Stan Svojanovsky
Missouri Western State University, Chemistry, Faculty Member
Research Interests: Biology, Prostate Cancer, Cancer Research, Medicine, Gene expression, and 15 moreCell Division, Humans, Mice, Animals, Male, Androgens, Clinical Sciences, Chromatin Immunoprecipitation, Disease Progression, Androgen Receptor, LNCaP, Cell Growth, Prostatic neoplasms, orchiectomy, and Paediatrics and reproductive medicine
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Research Interests: Neuroscience, Cognitive Science, Biophysics, Magnetic Resonance Imaging, Motor Control, and 15 moreMedicine, Brain Mapping, Anatomy, Articles, Cerebral Cortex, Animals, Male, Motor Cortex, Facilitation, Electromyography, Neuronal Activity, Macaca Mulatta, Neural pathways, Neurosciences, and Electric stimulation
Research Interests: Biology and Fibroblast
Research Interests: Computer Science, Principal Component Analysis, Back Propagation, Drug Discovery, Neural Networks, and 11 moreNeural Network, Medicine, Generalization, High throughput screening, Backpropagation, Reproducibility of Results, Artificial Neural Network, Data Set, Biochemistry and cell biology, Computer Science Neural Networks, and Training Set
In this study, forelimb organizations and output properties of the supplementary motor area (SMA) and the dorsal cingulate motor area (CMAd) were assessed and compared with primary motor cortex (M1). Stimulus-triggered averages of... more
In this study, forelimb organizations and output properties of the supplementary motor area (SMA) and the dorsal cingulate motor area (CMAd) were assessed and compared with primary motor cortex (M1). Stimulus-triggered averages of electromyographic activity from 24 muscles of the forelimb were computed from layer V sites of 2 rhesus monkeys performing a reach-to-grasp task. No clear segregation of the forelimb representation of proximal and distal muscles was found in SMA. In CMAd, sites producing poststimulus effects in proximal muscles tended to be located caudal to distal muscle sites, although the number of effects was limited. For both SMA and CMAd, facilitation effects were more prevalent in distal than in proximal muscles. At an intensity of 60 mA, the mean latencies of M1 facilitation effects were 8 and 12.1 ms shorter and the magnitudes ~10 times greater than those from SMA and CMAd. Our results show that corticospinal neurons in SMA and CMAd provide relatively weak input t...
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In this study, forelimb organizations and output properties of the supplementary motor area (SMA) and the dorsal cingulate motor area (CMAd) were assessed and compared with primary motor cortex (M1). Stimulus-triggered averages of... more
In this study, forelimb organizations and output properties of the supplementary motor area (SMA) and the dorsal cingulate motor area (CMAd) were assessed and compared with primary motor cortex (M1). Stimulus-triggered averages of electromyographic activity from 24 muscles of the forelimb were computed from layer V sites of 2 rhesus monkeys performing a reach-to-grasp task. No clear segregation of the forelimb representation of proximal and distal muscles was found in SMA. In CMAd, sites producing poststimulus effects in proximal muscles tended to be located caudal to distal muscle sites, although the number of effects was limited. For both SMA and CMAd, facilitation effects were more prevalent in distal than in proximal muscles. At an intensity of 60 mA, the mean latencies of M1 facilitation effects were 8 and 12.1 ms shorter and the magnitudes ~10 times greater than those from SMA and CMAd. Our results show that corticospinal neurons in SMA and CMAd provide relatively weak input t...
Research Interests: Psychology, Cognitive Science, Biophysics, Magnetic Resonance Imaging, Motor Control, and 15 moreMedicine, Brain Mapping, EMG, Cerebral Cortex, Animals, Male, Motor Cortex, Electromyography, Primate, Neuronal Activity, Macaca Mulatta, Neural pathways, Neurosciences, Psychomotor Performance, and Electric stimulation
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We have developed the web based tool GOAPhAR (Gene Ontology, Annotations and Pathways for Array Research), that integrates information from disparate sources regarding gene annotations, protein annotations, identifiers associated with... more
We have developed the web based tool GOAPhAR (Gene Ontology, Annotations and Pathways for Array Research), that integrates information from disparate sources regarding gene annotations, protein annotations, identifiers associated with probe sets, functional pathways, protein interactions, Gene Ontology, publicly available microarray datasets and tools for statistically validating clusters in microarray data. Genes of interest can be input as Affymetrix probe identifiers, Genbank, or Unigene identifiers for human, mouse or rat genomes. Results are provided in a user friendly interface with hyperlinks to the sources of information.
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Several mutations are known or suspected to affect mRNA splicing of CYP2C19, CYP2D6 and CYP3A5 genes; however, little experimental evidence exists to support these conclusions. The present study applies mathematical models that measure... more
Several mutations are known or suspected to affect mRNA splicing of CYP2C19, CYP2D6 and CYP3A5 genes; however, little experimental evidence exists to support these conclusions. The present study applies mathematical models that measure changes in information content of splice sites in these genes to demonstrate the relationship between the predicted phenotypes of these variants to the corresponding genotypes. Based on information analysis, the CYP2C19*2 variant activates a new cryptic site 40 nucleotides downstream of the natural splice site. CYP2C19*7 abolishes splicing at the exon 5 donor site. The CYP2D6*4 allele similarly inactivates splicing at the acceptor site of exon 4 and activates a new cryptic site one nucleotide downstream of the natural acceptor. CYP2D6*11 inactivates the acceptor site of exon 2. The CYP3A5*3 allele activates a new cryptic site 236 nucleotides upstream of the exon 4 natural acceptor site. CYP3A5*5 inactivates the exon 5 donor site and CYP3A5*6 strengthens a site upstream of the natural donor site, resulting in skipping of exon 7. Other previously described missense and nonsense mutations at terminal codons of exons in these genes affected splicing. CYP2D6*8 and CYP2D6*14 both decrease the strength of the exon 3 donor site, producing transcripts lacking this exon. The results of information analysis are consistent with the poor metabolizer phenotypes observed in patients with these mutations, and illustrate the potential value of these mathematical models to quantitatively evaluate the functional consequences of new mutations suspected of altering mRNA splicing.
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Research Interests: Analytical Chemistry, Cancer, Treatment, Quantitative analysis, Pharmaceutical, and 12 moreNatural Product, Enzyme, Analytical Method, Cancer Patient, Quantitative Analysis, Biological activity, Bovine Serum Albumin, High Sensitivity, Enzyme Linked Immunosorbent Assay, Anticancer Drug, therapeutic index, and Pharmacology and pharmaceutical sciences
Artificial neural networks (ANNs) are trained using high-throughput screening (HTS) data to recover active compounds from a large data set. Improved classification performance was obtained on combining predictions made by multiple ANNs.... more
Artificial neural networks (ANNs) are trained using high-throughput screening (HTS) data to recover active compounds from a large data set. Improved classification performance was obtained on combining predictions made by multiple ANNs. The HTS data, acquired from a methionine aminopeptidases inhibition study, consisted of a library of 43,347 compounds, and the ratio of active to nonactive compounds, R A/N, was 0.0321. Back-propagation ANNs were trained and validated using principal components derived from the physicochemical features of the compounds. On selecting the training parameters carefully, an ANN recovers one-third of all active compounds from the validation set with a 3-fold gain in R A/N value. Further gains in RA/N values were obtained upon combining the predictions made by a number of ANNs. The generalization property of the back-propagation ANNs was used to train those ANNs with the same training samples, after being initialized with different sets of random weights. ...
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Artificial neural networks (ANNs) have been applied in almost every aspect of food science over the past two decades, although most applications are in the development stage. ANNs are useful tools for food safety and quality analyses,... more
Artificial neural networks (ANNs) have been applied in almost every aspect of food science over the past two decades, although most applications are in the development stage. ANNs are useful tools for food safety and quality analyses, which include modeling of microbial growth and from this predicting food safety, interpreting spectroscopic data, and predicting physical, chemical, functional and sensory properties of various food products during processing and distribution. ANNs hold a great deal of promise for modeling complex tasks in process control and simulation and in applications of machine perception including machine vision and electronic nose for food safety and quality control. This review discusses the basic theory of the ANN technology and its applications in food science, providing food scientists and the research community an overview of the current research and future trend of the applications of ANN technology in the field.
Research Interests: Microbiology, Algorithms, Artificial Intelligence, Food Science, Food Safety, and 15 moreMachine Vision, Neural Network, Animal Production, Food Microbiology, Food Technology, Machine Perception, Humans, Electronic Nose, Application, Fermentation, Food Sciences, Food Products, Model Complexity, Artificial Neural Network, and Microbial Growth
Research Interests: Immunology, Gene regulation, Cell Signaling, Gene expression, Signal Transduction, and 15 moreClinical immunology, Humans, Microarray, Female, Clinical, Risk factors, Middle Aged, Adult, Risk Factors, Disease Activity, Estradiol, Mediator complex, Gene expression profiling, Differential expression, and Signaling pathway
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Although migraine is more common in women than men and often linked to the menstrual cycle, few studies have investigated the biological basis of hormonal influences on the trigeminovascular system. In the present study we investigated... more
Although migraine is more common in women than men and often linked to the menstrual cycle, few studies have investigated the biological basis of hormonal influences on the trigeminovascular system. In the present study we investigated the effect of physiological levels (10-9 M) oestrogen on female rat trigeminal ganglia in vitro. Immunocytochemical analysis demonstrated the presence of oestrogen receptor-alpha in a predominantly cytoplasmic location and in neurites. Microarray analysis demonstrated that oestrogen treatment regulates several genes with potential relevance to menstrual migraine. The genes that were upregulated included synapsin-2, endothelin receptor type B, activity and neurotransmitter-induced early gene 7 (ania-7), phosphoserine aminotransferase, MHC-1b, and ERK-1. Down-regulated genes included IL-R1, bradykinin B2 receptor, N- tropomodulin, CCL20, GABA transporter protein, fetal intestinal lactase-phlorizin hydrolase, carcinoembryonic antigen-related protein, zin...