Resultados de investigación

The excel file contains the following tabs: Cell diameter microscopy, sc-ICP-MS glucose, sc-ICP-MS AAPH If any doubt arises when processing it or additional information is needed about the concentrations or measures used, first author/corresponding author should be contacted., This work was financially supported through projects PID2019-107838RB-I00/Agencia Estatal de Investigación (AEI)/10.13039/501100011033) and AYUD/2021/51289-FICYT. P. Menero-Valdés acknowledges the FPU Grant with ref FPU19/00556 (Ministry of Education, Spain).

The excel file contains the following tabs: Viability and ROS assay, optimization sc intro, Ab concentration optimization, ELISA kits, LA-ICP-MS, sc-ICP-MS APOE and sc-ICP-MS claudin 1. If any doubt arises when processing it or additional information is needed about the concentrations or measures used, first author/corresponding author should be contacted., This work was financially supported through projects PID2019-107838RB-I00/Agencia Estatal de Investigación (AEI)/10.13039/501100011033) in Spain and AYUD/2021/51289 - FICYT. P. Menero-Valdés acknowledges the FPU Grant with Ref. FPU19/00556 (Ministry of Education, Spain).

Dataset collected for the experiments of a tool related to the maintenance of data integrity in column-oriented database applications, Spanish Ministry of Economy and Competitiveness and MCIN/ AEI/10.13039/501100011033 (Spain)

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”.

This work was supported by grant CTQ2017-85658-R funded by MCIN/AEI/10.13039/501100011033/ FEDER “Una manera de hacer Europa”, grant PID2020-114256RB-I00 funded by MCIN/AEI/10.13039/501100011033, and the diaRNAgnosis project funded by the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 101007934. P.M.R.P. acknowledges funding from Fundação para a Ciência e a Tecnologia, I.P., through projects UIDB/00100/2020 and 2022.04076.PTDC., Controlling the nano- and micropatterning of metal structures is an important requirement for various technological applications in photonics and biosensing. We present a method for controllably creating silver micropatterns by laser-induced photo-sculpting. Photo-sculpting is driven by plasmonic interactions between pulsed laser radiation and silver nanorods (AgNRs) in aqueous suspension; this process leads to optical binding forces transporting the AgNRs in the surroundings, while electronic thermalization results in photooxidation, melting, and ripening of the AgNRs into well-defined 3D structures. We called these structures Airy castles due to their structural similarity with a diffraction-limited Airy disk. The photo-sculpted Airy castles contain emissive Ag nanoclusters, allowing for the visualization and examination of the aggregation process using luminescence microscopy. We comprehensively examine the factors that define the photo-sculpting process, namely, the concentration and shape of the AgNRs, as well as the energy, power and repetition rate of the laser. Finally, we investigate the potential applications by measuring the metal-enhanced luminescence of a europium-based luminophore using Airy castles., Grant CTQ2017-85658-R funded by MCIN/AEI/10.13039/501100011033/ FEDER “Una manera de hacer Europa”, Grant PID2020-114256RB-I00 funded by MCIN/AEI/10.13039/501100011033, diaRNAgnosis project funded by the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 101007934, Fundação para a Ciência e a Tecnologia, I.P., through projects UIDB/00100/2020 and 2022.04076.PTDC

Raw data of a mansucript to be submitted to Geochimica et Cosmochimica Acta, Calcium carbonate isotopic compositions have been widely used to reconstruct past environments. However, if the isotopic composition is modified as a result of the mineral formation from an amorphous precursor, the reliability of carbonate minerals as paleo-geochemical proxies can be compromised. This study explores the changes in the oxygen isotope compositions during the transformation of amorphous calcium carbonate (ACC) into crystalline carbonate under different conditions of relative humidity (RH of 33 to 95%), temperature (T of 5 ºC and 20 ºC) and in the presence/absence of atmospheric CO2. The data shows that at low RH and_T (e.g., RH ≤ 45% and 5 ºC), a complete ACC–crystalline carbonate transformation does not take place and the primarily ACC δ18O values remained relatively constant (δ18OCaCO3 = −15.9 ± 1.0 ‰, VPDB) throughout our experimental runtime (up to 144 days). In contrast, in fully crystallized CaCO3 (e.g., at RH ≥ 60 %) the δ18OCaCO3 values increased rapidly over the first few days, followed by a slower consistent increase. By the end of the experiments (after 103 to 144 days) almost constant δ18OCaCO3 values were reached, ranging from −10.4 ‰ to −8.1 ‰ in the presence of atmospheric CO2 and from −12.6 ‰ to −9.5 ‰ in the CO2-free experiments. During the experiments the changes in oxygen isotope compositions of the CaCO3 reaction product were mainly driven by exchange with H2O from the hydrated ACC. Calcite and/or vaterite were found as final crystalline products. Considering the well-known oxygen isotope fractionation between calcite and fluid at equilibrium, in the presence of CO2, the herein obtained Δ18OCaCO3-H2O = 18OCaCO3 - δ18OH2O(ACC) tended to approach but did not reach isotopic equilibrium at the given temperature. The latter effect could be explained by a decrease in the pH of the aqueous fluid released from ACC dissolution during CO2 absorption, which increased the oxygen isotope exchange kinetics between H2O and dissolved inorganic carbon (DIC) via the hydration/hydroxylation of CO2(aq) and H2O in the fluid. However, at 60 to 95 % RH rapid deprotonation could have led to 18O-enriched CO32− due to the incorporation of heavier HCO3−; and resulting in fractionation factors that exceeded equilibrium values. In the CO2-free experiments, the isotopic equilibrium between the crystalline phase with the synthesis fluid was not reached. This oxygen isotope disequilibrium suggests that the CO32− could have been buffered by a lighter source, such as, the CO32− released from the ACC/calcite during the dissolution-reprecipitation process. The results suggest that the oxygen isotopic composition of natural carbonates formed from ACC transformation in air and at low water/solid ratio (e.g., biominerals or carbonates formed in caves) are complex and cannot be used as simple proxy if kinetics (RH/CO2/T) and H2O sources are not known and quantified., This project has received funding from the Junta de Andalucía through the EMERGIA research programme under the grant agreement EMERGIA20_38594, the European Research Council Advanced Grant 788752, the Institute of Earth Surface Dynamics (IDYST, University of Lausanne, Switzerland), the research groups of the Junta de Andalucía RNM 179 and 190, and the PID2021-125619OB-C21 funded by Ministerio Ciencia e Innovación/Agencia Estatal de Investigación/ 10.13039/501100011033/ and Fondo Europeo de Desarrollo Regional “Una manera de hacer Europa”.

The aim of this document is to describe how to reproduce the results derived in the article “Exploring and correcting the bias in the estimation of the Gini measure of income inequality”, published in the journal Sociological Methods & Research. First (Section 2), we describe (load) the various R packages required for the computation of the estimators described in this article. In Section 3, we compute the parameters of the probabilistic distributions considered in simulation studies. Section 4 gives examples on how samples can be selected for the various scenarios. For both infinite and finite populations, codes for computing the various estimators of the Gini index are provided in Section 5. Box plots to investigate the effect of the skewness on the bias of the estimation of the Gini index can be seen in Section 6. For the various estimators defined in this document, Section 7 provides codes for computing empirical measures related to such estimators. In particular, functions inf.empirical.measures and fin.empirical.measures gives the: (i) Relative Bias (RB); (ii) Relative Root Mean Square Error (RRMSE); (iii) Bias Ratio (BR); (iv) Expected value based on estimates of the Gini index and; (v) Expected value based on estimates of the coefficient of skewness. Some examples are included, and they indicate how to carry out simulation studies. Finally, various estimators of the Gini index are computed using the data set ES-SILC, with size n=26. The various real data sets can be loaded using the file Datasets.RData., The aim of this document is to describe how to reproduce the results derived in the article “Exploring and correcting the bias in the estimation of the Gini measure of income inequality”, published in the journal Sociological Methods & Research. First (Section 2), we describe (load) the various R packages required for the computation of the estimators described in this article. In Section 3, we compute the parameters of the probabilistic distributions considered in simulation studies. Section 4 gives examples on how samples can be selected for the various scenarios. For both infinite and finite populations, codes for computing the various estimators of the Gini index are provided in Section 5. Box plots to investigate the effect of the skewness on the bias of the estimation of the Gini index can be seen in Section 6. For the various estimators defined in this document, Section 7 provides codes for computing empirical measures related to such estimators. In particular, functions inf.empirical.measures and fin.empirical.measures gives the: (i) Relative Bias (RB); (ii) Relative Root Mean Square Error (RRMSE); (iii) Bias Ratio (BR); (iv) Expected value based on estimates of the Gini index and; (v) Expected value based on estimates of the coefficient of skewness. Some examples are included, and they indicate how to carry out simulation studies. Finally, various estimators of the Gini index are computed using the data set ES-SILC, with size n=26. The various real data sets can be loaded using the file Datasets.RData.