Additional file 1: of Systematic discovery of novel eukaryotic transcriptional regulators using sequence homology independent prediction

Tables S1, S3 and S4 list the candidate transcriptional regulators predicted in Arabidopsis, fruit fly, and human, respectively. Table S2 shows the number of families predicted from the genome by each criterion and the enrichment fold yield by each criteria towards the identification of regulators in Arabidopsis, fruit fly and human. Table S5 lists the physical interactions between predicted regulators and proteins involved in transcription available in the BioGRID database [108] and determined in this study. Table S6 shows the results of the segregation analysis of chiq1–1 phenotype (dwarfism) in the F2 populations of chiq1–1 x Col-0 (wild type) crosses. Table S7 shows the results of the linkage analysis of chiq1–1 phenotype (dwarfism) and genotype in the F2 populations of chiq1–1 x Col-0 (wild type) crosses. Table S8 lists the proteins that co-immunoprecipitated (Co-IP/MS) with CHIQ1-GFP in vivo. Table S9 lists the physical interactions among nine CHIQ proteins. Figure S1 illustrates the pipeline workflow and the number of predictions in yeast, fruit fly and human. Figure S2 shows the proportion of unknown genes in families with less than three or more than two members in Arabidopsis, yeast, fruit fly and human and the proportion of the predictions among the unknown families with more than two members. Figure S3 shows the precision, recall and F1 score of TF predictions in Arabidopsis. Figure S4 shows the maximum number of aspartic acid, glutamic acid, asparagine, glutamine, serine, proline and acidic amino acids in all proteins, TFs and the predicted regulators in Arabidopsis, fruit fly and human. Figure S5 shows the GUS activity of the negative controls for the in planta transactivation assay. Figure S6 shows the number of leaves at different ages and the age of bolting in wild type (Col-0), chiq1–1 and B12 (complemented line). (DOCX 1780 kb

DataSheet1_Protracted post-glacial hydrocarbon seepage in the Barents Sea revealed by U–Th dating of seep carbonates.PDF

The hydrocarbon seepage chronology during deglaciation across the formerly glaciated Barents Sea was established using uranium-thorium (U–Th) dating of seep carbonates. Seep carbonates were sampled with remotely operated vehicles (ROV) from the seafloor at three active hydrocarbon seeps (water depth 156–383 m), located in the north-west (Storfjordrenna), north-central (Storbanken High), and south-west (Loppa High) Barents Sea. Overall, the U–Th dates range from 13.5 to 1.2 thousand years (ka) before present, indicating episodic seep carbonate formation since the late Pleistocene throughout the Holocene. The new U–Th dates indicate protracted post-glacial gas seepage, congruent with previously published seep carbonate ages from the south-west Barents Sea. Gas hydrate dissociation and associated seep carbonate formation occurred at Storfjordrenna between ≈6 and 1.2 ka, and around 13.5 and 6 ka at Storbanken. Early and late Holocene seep carbonate ages from Loppa High support post-glacial seismic activity as potential seepage trigger mechanism.</p

Table1_Protracted post-glacial hydrocarbon seepage in the Barents Sea revealed by U–Th dating of seep carbonates.XLSX

The hydrocarbon seepage chronology during deglaciation across the formerly glaciated Barents Sea was established using uranium-thorium (U–Th) dating of seep carbonates. Seep carbonates were sampled with remotely operated vehicles (ROV) from the seafloor at three active hydrocarbon seeps (water depth 156–383 m), located in the north-west (Storfjordrenna), north-central (Storbanken High), and south-west (Loppa High) Barents Sea. Overall, the U–Th dates range from 13.5 to 1.2 thousand years (ka) before present, indicating episodic seep carbonate formation since the late Pleistocene throughout the Holocene. The new U–Th dates indicate protracted post-glacial gas seepage, congruent with previously published seep carbonate ages from the south-west Barents Sea. Gas hydrate dissociation and associated seep carbonate formation occurred at Storfjordrenna between ≈6 and 1.2 ka, and around 13.5 and 6 ka at Storbanken. Early and late Holocene seep carbonate ages from Loppa High support post-glacial seismic activity as potential seepage trigger mechanism.</p

Additional file 2 of The chronic kidney disease epidemiology collaboration equation combining creatinine and cystatin C accurately assesses renal function in patients with cirrhosis

Characteristics of 8 cirrhotic patients with mGFR < 60 ml/min/1.73 m2. CTP, Child Turcotte Pugh Score; mGFR, measured glomerular filtration rate; PSC, primary sclerosing cholangitis. (JPG 27 kb

Additional file 1 of The chronic kidney disease epidemiology collaboration equation combining creatinine and cystatin C accurately assesses renal function in patients with cirrhosis

GFR equations used in the study. Cr, serum creatinine (mg/dL); CysC, serum Cystatin C (mg/dL). (JPG 58 kb