Population-Based Resequencing of LIPG and ZNF202 Genes in Subjects with Extreme HDL Levels

Endothelial lipase (LIPG) and zinc finger protein 202 (ZNF202) are two pivotal genes in high density lipoprotein (HDL metabolism). We sought to determine their genetic contribution to variation in HDL-cholesterol levels by comprehensive resequencing of both genes in 235 individuals with high or low HDL-C levels. The selected subjects were 141 Whites (High HDL Group: n = 68, x¯=76.90mg/dl; Low HDL Group: n = 73, x¯=32.55mg/dl) and 94 Hispanics (High HDL Group: n = 46, x¯=74.85mg/dl; Low HDL Group: n = 48, x¯=29.95mg/dl). We identified a total of 185 and 122 sequence variants in LIPG and ZNF202, respectively. We found only two missense variants in LIPG (T111I and N396S) and two in ZNF202 (A154V and K259E). In both genes, there were several variants unique to either the low or high HDL group. For LIPG, the proportion of unique variants differed between the high and low HDL groups in both Whites (p = 0.022) and Hispanics (p = 0.017), but for ZNF202 this difference was observed only in Hispanics (p = 0.021). We also identified a common haplotype in ZNF202 among Whites that was significantly associated with the high HDL group (p = 0.013). These findings provide insights into the genetics of LIPG and ZNF202, and suggest that sequence variants occurring with high frequency in non-exonic regions may play a prominent role in modulating HDL-C levels in the general population

A Time Series Model for Assessing the Trend and Forecasting the Road Traffic Accident Mortality

Background: Road traffic accident (RTA) is one of the main causes of trauma and known as a growing public health concern worldwide, especially in developing countries. Assessing the trend of fatalities in the past years and forecasting it enables us to make the appropriate planning for prevention and control. Objectives: This study aimed to assess the trend of RTAs and forecast it in the next years by using time series modeling. Materials and Methods: In this historical analytical study, the RTA mortalities in Zanjan Province, Iran, were evaluated during 2007 - 2013. The time series analyses including Box-Jenkins models were used to assess the trend of accident fatalities in previous years and forecast it for the next 4 years. Results: The mean age of the victims was 37.22 years (SD = 20.01). From a total of 2571 deaths, 77.5% (n = 1992) were males and 22.5% (n = 579) were females. The study models showed a descending trend of fatalities in the study years. The SARIMA (1, 1, 3) (0, 1, 0) 12 model was recognized as a best fit model in forecasting the trend of fatalities. Forecasting model also showed a descending trend of traffic accident mortalities in the next 4 years. Conclusions: There was a decreasing trend in the study and the future years. It seems that implementation of some interventions in the recent decade has had a positive effect on the decline of RTA fatalities. Nevertheless, there is still a need to pay more attention in order to prevent the occurrence and the mortalities related to traffic accidents

The Relationship Between Serum Levels of Interleukins 6, 8, 10 and Clinical Outcome in Patients With Severe Traumatic Brain Injury

Background: Clinical outcome in patients with severe traumatic brain injury (TBI) depends on both primary and secondary brain injuries. Neuroinflammation is an important secondary mechanism, which occurs by releasing interleukins (ILs). Increased levels of ILs may affect clinical outcome following TBI. Objectives: This study aimed to determine the relationship between the serum levels of interleukins 6, 8 and 10 and clinical outcome in patients with severe TBI 6 months after injury. Patients and Methods: In a descriptive-analytical study, 44 patients with GCS ≤ 8 (Glasgow coma scale) and age ≥ 14 years were included. Their blood samples were collected at first 6 hours after injury. Clinical outcome was determined based on GOS (Glasgow Outcome Scale) at 6 months after head injury. Serum levels of interleukins 6, 8 and 10 were measured using the ELISA method. Spearman's rho, independent T-Test, and Mann-Whitney Test were used for data analysis. Results: Comparing the serum levels of interleukins in two groups with favorable and unfavorable clinical outcomes showed that the mean serum levels of interleukins 6 and 8 in group with favorable outcome was 85.2 ± 51.6 and 52.2 ± 31.9, respectively lower than those of group with unfavorable outcome with 162.3 ± 141.1 and 173.6 ± 257.3 (P < 0.03) and (P < 0.01). Conclusions: Increased serum levels of interleukins 6 and 8 as a predictive marker might be associated with unfavorable clinical outcome in patients with severe TBI

Supplemental irrigation management of rainfed grapevines under drought conditions using the CropSyst model

Aim of study: To determine how much water should be used and when it should be applied in rain-fed grapevine using a cropping system simulation model (CropSyst), and also the economic analysis of supplemental irrigation for rainfed grapevine.Area of study: This study was conducted at the School of Agriculture, Shiraz University, Shiraz, Iran, in 2012, 2013 and 2014.Material and methods: The CropSyst model was calibrated to predict the rainfed yields of ‘Askari’ and ‘Yaghooti’ grapevines in different climates using four amounts of SI: 250 L (I1), 500 L (I2), 1000 L (I3) and 0 (I4), five SI times: single in March (T1), single in April (T2), single in March + single in April (T3), single in May (T4) and single in June (T5).Main results: Treatment T3 increased the average simulated yield of ‘Askari’ by 15% to 40% at regions with P/ETo&gt;0.6, 17% to 61% at 0.2&lt;P/ETO&lt;0.6, and 26% to 61% at P/ETO&lt;0.2, while in ‘Yaghooti’ it increased about 2% to 41% at regions with P/ETo&gt;0.6, 4% to 36% at 0.2&lt;P/ETO&lt;0.6 and 2% to 26% at P/ETO&lt;0.2. By increasing the water price by 30% and 50%, net benefits for the ‘Askari’ decreased by about 31% and 54%, while 6% and 18%, for ‘Yaghooti’ respectively.Research highlights: The CropSyst model can successfully predict soil water content and grapevine yields. Application of SI in May increased significantly the grapevine yield as compared to other SI times

Magnesium-based nanocomposites: A review from mechanical, creep and fatigue properties

The addition of nanoscale additions to magnesium (Mg) based alloys can boost mechanical characteristics without noticeably decreasing ductility. Since Mg is the lightest structural material, the Mg-based nanocomposites (NCs) with improved mechanical properties are appealing materials for lightweight structural applications. In contrast to conventional Mg-based composites, the incorporation of nano-sized reinforcing particles noticeably boosts the strength of Mg-based nanocomposites without significantly reducing the formability. The present article reviews Mg-based metal matrix nanocomposites (MMNCs) with metallic and ceramic additions, fabricated via both solid-based (sintering and powder metallurgy) and liquid-based (disintegrated melt deposition) technologies. It also reviews strengthening models and mechanisms that have been proposed to explain the improved mechanical characteristics of Mg-based alloys and nanocomposites. Further, synergistic strengthening mechanisms in Mg matrix nanocomposites and the dominant equations for quantitatively predicting mechanical properties are provided. Furthermore, this study offers an overview of the creep and fatigue behavior of Mg-based alloys and nanocomposites using both traditional (uniaxial) and depth-sensing indentation techniques. The potential applications of magnesium-based alloys and nanocomposites are also surveyed

Wavelet analysis method for solving linear and nonlinear singular boundary value problems

In this paper, a robust and accurate algorithm for solving both linear and nonlinear singular boundary value problems is proposed. We introduce the Chebyshev wavelets operational matrix of derivative and product operation matrix. Chebyshev wavelets expansions together with operational matrix of derivative are employed to solve ordinary differential equations in which, at least, one of the coefficient functions or solution function is not analytic. Several examples are included to illustrate the efficiency and accuracy of the proposed method

Mycobiota and aflatoxin B1 contamination of rainbow trout (Oncorhinchus mykiss) feed with emphasis to Aspergillus section Flavi

In the present study, mycobiota and natural occurrence of aflatoxin B1 (AFB1) in pellet feed and feed ingredients used in a feed manufacturing plant for rainbow trout nutrition was investigated. The samples were cultured on the standard isolation media for 2 weeks at 28 ºC. Identification of fungal isolates was implemented based on the macro- and microscopic morphological criteria. AFB1 was detected using high performance liquid chromatography (HPLC). Based on the results obtained, a total of 109 fungal isolates were identified of which Aspergillus was the prominent genus (57.0%), followed by Penicillium (12.84%), Absidia (11.01%) and Pseudallscheria (10.10%). The most frequent Aspergillus species was A. flavus (60.66%) isolated from all feed ingredients as well as pellet feed. Among 37 A. flavus isolates, 19 (51.35%) were able to produce AFB1 on YES broth in the range of 10.2 to 612.8 µg/g fungal dry weight. HPLC analysis of trout feed showed that pellet feed and all feed ingredients tested except gluten were contaminated with different levels of AFB1 in the range of 1.83 to 67.35 µg/kg. Unacceptable levels of AFB1 were reported for feed including soybean, fish meal and wheat. These results indicate the importance of AF contamination of trout feed in amounts higher than the acceptable level as a risk factor for fish farming production