of neutrophil-to-lymphocyte ratio (NLR) with the cardiovascular disease (CVD) and all-cause mortality in patients with chronic kidney disease (CKD).MethodsUsing date from NHANES survey 2009–2018, 2,635 patients with CKD were eventually included in this study. The population was stratified into two groups based on the median NLR. Kaplan-Meier method with log-rank tests for significance was used for survival analysis. Weighted Cox proportional hazards regression models were employed to estimate the hazard ratio (HR) and corresponding 95% confidence interval (CI) for all-cause and CVD mortality. The potential nonlinear relationship between NLR and CVD and all-cause mortality was assessed using restricted cubic spline (RCS) models. The time-dependent receiver operating characteristic (ROC) curve was utilized to assess the precision of NLR in predicting survival outcomes.ResultsThe Kaplan-Meier curve indicated a significant difference in overall survival between the two groups (log-rank test, p < 0.0001). Compared to lower NLR group, participants in the higher NLR group had HR of 1.56 (1.30, 1.87) for all-cause mortality and 2.07 (1.51, 2.84) for CVD mortality, respectively. We observed a significant nonlinear relationship between NLR and CVD and all-cause mortality (p < 0.0001). The time-dependent ROC curve demonstrated that the areas under the curve for 1-, 3-, 5-, and 10-year survival rates were 0.69, 0.65, 0.63, and 0.62 for all-cause mortality, and 0.71, 0.67, 0.66, and 0.64 for CVD mortality, respectively.ConclusionA higher NLR is linked to an elevated risk of CVD and all-cause mortality in patients with CKD. Additionally, NLR can serve as a potential prognostic indicator for CKD patients.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fsysb.2025.1717030</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fsysb.2025.1717030</link>
        <title><![CDATA[Correction: A guide to bayesian networks software for structure and parameter learning, with a focus on causal discovery tools]]></title>
        <pubdate>2025-10-23T00:00:00Z</pubdate>
        <category>Correction</category>
        <author>Francesco Canonaco</author><author>Joverlyn Gaudillo</author><author>Nicole Astrologo</author><author>Fabio Stella</author><author>Enzo Acerbi</author>
        <description></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fsysb.2025.1693064</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fsysb.2025.1693064</link>
        <title><![CDATA[Structural properties and asymptotic behavior of bacterial two-component systems]]></title>
        <pubdate>2025-10-21T00:00:00Z</pubdate>
        <category>Hypothesis and Theory</category>
        <author>Irene Zorzan</author><author>Chiara Cimolato</author><author>Luca Schenato</author><author>Massimo Bellato</author>
        <description><![CDATA[Bacteria rely on two-component signaling systems (TCSs) to detect environmental cues and orchestrate adaptive responses. Despite their apparent simplicity, TCSs exhibit a rich spectrum of dynamic behaviors arising from network architectures, such as bifunctional enzymes, multi-step phosphorelays, transcriptional feedback loops, and auxiliary interactions. This study develops a generalized mathematical model of a TCS that integrates these various elements. Using systems-level analysis, we elucidate how network architecture and biochemical parameters shape key properties such as stability, monotonicity, and signal amplification. Analytical conditions are derived for when the steady-state levels of phosphorylated proteins exhibit robustness to variations in protein abundance. The model characterizes how equilibrium phosphorylation levels depend on the absolute and relative abundances of the two components. Specific scenarios are explored, including the MprAB system from Mycobacterium tuberculosis and the EnvZ/OmpR system from textit Escherichia coli, to describe the potential role of reverse phosphotransfer reactions. By combining mechanistic modeling with system-level techniques, such as nullcline analysis, this study offers a unified perspective on the design principles underlying the versatility of bacterial signal transduction. The generalized modeling framework lays a theoretical foundation for interpreting experimental dynamics and rationally engineering synthetic TCS circuits with prescribed response dynamics.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fsysb.2025.1622753</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fsysb.2025.1622753</link>
        <title><![CDATA[Dietary composition and fasting regimens differentially impact the gut microbiome and short-chain fatty acid profile in a Pakistani cohort]]></title>
        <pubdate>2025-10-17T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Farzana Gul</author><author>Hilde Herrema</author><author>Aqsa Ameer</author><author>Mark Davids</author><author>Arshan Nasir</author><author>Konstantinos Gerasimidis</author><author>Umer Zeeshan Ijaz</author><author>Sundus Javed</author>
        <description><![CDATA[PurposeFasting is known to have beneficial effects on human physiology and health due to changes in gut microbiota and its associated metabolites. We investigated the effects of intermittent and Ramadan fasting on the gut microbial composition, diversity, and short-chain fatty acid (SCFA) profile in a Pakistani population.MethodsPaired fecal samples—a total of 29 for Ramadan fasting (divided into three groups, before and after completion and after 3 months) and 22 for intermittent fasting (divided into two groups, day 1 and day 10)—were collected for both 16S rRNA microbiome profiling and SCFA analysis. Study volunteers also provided a detailed questionnaire about the dietary regimen before and during the fasting period. Descriptive statistics were applied to ascertain variations in the gut microbiome and SCFAs attributable to changes in food consumption during fasting.ResultsRamadan fasting increased the bacterial taxonomic and functional diversity and decreased the abundance of certain harmful microbes such as Blautia, Haemophilus, Desulfovibrio, Lachnoclostridium, and Porphyromonas. Intermittent fasting showed increased abundance of Prevotella, Lactobacillus, and Anaerostipes. Ramadan fasting also led to a significant increase in SCFAs including C7, iC4, and iC6, accounting for variability in microbial composition and phylogeny, respectively. In intermittent fasting, C5, iC5, and iC6 contributed to variability in microbial composition, phylogeny, and function, respectively.ConclusionBoth fasting regimens impacted gut microbiome and metabolic signatures, but Ramadan fasting showed a more drastic effect due to the 30 days compliance period and water restriction than intermittent fasting. Ramadan fasting also improved metabolic health by increasing the abundance of SCFA-producing microbes. With Ramadan fasting, most microbial taxa reverted to their prefasting state after resumption of normal feeding patterns with few exceptions, indicating impact on microbial niche creation with prolonged fasting regimens that benefit Enterococcus, Turibacter, and Klebsiella colonization. The dietary regimen adopted during fasting, especially the consumption of high-fat-content food items, accounted for persistent gut microbial changes.]]></description>
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