CO, NO_<i>x</i>, PCDD/F, and Total Particulate Matter Emissions from Two Small Scale Combustion Appliances Using Agricultural Biomass Type Test Fuels

In Germany, solid biomass fuels based on agricultural byproducts are only used in marginal amounts for small scale combustion. This is the consequence of several regulatory constraints, in particular requirements defined in the first ordinance of the German emission control act (1. BImSchV) including the mandatory utilization of dedicated licensed boilers for such fuels. For the licensing, test fuels with defined fuel composition representing straw and cereal grain like fuels are demanded, and strict emission thresholds have to be met both during type testing and during periodic chimney sweep measurements. To facilitate the market introduction of the first licensed boiler, agricultural biomass test fuels with characteristics being representative for the composition of these assortments were produced and utilized for combustion tests. Emission measurements (i.e., for CO, NO_<i>x</i>, PCDD/F, and total particulate matter) were performed by an accredited institute according to the relevant methods. It was demonstrated that test fuels with dedicated fuel composition can be produced on the bench scale. The results prove that compliance with the strict emission thresholds of 1. BImSchV in Germany can be realized even with challenging fuels if an appropriate boiler is combined with an efficient dust separator. Accordingly, PCDD/F emission levels and toxicity almost as low as for wood combustion were observed

Mutation Discovery in Regions of Segmental Cancer Genome Amplifications with CoNAn-SNV: A Mixture Model for Next Generation Sequencing of Tumors

<div><p>Next generation sequencing has now enabled a cost-effective enumeration of the full mutational complement of a tumor genome—in particular single nucleotide variants (SNVs). Most current computational and statistical models for analyzing next generation sequencing data, however, do not account for cancer-specific biological properties, including somatic segmental copy number alterations (CNAs)—which require special treatment of the data. Here we present CoNAn-SNV (<u>Co</u>py <u>N</u>umber <u>An</u>notated SNV): a novel algorithm for the inference of single nucleotide variants (SNVs) that overlap copy number alterations. The method is based on modelling the notion that genomic regions of segmental duplication and amplification induce an extended genotype space where a subset of genotypes will exhibit heavily skewed allelic distributions in SNVs (and therefore render them undetectable by methods that assume diploidy). We introduce the concept of modelling allelic counts from sequencing data using a panel of Binomial mixture models where the number of mixtures for a given locus in the genome is informed by a discrete copy number state given as input. We applied CoNAn-SNV to a previously published whole genome shotgun data set obtained from a lobular breast cancer and show that it is able to discover 21 experimentally revalidated somatic non-synonymous mutations in a lobular breast cancer genome that were not detected using copy number insensitive SNV detection algorithms. Importantly, ROC analysis shows that the increased sensitivity of CoNAn-SNV does not result in disproportionate loss of specificity. This was also supported by analysis of a recently published lymphoma genome with a relatively quiescent karyotype, where CoNAn-SNV showed similar results to other callers except in regions of copy number gain where increased sensitivity was conferred. Our results indicate that in genomically unstable tumors, copy number annotation for SNV detection will be critical to fully characterize the mutational landscape of cancer genomes.</p> </div

Effect of copy number amplifications on germline alleles.

<p>These variants exhibit an amplification of the reference allele and show allelic skew, and as a result suggest an unbalanced allelic amplification over the tumor evolution.Impact refers to functional impact as determined by MutationAssessor.</p

Venn diagram of predictions made by samtools, SNVMix, CoNAn-SNV.

<p>Separating by CNA state shows an enrichment of CoNAn-SNV specific predictions in the GAIN, AMP and HLAMP segments of the genome.</p

Receiver operator characteristic curve for CoNAn-SNV and SNVMix broken down by amplification status.

<p>Receiver operator characteristic curve for CoNAn-SNV and SNVMix broken down by amplification status.</p

Discovery Flow Diagram.

<p>Discovery Flow Diagram.</p

Novel somatic variants identified by CoNAn-SNV.

<p>Somatic variants that were uniquely predicted by CoNAn-SNV and were successfully validated by targeted ultradeep amplicon sequencing.Impact refers to functional impact as determined by MutationAssessor.</p>*<p>Refers to a stop codon.</p

Differentially expressed isoforms (as predicted by LongSAGE tag positions) for the transcript (see text)

The tag sequence at position 9 results in the loss of the 3' UTR region targeted by evolutionarily conserved miRNAs. Putative miRNA target sites were predicted using miRanda [34] and are represented by hashed boxes.<p><b>Copyright information:</b></p><p>Taken from "LongSAGE profiling of nine human embryonic stem cell lines"</p><p>http://genomebiology.com/2007/8/6/R113</p><p>Genome Biology 2007;8(6):R113-R113.</p><p>Published online 14 Jun 2007</p><p>PMCID:PMC2394759.</p><p></p

Expression of selected transcripts during embryoid body differentiation

qPCR was used to monitor expression of selected transcripts in ESCs stimulated to differentiate into embryoid bodies. Three control markers, Oct4, Lin28 and Msx1, were included. Expression levels are reported as the mean of triplicate measurements and are normalized to GAPDH.<p><b>Copyright information:</b></p><p>Taken from "LongSAGE profiling of nine human embryonic stem cell lines"</p><p>http://genomebiology.com/2007/8/6/R113</p><p>Genome Biology 2007;8(6):R113-R113.</p><p>Published online 14 Jun 2007</p><p>PMCID:PMC2394759.</p><p></p