Computational models in inflammatory bowel disease

Ziziphus jujuba Miller Ethanol Extract Restores Disrupted Intestinal Barrier Function via Tight Junction Recovery and Reduces Inflammation

Inflammatory bowel disease (IBD) is a chronic inflammatory condition caused by the disruption of the intestinal barrier. The intestinal barrier is maintained by tight junctions (TJs), which sustain intestinal homeostasis and prevent pathogens from entering the microbiome and mucosal tissues. Ziziphus jujuba Miller (Z. jujuba) is a natural substance that has been used in traditional medicine as a therapy for a variety of diseases. However, in IBD, the efficacy of Z. jujuba is unknown. Therefore, we evaluated ZJB in Caco2 cells and a dextran sodium sulfate (DSS)-induced mouse model to demonstrate its efficacy in IBD. Z. jujuba extracts were prepared using 70% ethanol and were named ZJB. ZJB was found to be non-cytotoxic and to have excellent antioxidant effects. We confirmed its anti-inflammatory properties via the down-regulation of inflammatory factors, including inducible nitric oxide synthase (iNOS) and cyclooxygenase-2 (COX-2). To evaluate the effects of ZJB on intestinal barrier function and TJ improvement, the trans-epithelial electrical resistance (TEER) and fluorescein isothiocyanate-dextran 4 kDa (FITC-Dextran 4) permeability were assessed. The TEER value increased by 61.389% and permeability decreased by 27.348% in the 200 μg/mL ZJB group compared with the 50 ng/mL IL-6 group after 24 h. Additionally, ZJB alleviated body weight loss, reduced the disease activity index (DAI) score, and induced colon shortening in 5% DSS-induced mice; inflammatory cytokines, tumor necrosis factor (TNF)-α, and interleukin (IL)-6 were down-regulated in the serum. TJ proteins, such as Zonula occludens (ZO)-1 and occludin, were up-regulated by ZJB in an impaired Caco2 mouse model. Additionally, according to the liquid chromatography results, in tandem with mass spectrometry (LC-MS/MS) analysis, seven active ingredients were detected in ZJB. In conclusion, ZJB down-regulated inflammatory factors, protected intestinal barrier function, and increased TJ proteins. It is thus a safe, natural substance with the potential to be used as a therapeutic agent in IBD treatment.

Impact of artificial intelligence on prognosis, shared decision-making, and precision medicine for patients with inflammatory bowel disease: a perspective and expert opinion

INTRODUCTION

Artificial intelligence (AI) is expected to impact all facets of inflammatory bowel disease (IBD) management, including disease assessment, treatment decisions, discovery and development of new biomarkers and therapeutics, as well as clinician-patient communication.

AREAS COVERED

This perspective paper provides an overview of the application of AI in the clinical management of IBD through a review of the currently available AI models that could be potential tools for prognosis, shared decision-making, and precision medicine. This overview covers models that measure treatment response based on statistical or machine-learning methods, or a combination of the two. We briefly discuss a computational model that allows integration of immune/biological system knowledge with mathematical modeling and also involves a 'digital twin', which allows measurement of temporal trends in mucosal inflammatory activity for predicting treatment response. A viewpoint on AI-enabled wearables and nearables and their use to improve IBD management is also included.

EXPERT OPINION

Although challenges regarding data quality, privacy, and security; ethical concerns; technical limitations; and regulatory barriers remain to be fully addressed, a growing body of evidence suggests a tremendous potential for integration of AI into daily clinical practice to enable precision medicine and shared decision-making.

Using Constrained-Disorder Principle-Based Systems to Improve the Performance of Digital Twins in Biological Systems

Digital twins are computer programs that use real-world data to create simulations that predict the performance of processes, products, and systems. Digital twins may integrate artificial intelligence to improve their outputs. Models for dealing with uncertainties and noise are used to improve the accuracy of digital twins. Most currently used systems aim to reduce noise to improve their outputs. Nevertheless, biological systems are characterized by inherent variability, which is necessary for their proper function. The constrained-disorder principle defines living systems as having a disorder as part of their existence and proper operation while kept within dynamic boundaries. In the present paper, we review the role of noise in complex systems and its use in bioengineering. We describe the use of digital twins for medical applications and current methods for dealing with noise and uncertainties in modeling. The paper presents methods to improve the accuracy and effectiveness of digital twin systems by continuously implementing variability signatures while simultaneously reducing unwanted noise in their inputs and outputs. Accounting for the noisy internal and external environments of complex biological systems is necessary for the future design of improved, more accurate digital twins.

Artificial intelligence and inflammatory bowel disease: Where are we going?

Inflammatory bowel diseases, namely ulcerative colitis and Crohn’s disease, are chronic and relapsing conditions that pose a growing burden on healthcare systems worldwide. Because of their complex and partly unknown etiology and pathogenesis, the management of ulcerative colitis and Crohn’s disease can prove challenging not only from a clinical point of view but also for resource optimization. Artificial intelligence, an umbrella term that encompasses any cognitive function developed by machines for learning or problem solving, and its subsets machine learning and deep learning are becoming ever more essential tools with a plethora of applications in most medical specialties. In this regard gastroenterology is no exception, and due to the importance of endoscopy and imaging numerous clinical studies have been gradually highlighting the relevant role that artificial intelligence has in inflammatory bowel diseases as well. The aim of this review was to summarize the most recent evidence on the use of artificial intelligence in inflammatory bowel diseases in various contexts such as diagnosis, follow-up, treatment, prognosis, cancer surveillance, data collection, and analysis. Moreover, insights into the potential further developments in this field and their effects on future clinical practice were discussed.