Storm Surges in the Region of Western Alaska

Within the period of the historical record there have been several occurrences of extensive damage from storm-surge-related coastal flooding in the region of Nome, Alaska. The most recent of these events, although by no means the most destructive, occurred in association with the storm of 5–6 October 1992. Despite the small population of Nome (approximately 4000 people), total damage costs exceeded $6 million. The research into the nature and causes of such flooding events has focused on this October 1992 case. The authors have, however, also examined a weaker, shorter-duration event that occurred on 20 August 1993 and, for contrast, a case in September 1993 where a sustained offshore wind transported water out of Norton Sound. Tide gauge data from Nome were used to quantitatively assess the associated changes in water level, and meteorological analyses were utilized to examine the associated synoptic-scale circulations and their evolution. In addition, numerical modeling experiments were conducted using an extratropical storm surge model. (A version of this model is operational for the east coast of the United States.) Hindcasts of phase and amplitude for the October 1992 and September 1993 events agreed well with observations. Simulations of the shorter- duration August 1993 event were in poorer agreement with observations and indicate several possibilities for future improvement of the performance of the surge model: enhancement of the horizontal and temporal resolution of the model domain; more accurate input sea level pressure and wind data; and improvements to the surge model itself (e.g., inclusion of sea ice). Overall, however, results indicate that recent operational implementation of the model should be of significant benefit to coastal forecasters

Storm Surges in the Region of Western Alaska

Within the period of the historical record there have been several occurrences of extensive damage from storm-surge-related coastal flooding in the region of Nome, Alaska. The most recent of these events, although by no means the most destructive, occurred in association with the storm of 5–6 October 1992. Despite the small population of Nome (approximately 4000 people), total damage costs exceeded $6 million. The research into the nature and causes of such flooding events has focused on this October 1992 case. The authors have, however, also examined a weaker, shorter-duration event that occurred on 20 August 1993 and, for contrast, a case in September 1993 where a sustained offshore wind transported water out of Norton Sound. Tide gauge data from Nome were used to quantitatively assess the associated changes in water level, and meteorological analyses were utilized to examine the associated synoptic-scale circulations and their evolution. In addition, numerical modeling experiments were conducted using an extratropical storm surge model. (A version of this model is operational for the east coast of the United States.) Hindcasts of phase and amplitude for the October 1992 and September 1993 events agreed well with observations. Simulations of the shorter-duration August 1993 event were in poorer agreement with observations and indicate several possibilities for future improvement of the performance of the surge model: enhancement of the horizontal and temporal resolution of the model domain; more accurate input sea level pressure and wind data; and improvements to the surge model itself (e.g., inclusion of sea ice). Overall, however, results indicate that recent operational implementation of the model should be of significant benefit to coastal forecasters

Genetic associations with childhood brain growth, defined in two longitudinal cohorts

Genome-wide association studies (GWASs) are unraveling the genetics of adult brain neuroanatomy as measured by cross-sectional anatomic magnetic resonance imaging (aMRI). However, the genetic mechanisms that shape childhood brain development are, as yet, largely unexplored. In this study we identify common genetic variants associated with childhood brain development as defined by longitudinal aMRI. Genome-wide single nucleotide polymorphism (SNP) data were determined in two cohorts: one enriched for attention-deficit/hyperactivity disorder (ADHD) (LONG cohort: 458 participants; 119 with ADHD) and the other from a population-based cohort (Generation R: 257 participants). The growth of the brain's major regions (cerebral cortex, white matter, basal ganglia, and cerebellum) and one region of interest (the right lateral prefrontal cortex) were defined on all individuals from two aMRIs, and a GWAS and a pathway analysis were performed. In addition, association between polygenic risk for ADHD and brain growth was determined for the LONG cohort. For white matter growth, GWAS meta-analysis identified a genome-wide significant intergenic SNP (rs12386571, P = 9.09 × 10-9 ), near AKR1B10. This gene is part of the aldo-keto reductase superfamily and shows neural expression. No enrichment of neural pathways was detected and polygenic risk for ADHD was not associated with the brain growth phenotypes in the LONG cohort that was enriched for the diagnosis of ADHD. The study illustrates the use of a novel brain growth phenotype defined in vivo for further study

Genipin modified silk fibroin nanometric-nets

Nanometric silk-fibroin nets were fabricated by electrospinning from regenerated Bombyx mori silk-fibroin (SF)/formic acid solutions with the addition of genipin (GE), 2, 15 and 24 h after the solution preparation. After spinning, the pure fibroin nanofibers were water soluble and needed a further stabilization process, whereas the reaction of fibroin with genipin resulted in water-insoluble fibroin nets due to conformational changes induced in the fibroin by the genipin. SFGE nanofibers presented diameters ranging from 140 to 590 nm and were generally thinner than pure SF nanofibers. The secondary structure of SF into SFGE nanofibers showed the presence of a β-sheet conformation together with β-turn intermediates (turns and bends). The approach described in this paper provides an alternative method of designing SF nanofibers that are already water insoluble, without any stability post-treatment needed

Size distribution and rate of dust generated during grain elevator handling

Dust generated during grain handling can pose a safety and health hazard and is an air pollutant. This study was conducted to characterize the particle size distribution (PSD) of dust generated during handling of wheat and shelled corn in the research elevator of the USDA Grain Marketing and Production Research Center and determine the effects of grain lot, repeated transfer, and grain types on the PSD. Dust samples were collected on glass fiber filters with high volume samplers from the lower and upper ducts upstream of the cyclone dust collectors. A laser diffraction analyzer was used to measure the PSD of the collected dust. For wheat, the size distribution of dust from the upper and lower ducts showed similar trends among grain lots but differed between the two ducts. The percentages of particulate matter (PM)‐2.5, PM‐4, and PM‐10 were 5.15%, 9.65%, and 33.6% of the total wheat dust, respectively. The total dust mass flow rate was 0.94 g/s (equivalent to 64.6 g/t of wheat handled). For shelled corn, the size distributions of the dust samples from the upper and lower ducts also showed similar trends among transfers but differed between the two ducts. The percentages of PM‐2.5, PM‐4, and PM‐10 were 7.46%, 9.99%, and 28.9% of the total shelled corn dust, respectively. The total dust mass flow rate was 2.91 g/s (equivalent to 185.1 g/t of corn handled). Overall, the corn and wheat differed significantly in the size distribution and the rate of total dust generated

Proteomic analysis of the response of the plant growth-promoting bacterium Pseudomonas putida UW4 to nickel stress

<p>Abstract</p> <p>Background</p> <p>Plant growth-promoting bacteria can alleviate the inhibitory effects of various heavy metals on plant growth, via decreasing levels of stress-induced ethylene. However, little has been done to detect any mechanisms specific for heavy metal resistance of this kind of bacteria. Here, we investigate the response of the wild-type plant growth-promoting bacterium <it>Pseudomonas putida </it>UW4 to nickel stress using proteomic approaches. The mutant strain <it>P. putida </it>UW4/AcdS^-, lacking a functional 1-aminocyclopropane-1-carboxylic acid deaminase gene, was also assessed for its response to nickel stress.</p> <p>Results</p> <p>Two dimensional difference in-gel electrophoresis (DIGE) was used to detect significantly up- or down- regulated proteins (<it>p </it>< 0.05, | ratio | > 1.5) in <it>P. putida </it>in response to the presence of 2 mM Ni. Out of a total number of 1,702 proteins detected on the analytical gels for <it>P. putida </it>UW4, the expression levels of 82 (4.82%) proteins increased significantly while the expression of 81 (4.76%) proteins decreased significantly. Of 1,575 proteins detected on the analytical gels for <it>P. putida </it>UW4/AcdS^-, the expression levels of 74 (4.70%) proteins increased and 51 (3.24%) proteins decreased significantly. Thirty-five proteins whose expression was altered were successfully identified by mass spectrometry and sequence comparisons with related species. Nineteen of the identified proteins were detected as differentially expressed in both wild-type and mutant expression profiles.</p> <p>Conclusion</p> <p>Functional assessment of proteins with significantly altered expression levels revealed several mechanisms thought to be involved in bacterial heavy metal detoxification, including general stress adaptation, anti-oxidative stress and heavy metal efflux proteins. This information may contribute to the development of plant growth-promoting bacteria mediated phytoremediation processes.</p

Elevated fasting insulin predicts the future incidence of metabolic syndrome: a 5-year follow-up study

<p>Abstract</p> <p>Background</p> <p>There is controversy about the specific pathophysiology of metabolic syndrome (MS) but several authors have argued that hyperinsulinemia is a key feature of the cluster. We aimed to assess whether the baseline insulin levels could predict the development of MS in a well characterised cohort of otherwise healthy adults who were followed over a five year period.</p> <p>Methods</p> <p>We identified 2, 350 Koreans subjects who did not have MS in 2003 and who were followed up in 2008. The subjects were divided into 4 groups according to the baseline quartiles of fasting insulin, and the predictors of the incidence of MS were analyzed using multivariate regression analysis.</p> <p>Results</p> <p>Over the follow up period, 8.5% of the cohort developed MS. However, 16.4% of the subjects in the highest quartile of the insulin levels developed MS. In a model that included gender, age, the smoking status, the exercise level, alcohol consumption and the systolic blood pressure, the subjects in the highest quartile of the insulin levels had more than a 5 times greater risk of developing MS compared that of the subjects in the lowest quartile. This predictive importance remained significant even after correcting for all the individual features of MS.</p> <p>Conclusions</p> <p>These data suggest that high baseline fasting insulin levels are independent determinants for the future development of MS.</p

Old lessons learned anew: family-based methods for detecting genes responsible for quantitative and qualitative traits in the Genetic Analysis Workshop 17 mini-exome sequence data

Family-based study designs are again becoming popular as new next-generation sequencing technologies make whole-exome and whole-genome sequencing projects economically and temporally feasible. Here we evaluate the statistical properties of linkage analyses and family-based tests of association for the Genetic Analysis Workshop 17 mini-exome sequence data. Based on our results, the linkage methods using relative pairs or nuclear families had low power, with the best results coming from variance components linkage analysis in nuclear families and Elston-Stewart model-based linkage analysis in extended pedigrees. For family-based tests of association, both ASSOC and ROMP performed well for genes with large effects, but ROMP had the advantage of not requiring parental genotypes in the analysis. For the linkage analyses we conclude that genome-wide significance levels appear to control type I error well but that “suggestive” significance levels do not. Methods that make use of the extended pedigrees are well powered to detect major loci segregating in the families even when there is substantial genetic heterogeneity and the trait is mainly polygenic. However, large numbers of such pedigrees will be necessary to detect all major loci. The family-based tests of association found the same major loci as the linkage analyses and detected low-frequency loci with moderate effect sizes, but control of type I error was not as stringent