dataesr/scientific-paragraphs-categorization huggingface dataset:
The structures were solved by direct methods with SHELXS97 [58a] or SIR [58b] programs. Refinements were carried out by full-matrix least-squares on F 2 using the SHELXL97 program on the complete set of reflections [58a]. All nonehydrogen atoms were refined with anisotropic thermal parameters. The hydrogen atoms were placed in calculated positions and included in final refinement in a riding model with the isotropic temperature parameters set to U iso (H) ¼ 1. 2U eq (CH), U iso (H) ¼ 1. 3U eq  (C aromatic  ) and U iso (H) ¼ 1. 5U eq (CH 3 ). Crystallographic data (cif files) have been deposited with the Cambridge Crystallographic Data Centre as supplementary publication numbers 835275 (5i), 835276 (7a), 835277 (7b), 889646  (10)  and 941426  (11). Copy of these data can be obtained, free of charge, on application to CCDC, 12 Union Road, Cambridge CB2 IEZ, UK, fax: 144-(0)1223-336033 or e-mail: deposit@ccdc.
Both wild-type RefilinA and the Δ50-RefilinA lacking the PEST/DSG(X) 2-4 S motif are stabilized when cells are treated with the cell-permeable proteasome inhibitor MG132 (Fig. 1F ). Stabilization of Refilins is observed only after longterm incubation with MG132, whereas stabilization of protein degraded strictly in a proteasome-dependent manner occurs within minutes after the addition of MG132  (Mathes et al. , 2010; Zhou et al. , 2004). Several attempts to demonstrate a physical association of Refilins with βTrcp that recognizes the DSG(X) 2-4 S motif for proteasome-dependent protein degradation  (Zhou et al. , 2004)  were unsuccessful (data not shown). Ubiquitin-independent degradation of RefilinA was confirmed by mutagenesis studies. Mutations of the only two lysine residues present in rat RefilinA (K128 and K179) have no effect on the protein half-life (data not shown).
2% Triton X-100, and dried by centrifugation at 50 g. The slides were scanned using a Genepix 4000B scanner (Axon) and GenePix software (Molecular Devices), with the laser set at 635 mm, the laser power at 100%, and the photomultiplier tube voltage at 60%. The scanned image files were analysed using CodeLink expression software, version 4. 2 (GE Healthcare), which produces both a raw and normalized hybridization signal for each spot on the array.
Microarray data analysis The relative intensity of the raw hybridization signal on arrays varies in different experiments. CodeLink software was therefore used to normalize the raw hybridization signal on each array to the median of the array (median intensity is 1 after normalization) for better cross-array comparison. The threshold of detection was calculated using the normalized signal intensity of the 100 negative control samples in the array; spots with signal intensities below this threshold are referred to as 'absent'. Quality of processing was evaluated by generating scatter plots of positive signal distribution. Signal intensities were then converted to log base 2 values. Statistical comparison and filtering were performed using Genespring software 7. 0 (Agilent). Selection of genes was performed by pairwise comparisons between NG2+/A2B5-/O4-, NG2+/A2B5+ and NG2-/O4+ cells.
Quantitative PCR (qPCR) qPCR was performed on the LightCycler2. 0 machine (Roche) using LightCycler ® FastStart DNA MasterPLUS SYBR Green I mix (Roche) with the following program: 10 min incubation at 95°C, followed by 45 cycles of 95°C for 10 s, 55°C for 10 s and 72°C for 15 s, and a final step of 65°C for 15 s. The β-actin or Gapdh gene was selected as reference gene for internal standardization. Enrichment (x) was calculated using the following formula: x=2 -ΔΔCt  (Livak and Schmittgen, 2001). All the data were presented in terms of relative mRNA expressed as mean±s. d.
The four images were convolved to the same resolution 43. 8, and rebinned to the same pixel size 11. 5. To minimize the contribution from the line of sight, we subtracted the backgrounds for each image using a reference area away from 13 http://third. ucllnl. org/gps/ the bubble. The corresponding backgrounds were estimated to be 634 MJy sr -1 for 160 µm, 387 MJy sr -1 for 250 µm, 205 MJy sr -1 for 350 µm and 79 MJy sr -1 for 500 µm. By treating T dust and N H 2 as free parameters, the SED fitting was performed using the IDL program MPFITFUN 14   (Markwardt 2009). In principle, the 870 µm image should have been considered in the SED fitting. Although the 870 µm data constrain the dust temperature, as they are sensitive to colder components than Herschel data, they miss the bulk of extended emission, which is the major interest in our current work.
Therefore, we have correlated the six clumps with the YSOs in the RMS survey database  (Lumsden et al. 2013) , the sources in the Methanol Multi-Beam survey  (Green et al. 2010) , and the compact H ii region catalog in the CORNISH survey  (Purcell et al. 2013). It turns that there is only one source found in the RMS survey, which corresponds to the YSO candidate Y45 (see Figure  4 ). In addition, extended green objects (EGOs) identified based on their  1. 33 , which is expected to be as a threshold for forming high-mass stars  (Kauffmann & Pillai 2010). extended 4. 5 µm emission are thought to be massive YSO outflow candidates  (Cyganowski et al. 2008). Figure  4 (b) shows Spitzer 4. 5 µm emission overlaid with cold dust radiation at 250 µm. One can see that six clumps except for Clumps C and D peak at dark 4.
Therefore, the ALLWISE and MIPSGAL catalogs were taken into account. The former catalog includes photometries at 22 µmand the latter one includes photometries at 24 µm. In addition, these two catalogs have been cross matched with the 2MASS and/or GLIMPSE surveys, ensuring more photometries to be used in the SED fitting. From the two catalogs, 191 point sources were picked out. First, we retrieved a sample of 164 sources detected with a ratio of signal-to-noise (S/N) of > 10 in the four WISE bands and with an extension flag of < 2 from the ALLWISE Source catalog. The former simply ensures sources with detections at more wavelengths and with good enough data qualities and the latter guarantees the sources as a point source. Also, this sample has been complemented by that retrieved from the MIPSGAL catalog.
In this catalog, a sample of 32 point sources was chosen with a photometry uncertainty of < 0. 2 in the MIPS 24 µm and the four IRAC bands. These restrictions are equivalent to those mentioned previously. Except for 5 sources overlapping in these two samples, a total of 191 point sources were obtained. In addition, we tried searching for photometries at 70 µm for these selected sources. After investigating several published literatures, only one object, J180858. 77-181629. 7, has been found with 70 µm photometries  (Lumsden et al. 2013). Moreover, the 56 point sources from the CuTeX catalog (see Section 2. 1) were also inspected by a cross matching with the chosen 191 sources within a search radii of 2 in the software Topcat. 17 In a combination of visual inspections, only five photometries at 70 µm from the CuTeX catalog were considered in the following SED fittings.
In total, 6 out of 191 point sources have 70 µm photometries. In the fittings to the selected 191 sources, the distance was constrained in the range of 2. 3-4. 1 kpc, and the extinction was in the range of 0 to 16 Mag, which was estimated from the column density map by a relation of A v = 5. 34 × 10 -22 N(H 2 )  (Deharveng et al. 2009). After the SED fitting to the sources, the YSO candidates were determined by the following criteria. That is, the candidates should be those (1) with χ 2 best /N data ≤ 7 and (2) fitted well only by the YSO models, not by a model of a stellar photosphere with a foreground extinction. The former criterion has been determined by visually inspecting dozens of profiles of resulting SED fittings. We note that the value of 7 is a little greater than those adopted in the literature (e.
g. ,  Povich et al. 2009 Povich et al. , 2013;; Kang et al. 2009 ). This could be due to the fact that more data points (N data ) have been taken into account in this work. Figure  8  exemplifies a source satisfied with the above criteria. The candidate J180858. 77-181629. 7 has a good fit of the YSO models (Figure  8  (c)) but a poor fit of a stellar photosphere  (Figure 8 (d) ), indicating that this object is not a field star. These criteria result in 77 YSO candidates including 74 sources from the ALLWISE catalog and the remaining 3 from the MIPSGAL catalog. The color selection schemes were used to categorize the 77 YSO candidates. To begin, the classification method of  Koenig et al. (2012)  was adopted for the 74 candidates. According to the criteria in various color spaces, which can kick out possible contaminants such as star-forming galaxies, broad-line AGNs, and knots of shock emission, 16 PAH-contaminated emission sources were removed.
Statistical analysis Mean (±SD) was calculated for all variables. Data obtained at RCP and maximal load were compared between MSST and TEST using paired sample-t tests. _ VO 2 , _ VE, and heart rate curves were compared using a two-way repeated measures analysis of variance [Condition: (MSST vs. TEST) x Time: (10%, 20%. 100% of test duration)]. However, when the normality test failed, a Mann-Whitney rank sum test was performed between tests at each time interval. The Bonferroni test was used for post hoc comparisons. Finally, performance and _ VO 2 corresponding to RCP and maximal load were also correlated with the competitive level (ranking) of the players using Pearson rank order correlation for both tests. Data were tested for normality (Shapiro-Wilk test) and equality of variance (Fisher-Snedecor F-test).
Where significant effects were established, pairwise differences were identified using the Bonferroni post hoc analysis procedure adjusted for multiple comparisons. The following criteria were adopted to interpret the magnitude of r: <0. 1, trivial; 0. 1-0. 3, small; 0. 3-0. 5, moderate; 0. 5-0. 7, large; 0. 7-0. 9, very large; and 0. 9-1. 0, almost perfect  [22]. Statistical significance was accepted at p 0. 05. The statistical analyses were performed using SigmaStat 3. 5 software.
Data analysis The statistical analysis to evaluate the efficacy was performed using the software package SAS® (SAS Institute Inc. , Cary, NC, USA, release 9. 3), with the individual dog as statistical unit. The primary assessment variable in the study was the total number of mites counted in skin scraping following treatment. The percentage of efficacy against S. scabiei var. canis mites was calculated using geometric means with Abbott's formula: Efficacy (%) = 100 × (M C -M T ), where M C is the geometric mean number of total mite counts in the control group (group 3), and M T the geometric mean number of total mite counts in the treatment group (group 1 or 2). Log-transformed [ln(x + 1)] counts of S. scabiei mites were used to confirm the efficacy calculation. Significant differences were assessed between the log-counts of S.
Molecular Docking Study In silico docking is a very famous method employed to investigate molecular association. The knowing of the binding capabilities of the active site residues to specific groups on the agonist or antagonist leads to various strategies for the synthesis of very specific agents with a high probability of biological action. In silico docking experiments were conducted for compounds 1 and 2 against the X-ray crystal structure of b-estradiol-bound ERα receptor ligand binding domain (ERα-LBD, PDB: 1A52)  [13] , to compare the binding affinity of the tested compounds. Estrogen (standard drug) reveals Mol-Dock score of ´105. 9 and forms three hydrogen bonds between its phenolic OH moiety and Glu 353 with a bond distance of 2. 41 Å and another bond with Arg 394 with bond distance of 3.
19 Å and the alcoholic OH form one hydrogen bond with His 524 with bond distance of 2. 70 Å (Figure  3 ). Compounds 1 and 2 exhibited binding scores ´77. 61 and ´18. 54, respectively. Compound 1 has relatively good MolDock score and made two hydrogen bonds with same amino acids in the active site of ERα-LBD. The knowing of the binding capabilities of the active site residues to specific groups on the agonist or antagonist leads to various strategies for the synthesis of very specific agents with a high probability of biological action. In silico docking experiments were conducted for compounds 1 and 2 against the X-ray crystal structure of b-estradiol-bound ERα receptor ligand binding domain (ERα-LBD, PDB: 1A52)  [13] , to compare the binding affinity of the tested compounds. Estrogen (standard drug) reveals Mol-Dock score of -105.
General Experimental Procedures UV and IR spectra were obtained employing Perkin-Elmer Lambda 40 and Perkin-Elmer Spectrum BX instruments (PerkinElmer, Inc. , Waltham, USA), respectively. VLC grade (Macherey-Nagel, Polygoprep 60-50C18) was used for vacuum liquid chromatography. All organic solvents were distilled prior to use. HPLC was carried out using a Waters system, controlled by Waters Millenium software, consisting of a 600E pump, a 996 PDA, and a 717 plus autosampler (Waters Corporation, Milford, MA, USA). All NMR spectra were recorded on a Bruker Avance 300 and 500 DRX spectrometers (Bruker Corporation, Rheinstetten, Germany). Spectra were referenced to the residual solvent signals with resonances at δ H{C 2. 04/29. 8 (acetone-d 6 ) and δ H{C 7. 26/77. 0 (CDCl 3 ). ESI mass spectra were obtained on an Applied Biosystems/MDS Sciex API 2000 MS spectrometer (Applera Corporation and MDS Inc.
During that time the cells growing on top of the spots are being reverse transfected with prey and reporter plasmid. In cells coexpressing an interacting bait-prey pair, cytokine stimulation results in activation of the fluorescent reporter, which is detected by automated microscopic imaging. The fluorescence intensity of each spot is extracted using imaging analysis software applying a superimposed grid on each well of the array (Fig. 2A ). Typically, quadruplicate wells of each tested condition (e. g. with or without cytokine in the case of MAPPIT, or cytokine with or without MTX/TMP fusion compound in the case of MASPIT) are measured. The fluorescence intensity ratio between the differentially treated spots is calculated and analyzed using the Rank Product approach in order to generate a q-value used to sort the interactions  (26).
By combining MASPIT with the current cell microarray format, we now have access to a platform at a scale and throughput that enables application at industry level. The featured FIG. 5. A MASPIT cell microarray screen detects tamoxifen target proteins. A, A MASPIT ORF screen was performed in which quadruplicate wells of each screening plate were differentially treated with either leptin alone or leptin combined with 0. 1 M TMP-tamoxifen fusion compound. Data was analyzed as described in Fig. 3A. Interacting proteins confirmed in MASPIT retests are indicated. See supplemental Table  S4  for raw data. B, MASPIT retest of the hits selected using the standard selection thresholds (qϽ10 Ϫ10 ; ratio median value particle countϾ2). Cells coexpressing the DHFR anchor fusion and the indicated ORF preys were stimulated with leptin alone or leptin combined with 0.
Acknowledgment-We thank  Peter Van Den Hemel  for the continued IT support. * This work was supported by grants from the  Belgian government  (Interuniversity Attraction Poles Project  P6/36 ), the  Fund for Scientific Research -Flanders  ( FWO-V Project G. 0864. 10 ) and the  NIH  ( U01 HG001715 ). J. T. is the recipient of an  ERC Advanced Grant  (#  340941 ). □ S This article contains supplemental material. ¶ ¶ To  whom correspondence should be addressed:  VIB -Ghent University, Albert Baertsoenkaai 3, Ghent 9000 Belgium. Tel. : ϩ32 9  264 93 02 ; Fax: ϩ32 9  264 94 92 ; E-mail: jan. tavernier@vib-ugent. be. Current address: ʈʈOrionis  Biosciences, Ghent, Belgium. a  Sorbonne Universites, UPMC, INSERM, Centre de Recherche Saint-Antoine, Paris, France. b  Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, Massachusetts and Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, Massachusetts.
Fossil Beauprea-type pollen records The key words Beauprea, Beaupreaidites, and Peninsulapollis were fed into Google Scholar for the period 2013-2015, and all scholarly papers where they were mentioned were obtained. These were supplemented with records in volume 11 (Proteaceae issue) of Australian Systematic Botany. The identity of each Beauprea-type pollen species-rarely leavesas assigned was noted ("aff. " was treated as a separate species and "cf. " was treated as the same species), as well as its geographical location, estimated geological age, and whether it co-occurred (same sample) with Nothofagidites pollen. The age of the pollen was taken as the oldest recorded in actual stratigraphy diagrams (including multiple records in the same paper) or the exact midpoint if only part of a geological stage was noted; for example, if given as Late Santonian (that is, 85.
orbiculatus as being synonymous with Beauprea. We independently assessed all characters for Beauprea, Beaupreaidites, and Peninsulapollis but only supplemented characters for the other taxa from those listed by Sauquet et al. (42)  to ensure that all characters used were in common. Data or pollen photos were obtained from the studies of Pocknall and Crosbie (32), Dettmann and Jarzen (33), and Sauquet et al. (42)  and from other relevant papers. Characters that were unchanged among all species or for which complete data were unavailable were omitted. The consequent pollen morphological matrix comprised 11 binary and multistate characters (ordered for analysis). A neighbor-joining tree was constructed using PAUP software  (63). Estimates of the statistical significance of phylogenies were calculated by performing 1000 neighbor-joining bootstrap replicates.
The sequences were edited and aligned, and the alignments were joined using the computer software CLC Bio Genomics Workbench (CLC Bio-Qiagen). We used BEAST v2. 1. 0 to estimate phylogeny and divergence times under a relaxed clock model  (64). The data set partition for chloroplast DNA was unlinked and set to a general time-reversible model with g-distributed rate heterogeneity. We used a Yule prior for rates of cladogenesis and ran 10,000,000 analyses with a 10% burn-in and sampling every 2000 generations. Two fossil species were used to calibrate the tree. A minimum age for crown Beauprea was based on B. orbiculatus  (38) , the oldest pollen with Beauprea affinities according to our literature search, set at 83. 8 Ma (exact midpoint of the Upper Santonian, 84. 1 to 83. 5 Ma, in which the fossil was located).
The crown of Proteaceae was set at 95. 1 Ma, the midpoint of the Upper Cenomanian (96. 6 to 93. 6 Ma) in which the oldest pollen (Triorites africaensis) with Proteaceae affinities is recorded  (48) , as also supported by Sauquet et al. (42). We used the lognormal distribution prior for age reconstruction in BEAST. The Bayesian framework, as implemented in BEAST, allows modeling of calibration uncertainties  (65) , and 95% HPD intervals of age estimates are given as output data. Five separate runs were implemented, and results were viewed in Tracer and then combined using the LogCombiner package in BEAST. TreeAnnotator v2. 0. 3 was used to generate a maximum credibility tree based on this analysis  (66).
Acknowledgments: Special thanks to  C. Zongo  (deceased) for field assistance during our collecting trip in New Caledonia. We thank  S. Isnard ,  S. McCoy ,  H. Vandrot ,  G. Gateble , and  D. Letocart  for logistic and field assistance for material collection, and  L. Milne  for insightful discussions about Beauprea fossils. Funding: This work was supported by the  Australian Research Council  ( DP120103389 ). Author contributions: T. H. and B. B. L. conceived the idea and designed the study. T. H. , B. B. L. , and B. F. collected experimental material and performed the experiment. T. H. and B. B. L. performed the analysis and wrote the manuscript. Competing interests: The authors declare that they have no competing interests. Data and materials availability: DNA sequences generated in this study are accessible from the  NCBI database.
Landscape of kinase activity responses under perturbation To extensively study the heterogeneity and specificity of the human signaling response, we compiled and standardized 41 quantitative studies reporting the relative changes in phosphopeptide abundance after perturbation (see Materials and Methods). From the detected peptides, we collected identifications for 119,710 phosphosites in 12,505 proteins, 63% of which were already reported in phosphosite databases  (Fig EV1). For these sites, we normalized a total of 2,940,379 quantitative changes in phosphopeptide abundance in a panel of 435 biological conditions covering a broad spectrum of perturbations including targeted kinase inhibition, induced hESC differentiation, or cell cycle progression, among many others  (Appendix Fig S1, Table EV1).
In particular, for longer timescales this could be a confounding effect that should also be mitigated by the analysis of sets of sites. The described analysis can be periodically updated as new kinase targets are characterized and new human perturbation experiments refine the map of signaling responses. As such, we will maintain a growing online application (http://phosfate. com), where the community can explore the signaling regulation of all conditions in the atlas and analyze and compare their own phosphoproteomic datasets. The larger number of perturbations identifies the possible roles of kinases and how they relate to each other. We have shown that generalist kinases do not tend to be more essential than specialist kinases but, instead, tend to be more central in the signaling network.
Compilation of human quantitative phosphoproteomic data The atlas integrates a compilation of 41 selected publications reporting human MS-derived changes in phosphopeptide abundance under 435 perturbations. In order to consider a dataset for the atlas, we required peptide sequences, phosphorylation identifications, and detailed description of the biological perturbation and control for a minimum of 1,000 phosphopeptides (Table  EV1 ). From the 41 studies included, only the raw spectra derived from 16 studies were made available in public repositories. Three additional studies were deposited in the no longer available Tranche. The different labeling methodologies make difficult the processing of the public spectra with a common pipeline. Additionally, due to the poor metadata annotation of some of the conditions, reprocessing the spectra would not be possible for some of the datasets.
For these reasons, we relied on the original MS identifications performed by the experimental groups. We collected all quantifications from the supplementary data available in each of the 41 studies, including both significant and not significant changes. To standardize the peptide sequences and site positions across studies, we mapped all peptides to the same reference proteome using Ensembl v73  (Cunningham et al, 2015). For data storage purposes, we mapped the peptide quantifications to all matching protein isoforms and transformed all quantifications into log 2 ratios. Finally, the remapped 2,940,379 phosphopeptide quantifications and all their metadata were stored in a MySQL database that is publicly available in the Downloads section of http://phosfate. com.