Biologic stability of plasma ion-implanted miniscrews

published_or_final_versio

A modeling study on the response of Chesapeake Bay to hurricane events of Floyd and Isabel

The response of Chesapeake Bay to forcing from two hurricanes is investigated using an unstructured-grid three-dimensional hydrodynamic model SELFE. The model domain includes Chesapeake Bay, its tributaries, and the extended continental shelf in the mid-Atlantic Bight. The hurricanes chosen for the study are Hurricane Floyd (1999) and Hurricane Isabel (2003), both of which made landfall within 100 km of the mouth of the Bay. The model results agree reasonably well with field observations of water level, velocity, and salinity. From the Bay\u27s water level response to the hurricanes, it was found that the storm surge in the Bay has two distinct stages: an initial stage set up by the remote winds and the second stage - a primary surge induced by the local winds. For the initial stage, the rising of the coastal sea level was setup by the remote wind of both hurricanes similarly, but for the second stage, the responses to the two hurricanes\u27 local winds are significantly different. Hurricane Floyd was followed by down-Bay winds that canceled the initial setup and caused a set-down from the upper Bay. Hurricane Isabel, on the other hand, was followed by up-Bay winds, which reinforced the initial setup and continued to rise up against the head of the Bay. From the perspective of volume and salt fluxes, it is evident that an oceanic saltwater influx is pushed into the Bay from the continental shelf by the remote wind fields in the initial stages of the storm surge for both Floyd and Isabel. In the second stage after the hurricane made landfall, the Bay\u27s local wind plays a key role in modulating the salinity and velocity fields through vertical mixing and longitudinal salt transport. Controlled numerical experiments are conducted in order to identify and differentiate the roles played by the local wind in stratified and destratified conditions. Down-estuary local wind stress (of Hurricane Floyd-type) tends to enhance stratification under moderate winds, but exhibits an increasing-then-decreasing stage when the wind stress increases. The up-estuary local wind stress (of Hurricane Isabel-type) tends to penetrate deeper into the water column, which reduces stratification by reversing gravitational circulation. To characterize mixing conditions in the estuary, a modified horizontal Richardson number that incorporates wind stress, wind direction, horizontal salinity gradient, and vertical eddy viscosity is used for both hurricanes. Finally, the direct precipitation of rainfall into the Bay during Hurricane Floyd appears to create not only a thin surface layer of low salinity but also a seaward barotropic pressure gradient that affects the subsequent redistribution of salinity after the storm. (C) 2012 Elsevier Ltd. All rights reserved

Use of endobronchial one-way valves reveals questions on etiology of spontaneous pneumothorax: report of three cases

Spontaneous pneumothoraces are believed to arise when air from the supplying airway exit via a ruptured visceral pleural bleb into the pleural cavity. Endobronchial one-way valves (EBVs) allow air exit (but not entry) from individual segmental airways. Systematic deployment of EBVs was applied to three patients with secondary spontaneous pneumothoraces and persistent airleak. In all cases, balloon-catheter occlusion of the upper lobe bronchus stopped the airleak. EBVs applied to individual upper lobe segmental airways failed to terminate the airleak, which only stopped after placements of multiple EBVs to occlude all upper lobe segments. The observation questions the traditional belief of 'one-airway-one-bleb-one-leak' in spontaneous pneumothorax

IL-12p40 Homodimer Ameliorates Experimental Autoimmune Arthritis

IL-23 is the key cytokine that induces the expansion of Th17 cells. It is composed of p19 and p40 subunits of IL-12. The p40 subunit binds competitively to the receptor of IL-23 and blocks its activity. Our aim was to assess the preventive and therapeutic effect of the IL-12p40 homodimer (p40)(2) subunit in autoimmune arthritis animal models. In the current study, using IL-1R antagonist-knockout mice and a collagen-induced arthritis model, we investigated the suppressive effect of (p40)(2) on inflammatory arthritis. We demonstrated that the recombinant adenovirus-expressing mouse (p40)(2) model prevented the development of arthritis when given before the onset of arthritis. It also decreased the arthritis index and joint erosions in the mouse model if transferred after arthritis was established. (p40)(2) inhibited the production of inflammatory cytokines and Ag-specific T cell proliferation. It also induced CD4(+)CD25(+)Foxp3 regulatory T (Treg) cells in vitro and in vivo, whereas the generation of retinoic acid receptor-related organ receptor gamma t and Th17 cells was suppressed. The induction of Treg cells and the suppression of Th17 cells were mediated via activated STAT5 and suppressed STAT3. Our data suggest that (p40)(2) suppressed inflammatory arthritis successfully. This could be a useful therapeutic approach in autoimmune arthritis to regulate the Th17/Treg balance and IL-23 signaling.1156Ysciescopu

Brain structural covariance networks in obsessive-compulsive disorder: a graph analysis from the ENIGMA Consortium.

Brain structural covariance networks reflect covariation in morphology of different brain areas and are thought to reflect common trajectories in brain development and maturation. Large-scale investigation of structural covariance networks in obsessive-compulsive disorder (OCD) may provide clues to the pathophysiology of this neurodevelopmental disorder. Using T1-weighted MRI scans acquired from 1616 individuals with OCD and 1463 healthy controls across 37 datasets participating in the ENIGMA-OCD Working Group, we calculated intra-individual brain structural covariance networks (using the bilaterally-averaged values of 33 cortical surface areas, 33 cortical thickness values, and six subcortical volumes), in which edge weights were proportional to the similarity between two brain morphological features in terms of deviation from healthy controls (i.e. z-score transformed). Global networks were characterized using measures of network segregation (clustering and modularity), network integration (global efficiency), and their balance (small-worldness), and their community membership was assessed. Hub profiling of regional networks was undertaken using measures of betweenness, closeness, and eigenvector centrality. Individually calculated network measures were integrated across the 37 datasets using a meta-analytical approach. These network measures were summated across the network density range of K = 0.10-0.25 per participant, and were integrated across the 37 datasets using a meta-analytical approach. Compared with healthy controls, at a global level, the structural covariance networks of OCD showed lower clustering (P < 0.0001), lower modularity (P < 0.0001), and lower small-worldness (P = 0.017). Detection of community membership emphasized lower network segregation in OCD compared to healthy controls. At the regional level, there were lower (rank-transformed) centrality values in OCD for volume of caudate nucleus and thalamus, and surface area of paracentral cortex, indicative of altered distribution of brain hubs. Centrality of cingulate and orbito-frontal as well as other brain areas was associated with OCD illness duration, suggesting greater involvement of these brain areas with illness chronicity. In summary, the findings of this study, the largest brain structural covariance study of OCD to date, point to a less segregated organization of structural covariance networks in OCD, and reorganization of brain hubs. The segregation findings suggest a possible signature of altered brain morphometry in OCD, while the hub findings point to OCD-related alterations in trajectories of brain development and maturation, particularly in cingulate and orbitofrontal regions

Image informatics strategies for deciphering neuronal network connectivity

Brain function relies on an intricate network of highly dynamic neuronal connections that rewires dramatically under the impulse of various external cues and pathological conditions. Among the neuronal structures that show morphologi- cal plasticity are neurites, synapses, dendritic spines and even nuclei. This structural remodelling is directly connected with functional changes such as intercellular com- munication and the associated calcium-bursting behaviour. In vitro cultured neu- ronal networks are valuable models for studying these morpho-functional changes. Owing to the automation and standardisation of both image acquisition and image analysis, it has become possible to extract statistically relevant readout from such networks. Here, we focus on the current state-of-the-art in image informatics that enables quantitative microscopic interrogation of neuronal networks. We describe the major correlates of neuronal connectivity and present workflows for analysing them. Finally, we provide an outlook on the challenges that remain to be addressed, and discuss how imaging algorithms can be extended beyond in vitro imaging studies

Academic Performance and Behavioral Patterns

Identifying the factors that influence academic performance is an essential part of educational research. Previous studies have documented the importance of personality traits, class attendance, and social network structure. Because most of these analyses were based on a single behavioral aspect and/or small sample sizes, there is currently no quantification of the interplay of these factors. Here, we study the academic performance among a cohort of 538 undergraduate students forming a single, densely connected social network. Our work is based on data collected using smartphones, which the students used as their primary phones for two years. The availability of multi-channel data from a single population allows us to directly compare the explanatory power of individual and social characteristics. We find that the most informative indicators of performance are based on social ties and that network indicators result in better model performance than individual characteristics (including both personality and class attendance). We confirm earlier findings that class attendance is the most important predictor among individual characteristics. Finally, our results suggest the presence of strong homophily and/or peer effects among university students

Worksite health screening programs for predicting the development of Metabolic Syndrome in middle-aged employees: a five-year follow-up study

<p>Abstract</p> <p>Background</p> <p>Metabolic syndrome (MetS) management programs conventionally focus on the adults having MetS. However, risk assessment for MetS development is also important for many adults potentially at risk but do not yet fulfill MetS criteria at screening. Therefore, we conducted this follow-up study to explore whether initial screening records can be efficiently applied on the prediction of the MetS occurrence in healthy middle-aged employees.</p> <p>Methods</p> <p>Utilizing health examination data, a five-year follow-up observational study was conducted for 1384 middle-aged Taiwanese employees not fulfilling MetS criteria. Data analyzed included: gender, age, MetS components, uric acid, insulin, liver enzymes, sonographic fatty liver, hepatovirus infections and lifestyle factors. Multivariate logistic regression was used to estimate the adjusted odds ratios (OR) and 95% confidence interval (CI) of risk for MetS development. The synergistic index (SI) values and their confidence intervals of risk factor combinations were calculated; and were used to estimate the interacting effects of coupling MetS components on MetS development.</p> <p>Results</p> <p>Within five years, 13% (175 out of 1384) participants fulfilled MetS criteria. The ORs for MetS development among adults initially having one or two MetS components were 2.8 and 7.3, respectively (both p < 0.01), versus the adults having zero MetS component count at screening. Central obesity carried an OR of 7.5 (p < 0.01), which far exceeded other risk factors (all ORs < 2.7). Synergistic effects on MetS development existed between coupling MetS components: 1. High blood pressure plus low-HDL demonstrated an OR of 11.7 (p < 0.01) for MetS development and an SI of 4.7 (95% CI, 2.1-10.9). 2. High blood pressure plus hyperglycemia had an OR of 7.9 (p < 0.01), and an SI of 2.7 (95% CI, 1.2-6.4).</p> <p>Conclusion</p> <p>MetS component count and combination can be used in predicting MetS development for participants potentially at risk. Worksite MetS screening programs simultaneously allow for finding out cases and for assessing risk of MetS development.</p