39 resultados para sanitization of environmental surfaces
em Université de Lausanne, Switzerland
Resumo:
The contribution of secretory immunoglobulin A (SIgA) antibodies in the defense of mucosal epithelia plays an important role in preventing pathogen adhesion to host cells, therefore blocking dissemination and further infection. This mechanism, referred to as immune exclusion, represents the dominant mode of action of the antibody. However, SIgA antibodies combine multiple facets, which together confer properties extending from intracellular and serosal neutralization of antigens, activation of non-inflammatory pathways and homeostatic control of the endogenous microbiota. The sum of these features suggests that future opportunities for translational application from research-based knowledge to clinics include the mucosal delivery of bioactive antibodies capable of preserving immunoreactivity in the lung, gastrointestinal tract, the genito-urinary tract for the treatment of infections. This article covers topics dealing with the structure of SIgA, the dissection of its mode of action in epithelia lining different mucosal surfaces and its potential in immunotherapy against infectious pathogens.
Resumo:
Humans can recognize categories of environmental sounds, including vocalizations produced by humans and animals and the sounds of man-made objects. Most neuroimaging investigations of environmental sound discrimination have studied subjects while consciously perceiving and often explicitly recognizing the stimuli. Consequently, it remains unclear to what extent auditory object processing occurs independently of task demands and consciousness. Studies in animal models have shown that environmental sound discrimination at a neural level persists even in anesthetized preparations, whereas data from anesthetized humans has thus far provided null results. Here, we studied comatose patients as a model of environmental sound discrimination capacities during unconsciousness. We included 19 comatose patients treated with therapeutic hypothermia (TH) during the first 2 days of coma, while recording nineteen-channel electroencephalography (EEG). At the level of each individual patient, we applied a decoding algorithm to quantify the differential EEG responses to human vs. animal vocalizations as well as to sounds of living vocalizations vs. man-made objects. Discrimination between vocalization types was accurate in 11 patients and discrimination between sounds from living and man-made sources in 10 patients. At the group level, the results were significant only for the comparison between vocalization types. These results lay the groundwork for disentangling truly preferential activations in response to auditory categories, and the contribution of awareness to auditory category discrimination.
Advanced mapping of environmental data: Geostatistics, Machine Learning and Bayesian Maximum Entropy
Resumo:
This book combines geostatistics and global mapping systems to present an up-to-the-minute study of environmental data. Featuring numerous case studies, the reference covers model dependent (geostatistics) and data driven (machine learning algorithms) analysis techniques such as risk mapping, conditional stochastic simulations, descriptions of spatial uncertainty and variability, artificial neural networks (ANN) for spatial data, Bayesian maximum entropy (BME), and more.
Resumo:
The incidence of neurodegenerative disease like Parkinson's disease and Alzheimer's disease (AD) increases dramatically with age; only a small percentage is directly related to familial forms. The etiology of the most abundant, sporadic forms is complex and multifactorial, involving both genetic and environmental factors. Several environmental pollutants have been associated with neurodegenerative disorders. The present article focuses on results obtained in experimental neurotoxicology studies that indicate a potential pathogenic role of lead and mercury in the development of neurodegenerative diseases. Both heavy metals have been shown to interfere with a multitude of intracellular targets, thereby contributing to several pathogenic processes typical of neurodegenerative disorders, including mitochondrial dysfunction, oxidative stress, deregulation of protein turnover, and brain inflammation. Exposure to heavy metals early in development can precondition the brain for developing a neurodegenerative disease later in life. Alternatively, heavy metals can exert their adverse effects through acute neurotoxicity or through slow accumulation during prolonged periods of life. The pro-oxidant effects of heavy metals can exacerbate the age-related increase in oxidative stress that is related to the decline of the antioxidant defense systems. Brain inflammatory reactions also generate oxidative stress. Chronic inflammation can contribute to the formation of the senile plaques that are typical for AD. In accord with this view, nonsteroidal anti-inflammatory drugs and antioxidants suppress early pathogenic processes leading to Alzheimer's disease, thus decreasing the risk of developing the disease. The effects of lead and mercury were also tested in aggregating brain-cell cultures of fetal rat telencephalon, a three-dimensional brain-cell culture system. The continuous application for 10 to 50 days of non-cytotoxic concentrations of heavy metals resulted in their accumulation in brain cells and the occurrence of delayed toxic effects. When applied at non-toxic concentrations, methylmercury, the most common environmental form of mercury, becomes neurotoxic under pro-oxidant conditions. Furthermore, lead and mercury induce glial cell reactivity, a hallmark of brain inflammation. Both mercury and lead increase the expression of the amyloid precursor protein; mercury also stimulates the formation of insoluble beta-amyloid, which plays a crucial role in the pathogenesis of AD and causes oxidative stress and neurotoxicity in vitro. Taken together, a considerable body of evidence suggests that the heavy metals lead and mercury contribute to the etiology of neurodegenerative diseases and emphasizes the importance of taking preventive measures in this regard.
Resumo:
Background and Aims: To protect the population from environmental tobacco smoke (ETS) Switzerland introduced a nationwide rather heterogeneous smoking ban in May 2010. The exposure situation of non-smoking hospitality workers before and after implementation of the new law is being assessed in a prospective cohort study. Methods: Exposure to ETS was measured using a novel method developed by the Institute for Work and Health in Lausanne. It is a passive sampler called MoNIC (Monitor of NICotine). The nicotine of the ETS is fixed onto a filter and transformed into salt of not volatile nicotine. Subsequently the number of passively smoked cigarettes is calculated. Badges were placed at the workplace as well as distributed to the participants for personal measuring. Additionally a salivary sample was taken to determine nicotine concentration. Results: At baseline Spearman's correlation between workplace and personal badge was 0.47. The average cigarette equivalents per day at the workplace obtained by badge significantly dropped from 5.1 (95%- CI: 2.4 to 7.9) at baseline to 0.3 (0.2 to 0.4) at first follow-up (n=29) three months later (p<0.001). For personal badges the number of passively smoked cigarettes declined from 1.5 (2.7 to 0.4) per day to 0.5 (0.3 to 0.8) (n=16).Salivary nicotine concentration in a subset of 13 participants who had worked on the day prior to the examination was 2.63 ng/ml before and 1.53 ng/ml after the ban (p=0.04). Spearman's correlation of salivary nicotine was 0.56 with workplace badge and 0.79 with personal badge concentrations. Conclusions: Workplace measurements clearly reflect the smoking regulation in a venue. The MoNIC badge proves to be a sensitive measuring device to determine personal ETS exposure and it is a demonstrative measure for communication with lay audiences and study participants as the number of passively smoked cigarettes is an easily conceivable result.
Resumo:
Abstract: Traditionally, pollution risk assessment is based on the measurement of a pollutant's total concentration in a sample. The toxicity of a given pollutant in the environment, however, is tightly linked to its bioavailability, which may differ significantly from the total amount. Physico-chemical and biological parameters strongly influence pollutant fate in terms of leaching, sequestration and biodegradation. Bacterial sensorreporters, which consist of living micro-organisms genetically engineered to produce specific output in response to target chemicals, offer an interesting alternative to monitoring approaches. Bacterial sensor-reporters detect bioavailable and/or bioaccessible compound fractions in samples. Currently, a variety of environmental pollutants can be targeted by specific biosensor-reporters. Although most of such strains are still confined to the lab, several recent reports have demonstrated utility of bacterial sensing-reporting in the field, with method detection limits in the nanomolar range. This review illustrates the general design principles for bacterial sensor-reporters, presents an overview of the existing biosensor-reporter strains with emphasis on organic compound detection. A specific focus throughout is on the concepts of bioavailability and bioaccessibility, and how bacteria-based sensing-reporting systems can help to improve our basic understanding of the different processes at work.
Resumo:
The distribution of living organisms, habitats and ecosystems is primarily driven by abiotic environmental factors that are spatially structured. Assessing the spatial structure of environmental factors, e.g., through spatial autocorrelation analyses (SAC), can thus help us understand their scale of influence on the distribution of organisms, habitats, and ecosystems. Yet SAC analyses of environmental factors are still rarely performed in biogeographic studies. Here, we describe a novel framework that combines SAC and statistical clustering to identify scales of spatial patterning of environmental factors, which can then be interpreted as the scales at which those factors influence the geographic distribution of biological and ecological features. We illustrate this new framework with datasets at different spatial or thematic resolutions. This framework is conceptually and statistically robust, providing a valuable approach to tackle a wide range of issues in ecological and environmental research and particularly when building predictors for ecological models. The new framework can significantly promote fundamental research on all spatially-structured ecological patterns. It can also foster research and application in such fields as global change ecology, conservation planning, and landscape management.
Resumo:
We studied the distribution of Palearctic green toads (Bufo viridis subgroup), an anuran species group with three ploidy levels, inhabiting the Central Asian Amudarya River drainage. Various approaches (one-way, multivariate, components variance analyses and maximum entropy modelling) were used to estimate the effect of altitude, precipitation, temperature and land vegetation covers on the distribution of toads. It is usually assumed that polyploid species occur in regions with harsher climatic conditions (higher latitudes, elevations, etc.), but for the green toads complex, we revealed a more intricate situation. The diploid species (Bufo shaartusiensis and Bufo turanensis) inhabit the arid lowlands (from 44 to 789 m a.s.l.), while tetraploid Bufo pewzowi were recorded in mountainous regions (340-3492 m a.s.l.) with usually lower temperatures and higher precipitation rates than in the region inhabited by diploid species. The triploid species Bufo baturae was found in the Pamirs (Tajikistan) at the highest altitudes (2503-3859 m a.s.l.) under the harshest climatic conditions.
Resumo:
The variations of environmental conditions (T°, pH, δ13CDIC, [DIC], δ18O, Mg/Ca, and Sr/Ca) of ostracod habitats were examined to determine the controls of environmental parameters on the chemical and isotopic composition of ostracod valves. Results of a one-year monitoring of environmental parameters at five sites, with depths of between 2 and 70 m, in Lake Geneva indicate that in littoral to sub-littoral zones (2, 5, and 13 m), the chemical composition of bottom water varies seasonally in concert with changes in temperature and photosynthetic activity. An increase of temperature and photosynthetic activity leads to an increase in δ13C values of DIC and to precipitation of authigenic calcite, which results in a concomitant increase of Mg/Ca and Sr/Ca ratios of water. In deeper sites (33 and 70 m), the composition of bottom water remains constant throughout the year and isotopic values and trace element contents are similar to those of deep water within the lake. The chemical composition of interstitial pore water also does not reflect seasonal variations but is controlled by calcite dissolution, aerobic respiration, anaerobic respiration with reduction of sulphate and/or nitrate, and methanogenesis that may occur in the sediment pores. Relative influence of each of these factors on the pore water geochemistry depends on sediment thickness and texture, oxygen content in bottom as well as pore water. Variations of chemical compositions of the ostracod valves of this study vary according to the specific ecology of the ostracod species analysed, that is its life-cycle and its (micro-)habitat. Littoral species have compositions that are related to the seasonal variations of temperature, δ13C values of DIC, and of Mg/Ca and Sr/Ca ratios of water. In contrast, the compositions of profundal species are largely controlled by variations of pore fluids along sediment depth profiles according to the specific depth preference of the species. The control on the geochemistry of sub-littoral species is a combination of controls for the littoral and profundal species as well as the specific ecology of the species.