Additional file 2: Table S2. of Guillain-Barre syndrome caused by hepatitis E infection: case report and literature review

Serologic studies for hepatitis virus. Serologic studies for IgM and IgG anti-HEV were both positive. No serological evidence was found for hepatitis A virus, hepatitis B virus, hepatitis C virus, hepatitis D virus. (DOCX 15 kb

Additional file 3: Table S3. of Guillain-Barre syndrome caused by hepatitis E infection: case report and literature review

Serological study for HBV, HCV, Syphilis and HIV. Serologic studies for hepatitis B virus, hepatitis C virus, syphilis or human immunodeficiency virus was negative. (DOCX 15 kb

Additional file 1: Table S1. of Guillain-Barre syndrome caused by hepatitis E infection: case report and literature review

Liver function after admission in our hospital. The patient’s liver function tests showed showed 20 μmol/L total bilirubin, 10 μmol/L conjugated bilirubin, 126 U/L alanine aminotransferase, and 160 U/L gamma-glutamyl transpepidase. (DOCX 16 kb

Additional file 8: Table S8. of Guillain-Barre syndrome caused by hepatitis E infection: case report and literature review

Serological study for HEV(six months later). Six months after discharge, serological study showed IgM anti-HEV antibodies became negative. (DOCX 15 kb

DGGE profiles of the predominant intestinal bacteria in H7N9-infected patients.

<p><b>(a)</b> DGGE profiles of fecal bacteria in A, B and C groups. <b>(b)</b> Differences in the DGGE profiles of fecal samples taken at different time points from the same individual were apparent, particularly for patients D1, D2, D4, D5 and D7. This result suggests temporal instability in the predominant bacterial population in H7N9-infected patients with secondary infection.</p

Intestinal microbial diversity comparison.

<p><b>(a)</b> Shannon’s diversity index comparison. <b>(b)</b> Shannon’s evenness index comparison. <b>(c)</b> Species richness comparison. Shannon’s diversity index and Shannon’s evenness index were lower in all infected groups compared to the control group. A decreased Shannon’s diversity, evenness and species richness in group D patients compared to patients in the A and C groups. * P<0.05, ** P<0.01 <b>(d)</b> The changes in Shannon’s diversity and evenness in patient C1. X axis, time of sampling. <b>(e)</b> The changes in Shannon’s diversity and evenness in patient C3. <b>(f)</b> The changes in Shannon’s diversity and evenness in patient C5. <b>(g)</b> The changes in Shannon’s diversity and evenness in patient D3. After <i>B</i>. <i>subtilis</i> and <i>E</i>. <i>faecium</i> or <i>C</i>. <i>butyricum</i> administration, the fecal bacterial profiles of patients without antibiotics displayed a trend of increasing diversity and evenness. <b>(h)</b> The changes in Shannon’s diversity and evenness in patient D5. <b>(i)</b> The changes in Shannon’s diversity and evenness in patient D7. The results showed that a trend toward increasing diversity and evenness in D3, D5 and D7 after antibiotic cessation.</p

The numbers of predominant bands were excised from the DGGE gels.

<p>Each band represents a bacterial clone. Band numbers (corresponding to <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0151976#pone.0151976.g006" target="_blank">Fig 6</a> band classes) indicated the position of bands excised for sequence analyses (e.g. ‘“20”‘ means band 20).</p

Phylogenetic tree analysis of DGGE profiles.

<p>Phylogenetic tree of sequences constructed using the neighbor-joining method based on the DGGE profiles. The fragment sequences were named for their positions in the gels using the band-matching tool with BioNumerics software version 6.01 (Applied Math). Twenty-one band classes, indicated by black spots, displayed little variation in intensity in the follow-up samples. Seven band classes, indicated by black triangles, exhibited a increase in intensity in the follow-up samples. Six band classes, indicated by black squares, exhibited an decrease in the follow-up samples. The plot was generated using MEGA5.1 software.</p

Cluster analysis of the DGGE profiles of the predominant fecal bacteria of 15 patients in follow-up samples.

<p>Clustering was performed using Dice’s coefficient and UPGMA. <b>(a)</b> Cluster analysis of the DGGE profiles from the different groups. The metric scale denotes the degree of similarity. <b>(b)</b> MDS analysis of the cluster shown in (a). The plot is an optimized 3D representation of the similarity matrix obtained from BioNumerics software, and the x-, y-, and z-axes separately represent three different dimensions: Dim 1, Dim 2, and Dim 3. The Euclidean distance between two points reflects similarity. <b>(c)</b> PCA of fecal microbiota based on the DGGE fingerprinting shown in (a). The plot is reoriented to maximize variation among lanes along the first three principal components (the contributions 11.5, 20.0 and 26.7, respectively) obtained from BioNumerics software.</p