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Automated acoustic monitoring methods are frequently used to survey bat activity around wind turbines. The algorithms are often based on spectral features or threshold values of the recordings. Due to the generality of these features, a lot of recordings are noise, making manual analysis and labelling of the recordings time consuming. In this paper, we present an approach based on convolutional neural networks to detect and classify bat calls respectively. Recordings are converted to Mel-frequency cepstral coefficients (MFCCs), which are then fed as an image into the convolutional neural networks (CNNs) for classification. A dataset consisting of 43585 recordings gathered at 5 m height was used to train and test this method. An accuracy of 99.7% was achieved on a test set for the binary classification of noise and bat calls. For the species classification, this approach achieved an accuracy of 96%. Both networks, trained on data gathered at 5 m, were also tested on recordings gathered at heights of 33 m, 65 m and 95 m. In case of the binary classification task, the results showed an increased rate of misclassifications among noise recordings. For species classification, there was a higher amount of misclassifcations among all species. [ABSTRACT FROM AUTHOR]

Towards the establishment of a long-term lung-assist device to be used both as a bridge and as an alternative to lung transplantation according to final destination therapy, we develop the biohybrid lung (BHL) on the technical basis of contemporary extracorporeal membrane oxygenation (ECMO). Here, to overcome the significant drawbacks of ECMO, in particular the missing hemocompatibility of the artificial surfaces, all blood-contacting areas need to be endothelialized sufficiently. In continuation of our recent accomplishments, demonstrating the feasibility of establishing a physiological acting endothelial cell (EC) monolayer on the hollow fiber membranes (HFMs) of the ECMO in vitro, the next step towards BHL translation is the endothelialization of the complete oxygenator, consisting of HFMs and the surrounding housing. Therefore, we assessed EC seeding inside our model oxygenator (MOx), which simulated the conditions in the assembled HFM oxygenators in order to identify the most important factors influencing efficient endothelialization, such as cell seeding density, cell distribution, incubation time and culture medium consumption. Overall, upon adjusting the concentration of infused ECs to 15.2 × 10 4 /cm 2 and ensuring optimal dispersion of cells in the MOx, viable and confluent EC monolayers formed on all relevant surfaces within 24 h, even though they comprised different polymers, i.e., the fibronectin-coated HFMs and the polysulfone MOx housing. Periodic medium change ensured monolayer survival and negligible apoptosis rates comparable to the reference within the assembled system. By means of these results, revealing essential implications for BHL development, their clinical translation is coming one step closer to reality.

Machine Learning has become more important for materials engineering in the last decade. Globally, automated machine learning (AutoML) is growing in popularity with the increasing demand for data analysis solutions. Yet, it is not frequently used for small tabular data. Comparisons and benchmarks already exist to assess the qualities of AutoML tools in general, but none of them elaborates on the surrounding conditions of materials engineers working with experimental data: small datasets with less than 1000 samples. This benchmark addresses these conditions and draws special attention to the overall competitiveness with manual data analysis. Four representative AutoML frameworks are used to evaluate twelve domain-specific datasets to provide orientation on the promises of AutoML in the field of materials engineering. Performance, robustness and usability are discussed in particular. The results lead to two main conclusions: First, AutoML is highly competitive with manual model optimization, even with little training time. Second, the data sampling for train and test data is of crucial importance for reliable results., (© 2022. The Author(s).)

The use of wild plant species or their halophytic relatives has been considered in plant breeding programs to improve salt and drought tolerance in crop plants. Aeluropus littoralis serves as halophyte model for identification and isolation of novel stress adaptation genes. A. littoralis, a perennial monocot grass, grows in damp or arid areas, often salt-impregnated places and wasteland in cultivated areas, can survive periodically high water salinity, and tolerate high salt concentrations in the soil up to 1,100 mM sodium chloride. Therefore, it serves as valuable genetic resource to understand molecular mechanisms of stress-responses in monocots. The knowledge can potentially be used for improving tolerance to abiotic stresses in economically important crops. Several morphological, anatomical, ecological, and physiological traits of A . littoralis have been investigated so far. After watering with salt water the grass is able to excrete salt via its salt glands. Meanwhile, a number of ESTs (expressed sequence tag), genes and promoters induced by the salt and drought stresses were isolated, sequenced and annotated at a molecular level. Transfer of stress related genes to other species resulted in enhanced stress resistance. Here we describe the genome sequence and structure of A. littoralis analyzed by whole genome sequencing and histological analysis. The chromosome number was determined to be 20 (2 n = 2x = 20). The genome size was calculated to be 354 Mb. This genomic information provided here, will support the functional investigation and application of novel genes improving salt stress resistance in crop plants. The utility of the sequence information is exemplified by the analysis of the DREB-transcription factor family., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Hashemi-Petroudi, Arab, Dolatabadi, Kuo, Baez, Himmelbach, Nematzadeh, Maibody, Schmutzer, Mälzer, Altmann and Kuhlmann.)

To provide an alternative treatment option for patients with end-stage lung disease, we aim for biohybrid lung development (BHL) based on hollow fiber membrane (HFM) technology used in extracorporeal membrane oxygenators. For long-term BHL application, complete hemocompatibility of all blood-contacting surfaces is indispensable and can be achieved by their endothelialization. Indeed, albumin/heparin (AH) coated HFM enables initial endothelialization, but as inexplicable cell loss under flow conditions was seen, we assessed an alternative HFM coating using fibronectin (FN). Therefore, endothelial cell (EC) adherence and viability on both coated HFM were analyzed by fluorescence-based staining. Functional leukocyte and thrombocyte adhesion assays were performed to evaluate hemocompatibility, also in comparison to blood plasma coated HFM as a clinically relevant control. To assess monolayer resistance and EC behavior under clinically relevant flow conditions, a mock circulation setup was established, which also facilitates imitation of lung-disease specific blood gas settings. Besides quantification of flow-associated cell loss, endothelial responses towards external stimuli, like flow exposure or TNFα stimulation, were analyzed by qRT-PCR, focusing on inflammation, thrombus formation and extracellular matrix production. Under static conditions, both coated HFM enabled the generation of a viable, confluent, non-inflammatory and anti-thrombogenic monolayer. However, by means of homogenous FN coating, cell retention and physiologic gene regulation towards an improved hemocompatible-and extracellular matrix producing phenotype, was significantly superior compared to the inhomogeneous AH coating. In summary, our adaptable in-house FN coating secures the endothelial requirements for long-term BHL application and may promote monolayer establishment on all other blood contacting surfaces of the BHL (e.g., cannulae).

Unlabelled: We report on an 8-year-old boy with autism spectrum disorder (ASD), speech delay, behavioural problems, disturbed sleep and macrosomia including macrocephaly carrying a microdeletion that contains the entire NCAM2 gene and no other functional genes. Other family members with the microdeletion show a large skull circumference but do not exhibit any symptoms of autism spectrum disorder. Among many ASD-candidate genes, NCAM2 has been assumed to play a pivotal role in the development of ASD because of its function in the outgrowth and bundling of neurites. Our reported case raises the questions whether the NCAM2-deletion is the true cause of the ASD or only a risk factor and whether there might be any connection in NCAM2 with skull-size, Key Words: autism spectrum disorder, macrocephaly, neural cell adhesion molecule 2 protein (NCAM2), array comparative genomic hybridization (microarray)., (Copyright © 2016 Elsevier Masson SAS. All rights reserved.)

CHARGE syndrome is an autosomal dominant inherited multiple malformation disorder typically characterized by coloboma, choanal atresia, hypoplastic semicircular canal, cranial nerve defects, cardiovascular malformations and ear abnormalities. Mutations in the chromodomain helicase DNA-binding protein 7 (CHD7) gene are the major cause of CHARGE syndrome. Mutation analysis was performed in 18 patients with firm or tentative clinical diagnosis of CHARGE syndrome. In this study eight mutations distributed across the gene were found. Five novel mutations - one missense (c.2936T > C), one nonsense (c.8093C > A) and three frameshift mutations (c.804_805insAT, c.1757_1770del14, c.1793delA) - were identified. As far as familial data were available these mutations were found to have arisen de novo. Comparison of the clinical features of patients with the same mutation demonstrates that expression of the phenotype is highly variable. The mutation detection rate in this study was 44.4% in patients with a clinically established or suspected diagnosis of CHARGE syndrome., (Copyright © 2010 Elsevier Masson SAS. All rights reserved.)