BUSCADOR RECOLECTA

These datasets include the input files for HydroGeoSphere used in this study., Storm surges associated with tropical cyclones endanger atolls through groundwater flooding, where groundwater is discharged from the land surface as the sea level rises. Atolls are characterized by a “dual-aquifer” configuration, where recent Holocene sediments unconformably overlie highly permeable Pleistocene limestone, creating an interface called a “Thurber discontinuity.” This study aimed to quantitatively analyze how the dual-aquifer configuration of atolls controls the temporal dynamics of groundwater flooding caused by storm surge. To this end, we ran surface-subsurface coupled synthetic numerical simulations using HydroGeoSphere and compared 12 scenarios with different Thurber discontinuity elevations and hydraulic conductivities of the Pleistocene aquifer (KP). The results showed that the shallower the Thurber discontinuity and the higher the KP value, the higher the maximum water depth in the freshwater swamp on the atoll during the storm surge and the longer the flooding duration. Despite the effects of the different dual-aquifer configurations, the initial water table elevation and salinity distribution were almost identical in all the simulation cases. These findings suggest that accurate information on the dual-aquifer configuration is necessary to evaluate the potential risk of groundwater flooding on atolls accompanying storm surges. Furthermore, the results indicate that groundwater flooding caused by storm surges substantially contributes to cyclone-driven flooding on atolls, and hence, it should not be neglected in flood predictions to avoid underestimation., Peer reviewed

Data and script to generate figures in GRL paper entitled "The relation between dissipation and memory in two-fluid displacements in disordered media" by R. holtzman et al., We show that the return-point memory of cyclic macroscopic trajectories enables the derivation of a thermodynamic framework for quasistatically driven dissipative systems with multiple metastable states. We use this framework to sort out and quantify the energy dissipated in quasistatic fluid-fluid displacements in disordered media. Numerical computations of imbibition–drainage cycles in a quasi-2D medium with gap thickness modulations (imperfect Hele-Shaw cell) show that energy dissipation in quasistatic displacements is due to abrupt changes in the fluid-fluid configuration between consecutive metastable states (Haines jumps), and its dependence on microstructure and gravity. The relative importance of viscous dissipation is deduced from comparison with quasistatic experiments., Peer reviewed

Matlab codes to calculate ensemble and effective dispersion for the case of reversal of the flow field, analytically by applying linear stochastic theory and numerically based on particle-tracking random-walk. Codes belong to the manuscript: Stettler, M.-M., O.A. Cirpka, M. Dentz: Linear Stochastic Analysis of the Partial Reversibility of Ensemble and Effective Dispersion in Heterogeneous Porous Media. Water Resour. Res. (submitted), 2022., Macrodispersion in heterogeneous formations is caused by spatial variability of the velocity field, making different parts of a plume experience different advective displacements. Differential advection interacts with diffusion, which hardly affects longitudinal ensemble dispersion (i.e., the spread of the ensemble-averaged concentration) but determines effective dispersion, that is, the expected spread of individual plumes for point injections. The latter has been suggested as metric of solute mixing. Pure advection is fully reversible, whereas diffusion is completely irreversible. We quantify the partial reversibility of macrodispersion by analyzing the second central ensemble and effective spatial moments for advective-diffusive transport in heterogeneous domains with flow reversal, applying linear stochastic theory to approximate the corresponding moments and comparing them to particle-tracking random-walk simulations in periodic media. Diffusion causes solute particles to deviate from their forward trajectories when flow is reversed. As long as advective memory dominates, both types of second central moments decrease during backward motion, then reach a minimum, and increase again. The reversibility is considerably bigger for ensemble than effective dispersion but the latter also shows partial reversibility, challenging its use as metric of mixing. The stronger diffusion is in comparison to advection, the less reversible dispersion becomes. After equally long times of forward and backward motion, the two types of second central moments differ, but to a much smaller extent than in pure forward motion. In realistic settings, the advective memory affects dispersion so strongly that the asymptotic regime is not reached before the plume center has returned to its origin., Peer reviewed

Per- and polyfluoroalkyl substances (PFAS) are a group of persistent organic contaminants of which some are toxic and bioaccumulative. Several PFAS can be formed from the atmospheric degradation of precursors such as fluorotelomer alcohols (FTOHs) as well as hydrochlorofluorocarbons (HFCs) and other ozone-depleting chlorofluorocarbon (CFC) replacement compounds. Svalbard ice cores have been shown to provide a valuable record of long-range atmospheric transport of contaminants to the Arctic. This study uses a 12.3 m ice core from the remote Lomonosovfonna ice cap on Svalbard to understand the atmospheric deposition of PFAS in the Arctic. A total of 45 PFAS were targeted, of which 26 were detected, using supercritical fluid chromatography (SFC) tandem mass spectrometry (MS/MS) and ultra-performance liquid chromatography (UPLC) MS/MS. C2 to C11 perfluoroalkyl carboxylic acids (PFCAs) were detected continuously in the ice core and their fluxes ranged from 2.5 to 8200 ng m-2 yr-1 (9.51-16,500 pg L-1). Trifluoroacetic acid (TFA) represented 71 % of the total mass of C2 - C11 PFCAs in the ice core and had increasing temporal trends in deposition. The distribution profile of PFCAs suggested that FTOHs were likely the atmospheric precursor to C8 - C11 PFCAs, whereas C2 - C6 PFCAs had alternative sources, such as HFCs and other CFC replacement compounds. Perfluorooctanesulfonic acid (PFOS) was also widely detected in 82 % of ice core subsections, and its isomer profile (81 % linear) indicated an electrochemical fluorination manufacturing source. Comparisons of PFAS concentrations with a marine aerosol proxy showed that marine aerosols were insignificant for the deposition of PFAS on Lomonosovfonna. Comparisons with a melt proxy showed that TFA and PFOS were mobile during meltwater percolation. This indicates that seasonal snowmelt and runoff from post-industrial accumulation on glaciers could be a significant seasonal source of PFAS to ecosystems in Arctic fjords., Peer reviewed

This project aimed to collect temperature (T) and salinity (S) data from an opportunity vessel along the course of the Ocean Globe Race. It also aimed to develop an automated method to denoise such type of time series. Results show good accuracy in the filtering process and significant gains in time efficiency of the filtering process, ERC-2024-StG FRESH-CARE (Grant Agreement:276 101164517). With the institutional support of the ‘Severo Ochoa Centre of Excellence’ accreditation (CEX2019-000928-S), Time is in format YYYY MM DD hh mm ss, in one single CSV column. Latitude and Longitude are in decimal expression, with longitude range from -180º to 180º; legX.dat are files containing raw T,S data; flasks.fk contains bias correction data from water samples taken during legs 2, 3 and 4; outDenoise_legX.dat are files with updated quality control label,s according to denoising processing; constSBC_outDenoise_legX.dat are files with a constant bias correction of +0.130 in salinity, which is done after denoising; leg2.dat; leg3.dat; leg4.dat; flasks.fk; outDenoise_leg2.dat; outDenoise_leg3.dat; outDenoise_leg4.dat; constSBC_outDenoise_leg2.dat; constSBC_outDenoise_leg3.dat; constSBC_outDenoise_leg4.dat, Peer reviewed

Figure S1: Results of the FRET-Melting Assay at 1 μM ligand concentration; Figure S2: UV-Vis spectra of ligand (A) 1, (B) 2, (C) 3 and (D) 4 titrated with mit9438-K+ at the concentrations shown in the figure; Figure S3: UV-Vis spectra of ligand (A) 1, (B) 2, (C) 3 and (D) 4 titrated with SA5-K+ at the concentrations shown in the figure; Figure S4: UV-Vis spectra of ligand (A) 1, (B) 2, (C) 3 and (D) 4 titrated with EBR1-K+ at the concentrations shown in the figure; Figure S5: UV-Vis spectra of ligand (A) 1, (B) 2, (C) 3 and (D) 4 titrated with ds26-K+ at the concentrations shown in the figure; Figure S6: UV-Vis binding isotherm for the association between ligand (A) 1, (B) 2, (C) 4 and mit9438, SA5, EBR1 and ds26 following the change in ligand absorbance at (A) 350 nm, (B) 410 nm and (C) 450 nm; Figure S7: Results of cell uptake exhibited by compounds 1–4 at 1 µM for 15, 30 and 60 min at room temperature on (A) A. baumannii and (B) S.aureus; Table S1: Results of the FRET-Melting Assay carried out with ligands 1–4 at 5 µM; Tabla S2: Synergistic combinations for S.aureus., Peer reviewed

The full pipeline of the analysis is in the file **Alternative_splicing_project_code.sh**, this file will redirect you to other scripts also present in this repository. An outline summary of the contents of the scripts is: -Extract_isoforms_from_multisoform_genes.R: Extraction of multiform genes from the Anopheles gambiae genome (VectoBase,Release 54) -Repeticion_DESEQ_Isoformswitch_Inf_vs_Inf.R: Obtain Differential expressed isoforms of multisoform genes (DEMG) in the Inf MG vs. Inf SG comparison Quantification of the usage with IsoformSwitchAnalyzeR, obtaing isoforms differentially used (DUI) in the Inf MG vs. Inf SG comparison Comparison of our DEMG and DUI isoforms with genes present in the paper https://malariajournal.biomedcentral.com/articles/10.1186/1475-2875-12-216 -Repeticion_DESEQ_Isoformswitch_Inf_vs_ctrol.R:Obtain Differential expressed isoforms of multisoform genes (DEMG) in the Ctrl vs. Inf MG and Ctrl MG vs. Inf SG comparisons Quantification of the usage with IsoformSwitchAnalyzeR, obtaing isoforms differentially used (DUI) in the Ctrl vs. Inf MG and Ctrl vs. Inf SG comparisons Comparison of our DEMG and DUI isoforms with genes present in the paper https://malariajournal.biomedcentral.com/articles/10.1186/1475-2875-12-216 -Script_volcanos_percent_DUI_vs_DEMG.R: Obtain the volcano plot of DEMG vs DUI in the Inf MG vs. Inf SG comparison -AS_mechanism_by_conditions.R: See how many type of events apear in the DEMG and DUI isoforms of the Inf MG vs. Inf SG comparison -Check_overlaping_zones.R: How to check for overlapping areas by removing overlapping genes with promoters of our isoforms and calculate the correlation of the DEMG group without these overlapping genes. -Files_correlations_DEG_DUI.sh: Enrichment counts at promoters and in the body of isoforms, these counts are necessary for the study of the correlation between expression and accessibility -Correlation_DEMG_without_overlap.R: To see if there is a correlation between the expression and accessibility of the DEMG isoforms in the comparison Inf MG vs. Inf SG -DEMG_correlation_by_levels_without_overlap_expression.R: To see if there is a correlation between the levels of expression and accessibility of the DEMG isoforms in the comparison Inf MG vs. Inf SG. i.e. More expressed isoforms have also more accessibility in the promoter or in the gene body -Comparison_diffbind_peaks_with_splicing_sites_100bp_without_overlapping_genes.R: We searched for DiffBind peaks that matched splicing sites of our DUI isoforms -Motif_analysis_diffbind_splicing_sites_DUI.R: With the diffbind peaks coincident with splicing sites in the DUI we will do a motif analysis. We do the same with these peaks that are also located in splicing events of the exon skipping type -Merge_enhancers_with_DEMG_DUI.R: How we extract enhancers known by other authors and by our group taking Drosophila orthologs and we look how many of them are present and active in our groups of DEMG and DUI -Merge_enhancers_with_Diffbind_DEMG_DUI.R: Extract enhancers which has a DiffBind peak and also matches with our DEMG and DUI isoforms -Mergging_enh_with_SS.R: Extract enhancers with the Splicing Sites of our DEMG and DUI isoforms -Merge_enhancers_with_NOmultisoform.R: Extract enhancers known by other authors and by our group taking Drosophila orthologs and we look how many of them are present and active in No multisoform genes -Merge_enhancers_with_Diffbind_NOmultisoform.R: Extract enhancers which has a DiffBind peak and also matches with the NO multisoform genes -Mergging_enh_with_SS_NOmultisoform.R: Extract enhancers with the Splicing Sites of the NO multisoform genes, Analysis channel used in the article: Alternative splicing and its regulation in the malaria vector Anopheles gambiae, Alternative splicing (AS) is a highly conserved mechanism that allows to expand the coding capacity of the genome, by modifying the way multiple isoforms are expressed or used to generate different phenotypes. Despite its importance in physiology and disease, genome-wide studies of AS are lacking in most insects, including mosquitoes. Even for model organisms, chromatin associated processes involved in the regulation AS are poorly known. In this study, we investigated AS in the mosquito Anopheles gambiae in the context of tissue-specific gene expression and mosquito responses to a Plasmodium falciparum infection, as well as the relationship between patterns of differential isoform expression and usage with chromatin accessibility changes. For this, we combined RNA-seq and ATAC-seq data from A. gambiae midguts and salivary glands, and from infected and non-infected midguts. We report differences between tissues in the expression of 456 isoforms and in the use of 211 isoforms. Secondly, we find a clear and significant association between chromatin accessibility states and tissue-specific patterns of AS. The analysis of differential accessible regions located at splicing sites permitted the identification of several motifs resembling the binding sites of Drosophila transcription factors. Finally, the genome-wide analysis of tissue-dependent enhancer activity revealed that approximately 20% of A. gambiae transcriptional enhancers annotate to a differentially expressed or used isoform and that their activation status is linked to AS differences between tissues. This research elucidates the role of AS in mosquito vector gene expression and identifies regulatory regions potentially involved in AS regulation, which could be important in the development of novel strategies for vector control., Peer reviewed

Soil and its biota play fundamental roles in plant development and ecosystem functioning by regulating nutrient cycling, organic matter decomposition, and soil structure. Among them, earthworms (EWs) act as ecosystem engineers, enhancing soil aeration, nutrient availability, and microbial activity, with potential benefits for plant growth and pest control. Their coelomic extract (CEx) contains bioactive compounds that may induce plant defense responses; however, the mechanisms behind these effects remain poorly understood. This study evaluated the impact of EWs and their CEx on Solanum lycopersicum (tomato), assessing growth, nutrient content, and defense against the foliar fungal pathogen Botrytis cinerea. Plants were exposed to EWs, CEx, or water (control) and inoculated with B. cinerea after two weeks. Plant defense was monitored via expression of key defense-related genes at 24- and 48-hours post-inoculation (hpi), while growth, nutrient content, and fungal abundance and damage were assessed at 72 hpi. EWs enhanced aerial biomass, while both EWs and CEx reduced root dry weight, suggesting resource reallocation to aboveground growth. CEx significantly reduced B. cinerea-induced leaf damage and increased flavonol levels, a known marker of induced resistance. Both EWs and CEx activated the jasmonic acid signaling pathway, with CEx specifically upregulating genes involved in fungal pathogen defense and sustaining their expression over time. These results highlight the potential of EWs and their secretions to promote plant immunity and resilience, reinforcing their value in sustainable agriculture and the role of soil biodiversity in crop protection strategies., The CSIC i-coop+ 2018 grant (COOPA20231) and Instituto de Estudios Riojanos (IER), Government of La Rioja, Spain, ref. 8/2020, December 29th 2020. MC was supported by the mobility program stablished by the CSIC i-coop+ 2018 grant (COOPA20231). IVD is supported by FPI-UR (2021) fellowship from the University of La Rioja (Spain). RBP is supported by the contract Juan de la Cierva (JDC2022-048978-I) from the “European Union NextGenerationEU/PRTR” and MCIN/AEI/10.13039/501100011033. JDH is supported by the Programa Investigo from the Government of La Rioja and the “European Union NextGenerationEU/PRTR., Peer reviewed

Table S1: Comparative analysis of BBB penetration by studies of lipid nanoparticles, both unmodified and modified with commonly used materials such as surfactants or PEGylated lipids. -- Figure S1. Graphical illustration of the distribution of studies with lipid nanoparticles unmodified or modified with regularly used materials such as surfactants or PEGylated lipids. -- Figure S2. Scree plot for principal component analysis of studies with permeation enhancement ratio. -- Figure S3. Score plot for principal component analysis of studies with permeation enhancement ratio. -- Figure S4. Loading plot for principal component analysis of studies with permeation enhancement ratio. -- Figure S5-A: Classification and Regression tree (CART®) for permeation enhancement ratio, particle size, type of lipid nanoparticle, and category of functionalization, nodes 1 to 13, terminal nodes 1, 6 to 11. -- Figure S5-B: Classification and Regression tree (CART®) for permeation enhancement ratio, particle size, type of lipid nanoparticle and category of functionalization, nodes 6 to 9, and terminal nodes 2 to 6. -- Figure S5-C: Classification and Regression tree (CART®) for permeation enhancement ratio, particle size, type of lipid nanoparticle, and category of functionalization, nodes 14 to 16, and terminal nodes 12 to 16. -- Figure S6. Chart of relative variable importance for the Classification and Regression tree (CART®) for permeation enhancement ratio, particle size, type of lipid nanoparticle, and category of functionalization. -- Figure S7. Scatterplot for particle size and permeation enhancement ratio. -- Figure S8. Main effects analysis of permeation enhancement ratios., Peer reviewed

Table of Contents: Table S1. Total PQSs and PQS densities (per 100000 nucleotides) of sequences analyzed. Table S2. Most frequent PQSs harbouring already confirmed G4s in literature and the G4-iM Grinder database (version 2.502) per genome of T. cruzi analyzed. Table S3. Total PQSs with high G4-probability (that score ≥ 40), per genome of T. cruzi analyzed. Table S4. Most frequent PQSs with high G4-probability (that score ≥ 40), per genome of T. cruzi analyzed. Figure S1. Characterization of T. cruzi sequences (DCr, RCr, TCr and MCr) by NMM fluorescence assay. Figure S2. Characterization of T. cruzi sequences (DCr, RCr, TCr and MCr) by thermal difference spectra (TDS). Figure S3. Characterization of T. cruzi sequences (DCr, RCr, TCr and MCr) by isothermal difference spectra at 25 °C (IDS). Figure S4. CD melting curves of T. cruzi sequences (DCr, RCr, TCr and MCr) at 25 °C. Figure S5. CD spectra of RCr sequence in the presence of 100, 10 and 1 mM K+ concentration. Figure S6. Imino region of the proton-NMR spectra of RCr, TCr, MCr and DCr sequences. Figure S7. Imino region of the proton-NMR spectra of RCr sequence at different temperatures. Figure S8. Isomerisation of L3 to L4 followed by 1H NMR. Figure S9. Isomerisation of L5 to L6 followed by 1H NMR. Figure S10. Isomerisation of L7 to L8 followed by 1H NMR. Figure S11. Isomerisation of L11 to L12 followed by 1H NMR. Figure S12. Isomerisation of L13 to L14 followed by 1H NMR. Figure S13. FRET melting assay. FRET melting curves of A) F-MCr-T, B) F-TCr-T, C) F-21-T, D) F-MYC-T (all fluorescently labeled) DNA quadruplexes (0.2 μM) and E) F-dx-T DNA duplex (0.2 μM) in the absence and in the presence of the tested compounds L3 and L4 (10 μM). Figure S14. Competition FRET melting experiments run on A) F-21-T or B) F-RCr-T, for ligands L3 and L4 in the presence of increasing concentrations of ds26 competitor (0, 1, 3, 10 M). Figure S15. Imino region of the 1H-NMR spectra of A) RCr, B) TCr or C) MCr in aqueous buffer solution in the absence and presence of compound L3 or L4. Figure S16. CD melting curve of RCr quadruplex in the absence and presence of compound L4. Figure S17. CD melting curve of MCr quadruplex in the absence and presence of compound L3 and L4. Figure S18. UV spectra of L3 (A) or L4 (B) in the absence and presence of MCr or RCr DNA quadruplexes. Figure S19. UV spectra of L3 (A) or L4 (B) in the absence and presence of ds26 duplex DNA. 1H-NMR and 13C-NMR Spectra of the new compounds HPLC traces of compounds L3 and L4., Peer reviewed