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Objective To reduce the cancer burden in the Jinchang cohort and provide evidence for developing cancer prevention strategies and performing effectiveness evaluation in the Jinchang cohort.We are fitting thirteen years of cancer mortality data from the Jinchang cohort by using six kinds of predicting methods to compare relative fitness and to select good predicting methods for the prediction of cancer mortality trends.Methods The mortality data of cancer in Jinchnag cohort from 2001-2013 were fitted using six kinds of predicting methods:dynamic series,linear regression,exponential smoothing,autoregressive integrated moving average (ARIMA) model,grey model (GM),and Joinpoint regression.Weight coefficients of combination models were calculated by four methods:the arithmetic average method,the variance inverse method,the mean square error inverse method,and the simple weighted average method.Results The cancer mortality was fitted and compared by using six kinds of forecasting methods;the fitting precision of the Joinpoint linear regression had the highest accuracy (87.64％),followed by linear regression (87.32％),the dynamic series (86.99％),GM (1,1) (86.25％),exponential smoothing (85.72％) and ARIMA (1,0,0) (81.98％),respectively.Prediction accuracy of the combination model derived from GM (1,1) and linear regression (＞99％) was higher than that of the combination model derived from ARIMA (1,0,0) and GM (1,1).The combination model derived from the GM (1,1) and linear regression,with weight coefficients based on the arithmetic average method and the mean square error inverse method,had the best prediction effect of the four weight calculation methods.Conclusion Prediction accuracy of the combination model,with accuracy ＞95％,was higher than that of the single prediction methods.
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Objective To reduce the cancer burden in the Jinchang cohort and provide evidence for developing cancer prevention strategies and performing effectiveness evaluation in the Jinchang cohort.We are fitting thirteen years of cancer mortality data from the Jinchang cohort by using six kinds of predicting methods to compare relative fitness and to select good predicting methods for the prediction of cancer mortality trends.Methods The mortality data of cancer in Jinchnag cohort from 2001-2013 were fitted using six kinds of predicting methods:dynamic series,linear regression,exponential smoothing,autoregressive integrated moving average (ARIMA) model,grey model (GM),and Joinpoint regression.Weight coefficients of combination models were calculated by four methods:the arithmetic average method,the variance inverse method,the mean square error inverse method,and the simple weighted average method.Results The cancer mortality was fitted and compared by using six kinds of forecasting methods;the fitting precision of the Joinpoint linear regression had the highest accuracy (87.64％),followed by linear regression (87.32％),the dynamic series (86.99％),GM (1,1) (86.25％),exponential smoothing (85.72％) and ARIMA (1,0,0) (81.98％),respectively.Prediction accuracy of the combination model derived from GM (1,1) and linear regression (＞99％) was higher than that of the combination model derived from ARIMA (1,0,0) and GM (1,1).The combination model derived from the GM (1,1) and linear regression,with weight coefficients based on the arithmetic average method and the mean square error inverse method,had the best prediction effect of the four weight calculation methods.Conclusion Prediction accuracy of the combination model,with accuracy ＞95％,was higher than that of the single prediction methods.
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Objective To study the inactivation kinetics and injury mechanism of Escherichia coli under UV disinfection in drinking water.Methods The inactivation kinetics of E.coli ATCC 25922 was determined by plate count methods in the UV disinfection experiment.The morphology,cell membrane permeabilization and injury of biological macromolecules were observed under a transmission electron microscope (TEM).The rate of ONPG hydrolysis and changes in activities of antioxidant enzymes were observed Raman spectroscopy.Results the changes of damaged cells involved morphological damage such as loss of the structural integrity of the wall and membrane,condensation of cellular material and leakage of significant amounts of cytoplasmic material,a more than four-fold increase of cell membrane permeabilization and damage to the structure of protein,nucleic acids and phospholipid.Conclusion UV disinfection can lead to a multi-target damage.
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<p><b>OBJECTIVE</b>To understand the disease burden caused by cancers in Jinchang cohort, and develop effective strategies for cancer prevention and control in this population.</p><p><b>METHODS</b>The cancer mortality data from 2001 to 2013 and the medical records for cancer patients from 2001 to 2010 in Jinchang cohort were collected. The disease burden caused by cancer was analyzed by using mortality rate, potential years of life lost (PYLL), working PYLL (WPYLL), and direct economic burden.</p><p><b>RESULTS</b>During 2001-2013, in Jinchang cohort, the five leading cancers ranked by mortality rate were lung cancer (78.06/100,000), gastric cancer (38.03/100,000), liver cancer (37.23/100,000), esophageal cancer (19.06/100,000), and colorectal cancer (9.53/100,000). The five leading cancers in terms of PYLL (person-years) and WPYLL (person-years) were lung cancer (3480.33, 1161.00), liver cancer (2809.03, 1475.00), gastric cancer (2120.54, 844.00), esophageal cancer (949.61, 315.00), and colorectal cancer (539.90, 246.00). From 2001 to 2010, the five leading cancers in term of average daily cost of hospitalization were gastric cancer (8,102.23 Yuan), esophageal cancer (7135.79 Yuan), colorectal cancer (7064.38 Yuan), breast cancer (6723.53 Yuan), and lung cancer (6309.39 Yuan).</p><p><b>CONCLUSIONS</b>The cancers common causing higher disease burden in Jinchang cohort were lung cancer, gastric cancer, liver cancer, esophageal cancer and colorectal cancer. The lung cancer disease burden was the highest.</p>