Toxicity of non-abeta component of Alzheimer's disease amyloid, and N-terminal fragments thereof, correlates to formation of beta-sheet structure and fibrils.

Synucleins are small proteins that are highly expressed in brain tissue and are localised at presynaptic terminals in neurons. alpha-Synuclein has been identified as a component of intracellular fibrillar protein deposits in several neurodegenerative diseases, and two mutant forms of alpha-synuclein have been associated with autosomal-dominant Parkinson's Disease. A fragment of alpha-synuclein has also been identified as the non-Abeta component of Alzheimer's Disease amyloid. In this review we describe some structural properties of alpha-synuclein and the two mutant forms, as well as alpha-synuclein fragments, with particular emphasis on their ability to form beta-sheet on ageing and aggregate to form amyloid-like fibrils. Differences in the rates of aggregation and morphologies of the fibrils formed by alpha-synuclein and the two mutant proteins are highlighted. Interactions between alpha-synuclein and other proteins, especially those that are components of amyloid or Lewy bodies, are considered. The toxicity of alpha-synuclein and related peptides towards neurons is also discussing in relation to the aetiology of neurodegenerative diseases.

Nonlinear PCA with Local Approach for Diesel Engine Fault Detection and Diagnosis

This brief examines the application of nonlinear statistical process control to the detection and diagnosis of faults in automotive engines. In this statistical framework, the computed score variables may have a complicated nonparametric distri- bution function, which hampers statistical inference, notably for fault detection and diagnosis. This brief shows that introducing the statistical local approach into nonlinear statistical process control produces statistics that follow a normal distribution, thereby enabling a simple statistical inference for fault detection. Further, for fault diagnosis, this brief introduces a compensation scheme that approximates the fault condition signature. Experimental results from a Volkswagen 1.9-L turbo-charged diesel engine are included.

Process monitoring approach using fast moving window PCA

This paper introduces a fast algorithm for moving window principal component analysis (MWPCA) which will adapt a principal component model. This incorporates the concept of recursive adaptation within a moving window to (i) adapt the mean and variance of the process variables, (ii) adapt the correlation matrix, and (iii) adjust the PCA model by recomputing the decomposition. This paper shows that the new algorithm is computationally faster than conventional moving window techniques, if the window size exceeds 3 times the number of variables, and is not affected by the window size. A further contribution is the introduction of an N-step-ahead horizon into the process monitoring. This implies that the PCA model, identified N-steps earlier, is used to analyze the current observation. For monitoring complex chemical systems, this work shows that the use of the horizon improves the ability to detect slowly developing drifts.

The Effect of Volume Shape Factor on the Crystal Size Distribution of Fragments due to Attrition

The effect of volume shape factor on crystal size distribution (CSD) is usually ignored to simplify the analysis of population balance equation. In the present work, the CSD of fragments generated from a mechanically stirred crystallizer as the result of attrition mechanism has been reported when the volume shape factor conforms to normal distribution. The physical model of GAHN and MERSMANN which relates the attrition resistance of a crystalline substances to its mechanical properties has been employed. The simulation of fragment size distribution was performed by Monte Carlo (MC) technique. The results are compared with those reported by GAHN and MERSMANN.

Moving window kernel PCA for adaptive monitoring of nonlinear processes

This paper discusses the monitoring of complex nonlinear and time-varying processes. Kernel principal component analysis (KPCA) has gained significant attention as a monitoring tool for nonlinear systems in recent years but relies on a fixed model that cannot be employed for time-varying systems. The contribution of this article is the development of a numerically efficient and memory saving moving window KPCA (MWKPCA) monitoring approach. The proposed technique incorporates an up- and downdating procedure to adapt (i) the data mean and covariance matrix in the feature space and (ii) approximates the eigenvalues and eigenvectors of the Gram matrix. The article shows that the proposed MWKPCA algorithm has a computation complexity of O(N2), whilst batch techniques, e.g. the Lanczos method, are of O(N3). Including the adaptation of the number of retained components and an l-step ahead application of the MWKPCA monitoring model, the paper finally demonstrates the utility of the proposed technique using a simulated nonlinear time-varying system and recorded data from an industrial distillation column.

Llama antibody fragments have good potential for application as HIV-1 topical microbicides

There is an urgent global need for preventative strategies against HIV-1 infections. Llama heavy-chain antibody fragments (VHH) are a class of molecules recently described as potent cross-clade HIV-1 entry inhibitors. We studied the potential of a VHH-based microbicide in an application-oriented fashion. We show that VHH can be inexpensively produced in high amounts in the GRAS organism S. cerevisiae, resulting in very pure, and endotoxin free product. VHH are very stable under conditions they might encounter during transport, storage or use by women. We developed active formulations of VHH in aqueous gel and compressed and lyophilized tablets for controlled release from an intra vaginal device. The release profile of the VHH from e.g. a vaginal ring suggests sufficient bioavailability and protective concentration of the molecule at the mucosal site at the moment of the infection. The ex vivo penetration kinetics through human tissues show that the VHH diffuse into the mucosal layer and open the possibility to create a second defense layer either by blocking the HIV receptor binding sites or by blocking the receptors of immune cells in the mucosa. In conclusion, our data show that VHH have