67 research outputs found
Incorporation of Radiolabeled Leucine into Protein to Estimate Bacterial Production in Plant Litter, Sediment, Epiphytic Biofilms, and Water Samples
The present study assessed the application of tritiated leucine incorporation into protein, as a measure of bacterial biomass production, within four benthic habitats of a littoral freshwater wetland dominated by emergent vegetation. Basic assumptions underlying the method, such as linearity of leucine incorporation, saturation level of incorporation rates, and specificity of incorporation for bacterial assemblages, were tested, and two procedures for extracting radiolabeled protein were compared. TCA precipitation followed by ultrasonication, and subsequent alkaline dissolution in 0.5 M NaOH, 25 mM EDTA, and 0.1% w/v SDS, gave best results in terms of both extraction efficiency and signal-to-noise ratio. Incorporation of leucine was linear for all habitats for up to 1 h. Saturation concentrations of leucine incorporation into protein were 150 nM for littoral surface waters, >960 nM for biofilms on plant surfaces, and 50 mM for aerobic sediment and submerged plant litter. An experiment with prokaryotic and eukaryotic inhibitors designed to examine specificity of leucine incorporation into bacterial protein showed no significant leucine incorporation into eukaryotes during short-term incubations. Calculations based on kinetic parameters of fungal leucine uptake suggest, nevertheless, that significant leucine incorporation cannot be ruled out in all situations. Thus, the leucine methodology can be used for estimating bacterial production in benthic aquatic habitats, provided that substrate saturation and isotope dilution are determined and that the active biomass of eukaryotes, such as fungi, does not greatly exceed bacterial biomas
Anaphylaxis in Elderly Patients-Data From the European Anaphylaxis Registry
Background: Elicitors and symptoms of anaphylaxis are age dependent. However, little is known about typical features of anaphylaxis in patients aged 65 years or more.
Methods: The data from the Network for Online Registration of Anaphylaxis (NORA) considering patients aged ≥65 (elderly) in comparison to data from adults (18–64 years) regarding elicitors, symptoms, comorbidities, and treatment measures were analyzed.
Results: We identified 1,123 elderly anaphylactic patients. Insect venoms were the most frequent elicitor in this group (p < 0.001), followed by drugs like analgesics and antibiotics. Food allergens elicited less frequently anaphylaxis (p < 0.001). Skin symptoms occurred less frequently in elderly patients (77%, p < 0.001). The clinical symptoms were more severe in the elderly (51% experiencing grade III/IV reactions), in particular when skin symptoms (p < 0.001) were absent. Most strikingly, a loss of consciousness (33%, p < 0.001) and preexisting cardiovascular comorbidity (59%, p < 0.001) were more prevalent in the elderly. Finally, adrenaline was used in 30% of the elderly (vs. 26% in the comparator group, p < 0.001) and hospitalization was more often required (60 vs. 50%, p < 0.001).
Discussion and Conclusion: Anaphylaxis in the elderly is often caused by insect venoms and drugs. These patients suffer more often from cardiovascular symptoms, receive more frequently adrenaline and require more often hospitalization. The data indicate that anaphylaxis in the elderly tends to be more frequently life threatening and patients require intensified medical intervention. The data support the need to recognize anaphylaxis in this patient group, which is prone to be at a higher risk for a fatal outcome
Democratic population decisions result in robust policy-gradient learning: A parametric study with GPU simulations
High performance computing on the Graphics Processing Unit (GPU) is an emerging field driven by the promise of high computational power at a low cost. However, GPU programming is a non-trivial task and moreover architectural limitations raise the question of whether investing effort in this direction may be worthwhile. In this work, we use GPU programming to simulate a two-layer network of Integrate-and-Fire neurons with varying degrees of recurrent connectivity and investigate its ability to learn a simplified navigation task using a policy-gradient learning rule stemming from Reinforcement Learning. The purpose of this paper is twofold. First, we want to support the use of GPUs in the field of Computational Neuroscience. Second, using GPU computing power, we investigate the conditions under which the said architecture and learning rule demonstrate best performance. Our work indicates that networks featuring strong Mexican-Hat-shaped recurrent connections in the top layer, where decision making is governed by the formation of a stable activity bump in the neural population (a "non-democratic" mechanism), achieve mediocre learning results at best. In absence of recurrent connections, where all neurons "vote" independently ("democratic") for a decision via population vector readout, the task is generally learned better and more robustly. Our study would have been extremely difficult on a desktop computer without the use of GPU programming. We present the routines developed for this purpose and show that a speed improvement of 5x up to 42x is provided versus optimised Python code. The higher speed is achieved when we exploit the parallelism of the GPU in the search of learning parameters. This suggests that efficient GPU programming can significantly reduce the time needed for simulating networks of spiking neurons, particularly when multiple parameter configurations are investigated. © 2011 Richmond et al
Effects of a wearable exoskeleton stride management assist system (SMA®) on spatiotemporal gait characteristics in individuals after stroke: a randomized controlled trial
Effect of a rosmarinic acid supplemented hemodialysis fluid on inflammation of human vascular endothelial cells
Antibiotic mixture effects on growth of the leaf-shredding stream detritivore Gammarus fossarum
Contrasting effects of ultraviolet radiation on the growth efficiency of freshwater bacteria
Effects of Anacetrapib in Patients with Atherosclerotic Vascular Disease
BACKGROUND:
Patients with atherosclerotic vascular disease remain at high risk for cardiovascular events despite effective statin-based treatment of low-density lipoprotein (LDL) cholesterol levels. The inhibition of cholesteryl ester transfer protein (CETP) by anacetrapib reduces LDL cholesterol levels and increases high-density lipoprotein (HDL) cholesterol levels. However, trials of other CETP inhibitors have shown neutral or adverse effects on cardiovascular outcomes.
METHODS:
We conducted a randomized, double-blind, placebo-controlled trial involving 30,449 adults with atherosclerotic vascular disease who were receiving intensive atorvastatin therapy and who had a mean LDL cholesterol level of 61 mg per deciliter (1.58 mmol per liter), a mean non-HDL cholesterol level of 92 mg per deciliter (2.38 mmol per liter), and a mean HDL cholesterol level of 40 mg per deciliter (1.03 mmol per liter). The patients were assigned to receive either 100 mg of anacetrapib once daily (15,225 patients) or matching placebo (15,224 patients). The primary outcome was the first major coronary event, a composite of coronary death, myocardial infarction, or coronary revascularization.
RESULTS:
During the median follow-up period of 4.1 years, the primary outcome occurred in significantly fewer patients in the anacetrapib group than in the placebo group (1640 of 15,225 patients [10.8%] vs. 1803 of 15,224 patients [11.8%]; rate ratio, 0.91; 95% confidence interval, 0.85 to 0.97; P=0.004). The relative difference in risk was similar across multiple prespecified subgroups. At the trial midpoint, the mean level of HDL cholesterol was higher by 43 mg per deciliter (1.12 mmol per liter) in the anacetrapib group than in the placebo group (a relative difference of 104%), and the mean level of non-HDL cholesterol was lower by 17 mg per deciliter (0.44 mmol per liter), a relative difference of -18%. There were no significant between-group differences in the risk of death, cancer, or other serious adverse events.
CONCLUSIONS:
Among patients with atherosclerotic vascular disease who were receiving intensive statin therapy, the use of anacetrapib resulted in a lower incidence of major coronary events than the use of placebo. (Funded by Merck and others; Current Controlled Trials number, ISRCTN48678192 ; ClinicalTrials.gov number, NCT01252953 ; and EudraCT number, 2010-023467-18 .)
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