dataesr/scientific-paragraphs-categorization huggingface dataset:
All measurements are in mm. Specimens shown in Figure  5   Data availability 3D surface models of the described material of M. neogrivensis (reconstructed skeleton, reconstructed skull, carpal bones) are available at MorphoBank with identifier http://morphobank. org/permalink/?P3108. GenBank accession numbers for all the extant taxa considered in the phylogenetic analyses are provided in Supplementary File 2. All other data files are included in the supplementary information. The following dataset was generated: (Table  4 ). The minimum age for the split between Sciurus and Tamiasciurus is given by the oldest record of the former genus, Sciurus olsoni  (Emry et al. , 2005) , dating back to the middle-late Miocene (Clarendonian, 13. 6 -10. 3 Ma) from the Truckee Formation of Nevada (USA)  (Emry et al.
Only Eoglaucomys and the poorly-known genera Aeretes and Biswamayopterus could not be directly compared. Comparisons with Aeretes melanopterus are based on published data  (Thorington et al. , 2002; Thorington et al. , 2012). In addition, the posterior region of the skull of P. petaurista was scanned in order to compare its inner ear morphology to that of M. neogrivensis (see Materials and Methods, Video 4). Several cranial and mandibular measurements were taken in the specimens of M. neogrivensis and some comparative material (see Supplementary file 5-6). Measurements were also taken from the virtually reconstructed cranium of M. neogrivensis using Avizo 7. 0. Cranium. The cranium is relatively short and wide, as in most large-sized flying squirrels but Eupetaurus and a few species of Petaurista, such as Petaurista alborufus (Figure  6 ).
Two major global climatic events are also indicated. The morphological character list is given in Appendix 2. Genbank accession numbers for all the sequences used in phylogenetic analyses are given in Supplementary file 2 and morphological character matrix is given in Supplementary file 3. DOI: https://doi. org/10. 7554/eLife. 39270. 020The following figure supplement is available for figure7: Figure supplement 1. Sciurinae phylogeny and node dating estimates using BEAST. DOI: https://doi. org/10. 7554/eLife. 39270. 021.
Acknowledgements This research has been funded by the  Spanish Agencia Estatal de Investigacion  and the  European Regional Development Fund of the European Union  ( CGL2016-76431-P ,  CGL2017-82654-P ,  RYC-2013 -12470  to IC-V. FJCI-2014 -20380 fellowship to JG-P. ), by the  Generalitat de Catalunya  ( CERCA Programme ), and by the  Handel T Martin Endowment  to  O S. We  further acknowledge the support of the  Servei d'Arqueologia i Paleontologia of the Generalitat de Catalunya. Fieldwork was defrayed by  CESPA Gestion de Residuos, S A U. We thank  M Valls  ( ICP ) for the excellent preparation.
Acknowledgements This work was performed in the context of the European  COST Action   MP1302  Nanospectroscopy. The authors thank the  Lund Laser Center , the  Swedish Research Council  and the  Knut and Alice Wallenberg Foundation. R. C. acknowledges financial support from the  Research Foundation Flanders (FWO , postdoctoral fellowship), and  KU Leuven Research Fund  ( IDO/13/008  and a postdoctoral mandate-PDM). D. T. acknowledges a research grant  DFG-TA 1049/1-1  from the  German research foundation. J. S. thanks  China Scholarship Council  ( CSC ) for Ph. D. fellowship (file 201608110147). J. -Y. L. also thanks the  Swedish Research Council ,  Torsten Söderberg Foundation and ParkinsonFonden; AlzheimerFonden ;  Stiftelsen Olle Engkvist Byggmästare; BAGADI-LICO-Excellence in Parkinson and Huntington Research ; the  Strategic Research Area Multipark (Multidisciplinary research in Parkinson's disease at Lund University) ; EU-JPND research (aSynProtec and REfrAME) and  EU-Horizon2020  ( MSCA-ITN-2016 , SynDeGen), and also  National Natural Science Foundation of China  ( 81430025 ).
Introduction The atomic force microscopy (AFM)  [1]  is a powerful tool for direct visualization of biological samples in an aqueous solution with sub-molecular resolution. It allows non-invasive imaging in physiological conditions of unlabeled biological samples, such as nucleic acids  [2] [3] [4]  and cell membrane proteins  [5, 6]. AFM has rapidly emerged as an effective structural analysis tool, complementing atomic structure data acquired by other techniques such as X-ray crystallography, NMR and electron microscopy. In contrast to these latter methods, which heavily rely on ensemble averaging, AFM exhibits a superior signal-to-noise ratio, enabling molecules to be observed individually under aqueous environment. To acquire a topographic image, a sharp tip attached to the free end of a flexible cantilever is brought into contact and scanned over a sample and its profile height is recorded over the selected scan area.
MATLAB (MathWorks, USA ). This is a proprietary programming language specifically designed for simple and efficient matrix manipulation, data plotting and algorithm implementation (see Note 2). A 30-day trial version is available for free download (https://www. mathworks. com). All the procedures described in section 3. 5 can be carried out in MATLAB software environment. Routines written in this language for batch image processing described in section 3. 5 are available at https://sites. google. com/view/fm4b-lab/group-members/dr-arinmarchesi.
ImageJ (NIH). This is a free, Java-based image processing platform (https://imagej. nih. gov/ij/). Although not specifically designed for AFM image treatment, a number of user-written plugins exists to efficiently tackle several of the procedures described in section 3. 5. A routine written in MATLAB to convert the. asd HS-AFM file format in multipage 32-bit. tiff files supported by ImageJ is available at https://sites. google. com/view/fm4b-lab/group-members/dr-arinmarchesi.
HS-AFM video processing and displaying HS-AFM produces large data sets of image sequences that are affected by a number of instrument-specific peculiarities (such as drift of the piezoelectric elements, contrast discontinuities along the fast-and slow-scan axes, feedback parameters, etc. ) that need to be accounted for before any analysis is performed. Hereafter we provide some clues and suggestions in order to fix these instrument-specific hitches in what we believe is an accurate and time effective manner. 1. Open the HS-AFM data file with your favourite AFM software or programming language. Our own routine to read. asd HS-AFM file formats in MATLAB is available at https://sites. google. com/view/fm4b-lab/group-members/dr-arinmarchesi. To normalize the brightness across all the image stack subtract from each frame the frame average intensity (see Note 30).
Perform a horizontal line-by-line levelling (see Note 35). As the background has been already subtracted, a median (0 order) levelling will suffice (see Note 36). To avoid levelling artefacts make sure to exclude features not belonging to the substrate/background (usually by means of their height) from the computation. Define a region of interest over the substrate and fit the histogram with a Gaussian function to verify that the variance of the background has decreased after the procedure. 6. Fine align all the frames in the stack to a reference image using sub-pixel precision. For this purpose a software package that performs template matching by means of zero mean normalized cross-correlation was developed by our group some time ago  [20]. Alternatively, use the ImageJ plugin Template Matching and Slice Alignment (see Note 32).
Notes 1. Although AFM image processing and analysis is in general best done with the software supplied by the instrument manufacturer, software packages provided with HS-AFM instruments might be rather limited, and more powerful third party packages are often needed. 2. Alternatively, a free software compatible with many MATLAB scripts is GNU Octave (https://www. gnu. org/software/octave/). All the procedures described in section 3. 5 can be implemented in Octave. 3. Mica disks with a diameter of 1. 5 mm are used as sample surfaces. To obtain them, ~ 0. 05 mm thick mica sheets are perforated with a puncher. Careful attention must be paid in the selection of the mica disk. The disk should present a regular and flat border since only areas near the edges will be used for imaging. For gluing the mica disk on the glass-rod it can be used whether cyanoacrylate adhesive or a two-components epoxy adhesive.
So, in the case that after a few cycles of sharpening the required resolution is not achieved, the HS-AFM probe should be replaced. 30. This operation can be implemented in few simple steps using a for Routines perform in MATLAB this and other described processing steps are freely available at https://sites. google. com/view/fm4b-lab/group-members/dr-arinmarchesi. 31. The performance of image registration also depends upon the choice of the reference image (template). To increase the signal-to-noise ratio you shall build your reference image by averaging over several frames (usually 10-20). For this purpose, we recommend to use the median, which is more robust than the mean. Cropping is also commonly used to remove unwanted features from the edges of the averaged image. 32. Mechanical and piezo-scanner drifts may result into movies in which the sequential frames are not perfect real-space superposition.
Acknowledgements This work was supported by  French National Institute of Health and Medical Research (Inserm) ; the program " Investissements d'Avenir " by the  French National Research Agency ,  ANR-10-LABX-0083  ( Labex EFL ); Grant  ANR-16-CE15-0023  ( ANR SalmoTubes ); Grant  ANR-15-CE11-0020  ( ANR MoBaRhE ). A. M acknowledges support from the  Long Term EMBO Fellowship  ( ALTF 1427-2014 ) and the  Marie Curie Action  ( MSCA-IF-2014-EF-655157 ).
ChIP-seq, RNA-seq, and DRIP-seq data set analyses. SETX ChIP-Seq, RNAseq, and DRIP-Seq samples were sequenced using Illumina NextSeq 500 (singleend, 80-bp reads for SETX ChIP-Seq; paired-end, 75-bp reads for RNA-Seq and single-end, 85 bp reads for DRIP-Seq) at EMBL Genomics core facilities (Heidelberg, Germany). The quality of each raw sequencing file (fastq) was verified with FastQC (https://www. bioinformatics. babraham. ac. uk/projects/fastqc/). ChIP-Seq and DRIP-Seq files were aligned to the reference human genome (hg19) and processed using a classical ChIP-seq pipeline: bwa (http://bio-bwa. sourceforge. net/) for mapping and samtools (http://www. htslib. org/) for duplicate removal (rmdup), sorting (sort), and indexing (index). RNA-seq was mapped to a custom human genome (hg19 merge with ERCC92 sequences) to avoid mapping ERCC sequences on the human genome and processed as the same way as ChIP-Seq, except for the alignment in paired-end mode with STAR and without remove potential duplicate.
Coverage for each aligned ChIP-seq data set (. bam) were computed with the rtracklayer R package and normalized using total read count for each sample. Coverage data was exported as bigwig (file format) for further processing. Averaged ChIP-seq, RNA-seq, and DRIP-Seq profiles were generated using the R package ggplot2. For profiles relative to DSB, the x-axis represents genomic position relative to AsiSI site and the y-axis represents the mean coverage at each bp (Fig. 2d ). For metagene profiles, the mean coverage was computed in two parts: first, mean coverage was computed in 200 bp intervals 3 kb upstream TSS and downstream TSS. Second, gene bodies were divided into 100 equally sized bins, so average profiles could be computed as a percent of entire gene length. Profiles were computed for all genes (Supplementary Fig.
Acknowledgements We thank the genomic core facility of EMBL for high throughput sequencing. We are grateful to the  Non-Invasive Exploration service-US006  for the access to the irradiator (Biobeam 8000). We thank  Dr. Lionel Sanz  and  Dr. Frederic Chedin  ( UC Davis ) for providing advice for DRIP experiments. We thank  Dr. Bernard Lopez  ( IGR Paris ) for the NHEJ and HR reporter constructs, as well as  Dr. Jeremy Stark  ( City of Hope ) for the SSA reporter construct. pICE-NLSmCherry and pICE-RNaseHI-NLS-mCherry were a kind gift from  Dr. S. Britton  ( IPBS Toulouse ) We thank  Dr. M. Bushell  ( University of Leicester ) for helpful discussions and data exchange. We also thank  Dr D'adda di Fagagna  ( IFOM ) for sharing unpublished work. M. A. was supported by the  Fondation pour la Recherche Médicale (FRM).
Funding in GL laboratory was provided by grants from the  European Research Council  ( ERC-2014-CoG 647344 ),  Agence Nationale pour la Recherche  ( ANR-14-CE10-0002-01and ANR-13-BSV8-0013 ), the  Institut National contre le Cancer (INCA) , and the  Ligue Nationale contre le Cancer (LNCC, "équipe labelisée").
Spectroscopic observations We collected and retrieved 177 optical spectra of HD 150136 obtained with the Fibre-fed Extended Range Optical Spectrograph (FEROS) mounted successively on the ESO 1. 52 m (for observations before 2002) and on the MPG/ESO 2. 2 m (for observations after 2002) telescopes at La Silla observatory (Chile). These data were partially presented and analysed in  Mahy et al. (2012)  and in  Sana et al. (2013)  but spectra that were newly acquired around the periastron passage of the third component are introduced in the present paper. The monitoring of HD 150136 on FEROS started in 1999, and went on every year until 2016, with breaks in 2007 and in 2010. FEROS provides a resolving power of R = 48 000 and covers the entire optical range from 3800 to 9200 Å. The data were reduced following the procedure described in  Mahy et al.
(2012). We also obtained Director's Discretionary Time (DDT) with the UV-Visual Echelle Spectrograph (UVES; PI: Mahy 297. D-5007, PI: Gosset 295. D-5025, and PI: Gosset 294. D-5041) mounted on the ESO-VLT to acquire eight additional spectra, which we have completed with two additional spectra provided by the EDIBLES team (see  Cox et al. 2017; PI: Cox; Large Programme: 194. C-0833(C)) taken in June and July 2015. These data have a resolving power of R = 80 000. The eight DDT time spectra were acquired with the DIC 2 437+760 setup whilst the spectra taken in June and in July were obtained with the DIC 1 346+564 and the DIC 1 437+860 setups, respectively. The data reduction was performed with the standard reduction pipeline. Finally, we took three spectra of HD 150136 with the CORALIE spectrograph mounted on the Swiss 1.
Photometry We model the light curve of the inner system by using PHOEBE (PHysics Of Eclipsing BinariEs, v0. 31a, Prša & Zwitter 2005) software. The orbital period of the outer orbit being too long, we are not able to see any variations from the tertiary in our light curve. We therefore focus on the parameters of the inner system. We thus keep fixed the parameters of the inner orbit determined through the spectroscopic analysis. PHOEBE allows one to model the light curve and the RV curves of the object at the same time. This software is based on Wilson and Devinney's code  (Wilson & Devinney 1971)  and uses Nelder and Mead's Article number, page 4 of 8 Fig. 2. Left panel: RV curves of the outer system. Black dots represent the systemic velocities of the inner (P+S) system whilst the red ones represent the tertiary component.
Whilst the radii and the rotational velocities of the components agree with the observational measurements, the masses are larger than what we found. A general agreement gives an age between 0 and 2 Myrs for the global system. From their radii and their rotational velocities, the two stars of the inner system are in co-rotation with their orbit. To predict the evolution of HD 150136, we have used the triple-star evolution code TRES  (Toonen et al. 2016). We find that the outer star does not affect the evolution of the inner two stars. As the outer period is three orders of magnitude longer than that of the compact inner orbit, the outer and inner orbits are practically kinematically discoupled. A notorious manifestation of the three-body dynamics are the Lidov-Kozai cycles. During these cycles the mutual inclination and eccentricity of the inner binary vary periodically.
Photometry We model the light curve of the inner system by using PHysics Of Eclipsing BinariEs  (PHOEBE, v0. 31a; Prša & Zwitter 2005)  software. The orbital period of the outer orbit being too long, we are not able to see any variations from the tertiary in our light curve. We therefore focus on the parameters of the inner system. We thus keep fixed the parameters of the inner orbit determined through the spectroscopic analysis. PHOEBE allows one to model the light curve and the RV curves of the object at the same time. This software is based on Wilson and Devinney's code  (Wilson & Devinney 1971)  and uses Nelder and Mead's Simplex fitting method to adjust all the input parameters to find the best fit to the light curve. We take into account the effective temperatures of the inner components determined by  Mahy et al.
From their radii and their rotational velocities, the two stars of the inner system are in co-rotation with their orbit. To predict the evolution of HD 150136, we have used the triple-star evolution code TRES  (Toonen et al. 2016). We find that the outer star does not affect the evolution of the inner two stars. As the outer period is three orders of magnitude longer than that of the compact inner orbit, the outer and inner orbits are practically kinematically discoupled. A notorious manifestation of the three-body dynamics are the Lidov-Kozai cycles. During these cycles the mutual inclination and eccentricity of the inner binary vary periodically. The timescale of these cycles in HD 150136 is about 57 kyrs (based on  Kinoshita & Nakai 1999). A higher order level of interaction (i. e. the octupole level) is not strongly relevant for HD 150136 as estimated by the octupole parameter epsilon ǫ = 0.
According to our simulations, a single main-sequence-like star of ∼ 65 M ⊙ will be created, orbited by the previous tertiary star (see e. g. Glebbeek et al. 2013 , for simulations about high-mass stellar mergers). Article number, page 5 of 8 the components agree with the observational measurements, the masses are larger than what we found. A general agreement gives an age between 0 and 2 Myrs for the global system. From their radii and their rotational velocities, the two stars of the inner system are in co-rotation with their orbit. To predict the evolution of HD 150136, we have used the triple-star evolution code TRES  (Toonen et al. 2016). We find that the outer star does not affect the evolution of the inner two stars. As the outer period is three orders of magnitude longer than that of the compact inner orbit, the outer and inner orbits are practically kinematically discoupled.
Acknowledgements. We are very grateful to our anonymous referee for his or her remarks and comments with the goal of improving our manuscript. This research was supported by the  Fonds National de la Recherche Scientifique  (F. R. S. -F. N. R. S. ), by the  PRODEX XMM contract (Belspo) , and through the  ARC grant for Concerted Research Actions , financed by the  French Community of Belgium (Wallonia-Brussels Federation ). We kindly thank  Nick Cox  and the EDIBLES team for providing advance access to their UVES data for extracting the stellar RV values. AH is supported by the grant  14-02385S  from  GA ČR. Some of the observations obtained with the MPG 2. 2 m telescope were supported by the  Ministry of Education, Youth  and  Sports  project -LG14013 (Tycho Brahe: Supporting Ground-based Astronomical Observations ).
In the BACTH assay, the portion of Rv0613c (Rv0613c 314-550 ) interacting with HBHA represents only one quarter of the entire Rv0613c protein. Thus, the protease subdomain of Rv0613c could be distinct from the HBHA-interacting subdomain. It remains to be determined whether the protease activity of Rv0613c plays any role in HBHA maturation process. In addition to the SEC-C motif, MSMEG_1285 also contains a TPR domain. In spite of some divergence in the N-terminal part, the C-terminal part of the MSMEG_1285 TPR domain is very similar to the corresponding sequence of Rv0613c (Figure  2B ), strongly suggesting that Rv0613c also contains a TPR domain, although it was originally not annotated as such in protein databases. However, the web-based TPRpred tool (Available online: https://toolkit. tuebingen.
Then, a small piece of the membrane (1 cm × 1 cm square) was cut and the bottom side was quickly dried using precision wipes before being attached to a steel sample puck using a small piece of double side adhesive tape. The mounted samples were transferred into the AFM liquid cell while avoiding dewetting. AFM contact mode images and force-distance curves were obtained using a MultiMode 8 AFM (Bruker, Santa Barbara, CA, USA). Measurements were performed in PBS at room temperature using gold-coated Silicon Nitride cantilevers (OMCL-TR400PB, Olympus Ltd. , Tokyo, Japan). The spring constants of the cantilevers were measured using the thermal noise method (NanoScope Analysis software version 8. 15, Bruker), yielding values ranging from 0. 022 to 0. 026 N•m -1. All force measurements were performed using a constant approach and retraction speed of 1500 nm•s -1 , and with an interaction time of 500 ms.
Adhesion maps were obtained by recording 16 × 16 force curves on 400 nm × 400 nm areas of the cells, calculating the adhesion force values and displaying them as grey pixels. Histograms were obtained by pooling the data from several adhesion maps. Data analysis was done using in-house developed pyAF (python Atomic Force) software, version 1. 5. 1. All experiments were performed at least on four different bacteria and with two different heparin-coated AFM tips.
Acknowledgments: We thank  Alain Baulard  ( Institut Pasteur de Lille, France ) for kindly providing the Mtb Erdman library in pUT18C vector and  Carine Rouanet  ( Institut Pasteur de Lille, France ) for providing the sera from Rv0613c-immunized mice. We acknowledge the  BioImaging Center Lille (BICeL)  for access to equipment. This work has been supported by  ANR   10-EQPX-04-01  and  FEDER 12 , 001 , 407  to BICeL. This work was supported in part by the  European Commission Horizon 2020  ( TBVAC2020 ,  H2020-PHC-643381 ).
Whole-mount in situ hybridization Sequences were identified and annotated using combined information from expressed sequence tags and genome databases (GeneBank, http://www. ncbi. nlm. nih. gov; Ensembl, http://www. ensembl. org/index. html). The primers used for probe preparation are listed in supplementary Table  S1. nup133, pax2a, wt1a and cdh17 cDNAs were all isolated by RT-PCR from total RNA from 24-48 hpf embryos and cloned into TOPO pCRII vector (TA Cloning Kit Dual Promoter, Invitrogen) as previously described  55. The resulting plasmids were linearized for SP6 and T7 in vitro transcription and purified with phenol-chloroform. Digoxigenin (DIG)-labeled antisense (or sense, as negative control for nup133 expression) RNA probes were generated using DIG-RNA-labeling kit (Roche Diagnostic).
Semi thin section (2 µm) were stained with toluidine blue and used for histological studies. Ultrathin sections (65 nm) of the glomerulus and the proximal tubules, obtained using a Leica EM FCS ultramicrotome were collected on formvar coated copper grids, stained in lead for 5 minutes to increase the contrast, and examined with a Philips CM-100 scope at 80 kV. Images were acquired using the Gatan Microscopy Software.
nup133 ortholog is broadly expressed at early stages and becomes restricted to specific tissues at later stages Query of the latest version of the genome databases identified a provisional zebrafish Dr nup133 gene (ZFIN:ZDB-GENE-040426-2941; Ensembl:ENSDARG00000010078) containing 26 exons located on the forward strand of chromosome 1. The open reading frame is predicted to encode a protein of 1136 amino acids (aa) that shares 62. 3% overall amino acid identity with human Nup133 (Supplementary Fig. S1 online).