Association between Body Mass Index,Asymmetric Dimethylarginine and Risk of Cardiovascular Events and Mortality in Norwegian Patients with Suspected Stable Angina Pectoris

Background

Asymmetric dimethylarginine (ADMA) is associated with increased risk of atherosclerotic cardiovascular disease and mortality through inhibition of nitrogen oxide (NO) synthesis. As positive correlations between serum concentrations of NO and body mass index (BMI) have been observed, we aimed to explore whether the potential associations between plasma ADMA levels and the risk of acute myocardial infarction (AMI) and mortality were modified by BMI.

Methods

Multivariable Cox proportional hazard models were used to estimate the hazard ratios (HR) for AMI, cardiovascular death and all-cause mortality according to baseline plasma ADMA levels in 4122 patients with suspected stable angina pectoris. Analyses were subsequently repeated in patients with BMI below (low BMI) or above (high BMI) median.

Results

A total of 2982 patients (72%) were men. Median (range) age, plasma ADMA level and BMI were 62 (21–88) years, 0.54 (0.10–1.25) μmol/L and 26.3 (18.5–54.3) kg/m², respectively. During a mean (standard deviation) follow-up time of 4.7 (1.4) years, 337 (8%) patients suffered from an AMI, 300 (7%) died, whereof 165 (55%) due to cardiovascular disease. Each 0.1 μmol/L increment in plasma ADMA level was associated with an increased risk of AMI (HR (95% CI) 1.21 (1.08, 1.35) and cardiovascular death 1.30 (1.13, 1.49) in participants with low BMI only. Interactions were significant for AMI (p = 0.04) and CV death (p = 0.03). BMI did not modify the association between plasma ADMA levels and all-cause mortality.

Conclusion

Plasma ADMA levels were associated with risk of AMI and cardiovascular death among patients with low BMI only.     

Characterization of thin gelatin hydrogel membranes with balloon properties for dynamic tissue engineering

Cell or tissue stretching and strain are present in any in vivo environment, but is difficult to reproduce in vitro. Here, we describe a simple method for casting a thin (about 500 μm) and soft (about 0.3 kPa) hydrogel of gelatin and a method for characterizing the mechanical properties of the hydrogel simply by changing pressure with a water column. The gelatin is crosslinked with mTransglutaminase and the area of the resulting hydrogel can be increased up 13-fold by increasing the radial water pressure. This is far beyond physiological stretches observed in vivo. Actuating the hydrogel with a radial force achieves both information about stiffness, stretchability, and contractability, which are relevant properties for tissue engineering purposes. Cells could be stretched and contracted using the gelatin membrane. Gelatin is a commonly used polymer for hydrogels in tissue engineering, and the discovered reversible stretching is particularly interesting for organ modeling applications.     

Metabolites in Blood for Prediction of Bacteremic Sepsis in the Emergency Room

A metabolomics approach for prediction of bacteremic sepsis in patients in the emergency room (ER) was investigated. In a prospective study, whole blood samples from 65 patients with bacteremic sepsis and 49 ER controls were compared. The blood samples were analyzed using gas chromatography coupled to time-of-flight mass spectrometry. Multivariate and logistic regression modeling using metabolites identified by chromatography or using conventional laboratory parameters and clinical scores of infection were employed. A predictive model of bacteremic sepsis with 107 metabolites was developed and validated. The number of metabolites was reduced stepwise until identifying a set of 6 predictive metabolites. A 6-metabolite predictive logistic regression model showed a sensitivity of 0.91(95% CI 0.69–0.99) and a specificity 0.84 (95% CI 0.58–0.94) with an AUC of 0.93 (95% CI 0.89–1.01). Myristic acid was the single most predictive metabolite, with a sensitivity of 1.00 (95% CI 0.85–1.00) and specificity of 0.95 (95% CI 0.74–0.99), and performed better than various combinations of conventional laboratory and clinical parameters. We found that a metabolomics approach for analysis of acute blood samples was useful for identification of patients with bacteremic sepsis. Metabolomics should be further evaluated as a new tool for infection diagnostics.     

RosettaDDGPrediction for high-throughput mutational scans: From stability to binding

Reliable prediction of free energy changes upon amino acid substitutions (ΔΔGs) is crucial to investigate their impact on protein stability and protein–protein interaction. Advances in experimental mutational scans allow high-throughput studies thanks to multiplex techniques. On the other hand, genomics initiatives provide a large amount of data on disease-related variants that can benefit from analyses with structure-based methods. Therefore, the computational field should keep the same pace and provide new tools for fast and accurate high-throughput ΔΔG calculations. In this context, the Rosetta modeling suite implements effective approaches to predict folding/unfolding ΔΔGs in a protein monomer upon amino acid substitutions and calculate the changes in binding free energy in protein complexes. However, their application can be challenging to users without extensive experience with Rosetta. Furthermore, Rosetta protocols for ΔΔG prediction are designed considering one variant at a time, making the setup of high-throughput screenings cumbersome. For these reasons, we devised RosettaDDGPrediction, a customizable Python wrapper designed to run free energy calculations on a set of amino acid substitutions using Rosetta protocols with little intervention from the user. Moreover, RosettaDDGPrediction assists with checking completed runs and aggregates raw data for multiple variants, as well as generates publication-ready graphics. We showed the potential of the tool in four case studies, including variants of uncertain significance in childhood cancer, proteins with known experimental unfolding ΔΔGs values, interactions between target proteins and disordered motifs, and phosphomimetics. RosettaDDGPrediction is available, free of charge and under GNU General Public License v3.0, at https://github.com/ELELAB/RosettaDDGPrediction .     

Reconstitution of the Anti-Apoptotic Bcl-2 Protein into Lipid Membranes and Biophysical Evidence for Its Detergent-Driven Association with the Pro-Apoptotic Bax Protein

The anti-apoptotic B-cell CLL/lymphoma-2 (Bcl-2) protein and its counterpart, the pro-apoptotic Bcl-2-associated X protein (Bax), are key players in the regulation of the mitochondrial pathway of apoptosis. However, how they interact at the mitochondrial outer membrane (MOM) and there determine whether the cell will live or be sentenced to death remains unknown. Competing models have been presented that describe how Bcl-2 inhibits the cell-killing activity of Bax, which is common in treatment-resistant tumors where Bcl-2 is overexpressed. Some studies suggest that Bcl-2 binds directly to and sequesters Bax, while others suggest an indirect process whereby Bcl-2 blocks BH3-only proteins and prevents them from activating Bax. Here we present the results of a biophysical study in which we investigated the putative interaction of solubilized full-length human Bcl-2 with Bax and the scope for incorporating the former into a native-like lipid environment. Far-UV circular dichroism (CD) spectroscopy was used to detect direct Bcl-2-Bax-interactions in the presence of polyoxyethylene-(23)-lauryl-ether (Brij-35) detergent at a level below its critical micelle concentration (CMC). Additional surface plasmon resonance (SPR) measurements confirmed this observation and revealed a high affinity between the Bax and Bcl-2 proteins. Upon formation of this protein-protein complex, Bax also prevented the binding of antimycin A₂ (a known inhibitory ligand of Bcl-2) to the Bcl-2 protein, as fluorescence spectroscopy experiments showed. In addition, Bcl-2 was able to form mixed micelles with Triton X-100 solubilized neutral phospholipids in the presence of high concentrations of Brij-35 (above its CMC). Following detergent removal, the integral membrane protein was found to have been fully reconstituted into a native-like membrane environment, as confirmed by ultracentrifugation and subsequent SDS-PAGE experiments.     

Local temperatures inferred from plant communities suggest strong spatial buffering of climate warming across Northern Europe

Recent studies from mountainous areas of small spatial extent (<2500 km²) suggest that fine‐grained thermal variability over tens or hundreds of metres exceeds much of the climate warming expected for the coming decades. Such variability in temperature provides buffering to mitigate climate‐change impacts. Is this local spatial buffering restricted to topographically complex terrains? To answer this, we here study fine‐grained thermal variability across a 2500‐km wide latitudinal gradient in Northern Europe encompassing a large array of topographic complexities. We first combined plant community data, Ellenberg temperature indicator values, locally measured temperatures (LmT) and globally interpolated temperatures (GiT) in a modelling framework to infer biologically relevant temperature conditions from plant assemblages within <1000‐m² units (community‐inferred temperatures: CiT). We then assessed: (1) CiT range (thermal variability) within 1‐km² units; (2) the relationship between CiT range and topographically and geographically derived predictors at 1‐km resolution; and (3) whether spatial turnover in CiT is greater than spatial turnover in GiT within 100‐km² units. Ellenberg temperature indicator values in combination with plant assemblages explained 46–72% of variation in LmT and 92–96% of variation in GiT during the growing season (June, July, August). Growing‐season CiT range within 1‐km² units peaked at 60–65°N and increased with terrain roughness, averaging 1.97 °C (SD = 0.84 °C) and 2.68 °C (SD = 1.26 °C) within the flattest and roughest units respectively. Complex interactions between topography‐related variables and latitude explained 35% of variation in growing‐season CiT range when accounting for sampling effort and residual spatial autocorrelation. Spatial turnover in growing‐season CiT within 100‐km² units was, on average, 1.8 times greater (0.32 °C km^?1) than spatial turnover in growing‐season GiT (0.18 °C km^?1). We conclude that thermal variability within 1‐km² units strongly increases local spatial buffering of future climate warming across Northern Europe, even in the flattest terrains.     

snoRNPs Regulate Telomerase Activity in Neuroblastoma and Are Associated with Poor Prognosis

Amplification of the MYCN oncogene is strongly associated with poor prognosis in neuroblastoma (NB). In addition to MYCN amplification, many studies have focused on identifying patients with a poor prognosis based on gene expression profiling. The majority of prognostic signatures today are comprised of large gene lists limiting their clinical application. In addition, although of prognostic significance,most of these signatures fail to identify cellular processes that can explain their relation to prognosis. Here, we determined prognostically predictive genes in a data set containing 251 NBs. Gene Ontology analysis was performed on significant genes with a positive hazard ratio to search for cellular processes associated with poor prognosis. An enrichment in ribonucleoproteins (RNPs) was found. Genes involved in the stabilization and formation of the central small nucleolar RNP (snoRNP) complex were scrutinized using a backward conditional Cox regression resulting in an snoRNP signature consisting of three genes: DKC1, NHP2, and GAR1. The snoRNP signature significantly and independently predicted prognosis when compared to the established clinical risk factors. Association of snoRNP protein expression and prognosis was confirmed using tissue microarrays. Knockdown of snoRNP expression in NB cell lines resulted in reduced telomerase activity and an increase in anaphase bridge frequency. In addition, in patient material, expression of the snoRNP complex was significantly associated with telomerase activity, occurrence of segmental aberrations, and expression-based measurements of chromosomal instability. Together, these results underscore the prognostic value of snoRNP complex expression in NB and suggest a role for snoRNPs in telomere maintenance and genomic stability.     

Syntheses,biological evaluation and SAR of ingenol mebutate analogues for treatment of actinic keratosis and non-melanoma skin cancer

Ingenol mebutate is the active ingredient in Picato® a new drug for the treatment of actinic keratosis. A number of derivatives related to ingenol mebutate were prepared by chemical synthesis from ingenol with the purpose of investigating the SAR and potency in assays relating to pro-inflammatory effects (induction of PMN oxidative burst and keratinocyte cytokine release), the potential of cell death induction, as well as the chemical stability. By modifications of the ingenol scaffold several prerequisites for activity were identified. The chemical stability of the compounds could be linked to an acyl migration mechanism. We were able to find analogues of ingenol mebutate with comparable in vitro properties. Some key features for potent and more stable ingenol derivatives have been identified.