What Do We Know About Metal Recycling Rates?

The recycling of metals is widely viewed as a fruitful sustainability strategy, but little information is available on the degree to which recycling is actually taking place. This article provides an overview on the current knowledge of recycling rates for 60 metals. We propose various recycling metrics, discuss relevant aspects of recycling processes, and present current estimates on global end‐of‐life recycling rates (EOL‐RR; i.e., the percentage of a metal in discards that is actually recycled), recycled content (RC), and old scrap ratios (OSRs; i.e., the share of old scrap in the total scrap flow). Because of increases in metal use over time and long metal in‐use lifetimes, many RC values are low and will remain so for the foreseeable future. Because of relatively low efficiencies in the collection and processing of most discarded products, inherent limitations in recycling processes, and the fact that primary material is often relatively abundant and low‐cost (which thereby keeps down the price of scrap), many EOL‐RRs are very low: Only for 18 metals (silver, aluminum, gold, cobalt, chromium, copper, iron, manganese, niobium, nickel, lead, palladium, platinum, rhenium, rhodium, tin, titanium, and zinc) is the EOL‐RR above 50% at present. Only for niobium, lead, and ruthenium is the RC above 50%, although 16 metals are in the 25% to 50% range. Thirteen metals have an OSR greater than 50%. These estimates may be used in considerations of whether recycling efficiencies can be improved; which metric could best encourage improved effectiveness in recycling; and an improved understanding of the dependence of recycling on economics, technology, and other factors.     

Application of polyethyleneimine cellulose for the class separation of steroidal carboxylic acids from neutral steroids and pigments in urine

Metabolites of corticosteroids that contain the 21-oic acid moiety are found in human urine. The acids from neutral steroids and urinary pigments have been separated by passing the mixture through a column of polyethyleneimine cellulose. The acids adhering to the column are quantitatively eluted with dilute formic acid. The purified preparation is suitable for derivatization and chromatographic analysis.     

Genetic Targets of Hydrogen Sulfide in Ventilator-Induced Lung Injury – A Microarray Study

Recently, we have shown that inhalation of hydrogen sulfide (H₂S) protects against ventilator-induced lung injury (VILI). In the present study, we aimed to determine the underlying molecular mechanisms of H₂S-dependent lung protection by analyzing gene expression profiles in mice. C57BL/6 mice were subjected to spontaneous breathing or mechanical ventilation in the absence or presence of H₂S (80 parts per million). Gene expression profiles were determined by microarray, sqRT-PCR and Western Blot analyses. The association of Atf3 in protection against VILI was confirmed with a Vivo-Morpholino knockout model. Mechanical ventilation caused a significant lung inflammation and damage that was prevented in the presence of H₂S. Mechanical ventilation favoured the expression of genes involved in inflammation, leukocyte activation and chemotaxis. In contrast, ventilation with H₂S activated genes involved in extracellular matrix remodelling, angiogenesis, inhibition of apoptosis, and inflammation. Amongst others, H₂S administration induced Atf3, an anti-inflammatory and anti-apoptotic regulator. Morpholino mediated reduction of Atf3 resulted in elevated lung injury despite the presence of H₂S. In conclusion, lung protection by H₂S during mechanical ventilation is associated with down-regulation of genes related to oxidative stress and inflammation and up-regulation of anti-apoptotic and anti-inflammatory genes. Here we show that Atf3 is clearly involved in H₂S mediated protection.     

Mechanisms of neisserial serum resistance

Pathogenic Neisseria use a variety of mechanisms to survive the bactericidal action of the complement system. Serum resistance is a crucial virulence factor for the development of severe meningococcal disease, meningococcal meningitis and disseminated gonococcal infection. Furthermore, local inflammation at the site of gonococcal infection exposes the bacteria to moderate concentrations of complement factors. We review current concepts of neisserial serum resistance with emphasis on porins and polysaccharides exposed on the neisserial surface and their interaction with components of normal human serum.     

Interactions Among Fuel Management,Species Composition,Bark Beetles,and Climate Change and the Potential Effects on Forests of the Lake Tahoe Basin

Climate-driven increases in wildfires, drought conditions, and insect outbreaks are critical threats to forest carbon stores. In particular, bark beetles are important disturbance agents although their long-term interactions with future climate change are poorly understood. Droughts and the associated moisture deficit contribute to the onset of bark beetle outbreaks although outbreak extent and severity is dependent upon the density of host trees, wildfire, and forest management. Our objective was to estimate the effects of climate change and bark beetle outbreaks on ecosystem carbon dynamics over the next century in a western US forest. Specifically, we hypothesized that (a) bark beetle outbreaks under climate change would reduce net ecosystem carbon balance (NECB) and increase uncertainty and (b) these effects could be ameliorated by fuels management. We also examined the specific tree species dynamics—competition and release—that determined NECB response to bark beetle outbreaks. Our study area was the Lake Tahoe Basin (LTB), CA and NV, USA, an area of diverse forest types encompassing steep elevation and climatic gradients and representative of mixed-conifer forests throughout the western United States. We simulated climate change, bark beetles, wildfire, and fuels management using a landscape-scale stochastic model of disturbance and succession. We simulated the period 2010–2100 using downscaled climate projections. Recurring droughts generated conditions conducive to large-scale outbreaks; the resulting large and sustained outbreaks significantly increased the probability of LTB forests becoming C sources over decadal time scales, with slower-than-anticipated landscape-scale recovery. Tree species composition was substantially altered with a reduction in functional redundancy and productivity. Results indicate heightened uncertainty due to the synergistic influences of climate change and interacting disturbances. Our results further indicate that current fuel management practices will not be effective at reducing landscape-scale outbreak mortality. Our results provide critical insights into the interaction of drivers (bark beetles, wildfire, fuel management) that increase the risk of C loss and shifting community composition if bark beetle outbreaks become more frequent.     

State-of-the art data normalization methods improve NMR-based metabolomic analysis

Extracting biomedical information from large metabolomic datasets by multivariate data analysis is of considerable complexity. Common challenges include among others screening for differentially produced metabolites, estimation of fold changes, and sample classification. Prior to these analysis steps, it is important to minimize contributions from unwanted biases and experimental variance. This is the goal of data preprocessing. In this work, different data normalization methods were compared systematically employing two different datasets generated by means of nuclear magnetic resonance (NMR) spectroscopy. To this end, two different types of normalization methods were used, one aiming to remove unwanted sample-to-sample variation while the other adjusts the variance of the different metabolites by variable scaling and variance stabilization methods. The impact of all methods tested on sample classification was evaluated on urinary NMR fingerprints obtained from healthy volunteers and patients suffering from autosomal polycystic kidney disease (ADPKD). Performance in terms of screening for differentially produced metabolites was investigated on a dataset following a Latin-square design, where varied amounts of 8 different metabolites were spiked into a human urine matrix while keeping the total spike-in amount constant. In addition, specific tests were conducted to systematically investigate the influence of the different preprocessing methods on the structure of the analyzed data. In conclusion, preprocessing methods originally developed for DNA microarray analysis, in particular, Quantile and Cubic-Spline Normalization, performed best in reducing bias, accurately detecting fold changes, and classifying samples.

     

A novel probe for phosphatidylinositol 4-phosphate reveals multiple pools beyond the Golgi

Polyphosphoinositides are an important class of lipid that recruit specific effector proteins to organelle membranes. One member, phosphatidylinositol 4-phosphate (PtdIns4P) has been localized to Golgi membranes based on the distribution of lipid binding modules from PtdIns4P effector proteins. However, these probes may be biased by additional interactions with other Golgi-specific determinants. In this paper, we derive a new PtdIns4P biosensor using the PtdIns4P binding of SidM (P4M) domain of the secreted effector protein SidM from the bacterial pathogen Legionella pneumophila. PtdIns4P was necessary and sufficient for localization of P4M, which revealed pools of the lipid associated not only with the Golgi but also with the plasma membrane and Rab7-positive late endosomes/lysosomes. PtdIns4P distribution was determined by the localization and activities of both its anabolic and catabolic enzymes. Therefore, P4M reports a wider cellular distribution of PtdIns4P than previous probes and therefore will be valuable for dissecting the biological functions of PtdIns4P in its assorted membrane compartments.     

Normal vision can compensate for the loss of the circadian clock

Circadian clocks are thought to be essential for timing the daily activity of animals, and consequently increase fitness. This view was recently challenged for clock-less fruit flies and mice that exhibited astonishingly normal activity rhythms under outdoor conditions. Compensatory mechanisms appear to enable even clock mutants to live a normal life in nature. Here, we show that gradual daily increases/decreases of light in the laboratory suffice to provoke normally timed sharp morning (M) and evening (E) activity peaks in clock-less flies. We also show that the compound eyes, but not Cryptochrome (CRY), mediate the precise timing of M and E peaks under natural-like conditions, as CRY-less flies do and eyeless flies do not show these sharp peaks independently of a functional clock. Nevertheless, the circadian clock appears critical for anticipating dusk, as well as for inhibiting sharp activity peaks during midnight. Clock-less flies only increase E activity after dusk and not before the beginning of dusk, and respond strongly to twilight exposure in the middle of the night. Furthermore, the circadian clock responds to natural-like light cycles, by slightly broadening Timeless (TIM) abundance in the clock neurons, and this effect is mediated by CRY.     

Quantitative Evaluation of the Environmental Impact Quotient (EIQ) for Comparing Herbicides

Various indicators of pesticide environmental risk have been proposed, and one of the most widely known and used is the environmental impact quotient (EIQ). The EIQ has been criticized by others in the past, but it continues to be used regularly in the weed science literature. The EIQ is typically considered an improvement over simply comparing the amount of herbicides applied by weight. Herbicides are treated differently compared to other pesticide groups when calculating the EIQ, and therefore, it is important to understand how different risk factors affect the EIQ for herbicides. The purpose of this work was to evaluate the suitability of the EIQ as an environmental indicator for herbicides. Simulation analysis was conducted to quantify relative sensitivity of the EIQ to changes in risk factors, and actual herbicide EIQ values were used to quantify the impact of herbicide application rate on the EIQ Field Use Rating. Herbicide use rate was highly correlated with the EIQ Field Use Rating (Spearman’s rho >0.96, P-value <0.001) for two herbicide datasets. Two important risk factors for herbicides, leaching and surface runoff potential, are included in the EIQ calculation but explain less than 1% of total variation in the EIQ. Plant surface half-life was the risk factor with the greatest relative influence on herbicide EIQ, explaining 26 to 28% of the total variation in EIQ for actual and simulated EIQ values, respectively. For herbicides, the plant surface half-life risk factor is assigned values without any supporting quantitative data, and can result in EIQ estimates that are contrary to quantitative risk estimates for some herbicides. In its current form, the EIQ is a poor measure of herbicide environmental impact.