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.     

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.     

Genome-wide CRISPR Screens Reveal Host Factors Critical for SARS-CoV-2 Infection

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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.     

Environmentally constrained mutation and adaptive evolution in Salmonella

The relationship between environment and mutation is complex [1]. Claims of Lamarkian mutation [2] have proved unfounded [3], [4] and [5]; it is apparent, however, that the external environment can influence the generation of heritable variation, through either direct effects on DNA sequence [6] or DNA maintenance and copying mechanisms [7], [8], [9] and [10], or as a consequence of evolutionary processes [11], [12], [13], [14], [15] and [16]. The spectrum of mutational events subject to environmental influence is unknown [6] and precisely how environmental signals modulate mutation is unclear. Evidence from bacteria suggests that a transient recombination-dependent hypermutational state can be induced by starvation [5]. It is also apparent that chnages in the mutability of specific loci can be influenced by alterations in DNA topology [10] and [17]. Here we describe a remarkable instance of adaptive evolution in Salmonella which is caused by a mutation that occurs in intermediate-strength osmotic environments. We show that the mutation is not ‘directed’ and describe its genetic basis. We also present compelling evidence in support of the hypothesis that the mutational event is constrained by signals transmitted from the external environment via changes in the activity of DNA gyrase.     

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.