BUSCADOR RECOLECTA

Datos utilizados en los análisis estadísticos del artículo

Base de datos, Base de datos en programa SPSS.

This folder is an additional material to the PhD thesis "Analysis of the Sierra Nevada ELF station recordings: a contribution to the study of the Schumann Resonances". It contains a wide range of computational tools that allow the researchers to obtain, export, visualize and study all the information related to the SR parameters. These computational tools are presented in the form of a collection of Jupyter notebooks. The data (the SR parameters extracted from the Sierra Nevada ELF station) are also contained in the folder.

Dos bases de datos de donde se obtienen los resultados de un artículo de investigación

Transcripciones de grupos de discusión a jóvenes sobre vivienda y emancipación realizado por Joaquín Susino y Nayla Fuster en 2014-2015

Data used for meta-analysis of salvage logging effects on woody plant regeneration. point.id= unique identification number for each data point site.id= unique identification number for each publication (see references in attached file). country= Country where the study site was located .disturbance.type, disturbance.severity, time.disturbance.logging, time.logging.measurement, logging.intensity, forest.leaf.habit, forest.age, regeneration.syndrome, aridity = the effect moderators described in Supporting Information S1 of the paper. response= response variable. yi, vi= mean and variance of Hedge's d (effect sizes). data.origin= position in the publication where the data were obtained (or directly from author)., Funded by grants: RTI2018-096187-J-100 from FEDER/ Ministerio de Ciencia, Innovación y Universidades LRB20/1002 from the British Ecological Society Research Fellowship from the Alexander von Humboldt Foundation

Es una tabla en Word muy extensa que contiene material complementario de un TFG

MicroRNAs (miRs) have emerged as promising biomarkers for early disease diagnosis and personalised treatment monitoring. However, but their clinical utility has been hampered by technical limitations. Dynamic chemical labelling (DCL) based on capturing abasic PNA probes and reactive nucleobases, so-called SMART bases, is a PCR-free approach that has proven very useful for the direct interrogation of circulating miRs. In this work, we expand the palette of available tools for DCL miR detection methods with a newly synthesised SMART nucleobase, SMART-C-Eu. This nucleobase contains a stable lanthanide cryptate. Using this SMART-C-Eu base and time-gated (TG) luminescence imaging, we successfully detect and quantify miR-122-5p in human serum samples. miR-122-5p is a well-known biomarker for drug-induced liver injury. A bead-counting analysis approach improved statistical robustness and allowed the detection of miR-122-5p concentrations in the nanomolar range. Furthermore, we extend this approach to multiplexed detection of three different miRs (miR-371a-3p, miR-451a-5p, and miR-122-5p) using spectral and temporal filtering. Consistent results were obtained using machine learning algorithms for automatic bead classification. Although this technique requires further sensitivity improvements to detect miRs at lower concentrations, it represents a significant advancement in miR analysis. It offers multiplexing capabilities and the potential for automation, paving the way for more accurate and robust clinical applications in the future., European Union through the H2020 diaRNAgnosis project, under grant agreement No. 101007934, Agencia Estatal de Investigación (Spain) through grant PID2020-114256RB-I00 AEI/10.13039/501100011033, Agencia Estatal de Investigación (Spain) through grant CTQ2017-85658-R AEI/10.13039/501100011033/FEDER “Una manera de hacer Europa”.