Article
Biochemical Research Methods
Amanda E. Starr, Shelley A. Deeke, Zhibin Ning, Joseph de Nanassy, Ruth Singleton, Eric Benchimol, David R. Mack, Alain Stintzi, Daniel Figeys
Summary: Proteomic and bioinformatic analyses were conducted on colon biopsies from treatment-naive pediatric patients with IBD to characterize disease pathogenesis, revealing distinct proteomic patterns in inflamed and noninflamed tissues. Comparing pre- and post-treatment proteomes from CD patients identified proteins associated with therapy response, such as creatine kinase B and basigin.
JOURNAL OF PROTEOME RESEARCH
(2021)
Article
Immunology
Sruthi Vijaya Retnakumar, Ramasatyaveni Geesala, Alexis Bretin, Julien Tourneur-Marsille, Eric Ogier-Denis, Thorsten Maretzky, Hang Thi Thu Nguyen, Sylviane Muller
Summary: Inflammatory bowel disease (IBD) is a growing global health problem, and there is currently a lack of safe and targeted medicines for its treatment. This study investigated the potential use of a therapeutic peptide, P140, which corrects autophagy dysfunctions, in three mouse models of colitis. The results showed that P140 treatment attenuated the severity of colitis and corrected the expression of autophagy markers and pro-inflammatory mediators. These findings suggest that the autophagy modulator P140 holds promise for the treatment of IBD.
JOURNAL OF AUTOIMMUNITY
(2022)
Article
Gastroenterology & Hepatology
Flora Clement, Adrien Nougarede, Stephanie Combe, Frederique Kermarrec, Arindam K. Dey, Patricia Obeid, Arnaud Millet, Fabrice P. Navarro, Patrice N. Marche, Eric Sulpice, Xavier Gidrol
Summary: Inflammatory bowel diseases are debilitating conditions with limited treatment options. This study explores the potential of siRNA drugs targeting specific kinases involved in pro-inflammatory diseases. The results demonstrate that siRNA drugs have higher efficiency and selectivity at lower doses compared to traditional kinase inhibitors, offering a promising alternative for chronic inflammatory diseases.
JOURNAL OF CROHNS & COLITIS
(2022)
Article
Cardiac & Cardiovascular Systems
Kaiwen Wu, Aoshuang Li, Lei Liu, Tao Shu, Demeng Xia, Xiaobin Sun
Summary: A two-sample Mendelian randomization study found no evidence to support a significant impact of inflammatory bowel disease on cardiovascular disease outcomes. Similar results were observed using various MR analysis methods, with sensitivity analyses demonstrating the robustness of the findings.
FRONTIERS IN CARDIOVASCULAR MEDICINE
(2022)
Article
Gastroenterology & Hepatology
Nikolas Plevris, Charlie W. Lees
Summary: Inflammatory bowel disease is a progressive and debilitating condition, emphasizing the importance of early and effective treatment for improving patient outcomes. Proactive monitoring is crucial to ensuring treatment strategies are working, highlighting the need for an optimal treat-to-target monitoring strategy during key phases of the disease. The advent of new technology may enhance monitoring capabilities and shape future monitoring strategies for inflammatory bowel diseases.
Review
Cell Biology
Rirong Chen, Xiaobai Pang, Li Li, Zhirong Zeng, Minhu Chen, Shenghong Zhang
Summary: This article explores the role of deubiquitinases in inflammatory bowel disease (IBD), including their regulation of inflammation signalling pathways, impact on genetic susceptibility and intestinal barrier function, and influence on the immune system and gut microbiota. These studies provide important insights and potential therapeutic solutions for understanding and treating IBD.
CELL DEATH & DISEASE
(2022)
Article
Dermatology
Yunbo Wu, Xiaojian Li, Shiyu Chen, Tong Liu, Xiaomin Chen, Ping Zhan, Guirong Qiu
Summary: This study used Mendelian randomization (MR) design to explore the potential causal association between inflammatory bowel disease (IBD) and rosacea. The results showed a significant association between genetically predicted IBD and rosacea, with different subtypes of IBD having different degrees of association with rosacea.
DERMATOLOGIC THERAPY
(2023)
Review
Cardiac & Cardiovascular Systems
A. S. Giordani, A. Candelora, M. Fiacca, C. Cheng, B. Barberio, A. Baritussio, R. Marcolongo, S. Iliceto, E. Carturan, M. De Gaspari, S. Rizzo, C. Basso, G. Tarantini, E. V. Savarino, A. L. P. Caforio
Summary: This study retrospectively analyzed data and conducted a literature review on myocarditis associated with inflammatory bowel diseases (IBD). It found that myocarditis in association with IBD is more common in young males and generally has a benign clinical course, but a subset of patients may develop giant cell myocarditis and require immunosuppression.
INTERNATIONAL JOURNAL OF CARDIOLOGY
(2023)
Review
Biochemistry & Molecular Biology
HyunTaek Jung, Jae Seok Kim, Keum Hwa Lee, Kalthoum Tizaoui, Salvatore Terrazzino, Sarah Cargnin, Lee Smith, Ai Koyanagi, Louis Jacob, Han Li, Sung Hwi Hong, Dong Keon Yon, Seung Won Lee, Min Seo Kim, Paul Wasuwanich, Wikrom Karnsakul, Jae Il Shin, Andreas Kronbichler
Summary: Inflammatory bowel disease (IBD) is a chronic inflammatory disease of the gastrointestinal tract that mainly affects young people. Recent studies have shown that microRNAs (miRNAs) play an important role in the pathogenesis, diagnosis, and treatment of IBD.
INTERNATIONAL JOURNAL OF BIOLOGICAL SCIENCES
(2021)
Article
Gastroenterology & Hepatology
Tung On Yau, Jayakumar Vadakekolathu, Gemma Ann Foulds, Guodong Du, Benjamin Dickins, Christos Polytarchou, Sergio Rutella
Summary: This study collected transcriptomic data from inflammatory bowel disease patients receiving anti-TNF-alpha therapy and found that hyperactive neutrophil chemotaxis influenced the response to anti-TNF-alpha treatment. IL13RA2 was identified as a potential biomarker to predict the response to anti-TNF-alpha treatment.
JOURNAL OF GASTROENTEROLOGY AND HEPATOLOGY
(2022)
Review
Biochemistry & Molecular Biology
Mohammad Sheibani, Maryam Shayan, Mina Khalilzadeh, Zahra Ebrahim Soltani, Majid Jafari-Sabet, Mehdi Ghasemi, Ahmad Reza Dehpour
Summary: Tryptophan metabolism through the kynurenine pathway plays a central role in immune function and has cytoprotective and immunomodulatory effects. This pathway is believed to be pivotal in the development of both inflammatory bowel disease (IBD) and neurodegenerative disorders.
MOLECULAR BIOLOGY REPORTS
(2023)
Article
Medicine, General & Internal
Fabio Corsi, Luca Sorrentino, Sara Albasini, Francesco Colombo, Maria Cigognini, Alessandro Massari, Carlo Morasso, Serena Mazzucchelli, Francesca Piccotti, Sandro Ardizzone, Gianluca M. Sampietro, Marta Truffi
Summary: The study evaluated circulating FAP (cFAP) as a potential blood biomarker for IBD, showing reduced cFAP concentration in IBD patients compared to controls. cFAP had a sensitivity of 70% and specificity of 84% in discriminating IBD from controls, without strong correlation with routine inflammatory markers. Subgroup analysis revealed cFAP correlates with endoscopic mucosal healing in patients with Crohn's disease.
FRONTIERS IN MEDICINE
(2021)
Article
Gastroenterology & Hepatology
Vincent Joustra, Ishtu L. Hageman, Jack Satsangi, Alex Adams, Nicholas T. Ventham, Wouter J. de Jonge, Peter Henneman, Geert R. D'Haens, Andrew Y. F. Li Yim
Summary: This article systematically reviewed and meta-analyzed DNA methylation studies related to inflammatory bowel disease (IBD). The results showed differential methylation in peripheral blood and confirmed previous observations. The study highlights the need for methodological homogenization and provides a basis for future research on epigenetic biomarkers of IBD in peripheral blood leukocytes.
JOURNAL OF CROHNS & COLITIS
(2023)
Review
Biochemistry & Molecular Biology
Sem Geertsema, Arno R. Bourgonje, Raphael R. Fagundes, Ranko Gacesa, Rinse K. Weersma, Harry van Goor, Giovanni E. Mann, Gerard Dijkstra, Klaas N. Faber
Summary: Oxidative stress is an important mechanism in inflammatory bowel disease. The NRF2/Keap1 pathway regulates cellular responses to oxidative stress and has been implicated in the development of inflammatory bowel disease. Activation of the NRF2/Keap1 pathway enhances antioxidant responses and may potentially improve clinical outcomes for inflammatory bowel disease.
TRENDS IN MOLECULAR MEDICINE
(2023)
Article
Multidisciplinary Sciences
Dino Gobelli, Pablo Serrano-Lorenzo, Maria J. Esteban-Amo, Julia Serna, M. Teresa Perez-Garcia, Antonio Orduna, Alexis A. Jourdain, Miguel A. Martin-Casanueva, Miguel A. . de la Fuente, Maria Simarro
Summary: The subunits Sdha and Sdhb of the mitochondrial electron transport chain play important roles in the respiration and effector responses of macrophages. Their absence impairs the stabilization of HIF-1 alpha and the production of the pro-inflammatory cytokine IL-1 beta in response to LPS stimulation, and also inhibits the production of IL-10. This is due to the excessive accumulation of mitochondrial reactive oxygen species (mitoROS) and the inhibition of Stat3 tyrosine phosphorylation caused by the absence of Sdha and Sdhb.
Article
Biochemical Research Methods
Min Zeng, Yifan Wu, Chengqian Lu, Fuhao Zhang, Fang-Xiang Wu, Min Li
Summary: This study presents a deep learning framework, DeepLncLoc, for predicting the subcellular localization of lncRNAs. By introducing a novel subsequence embedding method, DeepLncLoc retains the order information of lncRNA sequences and utilizes a text convolutional neural network for high-level feature learning and prediction. Compared to traditional methods, DeepLncLoc shows improved performance.
BRIEFINGS IN BIOINFORMATICS
(2022)
Article
Biochemical Research Methods
Cheng Yan, Guihua Duan, Na Li, Lishen Zhang, Fang-Xiang Wu, Jianxin Wang
Summary: In this study, a new deep learning method called PDMDA is proposed to accurately predict deep-level miRNA-disease associations. By using graph neural networks (GNNs) and miRNA sequence features, PDMDA can extract valuable information from the feature representations of miRNAs and diseases, leading to efficient predictions.
Article
Biochemical Research Methods
Cheng Yan, Guihua Duan, Yayan Zhang, Fang-Xiang Wu, Yi Pan, Jianxin Wang
Summary: A drug-drug interaction (DDI) refers to the association between drugs where one drug's pharmacological effects are influenced by another drug. This study proposes a novel method, called DDI-IS-SL, to predict DDIs using integrated similarity and semi-supervised learning. DDI-IS-SL combines drug chemical, biological, and phenotype data to calculate the feature similarity of drugs. It also uses a semi-supervised learning method to calculate the interaction possibility scores of drug-drug pairs. DDI-IS-SL demonstrates better prediction performance and shorter computation time compared to other methods, and its performance is further supported by case studies.
IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS
(2022)
Article
Computer Science, Information Systems
Yulian Ding, Xiujuan Lei, Bo Liao, Fang-Xiang Wu
Summary: This study presents a new computational model (VGAMF) that integrates different types of information about miRNAs and diseases to predict their associations. The experimental results demonstrate the effectiveness of the model in predicting miRNA-disease associations, particularly in colon cancer and esophageal cancer.
IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS
(2022)
Article
Genetics & Heredity
Chunyan Fan, Xiujuan Lei, Jiaojiao Tie, Yuchen Zhang, Fang-Xiang Wu, Yi Pan
Summary: CircR2Disease v2.0 is an updated database that provides a comprehensive resource and web tool for the relationships between circular RNAs (circRNAs) and diseases. This version includes a significantly increased number of experimentally validated circRNA-disease associations and manually collected information on circRNA-miRNA, circRNA-miRNA-target, and circRNA-RBP interactions. It also provides links to various nomenclature databases for gene symbols and disease name IDs. Detailed descriptions and sample information have been integrated into the updated version. CircR2Disease v2.0 serves as a platform for systematic investigation of dysregulated circRNAs in various diseases and exploration of their posttranscriptional regulatory function in diseases.
GENOMICS PROTEOMICS & BIOINFORMATICS
(2022)
Article
Biochemical Research Methods
Ju Xiang, Xiangmao Meng, Yichao Zhao, Fang-Xiang Wu, Min Li
Summary: In this study, a hybrid disease-gene prediction method called HyMM is proposed, which utilizes multiscale module structure to enhance the prediction of disease-related genes. HyMM extracts module partitions at different scales and estimates gene-disease relatedness based on the abundance of disease-related genes within the modules. The results confirm the stable and good performance of HyMM compared to other state-of-the-art methods and demonstrate the further performance improvement achieved through parameter estimation.
BRIEFINGS IN BIOINFORMATICS
(2022)
Article
Biochemical Research Methods
Yulian Ding, Xiujuan Lei, Bo Liao, Fang-Xiang Wu
Summary: In this study, a factorization machine-based deep neural network with binary pairwise encoding (DFMbpe) is proposed to identify disease-related biomarkers. The DFMbpe model considers the interdependence of features and combines low-order and high-order feature interactions, leading to better performance compared to other biomarker identification models.
IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS
(2023)
Article
Engineering, Biomedical
Rayyan Azam Khan, Yigang Luo, Fang-Xiang Wu
Summary: In this study, a multilevel generative adversarial network (GAN) is proposed to enhance computed tomographic (CT) images for liver cancer diagnosis. The performance of the proposed method is investigated using three publicly available datasets, and it achieves good results in terms of performance metrics and computer-aided diagnosis. The effectiveness of the proposed multi-level GAN in producing enhanced biomedical images with preserved structural details and reduction in artifacts is demonstrated, and it shows consistently better performance among three datasets for computer-aided diagnosis.
BIOMEDICAL SIGNAL PROCESSING AND CONTROL
(2023)
Article
Computer Science, Information Systems
Minghan Fu, Meiyun Wang, Yaping Wu, Na Zhang, Yongfeng Yang, Haining Wang, Yun Zhou, Yue Shang, Fang-Xiang Wu, Hairong Zheng, Dong Liang, Zhanli Hu
Summary: A novel two-branch network architecture called SW-GCN is proposed to improve PET image quality. The network utilizes Swin Transformer units and graph convolution operation to handle different types of input information flow and enables better processing of long-range contextual information. Experimental results demonstrate that the proposed approach outperforms state-of-the-art methods in both quantitative and qualitative evaluations.
IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS
(2023)
Article
Chemistry, Analytical
Kawsar Ahmed, Francis M. Bui, Fang-Xiang Wu
Summary: To reduce the development time and effort of standard optical biosensors, machine learning approaches have been used to predict crucial parameters and evaluate the performance of the models based on performance indicators.
Article
Computer Science, Information Systems
Yuchen Zhang, Xiujuan Lei, Cai Dai, Yi Pan, Fang-Xiang Wu
Summary: More and more studies have shown that circRNAs can be used as disease markers due to their stability. Various computational methods, particularly those utilizing artificial intelligence, have been employed to predict circRNA-disease associations. However, these methods often use single, standard objective functions, leading to low prediction accuracy. This paper proposes a multiobjective evolutionary algorithm called ICDMOE to identify circRNA-disease associations, using matrix factorization and modularity of similarity networks to design four objective functions. Experimental results demonstrate that ICDMOE outperforms other prediction methods and can provide good candidates for biomedical experiments, as confirmed by existing studies, miRNA regulations, and expression profiles.
INFORMATION SCIENCES
(2023)
Article
Biochemical Research Methods
Xuhua Yan, Ruiqing Zheng, Fangxiang Wu, Min Li
Summary: CIAIRE is a novel contrastive learning-based batch correction framework that achieves a superior mix-heterogeneity trade-off. It proposes two complementary strategies, construction strategy and refinement strategy, to improve the appropriateness of positive pairs. CLAIRE outperforms existing methods in terms of mix-heterogeneity trade-off and achieves the best integration performance on six real datasets.
Article
Biochemical Research Methods
Yiming Li, Min Zeng, Fuhao Zhang, Fang-Xiang Wu, Min Li
Summary: In this study, DeepCellEss, a sequence-based interpretable deep learning framework, is proposed for cell line-specific essential protein predictions. By utilizing convolutional neural networks, bidirectional long short-term memory, and multi-head self-attention mechanism, DeepCellEss achieves effective prediction performance for different cell lines and outperforms existing methods and metrics.
Article
Biochemical Research Methods
Liangliang Liu, Shaojie Tang, Fang-Xiang Wu, Yu-Ping Wang, Jianxin Wang
Summary: This paper proposes an ensemble hybrid features selection method for the classification of neuropsychiatric disorders, which improves the performance of classification methods. The importance of phenotypic features and image features in different classification tasks is analyzed.
IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS
(2022)
Article
Biochemical Research Methods
Xiangmao Meng, Ju Xiang, Ruiqing Zheng, Fang-Xiang Wu, Min Li
Summary: Protein complexes play a crucial role in the biological functions of cells. This study proposes a method called DPCMNE to detect protein complexes using multi-level network embedding, which preserves both the local and global topological information of biological networks. Experimental results show that DPCMNE outperforms other existing methods in terms of F1 and F1+Acc, and the protein complexes detected by DPCMNE are biologically more significant.
IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS
(2022)