Editorial: Understanding Molecular Mechanisms in Diabetic Cardiomyopathy (DCM)

Cardiovascular disease is the leading cause of death worldwide, and diabetes, the most common metabolic syndrome, causes a 2–5 times higher risk for heart disease (1). Specifically, cardiovascular complications in people with diabetes mellitus (DM) are 2-3-fold more elevated than in non-diabetic counterparts, leading to a higher chance of causing diabetic cardiomyopathy (DCM). DCM is a prominent disease in people with DM, and molecular mechanisms that drive DCM are not fully understood as the disease itself is multifactorial and challenging potential treatment options (2). Therefore, this Research Topic is focused on understanding the molecular mechanism(s) contributing to DCM. The Research Topic comprised review and research articles from different experts working on DCM. The Research Topic of original research and review topics highlights the multifactorial molecular mechanisms involved in the DCM and some recent therapeutic advances in preclinical approaches at various levels in the pipeline.VS laboratory is partially supported by the American Heart Association grants (20CDA35260096 and 20TPA3542000)

Synthesis, spectral LFER and antimicrobial activities of some (E)-N׳-(1-(substituted phenyl)ethylidene)benzohydrazides

About eleven substituted (E)-N׳-(1-(substituted phenyl) ethylidene) benzo- hydrazides have been synthesized. They are characterized by their analytical, ultraviolet, infrared and NMR spectral data. The antibacterial and fungal activities of these chalcones have been evaluated

Integration of modeling and simulation into hospital-based decision support systems guiding pediatric pharmacotherapy

<p>Abstract</p> <p>Background</p> <p>Decision analysis in hospital-based settings is becoming more common place. The application of modeling and simulation approaches has likewise become more prevalent in order to support decision analytics. With respect to clinical decision making at the level of the patient, modeling and simulation approaches have been used to study and forecast treatment options, examine and rate caregiver performance and assign resources (staffing, beds, patient throughput). There us a great need to facilitate pharmacotherapeutic decision making in pediatrics given the often limited data available to guide dosing and manage patient response. We have employed nonlinear mixed effect models and Bayesian forecasting algorithms coupled with data summary and visualization tools to create drug-specific decision support systems that utilize individualized patient data from our electronic medical records systems.</p> <p>Methods</p> <p>Pharmacokinetic and pharmacodynamic nonlinear mixed-effect models of specific drugs are generated based on historical data in relevant pediatric populations or from adults when no pediatric data is available. These models are re-executed with individual patient data allowing for patient-specific guidance via a Bayesian forecasting approach. The models are called and executed in an interactive manner through our web-based dashboard environment which interfaces to the hospital's electronic medical records system.</p> <p>Results</p> <p>The methotrexate dashboard utilizes a two-compartment, population-based, PK mixed-effect model to project patient response to specific dosing events. Projected plasma concentrations are viewable against protocol-specific nomograms to provide dosing guidance for potential rescue therapy with leucovorin. These data are also viewable against common biomarkers used to assess patient safety (e.g., vital signs and plasma creatinine levels). As additional data become available via therapeutic drug monitoring, the model is re-executed and projections are revised.</p> <p>Conclusion</p> <p>The management of pediatric pharmacotherapy can be greatly enhanced via the immediate feedback provided by decision analytics which incorporate the current, best-available knowledge pertaining to dose-exposure and exposure-response relationships, especially for narrow therapeutic agents that are difficult to manage.</p

Studies on the dynamic response of coastal sediments due to natural and manmade activities for the Puducherry coast

1322-1326This paper presents the response of the coastal sediments by the impact of waves and construction of manmade structures in the Puducherry coastal stretch, East coast of India. Based on the real time wave climate data which was collected from the nearshore region of coast using wave rider buoy and wave direction indicator. The quantum of sediment movement is calculated using CERC formula for three years (2007, 2008, and 2009) and compared with Kamphuis method for one year i.e., 2009. In order to achieve a more reliable value on the sediment movement a sand trap was used at the littoral zone to collect the actual sediment samples for a period of two months i.e., February and March 2009. For all the three observation period the predominant sediment transport rate is Northerly. Estimated sediment transport rates were also determined by Kamphuis method. From the results obtained, CERC formula ‘over predicts’ the sediment transport rate when compared with Kamphuis method. The actual sediment transport calculated using sand trap was found to be 60% reliable when compared with theoretical sediment transport rate which has been determined by using Kamphuis method.</span

Understanding diabetes-induced cardiomyopathy from the perspective of renin angiotensin aldosterone system

Experimental and clinical evidence suggests that diabetic subjects are predisposed to a distinct cardiovascular dysfunction, known as diabetic cardiomyopathy (DCM), which could be an autonomous disease independent of concomitant micro and macrovascular disorders. DCM is one of the prominent causes of global morbidity and mortality and is on a rising trend with the increase in the prevalence of diabetes mellitus (DM). DCM is characterized by an early left ventricle diastolic dysfunction associated with the slow progression of cardiomyocyte hypertrophy leading to heart failure, which still has no effective therapy. Although the well-known "Renin Angiotensin Aldosterone System (RAAS)" inhibition is considered a gold-standard treatment in heart failure, its role in DCM is still unclear. At the cellular level of DCM, RAAS induces various secondary mechanisms, adding complications to poor prognosis and treatment of DCM. This review highlights the importance of RAAS signaling and its major secondary mechanisms involving inflammation, oxidative stress, mitochondrial dysfunction, and autophagy, their role in establishing DCM. In addition, studies lacking in the specific area of DCM are also highlighted. Therefore, understanding the complex role of RAAS in DCM may lead to the identification of better prognosis and therapeutic strategies in treating DCM.Qatar National Research Fund - Rapid Response Cal

Synthesis of FeCu Nanopowder by Levitational Gas Condensation Process

Condensation from the vapor state is an important technique for the preparation of nanopowders. Levitational gas condensation is one such technique that has a unique ability of attaining steady state. Here, we present the results of applying this technique to an iron-copper alloy (96Fe-4Cu). A qualitative model of the process is proposed to understand the process and the characteristics of resultant powder. A phase diagram of the alloy system in the liquid-vapor region was calculated to help understand the course of condensation, especially partitioning and coring during processing. The phase diagram could not explain coring in view of the simultaneous occurrence of solidification and the fast homogenization through diffusion in the nanoparticles; however, it could predict the very low levels of copper observed in the levitated drop. The enrichment of copper observed near the surface of the powder was considered to be a manifestation of the lower surface energy of copper compared with that of iron. Heat transfer calculations indicated that most condensed particles can undergo solidification even when they are still in the proximity of the levitated drop. It helped us to predict the temperature and the cooling rate of the powder particles as they move away from the levitated drop. The particles formed by the process seem to be single domain, single crystals that are magnetic in nature. They, thus, can agglomerate by forming a chain-like structure, which manifests as a three-dimensional network enclosing a large unoccupied space, as noticed in scanning electron microscopy and transmission electron microscopy studies. This also explains the observed low packing density of the nanopowders

Schematic of three-tier system architecture of hospital pharmacotherapy decision support system comprising a back end database tier, a business logic middle tier and data presentation/user interface front-end tier

<p><b>Copyright information:</b></p><p>Taken from "Integration of modeling and simulation into hospital-based decision support systems guiding pediatric pharmacotherapy"</p><p>http://www.biomedcentral.com/1472-6947/8/6</p><p>BMC Medical Informatics and Decision Making 2008;8():6-6.</p><p>Published online 28 Jan 2008</p><p>PMCID:PMC2254609.</p><p></p

Synthesis of FeCu nanopowder by levitational gas condensation process

Condensation from the vapor state is an important technique for the preparation of nanopowders. Levitational gas condensation is one such technique that has a unique ability of attaining steady state. Here, we present the results of applying this technique to an iron-copper alloy (96Fe-4Cu). A qualitative model of the process is proposed to understand the process and the characteristics of resultant powder. A phase diagram of the alloy system in the liquid-vapor region was calculated to help understand the course of condensation, especially partitioning and coring during processing. The phase diagram could not explain coring in view of the simultaneous occurrence of solidification and the fast homogenization through diffusion in the nanoparticles; however, it could predict the very low levels of copper observed in the levitated drop. The enrichment of copper observed near the surface of the powder was considered to be a manifestation of the lower surface energy of copper compared with that of iron. Heat transfer calculations indicated that most condensed particles can undergo solidification even when they are still in the proximity of the levitated drop. It helped us to predict the temperature and the cooling rate of the powder particles as they move away from the levitated drop. The particles formed by the process seem to be single domain, single crystals that are magnetic in nature. They, thus, can agglomerate by forming a chain-like structure, which manifests as a three-dimensional network enclosing a large unoccupied space, as noticed in scanning electron microscopy and transmission electron microscopy studies. This also explains the observed low packing density of the nanopowders