Use of the dried blood spot sampling process coupled with fast gas chromatography and negative-ion chemical ionization tandem mass spectrometry: application to fluoxetine, norfluoxetine, reboxetine, and paroxetine analysis.

The objective of this work was to combine the advantages of the dried blood spot (DBS) sampling process with the highly sensitive and selective negative-ion chemical ionization tandem mass spectrometry (NICI-MS-MS) to analyze for recent antidepressants including fluoxetine, norfluoxetine, reboxetine, and paroxetine from micro whole blood samples (i.e., 10 microL). Before analysis, DBS samples were punched out, and antidepressants were simultaneously extracted and derivatized in a single step by use of pentafluoropropionic acid anhydride and 0.02% triethylamine in butyl chloride for 30 min at 60 degrees C under ultrasonication. Derivatives were then separated on a gas chromatograph coupled with a triple-quadrupole mass spectrometer operating in negative selected reaction monitoring mode for a total run time of 5 min. To establish the validity of the method, trueness, precision, and selectivity were determined on the basis of the guidelines of the "Société Française des Sciences et des Techniques Pharmaceutiques" (SFSTP). The assay was found to be linear in the concentration ranges 1 to 500 ng mL(-1) for fluoxetine and norfluoxetine and 20 to 500 ng mL(-1) for reboxetine and paroxetine. Despite the small sampling volume, the limit of detection was estimated at 20 pg mL(-1) for all the analytes. The stability of DBS was also evaluated at -20 degrees C, 4 degrees C, 25 degrees C, and 40 degrees C for up to 30 days. Furthermore, the method was successfully applied to a pharmacokinetic investigation performed on a healthy volunteer after oral administration of a single 40-mg dose of fluoxetine. Thus, this validated DBS method combines an extractive-derivative single step with a fast and sensitive GC-NICI-MS-MS technique. Using microliter blood samples, this procedure offers a patient-friendly tool in many biomedical fields such as checking treatment adherence, therapeutic drug monitoring, toxicological analyses, or pharmacokinetic studies.

Modelling the curing process in magneto-sensitive polymers: Rate-dependence and shrinkage

This paper deals with a phenomenologically motivated magneto-viscoelastic coupled finite strain framework for simulating the curing process of polymers under the application of a coupled magneto-mechanical road. Magneto-sensitive polymers are prepared by mixing micron-sized ferromagnetic particles in uncured polymers. Application of a magnetic field during the curing process causes the particles to align and form chain-like structures lending an overall anisotropy to the material. The polymer curing is a viscoelastic complex process where a transformation from fluid. to solid occurs in the course of time. During curing, volume shrinkage also occurs due to the packing of polymer chains by chemical reactions. Such reactions impart a continuous change of magneto-mechanical properties that can be modelled by an appropriate constitutive relation where the temporal evolution of material parameters is considered. To model the shrinkage during curing, a magnetic-induction-dependent approach is proposed which is based on a multiplicative decomposition of the deformation gradient into a mechanical and a magnetic-induction-dependent volume shrinkage part. The proposed model obeys the relevant laws of thermodynamics. Numerical examples, based on a generalised Mooney-Rivlin energy function, are presented to demonstrate the model capacity in the case of a magneto-viscoelastically coupled load.

In-vivo brain neuroimaging provides a gateway for integrating biological and clinical biomarkers of Alzheimer's disease.

PURPOSE OF REVIEW: Only 5% of the Alzheimer's cases are explained by genetic mutations, whereas the remaining 95% are sporadic. The pathophysiological mechanisms underlying sporadic Alzheimer's disease are not well understood, suggesting a complex multifactorial cause. This review summarizes the recent findings on research aiming to show how biomarkers can be used for revealing the underlying mechanisms of preclinical stage Alzheimer's disease and help in their diagnosis. RECENT FINDINGS: The undisputed successful publicly accessible repositories provide longitudinal brain images, clinical, genetic and proteomic information of Alzheimer's disease. By combining with increasingly sophisticated data analysis methods, it is a great opportunity for searching new biomarkers. Innovative studies validated theoretical models of disease progression demonstrating the sequential ordering of well-established biomarkers. Novel observations shed light on the interaction between biomarkers to confirm that disease progression is related to multiple pathological factors. A typical example is the tau-associated neuronal toxicity that can be additionally potentiated by amyloid β peptides. To increase further the complexity, studies report specific impact of common genetic variants that can be traced from childhood through middle age up to the symptomatic onset of Alzheimer's disease. SUMMARY: The discovery of efficient therapies to prevent the disease or modify the progression of disease requires a more thorough understanding of the underlying biological processes. Neuroimaging, genetic and proteomic biomarkers for Alzheimer's disease are critically discussed and proposed to be included in clinical descriptions and diagnostic guidelines.

A multistep process of cancer associated fibroblasts determination under CSL-p53 control

Stromal fibroblast senescence has been linked to the aging-associated increase of tumors. However, in epithelial cancer, density and proliferation of cancer associated fibroblasts (CAF) are frequently increased, rather than decreased. We previously showed that genetic deletion or down-modulation of the canonical Notch effector CSL/RBP-JK in dermal fibroblasts is sufficient for CAF activation with consequent development of keratinocyte-derived tumors. We show here that CSL silencing induces senescence of primary fibroblasts from dermis, oral mucosa, breast and lung. CSL functions in these cells as direct repressor of multiple senescence- and CAF-effector genes. It also physically interacts with p53, repressing its activity. CSL is down-modulated in stromal fibroblasts of premalignant skin actinic keratosis lesions and squamous cell carcinomas (SCC), while p53 gene expression and function is down-modulated only in the latter, with paracrine influences of incipient cancer cells as a likely culprit. Concomitant loss of CSL and p53 overcomes fibroblast senescence, enhances CAF effector gene expression and promotes stromal and cancer cell expansion. The findings support a CAF activation/stromal co-evolution model under convergent CSL/p53 control of likely clinical relevance.

Repetitive Deliberate Fires: Critical Review of the Situation and Proposal of a Follow-Up Process and Systematic Analysis

Deliberate fires appear to be borderless and timeless events creating a serious security problem. There have been many attempts to develop approaches to tackle this problem, but unfortunately acting effectively against deliberate fires has proven a complex challenge. This article reviews the current situation relating to deliberate fires: what do we know, how serious is the situation, how is it being dealt with, and what challenges are faced when developing a systematic and global methodology to tackle the issues? The repetitive nature of some types of deliberate fires will also be discussed. Finally, drawing on the reality of repetition within deliberate fires and encouraged by successes obtained in previous repetitive crimes (such as property crimes or drug trafficking), we will argue that the use of the intelligence process cycle as a framework to allow a follow-up and systematic analysis of fire events is a relevant approach. This is the first article of a series of three articles. This first part is introducing the context and discussing the background issues in order to provide a better underpinning knowledge to managers and policy makers planning on tackling this issue. The second part will present a methodology developed to detect and identify repetitive fire events from a set of data, and the third part will discuss the analyses of these data to produce intelligence.

Prototype of a web-based participative decision support platform in natural hazards and risk management

This paper presents the current state and development of a prototype web-GIS (Geographic Information System) decision support platform intended for application in natural hazards and risk management, mainly for floods and landslides. This web platform uses open-source geospatial software and technologies, particularly the Boundless (formerly OpenGeo) framework and its client side software development kit (SDK). The main purpose of the platform is to assist the experts and stakeholders in the decision-making process for evaluation and selection of different risk management strategies through an interactive participation approach, integrating web-GIS interface with decision support tool based on a compromise programming approach. The access rights and functionality of the platform are varied depending on the roles and responsibilities of stakeholders in managing the risk. The application of the prototype platform is demonstrated based on an example case study site: Malborghetto Valbruna municipality of North-Eastern Italy where flash floods and landslides are frequent with major events having occurred in 2003. The preliminary feedback collected from the stakeholders in the region is discussed to understand the perspectives of stakeholders on the proposed prototype platform.