dataesr/scientific-paragraphs-categorization huggingface dataset:
Acknowledgments We thank the  Training Program in Nigeria for Non-Communicable Diseases Research (TRAPING-NCD ;  Fogarty International Center of the National Institutes of Health   D43TW009106-CA ) for providing funding support for EJ-A's PhD research work at the  London School of Hygiene & Tropical Medicine. The content is solely the responsibility of the authors and does not necessarily represent the official views of the  Fogarty International Center of the National Institutes of Health. Adjusted for all other variables, except for staging classification and study quality because of concerns of overadjustment,  † Adjusted  for all other variables, except region or race, staging classification, and study quality. ‡ The study population was classified as black if 80% of participants or more were black (appendix p 14, figure 3).
This is also visible in the growing contribution of highresolution cryo-EM structures over the four last years (B). The data are taken from the http://www. ebi. ac. uk/pdbe/emdb/ and http://www. rcsb. org/pdb/ websites (as of September 26, 2016). object which is seen under different orientations. Thus, reversely, a 3D map of the object can be obtained from 2D projection images by backprojection, that is the views of the 3D object seen under different orientations (viewing angles) can be combined into a single 3D reconstruction; this con-cept applies to both single particle cryo-EM and cryo electron tomography (cryo-ET; for detailed basics on image processing and 3D reconstruction see for example reviews by  van Heel et al. , 2000; Ray et al. , 2003; Briggs et al. , 2013; Lučič et al. , 2013; Milne et al.
Acknowledgements We apologise to our colleagues for any publications not being cited which is due to space limitations and the cross-disciplinary nature of this review article. We would like to thank our colleagues with whom we collaborate on the projects mentioned in this review, notably  Jean-Luc Vonesch ,  Alexander Spirin ,  Vladimir Shirokov ,  Dino Moras ,  Jean-Francois Peyron ,  Danièle Spehner  and  Christian Cambillau , and the members of our platforms and facilities for their support.
Funding This work was supported by the  European Research Council  ( ERC Starting Grant  N  243296 TRANS-LATIONMACHINERY ), the  Fondation pour la Recherche Médicale (FRM) , the  Association pour la Recherche sur le Cancer (ARC) , the  Alsace Region , the  Agence National pour la Recherche ,  Université de Strasbourg and Investissement d'Avenir (IDEX) , the  Institut National du Cancer (INCa) , the  Centre National pour la Recherche Scientifique (CNRS) , the  Institut National pour la Recherche Médicale (Inserm) , by 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).
6a ). Automated image processing algorithms on these time-lapse pictures allow moreover extracting detailed information about the worms' growth rate, not only at a population level, but also at single-worm resolution (Fig. 6b-c ). Specifically, the area occupied by each worm is here used as a quantitative indicator of growth. Data about the growth rate of individual worms allows preserving detailed information on the development of each nematode (Fig. 6b ), while the average growth trend is found to follow a well-defined sigmoidal dependence on time (Fig. 6c ). At desired moments during worms' development (e. g. , in our study, 43 h, 60 h and 91 h upon worm injection), the reversible worm immobilization protocol for high-resolution imaging (see Fig. 4a ) is employed. At each observation and in a matter of a few minutes, all the worms are perfectly immobilized in a PF127 gel matrix and SOD1-YFP expression can be monitored within their tissues via fluorescent microscopy through high-magnification objectives.
Motility assays C. elegans movement was recorded for 45 s at different days of adulthood using a Nikon DS-L2/DS-Fi1 camera and controller setup, attached to both a computer and a standard brightfield microscope. Five plates of worms, with 10 worms per plate were measured in each condition. Using these video recordings, the movement traces of worms during all recording periods were calculated by following the organism centroids using a modified version of the Parallel Worm Tracker for MATLAB  [52]. The average worm speed during the recording periods was then calculated for each plate and each condition.
Image acquisition and processing The microfluidic platform was placed within an inverted microscope (Axio Observer, Zeiss) equipped with two illumination systems: (i) a precisExcite High-Power LED illumination system (Visitron, Puchheim, Germany) for brightfield imaging and (ii) a Lambda DG4 illumination system (Sutter instruments, Novato, CA, USA) for fluorescence imaging. The microscope had a motorized xy-stage and the automated imaging process was controlled using VisiView Premier Image acquisition software (Visitron, Puchheim, Germany). Images were acquired through a Hamamatsu Orca-ER CCD camera (Hamamatsu, Solothurn, Switzerland). Image processing was performed with Fiji software (http://imagej. nih. gov/ij; version 1. 47b). In particular, worm areas were measured by processing time-lapse brightfield pictures as follows.
Acknowledgements Work in MG laboratory was supported by the  Ecole Polytechnique Fédérale de Lausanne  and the  EU Ideas program  ( ERC-2012-AdG-320404 ). The authors thank  R. Padovani ,  A. Sayah  ( Laboratory of Microsystems LMIS2 at EPFL ), and  P. Maoddi  ( Physics Department of the European Organization for Nuclear Research -CERN ) for very fruitful discussions about the project and  P. Abdel-Sayed  ( Biomedical Orthopedics Laboratory at EPFL ) for his help with PF127 viscosity measurements. JA is the Nestlé Chair in Energy Metabolism. Work in the JA laboratory is supported by the  Ecole Polytechnique Fédérale de Lausanne , the  EU Ideas program  ( ERC-2008-AdG-23118 ), the  NIH  ( R01AG043930 ), the  Swiss National Science Foundation  ( 31003A-124713 ) and Systems X ( 51RTP0-151019 ).
In-gel trypsin digestion and mass spectrometry In-gel trypsin digestion was carried out essentially as described previously  [9]. Briefly, following SDS-PAGE, stained protein bands were cut out from the gel and digested with sequence-grade modified bovine trypsin (Promega Corporation, Madison, WI, USA). The peptides generated were subsequently extracted and submitted to mass spectrometry on a MALDI-TOF instrument (Ultraflex, Bruker Corporation, Billerica, MA, USA). Monoisotopic peptide masses obtained were used for protein identification by database searching.
We found that the abrupt reversal of cue-outcome associations caused immediate changes in 5-HT US responses (Extended Data Fig. 8 ), including a robust positive response to the absence of a predicted reward (Fig. 2e ). The results for all US's are summarized in Fig. 2f. First, 5-HT neurons showed little or no response to expected water rewards before reversal, but responded robustly to the same rewards when they were unexpected, after reversal. In other words, they reported a positive reward prediction error (RPE) by an increase in firing. ,764 = 84. 36 p < 0. 001 for large reward, F 1,748 = 3. 49 p = 0. 062 for small reward, F 1,756 = 38. 17 p < 0. 001 for neutral, F 1,766 = 2. 79 p = 0. 095 for air puff). g, Same as f for midbrain DA neurons (n = 3 mice, F 1,249 = 67. 9 p < 0. 001 for large reward, F 1,277 = 8.
To analyse these data 4 sessions with predicted and unpredicted outcomes were pooled together for each mouse. All GCaMP6s experiments were performed within the limit of 1 month since viral injection date to avoid cell death due to overexpression of GCaMP6s in neurons. Fibre photometry setup -The dual-color fibre photometry acquisition setup consists of a 3-stage tabletop black case containing optical components (filters, dichroic mirrors, collimator), two light sources for excitation and two photomultiplier tubes (PMTs) for acquisition of fluorescence of a green (GCaMP6s) and of a red (tdTomato) fluorophore. We used a 473 nm (maximum power: 30mW) and a 561 nm (maximum power: 100mW) diode-pumped solid-state laser (both from Crystalaser) for excitation of GCaMP6s and of tdTomato, respectively.
This patchcord fibre was attached to the fibre cannula each animal had implanted (MFC_300/330-0. 22_5mm_RM3_FLT Fibre Polymicro, polymide removed) through a titanium M3 thread receptacle. Data Analysis -All data were analysed in MATLAB. For the hM4D experiment, lick rate was acquired at 1KHz and smoothed using convolution with a Gaussian filter of 50 ms. Mean anticipatory licking was calculated for each trial as the mean lick rate in the period of 500-2800 ms after odour onset subtracted by the mean lick rate in 1s before this period. For each mouse, trials of sessions around reversal were concatenated and a 3 trials smoothing was performed along trials. For each reversed odour and each mouse, the last 50 trials before reversal were fit by a constant function of the form (A+B); the first 200 trials after reversal were fit by an exponential function of the form (A+B*exp(-t/τ)) using fminsearch in MATLAB.
Then, for each trial we corrected the green ΔF/F 0 values using the parameters (a -slope; b -offset) obtained with the regression model of that mouse in that session: [ΔF/F 0 ] GREEN_corr = [ΔF/F 0 ] GREEN -a*[ΔF/F 0 ] RED -b. Behavioural data was organized as a function of US type and divided in CS and US responses. [ΔF/F 0 ] GREEN_corr US responses were normalized by subtracting the mean [ΔF/F 0 ] GREEN_corr of the interval of 1 s before US onset. The CS or US response was considered the mean of the signal during 1. 5 s after CS or US onset respectively. For each mouse, all CS and US responses were z-scored in the expert phase to compare the amplitudes of responses to the different events. Analysis of US response across time was done by z-scoring all US responses of each mouse across days for each US type.
Acknowledgements We thank  R. M. Costa  and  J. J. Paton Labs  for TH-Cre mice;  Susana Dias  and  Sérgio Casimiro  for histology and immunohistochemistry assistance;  Dario Sarra  for running behavioural experiments for a few days. We also thank  C. Poo ,  B. V. Atallah ,  M. Murakami ,  G. Agarwal  and  J. J. Paton  for comments on a previous version of the manuscript, and all members of the  Systems Neuroscience Lab  and the  Champalimaud Research  for useful discussions and feedback during the development of this project. This work was supported by  Fundação para a Ciência e Tecnologia  (fellowship  SFRH/BD/43072/2008  to S. M. ),  Human Frontier Science Program  (fellowship  LT000881/2011L  to E. L. ),  European Research Council  ( Advanced Investigator  Grants  250334  and  671251  to Z.
Acute myeloid leukemia patients' clinical response to idasanutlin (RG7388) is associated with pre-treatment MDM2 protein expression in leukemic blasts In translational research described, we investigated biomarker expression by flow cytometry for MDM2 antagonist clinical response association in relapsed/refractory AML patients treated with idasanutlin-based therapy (Clinicaltrials. gov identifier: NCT01773408). As MDM2 targets p53 for ubiquination/degradation, higher levels of MDM2 protein expression would be consistent with a mechanism of increased malignant potential by decreased p53 activity. We hypothesized that this comprises a mechanism for oncogene addiction whereby the cell is uniquely sensitive to enhanced p53 activity by MDM2 antagonism through reliance on this pathway. Flow cytometry assessment of MDM2 protein expression in leukemic blasts (CD45 dim or CD45 dim /CD34 + ) is established in both a proof of principle set comprising initial trial segments, and then validated in a trial segment comprising patients treated with a clinically optimized idasanutlin formulation.
5 Interestingly, in an analysis of blood specimens from patients with AML, none of the 4 genes alone showed significant association with patient outcomes following treatment with MDM2 antagonists. When a multigene algorithm was considered, however, an association with response was identified. 5 Because these results were from the whole blood of AML patients, signal association of individual genes may be obscured by non-AML contributions within the matrix. Thus, we examined MDM2 at the protein level using multiparametric flow cytometry refined to AML leukemic blasts. Idasanutlin (RG7388) is a potent and selective MDM2 antagonist showing promising responses in phase 1 studies in relapsed/refractory AML. Trial NP28679 (NCT01773408) is a phase 1/1b study evaluating idasanutlin treatment (monotherapy or in combination with cytarabine) in relapsed or refractory AML patients.
A proof of principle training data set comprised patients treated with idasanutlin monotherapy (400-1600 mg/day for 5 consecutive days within a 28-day cycle; microprecipitated bulk powder formulation) or in combination with cytarabine 1 g/m 2 IV on days 1-6 during the haematologica 2016; 101:e185 ) vs. no response (progressive disease, hematologic improvement, and partial response).
Airborne laser scanning (ALS) remote sensing data are now available for entire countries such as Switzerland. Methods for the estimation of forest parameters from ALS have been intensively investigated in the past years. However, the implementation of a forest mapping workflow based on available data at a regional level still remains challenging. A case study was implemented in the Canton of Valais (Switzerland). The national ALS dataset and field data of the Swiss National Forest Inventory were used to calibrate estimation models for mean and maximum height, basal area, stem density, mean diameter and stem volume. When stratification was performed based on ALS acquisition settings and geographical criteria, satisfactory prediction models were obtained for volume (R 2 =0. 61 with a root mean square error of 47%) and basal area (respectively 0.
Airborne laser scanning data ALS data was acquired for the whole Swiss territory between 2000 and 2008, for areas with altitude below 2000 m. ALS data are available as point clouds with X, Y and Z coordinates without other attributes. Point classification is not specified but the swissALTI3D digital terrain model (2-m resolution) was derived from this dataset. Flight metadata are limited to the following information: year and period of flight (spring / autumn / summer). The ALS point cloud in the study area was acquired in 2001 and 2005, and actually contains points up to an altitude of 2100 m. Average pulse density is around 0. 5 m -2 , which is sufficient for an area-based approach  (Monnet et al. 2015).
CONCLUSION Existing methodology for the calibration of prediction models with airborne laser scanning was successfully implemented in the case of a wide-area mapping of forest variables. Using NFI sample plots and existing ALS datasets is cost-effective and the resulting maps have high added-value for local forest managers, despite higher errors compared to values obtained in specifically designed ALS-based inventories. Regarding data acquisition, it seems important to have better meta data about acquisition parameters in order to be able to appropriately stratify the models in subsequent analysis. Besides, if statistical estimates have to be derived at some administrative level, attention should be paid to ensure homogeneous acquisition settings inside each administrative entity. Temporal and spatial differences between field and remote sensing acquisitions still remain troublesome.
Dwarf spheroidal galaxies around the Milky Way Together with the Galactic Centre, the spheroidal dwarf galaxies orbiting the Milky Way are the best targets for indirect dark matter searches with gamma rays. Indeed, they are vastly dark-matter dominated, according to the kinematics of their member stars, most of them are practically devoid of any gas, and thus are not expected to harbor the typical astrophysical processes yielding high-energy photons. While LAT initial results with one year of data  [54] , and imaging atmospheric Cherenkov telescopes (IACTs) observations with sufficiently long observing times  [55, 56] , already showed the potential strength of these targets, an important breakthrough occurred when the different dwarf galaxies were analyzed with a joint likelihood technique, generalized to account for statistical uncertainties in modeling the dark matter content from stellar data.
The cyan, blue, and yellow curves labeled in the top right panel present limits obtained with Segue 1 only, respectively with MAGIC  [64] , VERITAS  [65] , and Fermi-LAT  [58]. In the case of the LAT, the curve shown has been obtained with the same dark matter spatial distribution as in  [65] , and thus is directly comparable to it. Next, the curves labeled on the middle-left panel presents the best limits so far when performing a combined analysis with 15 dwarfs in the case of the LAT (in blue,  [58] ) and 5 dwarfs in the case of H. E. S. S. (in green,  [60] ), together with the current best IACT limits, obtained with a H. E. S. S. analysis of the Galactic halo in the vicinity of the Galactic center  [44]. Finally, the bottom-right panel labels the curves recently derived by the LAT team with the same dwarfs as in  [58] , but the updated and improved so-called "Pass 8" dataset  [61] : the limits in magenta are compared with the 68% and 95% bands estimated from 300 random sky positions, and the corresponding median expected limits in thin black dashed line.
Deeper observations have the potential of further improvements. The H. E. S. S. limits also include 90 h on Sagittarius, but the initial constraints presented in  [62]  have been revised to much lower values in  [63]. Nevertheless, the resulting combined limit shows the power of performing such a joint likelihood technique, which could also be used to combine data from different experiments. The results could eventually become competitive with the H. E. S. S. analysis of the Galactic Centre halo. To conclude this section, it appears that σ v in excess of 10 -25 cm 3 •s -1 is now ruled out at 95% confidence level over the WIMP mass range from 5 GeV/c 2 to ∼1 TeV/c 2.
Second, the determination of the dark matter density profile, which needs to include subhalo contributions, is hard to achieve. Third, galaxy clusters are actually expected to shine in gamma rays from standard astrophysical processes such as diffusive acceleration and radiation of local cosmic rays, and this emission has not even been detected so far. Despite these difficulties, the Fermi-LAT and IACT collaborations have analyzed the data in direction of some of the closest clusters: upper limits have been published for Fornax and Coma by the H. E. S. S. and VERITAS collaborations, respectively, and the Fermi-LAT team has separately studied these two clusters, and then combined them -in much the same way as the dwarf spheroidal galaxies-with three other clusters, which yields the best upper limits published so far.
of line production involves two additional weak couplings, so that the natural value for the annihilation into monochromatic photons is expected at or below 10 -28 cm 3 •s -1. The experimental limit reaches this value below masses of about 50 GeV. Note that it has been recently claimed that a gamma-ray line was observed close to the Galactic Centre with the data from Fermi-LAT  [78] , at an energy of about 130 GeV. Re-analysis of the dataset by the Fermi collaboration, illustrated in Fig. 6 , rules out this possibility.
Future searches With the important results reached by current-generation instruments during the past ten years, it is expected that next-generation gamma-ray telescopes will include indirect searches for a dark matter signal as one of their core topics. It is indeed the case with many projects introduced in  [14]  in this volume. Nevertheless, few have gone far enough as to make public preliminary studies of sensitivity. Fig. 8  shows a selection of such predicted limits from currently running experiments and future projects. For instance, the LAT dwarf spheroidal analysis (in cyan) has been simply extrapolated to ten years of Pass 8 data and a factor 3 more dwarfs used, while VERITAS will reach by 2018 an unprecedented exposure time on Segue 1 (in magenta). Likewise, the yellow and blue curves show upper limits expected from an analysis close to the Galactic Centre by H.
E. S. S. II and CTA, respectively. In the latter case, a more conservative discussion by  [83, 84]  that attempts to take into account uncertainties in the Galactic diffuse emission is presented in green and black, respectively. Finally, the red curve shows the limits on Segue 1 resulting from one year science operation of the full HAWC array. It is worth reminding here that the HAWC duty cycle is much larger than for IACTs and that it surveys a large fraction of the sky, so that these limits will quickly improve with an increased dataset and combined analyses of several dwarf spheroidals. Broadly speaking, it seems Fig. 7. Constraints on the decay constant of dark matter particles from gamma ray observations. Grey regions are excluded (figure from  [81] ). Fig. 8. Selection of some anticipated limits reachable with current or future experiments.
(2011) , respectively. Furthermore, for species included in clade A sensu  Arrigoni et al. (2014a) , IGR was amplified using MNC1F and MN-C1R primers  (Fukami et al. , 2004b; Huang et al. , 2009)  and the protocol described by  Arrigoni et al. (2016). All PCR products were purified with Illustra ExoStar (GE Healthcare, Buckinghamshire, UK) and directly sequenced in both strands using an ABI 3130xl Genetic Analyzer (Applied Biosystems, Carlsbad, CA, Clades within Lobophylliidae are coloured and labelled A to I according to  Arrigoni et al. (2014a). Specimens analyzed in this study are in bold. USA). Chromatograms were manually corrected for misreads, if necessary, and forward and reverse strands were merged into one sequence file using CodonCode Aligner 3. 6. 1 (CodonCode Corporation, Dedham, MA, USA).
In particular, chromatograms of products obtained with ITS4 and A18S primers did not show any intra-individual polymorphisms or double peaks, thereby allowing direct sequencing of this region. All newly obtained sequences were deposited in EMBL, and accession numbers are listed in S1. Sequence alignments were generated using the E-INS-i option in MAFFT 7. 130b  (Katoh et al. , 2002; Katoh and Standley, 2013)  under default parameters. For phylogenetic analyses, sequences of COI, histone H3, and ITS region were concatenated into one partitioned dataset. Three methods, maximum parsimony (MP), maximum likelihood (ML), and Bayesian inference (BI), were employed to reconstruct the phylogenetic relationships within the Lobophylliidae. For MP analysis, tree searches were generated in PAUP* 4. 0b10  (Swofford, 2003 ) using heuristic searches with 10000 random additions.
Results were analyzed for stationarity and convergence using Tracer 1. 6  (Rambaut and Drummond, 2009) , with a burn-in of 25% of sampled generations. Additionally, ML phylogenetic reconstructions for each separate COI, histone H3, and ITS region were obtained using PhyML  (Guindon and Gascuel, 2003)  under the substitution models proposed by  MrModeltest 2. 3 (Nylander, 2004). The SH-like test replicates was performed to assess the branch support of ML trees. Within clade A sensu  Arrigoni et al. (2014a) , Network 4. 6. 1. 2 (http://www. fluxus-technology. com) was used to construct a median-joining haplotype network  (Bandelt et al. , 1999)  for the IGR dataset. This method is especially applicable to non-recombinant DNA sequences, such as mitochondrial DNA, and combines all minimum spanning trees into a single network.