dataesr/scientific-paragraphs-categorization huggingface dataset:
Z), Polymerase II and CTCF. The chromatin state defined possesses specific functional, experimental, conservation, annotation and sequence-motif enrichments. In this work, we develop a novel HMM to classify genome-wide RT programs from 42 datasets into 15 RT states such that these RT states can be used to annotate the genome. The RT state annotation improves over the RD annotation (constitutive and developmental) introduced earlier  (Dileep et al. , 2015; Rivera-Mulia et al. , 2015)  by offering richer and more quantitative annotation with better resolution. Although both the RT and the chromatin states are developed from applying HMM to demarcate the chromosomes into segments of diverse flavors, the RT and chromatin states have different properties and are complementary to each other. In addition to the source of information, the major differences between RT and chromatin states are 4-fold: (1) while chromatin states change from one cell type to another, RT states is not cell type -specific.
Indeed, the state of the art presents various solutions that use different techniques (both 2D and 3D) such as monocular vision  [4] , CCD cameras  [5]  or laser range-imaging  [6]. Many types of vision systems and range sensors are available today, but the design and integration of them needs to take consideration of many issues such as; accuracy, speed, reliability, and cost, as well as environmental operating constraints such as; lighting, temperature, and humidity. Besides good sensing abilities, it is necessary to develop systems that can reduce the time and difficulty associated with tool path programming. In this respect, offline programming software (OLP)  [7]  has been developed in recent years, both as commercially available products (such as KUKA. Sim for KUKA  [8] , RobotStudio for ABB [9] and MotoSim for Motoman [10]) as well as in academic research field (for example ROBOMO  [11]  and Robott  [12] ).
System overview The automation of the fastener painting has been thought as a partially automated process where the human operator presents the parts to be operated by the robot, after having performed other manual operations on it previously. Each part is provided by an RFID tag that is scanned before presenting the part to the robot, and that allows uploading from a database the corresponding part information. After the manual operation, the part will be transferred to the painting robot by a conveyor. As the part will be placed randomly on the conveyor by the operator, painting robot must rely on external sensors to detect the exact position and orientation of the part in front of it. Meanwhile, specific painting end-effector will need to be designed as well for different fastener models in a real-world application.
Experimental Results To evaluate the proposed painting system, a test part with five fasteners was used in the experiment. Software running on the robot is written by the ABB RAPID programming language. Experiments were conducted with the set-up as shown in Figure  2 (b). Experimental results are illustrated in Figure  6. From the results, we can see that the fasteners can be successfully painted with the proposed system. It was observed that the vision accuracy could be affected by the ambient light. 5 camera acquisitions of the part were made at the shortest possible time span one after the other at four different times during the day (10 am, 1 pm, 2 pm, 5 pm) in order to test the camera with different levels of light and different light directions. The average errors between the camera results and the real positions are measured for all cases.
Hydrogen-deuterium exchange mass spectrometry was first applied to determine whether a specific peptide-docking site could be mapped on AGR2. Subsequently, an optimized consensus site for AGR2 binding peptides was used to search for human proteins with this consensus motif. An enrichment of transmembrane proteins containing the motif was identified suggesting that a major role for this motif could be in binding to client proteins destined for membrane localizations. A specific protein-protein interaction with the oncogenic membrane receptor EpCAM was validated. This suggests a mechanism for how this docking site on EpCAM can impact on the AGR2-EpCAM protein-protein interaction. These data have implications for how this ER-resident chaperone mediates maturation of proteins destined for the plasma membrane.
E. coli strains harboring plasmids were grown aerobically at 37 °C and 200 rpm in Luria-Bertani (LB) broth medium, supplemented with ampicillin (100 g/ml). Plasmids-The AGR2 recombinant plasmid (pmAGR2) encoding the mature version of the protein was described previously  (24). AGR2 was previously cloned into pDEST17 using Gateway cloning system (Invitrogen). The plasmid pmAGR2 contains an in-frame 6ϫ Histidine (His) epitope tag fused to the N terminus of AGR2 (amino acid. EpEX (amino acid 24 -265 of accession number NM_002354) was chemically synthesized and human codon optimized (GeneArt Gene Synthesis, ThermoFisher Scientific) and cloned into pET151/D-TOPO harboring 6x His epitope tag followed by TEV protease site fused to N terminus of EpEX. Mutants His-AGR2 and His-EpCAM were made according to the protocol described in QuickChange site-directed mutagenesis (Agilent Technologies) using High Fide-lity PCR, 2x Pfu Turbo master mix (Rovalab).
g. the deuteration reaction and sample processing were performed on four different days) with representative data from a time course of deuteration (AGR2 without and with peptides or wt-AGR2 compares to the AGR2 S134A mutant) highlighted in each experiment. Multiple peptide replicates were used to select data and the HDExaminer software selects peptides with high confidence meaning the selected peptides are identified in all submitted MS data of all samples (nondeuterated and deuterated time intervals). When peptic peptides are not identified in all time course samples, then the peptide is excluded from the analysis. Shorter peptides were used for HDX data interpretation (such as Figs. 4  and 5 ) and all set of the peptides identified by LC-MS/MS and submitted for HDExaminer evaluation are included in the Supplementary Figures.
1% formic acid in water, B -80% acetonitrile/0. 08% formic acid. The immobilized pepsin column, trap cartridge, and the analytical column were kept at 1 °C. Mass spectrometric analysis was carried out using an Orbitrap Elite mass spectrometer (Thermo Fisher Scientific) with ESI ionization on-line connected with a robotic system based on the HTS-XT platform (CTC Analytics). The instrument was operated in a data-dependent mode for peptide mapping (HPLC-MS/MS). Each MS scan was followed by MS/MS scans of the top three most intensive ions from both CID and HCD fragmentation spectra. Tandem mass spectra were searched using SequestHT against the cRap protein database (ftp://ftp. thegpm. org/fasta/cRAP) containing sequences of the AGR2 proteins with the following search settings: mass tolerance for precursor ions of 10 ppm, mass tolerance for fragment ions of 0.
6 Da, no enzyme specificity, two maximum missed cleavage sites, and no fixed or variable modifications were applied. The false discovery rate at peptide identification level was set to 1%. Sequence coverage was analyzed with Proteome Discoverer software version 1. 4 (Thermo Fisher Scientific). Analysis of deuterated samples was performed in HPLC-MS mode with ion detection in the orbital ion trap and the data were processed using HDExaminer (Sierra Analytics). Graphs summarizing deuteration kinetics were plotted using the Draw H/D Protection Plot  (34). All peptide plots (graphs showing % deuteration over a time course) are summarized in supplemental Figs. S1-S8. The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium via the PRIDE repository with the data set identifier PXD005782.
Cells were grown in 24 well plates over glass coverslips (diameter: 16 mm). Cells were transfected as indicated in the legends of Figs. 14  and 15. Twenty-four hours later, cells were fixed with 4% paraformaldehyde in PBS for 15 min at RT, permeabilized using 0. 25% TritonX-100 in PBS for 10 min, and blocked with 3% BSA in PBS for 30 min. Antibodies from different species (as described in the legends of Figs. [13] [14] [15]  were incubated on the slides, with combinations of AGR2 mouse (4. 1  (34) ) or rabbit antibodies (K47) and EpCAM antibodies (rabbit antibody, HPA026761, from Sigma, or mouse antibody, VU-1D9, from Calbiochem) at dilutions of 1:250 overnight at 4 °C. Proximity ligation was measured using the OLIGO Duolink designated protocol (35) using anti-mouse and anti-rabbit probes (Sigma, probe product number are 92004 (mouse minus) and 92002 (rabbit plus)).
1A , lane 5) can also be affinity purified using the Peptide A4 coupled beads (Fig. 1A , lane 8 versus 5-7). We evaluated the specificity of the peptide in affinity capture of AGR2 protein from beads without peptide (Fig. 1B , lane 2) and beads with peptide (Fig. 1B , lane 3). These data indicate that Peptide A4 can be used to affinity purify dimeric or monomeric protein and suggest the bioactivity of this peptide motif in crude lysates to AGR2 is relatively specific. However, the silver stain gel does reveal high molecular mass proteins that might either be binding to the peptide direct or through association with AGR2. These potential AGR2 binding proteins that were in these fractions were not evaluated. Nevertheless, the relative specificity of this peptide for AGR2, as defined by its ability to affinity purify the protein from crude lysates, suggests that this feature of AGR2 might selectively drive (some of) its protein-protein interaction functions.
We had previously set up hydrogen-deuterium exchange using the N-terminal domain of MDM2 protein (amino acids 1-126) as a model system to define effects of ligand binding on the exchange reaction  (32)  and the methodology in this study used ExPro Script to measure deuteration rates. Because this data was published, a new software package became available for use by life scientists (HDExaminer). This provides an additional robust tool to study protein dynamics in solution using deuterium exchange methodologies. We first evaluated, therefore, MDM2-ligand binding using HDExaminer as a positive control to measure the integrity of the data acquired using our methodology including; sample acidification after deuteration, freezing, thawing, and injection onto an immobilized pepsin column (flow rate FIG.
The protein in the polyacrylamide gel was (A) immunoblotted to determine whether intermediary species of cross-linked AGR2 could be affinity purified and (B) stained with silver to measure total protein captured. In part B, streptavidin beads were incubated with buffer only (lane 1), lysates (lane 2), and lysates with preconjugated peptide-A4-beads (lane 3). The 18 kDa and 36 kDa cross-linked and affinity purified silver-stained proteins (arrows, lane 3 versus lane 2) were excised using trypsin and AGR2 protein was confirmed present by MALDI-TOF mass spectrometry (data not shown; dimeric excised band; only human AGR2 peptides were detected, Score ϭ 161; queries matched ϭ 4; emPAI ϭ 0. 86). 100 l/minute), peptide trapping and desalting using a peptide microtrap for 3 min at flow rate 50 l/minute and peptide separation using an analytical column with a linear gradient.
S3  contains all of the primary raw graphical data and supplemental Fig. S4  visualizes overall datasets using a butterfly plot). The peptic coverage of a representative experiment using ligand-free AGR2 is shown in Fig. 3C. Peptic cleavage is not completely random throughout the sequence and can generally be grouped into four distinct domains (Fig. 3C ). These domains contain (1) the N-terminal domain from amino acids 21-53 that harbor intrinsically disordered sequences that negatively regulate dimer formation (7) (  23 ); (2) the central domain containing amino acids 54 -108 that harbor the dimer interface  (7) , the CXXS thioredoxin fold, and the Reptin docking site (20); (3) a region N-terminal to the specific peptide-binding domain (amino acids 109 -130; this study); and (4) the specific peptide binding domain adjacent to the ER retention site (Fig.
B, A representation of the minimal deuteration responsive motif from amino acids 131-135 motif (highlighted in pink) in AGR2 (PDB code: 2LNS) that is most significantly suppressed by peptide A4 binding. The main amino acids of focus were D132, P133, and S134 flanked by the hydrophobic amino acids V131 and L135. C, Data showing alanine substitution mutations generated at codons D132, P133, and S134 in bacterial expression plasmids with the corresponding DNA sequencing chromatogram traces of three of AGR2 peptide docking site mutations at position Asp132 to Ala, Pro133 to Ala, and Ser134 to Ala. D, An SDS-Coomassie blue gel showing the relative purity of the indicated mutant proteins expressed in E. coli after nickel affinity purification. E-F, An ELISA assay was developed to measure the binding of AGR2 to synthetic biotinylated peptide A4 captured on the streptavidin coated solid phase.
Reactions were added to the solid phase to measure binding to biotinylated peptide A4 on the solid phase. The data plot the binding of AGR2 in relative light units (RLU) as a function of increasing wt or mutant AGR2 protein isoforms, as indicate (in g) that was quantified using AGR2 specific antibody. pacts of AGR2 on p53 activity  (27). Proximity Ligation assays were performed in MCF7 cells (AGR2ϩ/EpCAMϩ) where the cells were incubated with different antibodies to the two proteins. We tested two sets of AGR2 and EpCAM antibodies. The first pair was an AGR2 mouse monoclonal antibody and an EpCAM rabbit polyclonal monoclonal (Fig. 10B , top panel). The merged data reveal cytosolic foci for the two proteins indicative of a protein-protein interaction. The second antibody set included an AGR2 rabbit polyclonal antibody and an EpCAM mouse monoclonal antibody (Fig.
Mutation of the Peptide-docking Site On AGR2 Induced a Gain-Of-Function Activity in EpCAM Protein Binding-Given the data highlighting a cell-based protein-protein interaction in cells suggests a physiologically relevant protein interaction pair, we set out to further fine map the impact of mutagenesis on the AGR2 and EpCAM protein interactions. The peptidebinding AGR2 mutants (D132A, P133A, and S134A) that exhibit neutral or attenuated binding to the synthetic peptide A4 (containing the TTIYY motif) were evaluated in EpCAM protein binding to determine the effects of these mutations on the AGR2: EpCAM protein-protein interaction. The AGR2:EpCAM binding reaction revealed a gain-offunction of all three mutants, relative to wt-AGR2. AGR2 S134A exhibited the most elevated gain-of-function activity (Fig.
The peptides sequences created are shown on the X-axis. The biotinylated peptide A4 was bound to the streptavidin-coated solid phase and fixed amounts (1 g) of AGR2 protein with 100 ng of the indicated synthetic peptide was added. AGR2 binding was detected using a secondary antibody and binding is measured in as RLU. The data revealed that amino acids at positions 2, 4, 5, and 6 are relatively fixed whereas changes at positions 1 and 3 can be relatively well tolerated. B, Schematic illustrating strategy to find novel AGR2 client proteins using linear peptide motif database mining. The AGR2 linear peptide consensus motif was used as input using a ScanProsite tool (http://prosite. expasy. org/scanprosite/) and the human proteome database was screened to identify proteins containing the motif.
05 value (depicted in yellow). G, The AGR2 linear peptide consensus motif was used as input using the SLiMSEARCH4 linear motif discovery tool (http://slim. ucd. ie/slimsearch/index. php) and the human proteome database was screened to identify proteins containing the motif. Enriched terms were ranked by p value (Hypergeometric test). H, Venn diagram highlighting the overlap and number of linear motifs identified between ScanProsite and SLiMSEARCH4 tools. it toward an oxidation-sensitive binding site on EpCAM; e. g. this AGR2-binding site on EpCAM is apparently sensitive to EpCAM redox state. Lastly, these data suggest that the conformation of EpCAM can also have distinct impacts on the stable binding of AGR2 protein. To evaluate whether AGR2 S134A does, in fact, have an altered conformation which is inferred from its-gain-of-function activity, hydrogen-deuterium exchange mass spectrometry was used to probe whether amide hydrogen-bonding deuterium exchange rates differ.
C, Three-dimensional cartoon representation of extracellular part of human EpCAM (PDB code: 4MZ) highlighting the AGR2 linear peptide motif at amino acid position Thr247 to Tyr251 9 (gray). Color coding is the same as in (B). D, Schematic representation of his-tagged EpCAM protein sequence highlighting the extracellular domain (EpEX), the TEV cleavage site, and the TLIYY motif. E, Coomassie Blue staining of purified His-EpCAM showing the major band at 32 kDa under reducing SDS-PAGE condition. F-G, Solid-phase binding assay to measure AGR2 binding to EpCAM protein. Increasing amounts of EpCAM were immobilized on the surface of a microtiter plate (0 -1 g). AGR2 (0 -1 g) was titrated in the mobile phase and AGR2 binding to immobilized EpCAM was quantified using AGR2 specific antibody. The binding of AGR2 is plotted as the extent of protein-protein complex formation as RLU as a function of increasing protein in the mobile phase.
H, DNA sequencing chromatogram traces of EpCAM Y251A. I, Coomassie Blue staining of purified His-EpCAM Y251A mutant protein showing the major band at 32 kDa under denaturing SDS-PAGE. J, His-EpCAM or His-EpCAM Y251A (1 g) was immobilized onto the well surface of a microtiter plate as in (F) His-AGR2 WT (0 -1 g) was titrated in the mobile phase. AGR2 binding to immobilized EpCAM was quantified using AGR2 specific antibody. The binding is plotted as the extent of protein-protein complex formation as RLU as a function of increasing protein in the mobile phase. mal in 3-dimensions (Fig. 14D , in red). These two regions also map adjacent to the TLIYY motif (Fig. 14D , in green) and overlap the detergent (decyl-beta-d-maltopyranoside decylmaltoside) binding pocket (Fig. 14D , molecule imbedded from PDB code 4MZV).
DATA AVAILABILITY The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium via the PRIDE repository with the data set identifier PXD005782. tion (MOHE) of Malaysia KPT(BS)870809015063 (MAM). The International Centre for Cancer Vaccine Science project is carried out within the International Research Agendas programme of the Foundation for Polish Science cofinanced by the European Union under the European Regional Development Fund. □ S This article contains supplemental material. ** To whom correspondence should be addressed: University of Edinburgh, Institute of Genetics and Molecular Medicine, Edinburgh, Scotland, United Kingdom, EH4 2XR. E-mail: ted. hupp@ed. ac. uk.
We review here the role of angular momentum distributions in the fission process. To do so the algorithm implemented in the FIFRELIN code [1] is detailed with special emphasis on the place of fission fragment angular momenta. The usual Rayleigh distribution used for angular momentum distribution is presented and the related model derivation is recalled. Arguments are given to justify why this distribution should not hold for low excitation energy of the fission fragments. An alternative ad hoc expression taking into account low-lying collectiveness is presented as has been implemented in the FIFRELIN code. Yet on observables currently provided by the code, no dramatic impact has been found. To quantify the magnitude of the impact of the low-lying staggering in the angular momentum distribution, a textbook case is considered for the decay of the 144 Ba nucleus with low excitation energy.
Indeed this decay process depends on the nuclear property of the isotope, such as the level scheme and transition branching ratios (or decay widths). These quantities can be obtained experimentally with spectroscopy techniques but the number of accurately measurable levels is limited. The limitations are not only due to statistics or to experimental resolution but can also come from the unstable nature of the isotope (β-decay). Therefore to describe the nuclear structure above some given level, models are used to fulfill gaps. In the present work we highlight the role of a specific degree of freedom in the fission phenomenon: the angular momenta of levels of fission fragments. To illustrate where these distributions can be used in fission models, we present first the model implemented in the FIFRELIN code  [1]  to describe fission observables.
Generation of initial fragments Particle emission in the FIFRELIN code is based on the Bečvář algorithm  [2]  for the simulation of γ cascades with extension to the emission of prompt neutrons. The decay algorithm and fission fragment (FF) generation are stochastic. Fission events are sampled many times and decay properties of fragments are recorded so that average properties can be provided to compare with experimental data. More detailed quantities can also be provided as well as correlations between observables. The first step in a simulation consists in sampling FF and FF states. The mass fragmentation is sampled in an experimental yield Y(A) such as shown in Fig. 1  for the 252 Cf(sf) reaction. The charge fragmentation is sampled according to a gaussian distribution P Z (see Fig. 1 ) with a mean value Z p that is given by the unchanged-charge-density value shifted by ±∆Z.
The usual Eq. (  1 ) has thus been modified in FIFRELIN so that even-odd enhancements can be reproduced. We also had to modify the code so that parity is sampled before angular momentum so that different distributions can be used according to parity. The alternative parity-dependent angular momentum distribution used is: P(J) = a(1 -a) 2 + 1 P(J) + a(a + 1) 4 [P(J + 1) + P(J -1)] a(π = +) = f a(π = -) = -f (6) In Eq. (  6 ), P(J) stands for the usual Rayleigh expression (Eq. (  1 )). Only even-even nuclei are impacted by this modification as it is expected that single-particle excitations quickly wash out the collective structures. In Eq. (  6 ), f is a parameter controlling the strength of the enhancement. For f = 0 one obtains P(J) = P(J), whereas for f = 1 one only obtains selected spins.
In order to better analyse the topology of proteins, protein complexes and their environment, we propose a panel of methods based on rigorous mathematical grounds, implemented in the numerical program VLDP (Voronoi Laguerre Delaunay Protein) 4-6 , freely available as web server 6 or upon request to the authors. The first task performed by VLDP is to build the Laguerre, or weighted Voronoi, diagram of the data, typically a set of positions describing the molecular structure as provided by bio-structural techniques, e. g. crystallography, NMR spectroscopy or simulation (molecular dynamics, Monte-Carlo, etc. ). Many such structures are registered in molecular data banks such as the PDB or NDB 7. The Laguerre space partition is the basis underlying all the implemented topological analysis methods: inter-atomic, inter-residue or inter-molecular contacts, connected components of the bulk or of the surface, optimal paths, porosity, genus of the surface, stratification.