503 resultados para RECEPTOR MODELING


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Context: Whether the action of estrogen in skeletal development depends on estrogen receptor α as encoded by the ESR1 gene is unknown. Objectives: The aim of this study was to establish whether the gain in area-adjusted bone mineral content (ABMC) in girls occurs in late puberty and to examine whether the magnitude of this gain is related to ESR1 polymorphisms. Design: We conducted a cross-sectional analysis. Setting: The study involved the Avon Longitudinal Study of Parents and Children (ALSPAC), a population-based prospective study. Participants: Participants included 3097 11-yr-olds with DNA samples, dual x-ray absorptiometry measurements, and pubertal stage information. Outcomes: Outcome measures included separate prespecified analyses in boys and girls of the relationship between ABMC derived from total body dual x-ray absorptiometry scans and Tanner stage and of the interaction between ABMC, Tanner stage, and ESR1 polymorphisms. Results: Total body less head and spinal ABMC were higher in girls in Tanner stages 4 and 5, compared with those in Tanner stages 1, 2, and 3. In contrast, height increased throughout puberty. No differences were observed in ABMC according to Tanner stage in boys. For rs2234693 (PvuII) and rs9340799 (XbaI) polymorphisms, differences in spinal ABMC in late puberty were 2-fold greater in girls who were homozygous for the C and G alleles, respectively (P = 0.001). For rs7757956, the difference in total body less head ABMC in late puberty was 50% less in individuals homozygous or heterozygous for the A allele (P = 0.006). Conclusions: Gains in ABMC in late pubertal girls are strongly associated with ESR1 polymorphisms, suggesting that estrogen contributes to this process via an estrogen receptor α-dependent pathway.

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Context: in the ESR1 gene encoding estrogen receptor (ER)-α may be associated with fat mass in adults. Objectives: The objective of the study was to establish whether ESR1 polymorphisms influence fat mass in childhood. Design: This was a cross-sectional analysis after genotyping of rs9340799, rs2234693, and rs7757956 ESR1 polymorphisms. Setting: The Avon Longitudinal Study of Parents and Children (ALSPAC) was a population-based prospective study. Participants: Participants included 3097 11-yr-old children with results for ESR1 genotyping, puberty measures, and dual-energy x-ray absorptiometry results. Outcomes: Relationships between ESR1 polymorphisms and indices of body composition were measured. Results: The rs7757956 polymorphism was associated with fat mass (P = 0.002). Total body fat mass (adjusted for height) was reduced by 6% in children with TA/AA genotypes, and risk of being overweight (≥85th centile of fat mass) was decreased by 20%. This genetic effect appeared to interact with puberty in girls (P = 0.05 for interaction): in those with the TT genotype, total body fat mass (adjusted for height) was 18% higher in Tanner stages 3-5 vs. stages 1-2; the equivalent difference was 7% in those with TA/AA genotypes. Furthermore, the risk of being overweight was 36% lower in girls with TA/AA genotypes in Tanner stages 3-5, but no reduction was seen in those in stages 1-2. Neither rs9340799 nor rs2234693 polymorphisms were associated with body composition measures. Conclusions: Fat mass in 11-yr-old children was related to the rs7757956 ESR1 polymorphism. This association was strongest in girls in more advanced puberty, in whom the risk of being overweight was reduced by 36% in those with the TA/AA genotype.

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Genetic factors are known to influence both the peak bone mass and probably the rate of change in bone density. A range of regulatory and structural genes has been proposed to be involved including collagen 1α1 (COL1A1), the estrogen receptor (ER), and the vitamin D receptor (VDR), but the actual genes involved are uncertain. We therefore studied the role of the COL1A1 and VDR loci in control of bone density by linkage in 45 dizygotic twin pairs and 29 nuclear families comprising 120 individuals. The influences on bone density of polymorphisms of COL1A1, VDR, and ER were studied by association both cross-sectionally and longitudinally in 193 elderly postmenopausal women (average age, 69 years) over a mean follow-up time of 6.3 years. Weak linkage of the COL1A1 locus with bone density was observed in both twins and families (p = 0.02 in both data sets), confirming previous observations of linkage of this locus with bone density. Association between the MscI polymorphism of COL1A1 and rate of lumbar spine bone loss was observed with significant gene-environment interaction related to dietary calcium intake (p = 0.0006). In the lowest tertile of dietary calcium intake, carriers of "s" alleles lost more bone than "SS" homozygotes (p = 0.01), whereas the opposite was observed in the highest dietary calcium intake (p = 0.003). Association also was observed between rate of bone loss at both the femoral neck and the lumbar spine and the TaqI VDR polymorphism (p = 0.03). This association was strongest in those in the lowest tertile of calcium intake, also suggesting the presence of gene-environment interaction involving dietary calcium and VDR, influencing bone turnover. No significant association was observed between the PvuII ER polymorphism alone or in combination with VDR or COL1A1 genotypes, with either bone density or its rate of change. These data support the involvement of COL1A1 in determination of bone density and the interaction of both COL1A1 and VDR with calcium intake in regulation of change of bone density over time.

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We have investigated the role of 23 candidate genes in the control of bone mineral density (BMD) by linkage studies in families of probands with osteoporosis (lumbar spine [LS] or femoral neck [FN] BMD T score < -2.5) and low BMD relative to an age- and gender-matched cohort (Z score < -2.0). One hundred and fifteen probands (35 male, 80 female) and 499 of their first- or second-degree relatives (223 males and 276 females) were recruited for the study. BMD was measured at the LS and FN using dual-energy X-ray absorptiometry and expressed as age- and gender-matched Z scores corrected for body mass index. The candidate genes studied were the androgen receptor, type I collagen A1 (COLIA1), COLIA2, COLIIA1, vitamin D receptor (VDR), colony-stimulating factor 1, calcium-sensing receptor, epidermal growth factor (EGF), estrogen receptor 1 (ESR1), fibrillin type 1, insulin-like growth factor 1, interleukin-1 alpha (IL-1α), interleukin-4 (IL-4), interleukin-6 (IL-6), interleukin-11 (IL-11), osteopontin, parathyroid hormone (PTH), PTH-related peptide, PTH receptor type 1 (PTHR1), transforming growth factor-beta 1, and tumor necrosis factors alpha and beta. Sixty-four microsatellites lying close to or within these genes were investigated for linkage with BMD. Using the program MapMaker/Sibs there was suggestive evidence of linkage between BMD and PTHR1 (maximum LOD score obtained [MLS] 2.7-3.5). Moderate evidence of linkage was also observed with EGF (MLS 1.8), COLIA1 (MLS 1.7), COLIIA1/VDR (MLS 1.7), ESR1 (MLS 1.4), IL-1α (MLS 1.4), IL-4 (MLS 1.2), and IL-6 (MLS 1.2). Variance components analysis using the program ACT, correcting for proband-wise ascertainment, also showed evidence of linkage (p ≤0.05) at markers close to or within the candidate genes IL- 1α, PTHR1, IL-6, and COLIIA1/VDR. Further studies will be required to confirm these findings, to refine the location of gene responsible for the observed linkage, and to screen the candidate genes targeted at these loci for mutations.

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Analyzing and redesigning business processes is a complex task, which requires the collaboration of multiple actors. Current approaches focus on collaborative modeling workshops where process stakeholders verbally contribute their perspective on a process while modeling experts translate their contributions and integrate them into a model using traditional input devices. Limiting participants to verbal contributions not only affects the outcome of collaboration but also collaboration itself. We created CubeBPM – a system that allows groups of actors to interact with process models through a touch based interface on a large interactive touch display wall. We are currently in the process of conducting a study that aims at assessing the impact of CubeBPM on collaboration and modeling performance. Initial results presented in this paper indicate that the setting helped participants to become more active in collaboration.

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Analyzing and redesigning business processes is a complex task, which requires the collaboration of multiple actors. Current approaches focus on collaborative modeling workshops where process stakeholders verbally contribute their perspective on a process while modeling experts translate their contributions and integrate them into a model using traditional input devices. Limiting participants to verbal contributions not only affects the outcome of collaboration but also collaboration itself. We created CubeBPM – a system that allows groups of actors to interact with process models through a touch based interface on a large interactive touch display wall. We are currently in the process of conducting a study that aims at assessing the impact of CubeBPM on collaboration and modeling performance. Initial results presented in this paper indicate that the setting helped participants to become more active in collaboration.

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Analyzing and redesigning business processes is a complex task, which requires the collaboration of multiple actors. Current approaches focus on workshops where process stakeholders together with modeling experts create a graphical visualization of a process in a model. Within these workshops, stakeholders are mostly limited to verbal contributions, which are integrated into a process model by a modeling expert using traditional input devices. This limitation negatively affects the collaboration outcome and also the perception of the collaboration itself. In order to overcome this problem we created CubeBPM – a system that allows groups of actors to interact with process models through a touch based interface on a large interactive touch display wall. Using this system for collaborative modeling, we expect to provide a more effective collaboration environment thus improving modeling performance and collaboration.

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Introduction Two symposia on “cardiovascular diseases and vulnerable plaques” Cardiovascular disease (CVD) is the leading cause of death worldwide. Huge effort has been made in many disciplines including medical imaging, computational modeling, bio- mechanics, bioengineering, medical devices, animal and clinical studies, population studies as well as genomic, molecular, cellular and organ-level studies seeking improved methods for early detection, diagnosis, prevention and treatment of these diseases [1-14]. However, the mechanisms governing the initiation, progression and the occurrence of final acute clinical CVD events are still poorly understood. A large number of victims of these dis- eases who are apparently healthy die suddenly without prior symptoms. Available screening and diagnostic methods are insufficient to identify the victims before the event occurs [8,9]. Most cardiovascular diseases are associated with vulnerable plaques. A grand challenge here is to develop new imaging techniques, predictive methods and patient screening tools to identify vulnerable plaques and patients who are more vulnerable to plaque rupture and associated clinical events such as stroke and heart attack, and recommend proper treatment plans to prevent those clinical events from happening. Articles in this special issue came from two symposia held recently focusing on “Cardio-vascular Diseases and Vulnerable Plaques: Data, Modeling, Predictions and Clinical Applications.” One was held at Worcester Polytechnic Institute (WPI), Worcester, MA, USA, July 13-14, 2014, right after the 7th World Congress of Biomechanics. This symposium was endorsed by the World Council of Biomechanics, and partially supported by a grant from NIH-National Institute of Biomedical Image and Bioengineering. The other was held at Southeast University (SEU), Nanjing, China, April 18-20, 2014.

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A modeling paradigm is proposed for covariate, variance and working correlation structure selection for longitudinal data analysis. Appropriate selection of covariates is pertinent to correct variance modeling and selecting the appropriate covariates and variance function is vital to correlation structure selection. This leads to a stepwise model selection procedure that deploys a combination of different model selection criteria. Although these criteria find a common theoretical root based on approximating the Kullback-Leibler distance, they are designed to address different aspects of model selection and have different merits and limitations. For example, the extended quasi-likelihood information criterion (EQIC) with a covariance penalty performs well for covariate selection even when the working variance function is misspecified, but EQIC contains little information on correlation structures. The proposed model selection strategies are outlined and a Monte Carlo assessment of their finite sample properties is reported. Two longitudinal studies are used for illustration.

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Purpose: Gamma-aminobutyric acid A (GABAA) receptors (GABAARs), which are ionotropic receptors involving chloride channels, have been identified in various neural (e.g., mouse retinal ganglion cells) and nonneural cells (e.g., mouse lens epithelial cells) regulating the intracellular calcium concentration ([Ca(2+)]i). GABAAR β-subunit protein has been isolated in the cultured human and rat RPE, and GABAAα1 and GABAAρ1 mRNAs and proteins are present in the chick RPE. The purpose of this study was to investigate the expression of GABAAα1 and GABAAρ1, two important subunits in forming functional GABAARs, in the cultured human RPE, and further to explore whether altering receptor activation modifies [Ca(2+)]i. Methods: Human RPE cells were separately cultured from five donor eye cups. Real-time PCR, western blots, and immunofluorescence were used to test for GABAAα1 and GABAAρ1 mRNAs and proteins. The effects of the GABAAR agonist muscimol, antagonist picrotoxin, or the specific GABAAρ antagonist 1,2,5,6-tetrahydropyridin-4-yl) methylphosphinic acid (TPMPA) on [Ca(2+)]i in cultured human RPE were demonstrated using Fluo3-AM. Results: Both GABAAα1 and GABAAρ1 mRNAs and proteins were identified in cultured human RPE cells; antibody staining was mainly localized to the cell membrane and was also present in the cytoplasm but not in the nucleus. Muscimol (100 μM) caused a transient increase of the [Ca(2+)]i in RPE cells regardless of whether Ca(2+) was added to the buffer. Muscimol-induced increases in the [Ca(2+)]i were inhibited by pretreatment with picrotoxin (300 μM) or TPMPA (500 μM). Conclusions: GABAAα1 and GABAAρ1 are expressed in cultured human RPE cells, and GABAA agents can modify [Ca(2+)]i.

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The aim was to investigate the effects of the GABAB receptor antagonist, CGP46381, on form-deprivation myopia (FDM) in guinea pigs. Twenty-four guinea pigs had monocular visual deprivation induced using a diffuser for 11 days (day 14 to 25). The deprived eyes were treated with daily subconjunctival injections (100 μl) of either 2% CGP46381, 0.2% CGP46381, or saline or received no injection. The fellow eyes were left untreated. Another six animals received no treatment. At the start and end of the treatment period, ocular refractions were measured using retinoscopy and vitreous chamber depth (VCD) and axial length (AL) using A-scan ultrasound. All of the deprived eyes developed relative myopia (treated versus untreated eyes, P < 0.05). The amount of myopia was significantly affected by the drug treatment (one-way ANOVA, P < 0.0001). The highest dose tested, 2% CGP46381, significantly inhibited myopia development compared to saline (2% CGP46381: -1.08 ± 0.40 D, saline: -4.33 ± 0.67 D, P < 0.01). The majority of these effects were due to less AL (2% CGP46381: 0.03 ± 0.01 mm, saline: 0.13 ± 0.02 mm, P < 0.01) and VCD (2% CGP46381: 0.02 ± 0.01 mm, saline: 0.08 ± 0.01 mm, P < 0.01) elongation. The lower dose tested, 0.2% CGP46381, did not significantly inhibit FDM (P > 0.05). Subconjunctival injections of CGP46381 inhibit FDM development in guinea pigs in a dose-dependent manner.

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With the rapid development of various technologies and applications in smart grid implementation, demand response has attracted growing research interests because of its potentials in enhancing power grid reliability with reduced system operation costs. This paper presents a new demand response model with elastic economic dispatch in a locational marginal pricing market. It models system economic dispatch as a feedback control process, and introduces a flexible and adjustable load cost as a controlled signal to adjust demand response. Compared with the conventional “one time use” static load dispatch model, this dynamic feedback demand response model may adjust the load to a desired level in a finite number of time steps and a proof of convergence is provided. In addition, Monte Carlo simulation and boundary calculation using interval mathematics are applied for describing uncertainty of end-user's response to an independent system operator's expected dispatch. A numerical analysis based on the modified Pennsylvania-Jersey-Maryland power pool five-bus system is introduced for simulation and the results verify the effectiveness of the proposed model. System operators may use the proposed model to obtain insights in demand response processes for their decision-making regarding system load levels and operation conditions.

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Online dynamic load modeling has become possible with the availability of Static Voltage Compensator (SVC) and Phasor Measurement Unit (PMU) devices. The power of the load response to the small random bounded voltage fluctuations caused from SVC can be measured by PMU for modelling purposes. The aim of this paper is to illustrate the capability of identifying an aggregated load model from high voltage substation level in the online environment. The induction motor is used as the main test subject since it contributes the majority of the dynamic loads. A test system representing simple electromechanical generator model serving dynamic loads through the transmission network is used to verify the proposed method. Also, dynamic load with multiple induction motors are modeled to achieve a better realistic load representation.

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OBJECTIVES To identify common genetic variants that predispose to caffeine-induced insomnia and to test whether genes whose expression changes in the presence of caffeine are enriched for association with caffeine-induced insomnia. DESIGN A hypothesis-free, genome-wide association study. SETTING Community-based sample of Australian twins from the Australian Twin Registry. PARTICIPANTS After removal of individuals who said that they do not drink coffee, a total of 2,402 individuals from 1,470 families in the Australian Twin Registry provided both phenotype and genotype information. MEASUREMENTS AND RESULTS A dichotomized scale based on whether participants reported ever or never experiencing caffeine-induced insomnia. A factor score based on responses to a number of questions regarding normal sleep habits was included as a covariate in the analysis. More than 2 million common single nucleotide polymorphisms (SNPs) were tested for association with caffeine-induced insomnia. No SNPs reached the genome-wide significance threshold. In the analysis that did not include the insomnia factor score as a covariate, the most significant SNP identified was an intronic SNP in the PRIMA1 gene (P = 1.4 x 10(-)(6), odds ratio = 0.68 [0.53 - 0.89]). An intergenic SNP near the GBP4 gene on chromosome 1 was the most significant upon inclusion of the insomnia factor score into the model (P = 1.9 x 10(-)(6), odds ratio = 0.70 [0.62 - 0.78]). A previously identified association with a polymorphism in the ADORA2A gene was replicated. CONCLUSIONS Several genes have been identified in the study as potentially influencing caffeine-induced insomnia. They will require replication in another sample. The results may have implications for understanding the biologic mechanisms underlying insomnia.