Time-Resolved Ultra–High Resolution Optical Coherence Tomography for Real-Time Monitoring of Selective Retina Therapy

Purpose: Selective retina therapy (SRT) is a novel treatment for retinal pathologies, solely targeting the retinal pigment epithelium (RPE). During SRT, the detection of an immediate tissue reaction is challenging as tissue effects remain limited to intracellular RPE photodisruption. Time-resolved ultra-high axial resolution optical coherence tomography (OCT) is thus evaluated for the monitoring of dynamic optical changes at and around the RPE during SRT. Methods: An experimental OCT system with an ultra-high axial resolution of 1.78 µm was combined with an SRT system and time-resolved OCT M-scans of the target area were recorded from four patients undergoing SRT. OCT scans were analyzed and OCT morphology was correlated with findings in fluorescein angiography, fundus photography and cross-sectional OCT. Results: In cases where the irradiation caused RPE damage proven by fluorescein angiography, the lesions were well discernible in time-resolved OCT images but remained invisible in fundus photography and cross-sectional OCT acquired after treatment. If RPE damage was introduced, all applied SRT pulses led to detectable signal changes in the time-resolved OCT images. The extent of optical signal variation seen in the OCT data appeared to scale with the applied SRT pulse energy. Conclusion: The first clinical results proved that successful SRT irradiation induces detectable changes in the OCT M-scan signal while it remains invisible in conventional ophthalmoscopic imaging. Thus, real-time high-resolution OCT is a promising modality to monitor and analyze tissue effects introduced by selective retina therapy and may be used to guide SRT in an automatic feedback mode.

All-sky Meteor Orbit System AMOS and preliminary analysis of three unusual meteor showers

All-sky Meteor Orbit System (AMOS) is a semi-autonomous video observatory for detection of transient events on the sky, mostly the meteors. Its hardware and software development and permanent placement on several locations in Slovakia allowed the establishment of Slovak Video Meteor Network (SVMN) monitoring meteor activity above the Central Europe. The data reduction, orbital determination and additional results from AMOS cameras–the SVMN database– as well as from observational expeditions on Canary Islands and in Canada provided dynamical and physical data for better understanding of mutual connections between parent bodies of asteroids and comets and their meteoroid streams. We present preliminary results on exceptional and rare meteor streams such as September ε Perseids (SPE) originated from unknown long periodic comet on a retrograde orbit, suspected asteroidal meteor stream of April α Comae Berenicids (ACO) in the orbit of meteorites Příbram and Neuschwanstein and newly observed meteor stream Camelopardalids (CAM) originated from Jupiter family comet 209P/Linear.

SMARTnet: First Experience of Setting Up a Telescope System to Survey the Geostationary Ring

Space debris in geostationary orbits may be detected with optical telescopes when the objects are illuminated by the Sun. The advantage compared to Radar can be found in the illumination: radar illuminates the objects and thus the detection sensitivity depletest proportional to the fourth power of the d istance. The German Space Operation Center, GSOC, together with the Astronomical Institute of the University of Bern, AIUB, are setting up a telescope system called SMARTnet to demonstrate the capability of performing geostationary surveillance. Such a telescope system will consist of two telescopes on one mount: a smaller telescope with an aperture of 20cm will serve for fast survey while the larger one, a telescope with an aperture of 50cm, will be used for follow-up observations. The telescopes will be operated by GSOC from Oberpfaffenhofen by the internal monitoring and control system called SMARTnetMAC. The observation plan will be generated by MARTnetPlanning seven days in advance by applying an optimized planning scheduler, taking into account fault time like cloudy nights, priority of objects etc. From each picture taken, stars will be identified and everything not being a star is treated as a possible object. If the same object can be identified on multiple pictures within a short time span, the trace is called a tracklet. In the next step, several tracklets will be correlated to identify individual objects, ephemeris data for these objects are generated and catalogued . This will allow for services like collision avoidance to ensure safe operations for GSOC’s satellites. The complete data processing chain is handled by BACARDI, the backbone catalogue of relational debris information and is presented as a poster.

Accuracy of continuous glucose monitoring during differing exercise conditions.

AIM Depending on intensity, exercise may induce a strong hormonal and metabolic response, including acid-base imbalances and changes in microcirculation, potentially interfering with the accuracy of continuous glucose monitoring (CGM). The present study aimed at comparing the accuracy of the Dexcom G4 Platinum (DG4P) CGM during continuous moderate and intermittent high-intensity exercise (IHE) in adults with type 1 diabetes (T1DM). METHODS Ten male individuals with well-controlled T1DM (HbA1c 7.0±0.6% [54±6mmol/mol]) inserted the DG4P sensor 2 days prior to a 90min cycling session (50% VO2peak) either with (IHE) or without (CONT) a 10s all-out sprint every 10min. Venous blood samples for reference glucose measurement were drawn every 10min and euglycemia (target 7mmol/l) was maintained using an oral glucose solution. Additionally, lactate and venous blood gas variables were determined. RESULTS Mean reference blood glucose was 7.6±0.2mmol/l during IHE and 6.7±0.2mmol/l during CONT (p<0.001). IHE resulted in significantly higher levels of lactate (7.3±0.5mmol/l vs. 2.6±0.3mmol/l, p<0.001), while pH values were significantly lower in the IHE group (7.27 vs. 7.38, p=0.001). Mean absolute relative difference (MARD) was 13.3±2.2% for IHE and 13.6±2.8% for CONT suggesting comparable accuracy (p=0.90). Using Clarke Error Grid Analysis, 100% of CGM values during both IHE and CONT were in zones A and B (IHE: 77% and 23%; CONT: 78% and 22%). CONCLUSIONS The present study revealed good and comparable accuracy of the DG4P CGM system during intermittent high intensity and continuous moderate intensity exercise, despite marked differences in metabolic conditions. This corroborates the clinical robustness of CGM under differing exercise conditions. CLINICAL TRIAL REGISTRATION NUMBER ClinicalTrials.gov NCT02068638.

A simulation study on the statistical monitoring of condemnation rates from slaughterhouses for syndromic surveillance: an evaluation based on Swiss data

Syndromic surveillance (SyS) systems currently exploit various sources of health-related data, most of which are collected for purposes other than surveillance (e.g. economic). Several European SyS systems use data collected during meat inspection for syndromic surveillance of animal health, as some diseases may be more easily detected post-mortem than at their point of origin or during the ante-mortem inspection upon arrival at the slaughterhouse. In this paper we use simulation to evaluate the performance of a quasi-Poisson regression (also known as an improved Farrington) algorithm for the detection of disease outbreaks during post-mortem inspection of slaughtered animals. When parameterizing the algorithm based on the retrospective analyses of 6 years of historic data, the probability of detection was satisfactory for large (range 83-445 cases) outbreaks but poor for small (range 20-177 cases) outbreaks. Varying the amount of historical data used to fit the algorithm can help increasing the probability of detection for small outbreaks. However, while the use of a 0·975 quantile generated a low false-positive rate, in most cases, more than 50% of outbreak cases had already occurred at the time of detection. High variance observed in the whole carcass condemnations time-series, and lack of flexibility in terms of the temporal distribution of simulated outbreaks resulting from low reporting frequency (monthly), constitute major challenges for early detection of outbreaks in the livestock population based on meat inspection data. Reporting frequency should be increased in the future to improve timeliness of the SyS system while increased sensitivity may be achieved by integrating meat inspection data into a multivariate system simultaneously evaluating multiple sources of data on livestock health.