DAIRY GRAZING FINANCES IN MICHIGAN AND WISCONSIN, 1999

The purpose of this paper is to demonstrate possible outcomes and problems of merging farm data sets from multiple states in order to build a statistically sound body of financial information that will help individual farmers analyze their own situations. This paper is in support of a grant titled "Regional/Multi-State Interpretation of Small Farm Financial Data" recently funded by USDA - IFAFS - Farm Efficiency and Profitability. Financial data sets came from dairy farms using management intensive grazing (MIG) strategies during 1999. There were 12 farms from Michigan and 19 farms from Wisconsin. Finpack and Finansum were used to process the data from all farms. Definitions and formulas are not given in this paper as they can be found in Finpack users' guides and manuals. The averages for all 31 farms are given in Tables 1 through 10 plus Figures 1 and 2. The averages for farms with less than 70 milk cows are given in Tables 11 through 20. Averages for farms with over 70 cows are in Tables 21 through 30. Towards the end of the paper is a discussion of the strengths and weaknesses of the data set and what should be considered as more states' data are merged into the grant project. The last page, Table 32, gives some income and expense categories on a per cow basis which may be useful in doing an individual farm comparative analysis.Agricultural Finance, Livestock Production/Industries,

DAIRY GRAZING FINANCES IN MICHIGAN AND WISCONSIN, 1999

The purpose of this paper is to demonstrate possible outcomes and problems of merging farm data sets from multiple states in order to build a statistically sound body of financial information that will help individual farmers analyze their own situations. This paper is in support of a grant titled "Regional/Multi-State Interpretation of Small Farm Financial Data" recently funded by USDA - IFAFS - Farm Efficiency and Profitability. Financial data sets came from dairy farms using management intensive grazing (MIG) strategies during 1999. There were 12 farms from Michigan and 19 farms from Wisconsin. Finpack and Finansum were used to process the data from all farms. Definitions and formulas are not given in this paper as they can be found in Finpack users' guides and manuals. The averages for all 31 farms are given in Tables 1 through 10 plus Figures 1 and 2. The averages for farms with less than 70 milk cows are given in Tables 11 through 20. Averages for farms with over 70 cows are in Tables 21 through 30. Towards the end of the paper is a discussion of the strengths and weaknesses of the data set and what should be considered as more states' data are merged into the grant project. The last page, Table 32, gives some income and expense categories on a per cow basis which may be useful in doing an individual farm comparative analysis

Cytosolic and nuclear caspase-8 have opposite impact on survival after liver resection for hepatocellular carcinoma

BACKGROUND: An imbalance between proliferation and apoptosis is one of the main features of carcinogenesis. TRAIL (TNF-related apoptosis-inducing ligand) induces apoptosis upon binding to the TRAIL death receptors, TRAIL receptor 1 (TRAIL-R1) and TRAIL-R2, whereas binding to TRAIL-R3 and TRAIL-R4 might promote cell survival and proliferation. The anti-tumor activity of TRAIL-R1 and TRAIL-R2 agonists is currently investigated in clinical trials. To gain further insight into the regulation of apoptosis in hepatocellular carcinoma (HCC), we investigated the TRAIL pathway and the regulators of apoptosis caspase-8, Bcl-xL and Mcl-1 in patients with HCC regarding patient survival. METHODS: We analyzed 157 hepatocellular carcinoma patients who underwent partial liver resection or orthotopic liver transplantation and healthy control liver tissue using immunohistochemistry on tissue microarrays for the expression of TRAIL-R1 to TRAIL-R4, caspase-8, Bcl-xL and Mcl-1. Immunohistochemical data were evaluated for potential associations with clinico-pathological parameters and survival. RESULTS: Whereas TRAIL-R1 was downregulated in HCC in comparison to normal liver tissue, TRAIL-R2 and –R4 were upregulated in HCC, especially in G2 and G3 tumors. TRAIL-R1 downregulation and upregulation of TRAIL-R2 and TRAIL-R4 correlated with tumor dedifferentiation (G2/G3). TRAIL-R3, Bcl-xL and Mcl-1 showed no differential expression in tumor tissue compared to normal tissue. The expression levels of TRAIL receptors did not correlate with patient survival after partial hepatectomy. Interestingly, in tumor tissue, but not in normal hepatocytes, caspase-8 showed a strong nuclear staining. Low cytosolic and high nuclear staining intensity of caspase-8 significantly correlated with impaired survival after partial hepatectomy, which, for cytosolic caspase-8, was independent from tumor grade. CONCLUSIONS: Assessment of TRAIL-receptor expression patterns may have therapeutic implications for the use of TRAIL receptor agonists in HCC therapy. Tumor-specific nuclear localisation of caspase-8 in HCC suggests an apoptosis-independent function of caspase-8 and correlates with patient survival