Iowa Influenza Surveillance Network: Weekly Activity Report Week 46, November 21, 2015

The Iowa Influenza Surveillance Network (IISN) was established in 2004, though surveillance has been conducted at the Iowa Department of Public Health. Schools and long-term care facilities report data weekly into a Web-based reporting system. Schools report the number of students absent due to illness and the total enrolled. Long-term care facilities report cases of influenza and vaccination status of each case. Both passively report outbreaks of illness, including influenza, to IDPH.

Iowa Influenza Surveillance Network: Weekly Activity Report Week 47, November 28, 2015

The Iowa Influenza Surveillance Network (IISN) was established in 2004, though surveillance has been conducted at the Iowa Department of Public Health. Schools and long-term care facilities report data weekly into a Web-based reporting system. Schools report the number of students absent due to illness and the total enrolled. Long-term care facilities report cases of influenza and vaccination status of each case. Both passively report outbreaks of illness, including influenza, to IDPH.

Iowa Influenza Surveillance Network: Weekly Activity Report Week 48, December 5, 2015

The Iowa Influenza Surveillance Network (IISN) was established in 2004, though surveillance has been conducted at the Iowa Department of Public Health. Schools and long-term care facilities report data weekly into a Web-based reporting system. Schools report the number of students absent due to illness and the total enrolled. Long-term care facilities report cases of influenza and vaccination status of each case. Both passively report outbreaks of illness, including influenza, to IDPH.

Iowa Influenza Surveillance Network: Weekly Activity Report Week 49, December 12, 2015

The Iowa Influenza Surveillance Network (IISN) was established in 2004, though surveillance has been conducted at the Iowa Department of Public Health. Schools and long-term care facilities report data weekly into a Web-based reporting system. Schools report the number of students absent due to illness and the total enrolled. Long-term care facilities report cases of influenza and vaccination status of each case. Both passively report outbreaks of illness, including influenza, to IDPH.

Iowa Influenza Surveillance Network: Weekly Activity Report Week 50, December 19, 2015

The Iowa Influenza Surveillance Network (IISN) was established in 2004, though surveillance has been conducted at the Iowa Department of Public Health. Schools and long-term care facilities report data weekly into a Web-based reporting system. Schools report the number of students absent due to illness and the total enrolled. Long-term care facilities report cases of influenza and vaccination status of each case. Both passively report outbreaks of illness, including influenza, to IDPH.

Iowa Influenza Surveillance Network: Weekly Activity Report Week 51, December 26, 2015

The Iowa Influenza Surveillance Network (IISN) was established in 2004, though surveillance has been conducted at the Iowa Department of Public Health. Schools and long-term care facilities report data weekly into a Web-based reporting system. Schools report the number of students absent due to illness and the total enrolled. Long-term care facilities report cases of influenza and vaccination status of each case. Both passively report outbreaks of illness, including influenza, to IDPH.

Iowa Influenza Surveillance Network: Weekly Activity Report Week 52, January 2, 2016

The Iowa Influenza Surveillance Network (IISN) was established in 2004, though surveillance has been conducted at the Iowa Department of Public Health. Schools and long-term care facilities report data weekly into a Web-based reporting system. Schools report the number of students absent due to illness and the total enrolled. Long-term care facilities report cases of influenza and vaccination status of each case. Both passively report outbreaks of illness, including influenza, to IDPH.

Monitoring the decreasing trend of testicular cancer mortality in Spain during 2005-2019 through a Bayesian approach

Purpose : To assess time trends of testicular cancer (TC) mortality in Spain for period 1985-2019 for age groups 15-74 years old through a Bayesian age-period-cohort (APC) analysis. Methods: A Bayesian age-drift model has been fitted to describe trends. Projections for 2005-2019 have been calculated by means of an autoregressive APC model. Prior precision for these parameters has been selected through evaluation of an adaptive precision parameter and 95% credible intervals (95% CRI) have been obtained for each model parameter. Results: A decrease of -2.41% (95% CRI: -3.65%; -1.13%) per year has been found for TC mortality rates in age groups 15-74 during 1985-2004, whereas mortality showed a lower annual decrease when data was restricted to age groups 15-54 (-1.18%; 95% CRI: -2.60%; -0.31%). During 2005-2019 is expected a decrease of TC mortality of 2.30% per year for men younger than 35, whereas a leveling off for TC mortality rates is expected for men older than 35. Conclusions: A Bayesian approach should be recommended to describe and project time trends for those diseases with low number of cases. Through this model it has been assessed that management of TC and advances in therapy led to decreasing trend of TC mortality during the period 1985-2004, whereas a leveling off for these trends can be considered during 2005-2019 among men older than 35.

Monitoring the decreasing trend of testicular cancer mortality in Spain during 2005-2019 through a Bayesian approach

Purpose : To assess time trends of testicular cancer (TC) mortality in Spain for period 1985-2019 for age groups 15-74 years old through a Bayesian age-period-cohort (APC) analysis. Methods: A Bayesian age-drift model has been fitted to describe trends. Projections for 2005-2019 have been calculated by means of an autoregressive APC model. Prior precision for these parameters has been selected through evaluation of an adaptive precision parameter and 95% credible intervals (95% CRI) have been obtained for each model parameter. Results: A decrease of -2.41% (95% CRI: -3.65%; -1.13%) per year has been found for TC mortality rates in age groups 15-74 during 1985-2004, whereas mortality showed a lower annual decrease when data was restricted to age groups 15-54 (-1.18%; 95% CRI: -2.60%; -0.31%). During 2005-2019 is expected a decrease of TC mortality of 2.30% per year for men younger than 35, whereas a leveling off for TC mortality rates is expected for men older than 35. Conclusions: A Bayesian approach should be recommended to describe and project time trends for those diseases with low number of cases. Through this model it has been assessed that management of TC and advances in therapy led to decreasing trend of TC mortality during the period 1985-2004, whereas a leveling off for these trends can be considered during 2005-2019 among men older than 35.

Monitoring the decreasing trend of testicular cancer mortality in Spain during 2005-2019 through a Bayesian approach

Purpose : To assess time trends of testicular cancer (TC) mortality in Spain for period 1985-2019 for age groups 15-74 years old through a Bayesian age-period-cohort (APC) analysis. Methods: A Bayesian age-drift model has been fitted to describe trends. Projections for 2005-2019 have been calculated by means of an autoregressive APC model. Prior precision for these parameters has been selected through evaluation of an adaptive precision parameter and 95% credible intervals (95% CRI) have been obtained for each model parameter. Results: A decrease of -2.41% (95% CRI: -3.65%; -1.13%) per year has been found for TC mortality rates in age groups 15-74 during 1985-2004, whereas mortality showed a lower annual decrease when data was restricted to age groups 15-54 (-1.18%; 95% CRI: -2.60%; -0.31%). During 2005-2019 is expected a decrease of TC mortality of 2.30% per year for men younger than 35, whereas a leveling off for TC mortality rates is expected for men older than 35. Conclusions: A Bayesian approach should be recommended to describe and project time trends for those diseases with low number of cases. Through this model it has been assessed that management of TC and advances in therapy led to decreasing trend of TC mortality during the period 1985-2004, whereas a leveling off for these trends can be considered during 2005-2019 among men older than 35.

Monitoring the decreasing trend of testicular cancer mortality in Spain during 2005-2019 through a Bayesian approach

Purpose : To assess time trends of testicular cancer (TC) mortality in Spain for period 1985-2019 for age groups 15-74 years old through a Bayesian age-period-cohort (APC) analysis. Methods: A Bayesian age-drift model has been fitted to describe trends. Projections for 2005-2019 have been calculated by means of an autoregressive APC model. Prior precision for these parameters has been selected through evaluation of an adaptive precision parameter and 95% credible intervals (95% CRI) have been obtained for each model parameter. Results: A decrease of -2.41% (95% CRI: -3.65%; -1.13%) per year has been found for TC mortality rates in age groups 15-74 during 1985-2004, whereas mortality showed a lower annual decrease when data was restricted to age groups 15-54 (-1.18%; 95% CRI: -2.60%; -0.31%). During 2005-2019 is expected a decrease of TC mortality of 2.30% per year for men younger than 35, whereas a leveling off for TC mortality rates is expected for men older than 35. Conclusions: A Bayesian approach should be recommended to describe and project time trends for those diseases with low number of cases. Through this model it has been assessed that management of TC and advances in therapy led to decreasing trend of TC mortality during the period 1985-2004, whereas a leveling off for these trends can be considered during 2005-2019 among men older than 35.

A comparison of Bayesian and frequentist approaches to incorporating external information for the prediction of prostate cancer risk.

We present the most comprehensive comparison to date of the predictive benefit of genetics in addition to currently used clinical variables, using genotype data for 33 single-nucleotide polymorphisms (SNPs) in 1,547 Caucasian men from the placebo arm of the REduction by DUtasteride of prostate Cancer Events (REDUCE®) trial. Moreover, we conducted a detailed comparison of three techniques for incorporating genetics into clinical risk prediction. The first method was a standard logistic regression model, which included separate terms for the clinical covariates and for each of the genetic markers. This approach ignores a substantial amount of external information concerning effect sizes for these Genome Wide Association Study (GWAS)-replicated SNPs. The second and third methods investigated two possible approaches to incorporating meta-analysed external SNP effect estimates - one via a weighted PCa 'risk' score based solely on the meta analysis estimates, and the other incorporating both the current and prior data via informative priors in a Bayesian logistic regression model. All methods demonstrated a slight improvement in predictive performance upon incorporation of genetics. The two methods that incorporated external information showed the greatest receiver-operating-characteristic AUCs increase from 0.61 to 0.64. The value of our methods comparison is likely to lie in observations of performance similarities, rather than difference, between three approaches of very different resource requirements. The two methods that included external information performed best, but only marginally despite substantial differences in complexity.

Bayesian estimation of diameter distribution during harvesting

Abstract

Cab45 is required for Ca(2+)-dependent secretory cargo sorting at the trans-Golgi network

Ca(2+) import into the lumen of the trans-Golgi network (TGN) by the secretory pathway calcium ATPase1 (SPCA1) is required for the sorting of secretory cargo. How is Ca(2+) retained in the lumen of the Golgi, and what is its role in cargo sorting? We show here that a soluble, lumenal Golgi resident protein, Cab45, is required for SPCA1-dependent Ca(2+) import into the TGN; it binds secretory cargo in a Ca(2+)-dependent reaction and is required for its sorting at the TGN.

Kinesin-5/Eg5 is important for transport of CARTS from the trans-Golgi network to the cell surface

Here we report that the kinesin-5 motor Klp61F, which is known for its role in bipolar spindle formation in mitosis, is required for protein transport from the Golgi complex to the cell surface in Drosophila S2 cells. Disrupting the function of its mammalian orthologue, Eg5, in HeLa cells inhibited secretion of a protein called pancreatic adenocarcinoma up-regulated factor (PAUF) but, surprisingly, not the trafficking of vesicular stomatitis virus G protein (VSV-G) to the cell surface. We have previously reported that PAUF is transported from the trans-Golgi network (TGN) to the cell surface in specific carriers called CARTS that exclude VSV-G. Inhibition of Eg5 function did not affect the biogenesis of CARTS; however, their migration was delayed and they accumulated near the Golgi complex. Altogether, our findings reveal a surprising new role of Eg5 in nonmitotic cells in the facilitation of the transport of specific carriers, CARTS, from the TGN to the cell surface.