BUSCADOR RECOLECTA

This dataset in an Excel file compares the wave of globalization before the outbreak of the Great Recession in 2007 with its alleged historical antecedent before the outbreak of World War One. We describe trends in trade and openness, estimate the gains from trade and investigate the proximate causes of the growth of openness. We argue that the conventional wisdom has to be revised. The first wave of globalization started around 1820 and culminated around 1870. In the next century, trade continued to grow, with the exception of the Great Depression, but openness and gains fluctuated widely. Growth resumed in the early 1970s. By 2007, the world was more open than a century earlier and its inhabitants gained from trade substantially more than their ancestors did. The current wave of globalization, in spite of some similarities with previous trends, has no historical antecedents. This dataset is related to the working paper "A tale of two globalizations : gains for trade and openness 1800-2010" by by Giovanni Federico and Antonio Tena Junguito, available on: http://hdl.handle.net/10016/22354

This dataset is supporting information to the paper pubished in the Working papers in Economic History series, n. 16-01., This dataset in an Excel file presents our data-base on world trade from 1800 to 1938. We have collected or estimated series of imports and exports, at current and constant (1913) prices and at current and at constant (1913) borders, for 149 polities. After a short review of the available series, we describe the methods for the construction of the data-base. We then deal with the criteria for the inclusion of polities, the representativeness of our series, the main types of sources, the procedures of deflation and, when necessary, of adjustments to 1913 borders. We discuss the details of the estimation of our polity series in Appendix B. Following Feinstein and Thomas (2001), we assess the reliability of our polity estimates. In the last two sections we present our trade series at current and 1913 borders and compare them with other available series. This dataset is related to the working paper "World trade, 1800-1938 : a new data-set" by Giovanni Federico and Antonio Tena Junguito, available on: http://hdl.handle.net/10016/22222.

1 figure, Including the identification of known and putative novel miRNAs, miRNA abundance profiling and differential abundance analysis. rRNA: ribosomal RNA; tRNA: transfer RNA; snoRNA: small nucleolar RNA; snRNA: small nuclear RNA; RE: repeat elements; qPCR: quantitative real-time PCR., Peer reviewed

1 figure, CKD: Chronic kidney disease; PN: Pyelonephritis; SB/C: Subclinical bacteriuria/Cystitis; UO: Ureteral obstruction, Peer reviewed

A. PCA of urine samples on the basis of normalized read counts of the known and putative novel miRNAs for the 38 samples initially processed. The red arrows indicate the outlier Control samples (C5, C6 and C7). B. PCA excluding the high outlier samples. CKD: Chronic kidney disease; PN: Pyelonephritis; SB/C: Subclinical bacteriuria/Cystitis; UO: Ureteral obstruction., Peer reviewed

A. Proportion of samples for which each of the known miRNAs across the different groups were detected. B. Cumulative abundance of the known feline miRNAs. The dots indicate the log10 of the miRNA abundance for each miRNA. miRNAs are sorted in each group in a decreasing order by their miRNA abundance on the x-axis, independently for each group. C. Proportion of samples for which each of the putative novel miRNA candidates across the different groups were detected. D. Cumulative abundance of the putative novel miRNAs. The dots indicate the log10 of the miRNA abundance for each miRNA. miRNAs are sorted in each group in a decreasing order by their miRNA abundance on the x-axis, independently for each group. CKD: Chronic kidney disease; PN: Pyelonephritis; SB/C: Subclinical bacteriuria/Cystitis; UO: Ureteral obstruction, CPM: Counts per million., Peer reviewed

1 figure., All samples together (all groups), as well as each one of the contrasts considered (Controls vs. PN; Control vs. SB/C; Control vs. UO; Control vs. CKD; PN vs. SB/C; PN vs. UO; PN vs. CKD and PN vs. other Pathologies) are shown. CKD: Chronic kidney disease; PN: Pyelonephritis; SB/C: Subclinical bacteriuria/Cystitis; UO: Ureteral obstruction., Peer reviewed

1 figure., CKD: Chronic kidney disease; PN: Pyelonephritis; SB/C: Subclinical bacteriuria/Cystitis; UO: Ureteral obstruction, CPM: Counts per million, Rq: Relative quantities., Peer reviewed

The data presented is from selected miRNAs that were DA (|log2FC| ≥ 1.5 for qPCR and |log2FC| ≥ 2 for small RNAseq; q-value < 0.05) using both methodologies. CKD: Chronic kidney disease; PN: Pyelonephritis; SB/C: Subclinical bacteriuria/Cystitis; UO: Ureteral obstruction, CPM: Counts per million, Rq: Relative quantities., Peer reviewed

1 table., The table includes for each miRNA the arguments for its selection for further validation, the forward and reverse sequence, the miRBase sequence used as template for primer design, if successful miRNA amplification was obtained with qPCR and qPCR amplification efficiency., Peer reviewed