The Pharmacological Potential of Mushrooms

This review describes pharmacologically active compounds from mushrooms. Compounds and complex substances with antimicrobial, antiviral, antitumor, antiallergic, immunomodulating, anti-inflammatory, antiatherogenic, hypoglycemic, hepatoprotective and central activities are covered, focusing on the review of recent literature. The production of mushrooms or mushroom compounds is discussed briefly

Growth characterization of CHO DP-12 cell lines with different high passage histories

Heinrich C, Timo W, Christina K, Northoff S, Noll T. Growth characterization of CHO DP-12 cell lines with different high passage histories. In: Hansjörg H, ed. BMC Proceedings. BMC Proceedings. Vol 5. BioMed Central; 2011

Estimating the gas hydrate recovery prospects in the western Black Sea basin based on the 3D multiphase flow of fluid and gas components within highly permeable paleo-channel-levee systems

Gas hydrate deposits are abundant in the Black Sea region and confirmed by direct observations as well as geophysical evidence, such as continuous bottom simulating reflectors (BSRs). Although those gas hydrate accumulations have been well-studied for almost two decades, the migration pathways of methane that charge the gas hydrate stability zone (GHSZ) in the region are unknown. The aim of this study is to explore the most probable gas migration scenarios within a three-dimensional finite element grid based on seismic surveys and available basin cross-sections. We have used the commercial software PetroMod TM(Schlumberger) to perform a set of sensitivity studies that narrow the gap between the wide range of sediment properties affecting the multi-phase flow in porous media. The high-resolution model domain focuses on the Danube deep-sea fan and associated buried sandy channel-levee systems whereas the total extension of the model domain covers a larger area of the western Black Sea basin. Such a large model domain allows for investigating biogenic as well as thermogenic methane generation and a permeability driven migration of the free phase of methane on a basin scale to confirm the hypothesis of efficient methane migration into the gas hydrate reservoir layers by horizontal flow along the carrier beds

Dealing with Small Annotated Datasets for Deep Learning in Medical Imaging: An Evaluation of Self-Supervised Pre-Training on CT Scans Comparing Contrastive and Masked Autoencoder Methods for Convolutional Models

Deep learning in medical imaging has the potential to minimize the risk of diagnostic errors, reduce radiologist workload, and accelerate diagnosis. Training such deep learning models requires large and accurate datasets, with annotations for all training samples. However, in the medical imaging domain, annotated datasets for specific tasks are often small due to the high complexity of annotations, limited access, or the rarity of diseases. To address this challenge, deep learning models can be pre-trained on large image datasets without annotations using methods from the field of self-supervised learning. After pre-training, small annotated datasets are sufficient to fine-tune the models for a specific task, the so-called ``downstream task". The most popular self-supervised pre-training approaches in medical imaging are based on contrastive learning. However, recent studies in natural image processing indicate a strong potential for masked autoencoder approaches. Our work compares state-of-the-art contrastive learning methods with the recently introduced masked autoencoder approach "SparK" for convolutional neural networks (CNNs) on medical images. Therefore we pre-train on a large unannotated CT image dataset and fine-tune on several downstream CT classification tasks. Due to the challenge of obtaining sufficient annotated training data in the medical imaging domain, it is of particular interest to evaluate how the self-supervised pre-training methods perform on small downstream datasets. By experimenting with gradually reducing the training dataset size of our downstream tasks, we find that the reduction has different effects depending on the type of pre-training chosen. The SparK pre-training method is more robust to the training dataset size than the contrastive methods. Based on our results, we propose the SparK pre-training for medical downstream tasks with small datasets.Comment: This paper is under review. The code will be released if accepte

Superimposed high-frequency jet ventilation combined with continuous positive airway pressure/assisted spontaneous breathing improves oxygenation in patients with H1N1-associated ARDS

Background: Numerous cases of swine-origin 2009 H1N1 influenza A virus (H1N1)-associated acute respiratory distress syndrome (ARDS) bridged by extracorporeal membrane oxygenation (ECMO) therapy have been reported; however, complication rates are high. We present our experience with H1N1-associated ARDS and successful bridging of lung function using superimposed high-frequency jet ventilation (SHFJV) in combination with continuous positive airway pressure/assisted spontaneous breathing (CPAP/ASB). Methods: We admitted five patients with H1N1 infection and ARDS to our intensive care unit. Although all patients required pure oxygen and controlled ventilation, oxygenation was insufficient. We applied SHFJV/CPAP/ASB to improve oxygenation. Results: Initial PaO2/FiO2 ratio prior SHFJV was 58-79 mmHg. In all patients, successful oxygenation was achieved by SHFJV (PaO2/FiO2 ratio 105-306 mmHg within 24 h). Spontaneous breathing was set during first hours after admission. SHFJV could be stopped after 39, 40, 72, 100, or 240 h. Concomitant pulmonary herpes simplex virus (HSV) infection was observed in all patients. Two patients were successfully discharged. The other three patients relapsed and died within 7 weeks mainly due to combined HSV infection and in two cases reoccurring H1N1 infection. Conclusions: SHFJV represents an alternative to bridge lung function successfully and improve oxygenation in the critically ill

Fiducial Marker based Extrinsic Camera Calibration for a Robot Benchmarking Platform

Korthals T, Wolf D, Rudolph D, Hesse M, Rückert U. Fiducial Marker based Extrinsic Camera Calibration for a Robot Benchmarking Platform. In: European Conference on Mobile Robots, ECMR 2019, Prague, CZ, September 4-6, 2019. 2019: 1-6.Evaluation of robotic experiments requires physical robots as well as position sensing systems. Accurate systems detecting sufficiently all necessary degrees of freedom, like the famous Vicon system, are commonly too expensive. Therefore, we target an economical multi-camera based solution by following these three requirements: Using multiple cameras to track even large laboratory areas, applying fiducial marker trackers for pose identification, and fuse tracking hypothesis resulting from multiple cameras via extended Kalman filter (i.e. ROS's robot\_localization). While the registration of a multi-camera system for collaborative tracking remains a challenging issue, the contribution of this paper is as follows: We introduce the framework of Cognitive Interaction Tracking (CITrack). Then, common fiducial marker tracking systems (ARToolKit, AprilTag, ArUco) are compared with respect to their maintainability. Lastly, a graph-based camera registration approach in SE(3), using the fiducial marker tracking in a multi-camera setup, is presented and evaluated