Evaluation of 99mTc-Sestamibi as a potential tool to investigate PgP activity in inflammation

Introduction: In the XXI Century ’s Society the scientific investigation process has been growing steadily , and the field of the pharmaceutical research is one of the most enthusiastic and relevant . Here, it is very important to correlate observed functional alterations with possibly modified drug bio distribution patterns . Cancer, inflammation and inf ection are processes that induce many molecular intermediates like cytokines, chemokines and other chemical complexes that can alter the pharmacokinetics of many drugs. One cause of such changes is thought to be the modulator action of these complexes in t he P - Glyco p rotein activity, because they can act like inducers/inhibitors of MDR - 1 expression. This protein results from the expression of MDR - 1 gene, and acts as an ATP energy - dependent efflux pump, with their substrates including many drugs , like antiretrovirals, anticancers, anti - infectives, immunosuppressants, steroids or opioids . Objectives: Because of the lack of methods to provide helpful information in the investigation of in vivo molecular changes in Pgp activity during infection/infl ammation processes, and its value in the explanation of the altered drug pharmacokinetic, this paper want to evaluate the potential utility of 99m Tc - Sestamibi scintigraphy during this kind of health sciences investigation. Although the a im is indeed to create a technique to the in vivo study of Pgp activity, this preliminary Project only reaches the in vitro study phase, assumed as the first step in a n evaluation period for a new tool development. Materials and Methods: For that reason , we are performing in vitro studies of influx and efflux of 99m Tc - Sestamibi ( that is a substrate of Pgp) in hepatocytes cell line (HepG2). We are interested in clarify the cellular behavior of this radiopharmaceutical in Lipopolysaccharide(LPS) stimulated cells ( well known in vitro model of inflammation) to possibly approve this methodology. To validate the results, the Pgp expression will be finally evaluated using Western Blot technique. Results: Up to this moment , we still don’t have the final results, but we have already enough data to let us believe that LPS stimulation induce a downregulation of MDR - 1, and consequently Pgp, which could conduce to a prolonged retention of 99m Tc - Sestamibi in the inflamed cells . Conclusions: If and when this methodology demonstrate the promising results we expect, one will be able to con clude that Nuclear Medicine is an important tool to help evidence based research also on this specific field .

Metabolic alterations in pregnant women: gestational diabetes

Gestational diabetes mellitus (GDM) and controversy are old friends. The impact of GDM on maternal and fetal health has been increasingly recognized. Nevertheless, universal consensus on the diagnostic methods and thresholds has long been lacking. Published guidelines from major societies differ significantly from one another, with recommendations ranging from aggressive screening to no routine screening at all. As a result, real-world practice is equally varied. This article recaps the latest evidence-based recommendations for the diagnosis and classification of GDM. It reviews the current evidence base for intensive multidisciplinary treatment of GDM and provides recommendations for postpartum management to delay and/or prevent progression to type 2 diabetes.

An intelligent clustering scheme for distributed intrusion detection in vehicular cloud computing

In recent years, vehicular cloud computing (VCC) has emerged as a new technology which is being used in wide range of applications in the area of multimedia-based healthcare applications. In VCC, vehicles act as the intelligent machines which can be used to collect and transfer the healthcare data to the local, or global sites for storage, and computation purposes, as vehicles are having comparatively limited storage and computation power for handling the multimedia files. However, due to the dynamic changes in topology, and lack of centralized monitoring points, this information can be altered, or misused. These security breaches can result in disastrous consequences such as-loss of life or financial frauds. Therefore, to address these issues, a learning automata-assisted distributive intrusion detection system is designed based on clustering. Although there exist a number of applications where the proposed scheme can be applied but, we have taken multimedia-based healthcare application for illustration of the proposed scheme. In the proposed scheme, learning automata (LA) are assumed to be stationed on the vehicles which take clustering decisions intelligently and select one of the members of the group as a cluster-head. The cluster-heads then assist in efficient storage and dissemination of information through a cloud-based infrastructure. To secure the proposed scheme from malicious activities, standard cryptographic technique is used in which the auotmaton learns from the environment and takes adaptive decisions for identification of any malicious activity in the network. A reward and penalty is given by the stochastic environment where an automaton performs its actions so that it updates its action probability vector after getting the reinforcement signal from the environment. The proposed scheme was evaluated using extensive simulations on ns-2 with SUMO. The results obtained indicate that the proposed scheme yields an improvement of 10 % in detection rate of malicious nodes when compared with the existing schemes.