Prevention of a chronic progressive form of experimental autoimmune encephalomyelitis by an antibody against mucosal addressin cell adhesion molecule-1, given early in the course of disease progression.

A role for α4 and β7 integrins in mediating leucocyte entry into the central nervous system in the multiple sclerosis (MS)-like disease experimental autoimmune encephalomyelitis (EAE) has been demonstrated. However, the individual contributions of their respective ligands mucosal addressin cell adhesion molecule-1 (MAdCAM-1), vascular cell adhesion molecule-1 (VCAM-1) and E-cadherin expressed on the blood-brain barrier has not been determined. In the present paper, it is shown that an antibody directed against MAdCAM-1, the preferential ligand for α4β7, effectively prevented the development of a progressive, non-remitting, form of EAE, actively induced by injection of myelin oligodendrocyte glycoprotein peptide (MOG(_35-55)) autoantigen. Combinational treatment with both anti-MAdCAM-1, VCAM-1, and intercellular adhesion molecule-1 (ICAM-1) (ligand for integrin lymphocyte function-associated antigen (LFA)-1) mAbs led to more rapid remission than that obtained with anti-MAdCAM-1 antibody alone. However, neither MAdCAM-1 monotherapy, nor combinational antibody blockade was preventative when administered late in the course of disease progression. In conclusion, MAdCAM-1 plays a major contributory role in the progression of chronic EAE and is a potential therapeutic target for the treatment of MS. Critically, antivascular addressin therapy must be given eaA role for alpha4 and beta7 integrins in mediating leucocyte entry into the central nervous system in the multiple sclerosis (MS)-like disease experimental autoimmune encephalomyelitis (EAE) has been demonstrated. However, the individual contributions of their respective ligands mucosal addressin cell adhesion molecule-1 (MAdCAM-1), vascular cell adhesion molecule-1 (VCAM-1) and E-cadherin expressed on the blood-brain barrier has not been determined. In the present paper, it is shown that an antibody directed against MAdCAM-1, the preferential ligand for alpha4beta7, effectively prevented the development of a progressive, non-remitting, form of EAE, actively induced by injection of myelin oligodendrocyte glycoprotein peptide (MOG(35-55)) autoantigen. Combinational treatment with both anti-MAdCAM-1, VCAM-1, and intercellular adhesion molecule-1 (ICAM-1) (ligand for integrin lymphocyte function-associated antigen (LFA)-1) mAbs led to more rapid remission than that obtained with anti-MAdCAM-1 antibody alone. However, neither MAdCAM-1 monotherapy, nor combinational antibody blockade was preventative when administered late in the course of disease progression. In conclusion, MAdCAM-1 plays a major contributory role in the progression of chronic EAE and is a potential therapeutic target for the treatment of MS. Critically, antivascular addressin therapy must be given early in the course of disease prior to the establishment of irreversible damage if it is to be effective, as a single treatment modality.

Progressive traditionalists : the emergence of a new discourse in Indonesia's Nahdlatul Ulama during the Addurrahman Wahid era

Studies the emergence of progressive thought amongst younger ulama, or Islamic scholars in Indonesia. Unlike most earlier traditionalist scholars, who were essentially limited to engaging with the intellectual heritage of mediaeval ulama, these young ulama are able to bridge the past and the present by synthesizing knowledge traditions.

The economic impact of progressive neurological illness on quality of life in Australia

The current study examined the impact of financial costs and self-reported economic pressure on the quality of life of patients with progressive neurological illness. Participants were 423 people from four illness groups in Australia. Participants completed measures of: 1. quality of life, 2. income, 3. expenses, 4. economic pressure, 5. social support, 6. relationship satisfaction, and 7. severity of illness. There was a strong negative association between quality of life and economic pressure (but not income or expenses) for all groups. Subjective assessment of economic pressure was strongly associated with quality of life for people with motor neurone disease and multiple sclerosis. Implications of these results for assisting people with progressive neurological illnesses to cope with the financial changes that occur due to their illness are discussed.

Predictors of quality of life in carers for people with a progressive neurological illness: a longitudinal study

Purpose The aim of the present research was to determine the predictors of quality of life (QOL) among carers for people living with a chronic degenerative neurological illness, with comparisons of the differences in significant predictors of QOL between illness groups.
Methods Psychosocial and economic variables were examined among 192 carers for people living at home with motor neurone disease, Huntington’s disease, multiple sclerosis, and Parkinson’s, over a twelve-month period, to determine their contribution to the prediction of carer QOL.
Results Mood was the only consistent predictor of carer QOL across groups; however, marital relationship satisfaction, social support satisfaction, income, and economic pressure significantly predicted carer QOL for at least one of the illness groups, in addition to mood.
Conclusions The findings highlight the importance of recognising the varying roles that psychosocial and economic variables play on the prediction of carer QOL within each of these illness groups.

Service-oriented wireless sensor networks and an energy-aware mesh routing algorithm

Service-oriented wireless sensor networks (WSNs) are being paid more and more attention because service computing can hide complexity of WSNs and enables simple and transparent access to individual sensor nodes. Existing WSNs mainly use IEEE 802.15.4 as their communication specification, however, this protocol suite cannot support IP-based routing and service-oriented access because it only specifies a set of physical- and MAC-layer protocols. For inosculating WSNs with IP networks, IEEE proposed a 6LoWPAN (IPv6 over LoW Power wireless Area Networks) as the adaptation layer between IP and MAC layers. However, it is still a challenging task how to discover and manage sensor resources, guarantee the security of WSNs and route messages over resource-restricted sensor nodes. This paper is set to address such three key issues. Firstly, we propose a service-oriented WSN architectural model based on 6LoWPAN and design a lightweight service middleware SOWAM (service-oriented WSN architecture middleware), where each sensor node provides a collection of services and is managed by our SOWAM. Secondly, we develop a security mechanism for the authentication and secure connection among users and sensor nodes. Finally, we propose an energyaware mesh routing protocol (EAMR) for message transmission in a WSN with multiple mobile sinks, aiming at prolonging the lifetime of WSNs as long as possible. In our EAMR, sensor nodes with the residual energy lower than a threshold do not forward messages for other nodes until the threshold is leveled down. As a result, the energy consumption is evened over sensor nodes significantly. The experimental results demonstrate the feasibility of our service-oriented approach and lightweight middleware SOWAM, as well as the effectiveness of our routing algorithm EAMR.

Extracting 3D mesh skeletons using antipodal points locations

Finding the skeleton of a 3D mesh is an essential task for many applications such as mesh animation, tracking, and 3D registeration. In recent years, new technologies in computer vision such as Microsoft Kinect have proven that a mesh skeleton can be useful such as in the case of human machine interactions. To calculate the 3D mesh skeleton, the mesh properties such as topology and its components relations are utilized. In this paper, we propose the usage of a novel algorithm that can efficiently calculate a vertex antipodal point. A vertex antipodal point is the diametrically opposite point that belongs to the same mesh. The set of centers of the connecting lines between each vertex and its antipodal point represents the 3D mesh desired skeleton. Post processing is completed for smoothing and fitting centers into optimized skeleton parts. The algorithm is tested on different classes of 3D objects and produced efficient results that are comparable with the literature. The algorithm has the advantages of producing high quality skeletons as it preserves details. This is suitable for applications where the mesh skeleton mapping is required to be kept as much as possible.

Towards a parameterless 3D mesh segmentation

This paper proposes a novel technique for 3D mesh segmentation using multiple 2D pose footprints. Such problem has been targeted many times in the literature, but still requires further development especially in the area of automation. The proposed algorithm applies cognition theory and provides a generic technique to form a 3D bounding contour from a seed vertex on the 3D mesh. Forming the cutlines is done in both 2D and 3D spaces to enrich the available information for the search processes. The main advantage of this technique is the possibility to operate without any object-dependent parameters. The parameters that can be used will only be related to the used cognition theory and the seeds suggestion, which is another advantage as the algorithm can be generic to more than one theory of segmentation or to different criterion. The results are competitive against other algorithms, which use object-dependent or tuning parameters. This plus the autonomy and generality features, provides an efficient and usable approach for segmenting 3D meshes and at the same time to reduce the computation load.

Progressive clustering based method for protein function prediction

In recent years, significant effort has been given to predicting protein functions from protein interaction data generated from high throughput techniques. However, predicting protein functions correctly and reliably still remains a challenge. Recently, many computational methods have been proposed for predicting protein functions. Among these methods, clustering based methods are the most promising. The existing methods, however, mainly focus on protein relationship modeling and the prediction algorithms that statically predict functions from the clusters that are related to the unannotated proteins. In fact, the clustering itself is a dynamic process and the function prediction should take this dynamic feature of clustering into consideration. Unfortunately, this dynamic feature of clustering is ignored in the existing prediction methods. In this paper, we propose an innovative progressive clustering based prediction method to trace the functions of relevant annotated proteins across all clusters that are generated through the progressive clustering of proteins. A set of prediction criteria is proposed to predict functions of unannotated proteins from all relevant clusters and traced functions. The method was evaluated on real protein interaction datasets and the results demonstrated the effectiveness of the proposed method compared with representative existing methods.