Ya-Ping Lu

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Alzheimer's disease (AD) is characterized pathologically by selective neuronal loss and by the formation of neurofibrillary tangles (NFTs) and senile plaques (SPs). Since calcium/calmodulin-dependent protein kinase II-alpha (CaMKII-alpha), one of the most abundant kinases in the brain, is involved in the phosphorylation of tau and amyloid precursor protein(More)
Emerging evidence has demonstrated the neuroprotection of estrogen in Alzheimer's disease (AD). The hippocampus, an important target of estrogen action, is severely affected in the Alzheimer process. The aim of present study was to detect the distribution of estrogen receptor-alpha (ER-alpha) and the relationship between ER-alpha-containing neurons and the(More)
Postmenopausal estrogen use may decrease the risk, and delay the onset and progression, of Alzheimer's disease (AD). By means of fluorescence immunocytochemistry, the present study investigated the distribution of estrogen receptor alpha (ERalpha) in the human hippocampus in controls and in AD cases. ERalpha immunoreactivity was observed in neurons and(More)
Deep networks are well known for their powerful function approximations. To train a deep network efficiently, greedy layer-wise pre-training and fine tuning are required. Typically, pre-training, aiming to initialize a deep network, is implemented via unsupervised feature learning, with multiple feature representations generated. However, in general only(More)
Nogo is widely expressed in higher vertebrate animals. Nogo gene gives rise to multiple isoforms. All the subtypes of Nogo proteins are characterized by a 200-amino-acid C-terminal domain, including two long hydrophobic sequences. Biological functions of Nogo include inhibition of neurite growth from the cell surface via specific receptors, intracellular(More)
The prediction and recognition of promoter in human genome play an important role in DNA sequence analysis. Entropy, in Shannon sense, of information theory is a multiple utility in bioinformatic details analysis. The relative entropy estimator methods based on statistical divergence (SD) are used to extract meaningful features to distinguish different(More)
Generally, in order to learn sparse representations for raw inputs via an auto-encoder, the Kullback-Leibler (KL) divergence as a sparsity regularizer is introduced to the loss function for penalizing active code units. In fact, there exist other sparsity regularizers except the KL divergence. This paper introduces some classical sparsity regularizers into(More)
OBJECTIVE To investigate the possible mechanism by which estrogen regulates apoptosis through the estrogen receptor. METHODS By means of fluorescence immunocytochemistry, the present study investigated the distribution of Bcl-2 and the colocolization of Bcl-2 and ERalpha immunoreactivity in the hippocampus of 10 Alzheimer's disease (AD) patients and 10(More)
The idea that with the help of proper dimensionality reduction, trying to make the samples with the same label be compact and the ones with the different labels be separate after projection, is introduced into classification problems with high-dimensional data. Based on the analysis of the drawbacks of Discriminant Neighborhood Embedding (DNE) and(More)