Postponing intubation in spontaneously breathing major trauma patients upon emergency room admission does not impair outcome

Background Pre-hospital emergency anaesthesia and tracheal intubation are life-saving interventions in trauma patients. However, there is evidence suggesting that the risks associated with both procedures outweigh the benefits. Thus, we assessed whether induction of anaesthesia and tracheal intubation of trauma patients can be postponed in spontaneously breathing patients until emergency room (ER) admission without increasing mortality. Methods Retrospective analysis of major trauma patients either intubated on-scene by an emergency medical service (EMS) physician (pre-hospital intubation, PHI) or within the first 10 min after admission at a level 1 trauma centre (emergency room intubation, ERI). Data was extracted from the German Trauma Registry, hospital patient data management and electronic clinical information system. Results From a total of 946 major trauma cases documented between 2010 and 2017, 294 patients matched the study inclusion criteria. Mortality rate of PHI (N = 258) vs. ERI (N = 36) patients was 26.4% vs. 16.7% (p = 0.3). After exclusion of patients with severe traumatic brain injury and/or pre-hospital cardiac arrest, mortality rate of PHI (N = 100) vs. ERI patients (N = 29) was 6% vs. 17.2%, (p = 0.07). Median on-scene time was significantly (p < 0.01) longer in PHI (30 min; IQR: 21–40) vs. ERI patients (20 min; IQR: 15–28). Conclusions There was no statistical difference in mortality rates of spontaneously breathing trauma patients intubated on-scene when compared with patients intubated immediately after hospital admission. Due to the retrospective study design and small case number, further studies evaluating the impact of airway management timing in sufficiently breathing trauma patients are warranted.publishedVersio

Shedding of Mycobacterium caprae by wild red deer (Cervus elaphus) in the Bavarian alpine regions, Germany

The number of natural infections with Mycobacterium caprae in wildlife and in cattle in the Bavarian and Austrian alpine regions has increased over the last decade. Red deer (Cervus elaphus) have been recognized as maintenance reservoir; however, the transmission routes of M. caprae among and from naturally infected red deer are unknown. The unexpected high prevalence in some hot spot regions might suggest an effective indirect transmission of infection. Therefore, this study was undertaken to diagnose the occurrence of M. caprae in faeces and secretions of red deer in their natural habitat. A total of 2,806 red deer hunted in this region during 2014–2016 were included in this study. After pathological examination, organs (lymph nodes, lung, heart), excretions and secretions (faeces, urine, saliva and tonsil swabs) were further investigated by qPCR specific for Mycobacterium tuberculosis complex (MTC), M. bovis and M. caprae. Samples tested positive by qPCR were processed for culturing of mycobacteria. In total, 55 (2.0%) animals were confirmed positive for M. caprae by pathological examination, PCR and culturing of the affected organ material. With the exception of one sample, all of the secretion and excretion samples were negative for mycobacteria of the Mycobacterium tuberculosis complex (MTC). From one red deer, M. caprae could be isolated from the heart sac as well as from the faeces. Whole‐genome sequencing confirmed that both strains were clonally related. This is the first confirmation that M. caprae can be shed with the faeces of a naturally infected red deer. However, further studies focusing on a higher number of infected animals, sample standardization and coordinated multiple sampling are necessary to improve the understanding of transmission routes under natural conditions

Detection Methods for Autoantibodies in Suspected Autoimmune Encephalitis

This review provides an overview on different antibody test methods that can be applied in cases of suspected paraneoplastic neurological syndromes (PNS) and anti-neuronal autoimmune encephalitis (AIE) in order to explain their diagnostic value, describe potential pitfalls and limitations, and discuss novel approaches aimed at discovering further autoantibodies. Onconeuronal antibodies are well-established biomarkers for PNS and may serve as specific tumor markers. The recommended procedure to detect onconeuronal antibodies is a combination of indirect immunohistochemistry on fixed rodent cerebellum and confirmation of the specificity by line assays. Simplification of this approach by only using line assays with recombinant proteins bears the risk to miss antibody-positive samples. Anti-neuronal surface antibodies are sensitive and specific biomarkers for AIE. Their identification requires the use of test methods that allow the recognition of conformation dependent epitopes. These commonly include cell-based assays and tissue based assays with unfixed rodent brain tissue. Tissue based assays can detect most of the currently known neuronal surface antibodies and thus enable broad screening of biological samples. A complementary testing on live neuronal cell cultures may confirm that the antibody recognizes a surface epitope. In patients with peripheral neuropathy, the screening may be expanded to teased nerve fibers to identify antibodies against the node of Ranvier. This method helps to identify a novel subgroup of peripheral autoimmune neuropathies, resulting in improved immunotherapy of these patients. Tissue based assays are useful to discover additional autoantibody targets that play a role in diverse autoimmune neurological syndromes. Antibody screening assays represent promising avenues of research to improve the diagnostic yield of current assays for antibody-associated autoimmune encephalitis

Regensburger Land. Der Landkreis Regensburg in Geschichte und Gegenwart 2 (2009)

Die Schriftenreihe „Regensburger Land. Der Landkreis Regensburg in Geschichte und Gegenwart“ soll im Stile eines Almanachs möglichst jährlich mit einem Band erscheinen und informative Beiträge zur regionalen Geschichte und Kultur enthalten. Ansprechend aufgemacht und reich bebildert, ist sie an eine breite Leserschaft gerichtet

Land Cover Classification of Landsat Images Using Problem-Adapted Artificial Neural Networks

Artificial Neural Networks (ANN) have gained increasing popularity as an alternative to statistical methods for classification of Remote Sensing Data. Their superiority to some of the classical statistical methods has been shown in the literature. Therefore, ANNs are commonly used for segmentation and classification purposes. In this paper we address a land cover classification problem using multi--spectral Landsat Thematic Mapper (TM) data employing ANNs. We concentrate on the search for the problem--adapted network topology and the appropriate number of training epochs for Multi--Layer Feed--Forward ANNs. To prevent the ANN from overfitting the number of training epochs is essential. For the automatic generation of problem--adapted topologies a method based on Genetic Algorithms (GA) is employed. With this approach populations of ANNs are generated, trained, and evaluated for the land--cover classification task. Individuals which solve the given task well receive a high fitness value..