Reinforcement learning using a continuous time actor-critic framework with spiking neurons.

Animals repeat rewarded behaviors, but the physiological basis of reward-based learning has only been partially elucidated. On one hand, experimental evidence shows that the neuromodulator dopamine carries information about rewards and affects synaptic plasticity. On the other hand, the theory of reinforcement learning provides a framework for reward-based learning. Recent models of reward-modulated spike-timing-dependent plasticity have made first steps towards bridging the gap between the two approaches, but faced two problems. First, reinforcement learning is typically formulated in a discrete framework, ill-adapted to the description of natural situations. Second, biologically plausible models of reward-modulated spike-timing-dependent plasticity require precise calculation of the reward prediction error, yet it remains to be shown how this can be computed by neurons. Here we propose a solution to these problems by extending the continuous temporal difference (TD) learning of Doya (2000) to the case of spiking neurons in an actor-critic network operating in continuous time, and with continuous state and action representations. In our model, the critic learns to predict expected future rewards in real time. Its activity, together with actual rewards, conditions the delivery of a neuromodulatory TD signal to itself and to the actor, which is responsible for action choice. In simulations, we show that such an architecture can solve a Morris water-maze-like navigation task, in a number of trials consistent with reported animal performance. We also use our model to solve the acrobot and the cartpole problems, two complex motor control tasks. Our model provides a plausible way of computing reward prediction error in the brain. Moreover, the analytically derived learning rule is consistent with experimental evidence for dopamine-modulated spike-timing-dependent plasticity.

A Prototype X-ray Framing Camera With Variable Exposure Time Based on Double-Gated Micro-Channel Plates

We present a novel X-ray frame camera with variable exposure time that is based on double-gated micro-channel plates (MCP). Two MCPs are connected so that their channels form a Chevron-MCP structure, and four parallel micro-strip lines (MSLs) are deposited on each surface of the Chevron-MCP. The MSLs on opposing surfaces of the Chevron-MCP are oriented normal to each other and subjected to high voltage. The MSLs on the input and output surfaces are fed high voltage pulses to form a gating action. In forming two-dimensional images, modifying the width of the gating pulse serves to set exposure times (ranging from ps to ms) and modifying the delay between each gating pulse serves to set capture times. This prototype provides a new tool for high-speed X-ray imaging, and this paper presents both simulations and experimental results obtained with the camera.

Intelligent Assembly Time Analysis Using a Digital Knowledge-Based Approach

The implementation of effective time analysis methods fast and accurately in the era of digital manufacturing has become a significant challenge for aerospace manufacturers hoping to build and maintain a competitive advantage. This paper proposes a structure oriented, knowledge-based approach for intelligent time analysis of aircraft assembly processes within a digital manufacturing framework. A knowledge system is developed so that the design knowledge can be intelligently retrieved for implementing assembly time analysis automatically. A time estimation method based on MOST, is reviewed and employed. Knowledge capture, transfer and storage within the digital manufacturing environment are extensively discussed. Configured plantypes, GUIs and functional modules are designed and developed for the automated time analysis. An exemplar study using an aircraft panel assembly from a regional jet is also presented. Although the method currently focuses on aircraft assembly, it can also be well utilized in other industry sectors, such as transportation, automobile and shipbuilding. The main contribution of the work is to present a methodology that facilitates the integration of time analysis with design and manufacturing using a digital manufacturing platform solution.

Social support and the likelihood of maintaining and improving levels of physical activity:the Whitehall II Study

Background: Evidence on the association between social support and leisure time physical activity (LTPA) is scarce and mostly based on cross-sectional data with different types of social support collapsed into a single index. The aim of this study was to investigate whether social support from the closest person was associated with LTPA.

Analysis of the organic matter associated to sea salt : definition of potential molecular markers based on the volatile composition and presence of glycosidic derivatives and polysaccharides

Sea salt is a natural product obtained from the evaporation of seawater in saltpans due to the combined effect of wind and sunlight. Nowadays, there is a growing interest for protection and re-valorisation of saltpans intrinsically associated to the quality of sea salt that can be evaluated by its physico-chemical properties. These man-made systems can be located in different geographical areas presenting different environmental surroundings. During the crystallization process, organic compounds coming from these surroundings can be incorporated into sea salt crystals, influencing their final composition. The organic matter associated to sea salt arises from three main sources: algae, surrounding bacterial community, and anthropogenic activity. Based on the hypothesis that sea salt contains associated organic compounds that can be used as markers of the product, including saltpans surrounding environment, the aim of this PhD thesis was to identify these compounds. With this purpose, this work comprised: 1) a deep characterisation of the volatile composition of sea salt by headspace solid phase microextraction combined with comprehensive two-dimensional gas chromatography time-of-flight mass spectrometry (HS-SPME/GCGC–ToFMS) methodology, in search of potential sea salt volatile markers; 2) the development of a methodology to isolate the polymeric material potentially present in sea salt, in amounts that allow its characterisation in terms of polysaccharides and protein; and 3) to explore the possible presence of triacylglycerides. The high chromatographic resolution and sensitivity of GC×GC–ToFMS enabled the separation and identification of a higher number of volatile compounds from sea salt, about three folds, compared to unidimentional chromatography (GC–qMS). The chromatographic contour plots obtained revealed the complexity of marine salt volatile composition and confirmed the relevance of GC×GC–ToFMS for this type of analysis. The structured bidimentional chromatographic profile arising from 1D volatility and 2D polarity was demonstrated, allowing more reliable identifications. Results obtained for analysis of salt from two locations in Aveiro and harvested over three years suggest the loss of volatile compounds along the time of storage of the salt. From Atlantic Ocean salts of seven different geographical origins, all produced in 2007, it was possible to identify a sub-set of ten compounds present in all salts, namely 6-methyl-5-hepten-2-one, 2,2,6-trimethylcyclohexanone, isophorone, ketoisophorone, β-ionone-5,6-epoxide, dihydroactinidiolide, 6,10,14-trimethyl-2-pentadecanone, 3-hydroxy-2,4,4-trimethylpentyl 2-methylpropanoate, 2,4,4-trimethylpentane-1,3-diyl bis(2-methylpropanoate), and 2-ethyl-1-hexanol. These ten compounds were considered potential volatile markers of sea salt. Seven of these compounds are carotenoid-derived compounds, and the other three may result from the integration of compounds from anthropogenic activity as metabolites of marine organisms. The present PhD work also allowed the isolation and characterisation, for the first time, of polymeric material from sea salt, using 16 Atlantic Ocean salts. A dialysis-based methodology was developed to isolate the polymeric material from sea salt in amounts that allowed its characterisation. The median content of polymeric material isolated from the 16 salts was 144 mg per kg of salt, e.g. 0.014% (w/w). Mid-infrared spectroscopy and thermogravimetry revealed the main occurrence of sulfated polysaccharides, as well as the presence of protein in the polymeric material from sea salt. Sea salt polysaccharides were found to be rich in uronic acid residues (21 mol%), glucose (18), galactose (16), and fucose (13). Sulfate content represented a median of 45 mol%, being the median content of sulfated polysaccharides 461 mg/g of polymeric material, which accounted for 66 mg/kg of dry salt. Glycosidic linkage composition indicates that the main sugar residues that could carry one or more sulfate groups were identified as fucose and galactose. This fact allowed to infer that the polysaccharides from sea salt arise mainly from algae, due to their abundance and composition. The amino acid profile of the polymeric material from the 16 Atlantic Ocean salts showed as main residues, as medians, alanine (25 mol%), leucine (14), and valine (14), which are hydrophobic, being the median protein content 35 mg/g, i.e. 4,9 mg per kg of dry salt. Beside the occurrence of hydrophobic volatile compounds in sea salt, hydrophobic non-volatile compounds were also detected. Triacylglycerides were obtained from sea salt by soxhlet extraction with n-hexane. Fatty acid composition revealed palmitic acid as the major residue (43 mol%), followed by stearic (13), linolenic (13), oleic (12), and linoleic (9). Sea salt triacylglycerides median content was 1.5 mg per kg of dry salt. Both protein and triacylglycerides seem to arise from macro and microalgae, phytoplankton and cyanobacteria, due to their abundance and composition. Despite the variability resulting from saltpans surrounding environment, this PhD thesis allowed the identification of a sea salt characteristic organic compounds profile based on volatile compounds, polysaccharides, protein, and triacylglycerides.

A physical activity intervention in a workplace setting

Physical inactivity poses a huge burden on Canada's health care system and is detrimental to the health of Canadians (Katzmarzyk & Janssen, 2004). Walking is a viable option for individuals to become physically active on a daily basis and is in fact the most commonly reported leisure time physical activity. It has been associated with many health benefits including weight loss/weight control, reduced risk of coronary artery disease and diabetes, lowered blood pressure, and improved psychological wellbeing (Brisson & Tudor-Locke, 2004). Specifically, individuals' stage of change, selfefficacy and health related quality of life (HRQL) are three psychological constructs that can be greatly improved with increased physical activity (Dishman, 1991; Penedo & Dahn, 2005; Poag & McAuley, 1992). Public health physical activity recommendations exist but many individuals find these difficult to meet due to overly busy lifestyles (Public Health Agency of Canada, 2003). Pedometers are inexpensive devices that can monitor individual bouts of walking so that the incorporation of physical activity into one's daily life is more plausible. They are also excellent tools for motivation, goalsetting, and immediate feedback (Brisson & Tudor-Locke, 2004). Since many people spend a large proportion of their time at their places of employment, workplaces have begun to be a common site for the development of physical activity interventions. These programs have been growing in popUlarity and have shown numerous benefits for both employees and employers (Voit, 2001). The purpose of the current study was to implement and evaluate the use of a pedometer-based physical activity intervention incorporating goal-setting and physical activity logs in a workplace setting, and to examine the relationship between different types of self-efficacy (task, barrier, and scheduling) and different phases of the intervention. Twenty male participants from a local steel manufacturing plant who exhibited health risk factors (e.g. hypertension, diabetes, etc.) were assigned to one of two groups (group A or group B). All participants were asked to wear pedometers on their waists, record their daily steps, set goals that were outlined on a step-tracking sheet (detennined by their baseline number of steps), and keep track of their work days, wakelbed time, sedentary time, and time spent doing other physical activity. Group A began the intervention immediately following the baseline measures, whereas group B continued with their regular routine for 4 weeks before beginning. Physiological measures (height, weight, blood pressure, relative body fat, waist and hip circumference, and body mass index) were taken and a battery of questionnaires that assessed barrier, task and scheduling self-efficacy, HRQL, and stage of change administered at baseline, week 5 (end of intervention for group A), week 9 (end of intervention for group B; follow-up for group A) and week 13 (follow-up for both groups). Results showed that this workplace physical activity intervention was successful at increasing the participants' daily steps, that task self-efficacy is a significant predictor of participants' exercise adherence during the initial stages of participation (intervention phase), and that the participants felt that this intervention was effective. Finally, further exploratory analyses showed that this intervention was effective for all participants, but most valuable for participants most in need of improvement - that is, those who were most sedentary prior to the intervention. This intervention is an inexpensive use of simple and effective tools (e.g. pedometers), has the potential to attract a wide variety of participants and become a pennanent part of any health promotion initiative.

Five-year predictors of physical activity decline among adults in low-income communities: a prospective study

Affiliation: J. O'Loughlin: Department of Social and Preventive Medicine, Centre de recherche CHUM, Université de Montréal

First-principle data-driven models for assessment of motor disorders in Parkinson’s disease

Parkinson’s disease (PD) is an increasing neurological disorder in an aging society. The motor and non-motor symptoms of PD advance with the disease progression and occur in varying frequency and duration. In order to affirm the full extent of a patient’s condition, repeated assessments are necessary to adjust medical prescription. In clinical studies, symptoms are assessed using the unified Parkinson’s disease rating scale (UPDRS). On one hand, the subjective rating using UPDRS relies on clinical expertise. On the other hand, it requires the physical presence of patients in clinics which implies high logistical costs. Another limitation of clinical assessment is that the observation in hospital may not accurately represent a patient’s situation at home. For such reasons, the practical frequency of tracking PD symptoms may under-represent the true time scale of PD fluctuations and may result in an overall inaccurate assessment. Current technologies for at-home PD treatment are based on data-driven approaches for which the interpretation and reproduction of results are problematic.  The overall objective of this thesis is to develop and evaluate unobtrusive computer methods for enabling remote monitoring of patients with PD. It investigates first-principle data-driven model based novel signal and image processing techniques for extraction of clinically useful information from audio recordings of speech (in texts read aloud) and video recordings of gait and finger-tapping motor examinations. The aim is to map between PD symptoms severities estimated using novel computer methods and the clinical ratings based on UPDRS part-III (motor examination). A web-based test battery system consisting of self-assessment of symptoms and motor function tests was previously constructed for a touch screen mobile device. A comprehensive speech framework has been developed for this device to analyze text-dependent running speech by: (1) extracting novel signal features that are able to represent PD deficits in each individual component of the speech system, (2) mapping between clinical ratings and feature estimates of speech symptom severity, and (3) classifying between UPDRS part-III severity levels using speech features and statistical machine learning tools. A novel speech processing method called cepstral separation difference showed stronger ability to classify between speech symptom severities as compared to existing features of PD speech. In the case of finger tapping, the recorded videos of rapid finger tapping examination were processed using a novel computer-vision (CV) algorithm that extracts symptom information from video-based tapping signals using motion analysis of the index-finger which incorporates a face detection module for signal calibration. This algorithm was able to discriminate between UPDRS part III severity levels of finger tapping with high classification rates. Further analysis was performed on novel CV based gait features constructed using a standard human model to discriminate between a healthy gait and a Parkinsonian gait. The findings of this study suggest that the symptom severity levels in PD can be discriminated with high accuracies by involving a combination of first-principle (features) and data-driven (classification) approaches. The processing of audio and video recordings on one hand allows remote monitoring of speech, gait and finger-tapping examinations by the clinical staff. On the other hand, the first-principles approach eases the understanding of symptom estimates for clinicians. We have demonstrated that the selected features of speech, gait and finger tapping were able to discriminate between symptom severity levels, as well as, between healthy controls and PD patients with high classification rates. The findings support suitability of these methods to be used as decision support tools in the context of PD assessment.

Activity modeling in practice: a case-based guide to human-centered software engineering

The purpose of this study was to identify whether activity modeling framework supports problem analysis and provides a traceable and tangible connection from the problem identification up to solution modeling. Methodology validation relied on a real problem from a Portuguese teaching syndicate (ASPE), regarding courses development and management. The study was carried out with a perspective to elaborate a complete tutorial of how to apply activity modeling framework to a real world problem. Within each step of activity modeling, we provided a summary elucidation of the relevant elements required to perform it, pointed out some improvements and applied it to ASPE’s real problem. It was found that activity modeling potentiates well structured problem analysis as well as provides a guiding thread between problem and solution modeling. It was concluded that activity-based task modeling is key to shorten the gap between problem and solution. The results revealed that the solution obtained using activity modeling framework solved the core concerns of our customer and allowed them to enhance the quality of their courses development and management. The principal conclusion was that activity modeling is a properly defined methodology that supports software engineers in problem analysis, keeping a traceable guide among problem and solution.

M-protein is down-regulated in cardiac hypertrophy driven by thyroid hormone in rats

Although it is well known that the thyroid hormone (T3) is an important positive regulator of cardiac function over a short term and that it also promotes deleterious effects over a long term, the molecular mechanisms for such effects are not yet well understood. Because most alterations in cardiac function are associated with changes in sarcomeric machinery, the present work was undertaken to find novel sarcomeric hot spots driven by T3 in the heart. A microarray analysis indicated that the M-band is a major hot spot, and the structural sarcomeric gene coding for the M-protein is severely down-regulated by T3. Real-time quantitative PCR-based measurements confirmed that T3 (1, 5, 50, and 100 physiological doses for 2 days) sharply decreased the M-protein gene and protein expression in vivo in a dose-dependent manner. Furthermore, the M-protein gene expression was elevated 3.4-fold in hypothyroid rats. Accordingly, T3 was able to rapidly and strongly reduce the M-protein gene expression in neonatal cardiomyocytes. Deletions at the M-protein promoter and bioinformatics approach suggested an area responsive to T3, which was confirmed by chromatin immunoprecipitation assay. Functional assays in cultured neonatal cardiomyocytes revealed that depletion of M-protein (by small interfering RNA) drives a severe decrease in speed of contraction. Interestingly, mRNA and protein levels of other M-band components, myomesin and embryonic-heart myomesin, were not altered by T3. We concluded that the M-protein expression is strongly and rapidly repressed by T3 in cardiomyocytes, which represents an important aspect for the basis of T3-dependent sarcomeric deleterious effects in the heart.

A Low Consumption Real Time Environmental Monitoring System for Smart Cities based on ZigBee Wireless Sensor Network

Nowadays, there is an increasing interest in wireless sensor networks (WSN) for environmental monitoring systems because it can be used to improve the quality of life and living conditions are becoming a major concern to people. This paper describes the design and development of a real time monitoring system based on ZigBee WSN characterized by a lower energy consumption, low cost, reduced dimensions and fast adaptation to the network tree topology. The developed system encompasses an optimized sensing process about environmental parameters, low rate transmission from sensor nodes to the gateway, packet parsing and data storing in a remote database and real time visualization through a web server.

Architectures and design patterns for functional design of logic control and diagnostics in industrial automation

Recently in most of the industrial automation process an ever increasing degree of automation has been observed. This increasing is motivated by the higher requirement of systems with great performance in terms of quality of products/services generated, productivity, efficiency and low costs in the design, realization and maintenance. This trend in the growth of complex automation systems is rapidly spreading over automated manufacturing systems (AMS), where the integration of the mechanical and electronic technology, typical of the Mechatronics, is merging with other technologies such as Informatics and the communication networks. An AMS is a very complex system that can be thought constituted by a set of flexible working stations, one or more transportation systems. To understand how this machine are important in our society let considerate that every day most of us use bottles of water or soda, buy product in box like food or cigarets and so on. Another important consideration from its complexity derive from the fact that the the consortium of machine producers has estimated around 350 types of manufacturing machine. A large number of manufacturing machine industry are presented in Italy and notably packaging machine industry,in particular a great concentration of this kind of industry is located in Bologna area; for this reason the Bologna area is called “packaging valley”. Usually, the various parts of the AMS interact among them in a concurrent and asynchronous way, and coordinate the parts of the machine to obtain a desiderated overall behaviour is an hard task. Often, this is the case in large scale systems, organized in a modular and distributed manner. Even if the success of a modern AMS from a functional and behavioural point of view is still to attribute to the design choices operated in the definition of the mechanical structure and electrical electronic architecture, the system that governs the control of the plant is becoming crucial, because of the large number of duties associated to it. Apart from the activity inherent to the automation of themachine cycles, the supervisory system is called to perform other main functions such as: emulating the behaviour of traditional mechanical members thus allowing a drastic constructive simplification of the machine and a crucial functional flexibility; dynamically adapting the control strategies according to the different productive needs and to the different operational scenarios; obtaining a high quality of the final product through the verification of the correctness of the processing; addressing the operator devoted to themachine to promptly and carefully take the actions devoted to establish or restore the optimal operating conditions; managing in real time information on diagnostics, as a support of the maintenance operations of the machine. The kind of facilities that designers can directly find on themarket, in terms of software component libraries provides in fact an adequate support as regard the implementation of either top-level or bottom-level functionalities, typically pertaining to the domains of user-friendly HMIs, closed-loop regulation and motion control, fieldbus-based interconnection of remote smart devices. What is still lacking is a reference framework comprising a comprehensive set of highly reusable logic control components that, focussing on the cross-cutting functionalities characterizing the automation domain, may help the designers in the process of modelling and structuring their applications according to the specific needs. Historically, the design and verification process for complex automated industrial systems is performed in empirical way, without a clear distinction between functional and technological-implementation concepts and without a systematic method to organically deal with the complete system. Traditionally, in the field of analog and digital control design and verification through formal and simulation tools have been adopted since a long time ago, at least for multivariable and/or nonlinear controllers for complex time-driven dynamics as in the fields of vehicles, aircrafts, robots, electric drives and complex power electronics equipments. Moving to the field of logic control, typical for industrial manufacturing automation, the design and verification process is approached in a completely different way, usually very “unstructured”. No clear distinction between functions and implementations, between functional architectures and technological architectures and platforms is considered. Probably this difference is due to the different “dynamical framework”of logic control with respect to analog/digital control. As a matter of facts, in logic control discrete-events dynamics replace time-driven dynamics; hence most of the formal and mathematical tools of analog/digital control cannot be directly migrated to logic control to enlighten the distinction between functions and implementations. In addition, in the common view of application technicians, logic control design is strictly connected to the adopted implementation technology (relays in the past, software nowadays), leading again to a deep confusion among functional view and technological view. In Industrial automation software engineering, concepts as modularity, encapsulation, composability and reusability are strongly emphasized and profitably realized in the so-calledobject-oriented methodologies. Industrial automation is receiving lately this approach, as testified by some IEC standards IEC 611313, IEC 61499 which have been considered in commercial products only recently. On the other hand, in the scientific and technical literature many contributions have been already proposed to establish a suitable modelling framework for industrial automation. During last years it was possible to note a considerable growth in the exploitation of innovative concepts and technologies from ICT world in industrial automation systems. For what concerns the logic control design, Model Based Design (MBD) is being imported in industrial automation from software engineering field. Another key-point in industrial automated systems is the growth of requirements in terms of availability, reliability and safety for technological systems. In other words, the control system should not only deal with the nominal behaviour, but should also deal with other important duties, such as diagnosis and faults isolations, recovery and safety management. Indeed, together with high performance, in complex systems fault occurrences increase. This is a consequence of the fact that, as it typically occurs in reliable mechatronic systems, in complex systems such as AMS, together with reliable mechanical elements, an increasing number of electronic devices are also present, that are more vulnerable by their own nature. The diagnosis problem and the faults isolation in a generic dynamical system consists in the design of an elaboration unit that, appropriately processing the inputs and outputs of the dynamical system, is also capable of detecting incipient faults on the plant devices, reconfiguring the control system so as to guarantee satisfactory performance. The designer should be able to formally verify the product, certifying that, in its final implementation, it will perform itsrequired function guarantying the desired level of reliability and safety; the next step is that of preventing faults and eventually reconfiguring the control system so that faults are tolerated. On this topic an important improvement to formal verification of logic control, fault diagnosis and fault tolerant control results derive from Discrete Event Systems theory. The aimof this work is to define a design pattern and a control architecture to help the designer of control logic in industrial automated systems. The work starts with a brief discussion on main characteristics and description of industrial automated systems on Chapter 1. In Chapter 2 a survey on the state of the software engineering paradigm applied to industrial automation is discussed. Chapter 3 presentes a architecture for industrial automated systems based on the new concept of Generalized Actuator showing its benefits, while in Chapter 4 this architecture is refined using a novel entity, the Generalized Device in order to have a better reusability and modularity of the control logic. In Chapter 5 a new approach will be present based on Discrete Event Systems for the problemof software formal verification and an active fault tolerant control architecture using online diagnostic. Finally conclusive remarks and some ideas on new directions to explore are given. In Appendix A are briefly reported some concepts and results about Discrete Event Systems which should help the reader in understanding some crucial points in chapter 5; while in Appendix B an overview on the experimental testbed of the Laboratory of Automation of University of Bologna, is reported to validated the approach presented in chapter 3, chapter 4 and chapter 5. In Appendix C some components model used in chapter 5 for formal verification are reported.

Levels and determinants of inflammatory biomarkers in a Swiss population-based sample (CoLaus study)

Objective to assess the levels and determinants of interleukin (IL)-1β, IL-6, tumour necrosis factor (TNF)-α and C-reactive protein (CRP) in a healthy Caucasian population. Methods population sample of 2884 men and 3201 women aged 35 to 75. IL-1β, IL-6 and TNF-α were assessed by a multiplexed particle-based flow cytometric assay and CRP by an immunometric assay. Results Spearman rank correlations between duplicate cytokine measurements (N = 80) ranged between 0.89 and 0.96; intra-class correlation coefficients ranged between 0.94 and 0.97, indicating good reproducibility. Among the 6085 participants, 2289 (37.6%), 451 (7.4%) and 43 (0.7%) had IL-1β, IL-6 and TNF-α levels below detection limits, respectively. Median (interquartile range) for participants with detectable values were 1.17 (0.48–3.90) pg/ml for IL-1β; 1.47 (0.71–3.53) pg/ml for IL-6; 2.89 (1.82–4.53) pg/ml for TNF-α and 1.3 (0.6–2.7) ng/ml for CRP. On multivariate analysis, greater age was the only factor inversely associated with IL-1β levels. Male sex, increased BMI and smoking were associated with greater IL-6 levels, while no relationship was found for age and leisure-time PA. Male sex, greater age, increased BMI and current smoking were associated with greater TNF-α levels, while no relationship was found with leisure-time PA. CRP levels were positively related to age, BMI and smoking, and inversely to male sex and physical activity. Conclusion Population-based levels of several cytokines were established. Increased age and BMI, and to a lesser degree sex and smoking, significantly and differentially impact cytokine levels, while leisure-time physical activity has little effect.

IS711-based real-time PCR assay as a tool for detection of Brucella spp. in wild boars and comparison with bacterial isolation and serology

BACKGROUND: Control of brucellosis in livestock, wildlife and humans depends on the reliability of the methods used for detection and identification of bacteria. In the present study, we describe the evaluation of the recently established real-time PCR assay based on the Brucella-specific insertion sequence IS711 with blood samples from 199 wild boars (first group of animals) and tissue samples from 53 wild boars (second group of animals) collected in Switzerland. Results from IS711 real-time PCR were compared to those obtained by bacterial isolation, Rose Bengal Test (RBT), competitive ELISA (c-ELISA) and indirect ELISA (i-ELISA). RESULTS: In the first group of animals, IS711 real-time PCR detected infection in 11.1% (16/144) of wild boars that were serologically negative. Serological tests showed different sensitivities [RBT 15.6%, c-ELISA 7.5% and i-ELISA 5.5%] and only 2% of blood samples were positive with all three tests, which makes interpretation of the serological results very difficult. Regarding the second group of animals, the IS711 real-time PCR detected infection in 26% of animals, while Brucella spp. could be isolated from tissues of only 9.4% of the animals. CONCLUSION: The results presented here indicate that IS711 real-time PCR assay is a specific and sensitive tool for detection of Brucella spp. infections in wild boars. For this reason, we propose the employment of IS711 real-time PCR as a complementary tool in brucellosis screening programs and for confirmation of diagnosis in doubtful cases.

Development and Validation of a Symptom-Based Activity Index for Adults with Eosinophilic Esophagitis

BACKGROUND & Aims: Standardized instruments are needed to assess the activity of eosinophilic esophagitis (EoE), to provide endpoints for clinical trials and observational studies. We aimed to develop and validate a patient-reported outcome (PRO) instrument and score, based on items that could account for variations in patients' assessments of disease severity. We also evaluated relationships between patients' assessment of disease severity and EoE-associated endoscopic, histologic, and laboratory findings. METHODS We collected information from 186 patients with EoE in Switzerland and the US (69.4% male; median age, 43 years) via surveys (n = 135), focus groups (n = 27), and semi-structured interviews (n = 24). Items were generated for the instruments to assess biologic activity based on physician input. Linear regression was used to quantify the extent to which variations in patient-reported disease characteristics could account for variations in patients' assessment of EoE severity. The PRO instrument was prospectively used in 153 adult patients with EoE (72.5% male; median age, 38 years), and validated in an independent group of 120 patients with EoE (60.8% male; median age, 40.5 years). RESULTS Seven PRO factors that are used to assess characteristics of dysphagia, behavioral adaptations to living with dysphagia, and pain while swallowing accounted for 67% of the variation in patients' assessment of disease severity. Based on statistical consideration and patient input, a 7-day recall period was selected. Highly active EoE, based on endoscopic and histologic findings, was associated with an increase in patient-assessed disease severity. In the validation study, the mean difference between patient assessment of EoE severity and PRO score was 0.13 (on a scale from 0 to 10). CONCLUSIONS We developed and validated an EoE scoring system based on 7 PRO items that assesses symptoms over a 7-day recall period. Clinicaltrials.gov number: NCT00939263.