dataesr/scientific-paragraphs-categorization huggingface dataset:
g. 1-min EEG segment). It is recommended to test several threshold levels and epoch times. For instance, when increasing the threshold of a determined method, the sensitivity decreases, but the specificity rises  [13, 14]. Similarly, depending on the epoch time used for thresholding, the estimation of the local background energy differs due to changes in the vigilance state, artifacts and epileptic activity  [34]. Usual epoch times for energy thresholding are 10-min, 5-min, 3-min and 1-min  [10, 31] , though still, the user can establish a custom epoch time. Inclusion of a new detection method in RIPPLELAB. RIPPLELAB allows advanced users to include new detection methods. For this, the scripts are written in MATLAB sections named according to the functionality of the code, and the object handles are stored in MATLAB structures.
Software validation In order to minimize eventual programming errors in all developed scripts, we extensively and systematically tested each step of all the implemented detection algorithms using different types of data with distinct characteristics of noise, pathological activity and vigilance states. Extensive validations were also carried out on the different functionalities for signal preprocessing and inspection (display, filtering, spectral estimation, etc. ). The performance and reliability of the tool for HFO analysis was also exhaustively evaluated for all detection methods on simulated and real data. Simulated HFOs dataset. To test the HFO detection capabilities of RIPPLELAB, we first created a controlled scenario where the following types of events were simulated: spikes, gamma, ripple and fast ripple as well as different types of artifacts including 50 Hz noise.
For both simulated background cases, all the detection methods were executed using the same parameters as published, and HFOs were detected for a frequency band between 80 and 500Hz. The sensibility and specificity of the detection was determined by the following equations: Sensitivity ¼ TP TP þ FN ð5Þ Specificity ¼ TN TN þ FP ð6Þ where TP stands for true positives, TN for true negatives, FP for false positives and FN for False negatives. Detections of gamma, ripples, fast ripples and spike + fast ripples oscillations were considered as true detections, while spikes, artifacts and noise were considered as false detections. Real EEG dataset. To assess RIPPLELAB's capability to handle large databases--a common scenario found in clinic and research contexts--we completed an extensive analysis of 16 patients with invasive macro-electrodes from the EPILEPSIAE database  [41].
This database contains long-term EEG recordings of epileptic patients (a total of 275) complemented with extensive metadata and standardized annotations of the data sets. These patients were all implanted with invasive macroelectrodes (depth electrodes, or subdural grids and strips) as a part of their clinical procedure to determine the epileptogenic zone. In our work, we first evaluated the automatic detection of HFOs from large amounts of data analyzing long-term EEG records, and then we implemented a visual validation for a group of candidate events. For the first part of the analysis, two nights per patient were selected, one of them without any clinically marked seizure. For two patients, however, only one night was included because they did not present seizure-free nights. Only channels in the seizure onset zone were analyzed (n = 205 from 16 patients).
Simulated data analysis For both background cases all methods accomplished high sensibility and specificity. Specifically, for the non-background case, all methods accomplished a sensibility and specificity of 100%. In addition, the event detection was consistent among each detection method, meaning that the event boundaries established for each method were uniform across all the events of the same type. It is important to note that for the MNI detector, the analysis was carried out using the detection for channels with baseline (right branch in  Fig 4) , which is expected because there are not components inside the band of interest besides the simulated events. In the real background case, sensitivities for STE, SLL and MNI detectors were 100%, and 99. 33% for the HIL method. For this same case, the specificities were 100% for STE and HIL methods, 99.
Real data analysis As a result of the first part of this analysis, the SLL method detected the largest number of events in comparison to the STE (1. 040. 437 and 252. 642 respectively). On average, the STE method spent 32. 07 ± 10. 6 seconds analyzing hour-long segments whereas the SLL method performed slightly faster processing one hour segments in 30. 52 ± 10. 2 seconds. Nevertheless, the proportions of detected events using both methods were comparable for all but three patients. This result suggests that STE and SLL methods identify similar HFO densities on most of the signals even though the characteristics they use to evaluate HFOs are different, which is expected for different methods of high sensitivity. For a complete summary of the results, see Table  1. For the second part of the analysis, a total of 14.
Discussion HFO detection and analysis is a difficult task that requires the use of different tools such as detection algorithms, diverse signal processing techniques and specific visualization options. Even though several computational tools exist for the analysis of neural data, none of them includes the appropriate graphical environment nor the implementation of any detection method for HFO analysis, for which our software tool is particularly oriented. For this reason RIPPLELAB becomes a unique tool that consolidates a variety of current analytic methodologies for the analysis of these type of events. RIPPLELAB is a free-of-charge and open source software tool that includes both manual and automatic detection of HFO events. It can handle different types of electrophysiological data such as invasive and scalp EEGs through several file formats.
Acknowledgments We would like to thank  Vincent Navarro  ( Centre de Recherche de L'Institut du Cerveau et de la Moelle Epinière, Paris, France ) for valuable suggestions on the interface design,  Samuel Ahn , ( Department of Neurology, David Geffen School of Medicine at UCLA, Los Angeles, USA ) and  Gerriet Janssen  for helpful comments on the manuscript. This research was partially supported by  COLCIENCIAS  (Grant  567 ).
Imaging Imaging was performed using Leica SP5 and SP6 confocal microscopes (Wetzlar). Images were processed using ImageJ software (NIH). Figures were prepared using Adobe Photoshop (Adobe). Immunoprecipitation S2 cells were cultured in 6-well plates at 25 C in Sf900II medium. Transfections were performed with indicated constructs. Cells were lysed using RIPA buffer including NaF and Na 3 VO 4 phosphatase inhibitors. anti-GFP conjugated beads (Chromotek) were used for immunoprecipitation. Western Blotting SDS-PAGE was performed using 4%-12% gradient polyacrylamide gels and then transferred to nitrocellulose membranes, according to standard protocols.
ACKNOWLEDGMENTS This work was supported by  VIB (B. A. H. , D. S. ), the  WiBrain Interuniversity Attraction Pole (BELSPO IUAP) network (B. A. H. , D. S. ),  Fonds Wetenschappelijke Onderzoek (FWO)  grants  G. 0543. 08 , G. 0680. 10, G. 0681. 10, and G. 0503. 12 (B. A. H. ), ICM-P09015F (J. S. ),  FONDECYT 11150610  (C. O. ), the  Wellcome Trust  (N. S. -S. , grant to Manchester fly facility  087742/Z/08/Z ), the  Biotechnology and Biological Sciences Research Council  (N. S. -S. , grants  BB/M007456/1  and  BB/I002448/1 ), the  Universities of Liverpool and Manchester  (N. S. -S. ), a postdoctoral fellowship from  Becas Chile  to C. O. ,  University of Leuven postdoctoral fellowship (PDM)  to A. S. , and  FWO postdoctoral fellowships  to N. M and D. D. We are grateful to Somersault18: 24  for help with schematics and to members of the  Hassan laboratory  for discussions.
ANTICIPATED RESULTS The protocol concerns the purification of two fusion NAPs with a C-terminal 3xFlag tail: H-NS-3xF (18 kDa) and StpA-3xF (18 kDa). Their corresponding genes were cloned in vector pET21 and expressed in strain E. coli BL21 (DE3). The proposed method adds three steps to the standard NAP purification by affinity columns: i) benzonase nuclease treatment, ii) ammonium sulfate precipitation and iii) heparin column purification. The current 3-step procedure was used to purify biological duplicates of each protein (Fig. 1 2 3 4 and data not shown). The purification efficiency was monitored at different steps of the procedure. SDS-PAGE analysis of different samples taken from the H-NS-3xF replicate 1 purification is shown in Figure  1 : H-NS was shown to be pure at the end of the procedure (Fig.
1E ). Similar results were obtained for the second replicate of H-NS and the StpA samples (data not shown). As the method includes benzonase treatment, the presence of the nuclease was monitored during the purification procedure. 150 ng of a pET29b circular plasmid DNA (Fig. 2A ) was incubated 1 h at 37°C with protein extracts from different steps of the purification (Fig. 2 ). The plasmid was added in a 20 µl total mix containing the same concentration of protein extract (estimated on Coomassie blue SDS-PAGE) and 2 mM MgCl2 as required for benzonase activity. The results showed that the nuclease is still active after the heparin purification as the plasmid was digested (Fig. 2B ). However, at the final step of protein purification on the anti-Flag M2 resin, the nuclease was removed from the protein and found in the flow-through.
In Vitro Translation 35 S-Methionine labeled Hermes proteins were synthesized in rabbit reticulocyte lysates (Promega) using capped in vitro transcribed RNA following the manufacturer's protocol. For radiolabeling, 20 µCi of 35 S-methionine was included (New England Nuclear, Boston, MA, USA, NEG009A, 1200 Ci/mmol). Samples were immunoprecipitated under denaturing conditions with anti-myc antibody and analyzed by SDS-PAGE. The bound protein was quantitated using a PhosphorImager™ (Storm 840, Molecular Dynamics/GE Healthcare Life Sciences, Pittsburgh, PA, USA) with the ImageQuant software package (8. 1, GE Healthcare Life Sciences, Pittsburgh, PA, USA).
Both Vg1RBP/Vera and hnRNP I however, are excluded from the MC suggesting the RNP particles destined for the germ plasm are different from those following the late Vg1 localization pathway (Figure  5C, D ). We attempted to visually capture Hermes/Rbpms-nanos RNA interaction within the ooplasm during the process of RNA localization into the MC. Fluorescently tagged nanos 3′UTR RNA was injected into stage I oocytes, and after 5 or 20 h, oocytes were fixed. The 3′UTR of nanos RNA was used in order to eliminate the possibility of nanos translation, an event that could obscure RNAprotein interactions. Endogenous Hermes/Rbpms protein was identified by immunofluorescence after staining with an anti-Hermes/Rbpms antibody. Regardless of conditions or time, we could not detect any co-localization between injected nanos 3′UTR RNA and endogenous Hermes/Rbpms (data not shown).
Acknowledgments: We would like to thank the  Krieg lab  for providing two deletion mutants and a HA tagged Hermes/Rbpms construct [48]. The anti-hnRNP I antibody was a generous gift from  K. Mowry  ( Brown University, RI, USA). Nancy Standart (University of Cambridge, UK ) kindly provided the anti-Vg1RBP/Vera antibody. We thank  Karen Newman  for her expert technical assistance and  Kenneth Dunner Jr. at the  MD Anderson Cancer Center  for EM technical service (supported by Core Grant  CA16672 ). This work was supported by  NIH  grant  GM102397  to M. L. K. and an  AHA postdoctoral  fellowship to Y. Z. ( 0525528B ).
40 Also of note, HK activation rather than inhibition has also recently been described as a strategy to control virulence of Gram-negative bacteria, since avirulent Salmonella and Haemophilus species commonly have mutations that lead to constitutive activation of the conjugative plasmid expression TCS CpxRA. 41 The development of new inhibitors capable of disrupting TCS signaling remains a challenging. In the present study, we used a structure-based drug design strategy, based on the crystal structure of the ATP pocket of essential cell wall homeostasis regulator kinase WalK (Protein Data Bank [PDB]: 3SL2), and PLANTS as a virtual screening software to identify new inhibitors of HK. To this end, we utilized the fact that HKs share a related CA domain with DNA-gyrases and topoisomerases. The latter represent known antimicrobials targets, and high-resolution structures of inhibitor-bound proteins exist.
To design the inhibitors, we used the available X-ray structure of the ATP-binding domain of WalK (PDB: 3SL2  46  ) at a resolution of 1. 61 Å. This structure comprises a twolayer α/β sandwich-fold with a large ATP pocket (Figure  2A ). One layer is composed of a five-stranded β-sheet. Strands 1 and 2 run parallel, whereas the directions of strands 2, 3, 5 and 4 alternate. The second layer is made of three α-helices. These two layers are linked by a large flexible loop (Asp533-Gly567) containing a short helical segment that is crucially involved in ATP binding  46. This loop is designated as the ATP-lid. The interactions among ATP, Asp533 and Water822 are known to be critical for protein-cofactor binding. Additionally, we observed π-stacking between the adenine ring and Tyr507 (Figure  2B ).
Thus, our aim was to design ligands that can form hydrogen bonds and hydrophobic interactions with these elements. As mentioned above, the ATP-binding domain of the TCS, a Bergerat fold, is also found in Gyrase B, heat shock protein Hsp90, histidine kinases and mutator protein MutL  44, 47. PDB was probed for structures of ligand-bound domains of these proteins to investigate the inhibitors' binding modes. 9] [50]  Moreover, a Gyrase B ligand has been reported to bind to the ATP-domain of HKs. 45, 47 We decided to focus on the complex PDB: 3TTZ because the ligand 2-[(3S,4R)-4-{[(3,4-dichloro-5-methyl-1Hpyrrol-2-yl)carbonyl]amino}-3-fluoropiperidin-1-yl]-1,3-thiazole-5-carboxylic acid (pyrrolamide, Figure  3 D ) has an 50% inhibitory concentration (IC 50 ) value of 4 nM. 49 omparative docking was performed according to the typical protein kinase protocol.
In position R', we chose to add polar substituents to increase the compounds' solubility. We docked this virtual chemical library into the ATPbinding site of WalK (PDB: 3SL2) using PLANTS  55. Protein and ligands were prepared with SPORES  56, 57  before docking and the docking poses were reevaluated using the DSX  54  scoring function. When inspecting the docking poses, the phenyl ring can be observed at the bottom of the pocket, and the substituent points in the direction of Asp533. The thiophene ring participates in π-staking with Tyr507, and the polar substituents note of the pocket towards the solvent (Figure  6A  and 6B ). When comparing the binding poses and the scores obtained from both the docking and reevaluation experiments (Table  1 ), 21 compounds in the virtual library were considered promising and singled out for synthesis.
A typical assay for compound 6e is depicted in Figure  8A , demonstrating that this compound inhibits all three HKs to varying extents. Similar results were obtained for the other seven compounds and the IC 50 values are summarized in Table  4. Screens were also performed with the B. subtilis sporulation HK KinA, resulting in similar inhibition patterns: the IC 50 values were not determined for this kinase (data not shown). Of note, one compound 6s showed significantly better inhibition of PhoR (IC 50 : 1. 6 μM) than ResE and WalK, demonstrating that selectivity can be achieved by varying phenyl group substituents. At this point we can only speculate why this compound would be selectively inhibiting PhoR. The docking pose in Figure  6  suggests that the phenyl group substituents are in contact with conserved Asp533 deep within the ATP binding pocket.
2. 3. 8 The relatively soluble HCl salts of amines do not improve antimicrobial activities or HK inhibition-Several of the eight tested compounds showed very low solubility, which we suspected may have contributed to the lack of antimicrobial activity among some of them. To test whether increasing solubility of any of these compounds would positively affect their antimicrobial activities, we evaluated the HCl salts of the amines of compounds 6c, 6h and 6i. These compounds did indeed show higher solubility in aqueous solutions. However, antimicrobial activity was not observed for any of the HCl salts according to the Kirby Bauer disk diffusion method (data not shown). Exposing PhoR kinase to these compounds also revealed that the HCl salts were significantly less-potent HK inhibitors than their less-soluble counterparts (data not shown).
Computational Studies: Preparation of Enzyme and Compounds for Docking The crystal structure of the ATP-binding domain of Histidine kinase WalK was extracted from Protein Data Bank (PDB code: 3SL2). 46 All the water molecules except water822 and heteroatoms were removed. The protein was completed, hydrogen atoms were added, and reprotonated with SPORES. 57 The chemical structures of all the synthesized compounds were generated using Marvin sketch and were subsequently converted into 3D format using Open Babel  62  and prepared with SPORES. A serie of docking experiment were carried out with all the designed compounds against the ATP-binding domain of WalK using PLANTS for possible Histidine kinase inhibition activities. The compounds were selected on the basis of their scores and their pose, all compounds were re-scored with DSX.
Acknowledgments H. S. was supported by grant no. GM106085  from the  U. S. National Institute of General Medical Sciences, National Institutes of Health. The authors thank  Marta Perego ,  Christopher Kristich  and  Liang Tang  for the purified recombinant proteins and expression plasmids. D. B. , T. B. , Z. B. , P. M. and A. L. thank the  French "ministère de l'éducation nationale, de l'enseignement supérieur et de la recherche" and the University of Nîmes  for their financial support.
Gel Permeation Chromatography GPC measurements in THF were performed with highly-dilute fractions eluting from a SEC system consisting of an Agilent 1100 solvent delivery system (Agilent Technologies, Santa Clara, CA, USA) with isopump, manual injector, and an Agilent 1100 differential refractometer. Three 30 cm columns were used (PLgel Mixed C, Agilent Technologies, Santa Clara, CA, USA, 5 µm particle size) to separate polymer samples. The mobile phase was THF and the flow rate was 1. 0 mL¨min ´1. The columns were held at room temperature. For each measurement, 100 µL of a sample of 15 or a 5 mg mL ´1 solution was injected. WinGPC Unity from PSS was used to acquire data from the seven scattering angles (detectors) and the differential refractometer. Molecular weights and molecular-weight distributions were compared with poly(methyl methacrylate) (PMMA) standards (PSS, Mainz, Germany).
GPC in DMF data was obtained by measurements using a Shimadzu (Kyoto, Japan) liquid chromatography (LC) set up with degasser, pump, auto sampler, column oven, and differential refractometer. Three PolarSil columns (PSS Polymer Standards Service GmbH, Mainz, Germany; PolarSil 8 mm ˆ300 mm, 100, 1000, 3000 Å with 5 µm particle size) using DMF with 0. 3% LiBr and 0. 6% acetic acid as the mobile phase at a flow rate of 1 mL¨min ´1 were used to analyze polymer samples. The columns were operated at 40 ˝C with the RI detector set to the same temperature. The calibration was performed by using polystyrene standard (PSS, Mainz, Germany). Samples were measured at a concentration of 10 mg¨mL ´1 injecting 100 µL. LC solution software from Shimadzu was used for data acquirement and interpretation.
Dynamic Light Scattering DLS experiments were performed using a Malvern Zetasizer Nano instrument (Malvern Instruments Ltd, Worcestershire, UK) equipped with a He-Ne laser (633 nm) using backscattering mode (detector angle 173 ˝). The CMS nanocarriers were dissolved in dH 2 O, mixed by a Vortex shaker for 2 min, followed by filtration using a 0. 45 µm RC syringe filter. 100 µL of the filtered solution was added to a disposable Plastibrand®micro cuvette (Brand GmbH + Co KG, Wertheim, Germany) with a round aperture. The autocorrelation functions of the backscattered light fluctuation were analyzed using Zetasizer DLS software from Malvern Instruments Ltd (Worcestershire, UK) to determine the size distribution by intensity and volume. The measurements were performed at 25 ˝C, equilibrating the system on this temperature for 120 s.
High Pressure Liquid Chromatography HPLC measurements for the analysis of dexamethasone content was performed on a Knauer Smartline-HPLC system with an internal UV absorption detector (λ = 254 nm), equipped with a Gemini RP C18 column (Phenomenix, 250 nm ˆ4. 6 mm, particle size: 5 µm) and run with an acetonitrile-water (40:60) mixture as the mobile phase at a flow rate of 1. 0 mL¨min ´1 under isocratic regime. The data were analyzed with Chromgate software (Knauer, Berlin, Germany). A calibration curve of dexamethasone was obtained by measuring dexamethasone in an acetonitrile-water (40:60) mixture in the concentration range of 0. 004-2 mg¨mL ´1.
Acknowledgments: This work was supported by the  SFB 1112  ( Sonderforschungsbereich 1112-Nanocarrier ). We want to thank  Andreas Schäfer  for advice in NMR spectroscopy,  Florian Paulus  and  Cathleen Schlesener  for GPC measurement and  Marleen Selent  for HPLC analysis. Additionally we want to thank  Bala Naga Satyanarayana Thota  for helpful scientific discussion.
RNA extraction, sequencing, and data analysis Extraction of total RNA was achieved with the Spectrum Plant Total RNA kit (Sigma-Aldrich) using ~80 mg of grounded skins according to the manufacturer's protocol. The integrity of the extracted RNA was determined on an Agilent 2100 Bioanalyzer (Agilent) ensuring a RIN score >7. 5 prior to library construction. Ribosomal RNA depleted library construction was performed using an in-house workflow using customized kits from NEB at the Canada's Michael Smith Genome Sciences Center (Vancouver, Canada) followed by sequencing (V4 chemistry) on an Illumina HiSeq 2500 platform (Illumina) and in-house quality control and filtering of 75-bp paired-end generated reads. Filtered pair-end reads were aligned against the 12× reference genome  [33]  using Burrows-Wheeler Aligner with default parameters  [34].
Read summarization was performed with htseq-count (version 0. 6. 0) with intersection non-empty settings  [35]  using the grapevine 12× genome assembly available from EnsemblPlants (http://plants. ensembl. org/Vitis_vinifera/ Info/Index). Differential gene expression analysis was carried out using edgeR (version 3. 10. 2)  [36]. Genes were deemed differentially expressed (DE) between pairwise comparisons at a threshold of false discovery rate (FDR) < 0. 05. Transcript abundance was calculated as Fragments Per Kilobase of exon per Million (FPKM) mapped reads using edgeR. Transcripts having FPKM values <0. 5 and assigned counts <5 were discarded. Clustering, functional enrichment, and promoter analysis Clustering of DE genes using edgeR's estimated gene expression (normalized counts) log2 fold change (log2FC) between small/large berries was performed using the kmeans method with 1000 iterations and the Speaman's rank correlation as the similarity metric.