Coding region polyadenylation generates a truncated tRNA synthetase that counters translation repression.

Posttranscriptional regulatory mechanisms superimpose "fine-tuning" control upon "on-off" switches characteristic of gene transcription. We have exploited computational modeling with experimental validation to resolve an anomalous relationship between mRNA expression and protein synthesis. The GAIT (gamma-interferon-activated inhibitor of translation) complex repressed VEGF-A synthesis to a low, constant rate independent of VEGF-A mRNA expression levels. Dynamic model simulations predicted an inhibitory GAIT-element-interacting factor to account for this relationship and led to the identification of a truncated form of glutamyl-prolyl tRNA synthetase (EPRS), a GAIT constituent that mediates binding to target transcripts. The truncated protein, EPRS(N1), shields GAIT-element-bearing transcripts from the inhibitory GAIT complex, thereby dictating a "translational trickle" of GAIT target proteins. EPRS(N1) mRNA is generated by polyadenylation-directed conversion of a Tyr codon in the EPRS-coding sequence to a stop codon (PAY(∗)). Genome-wide analysis revealed multiple candidate PAY(∗) targets, including the authenticated target RRM1, suggesting a general mechanism for production of C terminus-truncated regulatory proteins.

Whole-body iron transport and metabolism: Mechanistic, multi-scale model to improve treatment of anemia in chronic kidney disease.

Iron plays vital roles in the human body including enzymatic processes, oxygen-transport via hemoglobin and immune response. Iron metabolism is characterized by ~95% recycling and minor replenishment through diet. Anemia of chronic kidney disease (CKD) is characterized by a lack of synthesis of erythropoietin leading to reduced red blood cell (RBC) formation and aberrant iron recycling. Treatment of CKD anemia aims to normalize RBC count and serum hemoglobin. Clinically, the various fluxes of iron transport and accumulation are not measured so that changes during disease (e.g., CKD) and treatment are unknown. Unwanted iron accumulation in patients is known to lead to adverse effects. Current whole-body models lack the mechanistic details of iron transport related to RBC maturation, transferrin (Tf and TfR) dynamics and assume passive iron efflux from macrophages. Hence, they are not predictive of whole-body iron dynamics and cannot be used to design individualized patient treatment. For prediction, we developed a mechanistic, multi-scale computational model of whole-body iron metabolism incorporating four compartments containing major pools of iron and RBC generation process. The model accounts for multiple forms of iron in vivo, mechanisms involved in iron uptake and release and their regulation. Furthermore, the model is interfaced with drug pharmacokinetics to allow simulation of treatment dynamics. We calibrated our model with experimental and clinical data from peer-reviewed literature to reliably simulate CKD anemia and the effects of current treatment involving combination of epoietin-alpha and iron dextran. This in silico whole-body model of iron metabolism predicts that a year of treatment can potentially lead to 90% downregulation of ferroportin (FPN) levels, 15-fold increase in iron stores with only a 20% increase in iron flux from the reticulo-endothelial system (RES). Model simulations quantified unmeasured iron fluxes, previously unknown effects of treatment on FPN-level and iron stores in the RES. This mechanistic whole-body model can be the basis for future studies that incorporate iron metabolism together with related clinical experiments. Such an approach could pave the way for development of effective personalized treatment of CKD anemia.

Mechanistic, mathematical model to predict the dynamics of tissue genesis in bone defects via mechanical feedback and mediation of biochemical factors.

The link between mechanics and biology in the generation and the adaptation of bone has been well studied in context of skeletal development and fracture healing. Yet, the prediction of tissue genesis within - and the spatiotemporal healing of - postnatal defects, necessitates a quantitative evaluation of mechano-biological interactions using experimental and clinical parameters. To address this current gap in knowledge, this study aims to develop a mechanistic mathematical model of tissue genesis using bone morphogenetic protein (BMP) to represent of a class of factors that may coordinate bone healing. Specifically, we developed a mechanistic, mathematical model to predict the dynamics of tissue genesis by periosteal progenitor cells within a long bone defect surrounded by periosteum and stabilized via an intramedullary nail. The emergent material properties and mechanical environment associated with nascent tissue genesis influence the strain stimulus sensed by progenitor cells within the periosteum. Using a mechanical finite element model, periosteal surface strains are predicted as a function of emergent, nascent tissue properties. Strains are then input to a mechanistic mathematical model, where mechanical regulation of BMP-2 production mediates rates of cellular proliferation, differentiation and tissue production, to predict healing outcomes. A parametric approach enables the spatial and temporal prediction of endochondral tissue regeneration, assessed as areas of cartilage and mineralized bone, as functions of radial distance from the periosteum and time. Comparing model results to histological outcomes from two previous studies of periosteum-mediated bone regeneration in a common ovine model, it was shown that mechanistic models incorporating mechanical feedback successfully predict patterns (spatial) and trends (temporal) of bone tissue regeneration. The novel model framework presented here integrates a mechanistic feedback system based on the mechanosensitivity of periosteal progenitor cells, which allows for modeling and prediction of tissue regeneration on multiple length and time scales. Through combination of computational, physical and engineering science approaches, the model platform provides a means to test new hypotheses in silico and to elucidate conditions conducive to endogenous tissue genesis. Next generation models will serve to unravel intrinsic differences in bone genesis by endochondral and intramembranous mechanisms.

Computational modeling and analysis of iron release from macrophages.

A major process of iron homeostasis in whole-body iron metabolism is the release of iron from the macrophages of the reticuloendothelial system. Macrophages recognize and phagocytose senescent or damaged erythrocytes. Then, they process the heme iron, which is returned to the circulation for reutilization by red blood cell precursors during erythropoiesis. The amount of iron released, compared to the amount shunted for storage as ferritin, is greater during iron deficiency. A currently accepted model of iron release assumes a passive-gradient with free diffusion of intracellular labile iron (Fe2+) through ferroportin (FPN), the transporter on the plasma membrane. Outside the cell, a multi-copper ferroxidase, ceruloplasmin (Cp), oxidizes ferrous to ferric ion. Apo-transferrin (Tf), the primary carrier of soluble iron in the plasma, binds ferric ion to form mono-ferric and di-ferric transferrin. According to the passive-gradient model, the removal of ferrous ion from the site of release sustains the gradient that maintains the iron release. Subcellular localization of FPN, however, indicates that the role of FPN may be more complex. By experiments and mathematical modeling, we have investigated the detailed mechanism of iron release from macrophages focusing on the roles of the Cp, FPN and apo-Tf. The passive-gradient model is quantitatively analyzed using a mathematical model for the first time. A comparison of experimental data with model simulations shows that the passive-gradient model cannot explain macrophage iron release. However, a facilitated-transport model associated with FPN can explain the iron release mechanism. According to the facilitated-transport model, intracellular FPN carries labile iron to the macrophage membrane. Extracellular Cp accelerates the oxidation of ferrous ion bound to FPN. Apo-Tf in the extracellular environment binds to the oxidized ferrous ion, completing the release process. Facilitated-transport model can correctly predict cellular iron efflux and is essential for physiologically relevant whole-body model of iron metabolism.

Distinguishing the effects of convective and diffusive O2 delivery on VO2 on-kinetics in skeletal muscle contracting at moderate intensity.

With current techniques, experimental measurements alone cannot characterize the effects of oxygen blood-tissue diffusion on muscle oxygen uptake (Vo2) kinetics in contracting skeletal muscle. To complement experimental studies, a computational model is used to quantitatively distinguish the contributions of convective oxygen delivery, diffusion into cells, and oxygen utilization to Vo2 kinetics. The model is validated using previously published experimental Vo2 kinetics in response to slowed blood flow (Q) on-kinetics in canine muscle (τQ = 20 s, 46 s, and 64 s) [Goodwin ML, Hernández A, Lai N, Cabrera ME, Gladden LB. J Appl Physiol. 112:9-19, 2012]. Distinctive effects of permeability-surface area or diffusive conductance (PS) and Q on Vo2 kinetics are investigated. Model simulations quantify the relationship between PS and Q, as well as the effects of diffusion associated with PS and Q dynamics on the mean response time of Vo2. The model indicates that PS and Q are linearly related and that PS increases more with Q when convective delivery is limited by slower Q dynamics. Simulations predict that neither oxygen convective nor diffusive delivery are limiting Vo2 kinetics in the isolated canine gastrocnemius preparation under normal spontaneous conditions during transitions from rest to moderate (submaximal) energy demand, although both operate close to the tipping point.

Model analysis of the relationship between intracellular PO2 and energy demand in skeletal muscle.

On the basis of experimental studies, the intracellular O(2) (iPo(2))-work rate (WR) relationship in skeletal muscle is not unique. One study found that iPo(2) reached a plateau at 60% of maximal WR, while another found that iPo(2) decreased linearly at higher WR, inferring capillary permeability-surface area (PS) and blood-tissue O(2) gradient, respectively, as alternative dominant factors for determining O(2) diffusion changes during exercise. This relationship is affected by several factors, including O(2) delivery and oxidative and glycolytic capacities of the muscle. In this study, these factors are examined using a mechanistic, mathematical model to analyze experimental data from contracting skeletal muscle and predict the effects of muscle contraction on O(2) transport, glycogenolysis, and iPo(2). The model describes convection, O(2) diffusion, and cellular metabolism, including anaerobic glycogenolysis. Consequently, the model simulates iPo(2) in response to muscle contraction under a variety of experimental conditions. The model was validated by comparison of simulations of O(2) uptake with corresponding experimental responses of electrically stimulated canine muscle under different O(2) content, blood flow, and contraction intensities. The model allows hypothetical variation of PS, glycogenolytic capacity, and blood flow and predictions of the distinctive effects of these factors on the iPo(2)-contraction intensity relationship in canine muscle. Although PS is the main factor regulating O(2) diffusion rate, model simulations indicate that PS and O(2) gradient have essential roles, depending on the specific conditions. Furthermore, the model predicts that different convection and diffusion patterns and metabolic factors may be responsible for different iPo(2)-WR relationships in humans.

Regulation of cytosolic and mitochondrial oxidation via malate-aspartate shuttle: an observation using dynamic ¹³C NMR spectroscopy.

The malate-aspartate (M-A) shuttle provides an important mechanism of metabolic communication between the cytosol and the mitochondria. In this study, dynamic (13)C NMR spectroscopy was combined with a multi-domain model of cardiac metabolism for direct quantification of metabolic fluxes through the tricarboxylic acid (TCA) cycle (VTCA) and the M-A shuttle (VM-A) in intact heart. The sensitivity of this approach to altered M-A shuttle activity was examined at different cytosolic redox states. Dynamic (13)C NMR spectra were acquired from isolated rat hearts perfused with (13)C labeled fatty acid at either low (fatty acid only) or high cytosolic redox state induced by exogenous glucose and lactate. VTCA and VM-A were determined by least-square fitting of the model to NMR data. Our results showed that while VTCA was similar, VM-A increased by 75% at high cytosolic redox state. Therefore, our proposed method provides the opportunity for direct quantification of metabolic communication between subcellular compartments via the M-A shuttle.

Hemoglobin and myoglobin contributions to skeletal muscle oxygenation in response to exercise.

The quantitative contributions of hemoglobin and myoglobin oxygenation in skeletal muscle depend on physiological factors, especially muscle blood flow (Q( m )) and capillary permeability-surface area (PS). Near-infrared spectroscopy (NIRS) can be used to quantify total heme oxidation, but it is unable to distinguish between hemoglobin and myoglobin. Therefore, a mechanistic computational model has been developed to distinguish the contributions of oxygenated hemoglobin and myoglobin to the total NIRS signal. Model simulations predict how Q( m ) and PS can affect oxygenated hemoglobin and myoglobin.Although both hemoglobin and myoglobin oxygenation decrease with impaired Q( m ), simulations show that myoglobin provides a greater contribution to the overall NIRS signal. A decrease of PS primarily affects myoglobin oxygenation. Based on model simulations, the contribution of myoglobin oxygenation to the total NIRS signal can be significantly different under pathophysiological conditions, such as diabetes and peripheral arterial disorder.

Computational model of cellular metabolic dynamics: effect of insulin on glucose disposal in human skeletal muscle.

Identifying the mechanisms by which insulin regulates glucose metabolism in skeletal muscle is critical to understanding the etiology of insulin resistance and type 2 diabetes. Our knowledge of these mechanisms is limited by the difficulty of obtaining in vivo intracellular data. To quantitatively distinguish significant transport and metabolic mechanisms from limited experimental data, we developed a physiologically based, multiscale mathematical model of cellular metabolic dynamics in skeletal muscle. The model describes mass transport and metabolic processes including distinctive processes of the cytosol and mitochondria. The model simulated skeletal muscle metabolic responses to insulin corresponding to human hyperinsulinemic-euglycemic clamp studies. Insulin-mediated rate of glucose disposal was the primary model input. For model validation, simulations were compared with experimental data: intracellular metabolite concentrations and patterns of glucose disposal. Model variations were simulated to investigate three alternative mechanisms to explain insulin enhancements: Model 1 (M.1), simple mass action; M.2, insulin-mediated activation of key metabolic enzymes (i.e., hexokinase, glycogen synthase, pyruvate dehydrogenase); or M.3, parallel activation by a phenomenological insulin-mediated intracellular signal that modifies reaction rate coefficients. These simulations indicated that models M.1 and M.2 were not sufficient to explain the experimentally measured metabolic responses. However, by application of mechanism M.3, the model predicts metabolite concentration changes and glucose partitioning patterns consistent with experimental data. The reaction rate fluxes quantified by this detailed model of insulin/glucose metabolism provide information that can be used to evaluate the development of type 2 diabetes.

Modeling of laser coagulation of tissue with MRI temperature monitoring.

Light energy from a laser source that is delivered into body tissue via a fiber-optic probe with minimal invasiveness has been used to ablate solid tumors. This thermal coagulation process can be guided and monitored accurately by continuous magnetic resonance imaging (MRI) since the laser energy delivery system does not interfere with MRI. This report deals with mathematical modeling and analysis of laser coagulation of tissue. This model is intended for "real-time" analysis of magnetic resonance images obtained during the coagulation process to guide clinical treatment. A mathematical model is developed to simulate the thermal response of tissue to a laser light heating source. For fast simulation, an approximate solution of the thermal model is used to predict the dynamics of temperature distribution and tissue damage induced by a laser energy line source. The validity of these simulations is tested by comparison with MRI-based temperature data acquired from in vivo experiments in rabbits. The model-simulated temperature distribution and predicted lesion dynamics correspond closely with MRI-based data. These results demonstrate the potential for using this combination of fast modeling and MRI technologies during laser heating of tissue for online prediction of tumor lesion size during laser heating.

Modeling oxygenation in venous blood and skeletal muscle in response to exercise using near-infrared spectroscopy.

Noninvasive, continuous measurements in vivo are commonly used to make inferences about mechanisms controlling internal and external respiration during exercise. In particular, the dynamic response of muscle oxygenation (Sm(O(2))) measured by near-infrared spectroscopy (NIRS) is assumed to be correlated to that of venous oxygen saturation (Sv(O(2))) measured invasively. However, there are situations where the dynamics of Sm(O(2)) and Sv(O(2)) do not follow the same pattern. A quantitative analysis of venous and muscle oxygenation dynamics during exercise is necessary to explain the links between different patterns observed experimentally. For this purpose, a mathematical model of oxygen transport and utilization that accounts for the relative contribution of hemoglobin (Hb) and myoglobin (Mb) to the NIRS signal was developed. This model includes changes in microvascular composition within skeletal muscle during exercise and integrates experimental data in a consistent and mechanistic manner. Three subjects (age 25.6 +/- 0.6 yr) performed square-wave moderate exercise on a cycle ergometer under normoxic and hypoxic conditions while muscle oxygenation (C(oxy)) and deoxygenation (C(deoxy)) were measured by NIRS. Under normoxia, the oxygenated Hb/Mb concentration (C(oxy)) drops rapidly at the onset of exercise and then increases monotonically. Under hypoxia, C(oxy) decreases exponentially to a steady state within approximately 2 min. In contrast, model simulations of venous oxygen concentration show an exponential decrease under both conditions due to the imbalance between oxygen delivery and consumption at the onset of exercise. Also, model simulations that distinguish the dynamic responses of oxy-and deoxygenated Hb (HbO(2), HHb) and Mb (MbO(2), HMb) concentrations (C(oxy) = HbO(2) + MbO(2); C(deoxy) = HHb + HMb) show that Hb and Mb contributions to the NIRS signal are comparable. Analysis of NIRS signal components during exercise with a mechanistic model of oxygen transport and metabolism indicates that changes in oxygenated Hb and Mb are responsible for different patterns of Sm(O(2)) and Sv(O(2)) dynamics observed under normoxia and hypoxia.

Non-invasive estimation of metabolic flux and blood flow in working muscle: effect of blood-tissue distribution.

Muscle oxygenation measurements by near infrared spectroscopy (NIRS) are frequently obtained in humans to make inferences about mechanisms of metabolic control of respiration in working skeletal muscle. However, these measurements have technical limitations that can mislead the evaluation of tissue processes. In particular, NIRS measurements of working muscle represent oxygenation of a mix of fibers with heterogeneous activation, perfusion and architecture. Specifically, the relative volume distribution of capillaries, small arteries, and venules may affect NIRS data. To determine the effect of spatial volume distribution of components of working muscle on oxygen utilization dynamics and blood flow changes, a mathematical model of oxygen transport and utilization was developed. The model includes blood volume distribution within skeletal muscle and accounts for convective, diffusive, and reactive processes of oxygen transport and metabolism in working muscle. Inputs to the model are arterial O2 concentration, cardiac output and ATP demand. Model simulations were compared to exercise data from human subjects during a rest-to-work transition. Relationships between muscle oxygen consumption, blood flow, and the rate coefficient of capillary-tissue transport are analyzed. Blood volume distribution in muscle has noticeable effects on the optimal estimates of metabolic flux and blood flow in response to an exercise stimulus.

Soil mobility of synthetic and virus-based model nanopesticides.

Large doses of chemical pesticides are required to achieve effective concentrations in the rhizosphere, which results in the accumulation of harmful residues. Precision farming is needed to improve the efficacy of pesticides, but also to avoid environmental pollution, and slow-release formulations based on nanoparticles offer one solution. Here, we tested the mobility of synthetic and virus-based model nanopesticides by combining soil column experiments with computational modelling. We found that the tobacco mild green mosaic virus and cowpea mosaic virus penetrate soil to a depth of at least 30 cm, and could therefore deliver nematicides to the rhizosphere, whereas the Physalis mosaic virus remains in the first 4 cm of soil and would be more useful for the delivery of herbicides. Our experiments confirm that plant viruses are superior to synthetic mesoporous silica nanoparticles and poly(lactic-co-glycolic acid) for the delivery and controlled release of pesticides, and could be developed as the next generation of pesticide delivery systems.

Multi-scale model of O2 transport and metabolism: response to exercise.

Regulation of pulmonary oxygen uptake (VO2p) during exercise depends on cellular energy demand, blood flow, ventilation, oxygen exchange across membranes, and oxygen utilization in the contracting skeletal muscle. In human and animal studies of metabolic processes that control cellular respiration in working skeletal muscle, pulmonary VO2 dynamics is measured at the mouth using indirect calorimetry. To provide information on the dynamic balance between oxygen delivery and oxygen consumption at the microvascular level, muscle oxygenation is measured using near-infrared spectroscopy. A multi-scale computational model that links O2 transport and cellular metabolism in the skeletal muscle was developed to relate the measurements and gain quantitative understanding of the regulation of VO2 at the cellular, tissue, and whole-body level. The model incorporates mechanisms of oxygen transport from the airway openings to the cell, as well as the phosphagenic and oxidative pathways of ATP synthesis in the muscle cells.

The role of Ca2+ in coupling cardiac metabolism with regulation of contraction: in silico modeling.

The heart adapts the rate of mitochondrial ATP production to energy demand without noticeable changes in the concentration of ATP, ADP and Pi, even for large transitions between different workloads. We suggest that the changes in demand modulate the cytosolic Ca2+ concentration that changes mitochondrial Ca2+ to regulate ATP production. Thus, the rate of ATP production by the mitochondria is coupled to the rate of ATP consumption by the sarcomere cross-bridges (XBs). An integrated model was developed to couple cardiac metabolism and mitochondrial ATP production with the regulation of Ca2+ transient and ATP consumption by the sarcomere. The model includes two interrelated systems that run simultaneously utilizing two different integration steps: (1) The faster system describes the control of excitation contraction coupling with fast cytosolic Ca2+ transients, twitch mechanical contractions, and associated fluctuations in the mitochondrial Ca2+. (2) A slower system simulates the metabolic system, which consists of three different compartments: blood, cytosol, and mitochondria. The basic elements of the model are dynamic mass balances in the different compartments. Cytosolic Ca2+ handling is determined by four organelles: sarcolemmal Ca2+ influx and efflux; sarcoplasmic reticulum (SR) Ca2+ release and sequestration (SR); binding and dissociation from sarcomeric regulatory troponin complexes; and mitochondrial Ca2+ flows. Mitochondrial Ca2+ flows are determined by the Ca2+ uniporter and the mitochondrial Na+Ca2+ exchanger. The cytosolic Ca2+ determines the rate of ATP consumption by the sarcomere. Ca2+ binding to troponin regulates the rate of XBs recruitment and force development. The mitochondrial Ca2+ concentration determines the pyruvate dehydrogenase activity and the rate of ATP production by the F(1)-F(0) ATPase. The workload modulates the cytosolic Ca2+ concentration through feedback loops. The preload and afterload affect the number of strong XBs. The number of strong XBs determines the affinity of troponin for Ca2+, which alters the cytosolic Ca2+ transient. Model simulations quantify the role of Ca2+ in simultaneously controlling the power of contraction and the rate of ATP production. It explains the established empirical observation that significant changes in the metabolic fluxes can occur without significant changes in the key nucleotide (ATP and ADP) concentrations. Quantitative investigations of the mechanisms underlying the cardiac control of biochemical to mechanical energy conversion may lead to novel therapeutic modalities for the ischemic and failing myocardium.

A computational model of adipose tissue metabolism: evidence for intracellular compartmentation and differential activation of lipases.

Regulation of lipolysis in adipose tissue is critical to whole body fuel homeostasis and to the development of insulin resistance. Due to the challenging nature of laboratory investigations of regulatory mechanisms in adipose tissue, mathematical models could provide a valuable adjunct to such experimental work. We have developed a computational model to analyze key components of adipose tissue metabolism in vivo in human in the fasting state. The various key components included triglyceride-fatty acid cycling, regulation of lipolytic reactions, and glyceroneogenesis. The model, consisting of spatially lumped blood and cellular compartments, included essential transport processes and biochemical reactions. Concentration dynamics for major substrates were described by mass balance equations. Model equations were solved numerically to simulate dynamic responses to intravenous epinephrine infusion. Model simulations were compared with the corresponding experimental measurements of the arteriovenous difference across the abdominal subcutaneous fat bed in humans. The model can simulate physiological responses arising from the different expression levels of lipases. Key findings of this study are as follows: (1) Distinguishing the active metabolic subdomain ( approximately 3% of total tissue volume) is critical for simulating data. (2) During epinephrine infusion, lipases are differentially activated such that diglyceride breakdown is approximately four times faster than triglyceride breakdown. (3) Glyceroneogenesis contributes more to glycerol-3-phosphate synthesis during epinephrine infusion when pyruvate oxidation is inhibited by a high acetyl-CoA/free-CoA ratio.

Role of the malate-aspartate shuttle on the metabolic response to myocardial ischemia.

The malate-aspartate (M-A) shuttle provides an important mechanism to regulate glycolysis and lactate metabolism in the heart by transferring reducing equivalents from cytosol into mitochondria. However, experimental characterization of the M-A shuttle has been incomplete because of limitations in quantifying cytosolic and mitochondrial metabolites. In this study, we developed a multi-compartment model of cardiac metabolism with detailed presentation of the M-A shuttle to quantitatively predict non-observable fluxes and metabolite concentrations under normal and ischemic conditions in vivo. Model simulations predicted that the M-A shuttle is functionally localized to a subdomain that spans the mitochondrial and cytosolic spaces. With the onset of ischemia, the M-A shuttle flux rapidly decreased to a new steady state in proportion to the reduction in blood flow. Simulation results suggest that the reduced M-A shuttle flux during ischemia was not due to changes in shuttle-associated enzymes and transporters. However, there was a redistribution of shuttle-associated metabolites in both cytosol and mitochondria. Therefore, the dramatic acceleration in glycolysis and the switch to lactate production that occur immediately after the onset of ischemia is mediated by reduced M-A shuttle flux through metabolite redistribution of shuttle associated species across the mitochondrial membrane.

Drug-eluting polymer implants in cancer therapy.

BACKGROUND: Drug-eluting polymer implants present a compelling parenteral route of administration for cancer chemotherapy. With potential for minimally invasive, image-guided placement and highly localized drug release, these delivery systems are playing an increasingly important role in cancer management. This is particularly true as the use of labile proteins and other bioactive molecules is likely to increase in the upcoming years. OBJECTIVE: In this review, we present the current trends in the application of Pre-formed and in situ-forming systems as drug-eluting implants for cancer chemotherapy. METHODS: We outline the clinically available options as well as up-and-coming technologies and their advantages and challenges. We also describe ongoing related innovations with image-guided drug delivery, mathematical modeling of implanted delivery systems and implanted drug delivery in combination with other therapies. RESULTS/CONCLUSION: Whether used alone or combined with other minimally invasive procedures, drug-eluting polymeric implants will play a significant role in the future of cancer management.

Modeling cellular metabolism and energetics in skeletal muscle: large-scale parameter estimation and sensitivity analysis.

Skeletal muscle plays a major role in the regulation of whole-body energy metabolism during physiological stresses such as ischemia, hypoxia, and exercise. Current experimental techniques provide relatively little in vivo data on dynamic responses of metabolite concentrations and metabolic fluxes in skeletal muscle to such physiological stimuli. As a complementary approach to experimental measurements and as a framework for quantitatively analyzing available in vivo data, a physiologically based model of skeletal muscle cellular metabolism and energetics is developed. This model, which incorporates key transport and reaction processes, is based on dynamic mass balances of 30 chemical species in capillary (blood) and tissue (cell) domains. The reaction fluxes in the cellular domain are expressed in terms of a generalized Michaelis?Menten equation involving energy controller ratios ATP/ADP and ATP/ADP and NADH/NAD+ . This formalism introduces a large number of unknown parameters ( approximately 90). Estimating these parameters from in vivo sparse data and evaluating dynamic sensitivities of the model outputs with respect to these parameters is a challenging problem. Parameter estimation is accomplished using an efficient, nonlinear, constraint-based, optimization algorithm that minimizes differences between available experimental data and corresponding model outputs by explicitly utilizing equality constraints on resting fluxes and concentrations. With the estimated parameter values, the model is able to simulate dynamic responses to reduced blood flow (ischemia) of key metabolite concentrations and metabolic fluxes, both measured and nonmeasured. A general parameter sensitivity analysis is carried out to determine and characterize the parameters having the most and least effects on the measured outputs.

Dynamics of MRI-Guided thermal ablation of VX2 tumor in paraspinal muscle of rabbits.

This study combines fast magnetic resonance imaging (MRI) and model simulation of tissue thermal ablation for monitoring and predicting the dynamics of lesion size for tumor destruction. In vivo experiments were conducted using radiofrequency (RF) thermal ablation in paraspinal muscle of rabbit with a VX2 tumor. Before ablation, turbo-spin echo (TSE) images visualized the 3-D tumor (necrotic core and tumor periphery) and surrounding normal tissue. MR gradient-recalled echo (GRE) phase and magnitude images were acquired repeatedly in 3.3 s at 30-s intervals during and after thermal ablation to follow tissue temperature distribution dynamics and lesion development in tumor and surrounding normal tissue. Final lesion sizes estimated from GRE magnitude, post-ablation TSE, and stained histologic images were compared. Model simulations of temperature distribution and lesion development dynamics closely corresponded to the experimental data from MR images in tumor and normal tissue. The combined use of MR image monitoring and model simulation has the potential for improving pretreatment planning and real-time prediction of lesion-size dynamics for guidance of thermal ablation of tumors.