BUSCADOR RECOLECTA

Crystallographic structure of [Au25(Cys)18], intensity distribution and emission wavelength of white light, time-resolved 1O2 phosphorescence decay of treated silicones, stability test of treated silicones, and comparison of photobactericidal enhancement by [Au25(Cys)18] nanoclusters synthesized through two different synthetic methods., Peer reviewed

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Figure S1: Langmuir balance studies of Aβ42 interaction with membrane lipids. Representative time courses of the change in surface pressure of a lipid monolayer, at the air-water interface, upon addition of Aβ42 monomers into the subphase. Aβ42 stock solution was 50 μM. Aβ42 final concentration in the trough was 1.22 μM. T = 22 °C. Monolayer compositions and state of aggregation of Aβ are given on top of each plot., Peer reviewed

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Figure S1. Flow chart illustrating the workflow for characterizing the probability that a given Sus scrofa high density single nucleotide polymorphism (SNP) genotype could be described under the null hypothesis – descending strictly from contributions from domestic pigs – relative to the alternative hypothesis of allowing for European wild boar ancestry. Table S1. A complete list of the high-density single nucleotide polymorphism (SNP) Sus scrofa genotypes included in the study, with 1,421 reference samples organized into five groups (mixed-commercial breeds, Durocs, heritage breeds, primitive breeds, and European wild boar) for the development of the Delta Likelihood test static, and, for evaluation of the Delta Likelihood approach, a test set of 435 genotypes from 29 additional domestic breeds and 6,566 wild pigs sampled across the invaded range within the contiguous United States. The original publishing source for genotypes is presented in the table with complete references below. Figure S2. Illustration of the genetic structure, as revealed with principal component analysis (plotting principal component 1 versus 2), among the five reference groups of Sus scrofa genotyped with a high-density single nucleotide polymorphism (SNP) array for the development of the Delta Likelihood statistic – an approach to probabilistically describe that a given genotype possesses wild boar ancestry in full or in part (i.e., a wild boar-domestic pig hybrid). Figure S3. Barplots illustrating genetic structure among the 1,421 genotypes that comprise five reference groups of Sus scrofa – organized as mixed-commercial breeds of domestic pig, Durocs, heritage breeds, primitive breeds, and European wild boar – as revealed with high-density single nucleotide polymorphism (SNP) genotypes and leave-one-out analyses conducted in ADMIXTURE (v1.3.0; Alexander et al., 2009) in a supervised framework as described in Smyser et al. (2020). Figure S4. Delta Likelihood statistics calculated from high-density single nucleotide polymorphism (SNP) genotypes for Sus scrofa reference genotypes, organized into reference groups representing mixed-commercial breeds (n = 310), Durocs (n = 159), heritage breeds (n =381), primitive breeds (n = 189), and European wild boar (n = 382); plots represent kernel density estimates of Delta Likelihood statistics for the respective reference groups in which the loci retained for analysis were pruned for linkage disequilbrium (LD) base on the specific reference group listed in the plot title. Pruning for LD based on the heritage reference group resulted in the greatest difference between the upper tail of the kernel density estimate observed among the domestic pig reference groups versus the lower tail of the wild boar reference group (difference of 36.07 when LD pruning was based on the heritage reference group versus 32.72 for the mixed-commercial reference group, 28.79 for Duroc, 35.17 for primitive, and 30.79 for wild boar); thus, the set of 18,790 loci based on the heritage reference set LD prune was retained for subsequent analyses. Table S2. The statistical distribution and associated parameters for respective distributions fitted to Delta Likelihood statistics calculated for domestic pig reference groups (i.e., mixedcommercial breeds, Durocs, heritage breeds, primitive breeds) based on bootstrapped iterations in which the composition of the specific genotypes included in the reference groups were resampled with replacement 1,000 times. Figure S5. Kernel density estimates of Delta Likelihood statistics calculated with 18,790 single nucleotide polymorphic (SNP) loci for Sus scrofa reference genotypes, organized into reference groups representing mixed-commercial breeds (n = 310), Durocs (n = 159), heritage breeds (n = 381), primitive breeds (n = 189), European wild boar (n = 382) and an empirical test set of an additional 29 domestic breeds, represented by 435 genotypes, that were excluded from the reference set. Figure S6. Delta Likelihood statistics calculated from simulated high-density single nucleotide polymorphism (SNP) genotypes (18,790 loci) for Sus scrofa in which genotypes were simulated with R package gscramble (Anderson 2023, R Development Core Team 2023) from fourgeneration pedigrees established by randomly sampling without replacement a total of 16 genotypes from one of four domestic pig reference groups (16 – 1 genotypes drawn from either mixed-commercial, Duroc, heritage, or primitive reference groups) and a complementary number of genotypes (0 – 15) drawn from the wild boar reference group. Following four generations of one-to-one pairing with no inbreeding conducted within the simulation, while allowing for biologically realistic rates of recombination (1 centimorgan per megabase) to reflect the linkage structure among proximate loci and tracking the proportion of each genotype attributable to wild boar ancestry versus domestic pig ancestry, we randomly selected a single simulated genotype for analysis from the 64,000 iterations conducted., Peer reviewed

The Southern Ocean remains one of the most data-deficient ocean basins despite its influence on global climate. Sailboats participating in the Barcelona World Race (2010/2011 and 2014/2015 editions) and the Vendée Globe Race (2020/2021 edition) are used here as opportunity boats to collect sea surface temperature and salinity data, crucial parameters for understanding the changes in Southern Ocean hydrography forced by climate variability in the last decade. We conducted an inter-annual analysis of temperature and salinity anomalies, compared with reanalysis and climatological data for the three race editions to assess changes and variability in the region. Results reveal a warming trend along with a general freshening in the Southern Ocean. The highest anomalies were observed in the Indian and Atlantic sectors, while the Pacific sector showed the lowest anomalies in absolute terms. Notably, our findings reveal correlations between observed anomalies and distinct climate events: lower anomalies in the Pacific sector and elevated anomalies in southeastern South America align with positive Southern Annular Mode events, whereas decreased temperatures coincide with La Niña occurrences. Overall, this study underscores the usefulness of non-research sailing vessels to monitor the evolution of the Antarctic region in response to climate variability, This work has been carried out thanks to European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie Grant Agreement No. 840374. With the institutional support of the ‘Severo Ochoa Centre of Excellence’ accreditation (CEX2019-000928-S), Temperature and salinity of the ocean surface, Peer reviewed

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