Effect of Juvenile Wood and Choice of Parametric Property Distributions on Reliability-Based Beam Design

A comparison is made of the effect of choice of the SB distribution, Weibull distribution, or log-normal distribution on reliability-based design of a 2 x 4 southern pine beam, No. 2 grade. The SB distribution provided most flexibility in describing the lumber properties.The presence of juvenile wood in lumber may affect the distributional characterization of lumber properties and in turn affect reliability-based design results. This study shows that juvenile wood had a significant effect on the reliability-based design results when stiffness was the limiting state. Unless juvenile wood lumber is separated from mature wood lumber in the grading process, a considerable loss in efficiency in utilizing lumber from fast-grown trees will occur where stiffness is critical

A Numerical Model for Heat Transfer and Moisture Evaporation Processes in Hot-Press Drying—An Integral Approach

A numerical model, which was based on the energy principle that the rate of water evaporation from the interface (or wet line) at a given time during hot-press drying was controlled by the rate of heat energy reaching the interface at that time, has been developed. The model treated the drying as a process in which the retreat of the interface and free water flow to the interface occur simultaneously. After all parameters were determined according to the available literature and experiments, the numerical model worked well in predicting the drying curves from process and material variables. The model, which has a sound theoretical base but is numerically simple, has a good potential to be expanded for general high temperature drying and to be adopted in a production line to presort the lumber for good drying practice

Ovarian Carcinoma‐Associated Mesenchymal Stem Cells Arise from Tissue‐Specific Normal Stroma

Carcinoma‐associated mesenchymal stem cells (CA‐MSCs) are critical stromal progenitor cells within the tumor microenvironment (TME). We previously demonstrated that CA‐MSCs differentially express bone morphogenetic protein family members, promote tumor cell growth, increase cancer “stemness,” and chemotherapy resistance. Here, we use RNA sequencing of normal omental MSCs and ovarian CA‐MSCs to demonstrate global changes in CA‐MSC gene expression. Using these expression profiles, we create a unique predictive algorithm to classify CA‐MSCs. Our classifier accurately distinguishes normal omental, ovary, and bone marrow MSCs from ovarian cancer CA‐MSCs. Suggesting broad applicability, the model correctly classifies pancreatic and endometrial cancer CA‐MSCs and distinguishes cancer associated fibroblasts from CA‐MSCs. Using this classifier, we definitively demonstrate ovarian CA‐MSCs arise from tumor mediated reprograming of local tissue MSCs. Although cancer cells alone cannot induce a CA‐MSC phenotype, the in vivo ovarian TME can reprogram omental or ovary MSCs to protumorigenic CA‐MSCs (classifier score of >0.96). In vitro studies suggest that both tumor secreted factors and hypoxia are critical to induce the CA‐MSC phenotype. Interestingly, although the breast cancer TME can reprogram bone marrow MSCs into CA‐MSCs, the ovarian TME cannot, demonstrating for the first time that tumor mediated CA‐MSC conversion is tissue and cancer type dependent. Together these findings (a) provide a critical tool to define CA‐MSCs and (b) highlight cancer cell influence on distinct normal tissues providing powerful insights into the mechanisms underlying cancer specific metastatic niche formation. Stem Cells 2019;37:257–269Ovarian cancer reprograms normal tissue derived mesenchymal stem cells (MSCs) into ovarian cancer promoting carcinoma‐associated mesenchymal stem cells (CA‐MSCs) in a tissue specific manner. Ovarian cancer cells convert ovary and omental MSCs into CA‐MSCs but fail to reprogram bone marrow (BM)‐MSCs whereas breast cancer cells convert BM‐MSCs into breast cancer supporting CA‐MSCs.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/147827/1/stem2932_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/147827/2/stem2932.pd

The emergence of modern statistics in agricultural science : Analysis of variance, experimental design and the reshaping of research at Rothamsted Experimental Station, 1919–1933

During the twentieth century statistical methods have transformed research in the experimental and social sciences. Qualitative evidence has largely been replaced by quantitative results and the tools of statistical inference have helped foster a new ideal of objectivity in scientific knowledge. The paper will investigate this transformation by considering the genesis of analysis of variance and experimental design, statistical methods nowadays taught in every elementary course of statistics for the experimental and social sciences. These methods were developed by the mathematician and geneticist R. A. Fisher during the 1920s, while he was working at Rothamsted Experimental Station, where agricultural research was in turn reshaped by Fisher’s methods. Analysis of variance and experimental design required new practices and instruments in field and laboratory research, and imposed a redistribution of expertise among statisticians, experimental scientists and the farm staff. On the other hand the use of statistical methods in agricultural science called for a systematization of information management and made computing an activity integral to the experimental research done at Rothamsted, permanently integrating the statisticians’ tools and expertise into the station research programme. Fisher’s statistical methods did not remain confined within agricultural research and by the end of the 1950s they had come to stay in psychology, sociology, education, chemistry, medicine, engineering, economics, quality control, just to mention a few of the disciplines which adopted them

Genome analysis of the necrotrophic fungal pathogens Sclerotinia sclerotiorum and Botrytis cinerea

Sclerotinia sclerotiorum and Botrytis cinerea are closely related necrotrophic plant pathogenic fungi notable for their wide host ranges and environmental persistence. These attributes have made these species models for understanding the complexity of necrotrophic, broad host-range pathogenicity. Despite their similarities, the two species differ in mating behaviour and the ability to produce asexual spores. We have sequenced the genomes of one strain of S. sclerotiorum and two strains of B. cinerea. The comparative analysis of these genomes relative to one another and to other sequenced fungal genomes is provided here. Their 38–39 Mb genomes include 11,860–14,270 predicted genes, which share 83% amino acid identity on average between the two species. We have mapped the S. sclerotiorum assembly to 16 chromosomes and found large-scale co-linearity with the B. cinerea genomes. Seven percent of the S. sclerotiorum genome comprises transposable elements compared t

Pervasive and Persistent Redundancy among Duplicated Genes in Yeast

The loss of functional redundancy is the key process in the evolution of duplicated genes. Here we systematically assess the extent of functional redundancy among a large set of duplicated genes in Saccharomyces cerevisiae. We quantify growth rate in rich medium for a large number of S. cerevisiae strains that carry single and double deletions of duplicated and singleton genes. We demonstrate that duplicated genes can maintain substantial redundancy for extensive periods of time following duplication (∼100 million years). We find high levels of redundancy among genes duplicated both via the whole genome duplication and via smaller scale duplications. Further, we see no evidence that two duplicated genes together contribute to fitness in rich medium substantially beyond that of their ancestral progenitor gene. We argue that duplicate genes do not often evolve to behave like singleton genes even after very long periods of time

ATBF1 and NQO1 as candidate targets for allelic loss at chromosome arm 16q in breast cancer: Absence of somatic ATBF1 mutations and no role for the C609T NQO1 polymorphism

<p>Abstract</p> <p>Background</p> <p>Loss of heterozygosity (LOH) at chromosome arm 16q is frequently observed in human breast cancer, suggesting that one or more target tumor suppressor genes (TSGs) are located there. However, detailed mapping of the smallest region of LOH has not yet resulted in the identification of a TSG at 16q. Therefore, the present study attempted to identify TSGs using an approach based on mRNA expression.</p> <p>Methods</p> <p>A cDNA microarray for the 16q region was constructed and analyzed using RNA samples from 39 breast tumors with known LOH status at 16q.</p> <p>Results</p> <p>Five genes were identified to show lower expression in tumors with LOH at 16q compared to tumors without LOH. The genes for NAD(P)H dehydrogenase quinone (<it>NQO1</it>) and AT-binding transcription factor 1 (<it>ATBF1</it>) were further investigated given their functions as potential TSGs. <it>NQO1 </it>has been implicated in carcinogenesis due to its role in quinone detoxification and in stabilization of p53. One inactive polymorphic variant of <it>NQO1 </it>encodes a product showing reduced enzymatic activity. However, we did not find preferential targeting of the active <it>NQO1 </it>allele in tumors with LOH at 16q. Immunohistochemical analysis of 354 invasive breast tumors revealed that NQO1 protein expression in a subset of breast tumors is higher than in normal epithelium, which contradicts its proposed role as a tumor suppressor gene.</p> <p><it>ATBF1 </it>has been suggested as a target for LOH at 16q in prostate cancer. We analyzed the entire coding sequence in 48 breast tumors, but did not identify somatic sequence changes. We did find several in-frame insertions and deletions, two variants of which were reported to be somatic pathogenic mutations in prostate cancer. Here, we show that these variants are also present in the germline in 2.5% of 550 breast cancer patients and 2.9% of 175 healthy controls. This indicates that the frequency of these variants is not increased in breast cancer patients. Moreover, there is no preferential LOH of the wildtype allele in breast tumors.</p> <p>Conclusion</p> <p>Two likely candidate TSGs at 16q in breast cancer, <it>NQO1 </it>and <it>ATBF1</it>, were identified here as showing reduced expression in tumors with 16q LOH, but further analysis indicated that they are not target genes of LOH. Furthermore, our results call into question the validity of the previously reported pathogenic variants of the <it>ATBF1 </it>gene.</p

Epistatic Module Detection for Case-Control Studies: A Bayesian Model with a Gibbs Sampling Strategy

The detection of epistatic interactive effects of multiple genetic variants on the susceptibility of human complex diseases is a great challenge in genome-wide association studies (GWAS). Although methods have been proposed to identify such interactions, the lack of an explicit definition of epistatic effects, together with computational difficulties, makes the development of new methods indispensable. In this paper, we introduce epistatic modules to describe epistatic interactive effects of multiple loci on diseases. On the basis of this notion, we put forward a Bayesian marker partition model to explain observed case-control data, and we develop a Gibbs sampling strategy to facilitate the detection of epistatic modules. Comparisons of the proposed approach with three existing methods on seven simulated disease models demonstrate the superior performance of our approach. When applied to a genome-wide case-control data set for Age-related Macular Degeneration (AMD), the proposed approach successfully identifies two known susceptible loci and suggests that a combination of two other loci—one in the gene SGCD and the other in SCAPER—is associated with the disease. Further functional analysis supports the speculation that the interaction of these two genetic variants may be responsible for the susceptibility of AMD. When applied to a genome-wide case-control data set for Parkinson's disease, the proposed method identifies seven suspicious loci that may contribute independently to the disease