Association between LRP5 polymorphism and bone mineral density: a Bayesian meta-analysis

<p>Abstract</p> <p>Background</p> <p>The low-density lipoprotein receptor-related protein 5 gene (LRP5) was identified to be linked to the variation in BMD in high bone mass pedigrees. Subsequent population-based studies of the association between the LRP5 gene and BMD have yielded conflicting results. The present study was aimed at examining the association between LRP5 gene and BMD by using meta-analysis.</p> <p>Methods</p> <p>A systematic electronic search of literature was conducted to identify all published studies in English on the association between LRP5 gene and osteoporosis-related phenotypes, including bone mineral density and fracture. BMD data were summarized from individual studies by LRP5 genotype, and a synthesis of data was performed with random-effects meta-analyses. After excluding studies on animal and review papers, there were 19 studies for the synthesis. Among these studies, 10 studies used the rs3736228 (A1330V) polymorphism and reported BMD values.</p> <p>Results</p> <p>The 10 eligible studies comprised 16,705 individuals, with the majority being women (n = 8444), aged between 18 – 81 years. The overall distribution of genotype frequencies was: AA, 68%, AV and VV, 32%. However, the genotype frequency varied significantly within as well as between ethnic populations. On random-effects meta-analysis, lumbar spine BMD among individuals with the AA genotype was on average 0.018 (95% confidence interval [CI]: 0.012 to 0.023) g/cm²higher than those with either AV or VV genotype. Similarly, femoral neck BMD among carriers of the AA genotype was 0.011 (95%CI: 0.004 to 0.017) g/cm²higher than those without the genotype. While there was no significant heterogeneity in the association between the A1330V polymorphism and lumbar spine BMD (p = 0.55), the association was heterogeneous for femoral neck BMD (p = 0.05). The probability that the difference is greater than one standard deviation was 0.34 for femoral neck BMD and 0.54 for lumbar spine BMD.</p> <p>Conclusion</p> <p>These results suggest that there is a modest effect of the A1330V polymorphism on BMD in the general population, and that the modest association may limit its clinical use.</p

Temporal and instantaneous connectivity of default mode network estimated using Gaussian Bayesian network frameworks

By probing its functional anatomy, the default mode network (DMN) can be considered consisting of two interacting hub and non-hub subsystems. The hub subsystem includes posterior cingulate cortex (PCC), medial prefrontal cortex (MPFC) and bilateral inferior parietal cortex (IPC). The non-hub subsystem contains inferior temporal cortex (ITC) and (para) hippocampus (HC). In this study, Gaussian Bayesian Network (BN) and Gaussian Dynamic Bayesian Network (DBN) were applied separately to detect the instantaneous and temporal connection relationship within each and between the two DMN subsystems. It was found that the directional instantaneous interactions between the two subsystems were primarily "from non-hub to hub". The temporal interactions between hub and non-hub regions, on the other hand, are less presented between the two subsystems. The hub subsystem demonstrated both strong instantaneous and temporal interactions among the hub regions, while the non-hub regions were only strongly inter-connected instantaneously but temporally isolated with each other. In addition, one of the hub regions, PCC, appears to be a confluent node and important in the functional integration within the network. (c) 2012 Elsevier Ireland Ltd. All rights reserved

The processes leading to deception: ERP spatiotemporal principal component analysis and source analysis

The cognitive and neural mechanisms leading to deception were studied by the event-related brain potential (ERP) technique. In a simulated deception situation with graded monetary incentives, participants made a decision to lie or be truthful in each trial and held their response until a delayed imperative signal was presented. Spatiotemporal principal component analysis (PCA) and source analysis revealed that brain activities dominant in the left lateral frontal area approximately 800-1,000 ms post-stimulus and over the central-frontal-parietal and right frontal areas after 1,300 ms were significantly more negative in the deceptive condition than in the truthful condition. These results suggest that two serial cognitive processes, decision making and response preparation, are related to deliberate deception

Pitch and loudness information encoded in auditory imagery as revealed by event-related potentials

Two experiments using the ERP method and a task that involved comparing an imagined-S1 (the first stimulus) with a perceived-S2 (the second stimulus) were conducted to investigate whether imagined auditory representations encode pitch and loudness information. It was found that the amplitude of the imagery-related late positive complex (LPC) decreased with pitch but increased with loudness of the imagined sound, which was consistent with amplitude modulations of the auditory perception-related N1 component, thereby providing the first neural evidence that auditory imagery encodes perceptual attributes of auditory experiences.Two experiments using the ERP method and a task that involved comparing an imagined-S1 (the first stimulus) with a perceived-S2 (the second stimulus) were conducted to investigate whether imagined auditory representations encode pitch and loudness information. It was found that the amplitude of the imagery-related late positive complex (LPC) decreased with pitch but increased with loudness of the imagined sound, which was consistent with amplitude modulations of the auditory perception-related N1 component, thereby providing the first neural evidence that auditory imagery encodes perceptual attributes of auditory experiences

Evaluation of semi-arid arable soil heavy metal pollution by magnetic susceptibility in the Linfen basin of China

The values of magnetic susceptibility and Cu, Zn, Ni, Pb, Cr, Cd concentrations of 70 topsoil samples were analyzed and assessed for soil contamination in the Linfen basin of China. The contamination factor (CF) and pollution load index (PLI) were used to assess the degree of heavy metal pollution. All heavy metal concentrations in the soil were greater than the background values of Shanxi agricultural soils. PLI values ranged from 1.27 to 2.18 indicating significant soil contamination. Principal component analyses and correlation analyses were adopted for data treatment to identify heavy metal sources. Cu, Zn, Ni, and Pb were responsible for 31.2% of the total variance suggesting that these elements mainly originated from agrochemistry and atmospheric deposition. A positive correlation of magnetic susceptibility with Cu and PLI were observed in cultivated soils. This study shows that magnetic susceptibility measurements can be used as a technique in which different types of soil pollution can be distinguished and can also be used to rapidly monitor anomalies in areas that might require expensive and time consuming detailed chemical analyses

Comparison of wind erosion based on measurements and SWEEP simulation: A case study in Kangbao County, Hebei Province, China

Farmland especially dry farmland managed in traditional ways has high wind erosion risk and contributes mainly to dust emission in arid area. Modeling predicting provides a general view to soil erosion susceptibility, and is very helpful for the understanding of potential spatial source of wind erosion. This study applied the Single-event Wind Erosion Evaluation Program (SWEEP) to predict soil wind erosion of farmland in the study area. SWEEP is a standalone version of the erosion sub-model from the Wind Erosion Prediction System (WEPS). It needs fewer calculation parameters than WEPS and is often used for single erosion events of limited size. The objective of this study was to test the feasibility of using SWEEP to estimate annual wind erosion of farmland over large areas (downwind distance >1600 m) with limited wind data (2005-2011) from weather stations. We validated the simulation results by comparing them with field measurements and wind tunnel data for the same soils. The soil material eroded by wind included PM10, suspension, saltation, and creep particles. Suspension particles were the main component involved in the soil loss (averaged 61.8%). However, saltation and creep particles dominate the particle clouds for fields with a downwind length of less than 550 m (averaged 56.6%), and the mass flux dominated by suspension particles stabilizes when this length is longer than 1000 m (averaged 83.4%). PM 10 always has very low proportion (<2.3%). Our validation results suggest that it is feasible to use SWEEP for large areas with limited wind data. However, SWEEP could not simulate the small soil losses that occur especially at low wind velocities well. Many factors contribute to this problem, but the main one is overestimation of the threshold wind velocity. Previous research suggest that it will be difficult to replace SWEEP's calculation algorithms for the threshold wind velocity, but both these algorithms and some SWEEP parameters must be improved to provide accurate predictions of soil erosion. (C) 2016 Elsevier B.V. All rights reserved

Spinulum lioui, a new species referred as to Lycopodium neopungens (Lycopodiopsida: Lycopodiaceae) in China

One earlier known species of Lycopodium from China, "L. neopungens H.S. Kung & Li Bing Zhang", is described as Spinulum lioui Li Bing Zhang & H.He (sp. nov.)

Disrupted Functional Brain Connectome in Individuals at Risk for Alzheimer's Disease

Background: Alzheimer's disease disrupts the topological architecture of whole-brain connectivity (i.e., the connectome); however, whether this disruption is present in amnestic mild cognitive impairment (aMCI), the prodromal stage of Alzheimer's disease, remains largely unknown. Methods: We employed resting-state functional magnetic resonance imaging and graph theory approaches to systematically investigate the topological organization of the functional connectome of 37 patients with aMCI and 47 healthy control subjects. Frequency-dependent brain networks were derived from wavelet-based correlations of both high-and low-resolution parcellation units. Results: In the frequency interval .031-.063 Hz, the aMCI patients showed an overall decreased functional connectivity of their brain connectome compared with control subjects. Further graph theory analyses of this frequency band revealed an increased path length of the connectome in the aMCI group. Moreover, the disease targeted several key nodes predominantly in the default-mode regions and key links primarily in the intramodule connections within the default-mode network and the intermodule connections among different functional systems. Intriguingly, the topological aberrations correlated with the patients' memory performance and differentiated individuals with aMCI from healthy elderly individuals with a sensitivity of 86.5% and a specificity of 85.1%. Finally, we demonstrated a high reproducibility of our findings across different large-scale parcellation schemes and validated the test-retest reliability of our network-based approaches. Conclusions: This study demonstrates a disruption of whole-brain topological organization of the functional connectome in aMCI. Our finding provides novel insights into the pathophysiological mechanism of aMCI and highlights the potential for using connectome-based metrics as a disease biomarker