P035 Potential biomarkers for diagnosis through proteomics, in patients with Inflammatory Bowel Disease

Background Currently,endoscopy,an invasive medical procedure, is the gold standard for diagnosis of inflammatory bowel disease (IBD) and to determine mucosal activity.Our main goal was to identify biomarkers in saliva samples that can be used as a screening tool for the diagnosis of ulcerative colitis(UC) and Crohn`s disease(CD). Methods 100 saliva samples were collected from: healthy individuals(20), UC-active stage(10),UC-remission stage(31),CD-active stage(7) and CD-remission stage(32) patients. The samples were thawed on ice and centrifugated at 10,000g for 15 min at 4ºC.The supernatants were aliquoted and stored at -80ºC. The protein extracts were digested with trypsin and peptides resulting from digestion were loaded onto a nano Acquity UPLC chromatograph and analysed in a nano Elute coupled on-line to a timsTOF Pro(Bruker).The data obtained was then processed and loaded onto the Progenesis LC-MS software (Nonlinear Dynamics) for Orbitrap data and PEAKS(Bioinformatics Solutions Inc.) for timsTOF Pro data. Finally, this information was converted to deregulation patterns at protein level and relative quantification was done. Saliva protein levels were compared between healthy (always as control) and CD remission,UC remission,UC active and CD active stages respectively.The identification of potential biomarkers was carried out with classical statistic methods(p value<0,05 and ratio> 1,5) and data Mining mathematical model(p-value<0,05, balanced accuracy ≥ 70, sensitivity ≥ 60 and specificity ≥ 60). Results We have chosen the most relevant classifiers according to statistical and biological criteria, based on their biological function and the pathogenesis of UC or CD(figure 1). We have identified 152 classifiers(biomarkers),118 single and 34 dual, defined by one or two proteins of a list of 135 proteins(table 1).The classifiers are shown for each cohort compared to healthy control:42 biomarkers were found in Active UC,16 in Remission UC, 99 in Active CD and 13 in Remission CD,all of them compared to healthy controls. Conclusion Multiple potential biomarkers have been identified in saliva in relation to IBD. Biomarkers with significant value have been found for identifying and classifying UC as well as CD, compared to controls.The number of biomarkers found in CD has been higher than in UC. The simple biomarker option(versus dual) is recommended,since its application involves fewer errors.

Condition Monitoring of Wind Turbine Drivetrain Bearings

The current pace of renewable energy development around the world is unprecedented, with offshore wind in particular proving to be an extremely valuable and reliable energy source. The global installed capacity of offshore wind turbines by the end of 2022 is expected to reach the 46.4 GW, among which 33.9 GW in Europe. Costs are critical for the future success of the offshore wind sector. The industry is pushing hard to make cost reductions to show that offshore wind is economically comparable to conventional fossil fuels. Efficiencies in Operations and Maintenance (O&M) offer potential to achieve significant cost savings as it accounts for around 20%–30% of overall offshore wind farm costs. One of the most critical and rather complex assembly of onshore, offshore and floating wind turbines is the gearbox. Gearboxes are designed to last till the end of the lifetime of the asset, according to the IEC 61400-4 standards. On the other hand, a recent study over approximately 350 offshore wind turbines indicate that gearboxes might have to be replaced as early as 6.5 years. Therefore sensing and condition monitoring systems for onshore, offshore and floating wind turbines are needed in order to obtain reliable information on the state and condition of different critical parts, focusing towards the detection and/or prediction of damage before it reaches a critical stage. The development and use of such technologies will allow companies to schedule actions at the right time, and thus will help reducing the costs of operation and maintenance, resulting in an increase of wind energy at a competitive price and thus strengthening productivity of the wind energy sector. At the academic level a plethora of methodologies have been proposed during the last decades for the analysis of vibration signatures focusing towards early and accurate fault detection with limited false alarms and missed detections. Among others, Envelope Analysis is one of the most important methodologies, where an envelope of the vibration signal is estimated, usually after filtering around a selected frequency band excited by impacts due to the faults. Different tools, such as Kurtogram, have been proposed in order to accurately select the optimum filter parameters (center frequency and bandwidth). Cyclostationary Analysis and corresponding methodologies, i.e. the Cyclic Spectral Correlation and the Cyclic Spectral Coherence, have been proved as powerful tools for condition monitoring. On the other hand the application, test and evaluation of such tools on general industrial cases is still rather limited. Therefore the main aim of this paper is the application and evaluation of advanced diagnostic techniques and diagnostic indicators, including the Enhanced Envelope Spectrum and the Spectral Flatness on real world vibration data collected from vibration sensors on gearboxes in multiple wind turbines over an extended period of time of nearly four years. The diagnostic indicators are compared with classical statistic time and frequency indicators, i.e. Kurtosis, Crest Factor etc. and their effectiveness is evaluated based on the successful detection of two failure events.

Notification as a mean to increase user activity in newborn online communities.

There is a considerable challenge in getting online communities of the ground; founders of such platforms employ many strategies to manage this issue and go over the tipping point; this study examines the influence of notifications on user activity in general, and in context of admin activity. An online platform for co-creation of playlists called Echo was studied; Both classical statistic and network analysis was employed in order to establish the relationship between these variables and the structure of the network. A weak to moderate relationship was found, while the main carriers of activity were admin users, as key carriers of user engagement in the early days of Echo.

Multi-Spectral Techniques Applied for the Measurement of the Microscale Temperature Through Cooled Multiplier Tube in Photon Counting Mode

The aim of this paper is to present a non-intrusive and optical method based on the classical thermal radiation laws for the measurement of microscale surface temperature. To overcome the diffraction limit, measurements are performed in the ultraviolet-visible range. According to the Planck’s law, emitting energy is low at these wavelengths and only a photonic flux can be measured through a cooled Photo-Multiplier Tube (PMT) and a photon-counting card. The photonic flux exhibits a random phenomenon that can be well-described through classical statistic laws such as Poisson or Normal distributions. We show in this paper that the signal we measure agrees well with these laws and that the surface temperature can be obtained either from the average or the standard-deviation of the Photonic flux. Multi-spectral techniques based on either physical and optical techniques like monochromatic filters and reflection/transmission diffraction gratings or digital techniques as a Multi-Channel Analyser (MCA) are proposed to get ride of the knowledge of the local surface emissivity. This is of a particular interest for the measurement of temperature in microscale applications. Finally, temperature measurements carried out on a specific High Temperature Blackbody developed in our laboratory are compared with those obtained through an infrared camera and allow to validate our facility and the presented measurement techniques.

Geostatistics as a tool to improve sampling and statistical analysis in wetlands: a case sudy on dynamics of organic matter distribution in the Pantanal of Mato Grosso, Brazil

The Pantanal of Mato Grosso presents distinct landscape units: permanently, occasionally and periodically flooded areas. In the last ones, sampling is especially difficult due to the high heterogeneity occurring inter and intrastratas. This paper presents a comparison of different methodological approaches showing that they can influence decisively the knowledge of distribution organic matter dynamics. In such an area in order to understand the role of the flood pulse in the distribution dynamics of organic matter in a wetland at the Pantanal, we considered that there is spatial dependence between points. This consideration contradicts the classical statistic principle that focuses on the aleatority, and allowed the obtainment of a larger volume of information from a minor sampling effort, which means better performance, with time and money economy.