Nurses' Competence and Job Related Factors among Nurses in University Hospitals: A Cross Sectional Descriptive Design

Introduction: Nurses' Competence is a critical factor for providing safe and quality care and self- assessment is a key issue in maintenance of competence. This study was conducted to identify the level of competence and its associations with some job related factors. Methods: A cross sectional and descriptive design was conducted at seven university hospitals in Rasht during September 2015. This study included 230 nurses working in university hospitals who were selected using stratified sampling method. The majority of nurses was female and had a bachelor's degree. Nurses' competence was measured using self reported competency inventory for registered nurses (Persian version). Data was analyzed with Spearman correlation, Mann-Whitney-U SPSS /21 software. Results: The average score of competence was 173.59±26.72 and was considered in high level. The highest and the lowest competence were in dimensions of 'ethical-legal performance' (M=3.23±.52) and 'Critical thinking/research aptitude' (M=3.11±.51) respectively. There were significant associations between nurses' competence and some job related factors consisting work experience (p = 0.001), monthly salary (p = 0.001), working hours per month (p = 0.004), Nurses' shift work (p = 0.021), and employment type (p = 0.003). Conclusions: Nurses assessed their competence at a desirable level, which may be due to self-assessment tool. Some job related factors associated with nurses' competence. Exploring the competence level and its relationship with these factors could be helpful in managerial interventions for professional competency

HyperDbg: Reinventing Hardware-Assisted Debugging (Extended Version)

Software analysis, debugging, and reverse engineering have a crucial impact in today's software industry. Efficient and stealthy debuggers are especially relevant for malware analysis. However, existing debugging platforms fail to address a transparent, effective, and high-performance low-level debugger due to their detectable fingerprints, complexity, and implementation restrictions. In this paper, we present HyperDbg, a new hypervisor-assisted debugger for high-performance and stealthy debugging of user and kernel applications. To accomplish this, HyperDbg relies on state-of-the-art hardware features available in today's CPUs, such as VT-x and extended page tables. In contrast to other widely used existing debuggers, we design HyperDbg using a custom hypervisor, making it independent of OS functionality or API. We propose hardware-based instruction-level emulation and OS-level API hooking via extended page tables to increase the stealthiness. Our results of the dynamic analysis of 10,853 malware samples show that HyperDbg's stealthiness allows debugging on average 22% and 26% more samples than WinDbg and x64dbg, respectively. Moreover, in contrast to existing debuggers, HyperDbg is not detected by any of the 13 tested packers and protectors. We improve the performance over other debuggers by deploying a VMX-compatible script engine, eliminating unnecessary context switches. Our experiment on three concrete debugging scenarios shows that compared to WinDbg as the only kernel debugger, HyperDbg performs step-in, conditional breaks, and syscall recording, 2.98x, 1319x, and 2018x faster, respectively. We finally show real-world applications, such as a 0-day analysis, structure reconstruction for reverse engineering, software performance analysis, and code-coverage analysis

Pre- and post-treatment of α-Tocopherol on cognitive, synaptic plasticity, and mitochondrial disorders of the hippocampus in icv-streptozotocin-induced sporadic Alzheimer’s-like disease in male Wistar rat

ObjectiveMost dementia cases in the elderly are caused by Alzheimer’s disease (AD), a complex, progressive neurological disease. Intracerebroventricular (ICV) administration of streptozotocin (STZ) in rat’s results in aberrant brain insulin signaling, oxidative stress, and mitochondrial dysfunction that impair cognition change neural plasticity, and eventually lead to neuronal death. The current study aims to define the neuroprotective action of alpha-tocopherol in enhancing mitochondrial function and the function of synapses in memory-impaired rats brought on by icv-STZ.MethodsMale Wistar rats were pre-treated with (α-Tocopherol 150 mg/kg) orally once daily for 7 days before and 14 days after being bilaterally injected with icv-STZ (3 mg/kg), while sham group rats received the same volume of STZ solvent. After 2 weeks of icv-STZ infusion, rats were tested for cognitive performance using a behaviors test and then were prepared electrophysiology recordings or sacrificed for biochemical and histopathological assays.ResultsThe cognitive impairment was significantly minimized in the behavioral paradigms for those who had taken α-Tocopherol. In the hippocampus of icv-STZ rat brains, α-Tocopherol ocopherol effectively prevented the loss of glutathione levels and superoxide dismutase enzyme activity, lowered mitochondrial ROS and mitochondrial membrane potential, and also brought about a decrease in Aβ aggregation and neuronal death.ConclusionOur findings demonstrated that by lowering neurobehavioral impairments caused by icv-STZ, oxidative stress, and mitochondrial dysfunction, α-Tocopherol enhanced intracellular calcium homeostasis and corrected neurodegenerative defects in the brain. These findings examine the available approach for delaying AD connected to mitochondrial malfunction and plasticity issues

HyperDbg: Reinventing Hardware-Assisted Debugging

Software analysis, debugging, and reverse engineering have a crucial impact in today's software industry. Efficient and stealthy debuggers are especially relevant for malware analysis. However, existing debugging platforms fail to address a transparent, effective, and high-performance low-level debugger due to their detectable fingerprints, complexity, and implementation restrictions. In this paper, we present StealthDbg, a new hypervisor-assisted debugger for high-performance and stealthy debugging of user and kernel applications. To accomplish this, StealthDbg relies on state-of-the-art hardware features available in today's CPUs, such as VT-x and extended page tables. In contrast to other widely used existing debuggers, we design StealthDbg using a custom hypervisor, making it independent of OS functionality or API. We propose hardware-based instruction-level emulation and OS-level API hooking via extended page tables to increase the stealthiness. Our results of the dynamic analysis of 10,853 malware samples show that StealthDbg's stealthiness allows debugging on average 22% and 26% more samples than WinDbg and x64dbg, respectively. Moreover, in contrast to existing debuggers, StealthDbg is not detected by any of the 13 tested packers and protectors. We improve the performance over other debuggers by deploying a VMX-compatible script engine, eliminating unnecessary context switches. Our experiment on three concrete debugging scenarios shows that compared to WinDbg as the only kernel debugger, StealthDbg performs step-in, conditional breaks, and syscall recording, 2.98x, 1319x, and 2018x faster, respectively. We finally show real-world applications, such as a 0-day analysis, structure reconstruction for reverse engineering, software performance analysis, and code-coverage analysis

Blood Eosinophil Count and Metabolic, Cardiac and Pulmonary Outcomes: A Mendelian Randomization Study.

Blood eosinophil count is associated with a variety of common complex outcomes in epidemiological observation. The aim of this study was to explore the causal association between determined blood eosinophil count and 20 common complex outcomes (10 metabolic, 6 cardiac, and 4 pulmonary). Through Mendelian randomization, we investigated genetic evidence for the genetically determined eosinophil in association with each outcomes using individual-level LifeLines cohort data (n = 13,301), where a weighted eosinophil genetic risk score comprising five eosinophil associated variants was created. We further examined the associations of the genetically determined eosinophil with those outcomes using summary statistics obtained from genome-wide association study consortia (6 consortia and 14 outcomes). Blood eosinophil count, by a 1-SD genetically increased, was not statistically associated with common complex outcomes in the LifeLines. Using the summary statistics, we showed that a higher genetically determined eosinophil count had a significant association with lower odds of obesity (odds ratio (OR) 0.81, 95% confidence interval (CI) [0.74, 0.89]) but not with the other traits and diseases. To conclude, an elevated eosinophil count is unlikely to be causally associated to higher risk of metabolic, cardiac, and pulmonary outcomes. Further studies with a stronger genetic risk score for eosinophil count may support these results

Genomic analyses identify hundreds of variants associated with age at menarche and support a role for puberty timing in cancer risk

The timing of puberty is a highly polygenic childhood trait that is epidemiologically associated with various adult diseases. Using 1000 Genomes Project-imputed genotype data in up to similar to 370,000 women, we identify 389 independent signals (P <5 x 10(-8)) for age at menarche, a milestone in female pubertal development. In Icelandic data, these signals explain similar to 7.4% of the population variance in age at menarche, corresponding to similar to 25% of the estimated heritability. We implicate similar to 250 genes via coding variation or associated expression, demonstrating significant enrichment in neural tissues. Rare variants near the imprinted genes MKRN3 and DLK1 were identified, exhibiting large effects when paternally inherited. Mendelian randomization analyses suggest causal inverse associations, independent of body mass index (BMI), between puberty timing and risks for breast and endometrial cancers in women and prostate cancer in men. In aggregate, our findings highlight the complexity of the genetic regulation of puberty timing and support causal links with cancer susceptibility

Multi-ancestry study of blood lipid levels identifies four loci interacting with physical activity.

Many genetic loci affect circulating lipid levels, but it remains unknown whether lifestyle factors, such as physical activity, modify these genetic effects. To identify lipid loci interacting with physical activity, we performed genome-wide analyses of circulating HDL cholesterol, LDL cholesterol, and triglyceride levels in up to 120,979 individuals of European, African, Asian, Hispanic, and Brazilian ancestry, with follow-up of suggestive associations in an additional 131,012 individuals. We find four loci, in/near CLASP1, LHX1, SNTA1, and CNTNAP2, that are associated with circulating lipid levels through interaction with physical activity; higher levels of physical activity enhance the HDL cholesterol-increasing effects of the CLASP1, LHX1, and SNTA1 loci and attenuate the LDL cholesterol-increasing effect of the CNTNAP2 locus. The CLASP1, LHX1, and SNTA1 regions harbor genes linked to muscle function and lipid metabolism. Our results elucidate the role of physical activity interactions in the genetic contribution to blood lipid levels

Multi-ancestry study of blood lipid levels identifies four loci interacting with physical activity

The present work was largely supported by a grant from the US National Heart, Lung, and Blood Institute (NHLBI) of the National Institutes of Health (R01HL118305). The full list of acknowledgments appears in the Supplementary Notes 3 and 4.Peer reviewedPublisher PD