446 research outputs found

    Biological response of an in vitro human 3D lung cell model exposed to brake wear debris varies based on brake pad formulation

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    Wear particles from automotive friction brake pads of various sizes, morphology, and chemical composition are significant contributors towards particulate matter. Knowledge concerning the potential adverse effects following inhalation exposure to brake wear debris is limited. Our aim was, therefore, to generate brake wear particles released from commercial low-metallic and non-asbestos organic automotive brake pads used in mid-size passenger cars by a full-scale brake dynamometer with an environmental chamber simulating urban driving and to deduce their potential hazard in vitro. The collected fractions were analysed using scanning electron microscopy via energy-dispersive X-ray spectroscopy (SEM-EDS) and Raman microspectroscopy. The biological impact of the samples was investigated using a human 3D multicellular model consisting of human epithelial cells (A549) and human primary immune cells (macrophages and dendritic cells) mimicking the human epithelial tissue barrier. The viability, morphology, oxidative stress, and (pro-)inflammatory response of the cells were assessed following 24 h exposure to similar to 12, similar to 24, and similar to 48 A mu g/cm(2) of non-airborne samples and to similar to 3.7 A mu g/cm(2) of different brake wear size fractions (2-4, 1-2, and 0.25-1 A mu m) applying a pseudo-air-liquid interface approach. Brake wear debris with low-metallic formula does not induce any adverse biological effects to the in vitro lung multicellular model. Brake wear particles from non-asbestos organic formulated pads, however, induced increased (pro-)inflammatory mediator release from the same in vitro system. The latter finding can be attributed to the different particle compositions, specifically the presence of anatase.Web of Science9272351233

    Rapid tree carbon stock recovery in managed Amazonian forests.

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    While around 20% of the Amazonian forest has been cleared for pastures and agriculture, one fourth of the remaining forest is dedicated to wood production [1] . Most of these production forests have been or will be selectively harvested for commercial timber, but recent studies show that even soon after logging, harvested stands retain much of their tree-biomass carbon and biodiversity [2,3] . Comparing species richness of various animal taxa among logged and unlogged forests across the tropics, Burivalova et al.[4] found that despite some variability among taxa, biodiversity loss was generally explained by logging intensity (the number of trees extracted). Here, we use a network of 79 permanent sample plots (376 ha total) located at 10 sites across the Amazon Basin [5] to assess the main drivers of time-to-recovery of post-logging tree carbon ( Table S1 ). Recovery time is of direct relevance to policies governing management practices (i.e., allowable volumes cut and cutting cycle lengths), and indirectly to forest-based climate change mitigation interventions

    The tropical managed forests observatory: a research network addressing the future of tropical logged forests.

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    While attention on logging in the tropics has been increasing, studies on the long-term effects of silviculture on forest dynamics and ecology remain scare and spatially limited. Indeed, most of our knowledge on tropical forests arises from studies carried out in undisturbed tropical forests. This biasis problematic given that logged and disturbed tropical forests are now covering a larger area thantheso-alled primary forests. A new network of permanent sample plots in logged forests, the Tropical managed Forests Observatory (TmFO), aims to ?ll this gap by providing unprecedented opportunities to examine long-term data on the resilience of logged tropical forests at regional and global scales. TmFO currently includes 24 experimental sites distributed across three tropical regions, with a total of 490 permanent plots and 921 ha of forest inventories

    Aboveground forest biomass varies across continents, ecological zones and successional stages: Refined IPCC default values for tropical and subtropical forests

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    For monitoring and reporting forest carbon stocks and fluxes, many countries in the tropics and subtropics rely on default values of forest aboveground biomass (AGB) from the Intergovernmental Panel on Climate Change (IPCC) guidelines for National Greenhouse Gas (GHG) Inventories. Default IPCC forest AGB values originated from 2006, and are relatively crude estimates of average values per continent and ecological zone. The 2006 default values were based on limited plot data available at the time, methods for their derivation were not fully clear, and no distinction between successional stages was made. As part of the 2019 Refinement to the 2006 IPCC Guidelines for GHG Inventories, we updated the default AGB values for tropical and subtropical forests based on AGB data from >25 000 plots in natural forests and a global AGB map where no plot data were available. We calculated refined AGB default values per continent, ecological zone, and successional stage, and provided a measure of uncertainty. AGB in tropical and subtropical forests varies by an order of magnitude across continents, ecological zones, and successional stage. Our refined default values generally reflect the climatic gradients in the tropics, with more AGB in wetter areas. AGB is generally higher in old-growth than in secondary forests, and higher in older secondary (regrowth >20 years old and degraded/logged forests) than in young secondary forests (20 years old). While refined default values for tropical old-growth forest are largely similar to the previous 2006 default values, the new default values are 4.0-7.7-fold lower for young secondary forests. Thus, the refined values will strongly alter estimated carbon stocks and fluxes, and emphasize the critical importance of old-growth forest conservation. We provide a reproducible approach to facilitate future refinements and encourage targeted efforts to establish permanent plots in areas with data gaps

    Ultrasensitive gold micro-structured electrodes enabling the detection of extra-cellular long-lasting potentials in astrocytes populations

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    Ultra-sensitive electrodes for extracellular recordings were fabricated and electrically characterized. A signal detection limit defined by a noise level of 0.3-0.4 mu V for a bandwidth of 12.5 Hz was achieved. To obtain this high sensitivity, large area (4 mm(2)) electrodes were used. The electrode surface is also micro-structured with an array of gold mushroom-like shapes to further enhance the active area. In comparison with a flat gold surface, the micro-structured surface increases the capacitance of the electrode/electrolyte interface by 54%. The electrode low impedance and low noise enable the detection of weak and low frequency quasi-periodic signals produced by astrocytes populations that thus far had remained inaccessible using conventional extracellular electrodes. Signals with 5 mu V in amplitude and lasting for 5-10 s were measured, with a peak-to-peak signal-to-noise ratio of 16. The electrodes and the methodology developed here can be used as an ultrasensitive electrophysiological tool to reveal the synchronization dynamics of ultra-slow ionic signalling between non-electrogenic cells.Portuguese Foundation for Science and Technology (FCT), through the project "Implantable organic devices for advanced therapies" (INNOVATE) [PTDC/EEI-AUT/5442/2014]; Instituto de Telecomunicacoes [UID/Multi/04326/2013]; Associated Laboratory - Institute of Nanoscience and Nanotechnology [POCI-01-0145-FEDER-016623]; [PTDC/CTM-NAN/3146/2014

    Evenness mediates the global relationship between forest productivity and richness

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    1. Biodiversity is an important component of natural ecosystems, with higher species richness often correlating with an increase in ecosystem productivity. Yet, this relationship varies substantially across environments, typically becoming less pronounced at high levels of species richness. However, species richness alone cannot reflect all important properties of a community, including community evenness, which may mediate the relationship between biodiversity and productivity. If the evenness of a community correlates negatively with richness across forests globally, then a greater number of species may not always increase overall diversity and productivity of the system. Theoretical work and local empirical studies have shown that the effect of evenness on ecosystem functioning may be especially strong at high richness levels, yet the consistency of this remains untested at a global scale. 2. Here, we used a dataset of forests from across the globe, which includes composition, biomass accumulation and net primary productivity, to explore whether productivity correlates with community evenness and richness in a way that evenness appears to buffer the effect of richness. Specifically, we evaluated whether low levels of evenness in speciose communities correlate with the attenuation of the richness–productivity relationship. 3. We found that tree species richness and evenness are negatively correlated across forests globally, with highly speciose forests typically comprising a few dominant and many rare species. Furthermore, we found that the correlation between diversity and productivity changes with evenness: at low richness, uneven communities are more productive, while at high richness, even communities are more productive. 4. Synthesis. Collectively, these results demonstrate that evenness is an integral component of the relationship between biodiversity and productivity, and that the attenuating effect of richness on forest productivity might be partly explained by low evenness in speciose communities. Productivity generally increases with species richness, until reduced evenness limits the overall increases in community diversity. Our research suggests that evenness is a fundamental component of biodiversity–ecosystem function relationships, and is of critical importance for guiding conservation and sustainable ecosystem management decisions

    Resilience to obesity among socioeconomically disadvantaged women : the READI study

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    Objective: This cross-sectional study aimed to identify sociodemographic and behavioural characteristics of ‘overweight-resilient’ women, that is, women who were in a healthy body weight range, despite living in socioeconomically disadvantaged neighbourhoods that place them at increased risk of obesity. The study also aimed to test a comprehensive theoretically derived model of the associations between intrapersonal, social and environmental factors and obesity among this target group.Participants: A total of 3235 women aged 18–45 years from 80 urban and rural neighbourhoods throughout Victoria, Australia, participated in the Resilience for Eating and Activity Despite Inequality study.Measurements: Women reported height, weight, sociodemographic characteristics, leisure-time physical activity, dietary behaviours and a range of theoretically derived cognitive, social and neighbourhood environmental characteristics hypothesized to influence obesity risk. A theoretical model predicting body mass index (BMI) was tested using structural equation models.Results: Women classified as ‘resilient’ to obesity tended to be younger, born overseas, more highly educated, unmarried and to have higher or undisclosed household incomes. They engaged in more leisure-time physical activity and consumed less fast foods and soft drinks than overweight/obese women. Neighbourhood characteristics, social characteristics and cognitive characteristics all contributed to explaining variation in BMI in the hypothesized directions.Conclusions: These results demonstrate several characteristics of women appearing ‘resilient’ to obesity, despite their increased risk conferred by residing in socioeconomically disadvantaged neighbourhoods. Acknowledging the cross-sectional study design, the results advance theoretical frameworks aimed at investigating obesity risk by providing evidence in support of a comprehensive model of direct and indirect effects on obesity of neighbourhood, as well as social, cognitive and behavioural characteristics
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