Oscillaria caldariorum mihi n. sp. eine Plage des Warmhauses

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CRISPR-Mediated Induction of Neuron-Enriched Mitochondrial Proteins Boosts Direct Glia-to-Neuron Conversion

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Feasibility of using gene expression analysis to study canine soft tissue sarcomas

The prognosis given for canine soft tissue sarcomas (STSs) is based primarily on histopathologic grade. The decision to administer adjuvant chemotherapy is difficult since less than half of patients with high-grade STSs develop metastatic disease. We hypothesize that there is a gene signature that will improve our ability to predict development of metastatic disease in STS patients. The objective of this study was to determine the feasibility of using cDNA microarray and quantitative real-time PCR (qRT-PCR) analysis to determine gene expression patterns in metastatic versus nonmetastatic canine STSs, given the inherent heterogeneity of this group of tumors. Five STSs from dogs with metastatic disease were evaluated in comparison to eight STSs from dogs without metastasis. Tumor RNA was extracted, processed, and labeled for application to the Affymetrix Canine Genechip 2.0 Array. Array fluorescence was normalized using D-Chip software and data analysis was performed with JMP/Genomics. Differential gene expression was validated using qRT-PCR. Over 200 genes were differentially expressed at a false discovery rate of 5%. Differential gene expression was validated for five genes upregulated in metastatic tumors. Quantitative RT-PCR confirmed increased relative expression of all five genes of interest in the metastatic STSs. Our results demonstrate that microarray and qRT-PCR are feasible methods for comparing gene signatures in canine STSs. Further evaluation of the differences between gene expression in metastatic STSs and in nonmetastatic STSs is likely to identify genes that are important in the development of metastatic disease and improve our ability to prognosticate for individual patients.     

Beiträge zur Kenntniss der adriatischen Algen

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Verzeichniss der im Golfe von Triest gesammelten Meeralgen

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Beiträge zur Kenntniss der adriatischen Algen

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Choice of Scale and Asymmetric Logistic Models

In recent years, a number of authors have proposed generalizations to the binomial logistic model. These proposals were motivated, in part, by the claimed inability of the logistic model to fit asymmetric data, that is, data that does not follow a symmetric S-shaped curve. In this note, it is demonstrated that by changing the scale of the independent variable(s), the logistic model can fit asymmetric data. Logistic models are fit to data from BLISS (1935) that had been used as an example by three of the authors; the logistic models fit Bliss' data as well as the proposed alternative models. In a general sense, these data serve as an example of the need to consider the appropriate choice of scale of the independent variables in logistic analysis.     

Purification and characterization of the elastase-like enzyme of the bovine granulocyte

The extracts of granules isolated from bovine granulocytes show elastase- and chymotrypsin-like activities, as detected with specific synthetic substrates. Extraction of these enzymes depends upon salt concentration. In the course of the present studies a 21-fold purification of the elastase-like enzyme was achieved on a (Ala)3-CH-Sepharose 4B gel. The molecular weight of the enzyme is 33 000, as determined by gel electrophoresis in the presence of sodium dodecyl sulfate. The elastase-like activity is inhibited by phenylmethylsulfonyl fluoride, soybean trypsin inhibitor, basic pancreatic inhibitor and by heparin at different rates. Elastatinal inhibits the enzyme competitively (Ki = 80 microM). The cytosol of bovine granulocytes contains a protein which strongly inhibits the elastase-like enzyme of the bovine granulocyte (Ki = 0.4 nM) as well as porcine pancreatic elastase (Ki = 11 nM).