XRCC1, but not APE1 and hOGG1 gene polymorphisms is a risk factor for pterygium.

PurposeEpidemiological evidence suggests that UV irradiation plays an important role in pterygium pathogenesis. UV irradiation can produce a wide range of DNA damage. The base excision repair (BER) pathway is considered the most important pathway involved in the repair of radiation-induced DNA damage. Based on previous studies, single-nucleotide polymorphisms (SNPs) in 8-oxoguanine glycosylase-1 (OGG1), X-ray repair cross-complementing-1 (XRCC1), and AP-endonuclease-1 (APE1) genes in the BER pathway have been found to affect the individual sensitivity to radiation exposure and induction of DNA damage. Therefore, we hypothesize that the genetic polymorphisms of these repair genes increase the risk of pterygium.MethodsXRCC1, APE1, and hOGG1 polymorphisms were studied using fluorescence-labeled Taq Man probes on 83 pterygial specimens and 206 normal controls.ResultsThere was a significant difference between the case and control groups in the XRCC1 genotype (p=0.038) but not in hOGG1 (p=0.383) and APE1 (p=0.898). The odds ratio of the XRCC1 A/G polymorphism was 2.592 (95% CI=1.225-5.484, p=0.013) and the G/G polymorphism was 1.212 (95% CI=0.914-1.607), compared to the A/A wild-type genotype. Moreover, individuals who carried at least one C-allele (A/G and G/G) had a 1.710 fold increased risk of developing pterygium compared to those who carried the A/A wild type genotype (OR=1.710; 95% CI: 1.015-2.882, p=0.044). The hOGG1 and APE1 polymorphisms did not have an increased odds ratio compared with the wild type.ConclusionsXRCC1 (Arg399 Glu) is correlated with pterygium and might become a potential marker for the prediction of pterygium susceptibility

Comparison of the surface roughness of gypsum models constructed using various impression materials and gypsum products

AbstractBackground/purposeThis study compared the surface roughness of gypsum models constructed using various impression materials, gypsum products, and storage times before repouring.Materials and methodsThree alginate impression materials, four commercial silicone impression materials, and three types of gypsum product (MG crystal rock, Super hard stone, and MS plaster) were used. Impression materials were mixed and poured into five plastic rings (20 mm in diameter and 2 mm high) for each group, and the surfaces of the set gypsum product models of 63 groups, which were poured immediately, and 1 hour and 24 hours later, were assessed using a surface roughness tester. One-way ANOVA and Bonferroni's comparison tests were used for the statistical analyses.ResultsThe surface roughness: (1) was greater for most specimens constructed from alginate impression material (2.72 ± 0.45–7.42 ± 0.66 μm) than from silicone impression materials (1.86 ± 0.19–2.75 ± 0.44 μm); (2) differed with the type of gypsum product when using alginate impression materials (surface roughness of Super hard stone > MG crystal rock > MS plaster), but differed little for silicone impression materials; and (3) differed very little with the storage time before repouring.ConclusionThe surface roughness of stone models was mainly determined by the type of alginate impression material, and was less affected by the type of silicone rubber impression material or gypsum product, or the storage time before repouring

Population aging in the People's Republic of China

This paper provides a factual assessment of China's population aging and its social and economic consequences. It is projected that China will have a substantially older population in the middle of the 21st century. Major policy implications concerning old age support and health care have been examined.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/26458/1/0000546.pd

Future change in extreme precipitation in East Asian spring and Mei-yu seasons in two high-resolution AGCMs

Precipitation in the spring and Mei-yu seasons, the main planting and growing period in East Asia, is crucial to water resource management. Changes in spring and Mei-yu extreme precipitation under global warming are evaluated based on two sets of high-resolution simulations with various warming pattern of sea surface temperature (SST'spa). In the spring season, extreme precipitation exhibits larger enhancements over the northern flank of the present-day prevailing rainy region and a tendency of increased occurrence and enhanced intensity in the probability distribution. These changes imply a northward extension of future spring rainband. Although the mean precipitation shows minor change, enhanced precipitation intensity, less total rainfall occurrence, and prolonged consecutive dry days suggest a more challenging water resource management in the warmer climate. The projected enhancement in precipitation intensity is robust compared with the internal variability related to initial conditions (σˆint) and the uncertainty caused by SST'spa (σˆΔSST). In the Mei-yu season, extreme precipitation strengthens and becomes more frequent over the present-day prevailing rainband region. The thermodynamic component of moisture flux predominantly contributes to the changes in the spring season. In the Mei-yu season, both the thermodynamic and dynamic components of moisture flux enhance the moisture transport and intensify the extreme precipitation from southern China to northeast Asia. Compared with spring season, projecting future Mei-yu precipitation is more challenging because of its higher uncertainty associated with 1) the σˆint and σˆΔSST embedded in the projections and 2) the model characteristics of present-day climatology that determines the spatial distribution of precipitation enhancement.publishedVersio

WKGM: Weight-K-space Generative Model for Parallel Imaging Reconstruction

Deep learning based parallel imaging (PI) has made great progresses in recent years to accelerate magnetic resonance imaging (MRI). Nevertheless, it still has some limitations, such as the robustness and flexibility of existing methods have great deficiency. In this work, we propose a method to explore the k-space domain learning via robust generative modeling for flexible calibration-less PI reconstruction, coined weight-k-space generative model (WKGM). Specifically, WKGM is a generalized k-space domain model, where the k-space weighting technology and high-dimensional space augmentation design are efficiently incorporated for score-based generative model training, resulting in good and robust reconstructions. In addition, WKGM is flexible and thus can be synergistically combined with various traditional k-space PI models, which can make full use of the correlation between multi-coil data and realizecalibration-less PI. Even though our model was trained on only 500 images, experimental results with varying sampling patterns and acceleration factors demonstrate that WKGM can attain state-of-the-art reconstruction results with the well-learned k-space generative prior.Comment: 11pages, 12 figure

A model-based circular binary segmentation algorithm for the analysis of array CGH data

<p>Abstract</p> <p>Background</p> <p>Circular Binary Segmentation (CBS) is a permutation-based algorithm for array Comparative Genomic Hybridization (aCGH) data analysis. CBS accurately segments data by detecting change-points using a maximal-<it>t </it>test; but extensive computational burden is involved for evaluating the significance of change-points using permutations. A recent implementation utilizing a hybrid method and early stopping rules (hybrid CBS) to improve the performance in speed was subsequently proposed. However, a time analysis revealed that a major portion of computation time of the hybrid CBS was still spent on permutation. In addition, what the hybrid method provides is an approximation of the significance upper bound or lower bound, not an approximation of the significance of change-points itself.</p> <p>Results</p> <p>We developed a novel model-based algorithm, extreme-value based CBS (eCBS), which limits permutations and provides robust results without loss of accuracy. Thousands of aCGH data under null hypothesis were simulated in advance based on a variety of non-normal assumptions, and the corresponding maximal-<it>t </it>distribution was modeled by the Generalized Extreme Value (GEV) distribution. The modeling results, which associate characteristics of aCGH data to the GEV parameters, constitute lookup tables (eXtreme model). Using the eXtreme model, the significance of change-points could be evaluated in a constant time complexity through a table lookup process.</p> <p>Conclusions</p> <p>A novel algorithm, eCBS, was developed in this study. The current implementation of eCBS consistently outperforms the hybrid CBS 4× to 20× in computation time without loss of accuracy. Source codes, supplementary materials, supplementary figures, and supplementary tables can be found at <url>http://ntumaps.cgm.ntu.edu.tw/eCBSsupplementary</url>.</p

Application and comparison of scoring indices to predict outcomes in patients with healthcare-associated pneumonia

Introduction: Healthcare-associated pneumonia HCAP is a relatively new category of pneumonia. It refers to infections that occur prior to hospital admission in patients with specific risk factors following contact or exposure to a healthcare environment. There is currently no scoring index to predict the outcomes of HCAP patients. We applied and compared different community acquired pneumonia CAP scoring indices to predict 30-day mortality and 3-day and 14-day intensive care unit ICU admission in patients with HCAP. Methods: We conducted a retrospective cohort study based on an inpatient database from six medical centers, recruiting a total of 444 patients with HCAP between 1 January 2007 and 31 December 2007. Pneumonia severity scoring indices including PSI pneumonia severity index, CURB 65 confusion, urea, respiratory rate, blood pressure , age 65, IDSA/ATS Infectious Diseases Society of America/American Thoracic Society, modified ATS rule, SCAP severe community acquired pneumonia, SMART-COP systolic blood pressure, multilobar involvement, albumin, respiratory rate, tachycardia, confusion, oxygenation, pH, SMRT- CO systolic blood pressure, multilobar involvement, respiratory rate, tachycardia, confusion, oxygenation, and SOAR systolic blood pressure, oxygenation, age, respiratory rate were calculated for each patient. Patient characteristics, co-morbidities, pneumonia pathogen culture results, length of hospital stay LOS, and length of ICU stay were also recorded. Results: PSI > 90 has the highest sensitivity in predicting mortality, followed by CURB-65 >= 2 and SCAP > 9 SCAP score area under the curve AUC: 0.71, PSI AUC: 0.70 and CURB-65 AUC: 0.66. Compared to PSI, modified ATS, IDSA/ATS, SCAP, and SMART-COP were easy to calculate. For predicting ICU admission Day 3 and Day 14, modified ATS AUC: 0.84, 0.82 , SMART-COP AUC: 0.84, 0.82, SCAP AUC: 0.82, 0.80 and IDSA/ ATS AUC: 0.80, 0 .79 performed better statistically significant difference than PSI, CURB- 65, SOAR and SMRT-CO. Conclusions: The utility of the scoring indices for risk assessment in patients with healthcare-associated pneumonia shows that the scoring indices originally designed for CAP can be applied to HCAP

Gravity Data Reveal New Evidence of an Axial Magma Chamber Beneath Segment 27 in the Southwest Indian Ridge

Hydrothermal systems are integral to mid-ocean ridge activity; they form massive seafloor sulfide (SMS) deposits rich in various metallic elements, which are potential mineral resources. Since 2007, many hydrothermal fields have been discovered along the ultraslow-spreading Southwest Indian Ridge (SWIR). The Duanqiao hydrothermal field is located at segment 27’s axis between the Indomed and Gallieni transform faults; tomography models reveal an obvious low-velocity anomaly beneath it, indicating a possible axial magma chamber (AMC). However, confirmation of an AMC’s existence requires further study and evidence. In this study, we first calculated the gravity effect to identify the heterogeneous distribution of crustal density beneath segment 27 and the surrounding area. Next, we used the gravity-inversion method to obtain the crustal density structure beneath the study area. The results indicate that a thickened crust and low-density crustal materials exist beneath segment 27. The low-density anomaly in the lower crust beneath the Duanqiao hydrothermal field suggests the existence of an AMC covered with a cold and dense upper crust. The density results identify several faults, which provide potential channels for magma migration. In addition, the melt migrates westward and redistributes laterally toward the segment’s western end. However, when migrating toward the segment’s eastern end, the melt is affected by a rapid cooling mechanism. Therefore, the segment’s ends present different density features and morphologies of nontransform discontinuities (NTDs