13 research outputs found

    An Autothermal, Representative Scale Test Of Compost Heat Potential Using Geostatistical Analysis

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    Composting has been practiced for thousands of years as a way of stabilizing and recycling organic matter into useful soil amendments. Thermophilic compost releases significant amounts of heat at temperatures (~140 °F) that are useful for environmental heating or process water. This heat has been taken advantage of in various ways throughout history, but development of a widely adopted technology remains elusive. The biggest barrier to adoption of compost heat recovery (CHR) systems is projecting accurate, attractive economic returns. The cost of transfer equipment is significant, and with variability in composting substrates and methods, it is difficult to predict the power and quality of heat a proposed system would produce. While the ultimate heat release may be calculated with standard techniques, the dynamics of compost temperature and thermal power are less understood. As heat yield is one of many goals, better understanding of compost’s thermal dynamics is important for CHR optimization. This research addresses the issue by developing a field test that measures heat release and temperature across a representative-scale compost volume. The compost test vessel was built from common construction materials and insulated enough to be self-heating in cold weather. A 4’ x 4’ x 4’ cube of 2” foam insulation panels held 1.812 cubic yards of active compost, intermittently aerated at ~35 CFM. Data from 84 temperature sensors, and one pressure sensor at the blower, was logged at 1-minute intervals for a period of 35 days. Spatial temperature fields were estimated by Kriging, and used to calculate conductive heat loss and compost volume temperature over time. Enthalpy loss was calculated using the blower pressure curve, temperature data and humidity assumptions. The compost exhibited wide variation in temperature and heat flow over time, and less horizontal symmetry than expected. The results are dynamic and best viewed graphically. Enthalpy loss varied with adjustments to the aeration cycle, ranging from 100 to 550 W (60-minute average rates), while conductive losses were in the range of 75 W. Peak sustained thermal output was around 600 W (500 W by aeration) from days 11-13 with about 0.6 yd3 of compost in the thermophilic zone; however, this cooled the compost significantly. Aeration was then reduced, and the compost temperature recovered, with 50% - 90% of the compost volume above 130 °F from days 14-23; during this period, total heat loss was around 150 - 200 W with aeration loss around 60-100 W. The test was successful in producing hot compost and building temperature field and heat loss models. However representative aeration rates cooled a large amount of the compost volume as cool air was drawn into the vessel. Aeration rate reduction accomplished desired compost temperatures, but resulted in low enthalpy extraction rate and temperature. Future work will address this issue with the ability to recirculate air through the compost

    Retrospective evaluation of whole exome and genome mutation calls in 746 cancer samples

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    Funder: NCI U24CA211006Abstract: The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) curated consensus somatic mutation calls using whole exome sequencing (WES) and whole genome sequencing (WGS), respectively. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2,658 cancers across 38 tumour types, we compare WES and WGS side-by-side from 746 TCGA samples, finding that ~80% of mutations overlap in covered exonic regions. We estimate that low variant allele fraction (VAF < 15%) and clonal heterogeneity contribute up to 68% of private WGS mutations and 71% of private WES mutations. We observe that ~30% of private WGS mutations trace to mutations identified by a single variant caller in WES consensus efforts. WGS captures both ~50% more variation in exonic regions and un-observed mutations in loci with variable GC-content. Together, our analysis highlights technological divergences between two reproducible somatic variant detection efforts

    Sex differences in oncogenic mutational processes

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    Sex differences have been observed in multiple facets of cancer epidemiology, treatment and biology, and in most cancers outside the sex organs. Efforts to link these clinical differences to specific molecular features have focused on somatic mutations within the coding regions of the genome. Here we report a pan-cancer analysis of sex differences in whole genomes of 1983 tumours of 28 subtypes as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium. We both confirm the results of exome studies, and also uncover previously undescribed sex differences. These include sex-biases in coding and non-coding cancer drivers, mutation prevalence and strikingly, in mutational signatures related to underlying mutational processes. These results underline the pervasiveness of molecular sex differences and strengthen the call for increased consideration of sex in molecular cancer research.Sex differences have been observed in multiple facets of cancer epidemiology, treatment and biology, and in most cancers outside the sex organs. Efforts to link these clinical differences to specific molecular features have focused on somatic mutations within the coding regions of the genome. Here we report a pan-cancer analysis of sex differences in whole genomes of 1983 tumours of 28 subtypes as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium. We both confirm the results of exome studies, and also uncover previously undescribed sex differences. These include sex-biases in coding and non-coding cancer drivers, mutation prevalence and strikingly, in mutational signatures related to underlying mutational processes. These results underline the pervasiveness of molecular sex differences and strengthen the call for increased consideration of sex in molecular cancer research.Peer reviewe

    Retrospective evaluation of whole exome and genome mutation calls in 746 cancer samples

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    The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) curated consensus somatic mutation calls using whole exome sequencing (WES) and whole genome sequencing (WGS), respectively. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2,658 cancers across 38 tumour types, we compare WES and WGS side-by-side from 746 TCGA samples, finding that ~80% of mutations overlap in covered exonic regions. We estimate that low variant allele fraction (VAF < 15%) and clonal heterogeneity contribute up to 68% of private WGS mutations and 71% of private WES mutations. We observe that ~30% of private WGS mutations trace to mutations identified by a single variant caller in WES consensus efforts. WGS captures both ~50% more variation in exonic regions and un-observed mutations in loci with variable GC-content. Together, our analysis highlights technological divergences between two reproducible somatic variant detection efforts.The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) curated consensus somatic mutation calls using whole exome sequencing (WES) and whole genome sequencing (WGS), respectively. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2,658 cancers across 38 tumour types, we compare WES and WGS side-by-side from 746 TCGA samples, finding that -80% of mutations overlap in covered exonic regions. We estimate that low variant allele fraction (VAFPeer reviewe

    Pan-cancer analysis of whole genomes

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    Author Correction: The landscape of viral associations in human cancers

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    Integrative pathway enrichment analysis of multivariate omics data

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    Multi-omics datasets represent distinct aspects of the central dogma of molecular biology. Such high-dimensional molecular profiles pose challenges to data interpretation and hypothesis generation. ActivePathways is an integrative method that discovers significantly enriched pathways across multiple datasets using statistical data fusion, rationalizes contributing evidence and highlights associated genes. As part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2658 cancers across 38 tumor types, we integrated genes with coding and non-coding mutations and revealed frequently mutated pathways and additional cancer genes with infrequent mutations. We also analyzed prognostic molecular pathways by integrating genomic and transcriptomic features of 1780 breast cancers and highlighted associations with immune response and anti-apoptotic signaling. Integration of ChIP-seq and RNA-seq data for master regulators of the Hippo pathway across normal human tissues identified processes of tissue regeneration and stem cell regulation. ActivePathways is a versatile method that improves systems-level understanding of cellular organization in health and disease through integration of multiple molecular datasets and pathway annotations
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