Evaluation of the flexural mechanical properties of various thermoplastic denture base polymers.

This study evaluated the flexural mechanical properties of various thermoplastic denture base polymers (six polyamides, four acrylic resins, polyester, polypropylene, and polycarbonate) by three different testing conditions; specimens were tested in water bath at 37°C (Wet/Water, by ISO 20795-1), or in ambient air (Wet/Air) after being immersed in distilled water for 50 h, or after desiccation for 7 days (Dry/Air). The mean ultimate flexural strength (UFS) and flexural modulus (FM) for most products ranged from 27 to 61 MPa and from 611 to 1,783 MPa respectively, which failed to meet the minimum requirements of the international standard, except for polycarbonate (89 and 2,245 MPa). The mean UFS and FM values were ranked Dry/Air>Wet/Air>Wet/Water (p<0.05). In conclusion, the flexural mechanical properties of denture base polymers varied with the products and were significantly affected by the testing medium (air or water) and specimen conditions (wet or dry).

Improved performance in CAPRI round 37 using LZerD docking and template-based modeling with combined scoring functions.

We report our group's performance for protein-protein complex structure prediction and scoring in Round 37 of the Critical Assessment of PRediction of Interactions (CAPRI), an objective assessment of protein-protein complex modeling. We demonstrated noticeable improvement in both prediction and scoring compared to previous rounds of CAPRI, with our human predictor group near the top of the rankings and our server scorer group at the top. This is the first time in CAPRI that a server has been the top scorer group. To predict protein-protein complex structures, we used both multi-chain template-based modeling (TBM) and our protein-protein docking program, LZerD. LZerD represents protein surfaces using 3D Zernike descriptors (3DZD), which are based on a mathematical series expansion of a 3D function. Because 3DZD are a soft representation of the protein surface, LZerD is tolerant to small conformational changes, making it well suited to docking unbound and TBM structures. The key to our improved performance in CAPRI Round 37 was to combine multi-chain TBM and docking. As opposed to our previous strategy of performing docking for all target complexes, we used TBM when multi-chain templates were available and docking otherwise. We also describe the combination of multiple scoring functions used by our server scorer group, which achieved the top rank for the scorer phase.

Increased risk of thyroid diseases in patients with systemic lupus erythematosus: A nationwide population-based Study in Korea.

We investigated the association between autoimmune thyroid disease and systemic lupus erythematosus (SLE) using nationwide insurance claims data for the entire Korean population. Claims data for the period 2009-2013 were retrieved from the National Health Insurance System database. SLE and thyroid disease were identified using the International Classification of Diseases codes and medication information. Logistic regression analyses were used to evaluate the association between SLE and thyroid disease. The study used records from 17,495 patients with SLE and 52,485 age- and sex-matched control subjects. A greater prevalence of Graves' disease (0.94% vs. 0.46%, P < 0.001), Hashimoto's thyroiditis (2.68% vs. 0.80%, P < 0.001), and thyroid cancer (1.81% vs. 1.30%, P < 0.001) was observed in SLE patients than in control subjects. Multivariate regression analyses demonstrated that SLE was significantly associated with an increased risk of both autoimmune thyroid disease and thyroid cancer (Graves' disease: odds ratio [OR] 2.07, 95% confidence interval [CI] 1.70-2.53; Hashimoto's thyroiditis: OR 3.42, 95% CI 3.00-3.91; thyroid cancer: OR 1.40, 95% CI 1.22-1.60). Age- and sex- stratified analyses revealed that the risk of autoimmune thyroid disease in SLE patients was increased for all age groups and the female group. An association between thyroid cancer and SLE was identified only in the 20- to 59-year-old age group and in the female group. Using a large population-based study, we demonstrated that patients with SLE are at a greater risk of developing thyroid disease than matched control individuals.

Human and server docking prediction for CAPRI round 30-35 using LZerD with combined scoring functions.

We report the performance of protein-protein docking predictions by our group for recent rounds of the Critical Assessment of Prediction of Interactions (CAPRI), a community-wide assessment of state-of-the-art docking methods. Our prediction procedure uses a protein-protein docking program named LZerD developed in our group. LZerD represents a protein surface with 3D Zernike descriptors (3DZD), which are based on a mathematical series expansion of a 3D function. The appropriate soft representation of protein surface with 3DZD makes the method more tolerant to conformational change of proteins upon docking, which adds an advantage for unbound docking. Docking was guided by interface residue prediction performed with BindML and cons-PPISP as well as literature information when available. The generated docking models were ranked by a combination of scoring functions, including PRESCO, which evaluates the native-likeness of residues' spatial environments in structure models. First, we discuss the overall performance of our group in the CAPRI prediction rounds and investigate the reasons for unsuccessful cases. Then, we examine the performance of several knowledge-based scoring functions and their combinations for ranking docking models. It was found that the quality of a pool of docking models generated by LZerD, that is whether or not the pool includes near-native models, can be predicted by the correlation of multiple scores. Although the current analysis used docking models generated by LZerD, findings on scoring functions are expected to be universally applicable to other docking methods. Proteins 2017; 85:513-527. © 2016 Wiley Periodicals, Inc.

Protein structure prediction using residue- and fragment-environment potentials in CASP11.

An accurate scoring function that can select near-native structure models from a pool of alternative models is key for successful protein structure prediction. For the critical assessment of techniques for protein structure prediction (CASP) 11, we have built a protocol of protein structure prediction that has novel coarse-grained scoring functions for selecting decoys as the heart of its pipeline. The score named PRESCO (Protein Residue Environment SCOre) developed recently by our group evaluates the native-likeness of local structural environment of residues in a structure decoy considering positions and the depth of side-chains of spatially neighboring residues. We also introduced a helix interaction potential as an additional scoring function for selecting decoys. The best models selected by PRESCO and the helix interaction potential underwent structure refinement, which includes side-chain modeling and relaxation with a short molecular dynamics simulation. Our protocol was successful, achieving the top rank in the free modeling category with a significant margin of the accumulated Z-score to the subsequent groups when the top 1 models were considered. Proteins 2016; 84(Suppl 1):105-117. © 2015 Wiley Periodicals, Inc.

Combined Approach of Patch-Surfer and PL-PatchSurfer for Protein-Ligand Binding Prediction in CSAR 2013 and 2014.

The Community Structure-Activity Resource (CSAR) benchmark exercise provides a unique opportunity for researchers to objectively evaluate the performance of protein-ligand docking methods. Patch-Surfer and PL-PatchSurfer, molecular surface-based methods for predicting binding ligands of proteins developed in our group, were tested on both CSAR 2013 and 2014 benchmark exercises in combination with an empirical scoring function-based method, AutoDock, while we only participated in CSAR 2013 using Patch-Surfer. The prediction results for Phase 1 task in CSAR 2013 showed that Patch-Surfer was able to rank all the four designed binding proteins within top ranks, outperforming AutoDock Vina. In Phase 2 of 2013, PL-PatchSurfer correctly selected the correct ligand pose for two target proteins. PL-PatchSurfer performed reasonably well in ranking ligands according to their binding affinity and in selecting near-native ligand poses in 2013 Phase 3 and 2014 Phase 1, respectively, although AutoDock Vina showed better performance. Lastly, in the 2014 Phase 2 exercise, the PL-PatchSurfer scores computed for ligands to target protein pairs correlated well with their pIC50 values, which was better or comparable to results by other participants. Overall, our methods showed fairly good performance in CSAR 2013 and 2014. Unique characteristics of the methods are discussed in comparison with AutoDock.

Tuning of Pectin Methylesterification: PECTIN METHYLESTERASE INHIBITOR 7 MODULATES THE PROCESSIVE ACTIVITY OF CO-EXPRESSED PECTIN METHYLESTERASE 3 IN A pH-DEPENDENT MANNER.

Pectin methylesterases (PMEs) catalyze the demethylesterification of homogalacturonan domains of pectin in plant cell walls and are regulated by endogenous pectin methylesterase inhibitors (PMEIs). In Arabidopsis dark-grown hypocotyls, one PME (AtPME3) and one PMEI (AtPMEI7) were identified as potential interacting proteins. Using RT-quantitative PCR analysis and gene promoter::GUS fusions, we first showed that AtPME3 and AtPMEI7 genes had overlapping patterns of expression in etiolated hypocotyls. The two proteins were identified in hypocotyl cell wall extracts by proteomics. To investigate the potential interaction between AtPME3 and AtPMEI7, both proteins were expressed in a heterologous system and purified by affinity chromatography. The activity of recombinant AtPME3 was characterized on homogalacturonans (HGs) with distinct degrees/patterns of methylesterification. AtPME3 showed the highest activity at pH 7.5 on HG substrates with a degree of methylesterification between 60 and 80% and a random distribution of methyl esters. On the best HG substrate, AtPME3 generates long non-methylesterified stretches and leaves short highly methylesterified zones, indicating that it acts as a processive enzyme. The recombinant AtPMEI7 and AtPME3 interaction reduces the level of demethylesterification of the HG substrate but does not inhibit the processivity of the enzyme. These data suggest that the AtPME3·AtPMEI7 complex is not covalently linked and could, depending on the pH, be alternately formed and dissociated. Docking analysis indicated that the inhibition of AtPME3 could occur via the interaction of AtPMEI7 with a PME ligand-binding cleft structure. All of these data indicate that AtPME3 and AtPMEI7 could be partners involved in the fine tuning of HG methylesterification during plant development.

Detecting local residue environment similarity for recognizing near-native structure models.

We developed a new representation of local amino acid environments in protein structures called the Side-chain Depth Environment (SDE). An SDE defines a local structural environment of a residue considering the coordinates and the depth of amino acids that locate in the vicinity of the side-chain centroid of the residue. SDEs are general enough that similar SDEs are found in protein structures with globally different folds. Using SDEs, we developed a procedure called PRESCO (Protein Residue Environment SCOre) for selecting native or near-native models from a pool of computational models. The procedure searches similar residue environments observed in a query model against a set of representative native protein structures to quantify how native-like SDEs in the model are. When benchmarked on commonly used computational model datasets, our PRESCO compared favorably with the other existing scoring functions in selecting native and near-native models.

Clinical risk factors for osteoporotic fracture: a population-based prospective cohort study in Korea.

Clinical risk factors (CRFs), either alone or in combination with bone mineral density, are used to determine the fracture risk for clinical assessment and to determine intervention thresholds. Because fracture risk is strongly affected by ethnicity and population-specific differences, we sought to identify Korean-specific CRFs for fracture, in combination with quantitative ultrasound (qUS) measurements of the radius and tibia. A total of 9351 subjects (4732 men and 4619 women) aged 40 to 69 years were followed for a mean of 46.3 +/- 2.2 months. We obtained CRF information using a standardized questionnaire and measured anthropometric variables. Speed of sound at the radius (SoSR) and tibia (SoST) were measured by qUS. Fracture events were recorded using a questionnaire, and a height-loss threshold was used as an indicator of vertebral fracture. Relative risks were calculated by Cox regression analysis. A total of 195 subjects (61 men and 134 women) suffered low-trauma fractures. Older age, lower body mass index (BMI), and previous fracture history were positively associated with fracture risk in both sexes. Decreased hip circumference, lack of regular exercise, higher alcohol intake, menopause, and osteoarthritis history were further independent CRFs for fracture in women. However, neither SoSR nor SoST was independently associated with fracture risk. In this study, we identified the major Korean-specific CRFs for fracture and found that smaller hip circumference was a novel risk factor. This information will allow optimal risk-assessment targeting Koreans for whom treatment would provide the greatest benefit.

Complexity changes of the EEG induced by alcohol cue exposure in alcoholics and social drinkers.

BACKGROUND: An understanding of the neurophysiological mechanisms underlying alcohol craving is important in the effective treatment of alcohol dependence. The aim of this study was to examine the utility of the electroencephalogram (EEG) to measure the changes in electrical brain activity of alcoholics when exposed to alcohol-specific cues. METHODS: Fifteen adult alcoholic subjects (four women) with a mean age of 35 (SD = 4.5) and 10 healthy social drinking controls (three women) with a mean age of 34 (SD = 5.6) were recruited. Subjects were serially rated for alcohol craving after presentations of pictures of control nonalcoholic and alcohol beverages. After the picture presentation, the EEG was recorded (16,384 data points for each epoch) with eyes closed. The dimensional complexity (D2) was estimated as a measure of complexity of the EEG. RESULTS: Alcoholic subjects exhibited a significant increase in the D2 values of the EEG in frontal (F3, F4), right posterior temporal (T6), and occipital (O1, O2) regions after viewing alcohol cues compared with viewing other beverage cues. These results indicate that more complex (or higher) cortical activity is induced over specific brain regions of alcoholic subjects by alcohol-specific cues. Changes in subscale of alcohol craving between nonalcoholic and alcohol pictures were correlated with changes in D2 values in the left frontal (F3) region in alcoholic subjects. CONCLUSIONS: These findings suggest that, when subjects are exposed to alcohol cues, changes in the EEG complexity are induced in frontal, right posterior temporal, and occipital areas, which may be key brain structures for alcohol craving. In addition, nonlinear measures like the D2 are useful in evaluating alcohol cue-induced brain activity from the EEG.

Delivery modes and neonatal EEG: spatial pattern analysis.

BACKGROUND: Animal studies indicate that postnatal adaptation and development of neonates could be different due to the birth method and that these effects may last throughout adulthood. STUDY DESIGN: We applied a spatio-temporal analysis to EEG recordings of a group of neonates to investigate the influence of a cesarean section on maturation and extrauterine adaptation of the brain. EEG were recorded at 2 h and at 24 h after delivery. SUBJECTS: A spectral analysis technique, the so-called Karhunen-Loeve (KL) method, was applied to EEG of 10 neonates from vaginal delivery and 17 from C-section to obtain the spatio-temporal eigenpatterns. RESULTS: Spatio-temporal analysis showed noticeable pattern differences between the two groups. Compared to the C-section, the vaginal delivered neonate's EEG recordings showed a significant increase of amplitude at Fp1 in the pattern 24 h after the delivery, but not 2 h after delivery. Dynamics in this spectral analyses were not significantly different between both groups 2 h after delivery, but the regional differences increased during the next day between both groups. CONCLUSIONS: This could come from the early insufficient complexity in C-section neonates. Global EEG complexity in C-section neonates fell short of that of vaginal delivered neonates 2 h after delivery. Many aspects of pattern change in C-section neonates followed the nature of vaginal delivered neonates. These could be considered as parts of a retarded transition of C-section neonates in the early adaptation, but some of the differences in global EEG pattern could not be explained in this way. Pattern analysis suggests that the neuronal activities of the neonatal brain are changing regionally concurrent with bi-hemispheric global dynamics. Moreover, the delivery modes could have an influence on the early postneonatal adaptation of the physiological activity in brain.