dataesr/scientific-paragraphs-categorization huggingface dataset:
4). 2. The field inventory is also constituted by many rockfalls (45% of the database), which are difficult to see on satellite images taken at vertical angle 3. Most of the mass movements detected by the field inventory occurred on the road  [36] , which were already cleaned at the time of the satellite acquisitions (at least 2 months after the earthquake, see Table  1 ). These deposits therefore cannot be detected on the satellite images. One exception is a small landslide scar (100 m 2 ) detected in the SPOT5 images, which furthermore matches the location of a mass movement detected on the field. 4. There are uncertainties on the field inventory where no testimony exists, i. e. , in arid regions the growth of vegetation is slow, and it is therefore difficult to really give a date to the observed landslides.
We also get an independent validation of the algorithm over the whole dataset. Indeed, we also realize an expert-based inventory of the largest landslides by screening all the images visually. We estimate our visual detection is complete for landslides of size greater than 40 pixels. We see that all the landslides detected visually are also detected by the automatic procedure. Over one scene (scene 1), 2 inventories are realized taking advantage of the multi-temporal acquisition (2005, 2008, 2010) (Figure  8 ). The 2005-2008 inventory is composed of 219 landslides (for an area of 215,000 m 2 ). The 2008-2010 inventory is composed of 10 landslides for an area of 5,000 m 2. A decrease by a factor 21 in numbers and 43 in area is therefore observed between the periods 2005-2008 and 2008-2010. The multi-temporal inventories show that not all of the landslides detected with 5 years baselines (2005-2010) are co-seismic landslides, but that the effect of the Pisco earthquake is major compared with other triggering factors in this area, and notably the rain effect.
Discussion on the Method The method used has been developed to work with simple datasets: panchromatic images coupled with a freely and globally available DEM. Thus, this method can also be used to realize landslide inventories in others parts of the globe subjected to earthquake activity, including for past events where only panchromatic images are available. It has been successfully applied to derive the first comprehensive landslide inventory triggered by the Pisco earthquake over a wide area (27,000 km 2 ). The detection errors compare favorably to other studies (e. g. ,  [21, 23] ) using other types of datasets (VHR, multi-spectral) in various areas. Commission errors are however larger with our method (50%) than for other studies using multispectral data (20%-25%). However, another study using panchromatic data  [34]  shows branching factors (ratio between the false alarms and the detected landslides) up to 3.
It is thus difficult to compare directly the scores obtained. A comparative study of the various methods with similar datasets would be very interesting for this purpose. The region affected by the Pisco earthquake is arid with limited vegetation. We can therefore wonder what is the applicability of the developed method to other climatic and vegetation contexts. It is first important to note that the precise co-registration is a key step to obtain high score of detection. The coregistration is here realized with a precision better than half a pixel, thanks to the selection of successive images with similar incidence angles (less than 7 • or B/H ratio below 0. 15 (Table  1 )). This prevents the histogram of the difference image from stretching out and thus allows a better definition of the detection thresholds (A).
Conclusions We developed a method for the detection of landslides in optical satellite images, with the purpose to cover extensive areas in arid environment. This method is adapted to the following dataset: high resolution (5 m) panchromatic SPOT5 images, coupled with coarse resolution (posting of 30 m) but freely available DEM (GDEM). The method enables to extract both the number and the area of the landslides. Score of detection reaches 80% of the landslides representing 93% of their area. The detection score, evaluated over two sub-regions where a detailed inventory has been manually obtained, is similar to that of previous studies using satellite images and DEM of better resolutions. The drawback of the method is the resulting high level of false alarms (50%), mainly due to the low resolution of the DEM that prevents picking the small undulations of the topography.
We suggest that this low slope exponent of the power law is related to the type of the soil cover of the study area. Another interesting characteristic of our inventory is the greater average size of landslides oriented parallel to the earthquake rupture. We argue that this particularity highlights the main role of the geomorphology in the propagation of landslides. A first analysis of the obtained database in relation with the topography shows an increase of the susceptibility of the slope to landslide with the slope gradient, and a site effect with flanks facing away from the wave source more susceptible than other flanks directions. Future work will include analysis of this database with the ground movements and with the geological settings, to decipher all these particularities. Because of the simple dataset required to use the proposed methodology, the method can be used for a large set of applications, mostly for covering wide areas, which is of particular interest for co-seismic landslides studies.
Raw MS data from the LTQ-Orbitrap were analysed using the MaxQuant software version 1. 3. 0. 5  (30, 31) , supported by Andromeda  (32)  applying a false-discovery rate for both peptide and protein identification at P 0. 01. MS/ MS spectra were searched against a concatenated S. cerevisiae decoy database from UniprotKB. Two missed cleavage were allowed, and only peptides with a minimum of seven amino acids were considered for identification. After data processing, SILAC quantification (H/L ratios) values from the 'proteinGroups. txt' output file of MaxQuant were taken for further analysis. The protein list was filtered to remove contaminants and reversed sequences. Proteins with a minimum of two measurements (ratio count ! 2) were selected for further analysis, and the H/L ratios were log 2 transformed.
CRAC and sequence analysis In vivo CRAC experiments were performed as described previously  (9). Briefly, cells expressing HTP-tagged Rlp7 and a non-tagged negative control strain were ultraviolet irradiated; cell extracts were then performed and subjected to a first affinity purification on IgG-Sepharose beads. Purified complexes were partially RNase-digested and subjected to a second affinity purification step on a nickel column under denaturing conditions. RNA molecules cross-linked to Rlp7-HTP were ligated to linkers, amplify by RT-PCR and subjected to Solexa sequencing to identify the relative location along the rDNA of the recovered RNA pieces. Similar experiments were performed with HTP-tagged L7 strains. Data analyses were done with the Integrative Genomics Viewer software  (38). In silico analysis of ribosome structure Atomic coordinates of the yeast 60S r-subunit were retrieved from the Protein Data Bank (PDB; www.
rcsb. org) with the accesion number 3U5D and 3U5E  (19). L7 structure was substracted from the 3U5E file (chain F). Rlp7 structure was built with the Modeller 9v2 program (39) using as templates the coordinates provided in pdb files 2ZKR, 3IZR, 3JYW, 3U5E, 3U5E, 3U5I, 3ZF7, 4A1C, 4A1E and 4B6A. Sequence identities percentages of the target versus the templates ranged from 42 (2ZKR) to 48% (3IZR). All models were visualized with the UCSF Chimera program  (40). Secondary structure of pre-and mature rRNAs were taken from Granneman et al. (7)  and The Comparative RNA Web Site (http://www. rna. icmb. utexas. edu/), respectively.
To determine whether Rlp7 and L7 co-exist in the same pre-ribosomal particles, we performed a SILAC experiment combined with LC-MS/MS mass spectrometry to monitor the relative amount of L7 present in affinity purified pre-ribosomal complexes from a strain expressing TAP-tagged Rlp7. We have identified 60 pre-60S factors and most r-proteins from 60S (Rpl) and 40S (Rps) rsubunits (Figure  1  and Supplementary Data Set S1). Proteins clearly arranged in two groups. Group 1 (specifically enriched proteins; log 2 of SILAC ratio between À6 and À1) comprises most Rpl proteins (including L7) and 31 pre-60S factors, in addition to Rlp7, which were strongly enriched in the Rlp7-TAP associated sample; among them, early-acting pre-60S factors including several A 3 factors (Erb1, Nop7, Nsa3, Ytm1 and Nop15)  (6)  were specifically abundant as judged from the total MS signal intensity.
ACKNOWLEDGEMENTS The authors thank  J. L. Woolford , Jr. and  J. Dembowski  for communicating unpublished results,  S. Granneman  for advices with  CRAC ,  D. Tollervey  for providing with models of the ITS2 structure and all colleagues mentioned in the text for their gifts of material used in this study. They are grateful to the proteomic platform of the  Pasteur Institute  for the availability of the Orbitrap.
FUNDING  Spanish Ministry of Science and Innovation and ERDF  [ BFU2010-15690  and  FR2009-0102 ];  Andalusian Government  [ CVI-271  and  P08-CVI-03508  to J. d. l. C. ];  Agence Nationale de la Recherche  [ ANR-2011-BSV6-011-785 02 ];  EGIDE Picasso Programme  (to M. F-R. );recipient of an  FPI fellowship  from the  Andalusian Government  (to R. B. ). Funding for open access charge:  Spanish Ministry of Science and Innovation and ERDF  [ BFU2010-15690  to J. d. l. C. ].
, 2009 , as specified in the SeaRISE project protocol: http://websrv. cs. umt. edu/isis/ index. php/Present_Day_Greenland). We obtain ice temperatures for the two GISM models from a GISM-SIA simulation HO, SIA and SSA are higher order, shallow ice and shallow shelf approximations; SS is steady state; SAT is surface air temperature data used for the spin-up simulation; g-ig is glacial-interglacial. All models use bedrock elevation data from  Bamber et al. (2013)  and geothermal heat flux from  Shapiro and Ritzwoller (2004)  of several glacial-interglacial cycles, rescaling the ice temperature field to the observed ice thickness  (Goelzer et al. , 2013). Geothermal heat flux fields in all spin-up simulations are from  Shapiro and Ritzwoller (2004). Ice temperature spin-up simulations are summarised in Table  1.
Boundary conditions The boundary conditions are geothermal heat flux, ice temperature, bedrock elevation, and projections of SMB. Geothermal heat fluxes are from  Shapiro and Ritzwoller (2004)  and held fixed in the simulations. We also keep the ice temperature fields (determined during initialisation; Sect. 2. 3 and Table  1 ) held fixed because there is negligible ice temperature response to changing atmospheric forcing over two centuries. We use bedrock elevations from the ice2sea data set  (Bamber et al. , 2013)  and hold these fixed because there is negligible isostatic adjustment on this timescale (e. g. Goelzer et al. , 2013). The SMB forcings are therefore the only time-varying boundary conditions. We force the ISMs with "anomalycorrected" SMB projections, S RCM , to remove the mean discrepancy in MAR between the GCM-forced and ERA-INTERIM reanalysis-forced simulations  (Fettweis et al.
Acknowledgements. This work was supported by funding from the ice2sea programme from the  European Union 7th Framework Programme , grant number  226375. Ice2sea contribution number  151. Elmer/Ice simulations were performed using HPC resources from  GENCI-CINES  (grant  2011016066 ) and from the  Service Commun de Calcul Intensif de l'Observatoire de Grenoble (SCCI). S. Price ,  M. Hoffman , and  M. Perego  were supported by the  US De-partment of Energy (DOE) Office of Science, Advanced Scientific Computing Research and Biological and Environmental Research programs. M. Hoffman  was partially supported by the  Center for Remote Sensing of Ice Sheets  at the  University of Kansas  through  US National Science Foundation  grant  ANT-0424589. CISM and MPAS simulations were conducted at the  National Energy Research Scientific Computing Center  and at the  Oak Ridge National Laboratory  (supported by  DOE's Office of Science  under Contracts  DE-AC02-05CH11231  and  DE-AC05-00OR22725 , respectively).
Crystals of the 1-363 fragment (proteolytic cleavage site similar to that described by  Szkaradkiewicz et al. , 2000;  see Supplementary Material 1  for characterization) suitable for X-ray analysis were grown at 294 K via sitting-drop vapour diffusion by mixing 8 ml reservoir solution consisting of 20% PEG 3350 and 0. 2 M ammonium nitrate as precipitants with the same volume of protein solution (in 20 mM HEPES pH 7. 5, 50 mM KCl, 20 mM MgCl 2 , 1 mM DTT); the protein solution was supplemented with 2. 5% glycerol beforehand, incubated for 30 min at 310 K and kept at 277 K overnight. Crystals grew within 1-3 weeks to Data-collection and structure-refinement statistics. The SeMet data were used for phasing and initial model building and the apo IF2 structure was refined against the native data; the other data sets were used for the IF2-GTP and IF2-GDP complexes.
The varying atom numbers are owing to partial disorder of the switch I and II regions and the beginning of domain III. Values in parentheses are for the highest resolution shell. R merge is defined according to XDS  (Kabsch, 2010) ; R work and R free are crystallographic R factors calculated for the work and test data sets  (Bru ¨nger, 1992)  dimensions of up to $130 Â 130 Â 260 mm (the crystals of the GTP complex were smaller). For phasing, selenomethioninelabelled protein was prepared using the methionine-auxotroph Escherichia coli strain B834 (DE3) grown in a medium in which methionine was substituted by selenomithionine (SeMet). The IF2 purification protocol was identical to that for native IF2. The molecular weight of SeMet IF2 as well as the degree of substitution by SeMet was determined by electrospray ionization mass spectrometry (ESI-MS + ), confirming the presence of all 15 methionines in IF2.
Data collection, structure determination and refinement Diffraction data for crystals of apo IF2, SeMet apo IF2, IF2-GTP and IF2-GDP were collected using a PILATUS detector at the Swiss Light Source synchrotron, Switzerland, with a typical exposure time of 2 s and an oscillation range of 1 for apo IF2 and SeMet apo IF2 on PXI and with an exposure time of 1 s and an oscillation range of 0. 1 for the nucleotide complexes on PXIII. Complete SeMet MAD data for apo IF2 were collected at three wavelengths corresponding to peak ( = 0. 97966 A ˚), inflection ( = 0. 97984 A ˚) and remote ( = 0. 97800 A ˚) points with respect to the selenium absorption edge. All X-ray diffraction data were integrated, processed and scaled using the XDS software  (Kabsch, 2010;  see Table  1  for statistics). The SHELXC/D/E programs  (Sheldrick, 2008)  as implemented in the HKL2MAP graphical interface  (Pape & Schneider, 2004)  were used to find and refine the selenium sites in the SeMet IF2 MAD data producing the initial phase set.
Only nine of the 15 possible Se sites were found. Indeed, gel electrophoresis and MALDI peptide mass fingerprinting analysis of the crystals showed that the crystals comprised amino-acid residues 1-363 (40 kDa) of IF2 (Supplementary Fig. 1 ), probably as a result of a spontaneous proteolytic event that occurred during crystallization. A proteolysis site around Arg363 has been confirmed by ESI-MS + analysis of IF2 under denaturating conditions after degradation. The electrondensity map was readily interpretable and automatic tracing was performed with Auto-Rickshaw  (Panjikar et al. , 2005) , which gave an 81% complete initial model that could be extended to encompass all residues (1-363). Refinement was performed against the high-resolution native data using phenix. refine (Afonine et al. , 2012).
The graphics program Coot  (Emsley & Cowtan, 2004)  was used for manual model building, visualization and nucleotide placement. The structures of the nucleotide complexes were determined using the structure of apo IF2 as a starting model in molecular replacement. The switch I and II loops required tracing using maps at lower contour levels (and residues 102-104 were not well defined in the three structures). Figures were prepared with  PyMOL (DeLano, 2002). Fig. 1(c ) was prepared with BioEdit (http://www. mbio. ncsu. edu/bioedit/bioedit. html) using a structure-based sequence alignment, and the secondary-structure annotation scheme was added using Adobe Photoshop. Data-collection and refinement statistics are given in Table  1. Structural alignment gives root-meansquare deviations (r. m. s.
d. s) of 1. 6/0. 6, 1. 5/0. 7 and 1. 2/0. 4 A ˚for overall/optimized (after rejection of residues with a high r. m. s. d. ) superposition of the full apo/GTP, apo/GDP and GTP/GDP complexes, respectively, and of 1. 2/0. 5, 1. 2/0. 6 and 1. 1/0. 3 A ˚, respectively, based on the G domains. The coordi- nates and structure factors have been deposited in the PDB with accession codes 4b3x, 4b48, 4b47 for the apo, GTP and GDP complexes, respectively. (Hendrickson et al. , 1990)  using selenomethionine and was refined to 1. 95 A ˚resolution (see Table  1  for data-collection and refinement statistics; see also Fig. 1 ). The IF2-GTP and IF2-GDP structures were obtained by nucleotide soaking and were refined to 2. 8 and 2. 3 A resolution, respectively (cocrystallization was also attempted but was unsuccessful and provided very small crystals at best; while it is possible that some additional conformational differences may be limited by the crystal lattice, these are probably different again in the fully functional context when IF2 is bound to the ribosome; moreover, cocrystallization would not have been possible with GTP, which can hydrolyze spontaneously if not used in rapid crystal soaking and cooling).
LSHG-CT-2006-031220 ), the  French Infrastructure for Integrated Structural Biology (FRISBI)   ANR-10-INSB-05-01  and Instruct as part of the  European Strategy Forum on Research Infrastructures (ESFRI). AS received a postdoctoral fellowship from the  FRM. The electron-microscope facility is supported by the  Alsace Region, FRM, INSERM, CNRS  and the  Association pour la Recherche sur le Cancer (ARC).
Acta Cryst. (2013). D69, 925-933 Simonetti et al. Protein core of translation initiation factor IF2 927 Figure 1 Crystal structure of IF2. (a) Overall structure of T. thermophilus IF2 (residues 1-363). Domains are annotated and colour-coded: N domain, orange; G domain, blue; domain II, red; beginning of domain III, pink. The switch I and II regions are indicated in green and the nucleotide-binding motifs G1 (P-loop), G2, G3 and G4 are highlighted in cyan. Helix H3N from the N domain and helix H8 from domain III are indicated. (b) Comparison of the T. thermophilus IF2 (this work) and M. thermoautotrophicum a/eIF5B (PDB entry 1g7t, GDPNP complex; Roll-Mecak et al. , 2000) structures showing significant structural differences between the eubacterial and archaeal homologues [IF2 domains are colour-coded as in (a); the view focuses on the structurally conserved core comprising the G domain and domain II; the view is rotated 180 compared with (a) in order to better illustrate the structural differences; the position of the C-terminal region beyond residue 363 of IF2 is indicated by an arrow].
" (F) Graph showing centrosome reorientation with the wound edge cells expressing the indicated constructs. Data are given as means ± SD of three independent experiments, with a total of ≥100 cells. (G) HeLa cells were transfected with the indicated constructs. (left) After 16 h, cells were fixed and stained with the indicated antibodies. (right) The percentage of cell area covered by vimentin was determined. Data are given as means ± SD of three independent experiments, with a total of ≥100 cells. *, P < 0. 05; **, P < 0. 01; ***, P < 0. 005. Higher magnifications of the boxed area in the images are shown on the right. HCX Plan Apochromat 63×/1. 40 NA oil confocal scanning objective (Leica). Microscopes were equipped with a camera (DFC350FX; Leica), and images were collected with LAS software (Leica).
Colocalization of IFs, APC, and microtubules was quantified using the ImageJ software (National Institutes of Health). Statistical analysis was performed using a Student's t test. IF organization in astrocytes. The astrocyte monolayer was scratched, and front cells were immediately microinjected. Cells were fixed after 16 h and stained with antitubulin and antivimentin (or GFAP or nestin) antibodies. Cells at the wound edge were scored as "cells with IF coaligned with microtubules" when the IF network was reorganized along with the polarized microtubule network and filled the protrusion. IF organization in HeLa cells, SW480 cells, HCT116 cells, and U138 cells. Vimentin spreading in HeLa cells was quantified as the ratio of the vimentin spreading area and the total cell area. The vimentin spreading area and the total cell area were manually determined using images of vimentin staining and GFP, HA, or tubulin staining.
Fig. S3  shows that the role of APC in IF organization does not involve -catenin-mediated transcription or APC function at microtubule plus ends and is not correlated with APC-mediated regulation of microtubule stability. Table  S1  shows the sequences of the various siRNA used in this study. Online supplemental material is available at http://www. jcb. org/ cgi/content/full/jcb. 201206010/DC1. Additional data are available in the JCB DataViewer at http://dx. doi. org/10. 1083/jcb. 201206010. dv. We are particularly grateful to I. Nathke and D. Pham-Dinh for plasmids and reagents. We thank C.
Machu and P. Roux from the Plate-Forme d'Imagerie Dynamique/Imagopole of Institut Pasteur, D. Vignjevic and S. Robine for technical support, and S. Carbonetto and J. -B. Manneville for critical reading of the manuscript. Y. Sakamoto is funded by the Uehara Memorial Foundation, and B. Boëda is supported by Institut National de la Santé et de la Recherche Médicale. This work was supported by the Agence Nationale pour la Recherche, the Institut National du Cancer, the Fondation Association pour la Recherche contre le Cancer, and La Ligue contre le Cancer. S. Etienne-Manneville's laboratory participates in the Nanomechanics of intermediate filament networks European Cooperation in Science and Technology action (BM1002). All siRNA duplexes were obtained from Proligo (TableS1). siRNAconstructs were introduced into rat astrocytes by nucleofection technology (Amaxa Biosystems;Etienne-Manneville, 2006).
02. 003 Bershadsky, A. D. , E. A. Vaisberg, and J. M. Vasiliev. 1991. Pseudopodial activity at the active edge of migrating fibroblast is decreased after druginduced microtubule depolymerization. Cell Motil. Cytoskeleton. 19:152-158. http://dx. doi. org/10. 1002/cm. 970190303 Bugyi, B. , and M. F. Carlier. 2010. Control of actin filament treadmilling in cell motility. Annu. Rev. Biophys. 39:449-470. http://dx. doi. org/10. 1146/ annurevbiophys051309103849 Cahoy, J. D. , B. Emery, A. Kaushal, L. C. Foo, J. L. Zamanian, K. S. Christopherson, Y. Xing, J. L. Lubischer, P. A. Krieg, S. A. Krupenko, et al. 2008. A tran scriptome database for astrocytes, neurons, and oligodendrocytes: a new.
IFNa/v-DC and IFNb-DC show differential gene expression profile Monocytes were differentiated into DC using GM-CSF and different type I IFN subtypes. In order to investigate effects not caused by different specific activities in inducing early transcriptional response, IFN concentrations were adjusted as described in the materials and methods section. First, the transcriptomes of IFNa1, a2, a8, a21 and b-derived DCs differentiated from monocytes isolated from the same individual were investigated by using HG-U133 Plus 2. 0 Affymetrix microarrays. In order to identify correlated gene expression patterns, unsupervised hierarchical clustering was applied to microarray data meeting the following criteria: the gene must be present in a least 80% of the samples and the deviation standard of the signal must be superior to 10%.