This study aimed to use multi-scale atrial models to investigate pulmonary arterial hypertension (PAH)-induced atrial fibrillation mechanisms. The results of our computer simulations revealed that, at the single-cell level, PAH-induced remodelling led to a prolonged action potential (AP) (ΔAPD: 49.6 ms in the right atria (RA) versus 41.6 ms in the left atria (LA)) and an increased calcium transient (CaT) (ΔCaT: 7.5 × 10-2 µM in the RA versus 0.9 × 10-3 µM in the LA). Moreover, heterogeneous remodelling increased susceptibility to afterdepolarizations, particularly in the RA. At the tissue level, we observed a significant reduction in conduction velocity (CV) (ΔCV: -0.5 m s-1 in the RA versus -0.05 m s-1 in the LA), leading to a shortened wavelength in the RA, but not in the LA. Additionally, afterdepolarizations in the RA contributed to enhanced repolarization dispersion and facilitated unidirectional conduction block. Furthermore, the increased fibrosis in the RA amplified the likelihood of excitation wave breakdown and the occurrence of sustained re-entries. Our results indicated that the RA is characterized by increased susceptibility to afterdepolarizations, slow conduction, reduced wavelength and upregulated fibrosis. These findings shed light on the underlying factors that may promote atrial fibrillation in patients with PAH.

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Recent research on item-method directed forgetting demonstrates that forget instructions not only decrease recognition for targets, but also decrease false recognition for foils from the same semantic categories as targets instructed to be forgotten. According to the selective rehearsal account of directed forgetting, this finding suggests that remember instructions may engage elaborative rehearsal of the category-level information of items. In contrast to this explanation, Reid and Jamieson (Canadian Journal of Experimental Psychology / Revue canadienne de psychologie expérimentale, 76(2), 75-86, 2022) proposed that the differential rates of false recognition may emerge at retrieval when foils from \"remember\" and \"forget\" categories are compared to traces in memory. Using MINERVA S, an instance model of memory based on MINERVA 2 that incorporates structured semantic representations, Reid and Jamieson successfully simulated lower false recognition for foils from \"forget\" categories without assuming rehearsal of category-level information. In this study, we extend the directed forgetting paradigm to categories consisting of orthographically related nonwords. Presumably participants would have difficulty rehearsing category-level information for these items because they would have no pre-experimental knowledge of these categories. To simulate the findings in MINERVA S, we imported structured orthographic representations rather than semantic representations. The model not only predicted differential rates of false recognition for foils from \"remember\" and \"forget\" categories, but also predicted higher rates of false recognition overall than what was observed for semantic categories. The empirical data closely matched these predictions. These data suggest that differential rates of false recognition due to remember and forget instructions emerge at retrieval when participants compare recognition probes to traces stored in memory.

Fiber metal laminates have been widely used as the primary materials in aircraft panels, and have excellent specific strength. Bending deformation is the most common loading mode of such components. An accurate theoretical predictive model for the bending process for the carbon reinforced aluminum laminates is of great significance for predicting the actual stress response. In this paper, based on the metal-plastic bending theory and the modified classical fiber laminate theory, a modified bending theory model of carbon-fiber-reinforced aluminum laminates was established. The plastic deformation of the thin metal layer in laminates and the interaction between fiber and metal interfaces were considered in this model. The bending strength was predicted analytically. The FMLs were made from 5052 aluminum sheets, with carbon fibers as the reinforcement, and were bonded and cured by locally manufacturers. The accuracy of the theory was verified by three-point bending experiments, and the prediction error was 8.4%. The results show that the fiber metal laminates consisting of three layers of aluminum and two layers of fiber had the best bending properties. The theoretical model could accurately predict the bending deformation behaviors of fiber metal laminates, and has significant value for the theoretical analysis and performance testing of laminates.

Neurocognitive theories of value-based choice propose that people additively accumulate choice attributes when making decisions. These theories cannot explain the emergence of complex multiplicative preferences such as those assumed by prospect theory and other economic models. We investigate an interactive attention mechanism, according to which attention to attributes (like payoffs) depends on other attributes (like probabilities) attended to previously. We formalize this mechanism using a Markov attention model combined with an accumulator decision process, and test our model on eye-tracking and mouse-tracking data in risky choice. Our tests show that interactive attention is necessary to make good choices, that most participants display interactive attention and that allowing for interactive attention in accumulation-based decision models improves their predictions. By equipping established decision models with sophisticated attentional dynamics, we extend these models to describe complex economic choice, and in the process, we unify two prominent theoretical approaches to studying value-based decision making.

Eosinophilic Esophagitis (EoE) is a chronic condition characterized by eosinophilic inflammation of the esophagus which leads to esophageal dysfunction with common symptoms including vomiting, feeding difficulty, dysphagia, abdominal pain. Current main treatment options of EoE include dietary elimination and swallowed steroids. Diet elimination approach could lead to identifying the trigger food(s), but it often requires repeated upper endoscopy with general anesthesia and potentially could negatively affect nutrition intake and growth of the child and individuals\' quality of life. Although the swallowed steroid treatment of effective, the EoE will universally recur after discontinuation of the treatment. Digestive Tea formula (DTF) has been used by the Traditional Chinese Medicine (TCM) practice to improve GI symptoms in EoE patients, including abdominal pain, GE reflux, and abnormal bowel movement. Previously, a flavonoid small molecule compound 7, 4 dihydroxy flavone (DHF) from Glycyrrhiza uralensis in DTF inhibited eotaxin, Th2 cytokine and IgE production in vitro and in vivo.
This study comprehensively evaluates the potential therapeutic and immunological mechanisms underlying DHF improvement of symptoms related to EoE using computational modeling, including target mining, gene ontology enrichment, pathway analyses, protein-protein interaction analyses, in silico molecular docking and dynamic simulation followed by ex-vivo target validation by qRT-PCR using cultured human esophagus biopsy specimen with or without DHF from patients with EoE.
Computational analyses defined 29 common targets of DHF on EoE, among which TNF-α, IL-6, IL1β, MAPK1, MAPK3 and AKT1 were most important. Docking analysis and dynamic simulation revealed that DHF directly binds TNF-α with a free binding energy of -7.7 kcal/mol with greater stability and flexibility. Subsequently, in the human esophagus biopsy culture system, significant reduction in levels of TNF-α, IL-6, IL-8 and IL1-β was found in the supernatant of biopsy sample cultured with DHF. Furthermore, the gene expression profile showed significant reduction in levels of TNF-α, IL1-β, IL-6, CCND and MAPK1 in the esophagus biopsy sample cultured with DHF.
Taken together, the current study provides us an insight into the molecular mechanisms underlying multi-targeted benefits of DHF in the treatment of EoE and paves the way for facilitating more effective EoE therapies.

How gene activities and biomechanics together direct organ shapes is poorly understood. Plant leaf and floral organs develop from highly similar initial structures and share similar gene expression patterns, yet they gain drastically different shapes later-flat and bilateral leaf primordia and radially symmetric floral primordia, respectively. We analyzed cellular growth patterns and gene expression in young leaves and flowers of Arabidopsis thaliana and found significant differences in cell growth rates, which correlate with convergence sites of phytohormone auxin that require polar auxin transport. In leaf primordia, the PRESSED-FLOWER-expressing middle domain grows faster than adjacent adaxial domain and coincides with auxin convergence. In contrast, in floral primordia, the LEAFY-expressing domain shows accelerated growth rates and pronounced auxin convergence. This distinct cell growth dynamics between leaf and flower requires changes in levels of cell-wall pectin de-methyl-esterification and mechanical properties of the cell wall. Data-driven computer model simulations at organ and cellular levels demonstrate that growth differences are central to obtaining distinct organ shape, corroborating in planta observations. Together, our study provides a mechanistic basis for the establishment of early aerial organ symmetries through local modulation of differential growth patterns with auxin and biomechanics.

Atrial fibrillation (AF) with multiple complications, high morbidity and mortality, and low cure rates, has become a global public health problem. Although significant progress has been made in the treatment methods represented by anti-AF drugs and radiofrequency ablation, the therapeutic effect is not as good as expected. The reason is mainly because of our lack of understanding of AF mechanisms. This field has benefited from mechanistic and (or) statistical methodologies. Recent renewed interest in digital twin techniques by synergizing between mechanistic and statistical models has opened new frontiers in AF analysis. In the review, we briefly present findings that gave rise to the AF pathophysiology and current therapeutic modalities. We then summarize the achievements of digital twin technologies in three aspects: understanding AF mechanisms, screening anti-AF drugs and optimizing ablation strategies. Finally, we discuss the challenges that hinder the clinical application of the digital twin heart. With the rapid progress in data reuse and sharing, we expect their application to realize the transition from AF description to response prediction.

Valvular heart disease is currently a common problem which causes high morbidity and mortality worldwide. Prosthetic valve replacements are widely needed to correct narrowing or backflow through the valvular orifice. Compared to mechanical valves and biological valves, tissue-engineered heart valves can be an ideal substitute because they have a low risk of thromboembolism and calcification, and the potential for remodelling, regeneration, and growth. In order to test the performance of these heart valves, various animal models and other models are needed to optimise the structure and function of tissue-engineered heart valves, which may provide a potential mechanism responsible for substantial enhancement in tissue-engineered heart valves. Choosing the appropriate model for evaluating the performance of the tissue-engineered valve is important, as different models have their own advantages and disadvantages. In this review, we summarise the current state-of-the-art animal models, bioreactors, and computational simulation models with the aim of creating more strategies for better development of tissue-engineered heart valves. This review provides an overview of major factors that influence the selection and design of a model for tissue-engineered heart valve. Continued efforts in improving and testing models for valve regeneration remain crucial in basic science and translational researches. Future research should focus on finding the right animal model and developing better in vitro testing systems for tissue-engineered heart valve.

Heart failure is associated with electrical remodeling of the electrical properties and kinetics of the ion channels and transporters that are responsible for cardiac action potentials. However, it is still unclear whether heart failure-induced ionic remodeling can affect the conduction of excitation waves at the Purkinje fiber-ventricle junction contributing to pro-arrhythmic effects of heart failure, as the complexity of the heart impedes a detailed experimental analysis. The aim of this study was to employ computational models to investigate the pro-arrhythmic effects of heart failure-induced ionic remodeling on the cardiac action potentials and excitation wave conduction at the Purkinje fiber-ventricle junction. Single cell models of canine Purkinje fiber and ventricular myocytes were developed for control and heart failure. These single cell models were then incorporated into one-dimensional strand and three-dimensional wedge models to investigate the effects of heart failure-induced remodeling on propagation of action potentials in Purkinje fiber and ventricular tissue and at the Purkinje fiber-ventricle junction. This revealed that heart failure-induced ionic remodeling of Purkinje fiber and ventricular tissue reduced conduction safety and increased tissue vulnerability to the genesis of the unidirectional conduction block. This was marked at the Purkinje fiber-ventricle junction, forming a potential substrate for the genesis of conduction failure that led to re-entry. This study provides new insights into proarrhythmic consequences of heart failure-induced ionic remodeling.