High Fat Diet Induces Liver Steatosis and Early Dysregulation of Iron Metabolism in Rats

This paper is dedicated to the memory of our wonderful colleague Professor Alfredo Colonna, who passed away the same day of its acceptance. Fatty liver accumulation, inflammatory process and insulin resistance appear to be crucial in non-alcoholic fatty liver disease (NAFLD), nevertheless emerging findings pointed an important role also for iron overload. Here, we investigate the molecular mechanisms of hepatic iron metabolism in the onset of steatosis to understand whether its impairment could be an early event of liver inflammatory injury. Rats were fed with control diet or high fat diet (HFD) for 5 or 8 weeks, after which liver morphology, serum lipid profile, transaminases levels and hepatic iron content (HIC), were evaluated. In liver of HFD fed animals an increased time-dependent activity of iron regulatory protein 1 (IRP1) was evidenced, associated with the increase in transferrin receptor-1 (TfR1) expression and ferritin down-regulation. Moreover, ferroportin (FPN-1), the main protein involved in iron export, was down-regulated accordingly with hepcidin increase. These findings were indicative of an increased iron content into hepatocytes, which leads to an increase of harmful free-iron also related to the reduction of hepatic ferritin content. The progressive inflammatory damage was evidenced by the increase of hepatic TNF-α, IL-6 and leptin, in parallel to increased iron content and oxidative stress. The major finding that emerged of this study is the impairment of iron homeostasis in the ongoing and sustaining of liver steatosis, suggesting a strong link between iron metabolism unbalance, inflammatory damage and progression of disease.     

A Model of Liver Regeneration

The network of interactions underlying liver regeneration is robust and precise with liver resections resulting in controlled hyperplasia (cell proliferation) that terminates when the liver regains its lost mass. The interplay of cytokines and growth factors responsible for the inception and termination of this hyperplasia is not well understood. A model is developed for this network of interactions based on the known data of liver resections. This model reproduces the relevant published data on liver regeneration and provides geometric insights into the experimental observations. The predictions of this model are used to suggest two novel strategies for speeding up liver mass recovery and a strategy for enabling liver mass recovery in cases where a resection leaves <20% of the liver that would otherwise result in complete loss of liver mass.     

A Neural Computational Model of Incentive Salience

Incentive salience is a motivational property with ‘magnet-like’ qualities. When attributed to reward-predicting stimuli (cues), incentive salience triggers a pulse of ‘wanting’ and an individual is pulled toward the cues and reward. A key computational question is how incentive salience is generated during a cue re-encounter, which combines both learning and the state of limbic brain mechanisms. Learning processes, such as temporal-difference models, provide one way for stimuli to acquire cached predictive values of rewards. However, empirical data show that subsequent incentive values are also modulated on the fly by dynamic fluctuation in physiological states, altering cached values in ways requiring additional motivation mechanisms. Dynamic modulation of incentive salience for a Pavlovian conditioned stimulus (CS or cue) occurs during certain states, without necessarily requiring (re)learning about the cue. In some cases, dynamic modulation of cue value occurs during states that are quite novel, never having been experienced before, and even prior to experience of the associated unconditioned reward in the new state. Such cases can include novel drug-induced mesolimbic activation and addictive incentive-sensitization, as well as natural appetite states such as salt appetite. Dynamic enhancement specifically raises the incentive salience of an appropriate CS, without necessarily changing that of other CSs. Here we suggest a new computational model that modulates incentive salience by integrating changing physiological states with prior learning. We support the model with behavioral and neurobiological data from empirical tests that demonstrate dynamic elevations in cue-triggered motivation (involving natural salt appetite, and drug-induced intoxication and sensitization). Our data call for a dynamic model of incentive salience, such as presented here. Computational models can adequately capture fluctuations in cue-triggered ‘wanting’ only by incorporating modulation of previously learned values by natural appetite and addiction-related states.     

A Dynamical Model of Lipoprotein Metabolism

We present a dynamical model of lipoprotein metabolism derived by combining a cascading process in the blood stream and cellular level regulatory dynamics. We analyse the existence and stability of equilibria and show that this low-dimensional, nonlinear model exhibits bistability between a low and a high cholesterol state. A sensitivity analysis indicates that the intracellular concentration of cholesterol is robust to parametric variations while the plasma cholesterol can vary widely. We show how the dynamical response to time-dependent inputs can be used to diagnose the state of the system. We also establish the connection between parameters in the system and medical and genetic conditions.     

A Model of Leaf Carbon Metabolism

A model relating the levels of some carbon metabolites in theleaves of C₃ plant species to the light and carbon dioxide environmentof the leaf is constructed, and provides a basis for quantitativeinvestigation of the diurnal variations in the carbon metabolitelevels. The model also predicts relationships between the respiratoryactivity of the leaf during the night and the preceding photosyntheticactivity of the leaf.     

Cuprizone Administration Alters the Iron Metabolism in the Mouse Model of Multiple Sclerosis

Cuprizone (CZ) is a widely used copper chelating agent to develop non-autoimmune animal model of multiple sclerosis, characterized by demyelination of the corpus callosum (CC) and other brain regions. The exact mechanisms of CZ action are still arguable, but it seems that the only affected cells are the mature oligodendrocytes, possibly via metabolic disturbances caused by copper deficiency. During the pathogenesis of multiple sclerosis, high amount of deposited iron can be found throughout the demyelinated areas of the brain in the form of extracellular iron deposits and intracellularly accumulated iron in microglia. In the present study, we used the accepted experimental model of 0.2% CZ-containing diet with standard iron concentration to induce demyelination in the brain of C57BL/6 mice. Our aim was to examine the changes of iron homeostasis in the CC and as a part of the systemic iron regulation, in the liver. Our data showed that CZ treatment changed the iron metabolism of both tissues; however, it had more impact on the liver. Besides the alterations in the expressions of iron storage and import proteins, we detected reduced serum iron concentration and iron stores in the liver, together with elevated hepcidin levels and feasible disturbances in the Fe–S cluster biosynthesis. Our results revealed that the CZ-containing diet influences the systemic iron metabolism in mice, particularly the iron homeostasis of the liver. This inadequate systemic iron regulation may affect the iron homeostasis of the brain, eventually indicating a relationship among CZ treatment, iron metabolism, and neurodegeneration.     

A Computational Model for the Analysis of Lipoprotein Distributions in the Mouse: Translating FPLC Profiles to Lipoprotein Metabolism

Disturbances of lipoprotein metabolism are recognized as indicators of cardiometabolic disease risk. Lipoprotein size and composition, measured in a lipoprotein profile, are considered to be disease risk markers. However, the measured profile is a collective result of complex metabolic interactions, which complicates the identification of changes in metabolism. In this study we aim to develop a method which quantitatively relates murine lipoprotein size, composition and concentration to the molecular mechanisms underlying lipoprotein metabolism. We introduce a computational framework which incorporates a novel kinetic model of murine lipoprotein metabolism. The model is applied to compute a distribution of plasma lipoproteins, which is then related to experimental lipoprotein profiles through the generation of an in silico lipoprotein profile. The model was first applied to profiles obtained from wild-type C57Bl/6J mice. The results provided insight into the interplay of lipoprotein production, remodelling and catabolism. Moreover, the concentration and metabolism of unmeasured lipoprotein components could be determined. The model was validated through the prediction of lipoprotein profiles of several transgenic mouse models commonly used in cardiovascular research. Finally, the framework was employed for longitudinal analysis of the profiles of C57Bl/6J mice following a pharmaceutical intervention with a liver X receptor (LXR) agonist. The multifaceted regulatory response to the administration of the compound is incompletely understood. The results explain the characteristic changes of the observed lipoprotein profile in terms of the underlying metabolic perturbation and resultant modifications of lipid fluxes in the body. The Murine Lipoprotein Profiler (MuLiP) presented here is thus a valuable tool to assess the metabolic origin of altered murine lipoprotein profiles and can be applied in preclinical research performed in mice for analysis of lipid fluxes and lipoprotein composition.     

高等植物中铁的代谢机制

铁在高等植物的生长发育中发挥着重要作用,但随着人类的耕作及土壤的盐碱化,缺铁已成为一个世界性植物营养问题。高等植物在长期的进化过程中,形成了完善的对环境铁信号响应的体系。本文围绕植物与环境的相互作用,综述了近年来植物铁营养的吸收、转运、分配和储存的研究进展,并总结了植物中铁营养代谢调控的相关机理。     

A Three-Dimensional Computational Model of Collagen Network Mechanics

Extracellular matrix (ECM) strongly influences cellular behaviors, including cell proliferation, adhesion, and particularly migration. In cancer, the rigidity of the stromal collagen environment is thought to control tumor aggressiveness, and collagen alignment has been linked to tumor cell invasion. While the mechanical properties of collagen at both the single fiber scale and the bulk gel scale are quite well studied, how the fiber network responds to local stress or deformation, both structurally and mechanically, is poorly understood. This intermediate scale knowledge is important to understanding cell-ECM interactions and is the focus of this study. We have developed a three-dimensional elastic collagen fiber network model (bead-and-spring model) and studied fiber network behaviors for various biophysical conditions: collagen density, crosslinker strength, crosslinker density, and fiber orientation (random vs. prealigned). We found the best-fit crosslinker parameter values using shear simulation tests in a small strain region. Using this calibrated collagen model, we simulated both shear and tensile tests in a large linear strain region for different network geometry conditions. The results suggest that network geometry is a key determinant of the mechanical properties of the fiber network. We further demonstrated how the fiber network structure and mechanics evolves with a local formation, mimicking the effect of pulling by a pseudopod during cell migration. Our computational fiber network model is a step toward a full biomechanical model of cellular behaviors in various ECM conditions.     

铜蓝蛋白与脑铁代谢

铜蓝蛋白（Cerulopasmin,CP)是人体重要的亚铁氧化酶。它的主要作用是催化二阶铁成为三阶铁,从而促进铁与转铁蛋白结合。由于它的     

A Mathematical Model of Leaf Carbon Metabolism

A dynamic mechanistic mathematical model of C₃ leaf carbon metabolism,incorporating the Calvin cycle with starch and sucrose synthesisand degradation, is proposed. The model consists of a systemof non-linear differential equations based on biochemical andphysiological assumptions. An analytical steady-state solution,with interesting mathematical properties that are interpretedbiologically, is presented and shown to be stable. The systemequations are integrated numerically, and an approximate analyticalsolution to the sucrose sub-system is derived. Some resultsof the model are compared with experimental data. Mathematical model, Calvin cycle, leaf carbon metabolism, photosynthesis, differential equations     

Hepcidin,调节铁代谢平衡的新型抗菌肽

Hepcidin是一种富含半胱氨酸的新型抗菌肽,在哺乳动物肝脏中特异表达,具有抗细菌和真菌等抗菌肽的特性。更重要的是,其在机体铁代谢平衡的调节中起关键作用,并参与多种铁代谢紊乱疾病的发病机制。对Hepcidin的进一步研究,有助于开发治疗铁代谢异常疾病的新药物。     

A Computational Model Predicting Disruption of Blood Vessel Development

Vascular development is a complex process regulated by dynamic biological networks that vary in topology and state across different tissues and developmental stages. Signals regulating de novo blood vessel formation (vasculogenesis) and remodeling (angiogenesis) come from a variety of biological pathways linked to endothelial cell (EC) behavior, extracellular matrix (ECM) remodeling and the local generation of chemokines and growth factors. Simulating these interactions at a systems level requires sufficient biological detail about the relevant molecular pathways and associated cellular behaviors, and tractable computational models that offset mathematical and biological complexity. Here, we describe a novel multicellular agent-based model of vasculogenesis using the CompuCell3D (http://www.compucell3d.org/) modeling environment supplemented with semi-automatic knowledgebase creation. The model incorporates vascular endothelial growth factor signals, pro- and anti-angiogenic inflammatory chemokine signals, and the plasminogen activating system of enzymes and proteases linked to ECM interactions, to simulate nascent EC organization, growth and remodeling. The model was shown to recapitulate stereotypical capillary plexus formation and structural emergence of non-coded cellular behaviors, such as a heterologous bridging phenomenon linking endothelial tip cells together during formation of polygonal endothelial cords. Molecular targets in the computational model were mapped to signatures of vascular disruption derived from in vitro chemical profiling using the EPA''s ToxCast high-throughput screening (HTS) dataset. Simulating the HTS data with the cell-agent based model of vascular development predicted adverse effects of a reference anti-angiogenic thalidomide analog, 5HPP-33, on in vitro angiogenesis with respect to both concentration-response and morphological consequences. These findings support the utility of cell agent-based models for simulating a morphogenetic series of events and for the first time demonstrate the applicability of these models for predictive toxicology.     

Iron Metabolism in the Reticuloendothelial System

Comprised mainly of monocytes and tissue macrophages, the reticuloendothelial system (RES) plays two major roles in iron metabolism: it recycles iron from senescent red blood cells and it serves as a large storage depot for excess iron. Although iron recycling by the RES represents the largest pathway of iron efflux in the body, the precise mechanisms involved have remained elusive. However, studies characterizing the function and regulation of Nramp1, DMT1, HFE, FPN1, CD163, and hepcidin are rapidly expanding our knowledge of the molecular aspects of RE iron handling. This review summarizes fundamental physiological and biochemical aspects of iron metabolism in the RES and focuses on how recent studies have advanced our understanding of these areas. Also discussed are novel insights into the molecular mechanisms contributing to the abnormal RE iron metabolism characteristic of hereditary hemochromatosis and the anemia of chronic disease.     

脑铁代谢和神经变性性疾病

最近关于脑铁代谢研究的新成果,尤其是与脑铁转运、储存、调节相关的某些突变基因的发现,足以得出以下结论,即异常增高的脑铁至少是部份神经变性疾病的起始原因。研究显示,脑铁过量积聚主要是由于遗传性和非遗传性因素所引起的某些服铁代谢蛋白功能异常或表达失控。正是异常增高的脑铁触发一系列病理反应,最终导致神经为性性疾病病人服神经元死亡。本文简要叙述了目前对服铁分布、功能和脑铁代谢蛋白的认识,讨论了内铁转运机制以及服铁和神经变性性疾病之间的关系研究的新进展。