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Objective: \ud Fibroblast-like synoviocytes (FLS) play a pivotal role in rheumatoid arthritis (RA) by contributing to synovial inflammation and progressive joint damage. An imprinted epigenetic state is associated with the FLS aggressive phenotype. We identified CASP8 (encoding for caspase-8) as a differentially marked gene and evaluated its pathogenic role in RA FLSs.\ud \ud Methods: \ud RA FLS lines were obtained from synovial tissues at arthroplasty and used at passage 5-8. Caspase-8 was silenced using small interfering RNA, and its effect was determined in cell adhesion, migration and invasion assays. Quantitative reverse transcription PCR and western blot were used to assess gene and protein expression, respectively. A caspase-8 selective inhibitor was used determine the role of enzymatic activity on FLS migration and invasion. Caspase-8 isoform transcripts and epigenetic marks in FLSs were analyzed in FLS public databases. Crystal structures of caspase-8B and G were determined.\ud \ud Results: \ud Caspase-8 deficiency in RA FLSs reduced cell adhesion, migration, and invasion independent of its catalytic activity. Epigenetic and transcriptomic analyses of RA FLSs revealed that a specific caspase-8 isoform, variant G, is the dominant isoform expressed (~80% of total caspase-8) and induced by PDGF. The crystal structures of caspase-8 variant G and B were identical except for a unique unstructured 59 amino acid N-terminal domain in variant G. Selective knockdown of caspase-8G was solely responsible for the effects of caspase-8 on calpain activity and cell invasion in FLS.\ud \ud Conclusion: \ud Blocking caspase-8 variant G could decrease cell invasion in diseases like RA without the potential deleterious effects of nonspecific caspase-8 inhibition.

An image dataset with hazmat labels on different backgrounds and pixel-accurate ground truth

In the agricultural sector there is a high interest for forecasts that predict relevant agroclimatic indicators related to heat accumulation and frost characteristics. The forecasts can simplify agricultural decisions related to planting and harvest timing. Motivated by this, we propose a probabilistic forecasting framework for predicting the end of the freeze-free season, or the time to a mean daily near-surface air temperature below 0 °C (here referred to as hard freeze). The forecasts are constructed based on a multi-model seasonal temperature forecast ensemble provided by the Copernicus Climate Data Store. The raw temperature forecast is statistically post-processed through a mean and variance correction. The resulting ensemble is next used as input to a survival analysis model. Survival analysis is a broad statistical field that is commonly used in the field of biostatistics, but rarely used in meteorology.The forecasting framework is evaluated by predicting the time to hard freeze from October 1 for 1993-2020 for a region in Fennoscandia that covers Norway and parts of Sweden, Finland and Russia. We find that the proposed forecast outperforms a climatology forecast from an observation-based data product at locations where the average predicted time to hard freeze is less than 40 days after the initialization date.Our work also forms an entry point showing how survival models can be used in general to construct seasonal forecasts for other meteorological events, e.g. the onset of the rainy season or the time to the next drought.

For the past two decades, BTK a tyrosine kinase and member of the Tec family has been a drug target of significant interest due to its potential to selectively treat various B cell-mediated diseases such as CLL, MCL, RA, and MS. Owning to the challenges encountered in identifying drug candidates exhibiting the potency block B cell activation via BTK inhibition, the pharmaceutical industry has relied on the use of covalent/irreversible inhibitors to address this unmet medical need. Herein, we describe a medicinal chemistry campaign to identify structurally diverse reversible BTK inhibitors originating from HITS identified using a fragment base screen. The leads were optimized to improve the potency and in vivo ADME properties resulting in a structurally distinct chemical series used to develop and validate a novel in vivo CD69 and CD86 PD assay in rodents.

In recent years, place recognition techniques have been extensively studied in the domain of robotic mapping, referred to as appearance-based mapping. Nonetheless, the majority of these methods focus the challenges of place recognition in offline or supervised scenarios, which in certain conditions, e.g., unknown environments, is infeasible. In this paper, we address the challenges of online place recognition and demonstrate the general applicability of our approach in versatile environments. To this end, a modified growing self-organizing network of neurons is proposed, which incrementally adapts itself to learn the topology of the perceptual space formed by gist features. Given a query image and the network state at any time instant, the expected activity of the network is estimated using a proposed Bayesian framework, and the current place is categorized as familiar or novel. Exhaustive experiments on 11 challenging sequences signify the strength of our algorithm for a reliable and real-time place recognition on routes as large as 18 km. Compared to many state-of-the-art approaches, our method does not need offline training or environment-specific parameter tuning.

Artificial visual attention has been an active research area for over two decades. Especially, the concept of saliency has been implemented in many different ways. Early approaches aimed at closely modeling saliency processing with concepts from biological attention to provide (at least in the long run) general-purpose attention for technical systems. More recent approaches have departed from this agenda, turning to more specific attention-guided tasks, most notably the accurate extraction of salient objects, for which large-scale ground truth datasets make it possible to quantify progress. While the first type of models is troubled by weak performance in these specific tasks, the second type, as we show with a new benchmark, has lost the ability to predict saliency in the original sense, which may be an important factor for future general-purpose attention systems. Here, we describe a new approach using growing neural gas to obtain pre-attentional structures for a scene at an early processing stage. On this basis, traditional saliency concepts can be applied while at the same time they can be linked to mechanisms that make models successful in salient object detection. The model shows high performance at predicting traditional saliency and makes substantial progress toward salient object detection, although it cannot reach the top-level performance of some specialized methods. We discuss the important implications of our findings.

Since the approval of ibrutinib for the treatment of B-cell malignancies in 2012, numerous clinical trials have been reported using covalent inhibitors to target Bruton's tyrosine kinase (BTK) for oncology indications. However, a formidable challenge for the pharmaceutical industry has been the identification of reversible, selective, potent molecules for inhibition of BTK. Herein, we report application of Tethering-fragment-based screens to identify low molecular weight fragments which were further optimized to improve on-target potency and ADME properties leading to the discovery of reversible, selective, potent BTK inhibitors suitable for pre-clinical proof-of-concept studies.

Weather-related risk makes the insurance industry inevitably concerned with climate and climate change. Buildings hit by pluvial flooding is a key manifestation of this risk, giving rise to compensations of the induced physical damages and business interruptions. In this work, we establish a nationwide, building-specific risk score for water damage associated with pluvial flooding in Norway. We fit a generalized additive model that relates the number of water damages to a wide range of explanatory variables that can be categorized into building attributes, climatological variables and topographical characteristics. The model assigns a risk score to every location in Norway, based on local topography and climate, which is not only useful for insurance companies, but also for city planning. Combining our model with an ensemble of climate projections allows us to project the (spatially varying) impacts of climate change on the risk of pluvial flooding towards the middle and end of the 21st century.

One of the major challenges for mobile robots in human-shaped environments is navigating stairways. This study presents a method for accurately detecting, localizing, and estimating the characteristics of stairways using point cloud data. The main challenge is the wide variety of different structures and shapes of stairways. This challenge is often aggravated by an unfavorable position of the sensor, which leaves large parts of the stairway occluded. This can be further aggravated by sparse point data. We overcome these difficulties by introducing a three-dimensional graph-based stairway-detection method combined with competing initializations. The stairway graph characterizes the general structural design of stairways in a generic way that can be used to describe a large variety of different stairways. By using multiple ways to initialize the graph, we can robustly detect stairways even if parts of the stairway are occluded. Furthermore, by letting the initializations compete against each other, we find the best initialization that accurately describes the measured stairway. The detection algorithm utilizes a plane-based approach. We also investigate different planar segmentation algorithms and experimentally compare them in an application-orientated manner. Our system accurately detects and estimates the stairway parameters with an average error of only [Formula: see text] for a variety of stairways including ascending, descending, and spiral stairways. Our method works robustly with different depth sensors for either small- or large-scale environments and for dense and sparse point cloud data. Despite this generality, our system’s accuracy is higher than most state-of-the-art stairway-detection methods.

This paper proposes a new concept, the Admissible Gap (AG), for reactive collision avoidance. A gap is called admissible if it is possible to find a collision-free motion control that guides a robot through it, while respecting the vehicle constraints. By utilizing this concept, a new navigation approach was developed, achieving an outstanding performance in unknown dense environments. Unlike the widely used gap-based methods, our approach directly accounts for the exact shape and kinematics, rather than finding a direction solution and turning it later into a collision-free admissible motion. The key idea is to analyze the structure of obstacles and virtually locate an admissible gap, once traversed, the robot makes progress towards the goal. For this purpose, we introduce a strategy of traversing gaps that respect the kinematic constraints and provides a compromise between path length and motion safety. We also propose a new methodology for extracting gaps that eliminates useless ones, thus reducing oscillations. Experimental results along with performance evaluation demonstrate the outstanding behavior of the proposed AG approach. Furthermore, a comparison with existing state-of-the-art methods shows that the AG approach achieves the best results in terms of efficiency, robustness, safety, and smoothness.

His-tRNA synthetase (HARS) is targeted by autoantibodies in chronic and acute inflammatory anti-Jo-1-positive antisynthetase syndrome. The extensive activation and migration of immune cells into lung and muscle are associated with interstitial lung disease, myositis, and morbidity. It is unknown whether the sequestration of HARS is an epiphenomenon or plays a causal role in the disease. Here, we show that HARS circulates in healthy individuals, but it is largely undetectable in the serum of anti-Jo-1-positive antisynthetase syndrome patients. In cultured primary human skeletal muscle myoblasts (HSkMC), HARS is released in increasing amounts during their differentiation into myotubes. We further show that HARS regulates immune cell engagement and inhibits CD4+ and CD8+ T-cell activation. In mouse and rodent models of acute inflammatory diseases, HARS administration downregulates immune activation. In contrast, neutralization of extracellular HARS by high-titer antibody responses during tissue injury increases susceptibility to immune attack, similar to what is seen in humans with anti-Jo-1-positive disease. Collectively, these data suggest that extracellular HARS is homeostatic in normal subjects, and its sequestration contributes to the morbidity of the anti-Jo-1-positive antisynthetase syndrome.

Bruton's tyrosine kinase (BTK) is an essential node on the BCR signaling in B cells, which are clinically validated to play a critical role in B-cell lymphomas and various auto-immune diseases such as Multiple Sclerosis (MS), Pemphigus, and rheumatoid arthritis (RA). Although non-selective irreversible BTK inhibitors have been approved for oncology, due to the emergence of drug resistance in B-cell lymphoma associated with covalent inhibitor, there an unmet medical need to identify reversible, selective, potent BTK inhibitor as viable therapeutics for patients. Herein, we describe the identification of Hits and subsequence optimization to improve the physicochemical properties, potency and kinome selectivity leading to the discovery of a novel class of BTK inhibitors. Utilizing Met ID and structure base design inhibitors were synthesized with increased in vivo metabolic stability and oral exposure in rodents suitable for advancing to lead optimization.

Curvature scale-space (CSS) analysis is an important technique for contour-based object recognition in digital images. To compute the CSS for a given contour, it is systematically convolved (smoothed) with Gaussians with increasing standard deviation. The convolutions are computationally expensive, especially for large and high resolution contours, but can be approximated using box filtering (also known as mean and average filtering). Together with running sums, the convolutions can be accelerated by 2–3 magnitudes without significant loss of precision. Nonetheless, box filtering has not been systematically investigated in connection with CSS computation. In this work, we present a theoretical and experimental analysis of different box-filtering techniques in this context and conclude which is the most efficient implementation. Based on this, the CSS of a contour can be computed in real time with high precision.

This paper presents a novel reactive collision avoidance method for mobile robots moving in dense and cluttered environments. The proposed method, entitled Tangential Gap flow (TGF), simplifies the navigation problem using a divide and conquer strategy inspired by the well-known Nearness-Diagram Navigation (ND) techniques. At each control cycle, the TGF extracts free openings surrounding the robot and identifies the suitable heading which makes the best progress towards the goal. This heading is then adjusted to avoid the risk of collision with nearby obstacles based on two concepts namely, tangential and gap flow navigation. The tangential navigation steers the robot parallel to the boundary of the closest obstacle while still emphasizing the progress towards the goal. The gap flow navigation safely and smoothly drives the robot towards the free area in between obstacles that lead to the target. The resultant trajectory is faster, shorter and less-oscillatory when compared to the ND methods. Furthermore, identifying the avoidance maneuver is extended to consider all nearby obstacle points and generate an avoidance rule applicable for all obstacle configurations. Consequently, a smoother yet much more stable behavior is achieved. The stability of the motion controller, that guides the robot towards the desired goal, is proved in the Lyapunov sense. Experimental results including a performance evaluation in very dense and complex environments demonstrate the power of the proposed approach. Additionally, a discussion and comparison with existing Nearness-Diagram Navigation variants is presented. A novel reactive collision avoidance approach, referred to as TGF, is presented.The TGF safely drives a mobile robot in very dense and cluttered environments.The trajectory is faster, shorter, and smoother compared to the well-known ND method.Experimental results demonstrate the power of the TGF approach.The performance is evaluated and compared with three different ND variants.

The estimation of optical flow in cases of illumination change, sparsely-textured regions or fast moving objects is a challenging problem. In this paper, we analyze the use of a texture constancy constraint based on local descriptors (i.e., HOG) integrated with the monocular epipolar geometry to estimate robustly optical flow. The framework is implemented in differential data fidelities using a total variation model in a multi-resolution scheme. Besides, we propose an effective method to refine the fundamental matrix along with the estimation of the optical flow. Experimental results based on the challenging KITTI dataset show that the integration of texture constancy constraint with the monocular epipolar line constraint and the enhancement of the fundamental matrix significantly increases the accuracy of the estimated optical flow. Furthermore, a comparison with existing state-of-the-art approaches shows better performance for the proposed approach.

The agent’s ability to locate itself in an unfamiliar environment is essential for a reliable navigation. To address this challenge, place recognition methods are widely adopted. A common trend among most of these methods is that they are either tailored to work in specific environments or need prior training overhead [11]. Whereas, others demand extreme computational resources, such as CNN [8]. In this paper, we study the existing GSOM-based place recognition framework [12] and investigate the question of translating the system to other feature spaces, such as HOG, for low-cost place recognition. The experiments performed on four challenging sequences demonstrate the algorithm’s ability to learn the representation of the new feature space without parameter tuning, provided the scaling factor along each dimension of the descriptor is taken into account. This highlights the feature-agnostic characteristic of the algorithm. We further observed that despite the low dimensionality of the HOG descriptor, the algorithm shows comparable place recognition results to the gist features, while offering threefold speed-ups in execution time.

Ahstract- In the last years, the demand for mobile robots in rescue and surveillance has increased considerably as these systems allow to reduce human harm and save the workforce. A major problem still is the mapping of unknown environments for localization and navigation purposes. Common 2D mapping is not sufficient for 3D environments with multiple levels and 3D structures. Unfortunately, recent approaches for 3D reconstruction suffer from high hardware requirements to meet real-time constraints and the accumulation of errors in the reconstruction result over time. Moreover, the loop closing problem could not be solved satisfactorily yet. In this paper, we propose a new approach for real-time 3D reconstruction that meets the hardware requirements of mobile robots and is capable of detecting and closing loops to reduce errors. We therefore combine and modify three state-of-the-art approaches into a 3D reconstruction system that is also working in sparse feature environments. Each of the subsystems runs in a parallel thread accelerated by the GPU and can easily be replaced by another algorithm if necessary.

Rescue robots and similar vehicles must recognize various visual objects. Some are of particular interest and must be reliably recognized, for example, hazard signs. Hazmat labels and other intentionally placed signs of danger are typically attached to walls, containers, or vehicles, in locations where they attract attention. These backgrounds typically are of relatively simple structure (though not guaranteed to be plain) while the labels have saturated colors and high contrasts. We provide a new dataset that contains such images and a novel hazmat detection method. It includes an attentional preselection, which exploits the salient design and placement of the labels to locate them, followed by a SIFT-based classification that determines the concrete label type. The results show substantial speed improvements and accuracy gains over the traditional method without an attention stage.

Optical flow is a key problem in computer vision with tremendous potential applications in many fields, such as action recognition, autonomous navigation and manipulation. In this paper, we propose a dense optical flow estimation approach for objects of interest. In order to improve the accuracy of the optical flow estimation, the intensity and depth data from the RGB-D sensor are used for doing object segmentation. Afterwards, a homography based method assuming the surface to be planar is applied to obtain dense optical flow for each segment. Several experiments have been performed to evaluate the proposed method. The results demonstrate the validity of our approach.

In this paper, a questionnaire-based survey on the use of online videos by undergraduate engineering students for study-related purposes is presented. Over the last few years, a large number of instructional videos has been uploaded to websites such as YouTube. Due to the widespread distribution of high-speed internet connections and (mobile) devices, such as smartphones or laptops, which are nowadays routinely used by students, online videos are also frequently used in higher education. While much research on this subject focuses on Massive Open Online Courses (MOOCs) or flipped classroom approaches, this survey examines use of videos for self-study, complementary to traditional face-to-face courses. Furthermore, we analyze the acceptance of a characteristic video production style, which uses specific 3D animations to clarify complex connections between technical and mathematical aspects. The results indicate extensive use of short videos which address subjects that are particularly difficult for the students. This survey can help educators to develop an impression of current video use by undergraduate engineering students. In this paper, a questionnaire-based survey on the use of online videos by undergraduate engineering students for study-related purposes is presented. Especially over the last few years, a large number of instructional videos has been uploaded to websites such as YouTube. Due to the widespread distribution of high-speed internet connections and (mobile) devices, such as smartphones or laptops, which are nowadays routinely used by students, online videos are also frequently used in higher education. While much research on this subject focuses on Massive Open Online Courses (MOOCs) or flipped classroom approaches, this survey examines usage behavior concerning the apparently much more common use of videos for self-study, complementary to traditional face-to-face courses. Furthermore, we analyze the acceptance of a characteristic video production style using specific 3D animations to clarify complex connections between technical and mathematical aspects. The results indicate that short videos addressing subjects that are particularly difficult for the students are extensively used. Additionally, this survey can help educators to develop a realistic understanding of current video use by undergraduate engineering students.

The initial phase of undergraduate engineering degree programmes often comprises courses requiring mathematical expertise which in some cases clearly exceeds school mathematics, but will be imparted only later in mathematics courses. In this article, an approach addressing this challenge by way of example within a fundamentals of electrical engineering course is presented. The concept focuses on gaining specific mathematical knowledge and competencies in the technical context of this course. For this purpose, a complementary blended learning scenario centring around a web-based learning platform and involving an adaptation of the course was developed. The concept particularly considers the heterogeneity of today's student groups and is discussed with regard to related approaches, didactical considerations, and technical implementation. For the interventions, the results of a questionnaire-based evaluation proving students' acceptance and positive influence on examination performance are presented.

This paper presents a new concept, the Admissible Gap, for collision avoidance. An admissible gap AG is defined as the gap that a robot may safely pass through, while obeying the shape and motion constraints. By employing this concept, a new obstacle avoidance approach was developed, improving the navigation performance in unknown cluttered environments. Unlike most state-of-the-art methods, our approach explicitly considers the robot shape and kinematic constraints rather than adapting a method originally designed for a holonomic pointlike robot. Experimental results demonstrated the power of the proposed AG approach. Moreover, a comparison with state-ofthe- art methods showed that the AG approach generates more efficient, safer, and smoother trajectories.

Most of the variational optical flow methods are based on the well-known brightness constancy assumption or high-order constancy assumptions to implement the data term in the optimization energy function. Unfortunately, any variation in the lighting within the scene violates the brightness constancy constraint; in turn, the gradient constancy assumption does not work properly with large illumination changes. This paper proposes an illumination-robust constancy based on a robust texture descriptor rather than the brightness constancy. Thus, the similarity function used as a data term was obtained from extracting texture features through the local directional pattern descriptor for two consecutive frames within the duality total variational optical flow algorithm. In addition, a weighted nonlocal term that depends on both the color similarity and the occlusion state of pixels is integrated during the optimization process to increase the accuracy of the resulting flow field. The experimental results show a qualitative comparison with the proposed approach and yield state-of-the-art results on the KITTI, Midleburry, and MPI-sintel data sets.

Mobile robots have to deal with an enormous amount of visual data containing static and dynamic stimuli. Depending on the task, only small portions of a scene are relevant. Artificial attention systems filter information at early stages. Among the various methods proposed to implement such systems, the region-based approach has proven to be robust and especially suited for integrating top-down influences. This concept was recently transferred to the spatiotemporal domain to obtain motion saliency. A full-featured integration of the spatial and spatiotemporal systems is presented here. We propose a biologically inspired two-stream system, which allows to use different spatial and temporal resolutions and to pick off spatiotemporal saliency at early stages. We compare the output to classic models and demonstrate the flexibility of the integrated approach in different experiments. These include online processing of continuous input, a task similar to thumbnail extraction and a top-down task of selecting specific moving and non-moving objects.

We propose a compact descriptor for the purpose of dense image matching and object recognition. The descriptor is calculated based on local gradients about each point in an image. It contains the averages of gradients at four different windows surrounding a center point. The descriptor is calculated much faster than histogram of oriented gradients (HOG). Additionally, it will be shown that it is more discriminative than HOG. We used the new descriptor for two applications needed in RoboCup competitions very often. First, computation of dense optical flows and 3D scene reconstruction from two views. Second, human face detection.

Can early visual attention processes facilitate the selection and execution of simple robotic actions? We believe that this is the case. Following the selection–for–action agenda known from human attention, we show that central perceptual processing can be avoided or at least relieved from managing simple motor processes. In an attention–classification–action cycle, salient pre-attentional structures are used to provide features to a set of classifiers. Their action proposals are coordinated, parametrized (via direct parameter specification), and executed. We evaluate the system with a simulated mobile robot.

This paper presents a new collision avoidance method for mobile robots operating in unknown cluttered environments. The proposed method computes the steering angle based on the location of all obstacles surrounding the robot, not just the closest one. Hence, our technique is capable of generating smooth robot trajectories, particularly for unstructured environments. Moreover, the stability of the robot’s motion is improved by providing a smoother bridge between avoiding obstacles and approaching the goal. Oscillations occurring in narrow corridors are reduced by considering the distribution of obstacles to both sides of the direction of motion. Simulation and experimental results are presented to demonstrate the performance of the proposed approach.

In this paper, the usage of the monocular epipolar geometry for the calculation of optical flow is investigated. We derive the necessary formulation to use the epipolar constraint for the calculation of differential optical flow using the total variational model in a multi-resolution pyramid scheme. Therefore, we minimize an objective function which contains the epipolar constraint with a residual function based on different types of descriptors (brightness, HOG, CENSUS and MLDP). For the calculation of epipolar lines, the relevant fundamental matrices are calculated based on the 7- and 8- point methods. Moreover, SIFT and Lukas-Kanade methods are used to obtain matched features between two consecutive frames, by which fundamental matrices can be calculated. The effect of using different combination of the feature matching methods, fundamental matrix calculation and descriptors are evaluated based on the KITTI 2012 dataset.

Recent research in appearance-based mapping has introduced a diverse range of techniques to deal with environments under varying conditions. Common to almost all the existing methods is that they expect a supervised or offline training. Furthermore, some approaches match sequences, assuming constant velocity over the routes. This work addresses the challenges of appearance-based mapping in an online setup without making assumptions or acquiring prior knowledge of the environment. For this purpose, we exploit the topology preserving capability of self-organizing neural networks and learn the perceptual representation of environments using GIST features. Due to the fact that real-world environments are complex and large-scale, we let the network grow while accounting for the amount of error in the network due to perceptual differences among the places. Given the current state of the network and a query image at any time instant, it is possible to identify whether a place comes from the visited location by computing maximum a posteriori estimate over the network. The extensive experiments on three standard datasets, St. Lucia (4 videos), KITTI (2 sequences), and the Oxford City Center dataset, demonstrate the strength of our approach for real-time place recognition while concurrently learning the spatial representation of scenes.

This paper presents a new concept, the “Directly Navigable Gap”, for reactive obstacle avoidance. A directly navigable gap DNG is defined as the gap that a robot can safely navigate through by executing only a single motion command. With this concept, it has been possible to achieve navigation in unknown cluttered environments, similar to the gap-based obstacle avoidance methods (e.g the Nearness-Diagram Navigation). Compared to these methods, however, our approach avoids the limitation of being prone to oscillatory and unstable motion, improving their navigation performance, especially in narrow spaces. Experimental results are presented to verify the outstanding performance of the proposed DNG approach. Moreover, a discussion and comparison with existing gap-based methods is reported where the DNG approach generates less-oscillatory, safer, and faster trajectories than its counterparts.

Perception is the main key in enabling robots to react to and interact with their environment. Particularly, for multi-floor operations, the robot must robustly detect and localize stairs to allow for safe climbing. In this paper, we develop a graph-based stairway detection method for point cloud data, that can detect a large variety of stairways. Our approach first segments planar regions and extracts the stair tread- and stair riser-shaped segments. With these segments, a dynamic graph model is initialized that is used to detect stairs including the railing system in the surroundings. We show that our system can accurately detect and localize different stairways from a variety of different positions, including descending stairs. Our system's accuracy is higher than those of most state-of-the-art stairway detection methods even in case of sparse point cloud data.

Suggesting that bioartificial vascular scaffolds cannot but tissue-engineered vessels can withstand biomechanical stress, we developed in vitro methods for preclinical biological material testings. The aim of the study was to evaluate the influence of revitalization of xenogenous scaffolds on biomechanical stability of tissue-engineered vessels. For measurement of radial distensibility, a salt-solution inflation method was used. The longitudinal tensile strength test (DIN 50145) was applied on bone-shaped specimen: tensile/tear strength (SigmaB/R), elongation at maximum yield stress/rupture (DeltaB/R), and modulus of elasticity were determined of native (NAs; n = 6), decellularized (DAs; n = 6), and decellularized carotid arteries reseeded with human vascular smooth muscle cells and human vascular endothelial cells (RAs; n = 7). Radial distensibility of DAs was significantly lower (113) than for NAs (135) (P < 0.001) or RAs (127) (P = 0.018). At levels of 120 mm Hg and more, decellularized matrices burst (120, 160 n = 2 and 200 mm Hg). Although RAs withstood levels up to 300 mm Hg, ANOVA revealed a significant difference from NA (P = 0.018). Compared with native vessels (NAs), SigmaB/R values were lower in DAs (44%; 57%) (P = 0.014 and P = 0.002, respectively) and were significantly higher in RAs (71%; 83%) (both P < 0.001). Similarly, DeltaB/R values were much higher in DAs compared with NAs (94%; 88%) (P < 0.001) and RAs (87%; 103%) (P < 0.001), but equivalent in NAs and RAs. Modulus of elasticity (2.6/1.1/3.7 to 16.6 N/mm(2)) of NAs, DAs, RAs was comparable (P = 0.088). Using newly developed in vitro methods for small-caliber vascular graft testing, this study proved that revitalization of decellularized connective tissue scaffolds led to vascular graft stability able to withstand biomechanical stress mimicking the human circulation. This tissue engineering approach provides a sufficiently stable autologized graft.

Objectives: Tissue-engineered arterial vessels (TEAV) offer substantial advantages in small-calibered human-bypass- grafting and vascularized scaffold applications. However, histological composition of TEAV must allow for functional properties, such as vasomotoricity. Aim of this study was to characterize human TEAVs regarding morphology and vasomotoricity. Methods: Three groups containing segments of porcine carotid artery < 5mm in diameter (native [NA, n = 6], decellularized [DA, n = 6], and decellularized/reseeded in a bioreactor [RA, n 7] with human vascular endothelial [hvECs] and smooth muscle cells [hvSMCs]) were examined. Light and scanning electron microscopy were applied, and hvSMCs- and hvECs-associated Vasomotoricity Test conducted in Krebs-solution was used for characterization of revitalized TEAVs. Results: Morphologic examination showed cell-free extracellular matrix in DAs. Light microscopy demonstrated intact extracellular matrix components in circle-layered formation in cross sections of DAs. RAs showed small cells migrating along the remaining medial fiber structures and flat cell layers at the luminal site, identified as hvECs and hvSMCs with lower CD-31 and alpha-actin signaling than controls. Scanning electron microscopy showed intact flat cell layers on luminal surfaces of RAs and dense hvSMCs at their media site. DAs showed decreasing strain after stimulation. RAs retrieved vasomotoricity compared to DAs, but showed reduced contraction and incomplete relaxation compared to NAs. Conclusions: This study shows that revitalization of DA with human vascular cells resembles NA-like morphology and can ensure vasomotoricity of TEAVs.

The proceedings of chemical structure descriptors for structure-activity studies is proposed. These descriptors are based on the set of properties distributed in a topological space (molecular graph). It dominates perceptions of empirical descriptors or of autocorrelation descriptors from physical properties of atoms, for instance, of electronegativities, polarisations or volumes of chemical groups. The choice between these different methods is determined by the type of interactions of chemical compound with the receptor. By means of pattern recognition techniques you can make a classification of molecules on the base of the activity features. As well we obtaine fuzzy results with 75–95% probabilities only

Resokine is a newly identified regulator of immune cell activity, and circulating levels of Resokine in normal individuals may represent a soluble set-point control to modulate T cell activity. Resokine activity is a non-canonical function arising from the tRNA synthetase gene family, and the activity is effected by a 60 amino acid N-terminal domain arising from the gene for histidyl-tRNA synthetase which is present in the full-length protein as well as multiple splice variants that have lost their original tRNA synthetase functionality. Resokine is secreted from cells, including tumor cell lines, and in vitro studies have demonstrated that Resokine can inhibit the activation of immune cells. In vitro, for example, Resokine addition during T cell activation induced by antibodies to CD3 and CD28, can result in reduced levels of inflammatory cytokines such as IL-2, interferon gamma, and TNF alpha; inhibition of the up-regulation of cell-surface activation markers, such as CD69, CD40L and 4-1BB; and inhibition of release of the cytotoxic mediator granzyme B. We have tested levels of circulating Resokine in both mice with syngeneic tumors as well as >300 cancer patients across multiple tumor types. In normal C57Bl6 mice serum levels of Resokine ranged from 70-250pM (n=10) whereas in mice bearing B16F10 tumors, levels were significantly higher (450-3000pM, p2333pM (n=148), with 18% of individuals having levels 300 cancer patients with different tumor types, exhibited higher circulating levels with only 4% of individuals having levels below the activity threshold of 30pM. This data is consistent with the hypothesis that tumors secrete Resokine as an additional mechanism to down-regulate immune activity, and suggests further investigation of the utility of Resokine levels as a new biomarker of immune activity in patients. Citation Format: Ryan Adams, Elisabeth Mertsching, Leslie Nangle, Kathy Ogilvie, Steven Crampton, John Bruner, Samantha Tyler, Sanna Rosengren, Andrea Cubitt, David King, John Mendlein. Circulating levels of Resokine, a soluble modulator of the immune system, are upregulated in both experimental cancer models and in patients across multiple tumor types [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 2728.

Histidyl-tRNA synthetase (HARS) is the autoantigen target of Jo-1 antibodies, which occur in the major form of anti-synthetase syndrome. These patients are characterized by an autoimmune myositis and interstitial lung disease. Circulating extracellular HARS is detected in healthy individuals, but is reduced or undetectable in Jo-1-positive individuals. Administration of ATYR1940, a recombinant form of HARS, ameliorates lung fibrosis and reduces T cell cytokine production in the bleomycin-induced lung injury model. Similar effects were observed with the N-terminal domain of HARS (the iMod domain) conjugated to IgG Fc, suggesting that this domain confers the immunomodulatory activity of HARS. To confirm primary immune effects of ATYR1940 and ATYR1923 (iMod.Fc), human T cells were isolated from PBMC from healthy individuals and stimulated with anti-CD3/anti-CD28. Proteins containing the HARS iMod domain reduced in vitro activation of human CD4+ and CD8+ T cells, as evidenced by reduced secretion of IL-2, IFNγ, TNFα, IL-17, IL-13, and granzyme B, as well as decreased upregulation of activation markers such as CD69 and CD40L. ATYR1940 and ATYR1923 also inhibited cytokine release after ex vivo stimulation of human memory T cells in a NSG mouse xenogeneic GVHD model. T cell inhibition by ATYR1940 was dependent on its iMod domain, as demonstrated using an iMod-specific blocking monoclonal antibody. The ATYR1940-induced T cell gene signature reflected a general inhibitory effect on activation as well as on cell cycle protein expression. These results suggest that circulating levels of HARS may act to control the threshold stimulatory signal required to activate T cells. We propose circulating HARS as a soluble immune set-point modulator.

Bruton's tyrosine kinase (BTK), a member of the TEC family of kinases, plays a crucial role in B-cell maturation and mast cell activation. Although the structures of the unphosphorylated mouse BTK kinase domain and the unphosphorylated and phosphorylated kinase domains of human ITK are known, understanding the kinase selectivity profiles of BTK inhibitors has been hampered by the lack of availability of a high resolution, ligand-bound BTK structure. Here, we report the crystal structures of the human BTK kinase domain bound to either Dasatinib (BMS-354825) at 1.9 A resolution or to 4-amino-5-(4-phenoxyphenyl)-7H-pyrrolospyrimidin- 7-yl-cyclopentane at 1.6 A resolution. This data provides information relevant to the development of small molecule inhibitors targeting BTK and the TEC family of nonreceptor tyrosine kinases. Analysis of the structural differences between the TEC and Src families of kinases near the Trp-Glu-Ile motif in the N-terminal region of the kinase domain suggests a mechanism of regulation of the TEC family members.

From 4 to 5 April 2008, international experts met for the second time in Tubingen, Germany, to present and discuss the latest proceedings in research on non-hematopoietic stem cells (NHSC). This report presents issues of basic research including characterization, isolation, good manufacturing practice (GMP)-like production and imaging as well as clinical applications focusing on the regenerative and immunomodulatory capacities of NHSC.

In this paper, we present an enhanced approach for estimating 3D motion parameters from 2D motion vector fields. The proposed method achieves valuable reduction in computational time and shows high robustness against noise in the input data. The output of the algorithm is part in a multiobject segmentation approach implemented in an active vision system. Hence, the improvement in the motion parameters estimation process leads to speed-up in the overall segmentation process.

This review article addresses the relevance and potential of bioartificial tissues in oncologic research and therapy and reconstructive oncologic surgery. In order to translate the findings from basic cellular research into clinical applications, cell-based models need to recapitulate both the 3 D-organization and multicellular complexity of an organ but at the same time accommodate systematic experimental intervention. Here, tissue engineering, the generation of human tissues and organs in vitro, provides new perspectives for basic and applied research by offering 3 D-tissue cultures resolving fundamental obstacles encountered in currently applied 2 D- and 3 D-cell culture systems. Tissue engineering has already been applied to create replacement structures for reconstructive surgery. Applied in vitro, these complex multicellular 3 D tissue cultures mimic the microenvironment of human tissues. In contrast to the currently available cell culture systems providing only limited insight into the complex interactions in tissue differentiation, carcinogenesis, angiogenesis and the stromal reaction, the more realistic (micro)environment afforded by the bioartificial tissue specific 3 D-test systems may accelerate the progress in design and development of cancer therapies.

Crosslinking Fc(epsilon)RI and FcgammaRIIB receptors inhibits mast cell and basophil activation, decreasing mediator release. In this study, a fusion protein incorporating human Fcgamma and Fc(epsilon) domains, hGE2, was shown to inhibit degranulation of human mast cells and basophils, and to exhibit efficacy in a nonhuman primate model of allergic asthma. hGE2 increased the provocative concentration of dust mite aeroallergen that induced an early phase asthmatic response. The treatment effect lasted up to 4 weeks and was associated with reduction in the number of circulating basophils and decreased expression of Fc(epsilon)RI on repopulating basophils. Repeat hGE2 dosing induced production of serum antibodies against human Fcgamma and Fc(epsilon) domains and acute anaphylaxis-like reactions. Immune serum induced histamine release from human IgE or hGE2-treated cord blood-derived mast cells and basophils in vitro. These results indicate that repeat administration with hGE2 induced an antibody response to the human molecule that resulted in activation rather than inhibition of allergic responses.

There exists ample research exploiting cognitive processes for robot localization and mapping, for instance RatSLAM [10]. In this regard, tasks such as visual perception and recognition, which are primarily governed by visual and perirhinal cortices, receive a little attention. To bridge this gap, we present a novel bio-inspired place recognition front-end for the RatSLAM system. Our algorithm uses Gist features to obtain the perceptual structure of the scenes and employs a modified growing self-organizing map (GSOM) to model the behavior of the cells found in perirhinal cortex, called recency and familiarity neurons [6]. This enables an online learning and recognition of the places without acquiring apriori knowledge of the environment. The experiments carried out on the standard St. Lucia dataset demonstrate that on average our approach achieves almost 10% improvement (in F1-Score); it is able to correctly flag the visited and unvisited places even for noisy and blurred visual inputs. The results show that the proposed method reaches fast convergence and utilizes a smaller number of cells (consumes less physical memory) to represent the traversed path compared to the RatSLAM approach.

This paper addresses a new obstacle avoidance method for mobile robots moving in dense and complex environments. Our approach, named Smooth Closest Gap (SCG) Navigation, builds on the concept of Closest Gap (CG) as a strategy to detect free openings surrounding the robot and select the most promising one to drive through. Obstacle avoidance is performed based on the configuration of obstacles between the current robot location and the selected gap, where all obstacle points are considered to compute the avoidance maneuver and simultaneously drive the robot towards the gap. Moreover, the free area available to maneuver along the desired heading is taken into account. In turn, unnecessary deflections towards free spaces are avoided, the smoothness of the robot's trajectory is improved, and a greater reliability is achieved. The power of the proposed method is demonstrated by experimental results.

Zugunsten groserer Freiheiten beim Innenraumdesign steht modernen Bediensystemen ein sich verringernder Bauraum zur Verfugung. Sie werden immer flacher und damit raumsparender ausgelegt. In der Folge wird die Leistungs- und Steuerungselektronik von den eigentlichen Bedienelementen entkoppelt und separat platziert werden. Preh hat deshalb ein universelles Steuergerat fur „Small Domains“ in modernen Client-Server-basierten Netzwerkarchitekturen von Kraftfahrzeugen entwickelt.

BackgroundTissue-engineered pulmonary arteries could overcome the drawbacks of homografts or prosthetic conduits used in the repair of many congenital cardiac defects. However, the ideal scaffold material for tissue-engineered conduits is still subject of intensive debate. In this study, we evaluated an acellularized allogeneic matrix scaffold for pulmonary artery tissue engineering with and without in-vitro reseeding with autologous endothelial cells in the pulmonary circulation in a growing sheep model.MethodsOvine pulmonary arteries (n = 10) were acellularized by trypsin/ethylenediamine tetraacetic acid incubation. Autologous endothelial cells were harvested from carotid arteries, and the pulmonary conduits were seeded with endothelial cells. We implanted in-vitro, autologous, reendothelialized (group A, n = 5) and acellularized pulmonary conduits (group B, n = 5) in the pulmonary circulation. The animals were sacrificed 6 months after the operation. Explanted valves were examined histologically and by immunohistochemistry.ResultsThe conduit diameter increased in both groups (group A, 44% ± 11%; group B, 87% ± 18%; p < 0.05). In group A, however, a proportional increase in diameter was present, whereas in group B, a disproportionate increase resulting in aneurysm formation was observed. Histologically, the conduit wall integrity was destroyed in group B and preserved in group A. In group B, the extracellularmatrix degenerated with a reduced amount of collagens and proteoglycanes. Furthermore, no elastic fibers were detectable. In contrast, the extracellularmatrix in group A was close to native ovine tissue.ConclusionsTissue-engineered pulmonary conduits (autologous endothelial cells and allogeneic matrix scaffolds) functioned well in the pulmonary circulation. They demonstrated an increase in diameter and an extracellular matrix comparable to that of native ovine tissue.

Objective We sought to grow in vitro functional smooth muscle cells, chondrocytes, and respiratory epithelium on a biologic, directly vascularized matrix as a scaffold for tracheal tissue engineering. Methods Ten- to 15-cm–long free jejunal segments with their own vascular pedicle were harvested and acellularized from donor pigs (n = 10) and used as a vascular matrix. Autologous costal chondrocytes, smooth muscle cells, and respiratory epithelium and endothelial progenitor cells were first cultured in vitro and then disseminated on the previously acellularized vascular matrix. Histologic, immunohistologic, molecular imaging, and Western blotting studies were then performed to assess cell viability. Results The endothelial progenitor cells re-endothelialized the matrix to such an extent that endothelial cell viability was uniformly documented through 2-(18F)-fluoro-2′-deoxyglucose positron emission tomography. This vascularized scaffold was seeded with functional (according to Western blot analysis) smooth muscle cells and successfully reseeded with viable ciliated respiratory epithelium. Chondrocyte growth and production of extracellular cartilaginous matrix was observed as soon as 2 weeks after their culture. Conclusions The fundamental elements for a bioartificial trachea were successfully engineered in vitro in a direct vascularized 10- to 15-cm–long bioartificial matrix. Future experimental work will be directed to give them a 3-dimensional aspect and a biomechanical profile of a functioning trachea.