BUSCADOR RECOLECTA

Descripción de los métodos utilizados para la recopilación/generación de datos: • UNIVERSO: Personas residentes en Andalucía con edades iguales o superiores a 18 años. • TAMAÑO DE LA MUESTRA TEÓRICA: 3.192 entrevistas. • TAMAÑO DE LA MUESTRA REAL: 3.190 entrevistas. • TIPO DE ENTREVISTA: Presencial mediante entrevistador, realizada en los domicilios. • TIPO DE MUESTREO: Estratificado con submuestreo por conglomerados, y elección de la unidad final por rutas aleatorias y cuotas de sexo y edad. • ESTRATIFICACIÓN: Se han utilizado dos variables para crear los estratos: la provincia, y una clasificación de secciones según criterios sociodemográficos basada en el Censo de 2001. El estrato final aparece con la combinación de ambas variables. La afijación por provincias es uniforme, con 399 entrevistas en cada una, con el objetivo de obtener un nivel de error inferior al 5% en cada una. La afijación por grupos sociodemográficos es proporcional a la población del universo dentro de cada provincia. • PROCESO MUESTRAL: Las 456 secciones se eligen a través de un muestro sistemático dentro de cada estrato (provincia). • CALIBRACIÓN: Dado que la muestra no es proporcional a la población de cada provincia, se calculan unos pesos que corrigen esta desproporción. • NIVELES DE ERROR: El nivel de error absoluto máximo esperado de los resultados de la encuesta, para las frecuencias de cada variable, es de ±1.9%, para un nivel de confianza del 95%. Para cada una de las provincias este nivel de error es del 5%. • TIEMPO MEDIO DE LA ENTREVISTA: 24,3 minutos., [ES] El objetivo del Ecobarómetro de Andalucía (EBA) es analizar la conciencia ambiental de los andaluces y cómo se relacionan con el medio ambiente. Para ello se elabora un sistema de indicadores a partir de los resultados proporcionados por una encuesta anual dirigida a la población andaluza mayor de 18 años. La encuesta tiene por finalidad medir las distintas dimensiones de la conciencia ambiental (afectiva, cognitiva, activa y conativa), analizando las percepciones, actitudes, conocimiento y comportamiento de los andaluces respecto a diversas cuestiones ambientales. Este dataset corresponde a los resultados obtenidos en la encuesta realizada a una muestra representativa de la población andaluza mayor de 18 años durante los meses de mayo y junio de 2011. El EBA presenta su undécima edición desde que se iniciara en el año 2001. La estabilidad del contenido del cuestionario, así como su comparabilidad con barómetros similares empleados en estudios de ámbito estatal o internacional, lo configuran como un valioso instrumento para el estudio de la opinión pública andaluza en temas de medio ambiente, así como su evolución en el tiempo y sus peculiaridades en el contexto más amplio de las sociedades europeas., [EN] The objective of Andalusian Barometer (EBA) is to analyze the environmental awareness of Andalusians and how they relate to the environment. For this purpose, a system of indicators is elaborated from the results provide by an annual survey directed to the Andalusian population over 18 years of age. The survey aims to measure the different dimensions of environmental awareness (affective, cognitive, active and conative), analyzing the perceptions, attitudes, knowledge and behavior of Andalusians respect different environmental issues. This dataset corresponds to the results obtained in the survey carried out on a representative sample of the Andalusian population over 18 years of age during the months of May and June 2011. The EBA is in its eleventh edition since it began in the year 2001. The stability of the content of questionnaire, as well as its comparability with similar barometers used in national or international studies, make it a valuable instrument for the study of Andalusian public opinion on environmental issues, as well as its evolution over time and its peculiarities in the broader context of the European societies., Research carried out within the framework of a collaboration agreement signed between the Department of Environment of the Regional Government of Andalusia and the Institute for Advanced Social Studies of the Spanish National Research Council (IESA-CSIC)., BAROMETER2011_Datafile.csv BAROMETER2011_Datafile.sav BAROMETER2011_Codebook_EN.pdf BAROMETER2011_Codebook_SP.pdf BAROMETER2011_Readme_EN.pdf BAROMETER2011_Readme_SP.pdf BAROMETER2011_Survey.pdf, Peer reviewed

The dataset contains measurements of Chlorophyll-a (mg m-3), nitrate (μM) and suspended matter (“SM”, g m-3) concentrations, temperature (ºC) and mesozooplankton biovolume (mL 100m-3), collected between 2002 and 2007, in a network of sampling stations (“Station_ID”) distributed across the northeast continental shelf of the Gulf of Cádiz. The year and Julian day (number of days after 1 January) in which each sample was obtained are indicated, as well as their geolocation with latitude and longitude coordinates in degrees. Chlorophyll-a, suspended matter (SM), nitrate and temperature data were taken from the surface layer (<5m) of the water column. Oblique plankton hauls were conducted up to 100 meters using a Bongo net with a 40-cm mouth diameter and 200 mm mesh size, for mesozooplankton sampling., [General Notes] The dataset is provided (“Dataset.txt”) within a compressed folder that also includes a single file in text format (“Readme.txt”) containing a detailed description of the data structure. Dataset.txt file has column titles as the first line. One column is written for each measured variable. Missing data are filled with NaN. Data files are in UTF8 encoding, plain text format with [space] used as the delimiter. The data are provided under an Attribution-ShareAlike 4.0 International license. However, if you use the data, so as to support the authors, please consider citing the above mentioned article where data collection and analytical techniques are given in detail. Here we only give a brief details and a guide to the contents of the data files., [Geographical coordinates of the sampling area] Coordinates.txt file provides the geographical coordinates of the sampling area., This data set includes physical and biogeochemical data collected between 2002 and 2007 on the northeast continental shelf of the Gulf of Cádiz., Data adquisition was supported by projects “Recursos pesqueros del golfo de Cádiz” and “Fluctuaciones y potencialidad de especies pesqueras de plataforma en la región atlántica andaluza” (Junta de Andalucía)., Peer reviewed

Figure S1. Presence/absence of genes coding for potential PAMPs and CWDE across well-annotated genomes of Xylella species. The circles from in to out represent elf18, csp20, chiA, pglA, prtA, lesA and wzy. GBK and fasta files of both the amino acid and nucleotide sequences of the represented genomes were downloaded from the NCBI database. Blast searches were performed using the sequence of X. fastidiosa subsp. fastidiosa Temecula as a template. Blasts using Koala were performed to check for presence absence of the LPS, EPS, and PGN biosynthesis pathway, as well as secretion systems. Table S1. Gene expression to microbial stimuli in xylem tissues. For creating this list, two published datasets were crossed: Wendrich et al., 2020 (https://bioit3.irc.ugent.be/plant-sc-atlas/) and Fröscher et al., 2020. Table S2. Potential PRRs and NLRs in genomes of plants susceptible to X. fastidiosa based on annotation searches. GBK files from each of the host plants' genomes were downloaded from the NCBI database. Then, for retrieving the number of potential PRR and NLR genes we have searched for known protein keywords related to these two families of genes using python custom scripts to parse the GBK files using the Biopython library and specifically SeqIO function. Based on gene name or TAIR locustag (in the case of A. thaliana) we dropped the duplicate genes (splicing products)., Peer reviewed

TotalDat.fits.gz: A FITS table storing information for each of the quasars used in the sample. The names, formats, and contents of each of the columns in this table are described in Table 1. All time-series data (MJD_x, MAG_x, MAG_ERR_x), structure function data (DT_REST_x, SF_x, SF_ERR_x), and PSD data (REST_FREQ_x, CARMA_PSD_x, CARMA_PSD_ERR_L_x, CARMA_PSD_ERR_U_x) are stored as arrays., EnsDat.fits.gz: A FITS table storing information for the ensemble analysis conducted on different subsets of the total sample. The names, formats, and contents of each of the columns in this table are described in Table 2. Similar to the previous file, time-series, structure function, and PSD data are stored as arrays., It should be noted that for each quasar/ensemble, each array will be the same length to conform to the FITS file standards. Therefore, to force each array to be the same shape, arrays shorter than the largest array will be filled with either NaNs or empty strings until they reach this maximum array length. There will be three columns for many of the values, one for each bandpass (g,r,i), also described in Table 1., Peer reviewed

Muscle development is a multistep process that involves cell specification, myoblast fusion, myotube migration, and attachment to the tendons. In spite of great efforts trying to understand the basis of these events, little is known about the molecular mechanisms underlying myotube migration. Knowledge of the few molecular cues that guide this migration comes mainly from studies in Drosophila. The migratory process of Drosophila embryonic muscles involves a first phase of migration, where muscle progenitors migrate relative to each other, and a second phase, where myotubes migrate searching for their future attachment sites. During this phase, myotubes form extensive filopodia at their ends oriented preferentially toward their attachment sites. This myotube migration and the subsequent muscle attachment establishment are regulated by cell adhesion receptors, such as the conserved proteoglycan Kon-tiki/Perdido. Laminins have been shown to regulate the migratory behavior of many cell populations, but their role in myotube migration remains largely unexplored. Here, we show that laminins, previously implicated in muscle attachment, are indeed required for muscle migration to tendon cells. Furthermore, we find that laminins genetically interact with kon-tiki/perdido to control both myotube migration and attachment. All together, our results uncover a new role for the interaction between laminins and Kon-tiki/Perdido during Drosophila myogenesis. The identification of new players and molecular interactions underlying myotube migration broadens our understanding of muscle development and disease., Peer reviewed

Muscle development is a multistep process that involves cell specification, myoblast fusion, myotube migration, and attachment to the tendons. In spite of great efforts trying to understand the basis of these events, little is known about the molecular mechanisms underlying myotube migration. Knowledge of the few molecular cues that guide this migration comes mainly from studies in Drosophila. The migratory process of Drosophila embryonic muscles involves a first phase of migration, where muscle progenitors migrate relative to each other, and a second phase, where myotubes migrate searching for their future attachment sites. During this phase, myotubes form extensive filopodia at their ends oriented preferentially toward their attachment sites. This myotube migration and the subsequent muscle attachment establishment are regulated by cell adhesion receptors, such as the conserved proteoglycan Kon-tiki/Perdido. Laminins have been shown to regulate the migratory behavior of many cell populations, but their role in myotube migration remains largely unexplored. Here, we show that laminins, previously implicated in muscle attachment, are indeed required for muscle migration to tendon cells. Furthermore, we find that laminins genetically interact with kon-tiki/perdido to control both myotube migration and attachment. All together, our results uncover a new role for the interaction between laminins and Kon-tiki/Perdido during Drosophila myogenesis. The identification of new players and molecular interactions underlying myotube migration broadens our understanding of muscle development and disease., Peer reviewed

Muscle development is a multistep process that involves cell specification, myoblast fusion, myotube migration, and attachment to the tendons. In spite of great efforts trying to understand the basis of these events, little is known about the molecular mechanisms underlying myotube migration. Knowledge of the few molecular cues that guide this migration comes mainly from studies in Drosophila. The migratory process of Drosophila embryonic muscles involves a first phase of migration, where muscle progenitors migrate relative to each other, and a second phase, where myotubes migrate searching for their future attachment sites. During this phase, myotubes form extensive filopodia at their ends oriented preferentially toward their attachment sites. This myotube migration and the subsequent muscle attachment establishment are regulated by cell adhesion receptors, such as the conserved proteoglycan Kon-tiki/Perdido. Laminins have been shown to regulate the migratory behavior of many cell populations, but their role in myotube migration remains largely unexplored. Here, we show that laminins, previously implicated in muscle attachment, are indeed required for muscle migration to tendon cells. Furthermore, we find that laminins genetically interact with kon-tiki/perdido to control both myotube migration and attachment. All together, our results uncover a new role for the interaction between laminins and Kon-tiki/Perdido during Drosophila myogenesis. The identification of new players and molecular interactions underlying myotube migration broadens our understanding of muscle development and disease., Peer reviewed

Muscle development is a multistep process that involves cell specification, myoblast fusion, myotube migration, and attachment to the tendons. In spite of great efforts trying to understand the basis of these events, little is known about the molecular mechanisms underlying myotube migration. Knowledge of the few molecular cues that guide this migration comes mainly from studies in Drosophila. The migratory process of Drosophila embryonic muscles involves a first phase of migration, where muscle progenitors migrate relative to each other, and a second phase, where myotubes migrate searching for their future attachment sites. During this phase, myotubes form extensive filopodia at their ends oriented preferentially toward their attachment sites. This myotube migration and the subsequent muscle attachment establishment are regulated by cell adhesion receptors, such as the conserved proteoglycan Kon-tiki/Perdido. Laminins have been shown to regulate the migratory behavior of many cell populations, but their role in myotube migration remains largely unexplored. Here, we show that laminins, previously implicated in muscle attachment, are indeed required for muscle migration to tendon cells. Furthermore, we find that laminins genetically interact with kon-tiki/perdido to control both myotube migration and attachment. All together, our results uncover a new role for the interaction between laminins and Kon-tiki/Perdido during Drosophila myogenesis. The identification of new players and molecular interactions underlying myotube migration broadens our understanding of muscle development and disease., Peer reviewed

Figure S1. Sequencing results of Orai1βE43Q-EGFP (corresponding to the E106Q mutant of the Orai1 α variant) (a) and GECO-Orai1E106Q mutants (b). Figure S2. STIM1, Orai1 variants/mutants and TRPC1 expression in HeLa cells. a HeLa cells were co-transfected with STIM1-CFP, Orai1α-GFP (or dnOrai1α mutant, as indicated), Orai1β-GFP (or dnOrai1β-GFP mutant, as indicated) and TRPC1. Forty-eight hours later cells were lysed and subjected to 10% SDS-PAGE and Western blotting with anti-STIM1 antibody, anti-Orai1 C-terminal antibody or anti-TRPC1 antibody, as described in Material and Methods. Membranes were reprobed with anti-β-actin antibody for protein loading control. Molecular masses indicated on the right were determined using molecular-mass markers run in the same gel. Blots are representative of three separate experiments. b HeLa cells were co-transfected with STIM1 and Orai1α, STIM1 and Orai1β or empty vector (mock). Fura-2-loaded cells were perfused with a Ca2+-free medium (250 μM EGTA added) and then stimulated with TG (1 μM) followed by reintroduction of external Ca2+ (final concentration 1 mM) to initiate Ca2+ entry. c Quantification of Ca2+ entry estimated as described in Material and Methods. Scatter plots are represented as mean ± SEM and were statistically analyzed using Kruskal–Wallis test with multiple comparisons (Dunn´s test). *p < 0.05 as compared to mock-treated cells. Figure S3. Histamine-induced Ca2+ oscillations in mock-treated HeLa cells. a Representative Ca2+ oscillations in response to 3 µM histamine measured using fura-2 in HeLa cells not incubated with plasmids but otherwise treated as cells in Figure 1. Cells were superfused with HBSS containing 1 mM Ca2+ and stimulated with 3 µM histamine at 1 min (indicated by arrow). Representative traces from five cells were chosen to represent the datasets. b-c Quantification of the percentage of oscillating and plateau cells (b) and total oscillations/cell in 10 min (c) for data presented in a (for b, n = 10; n-values correspond to independent experiments; for C n=24; n-values correspond to individual cells). d Quantification of Ca2+ mobilization estimated in mock-treated cells in comparison to cells expressing STIM1, Orai1α, Orai1β and TRPC1 (data from Fig. 1). Scatter plots are represented as mean ± SEM and were statistically analyzed using Mann–Whitney U test to HeLa cells expressing STIM1, Orai1α, Orai1β and TRPC1 (***p < 0.001). Figure S4. Orai1α and Orai1β, but not TRPC1, are required for histamine-induced Ca2+ oscillations. a-h Representative Ca2+ oscillations in response to 3 µM histamine measured using fura-2 in HeLa cells co-transfected with STIM1, Orai1α or Orai1β and TRPC1 or the corresponding dominant negative mutants, as described. Cells were superfused with HBSS containing 1 mM Ca2+ and stimulated with 3 µM histamine at 1 min (indicated by arrow). Representative traces from five cells/condition were chosen to represent the datasets. i-l Quantification of the percentage of oscillating cells (i), percentage of plateau cells (j), percentage of non-responding cells (k) and total oscillations/cell in 10 min (l) for data presented in a-h(for i to k, n = 4-5; n-values correspond to independent experiments; for l, from left to right, n=22, 20, 8, 6, 30, 28, 16 and 11; n-values correspond to individual cells). m-o Quantification of Ca2+ mobilization for all the conditions from a to h estimated in all the cells (m), oscillating cells (n) and plateau cells (o). Scatter plots are represented as mean ± SEM and were statistically analyzed using Kruskal–Wallis test with multiple comparisons (Dunn´s test) to HeLa cells expressing STIM1, Orai1α or Orai1β and TRPC1 (*p < 0.05 and ***p < 0.001), HeLa cells expressing STIM1, Orai1α or Orai1β and dnTRPC1 (for conditions including the expression of dnTRPC1; $p < 0.05 and $$p < 0.01) or the corresponding condition with WT TRPC1 vs dnTRPC1 (#p < 0.05). Figure S5. TRPC1 interacts exclusively with Orai1α. HeLa cells were suspended in HBS containing 1 mM Ca2+ and then stimulated for 1 min with 2 µM TG or the vehicle and lysed. Whole-cell lysates were immunoprecipitated with anti-Orai1 antibody (epitope N-terminal (NT): amino acids 2-61). The immunoprecipitates (pellet) were then subjected to 10% SDS-PAGE and Western blotting with the anti-TRPC1 antibody (a), as described in Material and Methods. Membranes were reprobed with the anti-Orai1 antibody (epitope C-terminal (CT): amino acids 288-301) for protein loading control (c). The supernatant of the immunoprecipitation with anti-Orai1 NT-antibody was further immunoprecipitated with the anti-Orai1 CT-antibody. The pellet was subjected to 10% SDS-PAGE and Western blotting with the anti-TRPC1 antibody (b) and membranes were reprobed with the anti-Orai1 CT-antibody for protein loading control (d). Molecular masses indicated on the right were determined using molecular-mass markers run in the same gel. Blots are representative of five separate experiments. e Quantification of TRPC1-Orai1 association under the different experimental conditions normalized to the Orai1 expression. Scatter plots are represented as mean ± SEM and were statistically analyzed using Mann–Whitney U test. ***p < 0.001 as compared to Control. Figure S6. TRPC1 does not alter either the plasma membrane location or serine phosphorylation of Orai1α. a-b HeLa cells were co-transfected with STIM1-CFP, Orai1α-GFP and TRPC1 (or dnTRPC1 mutant, as indicated). Forty-eight hours later cells were suspended in HBS containing 1 mM Ca2+ and then stimulated with 3 µM histamine. Samples were taken 1s before and 10 s, 1 min and 10 min after the addition of histamine and lysed. Whole-cell lysates were immunoprecipitated with anti-Orai1 C-terminal antibody. The immunoprecipitates were then subjected to 8% SDS-PAGE and Western blotting with specific anti-phosphoserine antibody (a, top panel), as described in Material and Methods. Membranes were reprobed with the anti-Orai1 C-terminal antibody for protein loading control (a, bottom panel). Molecular masses indicated on the right were determined using molecular-mass markers run in the same gel. b Quantification of Orai1α serine phosphorylation under the different experimental conditions normalized to the Orai1α expression. Scatter plots are represented as mean ± SEM, expressed as fold change (experimental/control) and were statistically analyzed using Kruskal–Wallis test with multiple comparisons (Dunn´s test). *p < 0.05 as compared to Control. c-d HeLa cells were co-transfected with STIM1-CFP, Orai1α-GFP and either TRPC1, dnTRPC1 mutant or shTRPC1, as indicated. Forty-eight hours later cells were suspended in HBS containing 1 mM Ca2+, stimulated for 1 min with 3 µM histamine or left untreated and mixed with biotinylation buffer containing EZ-Link sulfo-NHS-LC-biotin. Cell surface proteins were labeled by biotinylation as described in Material and Methods. Labeled proteins were pulled down with streptavidin-coated agarose beads. The pellet (containing the plasma membrane fraction) was analyzed by SDS-PAGE and Western blotting using anti-Orai1α (C terminal) or anti-PMCA antibody, as indicated. Molecular masses indicated on the right were determined using molecular-mass markers run in the same gel. These results are representative of 3 separate experiments. d Quantification of Orai1α plasma membrane expression under the different experimental conditions normalized to the PMCA expression. Scatter plots are represented as mean ± SEM and expressed as fold change (experimental/control (resting cells co-transfected with STIM1-CFP, Orai1α-GFP and TRPC1)). Data were statistically analyzed using Kruskal–Wallis test with multiple comparisons (Dunn´s test). Figure S7. Mn2+ influx in HeLa cells expressing STIM1, Orai1α, Orai1β and TRPC1. a Representative responses to 2 µM TG in HeLa cells co-transfected with STIM1, Orai1α, Orai1β and TRPC1 or mock transfected, as described. Cells were superfused with HBSS containing 0.5 mM Mn2+ and 1 mM Ca2+ and stimulated with 2 µM TG (indicated by arrow). Fura-2 fluorescence was measured at an excitation wavelength of 360 nm, the isoemissive wavelength. Representative traces were chosen to represent the datasets. b Quantification of the rate of decay of fura-2 fluorescence under the different experimental conditions (from left to right, n=28; n-values correspond to individual cells). Scatter plots are represented as mean ± SEM and were statistically analyzed using the Mann–Whitney U test. ***p < 0.001 as compared to mock transfected HeLa cells. Figure S8. Determination of Mn2+ influx in HeLa cells expressing STIM1 and Orai1α or STIM1 and Orai1β. Representative responses to 2 µM TG in HeLa cells co-transfected with STIM1 and Orai1α (a) or STIM1 and Orai1β (b), as described. Cells were superfused with HBSS containing 0.5 mM Mn2+ and 1 mM Ca2+ and stimulated with 2 µM TG (indicated by arrow). Fura-2 fluorescence was measured at an excitation wavelength of 360 nm, the isoemissive wavelength. Traces are representative of 3 independent experiments (n=28-34; n-values correspond to individual cells). Figure S9. Orai1α and Oraiβ modulate Mn2+ influx through TRPC1 in HEK293 cells. a-e Representative responses to TG in HEK293 cells co-transfected with empty vectors (mock cells; a), or expression plasmids for STIM1, TRPC1 and either EYFP-Orai1 (b), the dominant negative Orai1 mutant (c), Orai1α-EGFP (d) or Orai1β-EGFP (e), as described. Cells were superfused with HBSS containing 0.5 mM Mn2+ and 1 mM Ca2+ and stimulated with 2 µM TG (indicated by arrow). Fura-2 fluorescence was measured at an excitation wavelength of 360 nm, the isoemissive wavelength. Representative traces were chosen to represent the datasets. f Quantification of the rate of decay of fura-2 fluorescence under the different experimental conditions (from left to right, n=65, 53, 53, 78 and 70; n-values correspond to individual cells). Scatter plots are represented as mean ± SEM and were statistically analyzed using Kruskal–Wallis test with multiple comparisons (Dunn´s test). ***p < 0.001 as compared to mock cells. $$$p < 0.001 as compared to cells expressing STIM1, Orai1 and TRPC1., Peer reviewed

Supplementary Figure 1. Related to Figure 1. Characterization of the cholinergic system in bone. Supplementary Figure 2. Related to Figure 2. Interleukin-6 induces a cholinergic switch in sympathetic neurons. Supplementary Figure 3. Related to Figures 2 and 3. Interleukin-6 induces a cholinergic switch of sympathetic fibers in bone. Supplementary Figure 4. Related to Figure 4. Osteolineage cells contribute to the non-neuronal cholinergic system. Supplementary Figure 5. Related to Figure 5. GFRa2 loss causes reduced bone thickness and osteocyte degeneration. Supplementary Figure 6. Related to Figure 6. GFRa2 signaling maintains osteocyte connectivity and survival. Supplementary Figure 7. Related to Figure 7. Moderate exercise increases bone cholinergic innervation through sympathetic cholinergic fibers. Table S1. Oligonucleotide sequences used for mouse genotyping. Table S2. Oligonucleotide sequences used for quantitative real-time RT-PCR., Peer reviewed