General information of study subjects.

<p>General information of study subjects.</p

General information & PARV4 DNA positive rate of HBV infected groups.

<p>*p value: data for 2 HBV patient groups was compared with Pearson's χ2- test.</p

Phylogenetic tree of PARV4 isolates infecting HBV, HCV patients and healthy controls.

<p>The nucleotide sequence from 1564 to 1724 bp of ORF1 gene of PARV4 were amplified, sequenced and analyzed. Bootstrap percentages are given at the node of each branch (1000 replicates). Sequences H009, H108, H110, H113, H121, H122, H132, H142, H145 and H147 were from healthy controls. Sequences HBV02, HBV06, HBV09, HBV25, HBV42, HBV45, HBV50, HBV59, HBV63 and HBV73 were from HBV infected subjects with PARV4 infection. Sequences HCV037, HCV048,HCV052, HCV065, HCV074, HCV080, HCV112, HCV115, HCV130 and HCV145 were from HCV infected subjects with PARV4 infection. AY622943.1 and EU546211.1 represent 2 PARV4 genotype 1 reference strains, and DQ112361.11 and DQ873391.1 are sequences of 2 PARV4, genotype 2 reference strains. All reference strain sequences were downloaded from GenBank.</p

The PARV4 nucleic acid frequency in chronic HBV patients with/without HBV DNA, and with different ALT levels.

<p>The PARV4 nucleic acid frequency in chronic HBV patients with/without HBV DNA, and with different ALT levels.</p

Detection Rate of PARV4 DNA.

<p>Detection Rate of PARV4 DNA.</p

Maximum likelihood estimation on the temperature effect distribution of different time lags.

<p>Maximum likelihood estimation on the temperature effect distribution of different time lags.</p

Scatter plot of y_texp(-NS(t,df_t)-DOW_t) vs. Time by GAM model.

<p>From expression (5), we shall assume that the term µ_texp(-NS(t,df_t)-DOW_t) will have stable seasonality which does not change in different years. To achieve this property we need to check the seasonality of the term y_texp(-NS(t,df_t)-DOW_t) by the scatter plot under the certain selection of the degree of freedom for the natural spline functions. The figure shows good seasonality with df_t = 6 in part A and week seasonality with df_t = 20 in part B.</p

Scatter plot s of BD counts, Temperature and Humidity vs. Time.

<p>A. Daily BD counts from 2004 to 2008, with the solid line: Lowess estimation of BD counts. B. Daily averaged temperature from 2004 to 2008, with the solid line: Lowess estimation of averaged temperature. C. Daily averaged humidity from 2004 to 2008, with the solid line: Lowess estimation of averaged humidity.</p

Parameter estimation of predictive model.

<p>Parameter estimation of predictive model.</p

Real and fitted BD counts using the predictive MGAM model from 2004 to 2007.

<p>The light gray points are real daily BD counts from 2004 to 2007, and the dark blue points are fitted BD counts using predictive MGAM model. R-square of the model fitting is 0.875.</p