dataesr/scientific-paragraphs-categorization huggingface dataset:
post-mitotic neurons (D), and Neurog1+ sensory progenitors (E) between E10. 5 and E14. 5 in WT (blue curve) and Neurog2 À/À embryos (2 À/À , green curve). For each genotype, at least 3 embryos were analyzed at all stages. Data are represented as means ± SEM. *p < 0. 05; **p < 0. 01; ***p < 0. 001. (F) Quantification of Sox10+ cells at E10. 5 and E11. 5 in thoracic DRG of WT (blue columns; n = 4 at E10. 5 and n = 8 at E11. 5) and Neurog2 À/À embryos (2 À/À , green columns; n = 5 at E10. 5 and n = 10 at E11. 5). Data are represented as means ± SEM. ***p < 0. 001. See also Figures  S2  and S4. In addition, we found that these neurogenic defects were correlated to a deficit of Neurog1+ progenitors at all stages (Figures 3A, 3B, and 3E), particularly affecting those of the second-wave (Figure  S2C ).
ACKNOWLEDGMENTS We thank  F. Guillemot ,  A. McMahon , and  P. Topilko  for Neurog mutants, Wnt1Cre transgenic animals, and Egr2 DT knockin mice, respectively; as well as  J. F. Brunet ,  C. Goridis ,  L. Sommer , and  M. Wegner  for materials. This work was supported by  Inserm, France ;  CNRS, France ;  Fondation pour la Recherche Medicale, France ;  Agence Nationale pour la Recherche, France ; and  University of Montpellier, France.
Assuming that the star is spherically symmetric, namely that the gradient of the gravitational potential is only in the radial direction, then one has that g = -∂ r Φ. So, tackling the buoyancy work integral, it can be seen that ∆W B = ,m, 1 2 ,m2,ν2 rt r b dr (-1) m2 gr 2 2 + 1 √ + 1ψ * m ,1 - √ ψ * m ,-1 √ + 1 ∂ ∂r + + 2 r K -m,m2 1; ,1 2 ,ν2 - √ ∂ ∂r - -1 r K -m,m2 1 ; ,-1 2,ν2 ρ m2-m 1 ψ m2 2,ν2. (13) Similarly, the pressure work integral can be identi ed as Zenodo, 2016 ∆W P = rt r b drr 2 ,m, 1 2 ,m2 1 (2 + 1) (2 2 + 1) √ + 1 ∂ ∂r + + 2 r ψ * m+m2 ,1 + √ - ∂ ∂r + -1 r ψ * m+m2 ,-1 ν1 ψ m 1 ,ν1 2 + 1 ∂ ∂r - 2 r K m,m2 ; 1,ν1 2,1 -2 ∂ ∂r + 2 + 1 r K m,m2 ; 1,ν1 2,-1 P m2 2 + (-1) m+m2 γH , 1, 2 m,m2 P m 1 2 + 1 ∂ ∂r + 2 + 2 r ψ m2 2,1 + 2 - ∂ ∂r + 2 -1 r ψ m2 2,-1. (14) Here, H and K are coe cients related to the 3-j and 6-j symbols that arise from integrals over products of SVH that are then either projected onto the scalar spherical harmonics, which, along with J , are closely related to those de ned in  Varshalovich, D.
These results suggest that loop replacement did not significantly alter the coordination sphere of the metal ion in the active site. To rationalize the impact of changes in loop L3, we performed X-ray crystallographic studies. The L3IMP and L3Pro variants were crystallized, and both structures were solved at a resolution of 1. 65 and 1. 80 Å, respectively (Table  S2 ). Attempts to obtain crystals of the L3VIM variant were unsuccessful. The structures of both variants are very similar to the previously reported crystal structure of native NDM-1 (PDB code 3SPU)  (43). The overall structure of the enzymes and their active sites are highly conserved (Fig. 4A ), as accounted for the low RMSD values of the core structure without considering loop L3 (Ͻ0. 60 Å over all C␣). The active sites of L3IMP and L3Pro displayed bimetallic occupancy, i.
Strep-Tag II monoclonal antibodies (at a 1:1,000 dilution from a 200-g/ml solution; Novagen) and immunoglobulin G-alkaline phosphatase conjugates (at a 1:3,000 dilution) were used to detect M␤L expression. GroEL and MPB antibodies were added as loading controls. Protein band intensities were quantified from PVDF membranes with ImageJ software  (69). Cell-based assays. To test the phenotypic effect of the loop L3 substitutions, the MICs of piperacillin, ceftazidime, cefotaxime, cefepime, imipenem, and meropenem were determined for each clone in LB medium using the agar macrodilution method according to CLSI guidelines  (70). Protein expression was induced with 100 M IPTG, except for ceftazidime, where induction was performed with 20 M IPTG. In order to measure the effect of Zn(II) availability on antibiotic resistance, the growth medium was supplemented with various concentrations of the metal chelator dipicolinic acid (DPA [Merck], Ͼ98%).
18-MVR stopped-flow system associated with a photodiode-array detector (Applied Photophysics, United Kingdom). The measurements were performed in 100 mM HEPES (pH 7. 5), 200 mM NaCl, and 0. 3 mM ZnSO 4 at 6°C. Data were corrected for the instrument dead time (2 ms). In all cases, a 1:1 ratio of metallated enzyme and substrate was used. Thermal denaturation assays. Protein stability to thermal denaturation was determined on both holoand apoproteins by using a protein thermal shift assay (Applied Biosystems, Carlsbad, CA) according to the manufacturer's instructions. Data were fit to a two-step model as previously described  (75). Preparation of apo and Co(II) substituted enzymes. The nonmetallated forms of apo-NDM-1, apo-L3VIM, apo-L3IMP, and apo-L3Pro were prepared by successive dialysis of the purified holoproteins against chelators as described previously  (49).
0), 500 mM (NH 4 ) 2 SO 4 , 5 mM CoCl 2 -NiCl 2 -MgCl 2-CdCl 2 , and 12 to 30% (wt/vol) PEG 3350. All crystals were flash-frozen either in mother liquor supplemented with 35% glycerol or in 50% paraffin oil and then stored in liquid nitrogen. X-ray diffraction data were collected at 100 K at the Proxima 1 beamline (Synchrotron Soleil, Saint-Aubin, France). Data reduction was carried out using XDS  (76)  and Aimless from the CCP4 program suite  (77). The crystal structures of both proteins were solved by molecular replacement using the programs Molrep  (78)  or Phaser  (79)  and a previously determined NDM-1 structure (PDB entry 3SPU, chain C) as a search probe. The final crystallographic models were obtained through iterative rounds of refinement with Buster (80) and manual rebuilding with COOT  (81).
ACKNOWLEDGMENTS A. R. P. and E. G. received doctoral fellowships from CONICET. M. F. M. received a doctoral scholarship from  COLCIENCIAS. L. H. O. , S. K. , L. I. L. , and A. J. V. are CONICET staff members. This study was supported by a grant from  ANPCyT  (A. J. V. ),  National Institutes of Health (NIH)  grant  R01 AI100560  (A. J. V. and R. A. B. ),  NIH  grant  R01 AI063517 ,  NIH  grant  R01 AI072219  (R. A. B. ), the  ECOS-MinCyT  collaborative project (A. J. V. and P. M. A. ), the  Cleveland Department of Veterans Affairs and Development  ( 1I01BX001974 [R. A. B. ]) , and the  Geriatric Research Education and Clinical Center (R. A. B. ). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health or the  Department of Veterans Affairs.
Together, these results suggest that photo-activation causes changes in the activation kinetics of sim expression, which are compatible with reduced levels of Notch activity. The graded tissue-level pattern of sim activation was not reflected at the level of individual nuclei. In agreement with a recent study of sim enhancer regulation by NICD  [14] , sim nuclear dots were either absent or present and their intensity remained relatively stable (fluctuating around the mean) for the entire duration of cellularization 4H), as revealed also by quantitative fluorescent in situ hybridization of nascent After 25 min of signalling, there is no significant delay. The dataset used for quantification is the same as that used in (E). *P ≤ 0. 05, **P ≤ 0. 01, n. s. represents no statistically significant difference in a 2-sample t-test.
Error bars denote standard error of mean. H Graph showing that gradually increasing the time-period of active signalling from 0 min to 25 min does not change the mean spot intensity of sim transcripts compared to controls. There was only a 20% variation in spot intensity over time, a value that was smaller than the ~75% variation in spot intensity for a given time point. The dataset used for quantification is the same as that used in (E). Shaded areas represent the interquartile range. transcripts (Fig EV5D  -I ). These results suggest that a cumulative amount of Notch activation determines the competence of mesectodermal nuclei to express sim, and that the time-lag between the beginning of cellularization and sim expression is Notch dependent. Increasing the time of Notch activity from 5 min to 10 min to 20 min had no significant impact on the mean nuclear dot intensity of sim transcripts from the time-point at which they first became detectable until the endpoint of imaging.
Image analysis To quantify Delta::GFP::CRY2 clustering kinetics, a data pipeline was developed in Cell Profiler to automatically identify and segment individual Delta::GFP::CRY2 clusters in a series of individual confocal images. Segmentation serves to first map the positional coordinates for each cluster, allowing for automatic quantification of the number of clusters in each image. Delta protein abundance in individual clusters was then automatically quantified by integrating fluorescence intensity across the total area of each cluster as identified through segmentation. Data normalization was performed through the following formula: (Total Number of Clusters × Mean Intensity of Clusters)ÄTotal Intensity of Image. This approach to normalization provides a quantitative measure of the total amount of Delta protein (Delta::GFP:CRY2 locked into clusters), and the resulting data were plotted as the relative intensity of Delta clusters over time plus or minus standard deviation over time.
This image analysis pipeline automatically identifies and segments individual Delta-GFP-CRY2 clusters in a series of individual images collected using spinning disc confocal microscopy. Segmentation serves to first map the positional coordinates for each cluster, allowing for automatic quantification of the number of clusters in each image. Delta protein abundance in individual clusters is then automatically quantified by integrating fluorescence intensity across the total area of each cluster as identified through segmentation. For the quantification of Notch protein levels at the plasma membrane, confocal images were processed using Fiji and analysed using MATLAB-R2017b (MathWorks). A sum-of-slice projection of 10 focal planes was used to segment line profiles with a line width of 7 pixels, which were drawn across approximately 30 interfaces in both ectoderm and mesoderm of each embryo, and the corresponding intensity profiles were extracted in Fiji.
These data were then input into a customized MATLAB pipeline. Peak values in the intensity profile were identified using the findpeaks function in MATLAB, and the integrated intensity across individual interfaces was calculated by choosing an interval of 0. 78 lm centred at the peak. For the clonal analysis, the total number of sensory organ precursor cells (SOPs, marked by neur-iRFPnls) at the border of wild-type and Delta-CRY2 clones were counted manually and scored for their presence on the side of either the wild-type or Delta-CRY2 homozygous clone. The number of SOPs on the side of the Delta-CRY2 clone was then plotted as a percentage of total number of SOPs at the border in both the photo-activated and dark conditions. For the analysis and quantification of sim expression using the MS2-MCP system, the numbers of spots and associated intensity were quantified under different photo-activation regimes.
The late group was identified as having detectable levels of sim expression, and the cellularization furrow was positioned at least 5 lm below the base of the nuclei but prior to ventral furrow formation. To quantify Delta protein content at the plasma membrane, cell outlines were segmented based on the E-cadherin signal co-stained with Delta using Embryo Development Geometry Explorer (EDGE) software  [43]  (https://github. com/mgelbart/embryo-developmentgeometry-explorer). Image stacks spanning 3. 5 lm were projected in 2-D using sum-of-slices. The membrane-bound Delta signal was measured in a 0. 3-lm-thick region lining the segmented membrane, and for each embryo, the mean intensity value of the ectoderm and of the mesoderm was calculated. To quantify the membrane-to-cytoplasmic ratio of the Delta signal in the mesoderm, the central (cytoplasmic) signal was derived from the inverted mask of the segmented membrane and divided by the Delta signal measured at the surrounding cell edges.
An average membrane-to-cytoplasmic ratio was calculated from ~40 cells per embryo. To analyse the colocalization of Delta and Rab5 in the mesoderm, vesicles were detected in a 7-lm-spanning image stack using the Fiji "Spots colocalization" plugin ComDet v. 0. 4. 1 (https://github. com/ ekatrukha/ComDet). Identified Delta particles were binary classified for an overlap with Rab5 particles in at least 1 pixel. The percentage of Rab5-positive Delta vesicles were calculated per embryo.
The dataset used for quantification is the same as that used in (E). *P ≤ 0. 05, **P ≤ 0. 01, ***P ≤ 0. 001, n. s. represents no statistically significant difference in a 2-sample t-test. Error bars denote standard error of mean. G Bar plot showing that onset sim transcription is significantly delayed compared to control embryos as the duration of signalling is increased from 0 min to 20 min. After 25 min of signalling, there is no significant delay. The dataset used for quantification is the same as that used in (E). *P ≤ 0. 05, **P ≤ 0. 01, n. s. represents no statistically significant difference in a 2-sample t-test. Error bars denote standard error of mean. H Graph showing that gradually increasing the time-period of active signalling from 0 min to 25 min does not change the mean spot intensity of sim transcripts compared to controls.
Acknowledgements We thank all members of the  De Renzis laboratory  for helpful discussion. We thank  C. Tischer  for helping with image analysis and the data pipeline developed in Cell Profiler for quantifying Delta clustering kinetics. We thank  A. Aulehla ,  J. Crocker ,  J. Hartmann  and  T. Hiiragi  for helpful discussions and critical reading of the manuscript. We thank the advanced light microscopy for their advice and assistance. This work was supported by  EMBL  internal funding available to S. D. R. We thank the  Bloomington Drosophila Stock Center  and the  Drosophila Genomics Resource Center  for providing fly stocks and cDNAs. We thank  M. Levine  for providing fly stocks.
Traditional widefield fluorescence imaging was performed using Eclipse 50i epi-fluorescence microscope (Nikon, Champigny sur Marne, France) equipped with the Nis Element acquisition software and a 640 (numerical aperture, 1. 3) oil immersion objective (40X). Confocal microscopy was performed as previously reported  [9]  using a SP5 confocal microscope (Leica, Leica microsystems GmbH, Wetzlar, German) with a ×63/numerical aperture 1. 4 Plan Neofluor objective lens. To prevent cross-contamination between fluorochromes, each channel was imaged sequentially by using the multitrack recording module before merging. z-stack pictures were obtained using LAS AF, Leica software. Subsequent quantification of proteins in nucleoplasm, cytoplasm and NR were performed with ImageJ (v. 1. 52n)  [14]. Protein quantification in nucleoplasm, cytoplasm and foci was performed by measuring the pixel intensity with the "Plot Profile" function of ImageJ (v.
The CdtB subunit promotes the nuclear remodeling and UNR nucleoplasmic reticulum formation in hepatocytes To elucidate if the observed effects could be specifically attributed to the CdtB subunit, stable transgenic cell lines conditionally expressing the active CdtB  [10]  were used (Table  1 ). CdtB of and yellow arrowheads indicate UNR-NR and areas where lamina and chromatin (DAPI) are connected, respectively. (C) Nuclear area and (D) UNR-positive nuclei, representative of 3,000 cells per mice. (E) UNR protein quantification in cytoplasm vs NR. For panels (C) to (E), nuclear surface was quantified by isolating the DAPI fluorescence for each nucleus by using the 'Threshold' function of ImageJ (v. 1. 52n). The acquired images were calibrated according to the microscope software manufacturer.
A two-fold increase in ribosomes was found in the CdtB-induced NR compared to cytoplasm (RPL10, Fig 6B  and 6E ). Consequently, Hep3B transgenic living cells were subjected to triplicate. # All of the UNR-depleted CdtB-surviving cells are UNR-NR+. � p<0. 05. (B) Hepatic Hep3B transgenic cells were cultivated with doxycycline for 72 h. Inhibitors, i. e. U0126 (100 nM), SP600125 (100 nM), SB203580 (100 nM), PD98059 (100 nM), cycloheximide (1 μM), actinomycin D (0. 7 μM), thapsigargin (100 nM) and cyclopiazonic acid (50 nM) were added to the medium either 24 h or 48 h after doxycycline induction, leading to similar results. Only the 24 hours-experiment is presented in this figure. Quantification of UNR-NR positive nuclei (%) was performed on a minimum of 500 cells. Data represent the mean of triplicates in 1 representative experiment out of 3.
Acknowledgments 1) We wish to thank  James G. Fox  ( Division of Comparative Medicine and Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA ) for supplying the H. hepaticus strains. We are indebted to  Jean-Philippe Nougayrède, Eric Oswald and Frederic Taieb (Institut de Recherche en SanteDigestive, INRA, Toulouse, France)  for supplying the E. coli-producing shiga toxin 2 and colibactin, respectively. The authors thank  Dominique Weil  ( CNRS-UMR7622  and  UniversitePierre & Marie Curie (UPMC) ,  Institut de Biologie Paris-Seine (IBPS) Developmental Biology Laboratory, Compartmentation  and intracellular traffic of mRNPs, Paris, France) for helpful discussions and for providing the anti-DDX6. We are grateful to  Olivier Jean-Jean  ( CNRS-UMR8256  and  UPMC, IBPS, Biological Adaptation and Aging, Eukaryotic translation, Paris, France)  for supplying home-made anti-eRF1 and anti-eRF3.
5 µM -1 s -1 and to 27. 5 µM -1 s -1 and K OFF equal to 35. 8 s -1 nM and 2. 6 s -1 respectively, as used in Ait  Ouares et al. , 2019 , to take into account the difference in temperature and the radial diffusion from the published values  (Nägerl et al. , 2000). Calbindin D-28k dominates Ca 2+ binding in the millisecond time scale  (Schmidt and Eilers, 2009)  and has estimated concentration of 120 µM  (Kosaka et al. , 1993). The Ca 2+ influx associated with the CF was approximated by a Gaussian function of 15 or 20 µM/ms and 1. 5 ms time constant, consistent with the detailed model described in Ait  Ouares et al. (2019). We simulated 200 ms of recording using the function "ode45" in Matlab. In these 200 ms, the Gaussian function approximating the CF associated Ca 2+ influx was delayed by 180 ms from the beginning of the simulation and, in the simulations corresponding to the paired scenarios, it was preceded by a slow Ca 2+ influx approximated by another Gaussian function of 4 µM/ms and 45 ms time constant to estimate the effect of saturating the high affinity buffers.
EXPERIMENTAL DESIGN AND STATISTICAL ANALYSIS Data were processed and analysed using MATLAB. Changes produced by the pairing protocol with respect to the CF stimulation alone, or by the pharmacological action of an agent, were assessed by performing the paired Student's t-test on the signal parameter under the two different conditions. A change in the signal was considered significant when p < 0. 01. In all figures, a significant change was indicated with "*". In the specific case of data reported in Fig. 1 , the conclusion that the effect of adding CPCCOEt is different when the CF stimulation is delayed by 60 ms from the first PF stimulus, with respect to the cases of 100 ms and 150 ms delays, is supported by a paired t-test performed on the ∆F/F 0 ratios at two different delays that gave a value of p < 0.
This work was supported by the  Agence Nationale de la Recherche  through three grants ( ANR-14-CE17-0006 -WaveFrontImag ;  Labex Ion Channels Science and Therapeutics: program  number  ANR-11-LABX-0015  and  National Infrastructure France Life Imaging "Noeud Grenoblois ") and by the  Federation pour la recherché sur le Cerveau  ( FRC -Grant Espoir  en tête, Rotary France). We thank  Dr. Boris Barbour  for useful discussions during the project, for reading the manuscript before submission and for advices on improving the clarity of the figures.
TIRF microscopy and spinning disk confocal microscopy: live-cell imaging and image analysis The TIRF and spinning disk confocal microscopy experiments were as described  (Cocucci et al. , 2012). The single EGFP or TagRFP molecule calibration was carried out as described before  (Cocucci et al. , 2012; Cocucci et al. , 2014). The detection and tracking of all fluorescent traces was carried out using the cmeAnalysis software package  (Aguet et al. , 2013). For the automated detection, the minimum and maximum tracking search radius were 1 and 3 pixels, and the maximum gap length in a trajectory was 2 frames  (He et al. , 2017). Detection of an independent event was verified by establishing absence of significant signal during brief intervals preceding and following the first and last detected signals.
ACKNOWLEDGMENTS We thank  S. Sever  for the Aux1/GAK antibody gift and  Justin R. Houser  for maintaining the TIRF and spinning disc microscopes. We specially thank  S. C. Harrison  for discussions and editorial help. We also thank members of our laboratory for help and encouragement. E. S. was supported by grants from the  National Natural Science Foundation  (Grant No. 31270884 ) and by the  Youth Innovation Promotion Association, Chinese Academy of Sciences. T. K. acknowledges support from the  Janelia Visitor Program  and  Eric Betzig ,  Eric Marino ,  Tsung-Li Liu  and  Wesley R. Legant  for help and advice in constructing and installing the lattice light-sheet microscope. Construction of the lattice light-sheet microscope was supported by grants from  Biogen and Ionis Pharmaceuticals  to T.
A picture of each individual plant is taken every day at the same day-time and a semi-automatic segmentation process (with some manual corrections when required) is performed to extract leaf pixels. From this we exploit different traits: Projected Rosette Area (PRA), circle radius, convex hull area, average Red, Green and Blue components (leaf pixels, RGB colour scale), and derived phenotypic traits are calculated, such as the compactness (ratio PRA / convex hull area) and the Relative Expansion Rate (RER) over specific time windows (Fig  1 ), as previously described  [34]. The complete raw phenotypic dataset has been submitted to INRA institutional data repository (https://data. inra. fr) [48]. Principal component analysis (PCA) was performed using the ade4 R package based on phenotypic data from all the RIL sets in WW and WD conditions.
Interactive QTL maps for time-course series were generated using the R/qtl charts package  [89]. All QTL positions were projected on the consensus genetic map of the 4 crosses built with R/qtl (this is the map shown along the x axis on Figs 3, 5 and 6). A joint genotype dataset was constructed with 'A' alleles coding Col alleles (the common parent), 'B' alleles for non-Col alleles, and monomorphic markers in a cross coded as missing. The linkage groups were considered known from the individual maps and the physical position of markers, and a first marker order was calculated using orderMarkers() function. In case of conflicting marker order between individual, physical and consensus maps, the function switch. order() was used to retain the most probable order (i. e with the lowest number of recombination).