Visually evoked cerebral vasomotor response in smoking and nonsmoking young adults, investigated by functional transcranial Doppler

Smoking has been known to cause endothelial dysfunction and is an important risk factor for ischemic stroke. In our study we investigated whether chronic cigarette smoking affects the cerebral blood flow velocity response to a physiological, visual stimulus. By using a visual cortex stimulation paradigm, the flow velocity response in the posterior cerebral arteries (PCA) was measured bilaterally, in 32 young healthy adults (16 smokers, 16 nonsmokers). The stimulation protocol consisted of 10 cycles with a resting phase of 20 s and a stimulating phase of 40 s for each cycle. Besides functional transcranial Doppler (TCD), laboratory tests and measurement of intima-media-thickness (IMT) were also performed. Repeated-measure analysis of variance (ANOVA) was used to detect differences in visually evoked relative flow velocity time courses between smokers and nonsmokers. Repeated-measure ANOVA revealed marked difference in the peak systolic flow velocity time courses between smokers and nonsmokers (p< .001). Maximum percent change of visually evoked flow velocity after visual stimulation was 19+/-4% and 30+/-3% in smokers and nonsmokers, respectively (p< .0001). IMT values did not indicate atherosclerosis in young smokers. Infectious disease and hyperlipidemia were also ruled out by measurement of sensitive C-reactive protein and serum lipids. This is the first functional TCD study demonstrating impaired visually evoked flow velocity response caused by chronic cigarette smoking in otherwise healthy, young subjects. The impaired cerebral vasodilatory mechanism together with atherosclerosis may influence stroke occurrence and outcome in chronic smokers.     

Efficiently Detecting Metallodrug–Protein Adducts: Ion Trap versus Time‐of‐Flight Mass Analyzers

Modern mass spectrometry techniques have increasingly found use in studies on the binding of anticancer metallodrugs to potential cellular targets. In this context, investigations on the detection efficiency of adduct formation between antiproliferative Ru(arene) complexes and proteins in dependence of the mass analyzer used in the electrospray ionization (ESI) mass spectrometer are presented. The potential in detecting adducts between the metal center and the protein was found to be dependent on the mass analyzer and the denticity of the metal–protein interaction. This might be related to the design of the mass analyzers with different conditions in the ion travelling pathways, which affects adducts when the protein acts as a monodentate ligand more highly than in cases when the protein is a multidentate ligand. This could also impact the biological activity and indicate different pathways of metabolism of biomolecule adducts.     

Synthesis, σ Receptor Affinity,and Pharmacological Evaluation of 5‐Phenylsulfanyl‐ and 5‐Benzyl‐Substituted Tetrahydro‐2‐benzazepines

In accordance with a novel strategy for generating the 2‐benzazepine scaffold by connecting C6–C1 and C3–N building blocks, a set of 5‐phenylsulfanyl‐ and 5‐benzyl‐substituted tetrahydro‐2‐benzazepines was synthesized and pharmacologically evaluated. Key steps of the synthesis were the Heck reaction, the Stetter reaction, a reductive cyclization, and the introduction of diverse N substituents at the end of the synthesis. High σ₁ affinity was achieved for 2‐benzazepines with linear or branched alk(en)yl residues containing at least an n‐butyl substructure. The butyl‐ and 4‐fluorobenzyl‐substituted derivatives, (±)‐5‐benzyl‐2‐butyl‐2,3,4,5‐tetrahydro‐1H‐2‐benzazepine ( 19 b ) and (±)‐5‐benzyl‐2‐(4‐fluorobenzyl)‐2,3,4,5‐tetrahydro‐1H‐2‐benzazepine ( 19 m ), show high selectivity over more than 50 other relevant targets, including the σ₂ subtype and various binding sites of the N‐methyl‐D ‐aspartate (NMDA) receptor. In the Irwin screen, 19 b and 19 m showed clean profiles without inducing considerable side effects. Compounds 19 b and 19 m did not reveal significant analgesic and cognition‐enhancing activity. Compound 19 m did not have any antidepressant‐like effects in mice.     

ENDOW (efficient development of offshore wind farms): modelling wake and boundary layer interactions

While experience gained through the offshore wind energy projects currently operating is valuable, a major uncertainty in estimating power production lies in the prediction of the dynamic links between the atmosphere and wind turbines in offshore regimes. The objective of the ENDOW project was to evaluate, enhance and interface wake and boundary layer models for utilization offshore. The project resulted in a significant advance in the state of the art in both wake and marine boundary layer models, leading to improved prediction of wind speed and turbulence profiles within large offshore wind farms. Use of new databases from existing offshore wind farms and detailed wake profiles collected using sodar provided a unique opportunity to undertake the first comprehensive evaluation of wake models in the offshore environment. The results of wake model performance in different wind speed, stability and roughness conditions relative to observations provided criteria for their improvement. Mesoscale model simulations were used to evaluate the impact of thermal flows, roughness and topography on offshore wind speeds. The model hierarchy developed under ENDOW forms the basis of design tools for use by wind energy developers and turbine manufacturers to optimize power output from offshore wind farms through minimized wake effects and optimal grid connections. The design tools are being built onto existing regional‐scale models and wind farm design software which was developed with EU funding and is in use currently by wind energy developers. Copyright © 2004 John Wiley & Sons, Ltd.     

Metabolic fingerprinting of biofluids by infrared spectroscopy: modeling and optimization of flow rates for laminar fluid diffusion interface sample preconditioning

The laminar fluid diffusion interface (LFDI) is a microfluidic tool that manipulates the composition of liquid mixtures by exploiting differences among diffusion coefficients of the dissolved components. One application is the preprocessing of (bio)fluids prior to spectroscopic characterization. For example, in the case of infrared (IR) spectroscopy, the technique can improve sensitivity to low-concentration serum metabolites. The practical benefit is "metabolic fingerprinting" measurements that are more sensitive to low-concentration metabolites than are the counterpart measurements for the original serum sample. Optimal use of the LFDI technique has proven elusive, since the composition of the product of interest is very sensitive to the choice of flow rates for the liquid streams entering and emerging from the LFDI channel. To provide the basis for optimal use, this study had the objective of developing a simulation package that predicts the composition of the LFDI product, given the LFDI structural and operating parameters. To demonstrate the utility of the simulations, composition of the LFDI products predicted for two illustrative sets of trials were compared with experimental data. The flow rates thus derived provided a LFDI product that is relatively rich in serum metabolites, while largely depleted of protein, and very well suited for subsequent IR spectroscopic characterization.     

Damage due to heavy traffic on three RC road bridges

An investigation of the damage caused by road traffic on three reinforced concrete bridges was performed. This study was performed with a focus on the determination of the damage induced by heavy vehicles in relation to the damage caused by average everyday traffic. A damage model based on fatigue of reinforcement bars was employed. The stress cycles in the reinforcement bars were determined using measurements of the crack widths under traffic loading. Stress cycles were analyzed using the Rainflow Method and Miner’s Rule was employed to gain a measurement for the damage. Monitoring systems were installed on each of the three bridges and operated for several weeks continuously to collect input data for the damage model. Computer software was developed to process the monitoring data in the sense of the damage model. The described methodology was developed and used for the first time in the described project.Heavy traffic was shown to cause a disproportionate high portion of the overall damage on all three bridges. The obtained results indicated that the damage caused by singular events, such as the passage of a heavy vehicle, in relation to the damaging effects of every-day traffic differed significantly between the considered bridges. For one of the bridges the greatest damage from singular traffic events was computed for passages of special transport vehicles. The same bridge was also found to display the highest damage by a single passage in relation to average everyday traffic. Passages of short and heavy trucks with four and five axles were identified as the most detrimental traffic events on the other two bridges.