Prevalence of elevated alanine transaminase in Australia and its relationship to metabolic risk factors: A cross-sectional study of 9,447 people

BACKGROUND AND AIM: Elevated alanine transaminase (ALT) is a strong predictor of metabolic syndrome, but there are few data from the Australian population. We aimed to determine the prevalence of elevated ALT and association with metabolic risk factors. METHODS: In this cross-sectional study including adult participants (N = 9,447) from a nationwide, population-based survey, we assessed the prevalence of elevated ALT [defined as ≥ 40 IU/L (men) and ≥ 30 IU/L (women) as baseline, and ALT as ≥ 30 IU/L (men) and ≥ 19 IU/L (women) as lower threshold], distribution of metabolic risk factors, and independent predictors of elevated ALT in logistic regression models. Analyses were weighted to the population with population weights. RESULTS: Elevated ALT levels were found in 11.2% of the Australian population. People with elevated ALT were younger (43 vs 46 yrs) with more truncal adiposity (100 vs 91 cm), higher pro-atherogenic lipids and glucose and exercised less (120 vs 160 min per week, P < 0.05 for all analyses). Regression analyses indicated that younger age, male sex, diabetes, triglycerides, apolipoprotein B, and waist circumference were independent predictors of elevated ALT. The population attributable fraction of elevated ALT due to truncal obesity was estimated at 47%. CONCLUSION: These data demonstrate a high prevalence of elevated ALT in the general population that is closely associated with metabolic risk factors. Individuals with elevated ALT should be evaluated for co-existent metabolic disorders

Bioresponsive matrices in drug delivery

For years, the field of drug delivery has focused on (1) controlling the release of a therapeutic and (2) targeting the therapeutic to a specific cell type. These research endeavors have concentrated mainly on the development of new degradable polymers and molecule-labeled drug delivery vehicles. Recent interest in biomaterials that respond to their environment have opened new methods to trigger the release of drugs and localize the therapeutic within a particular site. These novel biomaterials, usually termed "smart" or "intelligent", are able to deliver a therapeutic agent based on either environmental cues or a remote stimulus. Stimuli-responsive materials could potentially elicit a therapeutically effective dose without adverse side effects. Polymers responding to different stimuli, such as pH, light, temperature, ultrasound, magnetism, or biomolecules have been investigated as potential drug delivery vehicles. This review describes the most recent advances in "smart" drug delivery systems that respond to one or multiple stimuli

Identifying Treatment Effect Modifiers in the STarT Back Trial: A Secondary Analysis

Identification of patient characteristics influencing treatment outcomes is a top low back pain (LBP) research priority. Results from the STarT Back Trial support the effectiveness of prognostic stratified care for LBP compared to current best care, however patient characteristics associated with treatment response have not yet been explored. The purpose of this secondary analysis was to identify treatment-effect modifiers within the STarT Back Trial at 4 months follow-up (n=688). Treatment response was dichotomized using back-specific physical disability measured by the Roland-Morris Disability Questionnaire (≥7). Candidate modifiers were identified using previous literature and evaluated using logistic regression with statistical interaction terms to provide preliminary evidence of treatment-effect modification. Socioeconomic status (SES) was identified as an effect modifier for disability outcomes (OR = 1.71, P=.028). High SES patients receiving prognostic stratified care were 2.5 times less likely to have a poor outcome compared to low SES patients receiving best current care (OR = 0.40, P=.006). Education level (OR = 1.33, P=.109) and number of pain medications (OR = 0.64, P=.140) met our criteria for effect modification with weaker evidence (0.20>P≥0.05). These findings provide preliminary evidence for SES, education, and number of pain medications as treatment-effect modifiers of prognostic stratified care delivered in the STarT Back Trial

Elevated Liver Enzymes and Mortality in Older Individuals: A Prospective Cohort Study

Aim of the study: The aim of the study was to determine the excess risk of all-cause and cardiovascular mortality in older people with elevated liver enzymes [alanine transaminase (ALT) and gamma glutamyltransferase (GGT)]. Methods: We utilized data from a large, prospective, population based study of 2061 people aged 50 to 99 years with linkage to a National Death Registry. Participants were categorized as having elevated liver enzymes using standard thresholds (for males, GGT>51 and ALT>40 IU/L, and GGT>33 and ALT>31 IU/L for females). Adjusted Cox proportional hazards models assessed the association of elevated liver enzymes and mortality with long duration follow-up. Results: Over a median follow-up of 10 years (20,145 person years), 701 people died, including 203 (34%) from cardiovascular disease. Cox regression models adjusted for sex, age, smoking, and alcohol intake indicated that people with elevated liver enzymes had an increased risk of all-cause mortality that was modified by age (test for interaction P=0.01). Age-stratified analyses demonstrated no increased risk at younger ages [age 59 y and below; hazard ratio (HR): 0.46; 95% confidence interval, 0.06-3.49], but increased risk with age; age 60 to 69, HR: 1.05 (0.53-2.07), age 70 to 79 years, HR: 1.54 (0.81 to 2.93), and age 80 years and above, HR: 3.53 (1.55 to 8.04). Similarly, the risk of cardiovascular mortality with elevated liver enzymes was also modified by, and increased with age (test for interaction P=0.02); age 70 to 79, HR: 3.15 (1.37 to 7.23), age 80 years and above, HR: 6.86 (2.44 to 19.30). Conclusions: In community-dwelling elderly persons, an elevation in both ALT and GGT are associated with an excess risk of all-cause and cardiovascular mortality which increases with age

Advanced Multilevel Node Separator Algorithms

A node separator of a graph is a subset S of the nodes such that removing S and its incident edges divides the graph into two disconnected components of about equal size. In this work, we introduce novel algorithms to find small node separators in large graphs. With focus on solution quality, we introduce novel flow-based local search algorithms which are integrated in a multilevel framework. In addition, we transfer techniques successfully used in the graph partitioning field. This includes the usage of edge ratings tailored to our problem to guide the graph coarsening algorithm as well as highly localized local search and iterated multilevel cycles to improve solution quality even further. Experiments indicate that flow-based local search algorithms on its own in a multilevel framework are already highly competitive in terms of separator quality. Adding additional local search algorithms further improves solution quality. Our strongest configuration almost always outperforms competing systems while on average computing 10% and 62% smaller separators than Metis and Scotch, respectively

Transcription profiling reveals potential mechanisms of dysbiosis in the oral microbiome of rhesus macaques with chronic untreated SIV infection.

A majority of individuals infected with human immunodeficiency virus (HIV) have inadequate access to antiretroviral therapy and ultimately develop debilitating oral infections that often correlate with disease progression. Due to the impracticalities of conducting host-microbe systems-based studies in HIV infected patients, we have evaluated the potential of simian immunodeficiency virus (SIV) infected rhesus macaques to serve as a non-human primate model for oral manifestations of HIV disease. We present the first description of the rhesus macaque oral microbiota and show that a mixture of human commensal bacteria and "macaque versions" of human commensals colonize the tongue dorsum and dental plaque. Our findings indicate that SIV infection results in chronic activation of antiviral and inflammatory responses in the tongue mucosa that may collectively lead to repression of epithelial development and impact the microbiome. In addition, we show that dysbiosis of the lingual microbiome in SIV infection is characterized by outgrowth of Gemella morbillorum that may result from impaired macrophage function. Finally, we provide evidence that the increased capacity of opportunistic pathogens (e.g. E. coli) to colonize the microbiome is associated with reduced production of antimicrobial peptides

Separation between coherent and turbulent fluctuations. What can we learn from the Empirical Mode Decomposition?

The performances of a new data processing technique, namely the Empirical Mode Decomposition, are evaluated on a fully developed turbulent velocity signal perturbed by a numerical forcing which mimics a long-period flapping. First, we introduce a "resemblance" criterion to discriminate between the polluted and the unpolluted modes extracted from the perturbed velocity signal by means of the Empirical Mode Decomposition algorithm. A rejection procedure, playing, somehow, the role of a high-pass filter, is then designed in order to infer the original velocity signal from the perturbed one. The quality of this recovering procedure is extensively evaluated in the case of a "mono-component" perturbation (sine wave) by varying both the amplitude and the frequency of the perturbation. An excellent agreement between the recovered and the reference velocity signals is found, even though some discrepancies are observed when the perturbation frequency overlaps the frequency range corresponding to the energy-containing eddies as emphasized by both the energy spectrum and the structure functions. Finally, our recovering procedure is successfully performed on a time-dependent perturbation (linear chirp) covering a broad range of frequencies.Comment: 23 pages, 13 figures, submitted to Experiments in Fluid

Tuning ultrafast electron thermalization pathways in a van der Waals heterostructure

Ultrafast electron thermalization - the process leading to Auger recombination, carrier multiplication via impact ionization and hot carrier luminescence - occurs when optically excited electrons in a material undergo rapid electron-electron scattering to redistribute excess energy and reach electronic thermal equilibrium. Due to extremely short time and length scales, the measurement and manipulation of electron thermalization in nanoscale devices remains challenging even with the most advanced ultrafast laser techniques. Here, we overcome this challenge by leveraging the atomic thinness of two-dimensional van der Waals (vdW) materials in order to introduce a highly tunable electron transfer pathway that directly competes with electron thermalization. We realize this scheme in a graphene-boron nitride-graphene (G-BN-G) vdW heterostructure, through which optically excited carriers are transported from one graphene layer to the other. By applying an interlayer bias voltage or varying the excitation photon energy, interlayer carrier transport can be controlled to occur faster or slower than the intralayer scattering events, thus effectively tuning the electron thermalization pathways in graphene. Our findings, which demonstrate a novel means to probe and directly modulate electron energy transport in nanoscale materials, represent an important step toward designing and implementing novel optoelectronic and energy-harvesting devices with tailored microscopic properties.Comment: Accepted to Nature Physic

Bioresponsive matrices in drug delivery

For years, the field of drug delivery has focused on (1) controlling the release of a therapeutic and (2) targeting the therapeutic to a specific cell type. These research endeavors have concentrated mainly on the development of new degradable polymers and molecule-labeled drug delivery vehicles. Recent interest in biomaterials that respond to their environment have opened new methods to trigger the release of drugs and localize the therapeutic within a particular site. These novel biomaterials, usually termed "smart" or "intelligent", are able to deliver a therapeutic agent based on either environmental cues or a remote stimulus. Stimuli-responsive materials could potentially elicit a therapeutically effective dose without adverse side effects. Polymers responding to different stimuli, such as pH, light, temperature, ultrasound, magnetism, or biomolecules have been investigated as potential drug delivery vehicles. This review describes the most recent advances in "smart" drug delivery systems that respond to one or multiple stimuli.Engineering and Applied Science