28 research outputs found

    Evaluating Forecasting Methods

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    Ideally, forecasting methods should be evaluated in the situations for which they will be used. Underlying the evaluation procedure is the need to test methods against reasonable alternatives. Evaluation consists of four steps: testing assumptions, testing data and methods, replicating outputs, and assessing outputs. Most principles for testing forecasting methods are based on commonly accepted methodological procedures, such as to prespecify criteria or to obtain a large sample of forecast errors. However, forecasters often violate such principles, even in academic studies. Some principles might be surprising, such as do not use R-square, do not use Mean Square Error, and do not use the within-sample fit of the model to select the most accurate time-series model. A checklist of 32 principles is provided to help in systematically evaluating forecasting methods

    Low-Dose Methotrexate Inhibits Methionine S-Adenosyltransferase In Vitro and In Vivo

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    Methionine S-adenosyltransferase (MAT) catalyzes the only reaction that produces the major methyl donor in mammals. Low-dose methotrexate is the most commonly used disease-modifying antirheumatic drug in human rheumatic conditions. The present study was conducted to test the hypothesis that methotrexate inhibits MAT expression and activity in vitro and in vivo. HepG2 cells were cultured under folate restriction or in low-dose methotrexate with and without folate or methionine supplementation. Male C57BL/6J mice received methotrexate regimens that reflected low-dose clinical use in humans. S-adenosylmethionine and MAT genes, proteins and enzyme activity levels were determined. We found that methionine or folate supplementation greatly improved S-adenosylmethionine in folate-depleted cells but not in cells preexposed to methotrexate. Methotrexate but not folate depletion suppressed MAT genes, proteins and activity in vitro. Low-dose methotrexate inhibited MAT1A and MAT2A genes, MATI/II/III proteins and MAT enzyme activities in mouse tissues. Concurrent folinate supplementation with methotrexate ameliorated MAT2A reduction and restored S-adenosylmethionine in HepG2 cells. However, posttreatment folinate rescue failed to restore MAT2A reduction or S-adenosylmethionine level in cells preexposed to methotrexate. Our results provide both in vitro and in vivo evidence that low-dose methotrexate inhibits MAT genes, proteins, and enzyme activity independent of folate depletion. Because polyglutamated methotrexate stays in the hepatocytes, if methotrexate inhibits MAT in the liver, then the efficacy of clinical folinate rescue with respect to maintaining hepatic S-adenosylmethionine synthesis and normalizing the methylation reactions would be limited. These findings raise concerns on perturbed methylation reactions in humans on low-dose methotrexate. Future studies on the clinical physiological consequences of MAT inhibition by methotrexate and the potential benefits of S-adenosylmethionine supplementation on methyl group homeostasis in clinical methotrexate therapies are warranted

    Modeling and Design of Distributed Information Systems

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    Protection of Aldehydes and Ketones

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