BUSCADOR RECOLECTA

Supplementary Figure S1. 1H-NMR spectrum of ascochlorin (1) (CDCl3, 400 MHz); Supplementary Figure S2. ESI/MS (+) spectrum of ascochlorin (1); Supplementary Figure S3. 1H-NMR spectrum of ascofuranol (2) (CDCl3, 400 MHz); Supplementary Figure S4. ESI/MS (+) spectrum of ascofuranol (2); Supplementary Figure S5. 1H-NMR spectrum of (R)-mevalonolactone (3) (CDCl3, 400 MHz); Supplementary Figure S6. ESI/MS (+) spectrum of (R)-mevalonolactone (3); Supplementary Figure S7. 1H-NMR spectrum of ascosalipyrone (4) (CDCl3, 400 MHz); Supplementary Figure S8. ESI/MS (+) spectrum of ascosalipyrone (4); Supplementary Figure S9. 1H-NMR spectrum of benzoic acid (5) (CDCl3, 400 MHz); Supplementary Figure S10. ESI/MS (+) spectrum of benzoic acid (5); Supplementary Figure S11. 1H-NMR spectrum of tyrosol (6) (CDCl3, 400 MHz); Supplementary Figure S12. ESI/MS (+) spectrum of tyrosol (6); Supplementary Figure S13. 1H-NMR spectrum of ascosalitoxin (7) (CDCl3, 400 MHz); Supplementary Figure S14. ESI/MS (+) spectrum of ascosalitoxin (7); Supplementary Figure S15. Images of the symptoms of each of the compounds. Supplementary Table S1. Diseased area (mm2) measured on detached leaves of several legume crops with exudates from the fungus A. fabae growth in vitro on 3 different culture media (Czapek-Dox = CD, potato dextrose broth = PDB, and rice) at concentrations of 0.5, 1, and 2 mg/mL. Negative (blank untreated, water and MeOH 5%) controls were also included. The experiment was repeated four times. Supplementary Table S2. Diseased area (mm2) measured in leaves detached from various legume crops with metabolites produced by the exudate of the A. fabae fungus from the three-growth media at concentrations of 1, 10, and 100 µM. Negative controls (untreated blank, water, and MeOH 5%) were also included. p-value compared with value from MeOH 5% control., Peer reviewed

Silico-DArT and SNP datasets of the IAS pea core collection. Each file contain key information of the molecular markers used to establish the population structure and genetic diversity of the IAs pea core collection., These datasets are part of the research project AGL2017-82907-R funded by MCIN/AEI/ 10.13039/501100011033 and by "ERDF A way of making Europe" and by the project PID2020-114668RB-100 funded by MCIN/AEI/ 10.13039/501100011033., Peer reviewed

11 figuras y 3 tablas con bibliografía al final, Peer reviewed

This dataset encompasses the input files associated with diverse numerical models investigating the hydro-mechanical behavior of a fractured specimen under different mean effective stresses. The folder contains simulations for Hydro-Mechanical ("HM_") problems. The simulations are conducted for different mean effective stresses ("P03"; "P05"; "P10"; "P15"; and "P20"). Within each subfolder, files with the suffix "_gen.dat" provide input data for the model, encompassing material properties, initial and boundary conditions, and time intervals. Correspondingly, files concluding with "_gri.dat" contain information on the mesh employed. To execute a model, launching the executable "Cb_v9_1_3par4.exe" within each ".gid" folder is sufficient., European Research Council (ERC) under the European Union’s Horizon 2020 Research and Innovation Program through the Starting Grant GEoREST (www.georest.eu), under grant agreement No. 801809. IMEDEA is an accredited "Maria de Maeztu Excellence Unit" (Grant CEX2021-001198, funded by MCIN/AEI/10.13039/501100011033)., With funding from the Spanish government through the "Severo Ochoa Centre of Excellence" accreditation (CEX2021-001198)., README.txt (this file) \HM_P03.gid \HM_P05.gid \HM_P10.gid \HM_P15.gid \HM_P20.gid \HM_P20_higherKn.gid, Peer reviewed

The supplemental file provides a description of the model choices and parameters for the Milky Way dark matter density distribution, observational data and definition of the region of interest, and a systematic uncertainty treatment of the background modelling in the likelihood calculation., Peer reviewed

Additional file 1. HFCD feeding induces more severe steatohepatitis in males than females, especially in CD1d−/− mice. a Representative H&E staining of liver sections, scale bar: 100 μm; b body weight; and c liver weight of 6 weeks HFCD-fed Balb/c (WT) and CD1d-KO mice, males or females. n = 8–10. Data are expressed as mean ± SEM, *p < 0.05, **p < 0.005, ***p < 0.001 vs. corresponding HFCD-groups., Instituto de Salud Carlos III Ministerio de Ciencia e Innovación Fundació la Marató de TV3 Agència de Gestió d'Ajuts Universitaris i de Recerca Consejo Superior de Investigaciones Cientificas (CSIC), Peer reviewed

19 páginas, 7 tablas y figuras. Incluye bibliografía., Peer reviewed

Figure S1. SS31 and ER stress inhibition improves aneurysm severity. (A) ApoE−/− mice were infused with saline or angiotensin II (Ang II). Ang II-infused mice were either untreated or treated with SS-31, SS-20, TUDCA or PBA. The histogram shows abdominal aortic aneurysm (AAA) severity in percentage of mice, following the score established by Manning et al (2002). (B) Aneurysm severity in ApoE−/−/Chop−/− (DKO) mice and their littermates (ApoE−/−/Chop+/+) infused with either saline or Ang II. Figure S2. ER stress markers are up regulated in murine AAA. (A-E) Time-course analysis of Hspa5, Atf4, Atf6, Ern1 and Chop mRNA levels assessed by quantitative real-time PCR in abdominal aortas from ApoE−/− mice infused with Ang II. Values shown are the mean ± s.e.m. (n = 6–8). *P < 0.05 vs. t = 0 (one-way ANOVA, post hoc Bonferroni test). Figure S3. Effect of ER stress inhibitors on ER stress and mitochondrial dysfunction markers in the abdominal aorta from Ang II-infused ApoE−/− mice. ApoE−/− mice were infused with either saline or Ang II. Ang II-infused ApoE−/− mice were untreated or treated with either TUDCA or PBA. (A-F) Quantitative analysis of the mRNA levels of Hspa5, Atf4, Atf6, Ern1, Xbp1, sXbp1 and Chop (n = 10–15). (G-I) Abdominal aortic expression of mt-Co3, Dnml1 and Bnip3 were evaluated by real-time PCR (n = 10–15). Values, normalized to Gapdh expression, are shown as mean ± s.e.m. P < 0.05: * vs. saline; # vs. Ang II (one-way ANOVA, post hoc Bonferroni test; or Kruskal Wallis test when data did not fit normality). Figure S4. Effect of SS31 and ER stress inhibitors on cleaved-Atf6 and spliced Xbp1 protein in the abdominal aorta from Ang II-infused ApoE−/− mice. ApoE−/− mice were infused with either saline or Ang II. Ang II-infused ApoE−/− mice were untreated or treated with SS20, SS31, TUDCA or PBA. (A-D) Abdominal aortic protein expression of cleaved-Atf6 and sXbp1 were evaluated by western blot (n = 5–7). Quantitative analysis of the relative protein expression is shown as mean ± s.e.m. P < 0.05: * vs. saline; # vs. Ang II (one-way ANOVA, with Tukey's multiple comparisons test). Figure S5. The expression of both pro-inflammatory and ER stress markers is up-regulated in abdominal aortic aneurysm (AAA) from ApoE−/−/CHOP−/− mice. (A) Il1β, Il6 and Ccl2 mRNA levels (IF: inflammatory) and; (B) Hspa5, Atf4, Atf6, Ern-1 and Chop mRNA levels analyzed by quantitative real-time PCR in abdominal aorta from ApoE−/−/Chop−/− (DKO) mice infused with either saline or Ang II for 28 days were normalized to Gapdh (n = 6). Results are expressed as mean ± s.e.m. *P < 0.05 vs DKO saline (unpaired t-test). Figure S6. Mitochondrial and ER stress inhibition limits the cardiac expression of ER stress and hypertrophic markers induced by Ang II in Apo E−/− mice. ApoE−/− mice were infused with either saline or Ang II, then treated or not with SS31, SS20, TUDCA, or PBA. Quantitative analysis of aortic mRNA levels of Hspa5 (A), Atf4 (B), Atf6 (C), Chop (D), Anp (E) and Myh7 (F) normalized to Gapdh (n = 8). Values shown are mean ± s.e.m. P < 0.05: * vs. saline; # vs. Ang II and SS20 (one-way ANOVA, post hoc Bonferroni test). Table S1. Biochemical profile in all groups of mice. Table S2. Diastolic function parameters in all groups of ApoE−/− mice., Peer reviewed

Additional file 1: Figure S1. Infarct volume and heatmaps of global endothelial DEGs. A) Infarct volume of the PdgfbicreER:Rpl22HA mice. B) Heatmap of DEGs between ischemic and control endothelial cell RNA obtained from the PdgfbicreER:Rpl22HA mice. C) Infarct volume of the group of mice used for cell sorting. Differences in infarct volume between groups shown in (A) and (C) were not statistically significant (Mann–Whitney test, p = 0.69). The graphs in (A) and (C) show values for individual mice and the median and interquartile range. D) Heatmap showing corresponding transcriptomic data from CD31+ cells obtained by cell sorting comparing ischemic vs. control tissue (n = 4 per group and technique). Additional file 2: Table S1. Pathway enrichment analysis for the Pdgf-RiboTag technique Additional file 3: Table S2. Pathway enrichment analysis for the CD31+ cell sorting technique. Additional file 4: Figure S2. Comparison of DEGs in our data sets with published data focusing on BBB dysfunction. A) Endothelial specific and brain tissue specific genes reported by Cleuren et al. [19] were found in our data sets, but they were enriched in the cell sorting data vs. the Ribotag data. B) BBB breakdown is illustrated in brain tissue sections by IgG extravasation at 1-day and 4-day post-ischemia. Quantification of integrated optical density of the IgG signal showed increases in the ipsilateral vs. the contralateral hemisphere at day 1 (n = 6, *p = 0.019) and day 4 (n = 4, *p = 0.020) post-ischemia (Kruskal–Wallis test with Dunn’s multiple comparisons test). The graph shows a violin plot, where each value is represented together with the median and interquartile ranges. Ipsi: ipsilateral, Contra: contralateral. C) Comparison of ischemia induced DEGs with the BBB dysfunction module of genes reported by Munji et al. [6] using GSEA analysis. We identified 44 gene coincidences in the Ribotag data (C) and 74 genes in the CD31+ cell sorting data (E). Corresponding GSEA plot signatures for RiboTag data (D) and CD31+ cell sorting data (F) show good enrichment of the BBB dysfunction module in our data sets. Additional file 5: Figure S3. Validation of expression of cell-type marker genes by RT-PCR. In independent groups of naïve mice (n = 3 per group) we obtained endothelial mRNA by the RiboTag technique using PdgfbicreER:Rpl22HA mice, or by CD31+ cell sorting, as before. We extracted mRNA and carried out RT-PCR for validation of expression of cell markers. We compared the results with mRNA extracted from whole brain tissue (cortex) of naïve mice (n = 4). Values are expressed as fold vs. total brain tissue. Results show that the two methods of endothelial RNA extraction are enriched in endothelial markers, such as CD31 (Pecam1) and Vegfc. However, the platelet derived growth factor receptor beta, Pdgfrb, a marker of pericytes, is also enriched, and Tubb3, a marker of neurons is enriched in the mRNA obtained from the PdgfbicreER:Rpl22HA mice, confirming some contamination with RNA from other cell types in each preparation. ***p < 0.001, **p < 0.01. Two-way ANOVA and Šídák's multiple comparisons test. Data are shown as the mean ± SD. Additional file 6: Table S3. Gene sets differentially expressed in ischemic endothelium commonly found in the RiboTag technique and the CD31+ cell sorting technique. Additional file 7: Table S4. Pathways commonly up- or down-regulated in the RiboTag technique and CD31+ cell sorting technique. Additional file 8: Figure S4. Visualization of functional profiles for gene and gene clusters within DEGs of the ‘Endothelial response to acute ischemia’ module (related to Fig. 4) by means of gene set enrichment analysis with TopGO. Hierarchical relations among inflammatory/immune pathways are highlighted, since they predominated in the acute phase of stroke., Peer reviewed

Contents 1. Properties of ionic liquids used in this work 2. Effective mass of devices 2.1. MCNW devices 2.2. SANW devices 3. Accuracy of the point-mass approximation 3.1. Point-mass at a distance from the free end of the resonator 3.2. Thin film with a given wetting length 4. Comparison of mass measurements from nanomechanical sensing and from Scanning Electron Microscopy imaging 4.1. MCNW devices 4.2. SANW devices 5. Effects of bias voltage polarity and ambient conditions on mass flow control 6. References, Properties of ILs used in this work; characterization of the effective mass of the resonator devices; analysis of the accuracy of the point-mass approximation; comparison of mass measurements from nanomechanical sensing and from SEM imaging; effects of bias voltage polarity and ambient conditions on mass flow control (PDF), Peer reviewed