Polycaprolactone-based scaffold plus recombinant human bone morphogenetic protein (rhBMP-2) in an ovine model of anterior spinal fusion

Synthetic scaffolds combined with growth factors have the potential to replace allograft or autograft as a graft material for spinal interbody fusion. Such tissue engineering approaches may be useful in Adolescent Idiopathic Scoliosis (AIS) surgery, however there are no studies to date examining the use of such biodegradable implants in combination with biologics in a thoracic spine model. This in vivo study examines the use of biodegradable polycaprolactone (PCL) based scaffolds with rhBMP-2 as a bone graft substitute in a sheep thoracic fusion model, where an anterior approach is used to simulate minimally invasive surgical deformity correction in the setting of AIS.

Establishment and characterisation of an open mini-thoracotomy surgical approach to an ovine thoracic spine fusion model

Background A large animal model is required for assessment of minimally invasive, tissue engineering based approaches to thoracic spine fusion, with relevance to deformity correction surgery for human adolescent idiopathic scoliosis. Here we develop a novel open mini–thoracotomy approach in an ovine model of thoracic interbody fusion which allows assessment of various fusion constructs, with a focus on novel, tissue engineering based interventions. Methods The open mini-thoracotomy surgical approach was developed through a series of mock surgeries, and then applied in a live sheep study. Customized scaffolds were manufactured to conform with intervertebral disc space clearances required of the study. Twelve male Merino sheep aged 4 to 6 years and weighing 35 – 45 kg underwent the abovementioned procedure and were divided into two groups of six sheep at survival timelines of 6 and 12 months. Each sheep underwent a 3-level discectomy (T6/7, T8/9 and T10/11) with randomly allocated implantation of a different graft substitute at each of the three levels; (i) polycaprolactone (PCL) based scaffold plus 0.54μg rhBMP-2, (ii) PCL-based scaffold alone or (iii) autograft. The sheep were closely monitored post- operatively for signs of pain (i.e. gait abnormalities/ teeth gnawing/ social isolation). Fusion assessments were conducted post-sacrifice using Computed Tomography and hard-tissue histology. All scientific work was undertaken in accordance with the study protocol has been approved by the Institute's committee on animal research. Results. All twelve sheep were successfully operated on and reached the allotted survival timelines, thereby demonstrating the feasibility of the surgical procedure and post-operative care. There were no significant complications and during the post-operative period the animals did not exhibit marked signs of distress according to the described assessment criteria. Computed Tomographic scanning demonstrated higher fusion grades in the rhBMP-2 plus PCL-based scaffold group in comparison to either PCL-based scaffold alone or autograft. These results were supported by histological evaluation of the respective groups. Conclusion. This novel open mini-thoracotomy surgical approach to the ovine thoracic spine represents a safe surgical method which can reproducibly form the platform for research into various spine tissue engineered constructs (TEC) and their fusion promoting properties.

A multidimensional collaborative filtering fusion approach with dimensionality reduction

Multidimensional data are getting increasing attention from researchers for creating better recommender systems in recent years. Additional metadata provides algorithms with more details for better understanding the interaction between users and items. While neighbourhood-based Collaborative Filtering (CF) approaches and latent factor models tackle this task in various ways effectively, they only utilize different partial structures of data. In this paper, we seek to delve into different types of relations in data and to understand the interaction between users and items more holistically. We propose a generic multidimensional CF fusion approach for top-N item recommendations. The proposed approach is capable of incorporating not only localized relations of user-user and item-item but also latent interaction between all dimensions of the data. Experimental results show significant improvements by the proposed approach in terms of recommendation accuracy.

Partial intervertebral fusion secures successful outcomes after thoracoscopic anterior scoliosis correction: A low-dose computed tomography study

Study Design Retrospective review of prospectively collected data. Objectives To analyze intervertebral (IV) fusion after thoracoscopic anterior spinal fusion (TASF) and explore the relationship between fusion scores and key clinical variables. Summary of Background Information TASF provides comparable correction with some advantages over posterior approaches but reported mechanical complications, and their relationship to non-union and graft material is unclear. Similarly, the optimal combination of graft type and implant stiffness for effecting successful radiologic union remains undetermined. Methods A subset of patients from a large single-center series who had TASF for progressive scoliosis underwent low-dose computed tomographic scans 2 years after surgery. The IV fusion mass in the disc space was assessed using the 4-point Sucato scale, where 1 indicates <50% and 4 indicates 100% bony fusion of the disc space. The effects of rod diameter, rod material, graft type, fusion level, and mechanical complications on fusion scores were assessed. Results Forty-three patients with right thoracic major curves (mean age 14.9 years) participated in the study. Mean fusion scores for patient subgroups ranged from 1.0 (IV levels with rod fractures) to 2.2 (4.5-mm rod with allograft), with scores tending to decrease with increasing rod size and stiffness. Graft type (autograft vs. allograft) did not affect fusion scores. Fusion scores were highest in the middle levels of the rod construct (mean 2.52), dropping off by 20% to 30% toward the upper and lower extremities of the rod. IV levels where a rod fractured had lower overall mean fusion scores compared to levels without a fracture. Mean total Scoliosis Research Society (SRS) questionnaire scores were 98.9 from a possible total of 120, indicating a good level of patient satisfaction. Conclusions Results suggest that 100% radiologic fusion of the entire disc space is not necessary for successful clinical outcomes following thoracoscopic anterior selective thoracic fusion.

Comparative Analysis of Pilot-Assisted Distributed Cophasing Approaches in Wireless Sensor Networks

This paper compares and analyzes the performance of distributed cophasing techniques for uplink transmission over wireless sensor networks. We focus on a time-division duplexing approach, and exploit the channel reciprocity to reduce the channel feedback requirement. We consider periodic broadcast of known pilot symbols by the fusion center (FC), and maximum likelihood estimation of the channel by the sensor nodes for the subsequent uplink cophasing transmission. We assume carrier and phase synchronization across the participating nodes for analytical tractability. We study binary signaling over frequency-flat fading channels, and quantify the system performance such as the expected gains in the received signal-to-noise ratio (SNR) and the average probability of error at the FC, as a function of the number of sensor nodes and the pilot overhead. Our results show that a modest amount of accumulated pilot SNR is sufficient to realize a large fraction of the maximum possible beamforming gain. We also investigate the performance gains obtained by censoring transmission at the sensors based on the estimated channel state, and the benefits obtained by using maximum ratio transmission (MRT) and truncated channel inversion (TCI) at the sensors in addition to cophasing transmission. Simulation results corroborate the theoretical expressions and show the relative performance benefits offered by the various schemes.

Image fusion in GRDSS for Land use Mapping

Image fusion techniques are useful to integrate the geometric detail of a high-resolution panchromatic (PAN) image and the spectral information of a low-resolution multispectral (MSS) image, particularly important for understanding land use dynamics at larger scale (1:25000 or lower), which is required by the decision makers to adopt holistic approaches for regional planning. Fused images can extract features from source images and provide more information than one scene of MSS image. High spectral resolution aids in identification of objects more distinctly while high spatial resolution allows locating the objects more clearly. The geoinformatics technologies with an ability to provide high-spatial-spectral-resolution data helps in inventorying, mapping, monitoring and sustainable management of natural resources. Fusion module in GRDSS, taking into consideration the limitations in spatial resolution of MSS data and spectral resolution of PAN data, provide high-spatial-spectral-resolution remote sensing images required for land use mapping on regional scale. GRDSS is a freeware GIS Graphic User Interface (GUI) developed in Tcl/Tk is based on command line arguments of GRASS (Geographic Resources Analysis Support System) with the functionalities for raster analysis, vector analysis, site analysis, image processing, modeling and graphics visualization. It has the capabilities to capture, store, process, analyse, prioritize and display spatial and temporal data.

OPTICAL FLOW ESTIMATION USING APPROXIMATE NEAREST NEIGHBOR FIELD FUSION

This paper proposes an optical flow algorithm by adapting Approximate Nearest Neighbor Fields (ANNF) to obtain a pixel level optical flow between image sequence. Patch similarity based coherency is performed to refine the ANNF maps. Further improvement in mapping between the two images are obtained by fusing bidirectional ANNF maps between pair of images. Thus a highly accurate pixel level flow is obtained between the pair of images. Using pyramidal cost optimization, the pixel level optical flow is further optimized to a sub-pixel level. The proposed approach is evaluated on the middlebury dataset and the performance obtained is comparable with the state of the art approaches. Furthermore, the proposed approach can be used to compute large displacement optical flow as evaluated using MPI Sintel dataset.

Study on dynamic fusion barrier in heavy-ion fusion reactions

By means of the improved quantum molecular dynamics model, the incident energy dependent dynamical fusion potential barriers for heavy nucleus reaction systems are investigated. It is found that with decrease of incident energy the lowest dynamic barrier is obtained which approaches to the adiabatic static barrier and with increase of the incident energy the dynamic barrier goes up to the diabatic static barrier. Based on the dynamical study a microscopic understanding of the extra-push in fusion reactions of heavy systems and a new explanation of tunneling process for the fusion at the incident energy below the static and above the lowest dynamic barrier are presented. In order to understand the energy dependence of the dynamical barrier we also pay a great attention to study the neck formation and shape deformation during the dynamic lowering of the barrier.

Structural analysis of SNARE motifs from sea perch, Lateolabrax japonicus by computerized approaches

Three cDNA sequences encoding four SNARE (N-ethylmaleimide-sensitive fusion protein attachment protein receptors) motifs were cloned from sea perch, and the deduced peptide sequences were analyzed for structural prediction by using 14 different web servers and softwares. The "ionic layer" structure, the three dimensional extension and conformational characters of the SNARE 7S core complex by using bioinformatics approaches were compared respectively with those from mammalian X-ray crystallographic investigations. The result suggested that the formation and stabilization of fish SNARE core complex might be driven by hydrophobic association, hydrogen bond among R group of core amino acids and electrostatic attraction at molecular level. This revealed that the SNARE proteins interaction of the fish may share the same molecular mechanism with that of mammal, indicating the universality and solidity of SNARE core complex theory. This work is also an attempt to get the protein 3D structural information which appears to be similar to that obtained through X-ray crystallography, only by using computerized approaches. (C) 2007 Elsevier Ltd. All rights reserved.

Biologically Inspired Approaches to Automated Feature Extraction and Target Recognition

Ongoing research at Boston University has produced computational models of biological vision and learning that embody a growing corpus of scientific data and predictions. Vision models perform long-range grouping and figure/ground segmentation, and memory models create attentionally controlled recognition codes that intrinsically cornbine botton-up activation and top-down learned expectations. These two streams of research form the foundation of novel dynamically integrated systems for image understanding. Simulations using multispectral images illustrate road completion across occlusions in a cluttered scene and information fusion from incorrect labels that are simultaneously inconsistent and correct. The CNS Vision and Technology Labs (cns.bu.edulvisionlab and cns.bu.edu/techlab) are further integrating science and technology through analysis, testing, and development of cognitive and neural models for large-scale applications, complemented by software specification and code distribution.

Minimal residual disease detection in childhood acute lymphoblastic leukaemia patients at multiple time-points reveals high levels of concordance between molecular and immunophenotypic approaches

In this single centre study of childhood acute lymphoblastic leukaemia (ALL) patients treated on the Medical Research Council UKALL 97/99 protocols, it was determined that minimal residual disease (MRD) detected by real time quantitative polymerase chain reaction (RQ-PCR) and 3-colour flow cytometry (FC) displayed high levels of qualitative concordance when evaluated at multiple time-points during treatment (93.38%), and a combined use of both approaches allowed a multi time-point evaluation of MRD kinetics for 90% (53/59) of the initial cohort. At diagnosis, MRD markers with sensitivity of at least 0.01% were identified by RQ-PCR detection of fusion gene transcripts, IGH/TRG rearrangements, and FC. Using a combined RQ-PCR and FC approach, the evaluation of 367 follow-up BM samples revealed that the detection of MRD >1% at Day 15 (P = 0.04), >0.01% at the end of induction (P = 0.02), >0.01% at the end of consolidation (P = 0.01), >0.01% prior to the first delayed intensification (P = 0.01), and >0.1% prior to the second delayed intensification and continued maintenance (P = 0.001) were all associated with relapse and, based on early time-points (end of induction and consolidation) a significant log-rank trend (P = 0.0091) was noted between survival curves for patients stratified into high, intermediate and low-risk MRD groups.

The application of atomic physics within impurity diagnostics for fusion plasmas

With the focus of ITER on the transport and emission properties of tungsten, generating atomic data for complex species has received much interest. Focusing on impurity influx diagnostics, we discuss recent work on heavy species. Perturbative approaches do not work well for near neutral systems so non-perturbative data are required, presenting a particular challenge for these influx diagnostics. Recent results on Mo+ are given as an illustration of how the diagnostic applications can guide the theoretical calculations for such systems.

Information Exchange and Fusion in Dynamic and Heterogeneous Distributed Environments

Context awareness, dynamic reconfiguration at runtime and heterogeneity are key characteristics of future distributed systems, particularly in ubiquitous and mobile computing scenarios. The main contributions of this dissertation are theoretical as well as architectural concepts facilitating information exchange and fusion in heterogeneous and dynamic distributed environments. Our main focus is on bridging the heterogeneity issues and, at the same time, considering uncertain, imprecise and unreliable sensor information in information fusion and reasoning approaches. A domain ontology is used to establish a common vocabulary for the exchanged information. We thereby explicitly support different representations for the same kind of information and provide Inter-Representation Operations that convert between them. Special account is taken of the conversion of associated meta-data that express uncertainty and impreciseness. The Unscented Transformation, for example, is applied to propagate Gaussian normal distributions across highly non-linear Inter-Representation Operations. Uncertain sensor information is fused using the Dempster-Shafer Theory of Evidence as it allows explicit modelling of partial and complete ignorance. We also show how to incorporate the Dempster-Shafer Theory of Evidence into probabilistic reasoning schemes such as Hidden Markov Models in order to be able to consider the uncertainty of sensor information when deriving high-level information from low-level data. For all these concepts we provide architectural support as a guideline for developers of innovative information exchange and fusion infrastructures that are particularly targeted at heterogeneous dynamic environments. Two case studies serve as proof of concept. The first case study focuses on heterogeneous autonomous robots that have to spontaneously form a cooperative team in order to achieve a common goal. The second case study is concerned with an approach for user activity recognition which serves as baseline for a context-aware adaptive application. Both case studies demonstrate the viability and strengths of the proposed solution and emphasize that the Dempster-Shafer Theory of Evidence should be preferred to pure probability theory in applications involving non-linear Inter-Representation Operations.

Adjuvant-free immunization with hemagglutinin-Fc fusion proteins as an approach to influenza vaccines

The hemagglutinins (HAs) of human H1 and H3 influenza viruses and avian H5 influenza virus were produced as recombinant fusion proteins with the human immunoglobulin Fc domain. Recombinant HA-human immunoglobulin Fc domain (HA-HuFc) proteins were secreted from baculovirus-infected insect cells as glycosylated oligomer HAs of the anticipated molecular mass, agglutinated red blood cells, were purified on protein A, and were used to immunize mice in the absence of adjuvant. Immunogenicity was demonstrated for all subtypes, with the serum samples demonstrating subtype-specific hemagglutination inhibition, epitope specificity similar to that seen with virus infection, and neutralization. HuFc-tagged HAs are potential candidates for gene-to-vaccine approaches to influenza vaccination.

Robust multimodal face and fingerprint fusion in the presence of spoofing attacks

Anti-spoofing is attracting growing interest in biometrics, considering the variety of fake materials and new means to attack biometric recognition systems. New unseen materials continuously challenge state-of-the-art spoofing detectors, suggesting for additional systematic approaches to target anti-spoofing. By incorporating liveness scores into the biometric fusion process, recognition accuracy can be enhanced, but traditional sum-rule based fusion algorithms are known to be highly sensitive to single spoofed instances. This paper investigates 1-median filtering as a spoofing-resistant generalised alternative to the sum-rule targeting the problem of partial multibiometric spoofing where m out of n biometric sources to be combined are attacked. Augmenting previous work, this paper investigates the dynamic detection and rejection of livenessrecognition pair outliers for spoofed samples in true multi-modal configuration with its inherent challenge of normalisation. As a further contribution, bootstrap aggregating (bagging) classifiers for fingerprint spoof-detection algorithm is presented. Experiments on the latest face video databases (Idiap Replay- Attack Database and CASIA Face Anti-Spoofing Database), and fingerprint spoofing database (Fingerprint Liveness Detection Competition 2013) illustrate the efficiency of proposed techniques.