dataesr/scientific-paragraphs-categorization huggingface dataset:
The samples were duplicated on the same plate according to the following procedure: after an incubation of 2 min at 50 °C and a denaturation step of 10 min at 95 °C, samples were subjected to 40 cycles (30 s at 95 °C, 30 s at 60 °C, 30 s at 72 °C). All the amplified cDNA fragments were checked by automatically sequencing (Cogenics, Meylan, France). To evaluate the risk of amplification from genomic DNA potentially present in our total RNA preparations, all samples were amplified by PCR with each primer pair in the absence of reverse transcriptase. When no enzyme was present, no amplification product was detected (data not shown). The levels of mRNA expression were standardized to the geometric mean of three reference genes (UXT (Ubiquitouslyexpressed prefoldin-like chaperone), SDHA (Succinate dehydrogenase complex subunit A flavoprotein) and PPIA (Cyclophilin A)).
Statistical analysis All statistical analyses were performed with SAS software (version 9. 3; SAS Institute, Cary, NC). If not specified, data were analysed using the MIXED procedure for linear mixed models and we included "cow" as a variable. A repeated effect of time (week peripartum or pp) within animals was tested. The residuals from the observations generated from the mixed models were tested for normal distribution. The obtained values were normal distributed. The statistical model included the fixed effect of week for both experiment and diet, week, diet × week interaction as previously described  [25]. The CORR procedure was used to calculate and measure the strength and direction of associations that exist between variables measured. The area under the curve (AUC) of plasma RARRES2 concentrations was performed as the sum of linear AUC that was calculated according to the following formula: AUC = x (t1) + y (t2) × 2/(t2 -t1) with x and y as a value of plasma RARRES2 concentration at 2 times (t1 or t2).
a-tubulin bound to iE5 is in pink, with the regions that interact with the aRep in magenta; iE5 is in orange. a-tubulin from tubulin-iiH5 is in cyan, with the H7-T7-H8 region in brighter color and intermediate domain structural elements in blue; iiH5 is not shown. For clarity, the a-tubulin N-terminal H1-S2 loop is not traced. (B) Comparison of a-tubulin in the iiH5 complex (cyan and blue), in tubulin-iE5 (pink and magenta) and in the microtubule (gray; PDB: 3JAK), centered on the H7 helix. The a subunits have been aligned as in (A). (C) Same as in (B), but only the a-tubulin intermediate domain b sheet is depicted. (D) Comparison of a-tubulin H7 position in different structures after superposition as in (A), taking tubulin-iiH5 as a reference. The comparison is with microtubular tubulin (PDB: 3JAK) and with T 2 SLD (PDB: 3RYC;  Nawrotek et al.
Isothermal Titration Calorimetry Calorimetric experiments were conducted at 20 C with a MicroCal ITC200 instrument (Malvern). All proteins were buffer-exchanged to 20 mM Pipes-K pH 6. 8, 1 mM MgCl 2 , 0. 01 mM EGTA, 0. 01 mM GDP and 75 mM KCl. Aliquots (2 mL) of iE5 or iiH5 at 160 mM were injected into a 15 mM tubulin solution (cell volume, 0. 24 mL). Analysis of the data was performed using the MicroCal Origin software provided by the manufacturer according to the one-binding-site model.
Crystallization and Structure Determination Tubulin-iE5 was crystallized at 293 K by vapor diffusion in a crystallization buffer consisting of 13% (v/v) PEG 400, 0. 1 M Mes-K pH 6. 8. Crystals were harvested in a mother liquor containing 20% PEG 400 and flash-cooled in liquid nitrogen. Tubulin-iiH5 crystals were obtained at 277 K in 0. 2 M Na tartrate, 12% (w/v) PEG 3350 and cryoprotected in mother liquor supplemented with 20% glycerol. Datasets were collected at 100 K at the Proxima-1 beamline (SOLEIL Synchrotron, Saint-Aubin, France). Data were processed with XDS  (Kabsch, 2010)  using the XDSME package  (Legrand, 2017). Structures were solved by molecular replacement with Phaser  (McCoy et al. , 2007)  using tubulin (PDB: 4DRX) and aRep-n4-a (PDB: 3LTJ) as search models, and refined with BUSTER  (Bricogne et al.
ACKNOWLEDGMENTS We thank  M. Knossow  ( I2BC, Gif-sur-Yvette ) for discussions and critical reading of the manuscript. Diffraction data were collected at the SOLEIL synchrotron ( PX1  and  PX2  beam lines, Saint-Aubin, France) and at the  European Synchrotron Radiation Facility (ID30 beam line, Grenoble, France). We are most grateful to the machine and beam line groups for making these experiments possible. We thank  D. Mauchand  ( UniteCommune d'Experimentation Animale, Institut National de la Recherche Agronomique, Jouy en Josas, France ) for providing us with the material from which tubulin was purified. This work has benefited from the facilities and expertise of the I2BC crystallization and biophysics platforms. This work has been supported by the  Fondation ARC pour la Recherche sur le Cancer  (to B.
Protein search against the cucumber protein sequences (Phytozome) as well as in silico translated C. grandis flower bud transcriptome database, resulted in the identification of 2426 and 3385 proteins (FDR ≤ 1%), respectively. The latter database was chosen for further analysis as it led to the detection of higher number of proteins. Identified proteins were annotated using BLAST2GO pipeline. SWATH-MS-based comparative abundance analysis between Female_Early_vs_ Male_Early, Ag_Early_vs_Female_Early, GyM-H_Middle_vs_Male_Middle and Ag_Middle_vs_ Male_Middle led to the identification of 650, 1108, 905 and 805 differentially expressed proteins, respectively, at fold change ≥1. 5 and P ≤ 0. 05. Ethylene biosynthesis-related candidates as highlighted in protein interaction network were upregulated in female buds compared to male buds.
Recently, Manzano, et al. [41]  showed that overexpression of aerolysin-like protein from the dioecious plant R. acetosa induces male sterility in transgenic tobacco. In order to decipher differences in protein abundances among flower buds of male, female, gynomonoecious and chemically masculinized female plants of C. grandis, total proteome profiling was carried out at early and middle stages of flower development. Proteins were identified using IDA (Information dependent acquisition)-derived data using in silico translated in-house C. grandis flower bud transcriptome  [35]  database followed by label-free quantification using SWATH-MS (Sequential Window Acquisition of All Theoretical Mass Spectra) analysis. Differential protein abundance among various sex forms of C. grandis was studied to identify players potentially involved in sex expression and modification.
Flower bud proteome of C. grandis The tryptic-digested protein samples were analysed by tandem LC-MS in IDA model, and the acquired data was processed by Paragon TM as per experimental scheme shown in Fig. 1. A total of 1193777 spectra (68. 8% of total spectra) corresponding to 66842 distinct peptides representing total 3387 proteins (Additional file 1: Data S1) were identified from different categories of C. grandis flower buds with FDR ≤ 1% (Unused ProtScore Cutoff > 2. 0) using in silico translated in-house C. grandis flower bud transcriptome (Table  1 ). Simultaneously, protein identification using Cucumis sativus protein sequences as database led to the identification of 2426 proteins, out of which 434 were new proteins that were not detected using the in silico translated in-house C.
Annotation of identified proteins Proteins identified using ProteinPilot software were searched against viridiplantae subset of nr (non-redundant proteins) database using BLASTp with an e-value threshold of 1e-3 (Fig. 2a ). Total 3377 proteins fetched at least one BLAST hit. More than 95% of the proteins gave top BLAST hit against C. melo (melon) or C. sativus (cucumber). BLAST2GO was used to annotate and classify the identified proteins into three major gene ontology categories (molecular function, cellular component and biological process) (Additional file 2: Data S2). For biological process, majority of the proteins were involved in metabolic process (1956 proteins) and cellular process (1821 proteins) (Fig. 2b ). Interestingly, we could detect 71 proteins annotated with reproduction (GO: 0000003) term (Fig.
Differentially expressed proteins involved in the flower development In order to understand how the expression of proteins was regulated during the development of male flower in contrast to female flower, quantitative proteomics was performed using label-free SWATH-MS to identify the DEPs (differentially expressed proteins). Based on the identified proteins from all samples, SWATH-MS analysis led to the detection of total 2262 proteins that were quantified from 144 SWATH data files. PCA-DA (Principal Component Analysis and Discriminant Analysis) showed that replicates belonging to each category of the samples were fairly clustered together. Additionally, upon PCA-DA analysis, the relationship or differences between different samples as per tissue and/or developmental stages was noticeable.
Conclusion Current study has led to the identification of many proteins expressed in the flower buds of male, female and gynomonoecious forms of Coccinia grandis at early and middle stages of development. Protein search against the in silico translated C. grandis flower bud transcriptome database has resulted in the identification of 3385 proteins. Simultaneously, protein search analysis against cucumber protein sequences (Phytozome) led to 434 new proteins that could not be detected through C. grandis flower bud transcriptome. This has further improved the number of proteins identified from the C. grandis flower buds in the current study. Also, changes in the proteome profile upon AgNO 3 -mediated sex modification in female plants were revealed. Through protein interaction network maps, we observed that proteins involved in ethylene biosynthesis such as UBA2A, UBA2C and EFE were upregulated in female buds of C.
As till now, complete genome sequence of Coccinia is not available, it would be difficult to ascertain this. Future investigation is required to unravel the mechanistic link between ethylene mediated stamen inhibition as well as the role of Y-chromosome in pollen fertility. Overall, in light of the limited molecular resources for such non-model dioecious species, our current flower bud proteome datasets will serve as invaluable novel resources for future identification of key molecular players involved in the development of unisexual flowers in cucurbitaceae, the second largest horticultural plant family in terms of economic importance.
MS data acquisition for IDA and SWATH The reconstituted peptides were further diluted to yield concentrations of 3 μg/5 μL for IDA acquisitions and 1 μg/5 μL for SWATH acquisitions. Peptide digests were separated by using an Eksigent MicroLC 200 system equipped with Eksigent C18-reverse phase column (100*0. 3 mm, 3 μm, 120 Å). Samples were analyzed on AB-SCIEX Triple TOF 5600 mass spectrometer. The LC separation methods and parameter settings for MS acquisitions have been followed as per the protocol of Korwar, et al. [83]. The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium via the PRIDE  [84]  partner repository with the dataset identifier PXD011064. Peptide spectral library and data base search -IDA mass spectrometric files were searched using ProteinPilot software, version 5.
0. 1. 0. 4874 (AB SCIEX) with the Paragon algorithm against in silico translated in-house C. grandis flower bud transcriptome at FDR (false discovery rate) ≤ 1%. The ProteinPilot output file (. group) was used as a standard peptide spectral library. In order to identify proteins that might have gone undetected due to the limitation of Coccinia transcriptome database coverage, IDA mass spectrometric files were also searched against Cucumis sativus protein sequences available in Phytozome  [85]. SWATH analysis was performed for six biological replicates and technical triplicates each from early-staged male, female, Ag-H and GyM-H buds as well as middle-staged male, female, Ag-H and GyM-H buds. The spectral alignment and targeted data extraction of SWATH-MS data was performed using Peakview software, version 2.
2 (AB SCIEX). The peptide data (. MRKVW) files were used for quantification of proteins using Markerview software, version 1. 3 (AB SCIEX). Normalization was performed using β-galactosidase and actin-7 (TRINITY_DN116897) peak area followed by the total area sum. The peptides with a P ≤ 0. 05 were considered for quantification. PCA-DA analysis was carried out using Markerview in order to study the relationship between all the samples and replicates followed by t-test to identify DEPs among each pairwise comparisons in which fold change was set as ≥1. 5, and significance of P ≤ 0. 05 was chosen as cut-off.
Protein-protein interaction network analysis Accession ID of Arabidopsis thaliana homologs of the proteins identified by proteomic analysis were used to study the protein-protein interaction using Cytoscape 3. 6  [86]. The STRING database for Arabidopsis thaliana was used to import the annotation, interaction and further analysis was performed using STRING App 1. 2. 2  [87]. Gene enrichment analysis was performed and proteins grouped under reproductive process and floral development, were used for generating network representation.
Transcript abundance analysis In order to estimate the transcript levels for selected differentially enriched proteins, qRT-PCR was carried out using the same tissue samples that were used for proteomics. Complementary DNA (cDNA) synthesis was performed with two micrograms of total RNA by SuperScript IV reverse transcriptase (Invitrogen) using an oligo(dT) primer. BIO-RAD CFX96 machine was used for carrying out the qRT-PCR with gene-specific forward and reverse primers (Additional file 10: Table  S1 ). Takara SYBR Premix Ex Taq II (Takara Bio Inc. ) was used for the reactions and PCR plates were incubated at 95 °C for 3 min followed by 40 cycles of 95 °C for 15 s, 58 °C for 15 s and 72 °C for 15 s. Melting curve analysis was performed to ascertain PCR specificity. Data were analysed using the 2 -ΔΔCT method and CgACT2 was chosen as a reference gene for normalization  [88].
Acknowledgements Authors sincerely thank  Dr. Mahesh Kulkarni  and his PhD students,  Biochemical Science Division, CSIR-NCL Pune  for the critical discussion and suggestions throughout the study. We thank  Mr. Nitish Lahigude  for maintaining C. grandis plants in the green house as well as in the field. Dr. Narendra Kadoo 's technical input with regards to protein isolation is also acknowledged. Technical inputs regarding LC-MS received from  Dr. Shanthakumari ,  CSIR-NCL Pune  are also thankfully acknowledged.
Funding R. S. D. acknowledges research fellowship obtained from  CSIR, HRDG, New Delhi. Financial support from  DST, Govt. of India  (Grant No- SR/WOS-A/LS-1233/2014 ), and Director,  IISER Pune  are thankfully acknowledged. Funding body was not involved in the design of the study; collection, analysis, interpretation of data and in writing the manuscript.
Analysis of miR-194 activity in published datasets single sample GSEA (ssGSEA) Expression data was downloaded from GEO (Kumar 2016 (GSE77930) (  26 )), cBioportal (MSKCC  (27)  and SU2C (  28 )), TCGA  (29)  and dbGAP  (Beltran 2016 (30) ). ssGSEA  (31)  was implemented using the Broad Institute's public GenePattern server, using rank normalisation and default parameters. Since miRNAs repress expression of their target genes, miR-194 activity was calculated as the inverse value of ssGSEA scores for the miR-194 targetome.
ACCESSION NUMBERS Ago-HITS-CLIP and RNA-seq data have been deposited with the Gene Expression Omnibus bank under accession number GSE137072. 42 )). For each target identified, the Pearson correlation coefficient and its q value was calculated and plotted as -log q (on y-axis) versus correlation coefficient (on x-axis). To indicate the bias towards negative correlations, the mean correlation coefficient is indicated by a vertical black line and the 25th and 75th percentiles are coloured red and blue, respectively. P value was determined using a one-sided t test (****, p < 0. 0001).
ACKNOWLEDGEMENTS The authors thank: the  Australian Cancer Research Foundation (ACRF) Cancer Genomics Facility  for assistance with Ago-HITS-CLIP and RNA-seq;  Nicholas Choo  ( Monash University ),  Birunthi Niranjan  ( Monash University ),  Roxanne Toivanen  ( Monash University ) and  Susan Woods  ( University of Adelaide ) for expert technical assistance with organoid culture;  Jindan Yu  ( Northwestern University ) for providing a FOXA1 activity gene set;  Peter Nelson  and  Ilsa Coleman  ( Fred Hutchinson Cancer Research Center ) for providing transcriptomic data (64); and  Emily Hackett-Jones  ( University of South Australia ) for assistance with analysis of the Ago-HITS-CLIP data. We acknowledge the team that generated transcriptomic data from CRPC-Adeno and NEPC tumours ( 6), which we obtained from dbGaP (accession number  phs000909 ).
/or activity during the transition to NEPC likely explains -at least (45)ly -increased miR-194 expression in this disease state. However, since we have also noted elevated miR-194 expression and activity in metastases and "poor outcome" primary tumours(45), we speculated that other alterations may underlie dysregulation of miR-194 in PCa. MiR-194 is encoded by two separate loci on chromosomes 1 and 11; the MIR194-1 gene clusters with MIR215 within intron 12 of the IARS2 gene on chromosome 1, while the MIR194-2 gene clusters with MIR192 approximately 3kb downstream of the ATG2A gene on chromosome 11. By interrogating clinical genomic datasets, we found that MIR194-1/IARS2 and MIR194-2/ATG2A are more frequently gained/amplified in metastatic compared to primary PCa and in NEPC compared to CRPC-Adeno (Figure.
Ion-exchange membranes (IEMs) find more and more applications; the success of an application depends on the properties of the membranes selected for its realization. For the first time, the results of a comprehensive characterization of the transport properties of IEMs from three manufactures (Astom, Japan; Shchekinoazot, Russia; and Fujifilm, The Netherlands) are reported. Our own and literature data are presented and analyzed using the microheterogeneous model. Homogeneous Neosepta AMX and CMX (Astom), heterogeneous MA-41 and MK-40 (Shchekinoazot), and AEM Type-I, AEM Type-II, AEM Type-X, as well as CEM Type-I, CEM Type-II, and CEM Type-X produced by the electrospinning method (Fujifim) were studied. The concentration dependencies of the conductivity, diffusion permeability, as well as the real and apparent ion transport numbers in these membranes were measured.
The purpose of current work is a comprehensive study of the structural and transport characteristics (electric conductivity, diffusion permeability, transport numbers of co-ions and counterions) of three cation-exchange and three anion-exchange membranes manufactured by Fujifilm using the method of electrospinning. We will compare these data with the characteristics of known homogeneous and heterogeneous membranes and assess the prospects for using EN-IEMs in dialysis and electrodialysis processes.
The morphology and chemical composition of the air-dry IEM surface was studied using the AFM method in "contact" mode (JEOL 5400 microscope, Tokyo, Japan, JEOL 5400 software), as well as using a scanning electron microscope (MERLIN™, Carl Zeiss Microscopy GmbH, Jena, Germany) equipped with an energy dispersive spectrometer (accelerating voltage is 6 kV, working distance is 9. 9 mm) and the device for X-ray fluorescence elemental spectroscopy (XRF). To improve the contrast of the obtained images and reduce the electric field strength, a thin layer of platinum nanoparticles was sprayed onto air-dry membrane samples. The method of surface metallization is generally accepted for SEM studies of ion-exchange materials  [62]. It is known that nanoparticles of platinum and gold have the smallest size compared with other metals  [63].
Before the experiments, all samples were equilibrated with 0. 02 M NaCl solution. The first measurements were carried out for the concentration of NaCl solution in tract II equal to 0. 02 M. Then, this concentration was sequentially increased to 1. 0 M. The membrane under investigation was in contact with each of the solutions for at least 5 h. The cell scheme, the methodology for conducting the experiment and processing the obtained data are described in detail in  [68]. The error of determining the integral diffusion permeability coefficient, P, of membranes is equal to ±0. 4 × 10 -8 cm 2 s -1. The transport numbers of counterions (t * 1 ) and co-ions (t * A ) in the membranes under study were obtained using the concentration dependences of the specific conductivity (κ*) and the integral diffusion permeability coefficient of the membranes (P).
In the MS/MS mode, a quadrupole was used for selection of precursor ions to be further submitted to collision-induced dissociation (CID) in a collision cell. Accurate mass measurements were performed using internal calibration. In this instrument, air was used as the nebulizing gas (10 psi) while nitrogen was used as the curtain gas (20 psi) as well as the collision gas. Instrument control, data acquisition, and data processing of all experiments were achieved using Analyst software (QS 2. 0) provided by Applied Biosystems. Polymer solutions were prepared in methanol supplemented with ammonium acetate (3 mM) and introduced in the ionization source using a syringe pump (flow rate: 10 μL/min). Dissociation reactions proceed via cleavages of backbone bonds of the poly(phosphodiester) chains that give rise to α-containing (i.
Acknowledgements J. -F. L. thanks the  H2020 program  of the  European Union  (project  Euro-Sequences ,  H2020-MSCA-ITN-2014 , grant agreement no. 642083 ) and the  CNRS  for financial support. The Ph. D. position of N. F. K. is supported by the  ITN Euro-Sequences. L. C. acknowledges support from  Spectropole , the  Analytical Facility of Aix-Marseille University , by allowing a special access to the instruments purchased with European Funding ( FEDER OBJ2142-3341 ).
g. Refs. [10, 11]. The very forward region covered by the data contains the highest energy densities, dE/dη  [12, 13] , so far observed in proton-proton collisions at the LHC. Therefore, the present results can improve event generators used in simulations of extensive air showers induced by cosmic rays at ultra-high energies  [14]. Specifically, current air shower simulations are known to significantly underestimate muon production (see Ref. [15]  and references therein). The fraction of the energy going into the production of electrons or photons rather than long-lived hadrons has a crucial impact on the muon production rate in extensive air showers, see Ref. [16]. Since CASTOR consists of separate electromagnetic and hadron calorimeters, the data presented here provide new information that may improve understanding of muon production in air showers.
The events are classified according to the number of reconstructed charged tracks from the vertex. The average total, electromagnetic, and hadronic energy per event is calculated for each track multiplicity bin. The present data make it possible to study track multiplicities up to 150. The statistical uncertainties of the energy measurement are below 2%, much smaller than the systematic uncertainties. The most important sources of systematic uncertainties are described in the following and are summarised in Table  1 : CASTOR energy scale. The energy scale uncertainty of CASTOR is 17%  [9]. The energy scale is determined using a calibration procedure based on SPS test-beam data, LHC beam halo muon events, a cross-calibration to the HF calorimeters, and LED test pulses, in combination with a precise detector alignment.