Temporal evolution of strut light intensity after implantation of bioresorbable polymeric intracoronary scaffolds in the ABSORB cohort B trial-an application of a new quantitative method based on optical coherence tomography.

BACKGROUND Quantitative light intensity analysis of the strut core by optical coherence tomography (OCT) may enable assessment of changes in the light reflectivity of the bioresorbable polymeric scaffold from polymer to provisional matrix and connective tissues, with full disappearance and integration of the scaffold into the vessel wall. The aim of this report was to describe the methodology and to apply it to serial human OCT images post procedure and at 6, 12, 24 and 36 months in the ABSORB cohort B trial. METHODS AND RESULTS In serial frequency-domain OCT pullbacks, corresponding struts at different time points were identified by 3-dimensional foldout view. The peak and median values of light intensity were measured in the strut core by dedicated software. A total of 303 corresponding struts were serially analyzed at 3 time points. In the sequential analysis, peak light intensity increased gradually in the first 24 months after implantation and reached a plateau (relative difference with respect to baseline [%Dif]: 61.4% at 12 months, 115.0% at 24 months, 110.7% at 36 months), while the median intensity kept increasing at 36 months (%Dif: 14.3% at 12 months, 75.0% at 24 months, 93.1% at 36 months). CONCLUSIONS Quantitative light intensity analysis by OCT was capable of detecting subtle changes in the bioresorbable strut appearance over time, and could be used to monitor the bioresorption and integration process of polylactide struts.

The structural substrate of brain function: analysis of brain structural networks based on diffusion-weighted imaging

The brain is a complex neural network with a hierarchical organization and the mapping of its elements and connections is an important step towards the understanding of its function. Recent developments in diffusion-weighted imaging have provided the opportunity to reconstruct the whole-brain structural network in-vivo at a large scale level and to study the brain structural substrate in a framework that is close to the current understanding of brain function. However, methods to construct the connectome are still under development and they should be carefully evaluated. To this end, the first two studies included in my thesis aimed at improving the analytical tools specific to the methodology of brain structural networks. The first of these papers assessed the repeatability of the most common global and local network metrics used in literature to characterize the connectome, while in the second paper the validity of further metrics based on the concept of communicability was evaluated. Communicability is a broader measure of connectivity which accounts also for parallel and indirect connections. These additional paths may be important for reorganizational mechanisms in the presence of lesions as well as to enhance integration in the network. These studies showed good to excellent repeatability of global network metrics when the same methodological pipeline was applied, but more variability was detected when considering local network metrics or when using different thresholding strategies. In addition, communicability metrics have been found to add some insight into the integration properties of the network by detecting subsets of nodes that were highly interconnected or vulnerable to lesions. The other two studies used methods based on diffusion-weighted imaging to obtain knowledge concerning the relationship between functional and structural connectivity and about the etiology of schizophrenia. The third study integrated functional oscillations measured using electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) as well as diffusion-weighted imaging data. The multimodal approach that was applied revealed a positive relationship between individual fluctuations of the EEG alpha-frequency and diffusion properties of specific connections of two resting-state networks. Finally, in the fourth study diffusion-weighted imaging was used to probe for a relationship between the underlying white matter tissue structure and season of birth in schizophrenia patients. The results are in line with the neurodevelopmental hypothesis of early pathological mechanisms as the origin of schizophrenia. The different analytical approaches selected in these studies also provide arguments for discussion of the current limitations in the analysis of brain structural networks. To sum up, the first studies presented in this thesis illustrated the potential of brain structural network analysis to provide useful information on features of brain functional segregation and integration using reliable network metrics. In the other two studies alternative approaches were presented. The common discussion of the four studies enabled us to highlight the benefits and possibilities for the analysis of the connectome as well as some current limitations.

"Mir hei e Verein, i ghöre drzue" - Vereine in der Welterbe-Region

Clubs and societies offer a space for fun and games, sports, and cultural activities. But they do far more than that. They are important places of social identity building. By bringing different people together, they foster social cohesion and integration. And last but not least, they contribute to democratic culture. What kinds of associations exist in and around the Swiss Alps Jungfrau-Aletsch UNESCO World Heritage site, and what do they do?

Real-Time Localization Using Software Defined Radio

Service providers make use of cost-effective wireless solutions to identify, localize, and possibly track users using their carried MDs to support added services, such as geo-advertisement, security, and management. Indoor and outdoor hotspot areas play a significant role for such services. However, GPS does not work in many of these areas. To solve this problem, service providers leverage available indoor radio technologies, such as WiFi, GSM, and LTE, to identify and localize users. We focus our research on passive services provided by third parties, which are responsible for (i) data acquisition and (ii) processing, and network-based services, where (i) and (ii) are done inside the serving network. For better understanding of parameters that affect indoor localization, we investigate several factors that affect indoor signal propagation for both Bluetooth and WiFi technologies. For GSM-based passive services, we developed first a data acquisition module: a GSM receiver that can overhear GSM uplink messages transmitted by MDs while being invisible. A set of optimizations were made for the receiver components to support wideband capturing of the GSM spectrum while operating in real-time. Processing the wide-spectrum of the GSM is possible using a proposed distributed processing approach over an IP network. Then, to overcome the lack of information about tracked devices’ radio settings, we developed two novel localization algorithms that rely on proximity-based solutions to estimate in real environments devices’ locations. Given the challenging indoor environment on radio signals, such as NLOS reception and multipath propagation, we developed an original algorithm to detect and remove contaminated radio signals before being fed to the localization algorithm. To improve the localization algorithm, we extended our work with a hybrid based approach that uses both WiFi and GSM interfaces to localize users. For network-based services, we used a software implementation of a LTE base station to develop our algorithms, which characterize the indoor environment before applying the localization algorithm. Experiments were conducted without any special hardware, any prior knowledge of the indoor layout or any offline calibration of the system.

Real-time localization using software defined radio

Service providers make use of cost-effective wireless solutions to identify, localize, and possibly track users using their carried MDs to support added services, such as geo-advertisement, security, and management. Indoor and outdoor hotspot areas play a significant role for such services. However, GPS does not work in many of these areas. To solve this problem, service providers leverage available indoor radio technologies, such as WiFi, GSM, and LTE, to identify and localize users. We focus our research on passive services provided by third parties, which are responsible for (i) data acquisition and (ii) processing, and network-based services, where (i) and (ii) are done inside the serving network. For better understanding of parameters that affect indoor localization, we investigate several factors that affect indoor signal propagation for both Bluetooth and WiFi technologies. For GSM-based passive services, we developed first a data acquisition module: a GSM receiver that can overhear GSM uplink messages transmitted by MDs while being invisible. A set of optimizations were made for the receiver components to support wideband capturing of the GSM spectrum while operating in real-time. Processing the wide-spectrum of the GSM is possible using a proposed distributed processing approach over an IP network. Then, to overcome the lack of information about tracked devices’ radio settings, we developed two novel localization algorithms that rely on proximity-based solutions to estimate in real environments devices’ locations. Given the challenging indoor environment on radio signals, such as NLOS reception and multipath propagation, we developed an original algorithm to detect and remove contaminated radio signals before being fed to the localization algorithm. To improve the localization algorithm, we extended our work with a hybrid based approach that uses both WiFi and GSM interfaces to localize users. For network-based services, we used a software implementation of a LTE base station to develop our algorithms, which characterize the indoor environment before applying the localization algorithm. Experiments were conducted without any special hardware, any prior knowledge of the indoor layout or any offline calibration of the system.

Increased levels of choline metabolites are an early marker of docetaxel treatment response in BRCA1-mutated mouse mammary tumors: an assessment by ex vivo proton magnetic resonance spectroscopy.

BACKGROUND Docetaxel is one of the most frequently used drugs to treat breast cancer. However, resistance or incomplete response to docetaxel is a major challenge. The aim of this study was to utilize MR metabolomics to identify potential biomarkers of docetaxel resistance in a mouse model for BRCA1-mutated breast cancer. METHODOLOGY High resolution magic angle spinning (HRMAS) (1)H MR spectroscopy was performed on tissue samples obtained from docetaxel-sensitive or -resistant BRCA1-mutated mammary tumors in mice. Measurements were performed on samples obtained before treatment and at 1-2, 3-5 and 6-7 days after a 25 mg/kg dose of docetaxel. The MR spectra were analyzed by multivariate analysis, followed by analysis of the signals of individual compounds by peak fitting and integration with normalization to the integral of the creatine signal and of all signals between 2.9 and 3.6 ppm. RESULTS The HRMAS spectra revealed significant metabolic differences between sensitive and resistant tissue samples. In particular choline metabolites were higher in resistant tumors by more than 50% with respect to creatine and by more than 30% with respect to all signals between 2.9 and 3.6 ppm. Shortly after treatment (1-2 days) the normalized choline metabolite levels were significantly increased by more than 30% in the sensitive group coinciding with the time of highest apoptotic activity induced by docetaxel. Thereafter, choline metabolites in these tumors returned towards pre-treatment levels. No change in choline compounds was observed in the resistant tumors over the whole time of investigation. CONCLUSIONS Relative tissue concentrations of choline compounds are higher in docetaxel resistant than in sensitive BRCA1-mutated mouse mammary tumors, but in the first days after docetaxel treatment only in the sensitive tumors an increase of these compounds is observed. Thus both pre- and post-treatment tissue levels of choline compounds have potential to predict response to docetaxel treatment.