While the activation of primary somatosensory (SI) cortex during pain perception is consistently reported in functional imaging studies on normal subjects and chronic pain patients, the specific roles of SI, particularly the subregions within SI, in the processing of sensory aspects of pain are still largely unknown. Using optical imaging of intrinsic signal (OIS) and single unit electrophysiology, we studied cortical activation patterns within SI cortex (among Brodmann areas 3a, 3b and 1) and signal amplitude changes to various intensities of non-nociceptive, thermal nociceptive and mechanical nociceptive stimulation of individual distal finerpads in anesthetized squirrel monkeys. We have demonstrated that areas 3a and 1 are preferentially involved in the processing of nociceptive information while areas 3b and 1 are preferentially activated in the processing of non-nociceptive (touch) information. Nociceptive activations of individual fingerpad were organized topographically suggesting that nociceptive topographic map exits in areas 3a and 1. Signal amplitude was enhanced to increasing intensity of mechanical nociceptive stimuli in areas 3a, 3b and 1. Within area 1, nociceptive response co-localizes with the non-nociceptive response. Therefore, we hypothesize that nocicepitve information is area-specifically represented within SI cortex, in which nociceptive inputs are preferentially represented in areas 3a and 1 while non-nociceptive inputs are preferentially represented in areas 3b and 1.
Animals ; Brain Mapping ; Nociception ; physiology ; Pain ; Saimiri ; Somatosensory Cortex ; physiology ; Touch

A systematic phylogenetic footprinting approach was performed to identify conserved transcription factor binding sites (TFBSs) in mammalian promoter regions using human, mouse and rat sequence alignments. We found that the score distributions of most binding site models did not follow the Gaussian distribution required by many statistical methods. Therefore, we performed an empirical test to establish the optimal threshold for each model. We gauged our computational predictions by comparing with previously known TFBSs in the PCK1 gene promoter of the cytosolic isoform of phosphoenolpyruvate carboxykinase, and achieved a sensitivity of 75% and a specificity of approximately 32%. Almost all known sites overlapped with predicted sites, and several new putative TFBSs were also identified. We validated a predicted SP1 binding site in the control of PCK1 transcription using gel shift and reporter assays. Finally, we applied our computational approach to the prediction of putative TFBSs within the promoter regions of all available RefSeq genes. Our full set of TFBS predictions is freely available at http://bfgl.anri.barc.usda.gov/tfbsConsSites.
Algorithms ; Amino Acid Sequence ; Animals ; Base Sequence ; Binding Sites ; genetics ; Cell Line, Tumor ; Computational Biology ; methods ; Conserved Sequence ; Electrophoretic Mobility Shift Assay ; Humans ; Intracellular Signaling Peptides and Proteins ; genetics ; Luciferases ; genetics ; metabolism ; Mice ; Normal Distribution ; Oligonucleotides ; genetics ; metabolism ; Phosphoenolpyruvate Carboxykinase (GTP) ; genetics ; Promoter Regions, Genetic ; genetics ; Protein Binding ; Rats ; Recombinant Fusion Proteins ; genetics ; metabolism ; Regulatory Sequences, Nucleic Acid ; genetics ; Reproducibility of Results ; Sp1 Transcription Factor ; genetics ; metabolism ; Transcription Factors ; metabolism ; Transfection

BACKGROUNDLittle is known about the influence of metabolic syndrome (MetS) on coronary artery calcification (CAC) in China. In this article, we aimed to explore the distribution of CAC in populations with and without MetS, and estimate the influence of MetS and its components on CAC in a community-based population of Beijing.

METHODSA total of 1647 local residents of Beijing, age 40-77 years, were recruited for a cardiovascular risk factors survey and were determined fasting plasma glucose (FPG), blood lipids, and 64 multi-detector computed tomography (64-MDCT) coronary artery calcium score (CACS) measurement (Agatston scoring). The distribution of CAC was described, and the influence of MetS components on CAC was evaluated.

RESULTSIn this population, the prevalence and extent of CAC increased with increasing age and both were higher in MetS subjects compared to nonMetS subjects (all P < 0.05), with the exception of those older than 65 years old. The risk of CAC increased with increasing numbers of MetS components, and the odds ratios for predicting positive CAC in subjects with 1, 2, 3, and = 4 MetS components were 1.60, 1.84, 2.12, and 3.12, respectively (all P < 0.05). Elevated blood pressure, elevated FPG, elevated triglycerides, and overweight increased the risk of CAC, yielding odds ratios of 2.64, 1.67, 1.32, and 1.37, respectively (all P < 0.05).

CONCLUSIONSIn the Beijing community-based population, MetS increases the risk of CAC. The risk of CAC increases with increasing numbers of MetS components. Not only the number, but also the variety of risk factors for MetS is correlated with the risk of CAC. Elevated blood pressure, hyperglycemia, hypertriglyceridemia and overweight increase the risk of CAC.

Adult ; Aged ; China ; epidemiology ; Coronary Artery Disease ; epidemiology ; metabolism ; pathology ; Coronary Vessels ; metabolism ; pathology ; Female ; Humans ; Male ; Metabolic Syndrome ; epidemiology ; metabolism ; pathology ; Middle Aged ; Risk Factors