Glucose tolerance and two-year pulmonary exacerbation history.

<p>CFRD subjects had approximately twice as many pulmonary exacerbations as subjects with impaired (IGT) or normal glucose tolerance (NGT, left panel). The average length of admission was not significantly different between these groups (right panel). Diamonds are centered on each category’s mean and the vertical distance represents the 95% confidence interval.</p

R² and p-values from correlations between SG and clinical parameters.

<p>R² and p-values from correlations between SG and clinical parameters.</p

Comparisons of HbA_1c and SG by glucose tolerance.

<p>CFRD subjects had significantly higher HbA_1c than subjects with impaired (IGT) or normal glucose tolerance (NGT, left panel), while NGT subjects had significantly higher average sputum glucose than IGT or CFRD subjects (right panel). Diamonds are centered on each category’s mean and the vertical distance represents the 95% confidence interval.</p

Distribution of sputum glucose concentration in 117 samples.

<p>Sputum glucose (SG) was much lower than previously reported, with 34% reading < 0.01 mM, and 55% of samples reading < 1.0 mM. The distribution of SG was highly skewed: the median concentration was 0.7 mM (IQR, 0–3.5 mM) versus the mean of 4.75 mM (SD 11.4 mM).</p

Clinical parameters of CFRD subjects.

<p>Clinical parameters of CFRD subjects.</p

Mean pulmonary function test results by glycemic control in CFRD.

<p>CFRD subjects with HbA_1c > 6.5% had significantly reduced average scores of forced expiratory volume in one second (FEV₁, left panel) and forced expiratory flow in the 25–75% of the patient’s exhaled volume (FEF25–75%, right panel) compared to CFRD subjects with HbA_1c ≤ 6.5%. Diamonds are centered on each category’s mean and the vertical distance represents the 95% confidence interval.</p

Study participant demographic information, n = 88.

<p>Study participant demographic information, n = 88.</p

Additional file 4 of METABOLIC: high-throughput profiling of microbial genomes for functional traits, metabolism, biogeochemistry, and community-scale functional networks

Additional file 3: Figure S3. Functional network diagram based on the transcriptomic dataset from a deep-sea background sample

Additional file 1 of Author Correction: Microbial community dynamics and coexistence in a sulfide-driven phototrophic bloom

Additional file 1. Supplementary Materials, Methods and Results. Figure S1.Natural blooms in Trunk River. Figure S2.Color and appearance ofsamples from all holes, depths, and timepoints. Figure S3.Filters thatwere used for biomass measurements and spectral analysis. Figure S4.Total cell count of three samples (A2, A7 and K7). Figure S5. Depthprofile representation of chemical data presented in Fig.2. Figure S6. Physicochemistry. Iron, nitrate, ammonium, acetate, Ca2+, and K+measurements. Figure S7. Individual diversity indices of all samples. Figure S8. Trajectories of community structure in hole A, E and K. Figure S9. Relative sequence abundance of the 20 most abundant clades onphylum, class, order, family and genus level, as well as the 20 mostsequence abundant ASVs (amplicon sequence variants). Figure S10.Relative sequence abundance of Chlorobiales ASVs. Figure S11.Relativechange of ASV abundance between surface (V1) and deeper layers (V2-4). Figure S12.Chlorobiales phylogeny. Figure S13. Circular map ofmetagenome-assembled genomes (MAGs). Figure S14. Chlorobiales phy-logenomics. Figure S15. Protein comparison of Bin 6. Figure S16.Pro-tein comparison of Bin 10. Figure S17. Genes involved in sulfurcycling. Figure S18. CRISPR arrays and cas genes predictions Bin 6.Figure S19. CRISPR arrays and cas genes predictions Bin 10. Figure S20. Relative sequence abundance of viral family-level clades. Table S1. Over-view of sequencing output and diversity indices. Table S2. Genome sta-tistics. Table S3. Average nucleotide identity (ANI) comparisons. Table S4. Oxidative phosphorylation and chlorophyll biosynthesis genes of Bin6 and Bin 10. Table S5. CRISPR-Cas system information for eachmetagenome-assembled genome

Additional file 9 of METABOLIC: high-throughput profiling of microbial genomes for functional traits, metabolism, biogeochemistry, and community-scale functional networks

Additional file 8: Dataset S1. Conserved motif sequences and motif pairs used in our analyses