Cysteine residues on proteins have a high affinity for metals yet formulations used to determine bioaccessibility do not contain cysteine or thiol-containing molecules. As a result, we used a cysteine-simplified physiological-based extraction technique (SBET) and, the conventional glycine-SBET to determine bioaccesibility of selected heavy metals in biosolids and compared the data. We also determined speciation of the selected metals in the biosolids to assess further the health risk posed the use of biosolids as a soil amendment in agricultural soils. Samples, including a certified reference standard were analyzed using x-ray fluorescence and flame atomic absorption. Bioaccessibility was higher in cysteine-SBET than glycine-SBET, and regression data show that the two methods give different sets of results. We proposed a bioaccessibility model that involves cysteine and the hydrogen ion complementing each other to dissolve metals. The model also includes a three mode-bioavailability mechanism: absorption of free metal ions; ligand-mediated transport of metal ions from solution; and ligand-mediated transport of metal ions directly from the biosolids into the cell. Low pH in the gut increases bioaccessibility but reduces bioavailability due to protonation of receptor ligands. With the exception of Fe, bioaccessibility was directly correlated to the sequential extraction availability which followed the order: Mn(90.3 %)>Zn(50.3 %)>Cd(26.5 %)>Cu(24.9 %)>Fe(0.367 %). We calculated bioavailability from bioaccessibility using literature estimates of percent bioavailabilities. The order of abundance of the analyzed metals in the biosolids was as follows: Fe>Mn>Zn>Cu>Pb>Cd.

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Bei intravenöser Infusion von 0,8 g Alkohol/kg Körpergewicht in Form einer 33proz. (w/w) Lösung innerhalb von 5 oder von 14,3 Minuten wurde die Blutalkoholkonzentration im Blut der V. renalis, der V. jugularis int., in Extremitätenvenen und im arteriellen Blut bestimmt. Während der Anflutungsphase sind die Konzentrationen in dem aus Nieren und Gehirn abströmenden Blut höher als in den Extremitätenvenen. Die arterio-venösen Konzentrationsdifferenzen der Nieren und des Gehirns sind kleiner als die der Extremitäten. Die Bedeutung dieser Befunde für das Verhältnis Harnalkoholkonzentration/Blutalkoholkonzentration, für renale Clearanceuntersuchungen und weiterhin für das Verständnis der stärkeren psychophysischen Beeinflussung während der Aikoholanflutungsphase sowie für die Beurteilung von Injektionszwischenfällen wird diskutiert. Arterio-venous concentration differences in kidney and brain vessels during intravenous infusion (Studies on the distribution of ethyl alcohol in the organism)The alcohol concentration was measured in blood from the renal vein, the jugular vein, in veins of the extremities, and in arterial blood, following the intravenous infusion of 0.8 g of alcohol per kg body weight in the form of a 33% (w/w) solution. During the influx phase, the concentration of alcohol in the blood leaving the kidneys and brain was higher than in the extremities. The arterio-venous concentration differences in kidney and brain are smaller than those in the extremities. The significance of these findings for the ratio, urinary alcohol concentration/blood alcohol concentration, for renal clearance studies, for understanding the psychophysical effect during the influx phase and the evaluation of untoward injection reactions are discussed.

Large-scale cancer profiling using next generation sequencing (NGS) has become instrumental to the discovery and identification of new, targetable cancer alterations. A comprehensive set of 532 oncogene targets were combined to create the new xGen® Pan-Cancer Panel V2 for hybrid capture sequencing. This xGen panel covers 2.2 Mb of the human genome, and allows for the simultaneous detection of copy number variations (CNVs), insertions and deletions (indels), gene rearrangements, and microsatellite instability across a wide range of sample types, inputs, and quality. Using a new library prep workflow optimized for low quality samples and low input, panel performance was first evaluated with 30 ng of input DNA using libraries built from matched samples [formalin-fixed paraffin-embedded (FFPE) tumor gDNA, frozen adjacent normal tissue gDNA, and cell-free DNA (cfDNA)] from five lung cancer donors (n = 15). Sample quality ranged from a mean DIN of 4.4 ±1.1 to 8.3 ±0.9 for FFPE tumor gDNA and frozen normal gDNA, respectively. After subsampling to 200X mean target coverage, 96% of target bases had at least 40X coverage for all libraries. Comparative hierarchal clustering analysis was then used to identify lung cancer mutations shared in all tumor samples. NGS gDNA reference standards from Horizon Discovery (HD753, HD798, HD799, and HD803) with verified CNVs, single nucleotide variations (SNVs), amplifications, and fusions, and were used to evaluate detection rates at different library input masses down to 1 ng. cDNA libraries were also prepared from RNA extracted from FFPE 5-Fusion RNA Multiplex Reference Standards (HD796, HD783). We identified all possible gene fusion events in the positive control using the structural variant caller, LUMPY (https://github.com/arq5x/lumpy-sv). The xGen Pan-Cancer Panel V2 enables a cost-efficient and time-saving approach for the detection of multiple oncogene targets. Citation Format: Katharine Dilger, Yongming Sun, Kevin Lai, Ushati Das Chakravarty, Nicole Sponer, Kristina Giorda, Patrick Lau, Yu Wang. DNA-based fusion detection using a pan-cancer tumor profiling 532-oncogene panel [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 4348.

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