dataesr/scientific-paragraphs-categorization huggingface dataset:
On the other hand, the spatial coverage of CALIFA is larger than any of those surveys, both in physical and in projected terms (five times larger than SAMI and two times larger than MaNGA). In summary, CALIFA is the survey that samples the galaxies with the largest number of spatial elements for the largest FoV. The penalty for this wider coverage is the lower number of galaxies observed (6 times lower than SAMI and 15 times lower than MaNGA), and a lower spectral resolution of CALIFA in the full wavelength range. The shorter redshift range, covering 300 Myrs in cosmological times, provides homogeneity of the derived properties, such as the SFH or the gas abundances, which in other surveys should be corrected prior to making an homogeneous comparison of their full sample. The dataset analysed so far have produced significant advances in our knowledge of the stellar and gas composition in galaxies, their kinematical structure, and the overall star formation history and chemical enrichment (as reviewed in the introduction).
We have uncovered new local relations within galaxies, tightly connected to the global ones described using classical spectroscopic surveys. With this new DR we open to the astronomical communitty the posibility to futher analyse the spatially resolved properties of galaxies, presenting a panoramic view of the galaxy properties. Notes. ( a) CALIFA unique ID number for the galaxy. ( b) Equatorial coordinates of the galaxies as provided by NED. ( c) Redshift of the galaxies based on SDSS DR7 spectra or complemented with SIMBAD information if SDSS spectra are not available. ( d) Petrosian magnitudes as given by SDSS DR7 database corrected for Galactic extinction. ( e) Morphological type from our own visual classification (see W14 for details). "(x)" indicates ongoing mergers. ( f) Bar strength of the galaxy as an additional outcome of our visual classification.
Acknowledgements. CALIFA is the first legacy survey being performed at Calar Alto. The CALIFA collaboration would like to thank the  IAA-CSIC  and  MPIA-MPG  as major partners of the observatory, and CAHA itself, for the unique access to telescope time and support in manpower and infrastructures. The CALIFA collaboration thanks also the  CAHA  staff for the dedication to this project. RGB, RGD and EP are supported by the  Spanish Ministerio de Ciencia e Innovación  under grant  AYA2010-15081. SZ has been supported by the  EU Marie Curie Integration Grant "SteMaGE" Nr. PCIG12-GA-2012-326466  ( Call Identifier :  FP7-PEOPLE-2012 CIG ). JFB acknowledges support from grants  AYA2010-21322-C03-02  and  AIB-2010-DE-00227  from the  Spanish Ministry of Economy and Competitiveness (MINECO) , as well as from the  FP7 Marie Curie Actions  of the  European Commission , via the  Initial Training Network DAGAL  under  REA  grant agreement number  289313.
Support for L. G. is provided by the  Ministry of Economy, Development, and Tourism's Millennium Science Initiative  through grant  IC12009 , awarded to  The Millennium Institute of Astrophysics, MAS. L. G. also acknowledges support by  CONICYT  through  FONDECYT  grant  3140566. AG acknowledges support from the  FP7/2007-2013  under grant agreement n. 267251 (AstroFIt). JMG acknowledges support from the  Fundação para a Ciência e a Tecnologia (FCT)  through the  Fellowship   SFRH/BPD/66958/2009  from  FCT (Portugal)  and research grant  PTDC/FIS-AST/3214/2012. RAM was funded by the  Spanish programme of International.
Conversely, insertions in loci encoding the other two regulatory systems caused elimination or reduction of capsule formation, indicating that these are activators of CAP biosynthetic gene transcription. The second regulatory pathway, identified by 24 transposon insertions, is the BarA-GacA two-component signal transduction relay system. BarA-GacA is known to regulate a broad range of virulence and stress response systems in various gram-negative bacteria  [20]. The third regulatory system is identified by 14 insertions in pflu3654-pflu3657, a genomic region directly upstream of the CAP biosynthetic genes (see Fig. 3 ), most of which has no significant database matches. Notably, when a transcriptional fusion of gfpmut3 and the genomic region upstream of pflu3655-pflu3657 was inserted into the 1B 4 genome, expression of green fluorescent protein (GFP) in Cap + cells was observed (see S2 Fig and  S2  Text).
This demonstrates that this region contains a promoter sequence transcribed in response to the capsule ON signal. None of the above regulators bears homology to the Rcs phosphorelay that controls colanic acid gene transcription in the Escherichia, Erwinia, Klebsiella, and Rhizobium genera  [21]. Indeed, a search of the SBW25 genome using translated Basic Local Alignment Search Tool nucleotides (TBLASTN, a tool used to search a query protein against a translated nucleotide database) revealed no loci with homology to E. coli rcsA.
Genome Sequencing of Re1_4 A Re1_4 colony was grown overnight in KB. Cap + and Cap -fractions were separated by centrifugation, and genomic DNA was isolated from each fraction using the CTAB method. Equal quantities of each isolated DNA were mixed, and whole genome resequencing was performed (Illumina; Massey University, New Zealand). Point mutations were identified by aligning 36bp sequence reads to the SBW25 genome  [49]  via SOAP (short oligonucleotide alignment program  [50] ) and ELAND (Illumina). Insertions and deletions were identified by analysing genomic regions with unusual coverage and BLAST (Basic Local Alignment Search Tool) analysis of discarded sequences.
mRNA-seq Analysis SBW25, 1A 4 , and 1B 4 colonies were grown overnight in KB, diluted 1:1000 into 20 mL KB, and incubated for 24 h. Total RNA was harvested from each; for SBW25 and 1A 4 , 100 μL culture was mixed with 900 μL KB, pelleted, and resuspended in 1 mL of RNAlater (Ambion). For 1B 4 , 100 μL was separated into Cap + and Cap -by centrifugation, and each was resuspended in 1 mL RNAlater. All mRNA extractions proceeded using a RiboPure Bacteria Kit (Ambion). Two mRNA preparations from separate colonies were pooled for each strain. Normalized mRNAseq library preparation, followed by 100-bp single-end sequencing, was performed by the Australian Genome Research Facility (Brisbane, Australia; accession number GSE48900). The DEseq R package  [51]  was applied to identify differentially expressed genes.
The remaining culture was used to determine the number of cells per sample (cfu mL -1 ). Samples were extracted by cold extraction  [53]  and submitted to LC-MS, and the data were analysed as previously described  [54]. The second method involved radiolabelling followed by thin-layer chromatography and was used to measure 22 metabolites in triplicate across eight genotypes (S8 Table ). Cultures were grown exponentially in glycerol-SA with aeration and labelled with [ 33 P]-orthophosphate (Perkin-Elmer) from optical density of 0. 1 at 600 nm  [52]. For determination of nucleotide pools in Cap + and Cap -fractions, cultures were separated by centrifugation and propagated in fresh media for at least three generations before sampling. Charcoal-binding nucleotides were extracted, separated by two-dimensional thinlayer chromatography, and quantified  [55, 56].
Simulations Simulations were performed by incorporating the stochastic Gillespie algorithm into a MATLAB program  [28]  (S5 Fig,  S1  Code, and S2 Code). Initial parameter values were assigned randomly (with the proviso that UTP outnumbered activator molecules), and reaction rates were chosen to promote the equivalent of several cell divisions between switch events, reflecting observed heritability. UTP production rates were adjusted from low to high (1,000-fold difference) to simulate the intracellular state of a switcher and ancestral cell, respectively (S6 Fig). Reaction rates were sequentially increased and decreased by a factor of 10 to investigate the role of stochasticity in switching (S7 Fig and  S9  Table ). Simulations were run for 200,000 sec (55. 55 h) before removal of the initial 10,000 sec, allowing escape from any restrictive initial conditions.
2-μL aliquots of resuspension were used to inoculate 148 μL of appropriate fresh medium in wells of a 96-well plate. Four types of media were used: M9 (blue lines on graphs), M9 + arginine (0. 6 mM, pink lines), M9 + uracil (1 mM, orange lines), and M9 + arginine + uracil (green lines). Each of the eight genotype-medium combinations was replicated five times, and the 16 wells were used as media controls. The OD 600 of each well was measured at 5-min intervals for 50 h, with 5 sec shaking prior to each read (using a VERSA max plate reader). Hourly time-point data was plotted (data points are means of 5 replicates +/-1 SE). While 1B 4 grows more slowly than SBW25 in M9, 1B 4 is not an auxotroph. The 1B 4 growth rate deficiency is partially alleviated by addition of arginine, an effect that is increased by the addition of both arginine and uracil.
Comparison showing the effects of mutations 1-8 in the evolutionary series (see Fig. 1A ) on gene expression. Complete dataset available at the National Center for Biotechnology Information (NCBI) Gene Expression Omnibus (GEO) (accession number GSE48900). The table is a list of genes identified by mRNA-seq as having statistically significantly (adjusted p-value <0. 01) different mRNA levels in genotype 1 and genotype 2 (numbered in the order listed above). Each list is split into two worksheets: (a) genotype1_higher and (b) genotype2_higher. Within each unobtainable, while measurements of 0 were used represent concentrations below the limit of detection.
JG was supported by a  Tertiary Eduction Committee Bright Futures Scholarship  and is currently supported by a  Marie Curie IIF  Fellowship. GCF was supported by a  Foundation for Research, Science and Technology Postdoctoral Fellowship. PBR is the recipient of an International Blaise Pascal glimpse of how noise in regulatory networks can provide opportunity for evolution. Research Chair funded by the  French State  and the  Ile-de-France , managed by the  Fondation de l'Ecole Normale Supérieure. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
31 P MAS NMR measurements Magic angle spinning (MAS) NMR experiments were performed on a 9. 4 T Bruker spectrometer at the Larmor frequency of 161. 976 MHz. This equipment is combined with an active glovebox dedicated to the handling of radioactive materials, and described in detail elsewhere  [33]. The rotor was spun between 30 and 50 kHz. The single pulse experiment was made with a duration of 3. 2 μs (π/2). The spectrum was calibrated relative to a solid NH 4 H 2 PO 4 (0. 9 ppm)  [34]  and it was fitted using the "dmfit" software  [35]  with the option "CSA mas".
As one can notice, PuO 9 polyhedra and PO 4 tetrahedra both show a stronger distortion, as already observed for some other monazite-like phosphates  [39, 40]. There are not much difference in the structure of PuPO 4 and PrPO 4. Angles are rather similar. Only P-O1 distance shows a significance difference and concomitantly the Pu-O1 and Pr-O1 distances. This could be due to the different electronic configuration of the two cations. With the interatomic distances determined from the Rietveld analysis, one can now apply the bond-valence method to assess the oxidation state of the atoms (Table  4 ), i. e. by using the program Bond-String implemented in the Fullprof2k suite. The latter implements the empirical Zachariasen's formula s ¼ exp{(d 0 -d)/B 0 } and data from the literature  [41, 42]. The calculated valence states of plutonium, phosphorus and oxygen atoms are close to þ 3, þ 5, and À 2, respectively, and are consistent with the expected values.
R B ¼ Σ [I hkl (obs)-I hkl (calc)]/ ΣI hkl (obs); GOF¼ R wp /R exp. No difference of shape of the white line or periodicity on the first oscillation is observed. Considering the low content of americium, no EXAFS data could be collected to identify the americium local environment, limiting the clear identification of the americium compound. However, the presence of Am III instead of Am IV is fully in agreement with an Am III -phosphate. Based on the chemical/ isotopic compositions and the age of the original PuO 2 , one may conclude that the analyzed sample is actually a solid solution with the chemical formula Pu 0. 98 Am 0. 02 PO 4.
Background: High precision protein loop modelling remains a challenge, both in template based and template independent approaches to protein structure prediction. Method: We introduce the concepts of protein loop clustering and percolation, to develop a quantitative approach to systematically classify the modular building blocks of loops in crystallographic folded proteins. These fragments are all different parameterisations of a unique kink solution to a generalised discrete nonlinear Schrödinger (DNLS) equation. Accordingly, the fragments are also local energy minima of the ensuing energy function. Results: We show how the loop fragments cover practically all ultrahigh resolution crystallographic protein structures in Protein Data Bank (PDB), with a 0. 2 Ångström root-mean-square (RMS) precision.
The different fragments which are already available in the Protein Data Bank (PDB)  [22]  database could then be used like Lego bricks, as structural building blocks in constructing the loops. A given amino acid sequence is simply divided into short fragments, and the shape of the ensuing loop is deduced using homologically related fragments that have known structures. The entire protein is then assembled by joining these fragments together. For the process of joining the fragments, both all-atom energy functions and comparisons with closely homologous template structures in the Protein Data Bank can be utilised  [8, 9, 12, 14]. In the present article we propose a new systematic, purely quantitative method to identify and classify the modular building blocks of PDB loops; we identify a loop following the DSSP  [23]  convention.
clusters The 102 loop fragments in  [41]  that have been measured with better than 1. 0 Å resolution, have between five and nine residues. Here we have argued that a loop fragment modelled by (  10 ), (  11 ) has six residues. There are 70 such clusters among the 200, but only 14 of them contain more than 30 fragments. Moreover, two of these merge together into an α-helical structure, when we subject them to our clustering algorithm; we call them bends instead of kinks. The remaining 12 loop fragments determine clusters which cover around 38 % of the 1. 0 Å protein loop structures, when we use our 0. 2 Å RMSD cut-off. These loop fragments are our final initiators. In Table  1  we list the PDB entry codes and residue numbers of these initiators. We proceeded to describe some of the major features of the ensuing 12 clusters.
Cluster elongation and completion In addition of the 12 initiators listed in Table  1 , among the 102 loop fragments of  [41]  that we have considered, there is also one initiator that has only five residues. The PDB code is 1p1x_A (80-84). The ensuing cluster with five residue long elements is very large: There are a total of 42618 entries. The reason for the occurrence of such a large cluster is that the RMSD clustering criteria 0. 2 Å is too large for revealing clustering patterns in five-residuelong loop segment: The five-residue-long loop fragment covers all the five-residue-long loops, within the chosen cut-off criterion. In Fig. 13  we show the distribution of (κ, τ ) values in this cluster. There is also an overlap with each of the 12 clusters that we obtained previously. Together the 13 clusters cover around 96.
Cluster percolation We have also investigated the relation between the sequence and the structure, using the 42 clusters listed in Tables  1  and 3. Here we only describe some of the major features, more details can be found in Figure  S3  in Additional file 1. There are several examples of identical sequences that correspond to different structures in different proteins. Accordingly a sequence clearly does not determine a unique structure. When a given sequence gives rise to multiple structures, we have a phenomenon we call cluster percolation. These sequences with multiplet structures may be utilised to try and introduce novel clusters. For example, in Table  4  those sequences that are found both in Cluster VIII and outside of it, are listed, together with their PDB identifications and RMSD to the initiator of Cluster VIII.
The two putative kinks between helices C and D correspond to the residue sites  (41) (42) (43) (44) (45) (46)  and  (48) (49) (50) (51) (52) (53). The two putative kinks between helices E and F correspond to residue sites (77-82), and the practically overlapping (78-83). In Fig. 20  we show how in our PDB set, the number of matches for each of these four kinks depends on the RMS cut-off distance. The 1A6M is closely related to the PDB entries 1A6G, 1A6K and 1A6N; they represent four different ligation states of the same protein. Each of the three 1A6G, 1A6K and 1A6N have been measured with resolution above 1. 0 Å, thus they do not appear in our data set. In Table  5  the RMS distance of the four rare kinks of 1A6M are compared to the corresponding kinks in 1A6G, 1A6K and 1A6N. All the RMSD values are below the cut-off 0.
The goal of the PCC compounds is to populate new, biologically relevant chemical spaces that are typically not addressed in traditional screening collections from chemical vendors or corporate collections. This newly designed collection is based on proposals for libraries of compounds that are submitted by academic and industrial chemists (from either within or outside the consortium) adhering to strict quality workflows in terms of design, chemistry validation and production. Here, we describe the initial batch of PCC screening compounds delivered by the ELF Chemistry Consortium during the first 18 months of chemistry activities. These compounds are compared to the Maybridge Screening Collection (http://www. maybridge. com/portal/alias__Rainbow/lang__en/ tabID__146/DesktopDefault. aspx), the collection of the Molecular Library Program (MLP) of the National Institutes of Health (NIH)  [11]  and compounds curated in the ChEMBL database  [12].
The synthesized amounts have been defined so that each sample is available to all HTS campaigns and relevant follow-up activities during the course of the ELF project, without the need for its resynthesis. Additionally, each principal investigator who receives a qualified hit-list at the end of an ELF HTS and hit evaluation campaign could access the relevant physical samples and associated synthetic procedures for the compounds in the qualified hit-list to jump-start additional research efforts. Each hit compound appearing on such qualified hit-lists will be automatically removed from the JECL collection, as a way to protect the intellectual property of the principal investigator. Data sharing across the various ELF chemistry consortium partners, from the original library enumeration performed by the Lead Discovery Center, to experimental validation procedures from academic and SME groups, to the shipment of the final compounds to the screening centers from each SME, is facilitated by Tarosgate, a chemistry management solution especially designed for the ELF project.
2 when using the same ECFP6 metric. Furthermore, the PCC compounds are significantly dissimilar from existing compounds in the other collections considered in the present study. Intercollection similarity is less than 0. 2 for the PCC set compounds when compared with MPL-NIH, Maybridge and the ChEMBL database, as described in Fig. 1. The distributions of molecular descriptors commonly used in medicinal chemistry are shown in Fig. 2  for the PCC set, the Maybridge screening collection, the MLP library and the ChEMBL compound bank. Overall, all libraries share typical Lipinski rule-of-five  [14]  attributes. Here, the PCC library displays the highest polarity and molecular weight. In total, 85% of the PCC compounds have c log P values less than 4 compared with 80% for MLP, 62% for Maybridge and 67% for ChEMBL compounds.
In addition, 58% of the PCC compounds have a molecular mass greater than 400 Da (MLP, 30%; Maybridge, 21%, ChEMBL, 46%). The major differences between the libraries emerge when the number of chiral centers and the fraction of sp 3 hybridized carbon atoms (Fsp 3 ) are considered. 85% of the PCC compounds are chiral with 62% of them having two or more chiral centers (cf. Maybridge, 3%; MLP, 9% and ChEMBL, 22%). PCC compounds also have an increased 3D character, with 68% displaying Fsp 3 greater than 0. 4 (cf. Maybridge, 15%; MLP, 29% and ChEMBL, 34%). This translates as a marked difference at a molecular-shape level. When the 3D conformations of the final compounds were analyzed using the molecular principal moments of inertia (PMI)  [15]  and plane of best fit (PBF)  [16]  methods (see the supplementary material online), PCC compounds demonstrated a significantly less flat and more globular ('sphere-like') shape compared with compounds in any of the databases evaluated in the present study (Fig.
When comparing final compounds and scaffolds profiles, it is interesting to note that the polarity, structural complexity and 3D elements have been engineered in the scaffolds rather than deriving entirely from the subsequent chemical decoration. Given that the PCC scaffolds tend to be small, polar and chiral with a high 3D character, they provide versatile starting points and ample opportunities for further chemical exploration and growth during the hit-to-lead phase, based on the specific biological target and/or therapeutic area requirements. A strong focus of the ELF chemistry consortium is to populate areas of chemical space that are not directly accessible from commercial sources or the scientific literature. Thus, no structural overlap with the Maybridge, MLP or ChEMBL databases is observed.
Future prospects In this study, we present a robust model to study s-adRP in C. elegans. We focused our attention in atl-1 and egl-1, but we have identified other interesting genes in our data set (which is available at the Gene Expression Omnibus [GEO] repository) that are up-regulated in animals with reduced levels of spliceosomal proteins and that may have a role in compensating or repairing such deficiency. Among them, we identified genes coding for spliceosome components such as mog-4, mog-5, prpf-4, or ddx-23 (Supplemental Table  S1 ;  Kerins et al. 2010). Through an increased sensitivity to DNA insults and replicative stress we have opened a third way to explain the retina-specific apoptosis in s-adRP. This alternative way should be explored in terms of therapies that could alleviate the progressive loss of vision in s-adRP patients.
Animals synchronized at L1 stage were treated with the corresponding RNAi clone and grown at 20°C. More than 25 worms were measured after 48 h of treatment in each condition. Animal length is showed in millimeters and was scored using the ImageJ software. Statistical significance was calculated using Student's t-test for independent samples. Three asterisks indicate statistical significance with P < 0. 001. Whiskers were plotted by Tukey's test. (C ) Up-regulation of atl-1 and egl-1 after prp-8(RNAi) is tissue specific. qPCR results for atl-1 and egl-1 expression in wild-type and hypodermis-and muscle-specific RNAi animals represented in a bar graph. mRNA levels of these genes after prp-8(RNAi) are relative to their expression in control animals. Results obtained from three independent biological replicates.