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.     

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.

     

Galectin 9 is the sugar-regulated urate transporter/channel UAT

UAT, also designated galectin 9, is a multifunctional protein that can function as a urate channel/transporter, a regulator of thymocyte-epithelial cell interactions, a tumor antigen, an eosinophil chemotactic factor, and a mediator of apoptosis. We review the evidence that UAT is a transmembrane protein that transports urate, describe our molecular model for this protein, and discuss the evidence from epitope tag and lipid bilayer studies that support this model of the transporter. The properties of recombinant UAT are compared with those of urate transport into membrane vesicles derived from proximal tubule cells in rat kidney cortex. In addition, we review channel functions predicted by our molecular model that resulted in the novel finding that the urate channel activity is regulated by sugars and adenosine. Finally, the presence and possible functions of at least 4 isoforms of UAT and a closely related gene hUAT2 are discussed. Published in 2004.