dataesr/scientific-paragraphs-categorization huggingface dataset:
Precision assessment using A. thaliana Precision was evaluated by two parameters: sensitivity and specificity, assessed by comparing the proteins obtained with the workflow in A. thaliana to an "expected group" of proteins of this species. The "expected group" of A. thaliana proteins were the sequences in TAIR database  [32] , which met two conditions, i) there is evidence that these proteins are present in the polypeptides derived from contigs and ii) these proteins have significant homology to the A. lyrata or C. rubella proteomes. We counted as evidence of the presence of a protein of A. thaliana database in the polypeptide sequences produced at step 2, the fact that polypeptides were significantly aligned (i. e. identity > 60, target coverage > 70) to A. thaliana proteins with BLASTP software.
To meet the second condition, the proteins of C. rubella/A. lyrata were aligned to proteins of A. thaliana that met the first condition, these alignments were filtered (identity > 60, target coverage > 70), and A. thaliana proteins retained were considered the "expected group". After applying the workflow, we aligned the resulting A. thaliana protein product (PP) with BLASTP software to the "expected group" of proteins defining three categories: True Positive (TP): A A. thaliana PP has a significant alignment to a protein of the "expected group". False Positive (FP): A A. thaliana PP does not have a significant alignment to a protein of the "expected group". False Negative (FN): A protein of the expected group does not have a significant alignment to a A. thaliana PP. An alignment was considered significant if the identity was at least 60% and the coverage of the protein from the "expected group" was minimum 70%.
Functional annotation in coconut and comparative analysis of metabolic pathways Gene Ontologies: The gene ontology terms of coconut polypeptides before and after step 5 were determined using PRIAM software  [33]. The distribution of proteins in the categories of level II in the three graphs (cellular component, molecular function, biological process) was compared between coconut proteins and Oryza sativa proteins  [27]  with WEGO software  [34]. The enrichment analysis of coconut PPs which consist exclusively of polypeptides derived from new contigs (contigs founded by BRANCH software not identical at the sequence level to the contigs assembled by Trinity) was carried out with GOstats packages version 2. 38. 0  [35]  in R  [36]. A concise visualization of the results was performed with the software Revigo  [37].
Transcriptome representation on a comparative genome hub A website called PalmComparomics http://palm-comparomics. southgreen. fr/ was developed as a representation of the current analysis. This site is based on in-house Apache tools and tools of the Generic Model Organism Database (GMOD) project  [41]. For instance, coconut scaffolded polypeptide matches along oil palm genome are viewable using JBrowse  [42]. We exploited the facilities of Bio::DB::SeqFeature::Store schema to create a MySQL database with the annotations of coconut polypeptides from gff3 files. The website also included the CocoCyc Pathway/Genome Database (PGDB) containing the predicted metabolic pathways.
Data Workflow application in coconut. The methodology was applied to coconut transcriptomic data recovered from NCBI  [4] [5]. The first dataset corresponds to a transcriptomic analysis of endosperm, embryo and leaf of a dwarf variety (SRX518095, SRX534380 and SRX534428)  [4] , while the second represents transcriptome data from a mix of tissues from Hainan tall cultivar (SRX198908)  [5]. The new contigs were identified by using mRNAs of oil palm recovered from the NCBI Reference Sequence Database (RefSeq), annotation release 100  [28]. The translation into polypeptide sequences of coconut contigs was performed using as reference database the proteins of Elaeis guineensis [28], uniprotKB viridiplantae  [27] , Phoenix dactylifera [29] and Musa acuminata  [30]. Finally, Elaeis guineensis proteome (RefSeq 100) [28] was used in step 5 of the workflow to produce a coconut proteome.
Sensitivity and specificity test. We applied the workflow to three transcriptomic datasets of A. thaliana recovered from NCBI: SRR1640366, SRR1640370, SRR2895761  [43, 14]. The proteins of "expected group" of A. thaliana was derived from TAIR10 database  [32]. The Arabidopsis lyrata  [21]  and Capsella rubella  [22]  proteomes were recovered from phytozome v. 11  [44]. Functional annotation. The gene ontology terms of Oryza sativa v 7. 0 were recovered from UniprotKB  [27]. The biosynthetic pathways of Oryza sativa were recovered from PlantCyc  [40]. A complete description of the software and the parameters used in each of the steps of the workflow is described in the document S1 File. This document also presents how you can obtain the main results of our analysis of the website PalmComparomics (http://palmcomparomics.
18-0. 36%), approaching to that observed in A. thaliana (0. 43%). Finally, the average length of the polypeptide sequences was increased from 339 to 429 aa. The identity of alignments to proteins from A. thaliana TAIR10 before and after step 5 remained unchanged (99%), while the average coverage of protein in database was increased from 0. 87 to 0. 90. To describe the impact of the methodology on the coverage, the distribution of this trait was divided into ranges, and amount of polypeptides that changed their coverage range after the scaffolding of step 5 was calculated (S2 Table ). 53. 0% (10,745) polypeptides before scaffolding had already a 100% coverage to proteins in TAIR10. Among the 9,106 remaining polypeptides, 26. 4% (2,425) moved to a higher range of coverage after scaffolding. The polypeptides that were improved had an average increase of 18% in coverage, i.
The methodology provides an improved Cocos nucifera proteome We applied the methodology in order to obtain a proteome of coconut using oil palm as model species. In order to obtain a better representation of the coconut proteome, we worked with two different transcriptomes  [4, 5]. The contigs obtained with Trinity and BRANCH from the four different groups (20,847 new/264,349 de novo dwarf embryo, 29,122/185,242 dwarf endosperm, 27,625/88,707 dwarf leaf and 23,283/89,133 tall tissue mix) were pooled and identical sequences (full-length and fragments) were eliminated, yielding 591,511 sequences (Fig 1B  , step 1 ). Of these contigs, 14% (86,356) were identified by BRANCH software. 74% (439,300) of contigs were translated into polypeptides (step 2) sequences and 48% (285,975) of these had significant alignments to oil palm proteins (step 3 and 4).
At step 5, these polypeptides sequences aligning to oil palm proteins were integrated into 29,366 coconut protein products (PPs). Each of these polypeptides represented on average 9,74 sequences of step 4 and 24% (7,058) of them were improved by scaffolding. 35% polypeptides (153,325) were lost between step 2 and step 3 because they had no significant hits in oil palm proteome used in this analysis. Among them, 7,716 had significant alignments (identity > = 80%, coverage > = 70%) to proteins in TrEMBL database. The remaining 145,609 polypeptide sequences had an average length of 106 aa in comparison to a length of 336 aa in polypeptides that had significant alignments to oil palm or other species. These polypeptides without significant alignments may represent orphan genes or artifacts of de novo transcriptome due to the presence of genomic DNA in the sample and/or non-coding RNA.
The methodology identifies more coconut contigs In this section we consider a new contig as a sequence that has been found by the software BRANCH and is not identical at the level of nucleotide composition to contigs obtained with Trinity. These new sequences represent contigs with evidence in RNAseq data and that were assembled using the oil palm mRNA in step 1 of the methodology. In step 4 there were 79,021 polypeptide sequences derived from new contigs. 14,258 of these sequences were used in step 5 to obtain coconut PPs, while the remaining polypeptides obtained from the new contigs were identified as redundant. 11,196 of these 14,258 polypeptides were involved in the scaffolding of 4,059 coconut PPs, and 3,062 represented each a complete coconut PP sequence. This represented an average gain of 122 aa in the corresponding polypeptides.
The comparison of coconut proteome to public data shows the ability of our methodology to reduce transcript fragmentation We compared the proteome obtained in the current analyses with the polypeptides derived of two published transcriptomes  [4, 5]. 57,175 transcripts recovered from Fan et al  [5]  and 153,852 from Huang et al  [4]  were translated into 37,743 and 76,553 polypeptides (66% and 49% of the transcripts respectively). The percentage of translated transcripts in our methodology was 66%. These polypeptides datasets were aligned to rice proteome. The polypeptides of step IV have the highest amount of best-hits in rice  (19, 470) , followed by Coconut PPs derived from our methodology  (13, 237 ), compared to 11,018 in Huang et al  [5]  and 9,535 in Fan et al  [4]. The average identity for all datasets was similar, at around 66%.
The S3 Fig shows the distributions of the coverage of rice proteins for the different datasets. While the distribution is approximately flat for polypeptides obtained from Huang et al, the other three distributions were characterized by a large peak at high values of coverage of rice proteins (>90%). The distribution of PPs (step 5) presents the highest concentration of sequences with good coverage, followed by the polypeptides of step 4, which in turn have a slightly better distribution than that observed in Fan et al.
Nevertheless, the distribution of proteins in the gene ontology categories revealed interesting differences between coconut and rice, this comparison suggests a significant degree of specialization of rice proteins. For example, no coconut PP was found for the category "viral process" (GO:0016032), i. e. a multi-organism process in which a virus is a participant (S1 Fig). There are eight rice proteins belonging to this category, including CYP701A8, an enzyme involved in phytoalexins biosynthesis  [47]. We aligned these proteins to the coconut PPs. The best hit in coconut for rice protein CYP701A8 was Cn. pt. eg. 0300260001. 1 (Id = 58%, Cv = 96%). Cn. pt. eg. 0300260001. 1 was aligned to the non-redundant proteins NCBI database with smartblast  [31]. The best alignment was obtained for ALF95896.
PalmComparomics In order to facilitate the access to genomic information in coconut, we developed the web site "PalmComparomics" (http://palm-comparomics. southgreen. fr/) that contains the main results of the current analysis. This web site, hosted by the Southgreen bioinformatic platform, offers several tools for data querying and visual analyses. PalmComparomics has a browser where oil palm genes and the mapping of coconut polypeptides to oil palm pseudo chromosomes are represented. Data can be retrieved for specific terms of gene ontology, Pfam domains, metabolism pathways, Interpro domains or sequence homology. PalmComparomics provides a BLAST tool that allows the user to align sequences against the coconut polypeptides and contigs. The polypeptides and proteins products of our methodology can be downloaded in FASTA format.
Data used in the present paper can be retrieved at the following sites: Transcriptomic data at NCBI site (https:// www. ncbi. nlm. nih. gov/data available at the following sites: Uniprot gene ontology rice: ftp://ftp. ebi. ac. uk/pub/ databases/GO/goa/proteomes/23240. O_sativa_ indica. goa, Uniprot viridiplantae: http://www. uniprot. org/taxonomy/33090, Phytozome v11. 0: https://phytozome. jgi. doe. gov/pz/portal. html, PlantCyc sites: ftp://ftp. plantcyc. org/Pathways/ Data_dumps/PMN10_June2015/oryzacyc_ pathways. 20150608. Data produced during the present work can be downloaded at http://palmcomparomics.
Samples Lifetime measurements were performed for the UiO-67-Ru MOF and the UiO-67-Ru-Ti50, showing a decrease on the value with the exchanged MOF. UiO-67-Ru showed a lifetime value of 3. 43 Â 10 À7 seconds while the exchanged material showed a value of 4. 52 Â 10 À8 seconds (Fig. S7 † ). The decrease on this value can be related to the proximity of Ru to the Ti catalytic center. Also, the t was obtained with a mono-exponential tting, indicating the presence of just one type of light interaction of the Ru complex in the MOF. Dye sorption results are shown in Fig. S8. † With the introduction of Ru and Ti respectively, the sorption decreases considerably due to some obstructions of the MOF cavities by the Ru complex and the addition of Ti. The adsorption data obtained was tted to a pseudo-rst and pseudo-second-order rate equations.
MATERIALS AND METHODS All computational calculations have been performed on personal computer using the Gaussian 09W program packages developed by Frisch and coworkers  [7]. The Becke's three parameter hybrid functional using the LYP correlation functional (B3LYP), one of the most robust functional of the hybrid family, was herein used for all the calculations, with 6. 31G(d,p) basis set  [8, 9]. Gaussian output files were visualized by means of GAUSSIAN VIEW 05 software  [10]. Principal component analysis (PCA)  [11]  and Hierarchical cluster analysis (HCA)  [12]  are two chemometric methods were performed using software XLSTAT.
Computational method: Hansen solubility parameters and COSMO-RS calculations For Hansen Solubility Parameters (HSP) solvent optimization, the relative energy differences (REDs) of each couple solute/solvent were calculated using the software HSPiP Version 5. 0. 03 (Hansen-Solubility, Hørsholm, Denmark) using the method previously described by  Yara-Varon et al. (2016). The principle of COSMO-RS modeling of solvent-solute interactions has been explained in previous publications  (Sicaire, Vian, Fine, Carre, et al. , 2015; Yara-Varon et al. , 2016). In order to determine if HFO-1234ze can be an alternative to conventional solvent, technical properties of each solvent were compared. Table  1  reports physicochemical properties of liquefied HFO-1234ze, n-hexane, ethanol, acetone and water. Technical data was obtained from ACD-labs and from suppliers (Sigma-Aldrich, Inventec Performance Chemicals).
Spectroscopic characterization For UV-Vis ABS measurements, protein concentration was typically at 50 μM. Room temperature UV-Vis ABS spectra were recorded on a Cary 50 Bio (Varian) spectrophotometer. Low Temperature spectra were obtained with a Cary 300 (Varian) spectrophotometer modified to accommodate a Dewar mounted in the light path. This arrangement allows data collection at around 77 K. For this experiment, samples were diluted in buffer 50 mM sodium acetate containing 70% (v/v) glycerol. R L values correspond to the ratio between ~440 and ~600 nm peaks for green or blue perturbed copper sites or between ~368 and ~455 nm for red copper sites  [11]. Far-UV CD spectra were recorded on a Jasco J-715 spectropolarimeter at 298 K in a 1 mm path length cell. 20 μM of proteins in 50 mM sodium acetate at pH 5.
Acknowledgments We gratefully acknowledge the contribution of  Julie Gros  for technical assistance. We also thank  Marlène Martinho ,  Marianne Guiral  and  Pascale Infossi  for helpful discussions. The authors are grateful to the  EPR  facilities available at the  Aix-Marseille University EPR center. Financial support from the  national EPR network RENARD  ( IR CNRS 3443 ) and the  Aix-Marseille University  EPR center is gratefully acknowledged. Magali Roger  has a fellowship of the  French Ministry of Research (Ministère de l'Enseignement Supérieur et de la Recherche). Alejandro J. Vila  is a staff member from  CONICET (Argentina).
Finally, Figure  4 (c) shows the SA signal for RF modulation frequencies of 0. 5 (13 dBm), 1. 5 (13 dBm) and 2. 5 GHz (15 dBm). This demonstrates that the meta-atom detector can operate at speeds at least up to 2. 5 GHz. To gain a deeper insight into the high-frequency response of this detector architecture, we have measured the complex one port S-parameters (real and imaginary part of S11) of several single-pixel and arrays of detectors, using a 40-GHz network analyzer. In Figure  5 (a) the data for a representative single device (red curve, top panel) and an array (red curve, bottom panel) are plotted as normalized impedances z=ZL/Z0 (ZL is the device impedance loading the Z0=50 Ω measurement line) on a Smith chart. Note: the measurements were made at room temperature; the Smith chart summarizes the real and imaginary part of the S11 parameter on a single plot.
The Smith plot confirms that, as expected, the device sub-wavelength size prevents a good impedance-matching with the 50 Ω line over the entire frequency range. We have inferred the equivalent RF circuit of each device by fitting the predicted behavior (blue curves) against the experimental data (red curves) using commercial circuit simulation software (Keysight ADS). Figure  5(b)  shows the equivalent circuit of a single meta-atom detector, including the access contact lines. The circuit modeling the actual detector (within the dashed brown line) comprises the parallel combination of the capacitance Cc and resistance Rc that models the Au-Ti/n-GaAs Schottky contact situated on top of the MSM capacitor. This junction is in series with a resistor RAR accounting for the resistance of the semiconductor active core, and the resistance of the bottom ohmic Pd-Ge contact.
Finally, the extraction efficiency of the RF signal is only a few percent due to the impedance mismatch arising from the very small detector size and the read-out line. This is a known problem in RF technology. It can be overcome, over a small bandwidth around a chosen precise modulation frequency  [32] , by impedancematching to 50 Ohm using discrete reactive components (inductors, capacitors). Funding. We acknowledge financial support from the ERC "GEM" grant (Grant Agreement No. 306661), the EPSRC grants 'COTS' and 'HyperTerahertz' (EP/J017671/1 and EP/P021859/1 ), the FET-Open ULTRAQCL 665158 grant. This work was partly supported by the French RENATECH network. We also acknowledge support from the Royal Society and Wolfson Foundation. G. X. acknowledges support from the National Natural Science Foundation of China under Grant No.
Acknowledgements Our research was supported by the  Centre National de la Recherche Scientifique CNRS ,  Normandy University , and  Labex SynOrg  ( ANR-11-LABX-0029 ). H. C. thanks the  French "Ministère de la Recherche et de l'Enseignement Supèrieur"  for a doctoral fellowship. H. G. thanks  Normandy University  for a postdoctoral grant. The  French Fluorine Network (GIS Fluor)  is also acknowledged.
This work was supported by the Unitede Recherche de Chimie de l'Environnement et Moleculaire Structurale (URCHEMS), UniversiteFreres Mentouri Constantine, Algeria, and the Biotechnology Research Center (CRBt), Constantine, Algeria. Thanks are due to MESRS and ATRST (Ministere de l'Enseignement Superieur et de la Recherche Scientifique et l'Agence Thematique de Recherche en Sciences et Technologie, Algerie) for financial support via the PNR program.
Characterisation The crystallinity of as-prepared materials was analysed by powder X-ray diffraction (XRD) using a Cu X-ray tube (λ = 0. 15418 nm) on a Siemens D500 X-ray diffractometer. The powder patterns were collected at room temperature in the 5 < 2θ < 50 • range with a 2θ angle step of 0. 05 • and a 3 s dwell time. All data were processed using Jade software (V9. 5, Christchurch, New Zealand). Test specimens were prepared by mixing the zeolite sample with an internal standard (high purity corundum, Alpha Aesar, verified using NIST 674b standards). The mixture consisted of 40% internal standard by mass. A thin film analysis was performed on the 1. 0 M treated sample due to the small amount of zeolite remaining post synthesis. Sample topography and particle size were investigated by SEM.
ChemComm S36 Figure  S42. SANS curves of pure micelles BO14 and magnetically loaded micelles BO15 before and after treatment at 80°C for 30 min (the SANS curves being acquired afterwards, at 20°C). The curves of the untreated micelles were fitted by a polydisperse sphere form factor multiplied by a "sticky hard sphere" structure factor. Solid lines represent simulated curves using the SasView 3. 1. 2 software (http://sasview. org) with a polydisperse sphere form factor P(q) multiplied by a "sticky hard sphere" structure factor S(q) to take into account short-range attractive interactions between the micelles. 7 In addition to the SLDs that were fixed to their theoretical values, the parameters of the polydisperse sphere form factor were the volume fraction f, the incoherent background level, the median radius R 0 of the micelles and the width s of the distribution of radii as described by a Log-normal law.
work has been supported by the EPSRC (EP/M023664/1). MC thanks the University Research Fellowship scheme from the Royal Society for support. IH thanks The Higher Committee for Education Development in Iraq for support. The authors acknowledge the use of the IRIDIS HPC Facility at the University of Southampton. Development of Spinach is supported by EPSRC (EP/H003789/1). Financial support by the Access to Research Infrastructures activity in the 7th Framework Programme of the EC (Project number: 261863, Bio-NMR) for conducting the research is gratefully acknowledged. We would like to thank Prof. Emsley and.
Acknowledgements Funding:  DGA-MRIS and region Haute-Normandie  are gratefully acknowledged for PhD scholarship. The authors thank  DGA Maîtrise NRBC  (contract  n°2014910080 ),  DGA  (« ASTRID maturation »,  ANR-14-ASMA-0003 ),  ANR  ( ANR BLAN06-1_134538 ) and  ANR-LABEX SynOrg for postdoctoral fellowships  ( ANR-11-LABX-0029 ). Rouen University, INSA Rouen ,  CNRS ,  EFRD  and  Labex SynOrg  ( ANR-11-LABX-0029 ) are also acknowledged for their financial support.
Thee nzymesw ere named D56ST3Gal Ia nd D56ST6Gal I, respectively. AFLAG-tag and a preprotrypsin signal peptidew ere introduced into the recombinant chimericp roteins fore fficient secretion of an N-terminal FLAG-tagged recombinant enzyme into the culture mediumo ft ransiently transfected human embryonic kidney cells (HEK293). Thirty-six hours post-transfection, we detected the secreted FLAG-tagged enzymeb yw estern blotting with an anti-FLAG antibody( Figure1). D56ST3Gal Ia nd D56ST6Gal I migrateda sm ultiple bands with an apparent molecular masses of 40-50 and 54 kDa, respectively corresponding to glycosylated protein isoformsa sa ssessed by PNGase Ft reatment (data not shown). Low levels of D56ST6Gal Iw ere consistently obtained,w hereas D56ST3Gal Ie xpressed at much higher levels in the cell culture medium of transfected HEK293 cells.
Reported kinetic data forh uman sialyltransferases are sparse and vary significantly for recombinante nzymes. I nt his study, we performed enzymatic reactions for crude extracts of D56ST3Gal Ia nd D56ST6Gal Is ecreted in the HEK293 cell culture medium with freshly prepared CMP-Neu5Ac and radiola-beled CMP-[ 14 C]Neu5Ac as donor substrate,  [25]  and 60 mgo fd esialylated fetuin as an acceptor substrate. Fetal bovine fetuin containst hree N-glycans and three O-glycans,  [27]  and is commonly used as an acceptor substrate for both ST3Gal Ia nd ST6Gal I. HEK293 cells transiently transfected with an empty pFLAGp lasmid( mock) were used as an egative control, as this cell culture medium did not showa ny FLAG-tagged protein or sialyltransferase activity (Figures  1a nd 2 ). Sialylated product formation was monitored over time for each recombinant enzyme.