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In this paper we extend the use of a relational approach to simulation modelling, a widely used knowledge practice in sustainability science. Among modellers, there is awareness that model results can only be interpreted in view of the assumptions that inform model construction and analysis, but less systematic questioning of those assumptions. Moreover, current methodological discussions tend to focus on integrating social and ecological dynamics or diverse knowledges and data within a model. Yet choices regarding types of modelling, model structure, data handling, interpretation of results and model validation are not purely epistemic. They are entangled with values, contexts of production and use, power relations, and pragmatic considerations. Situated Modelling extends a relational understanding of the world to scientific knowledge production and with that to modelling itself in order to enable a systematic interrogation of these choices and to research social-ecological transformations relationally. To make tangible the situatedness of simulation modelling, we build on existing practices and describe the situatedness of three distinct modelling approaches. We then suggest four guiding principles for Situated Modelling: 1. attending to the apparatus of knowledge production that is socially and materially embedded and produced by e.g. research infrastructures, power relations, and ways of thinking; 2. considering how agency is distributed between model, world, data, modeller in model construction; 3. creating heterogenous collectives which together occupy the formerly individualised subject position; and 4. using agonism as an epistemic virtue to retain and work with significant differentiations of social-ecological dynamics throughout the modelling process. [ABSTRACT FROM AUTHOR]

Ausgehend von einer Analyse des sogenannten »Verstockungsauftrags« in Jes 6,9–10 untersucht der Beitrag Konzeptionen von Vulnerabilität im Buch. Während im Ersten Jesaja die Vorstellung der situativen Verwundung dominiert, gehen die Texte im Bereich des Zweiten Jesaja von einer ontologischen Verwundung aus. Die zwei Vorstellungen gehen auf unterschiedliche Krisenerfahrungen zurück, die die theologiegeschichtliche Überlieferung ausbilden und sich für die Rezipientenkreise als resilienzfördernd erwiesen haben. Starting from an analysis of the so-called »hardening saying« in Isa 6:9–10, the article analyses conceptions of vulnerability in the book. While in First Isaiah, the idea of situational vulnerability prevails, the texts in Second Isaiah speak of ontological vulnerability. The two concepts origin from different experiences of crisis that prove formative for the history of theology and bring about resilience for the recipients. [ABSTRACT FROM AUTHOR]

Several areas of wireless networking, such as wireless sensor networks or the Internet of Things, require application data to be distributed to multiple receivers in an area beyond the transmission range of a single node. This can be achieved by using the wireless medium's broadcast property when retransmitting data. Due to the energy constraints of typical wireless devices, a broadcasting scheme that consumes as little energy as possible is highly desirable. In this article, we present a novel multi-hop data dissemination protocol called BTP. It uses a game-theoretical model to construct a spanning tree in a decentralized manner to minimize the total energy consumption of a network by minimizing the transmission power of each node. Although BTP is based on a game-theoretical model, it neither requires information exchange between distant nodes nor time synchronization during its operation, and it inhibits graph cycles effectively. The protocol is evaluated in Matlab and NS-3 simulations and through real-world implementation on a testbed of 75 Raspberry Pis. The evaluation conducted shows that our proposed protocol can achieve a total energy reduction of up to 90% compared to a simple broadcast protocol in real-world experiments. [ABSTRACT FROM AUTHOR]

The article analyses the theology of homecoming in the book of Isaiah and makes a case for using resilience theory as a hermeneutical frame for the task of Hebrew Scripture theology. Defined as "positive adaptation despite adversity", resilience builds on the crisis setting of wide parts of the Hebrew Scriptures and demonstrates that the formation of theology represents a resilience discourse. In the case of the Isaianic prophecies of return, three concepts of return are distinguished (return, gathering and homecoming, a second Exodus) that respond to the adversities of exile and diaspora. Thus, the prophecies offer a literary home that the different religious communities through time can inhabit. [ABSTRACT FROM AUTHOR]

Mobile edge computing based on cloudlets is an emerging paradigm to improve service quality by bringing computation and storage facilities closer to end users and reducing operating cost for infrastructure providers (IPs) and service providers (SPs). To maximize their individual benefits, IP and SP have to reach an agreement about placing and executing services on particular cloudlets. We show that a Nash Bargaining Solution (NBS) yields the optimal solution with respect to social cost and fairness if IP and SP have complete information about the parameters of their mutual cost functions. However, IP and SP might not be willing or able to share all information due to business secrets or technical limitations. Therefore, we present a novel iterative bargaining approach without complete mutual information to achieve substantial cost reductions for both IP and SP. Furthermore, we investigate how different degrees of information sharing impact social cost and fairness of the different approaches. Our evaluation based on the mobile augmented reality game Ingress shows that our approach achieves up to about 82% of the cost reduction that the NBS achieves and a cost reduction of up to 147% compared to traditional Take-it-or-Leave-it approaches, despite incomplete information. [ABSTRACT FROM AUTHOR]

In this work we study different scheduling problems in the downlink of a Frequency Division Duplex multiuser wireless system that employs a hybrid precoding antenna architecture for massive Multiple Input Multiple Output. In this context, we propose a scheduling framework using Reinforcement Learning (RL) tools, namely Contextual Multi-Armed Bandits (CMAB), that can dynamically adapt themselves to solve three scheduling problems, which are: i) Maximum Throughput (MT); ii) Maximum Throughput with Fairness Guarantees (MTFG), and; iii) Maximum Throughput with QoS Guarantees (MTQG), which are well-known relevant problems. Before performing scheduling itself, we exploit statistical Channel State Information (CSI) to create clusters of spatially compatible User Equipmentss (UEss). This structure, combined with the usage of Zero-Forcing precoding, allows us to reduce the scheduler complexity by considering each cluster as an independent virtual RL scheduling agent. Next, we apply a new learning-based scheduler aiming to optimize the desired system performance metric. Moreover, only scheduled UEss need to feed back instantaneous equivalent CSI, which also reduces the signaling overhead of the proposal. The superiority of the proposed framework is demonstrated through numerical simulations in comparison with reference solutions. [ABSTRACT FROM AUTHOR]

In code-division multiple-access (CDMA) systems transmitting over time-varying multipath channels, both inter-symbol interference (ISI) and multiple-access interference (MAI) arise. The conventional suboptimum receiver consisting of a bank of matched filters is often inefficient because interference is treated as noise. The optimum multiuser detector is too complex to be implemented at present. In this paper, four suboptimum detection techniques based on zero forcing (ZF) and minimum mean-square-error (MMSE) equalization with and without decision feedback (DF) are presented and compared. They combat both ISI and MAI. The computational complexity of all four equalizers is essentially the same. All four equalizers are independent of the size of the data symbol alphabet. It is shown that the performance of the MMSE equalizers is better than that of the corresponding ZF equalizers. Furthermore, the performance of the equalizers with DF is better than that of the corresponding equalizers without DF. The impairing effect of error propagation on the equalizers with DF is reduced by channel sorting.

Abstract We consider non-regenerative multi-group multi-way (MGMW) relaying. A half-duplex non-regenerative multi-antenna relay station (RS) assists multiple communication groups. In each group, multiple half-duplex nodes exchange messages. In our proposal, the required number of communication phases is equal to the maximum number of nodes among the groups. In the first phase, all nodes transmit simultaneously to the RS. Assuming perfect channel state information is available at the RS, in the following broadcast (BC) phases the RS applies transceive beamforming to its received signal and transmits simultaneously to all nodes. We propose three BC strategies for the BC phases: unicasting, multicasting and hybrid uni/multicasting. For the multicasting strategy, network coding is applied to maintain the same number of communication phases as for the other strategies. We address transceive beamforming maximising the sum rate of non-regenerative MGMW relaying. Due to the high complexity of finding the optimum transceive beamforming maximising the sum rate, we design generalised low complexity transceive beamforming algorithms for all BC strategies: matched filter, zero forcing, minimisation of mean square error and BC-strategy-aware transceive beamforming. It is shown that the sum rate performance of non-regenerative MGMW relaying depends both on the chosen BC strategies and the applied transceive beamforming at the RS.

We propose non-regenerative multi-way relaying where a half-duplex multi-antenna relay station (RS) assists multiple single-antenna nodes to communicate with each other. The required number of communication phases is equal to the number of the nodes, N. There are only one multiple-access phase, where the nodes transmit simultaneously to the RS, and broadcast (BC) phases. Two transmission methods for the BC phases are proposed, namely, multiplexing transmission and analog network coded transmission. The latter is a cooperation method between the RS and the nodes to manage the interference in the network. Assuming that perfect channel state information is available, the RS performs transceive beamforming to the received signals and transmits simultaneously to all nodes in each BC phase. We address the optimum transceive beamforming maximising the sum rate of non-regenerative multi-way relaying. Due to the nonconvexity of the optimization problem, we propose suboptimum but practical signal processing schemes. For multiplexing transmission, we propose suboptimum schemes based on zero forcing, minimising the mean square error, and maximising the signal to noise ratio. For analog network coded transmission, we propose suboptimum schemes based on matched filtering and semidefinite relaxation of maximising the minimum signal to noise ratio. It is shown that analog network coded transmission outperforms multiplexing transmission.

The multiple access solution in an IMT-Advanced mobile radio system has to meet challenging requirements such as high throughput, low delays, high flexibility, good robustness, low computational complexity, and a high power efficiency, especially in the uplink. In this paper, a novel multiple access scheme for uplinks denoted as B-IFDMA is presented. We show that this scheme is able to provide equal or better error rate performance than the Single-Carrier Frequency Division Multiple Access (SCFDMA) schemes IFDMA and LFDMA, when considering realistic channel estimation performance at the receiver and no reliable channel state information at the transmitter. We also show that B-IFDMA provides better amplifier efficiency than OFDMA and can provide better end-to-end energy efficiency than IFDMA and LFDMA. Moreover, the scheme shows a promisingly high robustness to frequency-offsets and Doppler spread. Thus, this scheme can be regarded as a promising solution for the uplink of future mobile radio systems.

The leading cause of training interruption in sport is a muscle injury, for which the standard treatment is nonsteroidal anti‐inflammatory drugs (NSAIDs). To find alternative treatments, we investigated whether the radial extracorporeal shockwave application (rESWT) could stimulate muscle regeneration. A lesion with complete rupture (grade III muscle tear) was set in the musculus rectus femoris of 12‐week‐old Wistar rats, and the NSAID diclofenac, rESWT, or a combined therapy were applied on day 0, 3, and 5 directly following the surgery. Rats were euthanized at 2, 4, and 7 days after surgery and the area of muscle lesion was excised for histological and gene expression analysis to determine the progress in the healing of damaged fibers and tissue regeneration. The best effect on muscle regeneration was observed in the group treated with rESWT alone. Monotherapy by diclofenac showed a smaller but still positive effect and lowest effects were detected when both therapies were applied. rESWT alone demonstrated a significant upregulation of the muscle markers MyoD and myosin. The presence of myosin gene expression indicated newly formed muscle fibers, which was confirmed by hematoxylin and eosin staining. Seven days after injury the amount of mononucleated cell decreased and regenerating fibers could be detected. This effect is most pronounced in the group treated with rESWT alone. In our study, shockwaves demonstrated the best effect on muscle regeneration. Therefore, we recommend prospective clinical studies to analyze the effect of rESWT after sports trauma to improve muscle regeneration and to shorten the rehabilitation. [ABSTRACT FROM AUTHOR]

We study multi-hop data-dissemination in a wireless network from one source to multiple nodes where some of the nodes of the network act as re-transmitting nodes and help the source in data dissemination. In this network, we study two scenarios; i) the transmitting nodes do not need an incentive for transmission and ii) they do need an incentive and are paid by their corresponding receiving nodes by virtual tokens. We investigate two problems; P1) network power minimization for the first scenario and P2) social cost minimization for the second scenario, defined as the total cost paid by the nodes of the network for receiving data. In this paper, to address P1 and P2, we propose centralized and decentralized approaches that determine which of the nodes of the network should act as transmitting nodes, find their transmit powers and their corresponding receiving nodes. For the sake of energy efficiency, in our model, we employ maximal-ratio combining (MRC) at the receivers so that a receiver can be served by multiple transmitters. The proposed decentralized approach is based on a non-cooperative cost-sharing game (CSG). In our proposed game, every receiving node chooses its respective transmitting nodes and consequently, a cost is assigned to it according to the power imposed on its chosen transmitting nodes. We discuss how the network is formed in a decentralized way, find the action of the nodes in the game and show that, despite being decentralized, the proposed game converges to a stable solution. To find the centralized global optimum, which is a benchmark to our decentralized approach, we use a mixed-integer-liner-program (MILP). Simulation results show that our proposed decentralized approach outperforms the conventional algorithms in terms of energy efficiency and social cost while it can address the need for an incentive for collaboration. [ABSTRACT FROM AUTHOR]

In this paper, a low-cost linear algorithm for unbiased separation of not necessarily orthogonal signals is proposed. A new view on the suitability of signals is opened which increases the variety of candidate signals for e.g. CDMA applications. The proposed algorithm can be advantageously implemented by a modified matched filter bank.

We study multi-hop broadcast in wireless networks with one source node and multiple receiving nodes. The message flow from the source to the receivers can be modeled as a tree-graph, called broadcast-tree. The problem of finding the minimum-power broadcast-tree (MPBT) is NP-complete. Unlike most of the existing centralized approaches, we propose a decentralized algorithm, based on a non-cooperative cost-sharing game. In this game, every receiving node, as a player, chooses another node of the network as its respective transmitting node for receiving the message. Consequently, a cost is assigned to the receiving node based on the power imposed on its chosen transmitting node. In our model, the total required power at a transmitting node consists of (i) the transmit power and (ii) the circuitry power needed for communication hardware modules. We develop our algorithm using the marginal contribution (MC) cost-sharing scheme and show that the optimum broadcast-tree is always a Nash equilibrium (NE) of the game. Simulation results demonstrate that our proposed algorithm outperforms conventional algorithms for the MPBT problem. Besides, we show that the circuitry power, which is usually ignored by existing algorithms, significantly impacts the energy-efficiency of the network. [ABSTRACT FROM AUTHOR]

The use of injections to treat structural muscle injuries is controversially discussed. In our controlled in vitro study, we investigated the biological impact of Actovegin and Traumeel alone and in combination on primary human skeletal muscle cells. Cells were characterized by immunofluorescence staining for myogenic factor 5 (Myf5) and MyoD, and cultured with or without Actovegin and / or Traumeel. The effects of these agents were assayed by cell viability and gene expression of the specific markers MyoD, Myf5, neural adhesion molecule (NCAM), and CD31. Myotube formation was determined by myosin staining. Neither Actovegin nor Traumeel showed toxic effects or influenced cell viability significantly. High volumes of Actovegin down-regulated gene expression of NCAM after 3 days but had no effect on MyoD, Myf5, and CD31 gene expression. High volumes of Traumeel inhibited MyoD gene expression after 3 days, whereas after 7 days MyoD expression was significantly up-regulated. The combination of both agents did not significantly influence cell viability or gene expression. This is the first study demonstrating that Actovegin and Traumeel potentially modulate human skeletal muscle cells. The relevance of these in vitro findings has to be highlighted in further in vivo studies. [ABSTRACT FROM AUTHOR]

The complexity of the mode selection and resource allocation (MS&RA) problem has hampered the commercialization progress of Device-to-Device (D2D) communication in 5G networks. Furthermore, the combinatorial nature of MS&RA has forced the majority of existing proposals to focus on constrained scenarios or offline solutions to contain the size of the problem. Given the real-time constraints in actual deployments, a reduction in computational complexity is necessary. Adaptability is another key requirement for mobile networks that are exposed to constant changes such as channel quality fluctuations and mobility. In this article, we propose an online learning technique (i.e., CBMoS) which leverages combinatorial multi-armed bandits (CMAB) to tackle the combinatorial nature of MS&RA. Furthermore, our two-stage CMAB design results in a tight model, which eliminates the theoretically feasible but practicality invalid options from the solution space. We prototype the first SDR-based D2D testbed to verify the performance of CBMoS under real-world conditions. The simulations confirm that the fast learning speed of CBMoS leads to outperforming the benchmark schemes by up to 132%. In experiments, CBMoS exhibits even higher performance (up to 142%) than in the simulations. This stems from the adaptability/fast learning speed of CBMoS in presence of high channel dynamics which cannot be captured via statistical channel models used in the simulators. [ABSTRACT FROM AUTHOR]

Countless novel approaches to communication protocols, overlay networks, and distributed middleware are published every year, yet the adoption of such novel findings in the global Internet landscape progresses at a slow pace. Many of such new communication mechanisms excel (only) under specific deployment conditions, while user mobility and application usage patterns lead to dynamic operation conditions. This mismatch is one reason that makes a wide deployment of new specialized mechanisms particularly hard as observed, for example, for multipath transport protocol extensions until the emergence of multipath transmission control protocol (TCP). This paper formalizes the concept of Transitions, i.e., a method to instrumentalize adaptivity at runtime in communication systems. It allows to exchange communication mechanisms in a running system to optimize the communication quality. In the following, we describe the building blocks required to: 1) capture the features and relations within a communication system and 2) express and optimize the decision making process in such a system. We show how this concept maps intuitively to the Internet model which makes a protocol-independent deployment of applications feasible in the future Internet. [ABSTRACT FROM AUTHOR]

Millimeter-Wave (mmWave) bands have become the de-facto candidate for 5G vehicle-to-everything (V2X) since future vehicular systems demand Gbps links to acquire the necessary sensory information for (semi)-autonomous driving. Nevertheless, the directionality of mmWave communications and its susceptibility to blockage raise severe questions on the feasibility of mmWave vehicular communications. The dynamic nature of 5G vehicular scenarios and the complexity of directional mmWave communication calls for higher context-awareness and adaptability. To this aim, we propose an online learning algorithm addressing the problem of beam selection with environment-awareness in mmWave vehicular systems. In particular, we model this problem as a contextual multi-armed bandit problem. Next, we propose a lightweight context-aware online learning algorithm, namely fast machine learning (FML), with proven performance bound and guaranteed convergence. FML exploits coarse user location information and aggregates the received data to learn from and adapt to its environment. Furthermore, we demonstrate the feasibility of a real-world implementation of FML by proposing a standard-compliant protocol based on the existing architecture of cellular networks and the forthcoming features of 5G. We also perform an extensive evaluation using realistic traffic patterns derived from Google Maps. Our evaluation shows that FML enables mmWave base stations to achieve near-optimal performance on average within 33 mins of deployment by learning from the available context. Moreover, FML remains within ~ 5% of the optimal performance by swift adaptation to system changes (i.e., blockage, traffic). [ABSTRACT FROM AUTHOR]

Abstract: The combination of the two techniques of rapid prototyping 3D‐plotting and bioactive surface functionalization is presented, with emphasis on the in vitro effect of Bone Sialoprotein (BSP) on primary human osteoblasts (hOBs). Our primary objective was to demonstrate the BSP influence on the expression of distinctive osteoblast markers in hOBs. Secondary objectives included examinations of the scaffolds' surface and the stability of BSP‐coating as well as investigations of cell viability and proliferation. 3D‐plotted calcium phosphate cement (CPC) scaffolds were coated with BSP via physisorption. hOBs were seeded on the coated scaffolds, followed by cell viability measurements, gene expression analysis and visualization. Physisorption is an effective method for BSP‐coating. Coating with higher BSP concentrations leads to enhanced BSP release. Two BSP concentrations (50 and 200 μg/mL) were examined in this study. The lower BSP concentration (50 µg/mL) decreased ALP and SPARC expression, whereas the higher BSP concentration (200 μg/mL) did not change gene marker expression. Enhanced cell viability was observed on BSP‐coated scaffolds on day 3. hOBs developed a polygonal shape and connected in an intercellular network under BSP influence. Quantitative cell morphology analyses demonstrated for BSP‐coated CPCs an enhanced cell area and reduced circularity. The strength of the above‐mentioned effects of BSP‐coated scaffolds in vivo is unknown, and future work is focusing on bone ingrowth and vascularization in vivo. © 2018 Wiley Periodicals, Inc. J Biomed Mater Res Part B: Appl Biomater, 106B: 2565–2575, 2018. [ABSTRACT FROM AUTHOR]

In mobile crowdsourcing (MCS), mobile users accomplish outsourced human intelligence tasks. MCS requires an appropriate task assignment strategy, since different workers may have different performance in terms of acceptance rate and quality. Task assignment is challenging, since a worker’s performance 1) may fluctuate, depending on both the worker’s current personal context and the task context and 2) is not known a priori, but has to be learned over time. Moreover, learning context-specific worker performance requires access to context information, which may not be available at a central entity due to communication overhead or privacy concerns. In addition, evaluating worker performance might require costly quality assessments. In this paper, we propose a context-aware hierarchical online learning algorithm addressing the problem of performance maximization in MCS. In our algorithm, a local controller (LC) in the mobile device of a worker regularly observes the worker’s context, her/his decisions to accept or decline tasks and the quality in completing tasks. Based on these observations, the LC regularly estimates the worker’s context-specific performance. The mobile crowdsourcing platform (MCSP) then selects workers based on performance estimates received from the LCs. This hierarchical approach enables the LCs to learn context-specific worker performance and it enables the MCSP to select suitable workers. In addition, our algorithm preserves worker context locally, and it keeps the number of required quality assessments low. We prove that our algorithm converges to the optimal task assignment strategy. Moreover, the algorithm outperforms simpler task assignment strategies in experiments based on synthetic and real data. [ABSTRACT FROM AUTHOR]

Background: Uterine leiomyosarcoma (uLMS) is a rare tumor that accounts for 1% of all uterine malignancies. In spite of adequate surgical resection of uLMS, even in the early stage, patients remain at high risk for local and distant recurrence. Therefore, the treatment of advanced uLMS represents a considerable challenge. Methods: We report the case of a 47-year-old woman who presented with uLMS with abnormal vaginal bleeding. Results: The patient underwent a total hysterectomy and bilateral adnexectomy, which was followed by 1 year progression-free survival without adjuvant therapy. Thereafter, new lung metastases and local progression at the vaginal stump were observed. Chemotherapy with ifosfamide and doxorubicin was administered. However, after 4 cycles, a CT scan revealed disease progression in the lung metastases. Subsequently, the patient was treated with trabectedin at a dose of 1.5 mg/m² for 6 cycles resulting in complete remission of the lung metastases as well as partial remission of the mass in the vaginal stump after 9 cycles of trabectedin. The patient is currently on maintenance therapy with trabectedin and has no recurrence. Conclusion: Trabectedin seems to be an efficient option for patients with uLMS as demonstrated by a long-lasting response in a pretreated patient with an acceptable safety profile with no signs of cumulative toxicity. [ABSTRACT FROM AUTHOR]

Content caching in small base stations or wireless infostations is considered to be a suitable approach to improve the efficiency in wireless content delivery. Placing the optimal content into local caches is crucial due to storage limitations, but it requires knowledge about the content popularity distribution, which is often not available in advance. Moreover, local content popularity is subject to fluctuations, since mobile users with different interests connect to the caching entity over time. Which content a user prefers may depend on the user’s context. In this paper, we propose a novel algorithm for context-aware proactive caching. The algorithm learns context-specific content popularity online by regularly observing context information of connected users, updating the cache content and observing cache hits subsequently. We derive a sublinear regret bound, which characterizes the learning speed and proves that our algorithm converges to the optimal cache content placement strategy in terms of maximizing the number of cache hits. Furthermore, our algorithm supports service differentiation by allowing operators of caching entities to prioritize customer groups. Our numerical results confirm that our algorithm outperforms state-of-the-art algorithms in a real world data set, with an increase in the number of cache hits of at least 14%. [ABSTRACT FROM PUBLISHER]

In this paper, we propose a novel algorithm to maximize the sum-rate in interference-limited scenarios where each user decodes its own message with the presence of unknown interferences and noise. The problem of adapting the transmit and receive filters of the users to maximize the sum-rate with a transmit power constraint is nonconvex. Our novel approach is to formulate the sum-rate maximization problem as an equivalent multiconvex optimization problem by adding two sets of auxiliary variables. An iterative algorithm, which alternatingly adjusts the system variables and the auxiliary variables is proposed to solve the multiconvex optimization problem and we show that the algorithm converges to a stationary point. The proposed algorithm is applied to a downlink cellular scenario consisting of several cells each of which contains a base station serving several mobile stations. We examine the two cases, with or without several half-duplex amplify-and-forward relays assisting the transmission. A sum power constraint at the base stations and at the relays are assumed. The applicability of our approach to the individual power constraints case is also shown. Finally, we show that the proposed multiconvex formulation of the sum-rate maximization problem is applicable to many other wireless systems in which the estimated data symbols are multiaffine functions of the system variables. [ABSTRACT FROM PUBLISHER]

Orthopedic implant failure due to aseptic loosening and mechanical instability remains a major problem in total joint replacement. Improving osseointegration at the bone-implant interface may reduce micromotion and loosening. Bone sialoprotein (BSP) has been shown to enhance bone formation when coated onto titanium femoral implants and in rat calvarial defect models. However, the most appropriate method of BSP coating, the necessary level of BSP coating, and the effect of BSP coating on cell behavior remain largely unknown. In this study, BSP was covalently coupled to titanium surfaces via an aminosilane linker (APTES), and its properties were compared to BSP applied to titanium via physisorption and untreated titanium. Cell functions were examined using primary human osteoblasts (hOBs) and L929 mouse fibroblasts. Gene expression of specific bone turnover markers at the RNA level was detected at different intervals. Cell adhesion to titanium surfaces treated with BSP via physisorption was not significantly different from that of untreated titanium at any time point, whereas BSP application via covalent coupling caused reduced cell adhesion during the first few hours in culture. Cell migration was increased on titanium disks that were treated with higher concentrations of BSP solution, independent of the coating method. During the early phases of hOB proliferation, a suppressive effect of BSP was observed independent of its concentration, particularly when BSP was applied to the titanium surface via physisorption. Although alkaline phosphatase activity was reduced in the BSP-coated titanium groups after 4 days in culture, increased calcium deposition was observed after 21 days. In particular, the gene expression level of RUNX2 was upregulated by BSP. The increase in calcium deposition and the stimulation of cell differentiation induced by BSP highlight its potential as a surface modifier that could enhance the osseointegration of orthopedic implants. Both physisorption and covalent coupling of BSP are similarly effective, feasible methods, although a higher BSP concentration is recommended. [ABSTRACT FROM AUTHOR]

The identification of important features in multi-electrode recordings requires the decomposition of data in order to disclose relevant features and to offer a clear graphical representation. This can be a demanding task. Parallel Factor Analysis (PARAFAC; Hitchcock, 1927; Carrol and Chang, 1970; Harshman, 1970) is a method to decompose multi-dimensional arrays in order to focus on the features of interest, and provides a distinct illustration of the results. We applied PARAFAC to analyse spatio-temporal patterns in the functional connectivity between neurons, as revealed in their spike trains recorded in cat primary visual cortex (area 18). During these recordings we reversibly deactivated feedback connections from higher visual areas in the pMS (posterior middle suprasylvian) cortex in order to study the impact of these top-down signals. Cross correlation was computed for every possible pair of the 16 electrodes in the electrode array. PARAFAC was then used to reveal the effects of time, stimulus, and deactivation condition on the correlation patterns. Our results show that PARAFAC is able to reliably extract changes in correlation strength for different experimental conditions and display the relevant features. Thus, PARAFAC proves to be well-suited for the use in the context of electrophysiological (action potential) recordings. [ABSTRACT FROM AUTHOR]