PURPOSE Pinin (Pnn/DRS/memA) is a cell-adhesion-related and nuclear protein that has been identified as central in the establishment and maintenance of corneal epithelial cell-cell adhesion. To begin the elucidation of the role of Pnn within the nucleus of corneal epithelial cells, this study was undertaken to identify the proteins that bind to Pnn. METHODS Yeast two-hybrid analyses were perf...

Age-related changes in inhibitory neurotransmission in sensory cortex may underlie deficits in sensory function. Perineuronal nets (PNNs) are extracellular matrix components that ensheath some inhibitory neurons, particularly parvalbumin positive (PV+) interneurons. PNNs may protect PV+ cells from oxidative stress and help establish their rapid spiking properties. Although PNN expression has be...

CtBP is a transcriptional corepressor with tumorigenic potential that targets the promoter of the tumor suppressor gene E-cadherin. Pnn/DRS (Pnn) is a "nuclear speckle"-associated protein involved in mRNA processing as well as transcriptional regulation of E-cadherin via its binding to CtBP. Here, we show that CtBP can recruit Pnn to CtBP-associated complexes, resulting in Pnn-dependent chromat...

Increasing emphasis has been put on the influence of desmosome related proteins on progress of colorectal cancer (CRC). Pinin (PNN) is a desmosome-associated molecule that has been reported its overexpression could increase desmoglein 2 (DSG2) and E-cadherin (E-ca) levels. However, it was documented that DSG2 and E-ca had opposite functions in CRC. Thus, we attempted to elucidate function and m...

In this paper the major principles to effectively design a parameter-less, multi-objective evolutionary algorithm that optimizes a population of probabilistic neural network (PNN) classifier models are articulated; PNN is an example of an exemplar-based classifier. These design principles are extracted from experiences, discussed in this paper, which guided the creation of the parameter-less mu...

Phoneme recognition can be viewed as classifying multivariate observations. Multi-layer perceptrons (MLP) and probabilistic neural networks (PNN) approach the decision problem using two complementary models. The MLP models the discriminant surfaces between different phoneme categories, essentially by piece-wise planar approximations, while the PNN approximates class conditional probability dens...

Parallel system with distributed memory is a promising platform to achieve a high performance computing with less construction cost. Applications with less communications, such as a kind of parameter sweep applications (PSA), can be efficiently carried out on such a parallel system, but some applications are not suitable for the parallel system due to a large communication cost. We focus on PNN...

BACKGROUND Statistical learning (SL) techniques can address non-linear relationships and small datasets but do not provide an output that has an epidemiologic interpretation. METHODS A small set of clinical variables (CVs) for stage-1 non-small cell lung cancer patients was used to evaluate an approach for using SL methods as a preprocessing step for survival analysis. A stochastic method of ...

A multi-probabilistic neural network (multi-PNN) classification structure has been designed for distinguishing onemonth abstinent heroin addicts from normal controls by means of the Event-Related Potentials P600 component, selected at 15 scalp leads, elicited under a Working Memory (WM) test. The multi-PNN structure consisted of 15 optimally designed PNN lead-classifiers feeding an end-stage PN...

A transformer is an important part of the power system. Existing fault diagnosis methods are still limited by accuracy and efficiency solution excessively rely on manpower. In this paper, a novel neural network designed to overcome issue. Based traditional method judging ratio dissolved gas in internal insulation oil, fast model was built with improved probabilistic (PNN). The particle swarm op...