BUSCADOR RECOLECTA

Materials and methods: Diagnosis of VSP: Vasospasm diagnosis was performed via clinical symptoms, transcranial Doppler, or angiography between days 0 to 14 after the bleeding event. Symptomatic vasospasm was defined as worsening of the level of consciousness of ≥2 points on the Glasgow Coma Scale, or by the appearance of a focal defect (such as hemiparesis, aphasia, apraxia, hemianopia, or neglect) between days 4 and 14 after the bleeding event, not attributable to rebleeding, hematoma, hydrocephalia, metabolic alterations, infection, or oversedation. Transcranial Doppler exploration (Doppler Multidop-P, DWL) was performed with a 2-MHz ultrasound probe through the temporal window, in both hemispheres. The first study was carried out on the third day, and every day between days 3 and 14 after aSAH, and beyond this date if the transcranial Doppler recording was not normal. Transcranial Doppler vasospasm or sonographic vasospasm was defined as the mean flow velocity (MV) in any vessel of anterior cerebral circulation ≥120 cm/s. If the MV obtained reached 120 cm/s, the Lindegaard index was calculated by simultaneously recording the homolateral extracranial internal carotid artery at the submandibular site and the MV of the middle cerebral artery. The MV middle cerebral artery/MV extracranial internal carotid artery ratio of >3 was classified as sonographic vasospasm. Patients with MV >120 cm/s and Lindegaard index <3 were diagnosed with increased cerebral blood flow. Using digital subtraction angiography, angiographic vasospasm was defined as a reduction in the diameter of the cerebral artery by more than two-thirds of its baseline caliber., Supplemental Table 1. Statistical analysis of the expression of surface adhesion molecules in circulating and adherent lymphocytes and monocytes. n= 20 control subjects and 21 patients. *, **, *** P≤ 0.05, 0.01, 0.001., Supplemental Figure 1. Gating strategy for the immunocharacterization of PBMCs. (A) Identification of the cells of interest performed by SSC-A and FSC-A. (B) Singlets filter by FSC-A and FSC-H. (C) Alive cells by exclusion of 7-AAD. (D) Identification of PBMCs by SSC-A and expression of CD45. (E) Identification of lymphocytes and monocytes by SSC-A and expression of CD11b. (F) Identification of lymphocyte subpopulations by expression of CD3 and CD19., Supplemental Figure 2. Expression of surface adhesion molecules in circulating and adhered T lymphocytes and monocytes (these data are the same that are shown on Figure 4 of the manuscript, but shown patient by patient). Only statistically significant changes in the adhesion molecules are presented. Comparisons between experiments from the same patients were assessed by paired t test (* P≤ 0.05 vs. control; #P≤ 0.05 vs. P24h)., Peer reviewed

(A, A’) S9 triple>LanB1RNAi (B) egg chambers stained with anti-LanB1 antibody (green), the DNA marker Hoechst (blue) and the PC marker Fasciclin III (FasIII, red). (B–C’) Stills taken from live imaging of BCs from control (C306Gal4; slboGal4; tslGal4) and C306; slbo; tsl>LanB1RNAi egg chambers. (D) Quantification of the migration defects in egg chambers of the indicated genotypes. The statistical significance of differences was assessed with a t test. Horizontal and vertical lines indicate mean and SD, respectively. Scale bars in A” and B”, 20 μm. The raw data underlying panel D are available in S1 Data., Peer reviewed

(A) Schematic drawing of an early S9 egg chamber illustrating the BCs (yellow), NCs (gray), FCs (purple), BM (green), and the position where AFM measurements were taken (arrow). (B) Comparison of the apparent elastic modulus K in egg chambers of the designated genotypes. (C) Schematic drawing of a middle S9 egg chamber illustrating the BCs (yellow), NCs (gray), FCs (purple), BM (green), the mirror region (pink square) and the positions where AFM measurements were taken, anterior to the mirr region (A, black arrow) and in the mirr region (C, pink arrow). (D, E) Comparison of the apparent elastic modulus K in the mirr region (C) and anterior to the mirr region (E), in 4 control mirrGal4 (D) and mirr>EHBP1mCh egg chambers. A minimum of 4 different readings (circles)/egg chamber were taken. Horizontal lines in B, D, and E represent mean values. The statistical significance of differences was assessed with a t test, * P value < 0.05, ** P value < 0.01, and *** P value < 0.001. Horizontal and vertical lines indicate mean and SD, respectively. The raw data underlying panels B, D, and E are available in S1 Data., Peer reviewed

(A) S10 control tjGal4 and (B) tj>LanB1RNAi (B) egg chambers stained with anti-LanB1 antibody (green), the DNA marker Hoechst (blue) and the F-actin marker Rhodamine-Phalloidin (F-actin, red). (C) Quantification of the LanB1 levels in egg chambers of the specified genotypes. The statistical significance of differences was assessed with a t test, *** P value < 0.001. Horizontal and vertical lines indicate mean and SD, respectively. Scale bars in A and B, 20 μm. The raw data underlying panel C are available in S1 Data., Peer reviewed

This dataset includes very high spatial resolution observations at 1 m spatial resolution observations of the snow depth, the NDVI and the melt-out date (DOY of year) acquired with an Unmanned Aerial Vehicle at a sub-alpine site in the Pyrenees, the Izas Experimental Catchment. During two snow seasons (2019-2020 and 2020-2021), 14 NDVI and 17 snow depth distributions were acquired over 48ha. From the snow depth observations the melt-out dates have been derived. Also information on the main topographic variables (elevation, aspect and slope) is included, with same spatial resolution, in this dataset., Peer reviewed

Supplementary material: Table S1. Summary of UAV acquisition during the study period. DOY: Julian Day of the Year.-- Table S2: Plant species observed on each survey plot.-- Figure S1: Upper panel shows, mean, minimum and maximum daily temperatures (5-day moving average). The lower panel depicts the temporal evolution of the snow depth and the total precipitation observed at the automatic weather station.-- Figure S2: Box plots depicting the temporal evolution of the NDVI for the UAV acquisition dates in the plants survey plots in 2019-2020 (upper panel) and 2020-2021 (bottom panel). The boxes show first and third quantiles and the horizontal line inside each box the second percentile (median). Whiskers of each plot include maximum and minimum values for each plot and day.-- Figure S3: Box plot (upper panel) of ASD spectrometer and Sequoia camera mounted on the UAV for the four bands and the NDVI computed from the near infrared and red bands. Linear adjustment (bottom panel) between the NDVI observations of the UAV and the ASD., Peer reviewed

BC migration in tslGFP; mirrGal4 and tslGFP; mirr> AbiRNAi egg chambers, related to Fig 6. Scale bar, 20 μm., Peer reviewed

The excel file uploaded here contains data collected from livestock farmers across the Chitwan-Annapurna Landscape in Central Nepal. The file includes raw data for farmer\'92s perception rankings, traits, and knowledge corresponding to the questions asked within questionnaires that were conducted as part of the study methodology. The file also includes a legend with definitions for each column in the file., [Methods] Between 2018 and 2019, we conducted 141 interviews with livestock farmers across the Chitwan-Annapurna Landscaoe of Central Nepal. In each of the three study areas, we selected 16-24 villages according to their accessibility, and based on communications with local governmental officials and community leaders. At each village, we approached 1-6 individuals that identified as keeping livestock by a combination method of random and snowball sampling (Cortés-Avizanda et al. 2018, García-Alfonso et al. 2019). All data was collected by hand in the field, and then the corresponding author manually digitized all responses into corresponding entries within Microsoft Excel. Our fieldwork, including survey design and methodology, was conducted with the approval of The City University of New York’s Human Research Protection Program (HRRP) under the category of Human Subject Research (IRB File #2019-0413). In addition, we also received approval for our survey methodology and fieldwork from Nepal’s Department of National Parks and Wildlife Conservation. We sought verbal informed consent before proceeding with the survey, rather than written consent, due to variability in literacy rates, and farmers’ comfort with reading written documents and ability to sign. In accordance with the guidelines of our institution’s HRRP and Institution Review Board, we first read a pre-approved oral consent script aloud to participants that explained the purpose of our study, our local collaborators, and the nature of questions. Participants were assured that their identities would remain anonymous, and no personal identifiers would be recorded from the information collected., [Usage notes] Analyses were conducted using R software 3.3.1 (R Core Team 2016) with ‘glm’ from the stats package for “univariate” (with fixed factor) models, and ‘glmulti’ from the glmulti package (version 1.0.7.1) for multivariate model selection (Calcagno and de Mazancourt 2010). Missing values (e.g., farmer was not asked about species as it was not included in the survey for a given survey area, farmer did not respond to the specific question) are designated as "NA". All analyses omitted NAs, unless otherwise specified in the manuscript., 1. There is a long-standing relationship between humans and vertebrate scavengers, as scavengers’ contributions take on regulating (e.g. nutrient recycling, disease control), material (e.g. competition, livestock depredation) and non-material (e.g. sky burials, ecotourism) roles in society. A social-ecological approach to studying biodiversity is increasingly needed, since the inclusion of local perceptions and knowledge has proven critical for effective conservation programs and ecosystem management., 2. We examine livestock farmers’ perceptions and knowledge related to vertebrate scavengers in the highly diverse Chitwan-Annapurna Landscape (Nepal), and assess the sociodemographic traits that influence their perceived value of scavengers’ ecosystem services provisioning (ESP), and function via scavenging services (SS)., 3. Farmers’ perceptions of functional importance (SS) showed species-specific gradation, unlike ESP, where only avian scavengers were perceived as beneficial. Our results show that the perception of scavenging as a beneficial ecosystem service and its importance as a biological function are decoupled for facultative scavengers, and coupled for obligate scavengers. Relatedly, we identify that affluence-related traits drove positive perceptions of ESP, and local ecological knowledge-based traits were linked to increased knowledge of function via SS., 4. Thus, this increased awareness of functional importance based on close contact with nature does not guarantee positive valuations of scavengers’ contributions, whereas formal education did influence positive perceptions despite reduced awareness of function. Additionally, our findings suggest that existing environmental education measures are targeting the right groups, as these respondents coincide with lower favorability of scavengers’ ecosystem services, but may be unable to overcome existing human-wildlife conflict., 5. For the first time in South Asia, we survey relevant community stakeholder’s attitudes towards an entire scavenging guild and their associated benefits, detriments, and functional importance. Our study illustrates the varied perceptions that exist for different scavenger species, and closely examines a wide-ranging set of sociodemographic traits that show disparate influences on farmers’ knowledge of ecological function and perceived ecosystem service benefits. Crucially, these findings can guide conservation and management priorities by considering the differences in public perception and awareness of scavenging, as well as the interpretation of nature’s contribution to people., Peer reviewed

BC migration in tslGFP; tjGal4 and tslGFP; tj>AbiRNAi egg chambers. Scale bar, 20 μm., Peer reviewed

Figure S1. Correlation chart of environmental variables used for microclimatic models in the PNOMP.-- Table S1. Intercept and significant coefficients of environmental variables included in “microclimatic” Generalized Linear Models, after model selection by Akaike Information Criteria (stepAIC). All models were statistically significant (p<0.001).-- Table S2. Intercept and significant coefficients of environmental variables included in “refugial capacity” Generalized Linear Models, after model selection by Akaike Information Criteria (stepAIC). All models were statistically significant (p<0.001)., Peer reviewed