Affective and physiological responses to environmental noises and music

Research suggests that respiratory patterns may reflect general dimensions of emotional response. In this study, we investigated the relationships between judgments of affective valence (pleasantness) and arousal and respiratory responses to acoustic stimuli. Sixteen environmental noises and 16 musical fragments of 30 s duration were presented to 31 participants, while respiration, skin conductance level and heart rate were recorded. Judgments of valence and arousal were registered using the 9-point Self-Assessment Manikin. For noises, breathing accelerated and minute ventilation augmented with decreases in pleasantness for low-arousal stimuli and with increases in arousal for positive stimuli. For music, breathing accelerated and minute ventilation augmented with increases both in rated valence and arousal. Skin conductance level increased with arousal ratings for music but not for noises, whereas mean heart rate increased with rated arousal for noises but not for music. Although both noises and music are sound-vibrations, differences in the relationships between affective judgments and physiological responses were found suggesting differences in the processing of the two types of acoustic stimuli. [Authors]

Immunoproteomics for Serological Diagnosis of Hypersensitivity Pneumonitis Caused by Environmental Microorganisms.

Diagnosis of immunoallergenic pathologies due to microorganisms such as hypersensitivity pneumonitis includes detection of circulating specific antibodies. Detection of precipitins has classically been performed using immunoprecipitation techniques with crude antigenic extracts from microorganisms implicated as etiologic agents. However, these techniques lack standardization because of the different composition of fungal antigenic extracts from one batch to another. Therefore, there is high interest in developing standardized serological diagnostic methods using recombinant antigens. Immunoproteomics have proved to be useful for identifying the immunogenic proteins in several microorganisms linked to hypersensitivity pneumonitis. With this approach, the causative microorganisms are first isolated from the environment of patients. Then the proteins are separated by two-dimensional electrophoresis and revealed by Western blotting with sera of different patients suffering from the disease compared to sera of asymptomatic exposed controls. Immunoreactive proteins are identified by mass spectrometry. Identified immunoreactive proteins found to be specific markers for the disease could be subsequently produced as recombinant antigens using various expression systems to develop ELISA tests. Using recombinant antigens, standardized ELISA techniques can be developed, with sensitivity and specificity reaching 80% and 90%, respectively, and more if using a combination of several antigens. Immunoproteomics can be applied to any environmental microorganisms, with the aim of proposing panels of recombinant antigens able to improve the sensitivity and standardization of serologic diagnosis of hypersensitivity pneumonitis, but also other mold-induced allergic diseases such as allergic broncho pulmonary aspergillosis or asthma.

Assessing the environmental impact of water consumption by energy crops grown in Spain

The environmental impact of the water consumption of four typical crop rotations grown in Spain, including energy crops, was analyzed and compared against Spanish agricultural and natural reference situations. The life cycle assessment (LCA) methodology was used for the assessment of the potential environmental impact of blue water (withdrawal from water bodies) and green water (uptake of soil moisture) consumption. The latter has so far been disregarded in LCA. To account for green water, two approaches have been applied: the first accounts for the difference in green water demand of the crops and a reference situation. The second is a green water scarcity index, which measures the fraction of the soil-water plant consumption to the available green water. Our results show that, if the aim is to minimize the environmental impacts of water consumption, the energy crop rotations assessed in this study were most suitable in basins in the northeast of Spain. In contrast, the energy crops grown in basins in the southeast of Spain were associated with the greatest environmental impacts. Further research into the integration of quantitative green water assessment in LCA is crucial in studies of systems with a high dependence on green water resources.

Ensemble methods for environmental data modelling with support vector regression

This paper investigates the use of ensemble of predictors in order to improve the performance of spatial prediction methods. Support vector regression (SVR), a popular method from the field of statistical machine learning, is used. Several instances of SVR are combined using different data sampling schemes (bagging and boosting). Bagging shows good performance, and proves to be more computationally efficient than training a single SVR model while reducing error. Boosting, however, does not improve results on this specific problem.

Low environmental impact bleaching sequences for attaining high brightness level with eucalyptus SPP pulp

The alternatives used for minimizing the usage of chlorine dioxide in bleaching sequences included a hot acid hydrolysis (Ahot) stage, the use of hot chlorine dioxide (Dhot) and ozone stages at medium consistency and high consistency (Zmc and Zhc), in addition to stages with atmospheric hydrogen peroxide (P) and pressurized hydrogen peroxide (PO). The results were interpreted based on the cost of the chemical products, bleaching process yields and on minimizing the environmental impact of the bleaching process. In spite of some process restrictions, high ISO brightness levels were kept around 90 % brightness. Additionally, the inclusion of stages like acid hydrolysis, pressurized peroxide and ozone in the bleaching sequences provided an increase in operating flexibility, aimed at reducing environmental impact (ECF Light). The Dhot(EOP)D(PO) sequence presented lower operating cost for ISO brightness above 92 %. However, this kind of sequence was not allowed for closing the wastewater circuit, even partially. For ISO brightness level around 91%, the AhotZhcDP sequence presented a lower operating cost than the others

Gene-disease network analysis reveals functional modules in mendelian, complex and environmental diseases

AbstractBACKGROUND: Scientists have been trying to understand the molecular mechanisms of diseases to design preventive and therapeutic strategies for a long time. For some diseases, it has become evident that it is not enough to obtain a catalogue of the disease-related genes but to uncover how disruptions of molecular networks in the cell give rise to disease phenotypes. Moreover, with the unprecedented wealth of information available, even obtaining such catalogue is extremely difficult.PRINCIPAL FINDINGS: We developed a comprehensive gene-disease association database by integrating associations from several sources that cover different biomedical aspects of diseases. In particular, we focus on the current knowledge of human genetic diseases including mendelian, complex and environmental diseases. To assess the concept of modularity of human diseases, we performed a systematic study of the emergent properties of human gene-disease networks by means of network topology and functional annotation analysis. The results indicate a highly shared genetic origin of human diseases and show that for most diseases, including mendelian, complex and environmental diseases, functional modules exist. Moreover, a core set of biological pathways is found to be associated with most human diseases. We obtained similar results when studying clusters of diseases, suggesting that related diseases might arise due to dysfunction of common biological processes in the cell.CONCLUSIONS: For the first time, we include mendelian, complex and environmental diseases in an integrated gene-disease association database and show that the concept of modularity applies for all of them. We furthermore provide a functional analysis of disease-related modules providing important new biological insights, which might not be discovered when considering each of the gene-disease association repositories independently. Hence, we present a suitable framework for the study of how genetic and environmental factors, such as drugs, contribute to diseases.AVAILABILITY: The gene-disease networks used in this study and part of the analysis are available at http://ibi.imim.es/DisGeNET/DisGeNETweb.html#Download

Cutting edge: cell autonomous rather than environmental factors control bacterial superantigen-induced T cell anergy in vivo.

Anergic T cells display a marked decrease in their ability to produce IL-2 and to proliferate in the presence of an appropriate antigenic signal. Two nonmutually exclusive classes of models have been proposed to explain the persistence of T cell anergy in vivo. While some reports indicate that anergic T cells have intrinsic defects in signaling pathways or transcriptional activities, other studies suggest that anergy is maintained by environmental "suppressor" factors such as cytokines or Abs. To distinguish between these conflicting hypotheses, we employed the well-characterized bacterial superantigen model system to evaluate in vivo the ability of a trace population of adoptively transferred naive or anergized T cells to proliferate in a naive vs anergic environment upon subsequent challenge. Our data clearly demonstrate that bacterial superantigen-induced T cell anergy is cell autonomous and independent of environmental factors.

Environmental effects on photosynthetic capacity of bean genotypes

Photosynthetic responses to daily environmental changes were studied in bean (Phaseolus vulgaris L.) genotypes 'Carioca', 'Ouro Negro', and Guarumbé. Light response curves of CO2 assimilation and stomatal conductance (g s) were also evaluated under controlled (optimum) environmental condition. Under this condition, CO2 assimilation of 'Carioca' was not saturated at 2,000 µmol m-2 s-1, whereas Guarumbé and 'Ouro Negro' exhibited different levels of light saturation. All genotypes showed dynamic photoinhibition and reversible increase in the minimum chlorophyll fluorescence yield under natural condition, as well as lower photosynthetic capacity when compared with optimum environmental condition. Since differences in g s were not observed between natural and controlled conditions for Guarumbé and 'Ouro Negro', the lower photosynthetic capacity of these genotypes under natural condition seems to be caused by high temperature effects on biochemical reactions, as suggested by increased alternative electron sinks. The highest g s values of 'Carioca' were observed at controlled condition, providing evidences that reduction of photosynthetic capacity at natural condition was due to low g s in addition to the high temperature effects on the photosynthetic apparatus. 'Carioca' exhibited the highest photosynthetic rates under optimum environmental condition, and was more affected by daily changes of air temperature and leaf-to-air vapor pressure difference.

The immunological, environmental, and phylogenetic perpetrators of metastatic leishmaniasis.

Cutaneous leishmaniases have persisted for centuries as chronically disfiguring parasitic infections affecting millions of people across the subtropics. Symptoms range from the more prevalent single, self-healing cutaneous lesion to a persistent, metastatic disease, where ulcerations and granulomatous nodules can affect multiple secondary sites of the skin and delicate facial mucosa, even sometimes diffusing throughout the cutaneous system as a papular rash. The basis for such diverse pathologies is multifactorial, ranging from parasite phylogeny to host immunocompetence and various environmental factors. Although complex, these pathologies often prey on weaknesses in the innate immune system and its pattern recognition receptors. This review explores the observed and potential associations among the multifactorial perpetrators of infectious metastasis and components of the innate immune system.

Photosynthetic responses of young cashew plants to varying environmental conditions

The aim of this study was to characterize gas exchange responses of young cashew plants to varying photosynthetic photon flux density (PPFD), temperature, vapor-pressure deficit (VPD), and intercellular CO2 concentration (Ci), under controlled conditions. Daily courses of gas exchange and chlorophyll a fluorescence parameters were measured under natural conditions. Maximum CO2 assimilation rates, under optimal controlled conditions, were about 13 mmol m-2 s-1 , with light saturation around 1,000 mmol m-2 s-1. Leaf temperatures between 25ºC and 35ºC were optimal for photosynthesis. Stomata showed sensitivity to CO2, and a closing response with increasing Ci. Increasing VPD had a small effect on CO2 assimilation rates, with a small decrease above 2.5 kPa. Stomata, however, were strongly affected by VPD, exhibiting gradual closure above 1.5 kPa. The reduced stomatal conductances at high VPD were efficient in restricting water losses by transpiration, demonstrating the species adaptability to dry environments. Under natural irradiance, CO2 assimilation rates were saturated in early morning, following thereafter the PPFD changes. Transient Fv/Fm decreases were registered around 11h, indicating the occurrence of photoinhibition. Decreases of excitation capture efficiency, decreases of effective quantum yield of photosystem II, and increases in non-photochemical quenching were consistent with the occurrence of photoprotection under excessive irradiance levels.

Machine learning for spatial environmental data. Theory, applications and software

The book presents the state of the art in machine learning algorithms (artificial neural networks of different architectures, support vector machines, etc.) as applied to the classification and mapping of spatially distributed environmental data. Basic geostatistical algorithms are presented as well. New trends in machine learning and their application to spatial data are given, and real case studies based on environmental and pollution data are carried out. The book provides a CD-ROM with the Machine Learning Office software, including sample sets of data, that will allow both students and researchers to put the concepts rapidly to practice.