Activation of Akt/PKB, increased phosphorylation of Akt substrates and loss and altered distribution of Akt and PTEN are features of Alzheimer's disease pathology

Studies suggest that activation of phosphoinositide 3-kinase-Akt may protect against neuronal cell death in Alzheimer's disease (AD). Here, however, we provide evidence of increased Akt activation, and hyperphosphorylation of critical Akt substrates in AD brain, which link to AD pathogenesis, suggesting that treatments aiming to activate the pathway in AD need to be considered carefully. A different distribution of Akt and phospho-Akt was detected in AD temporal cortex neurons compared with control neurons, with increased levels of active phosphorylated-Akt in particulate fractions, and significant decreases in Akt levels in AD cytosolic fractions, causing increased activation of Akt (phosphorylated-Akt/total Akt ratio) in AD. In concordance, significant increases in the levels of phosphorylation of total Akt substrates, including: GSK3ßSer9, tauSer214, mTORSer2448, and decreased levels of the Akt target, p27kip1, were found in AD temporal cortex compared with controls. A significant loss and altered distribution of the major negative regulator of Akt, PTEN (phosphatase and tensin homologue deleted on chromosome 10), was also detected in AD neurons. Loss of phosphorylated-Akt and PTEN-containing neurons were found in hippocampal CA1 at end stages of AD. Taken together, these results support a potential role for aberrant control of Akt and PTEN signalling in AD.

An automated machine vision system for the histological grading of cervical intraepithelial neoplasia (CIN)

The histological grading of cervical intraepithelial neoplasia (CIN) remains subjective, resulting in inter- and intra-observer variation and poor reproducibility in the grading of cervical lesions. This study has attempted to develop an objective grading system using automated machine vision. The architectural features of cervical squamous epithelium are quantitatively analysed using a combination of computerized digital image processing and Delaunay triangulation analysis; 230 images digitally captured from cases previously classified by a gynaecological pathologist included normal cervical squamous epithelium (n = 30), koilocytosis (n = 46), CIN 1 (n = 52), CIN 2 (n = 56), and CIN 3 (n=46). Intra- and inter-observer variation had kappa values of 0.502 and 0.415, respectively. A machine vision system was developed in KS400 macro programming language to segment and mark the centres of all nuclei within the epithelium. By object-oriented analysis of image components, the positional information of nuclei was used to construct a Delaunay triangulation mesh. Each mesh was analysed to compute triangle dimensions including the mean triangle area, the mean triangle edge length, and the number of triangles per unit area, giving an individual quantitative profile of measurements for each case. Discriminant analysis of the geometric data revealed the significant discriminatory variables from which a classification score was derived. The scoring system distinguished between normal and CIN 3 in 98.7% of cases and between koilocytosis and CIN 1 in 76.5% of cases, but only 62.3% of the CIN cases were classified into the correct group, with the CIN 2 group showing the highest rate of misclassification. Graphical plots of triangulation data demonstrated the continuum of morphological change from normal squamous epithelium to the highest grade of CIN, with overlapping of the groups originally defined by the pathologists. This study shows that automated location of nuclei in cervical biopsies using computerized image analysis is possible. Analysis of positional information enables quantitative evaluation of architectural features in CIN using Delaunay triangulation meshes, which is effective in the objective classification of CIN. This demonstrates the future potential of automated machine vision systems in diagnostic histopathology. Copyright (C) 2000 John Wiley and Sons, Ltd.

Clinical Features of Dominant and Recessive Interferon γ Receptor 1 Deficiencies

Background Interferon ? receptor 1 (IFN? R1) deficiency is a primary immunodeficiency with allelic dominant and recessive mutations characterised clinically by severe infections with mycobacteria. We aimed to compare the clinical features of recessive and dominant IFN?R1 deficiencies. Methods We obtained data from a large cohort of patients worldwide. We assessed these people by medical histories, records, and genetic and immunological studies. Data were abstracted onto a standard form. Findings We identified 22 patients with recessive complete IFN?R1 deficiency and 38 with dominant partial deficiency. BCG and environmental mycobacteria were the most frequent pathogens. In recessive patients, 17 (77%) had environmental mycobacterial disease and all nine BCG-vaccinated patients had BCG disease. In dominant patients, 30 (79%) had environmental mycobacterial disease and 11 (73%) of 15 BCG-vaccinated patients had BCG disease. Compared with dominant patients, those with recessive deficiency were younger at onset of first environmental mycobacterial disease (mean 3·1 years [SD 2·5] vs 13·4 years [14·3], p=0·001), had more mycobacterial disease episodes (19 vs 8 per 100 person-years of observation, p=0·0001), had more severe mycobacterial disease (mean number of organs infected by Mycobacterium avium complex 4·1 [SD 0·8] vs 2·0 [1·1], p=0·004), had shorter mean disease-free intervals (1·6 years [SD 1·4] vs 7·2 years [7·6], p

An FPGA Based Coprocessor for GLCM and Haralick Texture Features and Their Application in Prostate Cancer Classification

Grey Level Co-occurrence Matrix (GLCM), one of the best known tool for texture analysis, estimates image properties related to second-order statistics. These image properties commonly known as Haralick texture features can be used for image classification, image segmentation, and remote sensing applications. However, their computations are highly intensive especially for very large images such as medical ones. Therefore, methods to accelerate their computations are highly desired. This paper proposes the use of programmable hardware to accelerate the calculation of GLCM and Haralick texture features. Further, as an example of the speedup offered by programmable logic, a multispectral computer vision system for automatic diagnosis of prostatic cancer has been implemented. The performance is then compared against a microprocessor based solution.

Structural and functional basis for ADP-ribose and poly(ADP-ribose) binding by viral macro domains.

Macro domains constitute a protein module family found associated with specific histones and proteins involved in chromatin metabolism. In addition, a small number of animal RNA viruses, such as corona- and toroviruses, alphaviruses, and hepatitis E virus, encode macro domains for which, however, structural and functional information is extremely limited. Here, we characterized the macro domains from hepatitis E virus, Semliki Forest virus, and severe acute respiratory syndrome coronavirus (SARS-CoV). The crystal structure of the SARS-CoV macro domain was determined at 1.8-Å resolution in complex with ADP-ribose. Information derived from structural, mutational, and sequence analyses suggests a close phylogenetic and, most probably, functional relationship between viral and cellular macro domain homologs. The data revealed that viral macro domains have relatively poor ADP-ribose 1"-phosphohydrolase activities (which were previously proposed to be their biologically relevant function) but bind efficiently free and poly(ADP-ribose) polymerase 1-bound poly(ADP-ribose) in vitro. Collectively, these results suggest to further evaluate the role of viral macro domains in host response to viral infection.