Search

AIMS COVID-19 has had enormous consequences on global health care and resulted in millions of fatalities. The exact mechanism and site of SARS-CoV-2 entry into the body remains insufficiently understood. Recently, novel virus receptors were identified, and alveolar macrophages were suggested as a potential viral entry cell type and vector for intra-alveolar virus transmission. Here, we investigated the protein expression of ten well-known and novel virus entry molecules along potential entry sites in humans using immunohistochemistry. METHODS AND RESULTS Samples of different anatomic sites from up to 93 patients were incorporated into tissue microarrays. Protein expression of ACE2, TMPRSS2, furin, CD147, C-type lectin receptors (CD169, CD209, CD299), neuropilin-1, ASGR1 and KREMEN1 were analyzed. In lung tissues, at least one of the three receptors ACE2, ASGR1 or KREMEN1 was expressed in the majority of cases. Moreover, all of the investigated molecules were found to be expressed in alveolar macrophages, and colocalization with SARS-CoV-2 N-protein was demonstrated using dual immunohistochemistry in lung tissue from a COVID-19 autopsy. While CD169 and CD209 showed consistent protein expression in sinonasal, conjunctival and bronchiolar tissues, neuropilin-1 and ASGR1 were mostly absent, suggesting a minor relevance of these two molecules at these specific sites. CONCLUSION Our results extend recent discoveries indicating a role for these molecules in virus entry at different anatomic sites. Moreover, they support the notion of alveolar macrophages being a potential entry cell for SARS-CoV-2.

Postural instability as a symptom of progressing Parkinson's disease (PD) greatly reduces quality of life. Hence, early detection of postural impairments is crucial to facilitate interventions. Our aim was to use a convolutional neural network (CNN) to differentiate people with early to mid-stage PD from healthy age-matched individuals based on spectrogram images obtained from their body movement. We hypothesized the time-frequency content of body sway to be predictive of PD, even when impairments are not yet manifested in day-to-day postural control. We tracked their center of pressure (COP) using a Wii Balance Board and their full-body motion using a Microsoft Kinect, out of which we calculated the trajectory of their center of mass (COM). We used 30 s-snippets of motion data from which we acquired wavelet-based time-frequency spectrograms that were fed into a custom-built CNN as labeled images. We used binary classification to have the network differentiate between individuals with PD and controls (n=15, respectively). Classification performance was best when the medio-lateral motion of the COM was considered. Here, our network reached an average predictive accuracy of 98.45 % with a receiver operating characteristic area under the curve of 1.0. Moreover, an explainable AI approach revealed high frequencies in the postural sway data to be most distinct between both groups. Our findings suggest a CNN classifier based on cost-effective and conveniently obtainable posturographic data to be a promising approach to detect postural impairments in early to mid-stage PD and to gain novel insight into the subtle characteristics of impairments at this stage of the disease.

The integration of Artificial Intelligence (AI) and Digital Pathology has been increasing over the past years. Nowadays, applications of deep learning (DL) methods to diagnose cancer from whole-slide images (WSI) are, more than ever, a reality within different research groups. Nonetheless, the development of these systems was limited by a myriad of constraints regarding the lack of training samples, the scaling difficulties, the opaqueness of DL methods, and, more importantly, the lack of clinical validation. As such, we propose a system designed specifically for the diagnosis of colorectal samples. The construction of such a system consisted of four stages: (1) a careful data collection and annotation process, which resulted in one of the largest WSI colorectal samples datasets; (2) the design of an interpretable mixed-supervision scheme to leverage the domain knowledge introduced by pathologists through spatial annotations; (3) the development of an effective sampling approach based on the expected severeness of each tile, which decreased the computation cost by a factor of almost 6x; (4) the creation of a prototype that integrates the full set of features of the model to be evaluated in clinical practice. During these stages, the proposed method was evaluated in four separate test sets, two of them are external and completely independent. On the largest of those sets, the proposed approach achieved an accuracy of 93.44%. DL for colorectal samples is a few steps closer to stop being research exclusive and to become fully integrated in clinical practice., Under Review

Im Gegensatz zu konventionellen Röntgenaufnahmen, wo nur Einzelbilder aufgenommen werden, ermöglicht Durchleuchtung die Beobachtung von Prozessen. Diese Methode wird bei einer Vielzahl von medizinischen Untersuchungen angewandt und kann sowohl durch kontinuierliche oder gepulste Strahlenexposition realisiert werden. Die Verwendung von gepulster Strahlung führt zu einer Reduktion der Patientendosis, schafft allerdings Probleme für Messgeräte dieser Strahlung. Die meisten der eingesetzten Messgeräte sind für kontinuierliche Strahlenfelder optimiert. Dementsprechend können Probleme bei der Messung von gepulsten Strahlenfelder auftauchen, was im schlimmsten Fall zu einer Unterschätzung der Strahlendosis führen kann. Obwohl Paper zu diesem Thema existieren beziehen sich bisherige Studien nur auf eine geringe Anzahl an Messgeräten, die nicht in Österreich eingesetzt werden. Diese Arbeit untersucht Messgeräte, die in Österreich eichfähig sind und dementsprechend weitläufig eingesetzt werden. Das Ziel dieser Arbeit ist die Überprüfung der Funktion verschiedener Messgeräte im gepulsten Strahlungsfeld eines C-Bogens. Basierend auf den Resultaten werden Empfehlungen für die Nutzer dieser Geräte gegeben, was zu einem besseren Strahlenschutz für Personen führen soll, die in gepulsten Strahlenfeldern medizinischer Anwendungen arbeiten., In contrast to conventional X-ray imaging, where only single images are taken, fluoroscopy enables the observation of dynamic processes. This method is used in a variety of medical examinations and can either be realised via continuous or pulsed ionising radiation. The use of pulsed radiation determines a reduction of dose for the patient but generates challenges for measurement devices. The majority of currently used devices are optimised for the use in continuous radiation fields. Therefore, difficulties can arise when measuring pulsed radiation, which in the worst case can lead to an underestimation of radiation dose. Although papers addressing this issue do exist, quantitative studies have only been done for a small number of devices of which the majority is not used in Austria. This thesis examines devices, which can be officially calibrated in Austria and are therefore in broad use. The aim of this thesis is to review the function of various measurement devices in the pulsed radiation field of a C-arm. Based on these results recommendations for the operators of such devices are formulated, which shall lead to an improved radiation protection of people working with pulsed ionising radiation in medical applications.

OBJECTIVES Quality of life, fundamental to the individual patient, has shown a lack of correlation with severity in research on several diseases. Thus, we aimed to identify factors associated with quality of life in patients with primary sclerosing cholangitis. METHODS The Short Form Health Survey and the Patient Health Questionnaire were used to assess quality of life and depression. Complete data sets of 113 patients were analyzed for correlation with sex, age, presence of concomitant inflammatory bowel disease and dominant stenosis, frequency of pruritus, and Mayo Risk Score. RESULTS Physical functioning decreased with age (P