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Soon Nan Wee,1,* Christian Liman,1,* Heidi C Waters,2 Christy R Houle,3 Miguel Renteria,1 Sankha S Mukherjee,1 Subina Surendran,1 Joshua Marcovici,1 Malaak Brubaker,2 Stine Rasmussen Meehan,4 Anne de Jong-Laird,2 A John Rush,5– 7 Joydeep Sarkar1 1Holmusk Technologies, Inc, New York, NY, USA; 2Otsuka Pharmaceutical Development & Commercialization, Inc, Princeton, NJ, USA; 3Lundbeck, Deerfield, IL, USA; 4H. Lundbeck A/S, Valby, Denmark; 5Department of Psychiatry, Duke-National University of Singapore, Singapore, Singapore; 6Department of Psychiatry, Duke University School of Medicine, Durham, NC, USA; 7Health Sciences Center, Texas Tech University, Odessa, TX, USA*These authors contributed equally to this workCorrespondence: Heidi C Waters, Otsuka Pharmaceutical Development & Commercialization, Inc, 508 Carnegie Center Drive, Princeton, NJ, 08540, USA, Tel +1 609 535 9626, Email heidi.waters@otsuka-us.comPurpose: Life engagement encompasses concepts such as life fulfillment, well-being, and participation in meaningful activities, encompassing cognitive, physical, social, and emotional dimensions. Patients with MDD experience impaired functioning across multiple domains of life engagement and have ranked concepts related to life engagement and fulfillment as important predictors of treatment success. Post-hoc analyses of three clinical trials of patients with MDD treated adjunctively with brexpiprazole have reported a significantly greater improvement in life engagement. This study investigated improvements in life engagement among patients with MDD following initiation of brexpiprazole treatment using a real-world dataset.Patients and Methods: Information was extracted from semi-structured clinical notes of the Mental Status Examination (MSE) of patients in a real-world setting to develop an outcome measure for quantifying life engagement of psychiatric patients. Measures of life engagement and its four sub-domains (emotional, physical, social, and cognitive) were calculated at each clinical visit for 624 adult patients with MDD during the 6 months following brexpiprazole initiation. Paired t-tests assessed differences between the index event and time periods within 6 months of the index event. Kaplan–Meier survival analyses were used to quantify the improvement in life engagement scores following brexpiprazole initiation.Results: The study identified 54 clinical features associated with life engagement. Statistically significant improvements were observed from as early as 1 month following brexpiprazole initiation, with 20.6%, 37.9%, and 53.9% of the patients demonstrating improved life engagement scores within 1, 3, and 6 months, respectively. The improvements were particularly apparent for the emotional and social sub-domains.Conclusion: The results of this study provide evidence of improved life engagement following brexpiprazole initiation in a real-world dataset.Keywords: brexpiprazole, major depressive disorder, real-world evidence, mental status examination, life engagement

This observational retrospective real-world study examined changes in healthcare resource utilization (HCRU) pre- and post-initiation of aripiprazole once-monthly (AOM 400) in patients with schizophrenia or bipolar I disorder.Electronic health record-derived, de-identified data from the NeuroBlu Database (2013-2020) were used to identify patients ≥18 years with schizophrenia (Statistically significant differences were seen in both schizophrenia and bipolar I disorder patient cohorts pre- and post-AOM 400 in inpatient hospitalization rates (A reduction in the rate of hospitalizations, emergency department visits, 30-day readmissions, and average length-of-stay was observed for patients diagnosed with either schizophrenia or bipolar I disorder, which suggests a positive effect of AOM 400 treatment on HCRU outcomes and is supportive of earlier analyses from different data sources.

Given the acknowledged lack of success in Alzheimer’s disease (AD) drug development over the past two decades, the objective of this review was to derive key insights from the myriad failures to inform future drug development. A systematic and exhaustive review was performed on all failed AD compounds for dementia (interventional phase II and III clinical trials from ClinicalTrials.gov) from 2004 to the present. Starting with the initial ∼2,700 AD clinical trials, ∼550 trials met our initial criteria, from which 98 unique phase II and III compounds with various mechanisms of action met our criteria of a failed compound. The two recent reported phase III successes of aducanumab and oligomannate are very encouraging; however, we are awaiting real-world validation of their effectiveness. These two successes against the 98 failures gives a 2.0% phase II and III success rate since 2003, when the previous novel compound was approved. Potential contributing methodological factors for the clinical trial failures were categorized into 1) insufficient evidence to initiate the pivotal trials, and 2) pivotal trial design shortcomings. Our evaluation found that rational drug development principles were not always followed for AD therapeutics development, and the question remains whether some of the failed compounds may have shown efficacy if the principles were better adhered to. Several recommendations are made for future AD therapeutic development. The whole database of the 98 failed compounds is presented in the Supplementary Material.

Sheryl Ker,1,* Jennifer Hsu,2,* Anisha Balani,1,* Sankha Subhra Mukherjee,1 A John Rush,3– 5 Mehreen Khan,2 Sara Elchehabi,2 Seth Huffhines,2 Dustin DeMoss,2,6 Miguel E Rentería,1 Joydeep Sarkar1 1Holmusk Technologies, Inc., New York, NY, USA; 2John Peter Smith Health Network, Fort Worth, TX, USA; 3Department of Psychiatry, Duke-National University of Singapore (NUS), Singapore; 4Duke University School of Medicine, Durham, NC, USA; 5Texas Tech Health Sciences Center, Odessa, TX, USA; 6University of North Texas Health Science Center/Texas Christian University, Fort Worth, TX, USA*These authors contributed equally to this workCorrespondence: Miguel E Rentería; Joydeep SarkarHolmusk Technologies, Inc., 4th Floor, 54 Thompson St, New York, NY, 10012, USAEmail miguel.renteria@holmusk.com; joydeep.sarkar@holmusk.comPurpose: To describe attrition patterns of opioid use disorder (OUD) patients treated with buprenorphine (BUP) and to assess how clinical, sociodemographic, or BUP medication dosing features are associated with attrition.Patients and Methods: Electronic health records of adults (16+ year-olds) with OUD treated with BUP from 23 different substance use or mental health care programs across 11 US states were examined for one year following BUP initiation in inpatient (IP), intensive outpatient (IOP), or outpatient (OP) settings. Treatment attrition was declared at > 37 days following the last recorded visit. Survival analyses and predictive modelling were used.Results: Retention was consistently 2– 3 times higher following BUP initiation in OP (n = 2409) than in IP/IOP (n = 2749) settings after 2 (50% vs 25%), 6 (27% vs 9%) and 12 months (14% vs 4%). Retention was higher for females, whites (vs blacks), and those with less severe OUD, better global function, or not using non-psychotropic medications. Comorbid substance use, other psychiatric disorders, and the number of psychotropic medications were variously related to retention depending on the setting in which BUP was initiated. Predictive modelling revealed that a higher global assessment of functioning and a smaller OUD severity based on the Clinical Global Impression – Severity led to longer retentions, a higher initial BUP dose led to higher retention in a few cases, an OP setting of BUP initiation led to longer retentions, and a lower total number of psychotropic and non-psychotropic medications led to longer retentions. These were the most important parameters in the model, which identified 75.2% of patients who left BUP treatment within three months post-initiation, with a precision of 90.5%.Conclusion: Of all the OUD patients who began BUP, 50– 75% left treatment within three months, and most could be accurately identified. This could facilitate patient-centered management to better retain OUD patients in BUP treatment.Keywords: opioids, buprenorphine, buprenorphine dosing, treatment engagement, treatment retention, treatment dropout, predictors

Background: Real world data on clinical outcomes and quality of care for patients with coronary artery disease (CAD) are fragmented. We describe the rationale and design of the Singapore Cardiovascular Longitudinal Outcomes Database (SingCLOUD). Methods and Results: We designed a health data grid to integrate clinical, administrative, laboratory, procedural, prescription and financial data from all public-funded hospitals and primary care clinics, which provide 80% of health care in Singapore. Here, we explain our approach to harmonize real-world data from diverse electronic medical and non-medical platforms to develop a robust and longitudinal dataset. We present pilot data on patients with myocardial infarction (MI) treated with percutaneous coronary intervention (PCI) between 2012 and 2014. The initial data set had 53,395 patients. Of these, 35,203 had CAD confirmed on coronary angiography, of whom 21,521 had PCI. Eventually, limiting to 2012-2014, 3,819 patients had MI with PCI, while 5,989 had MI. Compared with the quality improvement registry, Singapore Cardiac Data Bank, which had 189 fields for analysis, the SingCLOUD platform generated an additional 313 additional data fields, and was able to identify an additional 250 heart failure events, 664 major adverse cardiovascular events at 2 years, and low-density lipoprotein levels to 1 year for 3,747 patients. Conclusions: By integrating multiple incongruent data sources, SINGCLOUD enables in-depth analysis of real-world cardiovascular "big data".

Electric Vehicle (E.V.) relies on its batteries as the power source. One major issue hampering the use of EV is related to its short driving range due to exhaustion of battery. Battery power consumption suffers with many unbounded conditions that result in excess power consumption. Using the battery providently is the basic idea of the work discussed in this paper, and it can definitely contribute in augmenting the driving range of electric vehicle.In this paper, a system is described, by means of which the battery of E.V. can wisely be utilised by the constant loads of headlamps and thus, it becomes Provident Headlamps. By avoiding unnecessary use of battery and using it precisely when and wherever glow is required, battery power can be conserved. A circuitry is designed, which senses the illumination of the surroundings of vehicle and decides the output requirement of headlamps and will regulate the power from battery to the headlamps accordingly, thus conserving battery and slightly increasing the driving range. This technique has been extended to separate controls for left and right lamps, ensuring safety in two way traffic.

Technology is providing every individual the comfort & ease that is desired by them. Presently evolved sensors have limited human senses pretty well. In the view of this, efforts are undergoing to build up a helping mechanism for those individuals who are visually disabled.A Smart Walking stick based on various sensors may help an individual to perform daily activities easily. Many research activities are undergoing to develop a full-fledged version for it. In this paper, we will try to review most successful concepts and look into the constraints occurring in building smart stick. Then, we will realize camera based image processing as an effective solution, allowing texture recognition, face recognition & text recognition to support visual disability.

Psychiatric practice routinely uses semistructured and/or unstructured free text to record the behavior and mental state of patients. Many of these data are unstructured, lack standardization, and are difficult to use for analysis. Thus, it is difficult to quantitatively analyze a patient’s illness trajectory over time and his or her responsiveness to treatment, and it is also difficult to compare different patients quantitatively. In this article, experts in the field of psychiatry, along with machine learning models, have collaboratively transformed patient data available in status assessments generated by physicians into binary vector representations. Data from patients with mental health disorders collected within a real-world clinical setting from one of the largest behavioral electronic health record (EHR) systems in the United States have been used for generating these representations. The binary vector representation of these health records is shown to be useful in various clinical tasks, such as disease phenotyping, characterizing the suicidality of patients, and inferring diagnoses. To summarize, this approach can transform semistructured free-text summaries of patients’ status assessments into a structured, quantifiable format, which enriches the data that reside within EHR systems. This allows for effective intra- and interpatient quantifications and comparisons, which are much needed in the field of mental health. With the aid of these binary representations, patients’ mental states can be systematically tracked over time, as can their responses to medications at the individual and population levels.

A computational model of the physiological mechanisms driving an individual's health towards onset of type 2 diabetes (T2D) is described, calibrated and validated using data from the Diabetes Prevention Program (DPP). The objective of this model is to quantify the factors that can be used for prevention of T2D. The model is energy and mass balanced and continuously simulates trajectories of variables including body weight components, fasting plasma glucose, insulin, and glycosylated hemoglobin among others on the time-scale of years. Modeled mechanisms include dynamic representations of intracellular insulin resistance, pancreatic beta-cell insulin production, oxidation of macronutrients, ketogenesis, effects of inflammation and reactive oxygen species, and conversion between stored and activated metabolic species, with body-weight connected to mass and energy balance. The model was calibrated to 331 placebo and 315 lifestyle-intervention DPP subjects, and one year forecasts of all individuals were generated. Predicted population mean errors were less than or of the same magnitude as clinical measurement error; mean forecast errors for weight and HbA1c were ~5%, supporting predictive capabilities of the model. Validation of lifestyle-intervention prediction is demonstrated by synthetically imposing diet and physical activity changes on DPP placebo subjects. Using subject level parameters, comparisons were made between exogenous and endogenous characteristics of subjects who progressed toward T2D (HbA1c > 6.5) over the course of the DPP study to those who did not. The comparison revealed significant differences in diets and pancreatic sensitivity to hyperglycemia but not in propensity to develop insulin resistance. A computational experiment was performed to explore relative contributions of exogenous versus endogenous factors between these groups. Translational uses to applications in public health and personalized healthcare are discussed.

Traffic congestion is a threat to the economical, environmental, social and sustainable development of a city. The traffic management has always been an issue of concern for urban areas of a city. Geographic information system (GIS) offers an effective solution to the traffic management of a city and it helps the peoples to find out necessary information regarding traffic, road, location and direction of a destination. General traffic system is limited in data sharing and it is difficult to achieve integration in data processing. In this work, an urban traffic management system based on geographic information system (GIS) is implemented to handle the roads, landmarks, sensitive areas and traffic information for urban traffic police locus. Our work solves various traffic related problems and retrieves the traffic centres that have to be alert in different situations. The detected shortest path is visualized with the connected paths in our approach.

In many research activities related to improving wind turbine efficiency, the major focus has been in improvement of blade design, number of blades that is most suitable, and aerodynamics of design to make the design more strong and efficient. Also, to tackle the irregularities related to the wind pattern, many control systems have been designed to actively adapt to the wind conditions to capture the maximum power. To improve the energy capture efficiency of wind turbines, many maximum power point tracking algorithms have been developed. In this review paper, we will focus majorly on Permanent magnet synchronous generator based Wind energy conversion system and various maximum power tracking systems designed for such systems and will set a comparative analysis to determine the effectiveness of such control system.

Increased energy consumption in industrial and commercial sub-transmission networks has considerably increased the loading of transmission lines. In order to satisfy consumer demand, this capacity should be increased. Now a day's ACSR conductor are used for transmission of electrical energy. They can withstand temperature up to 85°C as well as their current carrying capacity is also less. So the, two main ways to increase capacity are by using high-temperature low-sag (HTLS) conductors, and by building new sub transmission lines. To construct new transmission line Right of Way (ROW) is big hurdle due huge rise in land cost. So to replace ACSR conductor by newly developed HTLS conductor is only way to increase transmission capacity and meet today's growing demand. This paper discuss the statistical results that shows high temperature low sag (HTLS) conductors can be used for transmission of nearly doubled electric power in comparison to exacting ACSR conductor.

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., Author summary Iron is mostly recycled with very little loss or replenishment. This model simulates the complex regulatory network that maintains iron within healthy limits. Iron diseases are typically characterized by breakdown of such regulatory pathways (e.g. synthesis of erythropoietin, inhibition of iron release by hepcidin, etc.) that lead to pathological lack of iron or deposition of iron. Most iron metabolism research focuses on the specific roles of the regulatory proteins (e.g. HFE, ceruloplasmin), but here we chose to focus on the interplay between ferroportin and hepcidin. The current literature lacks an integrated whole-body view of iron metabolism with key fluxes that are essential for investigating the roles of regulatory protein within feedback networks and molecular pathways. These aspects can be investigated by simulations with our top-down, mechanistic computational model. Our model simulations suggest possible improvements in treatment of anemia of chronic kidney disease. Furthermore, this model can provide a platform for future developments of powerful predictive tools that can be used to accelerate drug development of iron-disorder diseases.

Inflammation is a complex, non-linear process central to many of the diseases that affect both developed and emerging nations. A systems-based understanding of inflammation, coupled to translational applications, is therefore necessary for efficient development of drugs and devices, for streamlining analyses at the level of populations, and for the implementation of personalized medicine. We have carried out an iterative and ongoing program of literature analysis, generation of prospective data, data analysis, and computational modeling in various experimental and clinical inflammatory disease settings. These simulations have been used to gain basic insights into the inflammatory response under baseline, gene-knockout, and drug-treated experimental animals for in silico studies associated with the clinical settings of sepsis, trauma, acute liver failure, and wound healing to create patient-specific simulations in polytrauma, traumatic brain injury, and vocal fold inflammation; and to gain insight into host-pathogen interactions in malaria, necrotizing enterocolitis, and sepsis. These simulations have converged with other systems biology approaches (e.g., functional genomics) to aid in the design of new drugs or devices geared towards modulating inflammation. Since they include both circulating and tissue-level inflammatory mediators, these simulations transcend typical cytokine networks by associating inflammatory processes with tissue/organ impacts via tissue damage/dysfunction. This framework has now allowed us to suggest how to modulate acute inflammation in a rational, individually optimized fashion. This plethora of computational and intertwined experimental/engineering approaches is the cornerstone of Translational Systems Biology approaches for inflammatory diseases.

Hemorrhagic shock (HS) elicits a global acute inflammatory response, organ dysfunction, and death. We have used mathematical modeling of inflammation and tissue damage/dysfunction to gain insight into this complex response in mice. We sought to increase the fidelity of our mathematical model and to establish a platform for testing predictions of this model. Accordingly, we constructed a computerized, closed-loop system for mouse HS. The intensity, duration, and time to achieve target MAP could all be controlled using a software. Fifty-four male C57/black mice either were untreated or underwent surgical cannulation. The cannulated mice were divided into 8 groups: (a) 1, 2, 3, or 4 h of surgical cannulation alone and b) 1, 2, 3, or 4 h of cannulation + HS (25 mmHg). MAP was sustained by the computer-controlled reinfusion and withdrawal of shed blood within +/-2 mmHg. Plasma was assayed for the cytokines TNF, IL-6, and IL-10 as well as the NO reaction products NO2-/NO3-. The cytokine and NO2-/NO3- data were compared with predictions from a mathematical model of post-hemorrhage inflammation, which was calibrated on different data. To varying degrees, the levels of TNF, IL-6, IL-10, and NO2/NO3 predicted by the mathematical model matched these data closely. In conclusion, we have established a hardware/software platform that allows for highly accurate, reproducible, and mathematically predictable HS in mice.

Objective During lung transplantation, cells in the pulmonary parenchyma are subjected to ischemia, hypothermic storage, and reperfusion injury. Platelets, whose granular contents include adhesion receptors, chemokines, and coactivating substances that activate inflammatory and coagulant cascades, likely play a critical role in the lung allograft response to ischemia and reperfusion. The platelet response to the pulmonary allograft, however, has never been studied. Here we report significant platelet activation immediately after lung transplantation. Methods We performed a prospective cohort study comparing markers of platelet activation in patients undergoing lung transplantation and patients undergoing nontransplant thoracotomy. Plasma levels of soluble P-selectin, soluble CD40 ligand, and platelet–leukocyte conjugates were measured before surgery, after skin closure, and at 6 postoperative hours. Results Both soluble P-selectin and soluble CD40 ligand levels increased significantly after lung transplantation but not after thoracotomy. Additionally, platelet–monocyte conjugate fluorescence was significantly higher after lung transplantation than after thoracotomy alone. Conclusion These findings suggest that platelet activation is significantly increased after lung transplantation beyond that expected from the postoperative state. The increase in circulating platelet–monocyte conjugates suggests an important interaction between platelets and inflammatory cells. Further research should examine whether platelet activation affects early graft function after lung transplantation.

Trauma-induced critical illness is driven by acute inflammation, and elevated systemic interleukin-6 (IL-6) after trauma is a biomarker of adverse outcomes. We constructed a multicompartment, ordinary differential equation model that represents a virtual trauma patient. Individual-specific variants of this model reproduced both systemic inflammation and outcomes of 33 blunt trauma survivors, from which a cohort of 10,000 virtual trauma patients was generated. Model-predicted length of stay in the intensive care unit, degree of multiple organ dysfunction, and IL-6 area under the curve as a function of injury severity were in concordance with the results from a validation cohort of 147 blunt trauma patients. In a subcohort of 98 trauma patients, those with high-IL-6 single-nucleotide polymorphisms (SNPs) exhibited higher plasma IL-6 levels than those with low IL-6 SNPs, matching model predictions. Although IL-6 could drive mortality in individual virtual patients, simulated outcomes in the overall cohort were independent of the propensity to produce IL-6, a prediction verified in the 98-patient subcohort. In silico randomized clinical trials suggested a small survival benefit of IL-6 inhibition, little benefit of IL-1β inhibition, and worse survival after tumor necrosis factor-α inhibition. This study demonstrates the limitations of extrapolating from reductionist mechanisms to outcomes in individuals and populations and demonstrates the use of mechanistic simulation in complex diseases.

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., Author Summary Iron metabolism is an important physiological phenomenon essential for sustaining life. There is a tight regulation of iron levels in humans and both deficiency and overload can lead to disorders such as anemia and hemochromatosis. Recycling of iron in human body via macrophage iron release is crucial to maintain healthy iron levels. However, a computational model is needed to quantitatively analyze the mechanism underlying a key process in iron homeostasis, which is the release of iron from the macrophages. Using mechanistic, mathematical models to simulate experimental data, we found a novel mechanism by which macrophages release iron. A comparison of experimental data with model simulations shows that a currently accepted passive-gradient mechanism cannot represent the iron-release process from macrophages. However, our model with a facilitated-transport mechanism associated with ferroportin (only known protein for iron export) accurately reproduces the iron release process. This model quantifies for the first time the detailed molecular mechanism associated with iron transport via ferroportin. This quantitative predictive model of cellular iron efflux is essential for physiologically relevant simulation of whole-body model of iron metabolism in healthy and disease states.

Objective To gain insights into individual variations in acute inflammation and physiology. Design Large-animal study combined with mathematical modeling. Setting Academic large-animal and computational laboratories. Subjects Outbred juvenile swine. Interventions Four swine were instrumented and subjected to endotoxemia (100 µg/kg), followed by serial plasma sampling. Measurements and main results Swine exhibited various degrees of inflammation and acute lung injury, including one death with severe acute lung injury (PaO(2)/FIO(2) ratio μ200 and static compliance μ10 L/cm H(2)O). Plasma interleukin-1β, interleukin-4, interleukin-6, interleukin-8, interleukin-10, tumor necrosis factor-α, high mobility group box-1, and NO(2)/NO(3) were significantly (p μ .05) elevated over the course of the experiment. Principal component analysis was used to suggest principal drivers of inflammation. Based in part on principal component analysis, an ordinary differential equation model was constructed, consisting of the lung and the blood (as a surrogate for the rest of the body), in which endotoxin induces tumor necrosis factor-α in monocytes in the blood, followed by the trafficking of these cells into the lung leading to the release of high mobility group box-1, which in turn stimulates the release of interleukin-1β from resident macrophages. The ordinary differential equation model also included blood pressure, PaO(2), and FIO(2), and a damage variable that summarizes the health of the animal. This ordinary differential equation model could be fit to both inflammatory and physiologic data in the individual swine. The predicted time course of damage could be matched to the oxygen index in three of the four swine. Conclusions The approach described herein may aid in predicting inflammation and physiologic dysfunction in small cohorts of subjects with diverse phenotypes and outcomes.

Objective The receptor for advanced glycation end products (RAGE) is expressed at high levels in the lung, particularly in type 1 alveolar cells, and has been shown to amplify injury triggered by acute stress. Previous studies suggest serum concentrations of soluble RAGE increase during pulmonary reperfusion injury after transplantation. RAGE blockade has been shown to suppress hepatic and cardiac ischemia and reperfusion injury in mice. Thus we tested the hypothesis that RAGE mediates tissue-injury mechanisms in ischemia and reperfusion injury in the lung. Methods C57BL/6 mice were subjected to 30 minutes of pulmonary ischemia by clamping the left hilum, followed by 60 minutes of reperfusion. Lung function was assessed by means of blood gas analysis, and capillary leak was assessed by injecting fluorescein isothiocyanate–labeled albumin and comparing fluorescence in bronchial lavage fluid with that in serum. Histologic analysis of the lung was performed by a pathologist naive to the experimental conditions. Results In animals subjected to RAGE blockade, significant increases in P o 2 (108 vs 73 mm Hg, P = .0094) and more than 3-fold decrease in capillary leak Relative Fluorescent Units (RFU, 6.12 vs 1.75; P = .001) were observed. Histologic examination revealed significant injury reduction in soluble RAGE-treated animals versus control animals. RAGE knockout mice exhibited a protected phenotype when exposed to pulmonary ischemia and reperfusion. Additionally, interleukin 8 production and nuclear factor κB activation were increased in control mice. Conclusion Abrogation of RAGE signaling attenuates pulmonary ischemia and reperfusion injury. This study suggests that RAGE might play a central role in pulmonary reperfusion injury and in transplantation and that blockade of RAGE might offer a potential target to abrogate pulmonary reperfusion injury in clinical transplantation.

The reticuloendothelial system has a central role in erythropoiesis and iron homeostasis. An important function of reticuloendothelial macrophages is phagocytosis of senescent red blood cells. The iron liberated from heme is recycled for delivery to erythrocyte precursors for a new round of hemoglobin synthesis. The molecular mechanism by which recycled iron is released from macrophages remains unresolved. We have investigated the mechanism of macrophage iron efflux, focusing on the role of ceruloplasmin (Cp), a copper protein with a potent ferroxidase activity that converts Fe2+ to Fe3+ in the presence of molecular oxygen. As shown by others, Cp markedly increased iron binding to apotransferrin at acidic pH; however, the physiological significance of this finding is uncertain because little stimulation was observed at neutral pH. Introduction of a hypoxic atmosphere resulted in marked Cp-stimulated binding of iron to apotransferrin at physiological pH. The role of Cp in cellular iron release was examined in U937 monocytic cells induced to differentiate to the macrophage lineage. Cp added at its normal plasma concentration increased the rate of 55Fe release from U937 cells by about 250%. The stimulation was absolutely dependent on the presence of apotransferrin and hypoxia. Cp-stimulated iron release was confirmed in mouse peritoneal macrophages. Stimulation of iron release required an intracellular "labile iron pool" that was rapidly depleted in the presence of Cp and apotransferrin. Ferroxidase-mediated loading of iron into apotransferrin was critical for iron release because ferroxidase-deficient Cp was inactive and because holotransferrin could not substitute for apotransferrin. The extracellular iron concentration was critical as shown by inhibition of iron release by exogenous free iron, and marked enhancement of release by an iron chelator. Together these data show that Cp stimulates iron release from macrophages under hypoxic conditions by a ferroxidase-dependent mechanism, possibly involving generation of a negative iron gradient.

SummaryFerroxidases are essential for normal iron homeostasis in most organisms. The paralogous vertebrate ferroxidases ceruloplasmin (Cp) and hephaestin (Heph) are considered to have nonidentical functions in iron transport: plasma Cp drives iron transport from tissue stores while intestinal Heph facilitates iron absorption from the intestinal lumen. To clarify the function of Cp, we acutely bled Cp−/− mice to stress iron homeostasis pathways. Red cell hemoglobin recovery was defective in stressed Cp−/− mice, consistent with low iron availability. Contrary to expectations, iron was freely released from spleen and liver stores in Cp−/− mice, but intestinal iron absorption was markedly impaired. Phlebotomy of wild-type mice caused a striking shift of Cp from the duodenal epithelium to the underlying lamina propria, suggesting a critical function of Cp in basolateral iron transport. Regulated relocalization of intestinal Cp may represent a fail-safe mechanism in which Cp shares with Heph responsibility for iron absorption under stress.