Epitaxial Graphene Growth on SiC Wafers

An in vacuo thermal desorption process has been accomplished to form epitaxial graphene (EG) on 4H- and 6H-SiC substrates using a commercial chemical vapor deposition reactor. Correlation of growth conditions and the morphology and electrical properties of EG are described. Raman spectra of EG on Si-face samples were dominated by monolayer thickness. This approach was used to grow EG on 50 mm SiC wafers that were subsequently fabricated into field effect transistors with fmax of 14 GHz.Comment: 215th Meeting of the Electrochemical Society, 8 pages, 8 figure

Transcriptome Profiling of Citrus Fruit Response to Huanglongbing Disease

Huanglongbing (HLB) or “citrus greening” is the most destructive citrus disease worldwide. In this work, we studied host responses of citrus to infection with Candidatus Liberibacter asiaticus (CaLas) using next-generation sequencing technologies. A deep mRNA profile was obtained from peel of healthy and HLB-affected fruit. It was followed by pathway and protein-protein network analysis and quantitative real time PCR analysis of highly regulated genes. We identified differentially regulated pathways and constructed networks that provide a deep insight into the metabolism of affected fruit. Data mining revealed that HLB enhanced transcription of genes involved in the light reactions of photosynthesis and in ATP synthesis. Activation of protein degradation and misfolding processes were observed at the transcriptomic level. Transcripts for heat shock proteins were down-regulated at all disease stages, resulting in further protein misfolding. HLB strongly affected pathways involved in source-sink communication, including sucrose and starch metabolism and hormone synthesis and signaling. Transcription of several genes involved in the synthesis and signal transduction of cytokinins and gibberellins was repressed while that of genes involved in ethylene pathways was induced. CaLas infection triggered a response via both the salicylic acid and jasmonic acid pathways and increased the transcript abundance of several members of the WRKY family of transcription factors. Findings focused on the fruit provide valuable insight to understanding the mechanisms of the HLB-induced fruit disorder and eventually developing methods based on small molecule applications to mitigate its devastating effects on fruit production

Community profiling and gene expression of fungal assimilatory nitrate reductases in agricultural soil

Although fungi contribute significantly to the microbial biomass in terrestrial ecosystems, little is known about their contribution to biogeochemical nitrogen cycles. Agricultural soils usually contain comparably high amounts of inorganic nitrogen, mainly in the form of nitrate. Many studies focused on bacterial and archaeal turnover of nitrate by nitrification, denitrification and assimilation, whereas the fungal role remained largely neglected. To enable research on the fungal contribution to the biogeochemical nitrogen cycle tools for monitoring the presence and expression of fungal assimilatory nitrate reductase genes were developed. To the ∼100 currently available fungal full-length gene sequences, another 109 partial sequences were added by amplification from individual culture isolates, representing all major orders occurring in agricultural soils. The extended database led to the discovery of new horizontal gene transfer events within the fungal kingdom. The newly developed PCR primers were used to study gene pools and gene expression of fungal nitrate reductases in agricultural soils. The availability of the extended database allowed affiliation of many sequences to known species, genera or families. Energy supply by a carbon source seems to be the major regulator of nitrate reductase gene expression for fungi in agricultural soils, which is in good agreement with the high energy demand of complete reduction of nitrate to ammonium

Adjusting data to body size : a comparison of methods as applied to quantitative trait loci analysis of musculoskeletal phenotypes

The aim of this study was to compare three methods of adjusting skeletal data for body size and examine their use in QTL analyses. It was found that dividing skeletal phenotypes by body mass index induced erroneous QTL results. The preferred method of body size adjustment was multiple regression. Introduction: Many skeletal studies have reported strong correlations between phenotypes for muscle, bone, and body size, and these correlations add to the difficulty in identifying genetic influence on skeletal traits that are not mediated through overall body size. Quantitative trait loci (QTL) identified for skeletal phenotypes often map to the same chromosome regions as QTLs for body size. The actions of a QTL identified as influencing BMD could therefore be mediated through the generalized actions of growth on body size or muscle mass. Materials and Methods: Three methods of adjusting skeletal phenotypes to body size were performed on morphologic, structural, and compositional measurements of the femur and tibia in 200-day-old C57BL/6J x DBA/2 (BXD) second generation (F2) mice (n = 400). A common method of removing the size effect has been through the use of ratios. This technique and two alternative techniques using simple and multiple regression were performed on muscle and skeletal data before QTL analyses, and the differences in QTL results were examined. Results and Conclusions: The use of ratios to remove the size effect was shown to increase the size effect by inducing spurious correlations, thereby leading to inaccurate QTL results. Adjustments for body size using multiple regression eliminated these problems. Multiple regression should be used to remove the variance of co-factors related to skeletal phenotypes to allow for the study of genetic influence independent of correlated phenotypes. However, to better understand the genetic influence, adjusted and unadjusted skeletal QTL results should be compared. Additional insight can be gained by observing the difference in LOD score between the adjusted and nonadjusted phenotypes. Identifying QTLs that exert their effects on skeletal phenotypes through body size-related pathways as well as those having a more direct and independent influence on bone are equally important in deciphering the complex physiologic pathways responsible for the maintenance of bone health

Adjusting data to body size: A comparison of methods as applied to quantitative trait loci analysis of musculoskeletal phenotypes

The aim of this study was to compare three methods of adjusting skeletal data for body size and examine their use in QTL analyses. It was found that dividing skeletal phenotypes by body mass index induced erroneous QTL results. The preferred method of body size adjustment was multiple regression. Introduction: Many skeletal studies have reported strong correlations between phenotypes for muscle, bone, and body size, and these correlations add to the difficulty in identifying genetic influence on skeletal traits that are not mediated through overall body size. Quantitative trait loci (QTL) identified for skeletal phenotypes often map to the same chromosome regions as QTLs for body size. The actions of a QTL identified as influencing BMD could therefore be mediated through the generalized actions of growth on body size or muscle mass. Materials and Methods: Three methods of adjusting skeletal phenotypes to body size were performed on morphologic, structural, and compositional measurements of the femur and tibia in 200-day-old C57BL/6J x DBA/2 (BXD) second generation (F2) mice (n = 400). A common method of removing the size effect has been through the use of ratios. This technique and two alternative techniques using simple and multiple regression were performed on muscle and skeletal data before QTL analyses, and the differences in QTL results were examined. Results and Conclusions: The use of ratios to remove the size effect was shown to increase the size effect by inducing spurious correlations, thereby leading to inaccurate QTL results. Adjustments for body size using multiple regression eliminated these problems. Multiple regression should be used to remove the variance of co-factors related to skeletal phenotypes to allow for the study of genetic influence independent of correlated phenotypes. However, to better understand the genetic influence, adjusted and unadjusted skeletal QTL results should be compared. Additional insight can be gained by observing the difference in LOD score between the adjusted and nonadjusted phenotypes. Identifying QTLs that exert their effects on skeletal phenotypes through body size-related pathways as well as those having a more direct and independent influence on bone are equally important in deciphering the complex physiologic pathways responsible for the maintenance of bone health

Adjusting Data to Body Size: A Comparison of Methods as Applied to Quantitative Trait Loci Analysis of Musculoskeletal Phenotypes

The aim of this study was to compare three methods of adjusting skeletal data for body size and examine their use in QTL analyses. It was found that dividing skeletal phenotypes by body mass index induced erroneous QTL results. The preferred method of body size adjustment was multiple regression. INTRODUCTION: Many skeletal studies have reported strong correlations between phenotypes for muscle, bone, and body size, and these correlations add to the difficulty in identifying genetic influence on skeletal traits that are not mediated through overall body size. Quantitative trait loci (QTL) identified for skeletal phenotypes often map to the same chromosome regions as QTLs for body size. The actions of a QTL identified as influencing BMD could therefore be mediated through the generalized actions of growth on body size or muscle mass. MATERIALS AND METHODS: Three methods of adjusting skeletal phenotypes to body size were performed on morphologic, structural, and compositional measurements of the femur and tibia in 200-day-old C57BL/6J × DBA/2 (BXD) second generation (F(2)) mice (n = 400). A common method of removing the size effect has been through the use of ratios. This technique and two alternative techniques using simple and multiple regression were performed on muscle and skeletal data before QTL analyses, and the differences in QTL results were examined. RESULTS AND CONCLUSIONS: The use of ratios to remove the size effect was shown to increase the size effect by inducing spurious correlations, thereby leading to inaccurate QTL results. Adjustments for body size using multiple regression eliminated these problems. Multiple regression should be used to remove the variance of co-factors related to skeletal phenotypes to allow for the study of genetic influence independent of correlated phenotypes. However, to better understand the genetic influence, adjusted and unadjusted skeletal QTL results should be compared. Additional insight can be gained by observing the difference in LOD score between the adjusted and nonadjusted phenotypes. Identifying QTLs that exert their effects on skeletal phenotypes through body size-related pathways as well as those having a more direct and independent influence on bone are equally important in deciphering the complex physiologic pathways responsible for the maintenance of bone health

Analysis of Skeletal Muscle Gene Expression Patterns and the Impact of Functional Capacity in Patients With Systolic Heart Failure

BACKGROUND: Declining physical function is common among systolic heart failure (HF) patients and heralds poor clinical outcomes. We hypothesized that coordinated shifts in expression of ubiquitin-mediated atrophy-promoting genes are associated with muscle atrophy and contribute to decreased physical function. METHODS: Systolic HF patients (left ventricular ejection fraction [LVEF] ≤40%) underwent skeletal muscle biopsies (nondominant vastus lateralis) and comprehensive physical assessments. Skeletal muscle gene expression was assessed with the use of real-time polymerase chain reaction. Aerobic function was assessed with the use of cardiopulmonary exercise and 6-minute walk tests. Strength capacity was assessed with the use of pneumatic leg press (maximum strength and power). Serologic inflammatory markers also were assessed. RESULTS: 54 male patients (66.6 ± 10.0 years) were studied: 24 systolic HF patients (mean LVEF 28.9 ± 7.8%) and 30 age-matched control subjects. Aerobic and strength parameters were diminished in HF versus control. FoxO1 and FoxO3 were increased in HF versus control (7.9 ± 6.2 vs 5.0 ± 3.5, 6.5 ± 4.3 vs 4.3 ± 2.8 relative units, respectively; P ≤.05 in both). However, atrogin-1 and MuRF-1 were similar in both groups. PGC-1α was also increased in HF (7.9 ± 5.4 vs. 5.3 ± 3.6 relative units; P < .05). Muscle levels of insulin-like growth factor (IGF) 1 as well as serum levels of tumor necrosis factor α, C-reactive protein, inter-leukin (IL) 1β, and IL-6 were similar in HF and control. CONCLUSION: Expression of the atrophy-promoting genes FoxO1 and FoxO3 were increased in skeletal muscle in systolic HF compared with control, but other atrophy gene expression patterns (atrogin-1 and MuRF-1), as well as growth promoting patterns (IGF-1), were similar. PGC-1α, a gene critical in enhancing mitochondrial function and moderating FoxO activity, may play an important counterregulatory role to offset ubiquitin pathwayemediated functional decrements