dataesr/scientific-paragraphs-categorization huggingface dataset:
Peptides were separated on a BEH300 C18 (75 × 250 mm, 1. 7 mm) nanoAcquity UPLC column (Waters) using a stepwise 60-min gradient between 3% and 85% (v/v) ACN in 0. 1% (v/v) FA. Data acquisition was performed using a top-20 strategy where survey MS scans (m/z range 375-1,600) were acquired in the Orbitrap (R = 30,000) and up to 20 of the most abundant ions per full scan were fragmented by collision-induced dissociation (normalized collision energy = 40, activation Q = 0. 250) and analyzed in the LTQ. In order to focus the acquisition on larger crosslinked peptides, charge states 1, 2 and unknown were rejected. Dynamic exclusion was enabled with repeat count = 1, exclusion duration = 60 s, list size = 500, and mass window AE 15 ppm. Ion target values were 1,000,000 (or 500 ms maximum fill time) for full scans and 10,000 (or 50 ms maximum fill time) for MS/MS scans.
The sample was analyzed in technical duplicates (for DSG crosslinker) or triplicates (for DSS crosslinker). To assign the fragment ion spectra, raw files were converted to centroid mzXML using the Mass Matrix file converter tool and then searched using xQuest  [51]  against a fasta database containing the sequences of the crosslinked proteins. Posterior probabilities were calculated using xProphet, and results were filtered using the following parameters: FDR = 0. 05, min delta score = 0. 95, MS1 tolerance window of 4-7 ppm, ld score > 30. The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium via the PRIDE  [52]  partner repository with the data set identifier PXD005251.
ITC measurements Isothermal titration calorimetry was performed with a VP-ITC Microcal calorimeter (Microcal, Northampton, MA, USA). To measure the Elp1 Elp4 interactions, Elp1 samples were dialyzed extensively against ITC buffer (20 mM Tris-HCl, pH 7. 5, 150 mM NaCl, 2 mM b-mercaptoethanol). Lyophilized synthesized peptides (Peptide Specialty Laboratories, Germany) were solubilized in ITC buffer just before use. Protein/peptide concentration in the cell was 10 lM and 100 lM in the injection syringe. The data were analyzed using Origin software (GE Healthcare). 3. 5 ll aliquots of freshly purified Elp123 complex were applied to glow discharged carbon copper-collodion (Sigma) grids for 2 min and stained with a 1% uranyl acetate solution (w/v). A total of 216 images were collected on a FEI Tecnai Spirit microscope operated at 120 kV using a Gatan Ultrascan 4000 camera at a final magnification of 49,000×.
Structural modeling As initial structures for the modeling, we used the available crystal structures of Elongator subunits or homology models if crystal structures were not available. For WD40 domains of Elp1, we built homology models based on coatomer b'-subunit (PDB code: 3MKQ, chain A) based on the alignment generated by HHpred server  [59]. Due to low sequence similarity between Elp1 and coatomer b'subunit, these models should be regarded as low quality with the confident assignment of the fold but uncertain sequence register. For Elp1-CTD, we used the yeast crystal structure of Elp1-CTD (PDB code: 5CQS) with the missing region comprising residues 739-919 added from human Elp1-CTD structure (PDB code: 5CQR) by homology modeling. For Elp2, we used the structure published in this work. For Elp3, we built a homology model built based on Elp3 from Dehalococcoides mccartyi (PDB code: 5L7J).
This model is predicted to be of high confidence owing to the high sequence conservation between yeast and D. mccartyi Elp3. For Elp4, Elp5, and Elp6, we used the crystal structure of Elp456 hexamer (PDB code: 4A8J). Short loops and regions missing in the structures were added to the models as flexible loops and helices based on secondary structure predictions if they formed crosslinks potentially useful for model. These included, for example, residues 74-86 and 375-406 of Elp3 and 1,244-1,252 of Elp1. The homology modeling was performed using MODexplorer  [60] , HHpred server  [59] , and Modeller  [61]. The secondary structure predictions were generated using GeneSilico MetaServer  [62]. Fitting of each Elongator domain separately to the EM maps and calculations of P-values for the fitting scores was performed as described previously  [63, 64]  using UCSF Chimera software  [65].
Briefly, each domain was fitted using global search with an arbitrarily large number of 10,000 random initial placements and a normalized cross-correlation score as a fitting metric. The fits were then clustered, in the case of Elp123 sub-complex taking the twofold symmetry axis into account. The P-values for the cross-correlation scores were calculated by transforming to z-scores (Fisher's z-transform) and centering, and fitting an empirical null distribution from which two-sided P-values were computed  [64]. Automated integrative modeling was performed using our previously published workflow  [39]  based on the UCSF Chimera, Integrative Modeling Platform (IMP) package  [40] , version g72059d2, and Python Modeling Interface (PMI) library (https://github. com/ salilab/pmi), version gfe8bea8.
Crystallization and structure determination of Elp2 Native and selenomethionine substituted crystals were grown at 18°C using the hanging drop vapor diffusion method. Purified Elp2 protein in gel filtration buffer was concentrated to 10 mg/ml and combined with equal volume of 100 mM Tris pH 7. 5, 10% PEG 6K, 1,750 mM NaCl. Crystals grew until day 2, were cryo-protected with 25% glycerol, and subsequently flash-frozen in liquid nitrogen. Native and selenomethionine data sets for Elp2 were collected at ESRF beamline ID14-4 equipped with a CCD camera. Data processing was performed using XDS  [70]. SAD phases were calculated from identified selenium sites using autoSHARP  [71]. The resulting electron density map after solvent flattening was of good quality and an initial model was built and subsequently refined using Phenix  [72].
Accession numbers The atomic coordinates and structure factors for Elp2 (PDB ID 5M2N) have been deposited with the European Protein Data Bank (PDBe). The EM density maps of Elp123 (EMDB EMD-4151), holoElongator (EMD-4152), and partial Elp123 (EMD-4153) have been deposited with the EMData Bank (EMDB). Expanded View for this article is available online.
Even if the care episode does not concern the rare disease. Writing a systematic review about a rare diseases, or doing a short review in order to write a research article, requires querying one or more bibliographic databases with as much relevant keywords as possible  [6]. It seems of public health importance to provide all these participants with the appropriate tools to easily retrieve relevant information about rare diseases. PubMed is one of the most popular search engines to access medical literature. It browses the MEDLINE bibliographic database, which gathers a large part of biomedical scientific articles, and some other minor resources  [7]. MEDLINE is indexed using the MeSH® thesaurus. Although PubMed theoretically allows to access the literature about rare diseases, including the most recent scientific discoveries, the combination of the following elements may hinder users: the relative novelty of MeSH terms for rare diseases  [8].
PubMed overview PubMed is the most frequently used bibliographic database used by biomedical scientist throughout the world. It therefore constitute a standard in terms of information retrieval. MEDLINE is the major component of PubMed, gathering almost 90 % of the 26 millions of PubMed citations. MEDLINE curators affect to each citation a list of MeSH terms to describe it with a controlled level of granularity. The MeSH atomic part is the MeSH concept, a class of synonymous termsi. e. all terms gathered in a MeSH concept are true synonyms. MeSH concepts closely related to each other in meaning may be gathered in a MeSH descriptor (MeSH D) or a MeSH supplementary concept (MeSH SC), one of them being the prefered concept, and the other being narrower, broader or related to the preferred one.
Terminological queries In addition to the MeSH thesaurus, several other terminologies and ontologies are available on rare diseases: (a) a formal ontology named HRDO (Human Rare Disease Ontology)  [14]  was developed based on the Orphanet classification. This ontology is available in five European languages: English, French, German, Spanish and Portuguese; (b) the Online Mendelian Inheritance in Man (OMIM) database, developed at Johns Hopkins University  [15] ; (c) the Human Phenotype Ontology (HPO), a formal ontology, which allows the description in an unambiguous fashion of phenotypic information in medical publications and databases  [16]. The HPO is freely available at http://www. human-phenotype-ontology. org. One of the authors (SJD) has created exact match mappings between MeSH, OMIM, HPO and HRDO based on a natural language processing/conceptual based algorithm  [17, 18]  suggestions.
These genera could potentially correspond to either bacteria-enriched post-mortem that may participate in decomposition or, alternatively, particular residents of the ancient oral microbiomes analyzed in this study (Supplementary Tables  2  and 3 ). All together, our results indicate that although ancient dental pulps are invaded by environmental bacteria after death, they also conserve a good record of the microbial communities that are naturally present in the oral cavity and particularly in dental pulps. We finally explored the presence of pathogenic bacteria in all groups of samples (i. e. , unambiguous hits against known pathogens). We found almost exclusively hits against oral pathogenic bacteria (Fig. 1d ) from 18 different species, a group that is not overrepresented in the database used.
Genera found in blanks of polymerase chain reaction (PCR) and extraction were excluded from the analysis. The Jaccard distance was used to sort samples and genera. Richness was estimated using an even rarefaction of the reference-based OTU table at 1000 sequences per sample and counting the number of known genera observed for each sample. Unknown or uncultured environmental bacteria were not considered. Richness values and error bars correspond to averages and standard deviations, respectively, between all samples within a category. d All sequences from each data set were compared by BlastN against the 16S rRNA sequences of known pathogens in PATRIC database. The numbers of sequences used in the analysis are indicated in square brackets. Only sequences that showed a 100 % similarity against a pathogen sequence with at least 60 % of the read aligned were considered.
As an additional filter, these sequences were then compared against the full NCBI database and only sequences that showed 100 % similarity against non-ambiguous species (i. e. , only showed perfect hit against the same species that in PATRIC DB) were conserved. Bacteria that are commonly associated with oral pathologies are indicated in light blue on the left of the figure. Three bacterial species that are commonly isolated from the oral cavity but their role in oral pathogenesis has been only suspected are colored in dark blue. Pathogens from non-oral pathologies are indicated in gray. Samples were grouped by data set and a positive hit was considered when a pathogen was confidently found in at least one sample from that data set.
Localization microscopy using confocal fluorescence imaging of nuclear pore complexes is a super-resolution microscopic technique 'Localization microscopy' relies on detection of the centroid of point-like structures, and is classically not limited by diffraction, but by the signal-to-noise ratio of individual detections. To label NPC, we fused GFP or mRFP dimers with abundant NPC components (Nup49, Nup57, Nup2 or Nup159). We developed an algorithm called 'NucQuant', adapted from a previously described automated image analysis pipeline using spinning-disk fluorescence microscopy and MATLAB codes  (Berger et al. , 2008). We could detect a median of 22 peripheral spots per cell nucleus. Each detected spot should roughly correspond to a group of three to nine closely spaced NPCs, hereafter called cNPCs  (Winey et al.
, 1997). Importantly, detection of 22 spots per nucleus provided sufficient connecting points to evaluate the nuclear envelope position in 3D. Refractive index mismatch between optical setup and biological object is known to generate spherical aberration along the z-axis (Fig. 1A, B ). We measured and corrected this detection bias in our measurements. For exponentially growing cells in glucose, electron microscopy and X-ray tomography established that the yeast nucleus in interphase is mostly spherical  (Larabell and Le Gros, 2004; Murata et al. , 2014; Wei et al. , 2012; Winey et al. , 1997). We analyzed ∼1000 round cell nuclei and could generate a statistically robust dataset of ∼20,000 cNPC detections (Fig. 1C ). The nuclear sphericity allowed measurement of detection bias in our localization dataset.
In a sphere, distances between detected cNPCs and the nuclear center are the same in each dimension (x, y and z) (Fig. S1A, C ). Simulating the elongation along the z-axis (Fig. S1A, B ) modified the distribution of normalized distances between detected cNPCs and nuclear center along the x, y and z axes (compare Fig. S1C  and D ). Similar over-estimation along the z-axis was clearly detected in our experimental measurement (Fig. 1C ). In our experimental dataset, post-acquisition correction of localized cNPCs was performed as suggested previously (see Materials and Methods; Fig. S1E )  (Cabal et al. , 2006). This correction was calculated using round nuclei for each cell population analyzed, and was subsequently applied to the entire population (including nonround nuclei; Fig. S1F ). Note that spherical aberration was always detectable, but was specific for different objectives or microscope setups (confocal laser scanningversus laser spinning diskmicroscopes) (Fig.
However, data collection of serial sections analyzed by TEM is a time-consuming technical  performance and has been reported for sampling of less than 100 nuclei  (Winey et al. , 1997). Innovative imaging techniques, relying on cryo-fixation but with less tedious exploration of 3D space, as highvoltage scanning transmission electron tomography of thick sections  (Murata et al. , 2014) , focused ion beam combined with scanning electron microscopy (FIB-SEM)  (Wei et al. , 2012) , and soft-X-ray tomography  (Larabell and Le Gros, 2004 ) are very promising. However, they are not compatible with in vivo imaging, and they have not yet been combined with high-throughput image analysis algorithms required to extract statistically robust datasets. Recently, a 3D membrane reconstruction approach that used fluorescently tagged nuclear envelope or endoplasmic reticulum membrane marker proteins was published to precisely map the nuclear volume  (Zhao et al.
NucQuant: post-acquisition correction of z aberration Confocal images were processed and analyzed with MATLAB (MathWorks) script NucQuant, a modified version of nucloc (http://www. nucloc. org/). We calculated the distances between the nuclear center and the cNPCs. For each nucleus these distances were normalized by nucleus mean radius (R). This distribution was best fitted by the second-degree polynomial curve: ax 2 +bx+c. This equation could be used to correct the aberration along the z axis: d correct /R=d/R-(ax 2 +bx).
Data were obtained as OD and given as % of control, with control = cell in complete medium and, % of control = (OD sample/OD mean of control) ×100. [ 3 H]-Thymidine incorporation. Cells were inoculated into round-bottom 96-well plates at 2. 5 × 10 4 cells per well in of 200 μ L, stimulated under various conditions and allowed to incubate at 37 °C for 6 h, then pulsed with 0. 1 μ Ci [ 3 H]-Thymidine (Perkin-Elmer) for 18 h at 37 °C. Cells were harvested onto FilterMat A filters (Wallac) by using an automated cell harvester (Harvester 96, Tomtec). The FilterMat A was then dried and a solid scintillator (Meltlex, Perkin-Elmer) was used according to the manufacturer's instructions. β -scintillation counts, counts per minute (c. p. m), of [ 3 H]-Thymidine incorporated into DNA were determined with a MicroBeta reader (Wallac, Perkin-Elmer).
Mouse antibodies for MARCO (Clone ED31) and CD204 (Clone 2F8) were from AbD Serotec. Mouse antibody for CD36 (Clone HM36) was from Biolegend. Human antibodies for CD90 (Clone DG3), CD105 (Clone 43A4E1), CD73 (Clone AD2), CD34 (Clone 581), CD45 (Clone 5B1) and CD14 (Clone M5E2) were from Becton Dickinson. Detection of phosphatidylserine (PS) was achieved with FITC-conjugated Annexin V, cells were concomitantly stained with a propidium iodide (PI), and reagents were from Sigma-Aldrich. Appropriate staining controls were performed, data were acquired on a flow cytometer (FACS Calibur, or LSR Fortessa BD Biosciences) and analyzed by FlowJo (Tree star Inc. ) or Flowing (Turku Center). Transmission electronic microscopy (TEM). Cellular samples were fixed in 0. 9% NaCl, 1% glutaraldehyde (Wako) for 1 h at 4 °C.
ELISA data are given as picogram (intracellular cytokine) per milligram (pg/mg) total protein. ELISA. Samples for ELISA were supernatants or cell lysates of cells stimulated under conditions with cells plated at 10 6 cells in 1 mL final volume per well, in 24-well plates. Cell culture supernatants or cell lysates or biological fluids from mice were assayed for mouse IL-1β , TNF-α and IL-10 (Mouse ELISA MAX Deluxe, Biolegend). Cell culture supernatants or cell lysates were assayed for human IL-1α , IL-1β , TNF-α and IL-10 (Human ELISA MAX Deluxe, Biolegend).
e. , <1 mm interaction range) before hard-wall contact were used for further analysis. Force curves on the COC were acquired at desired positions, with a lateral resolution of a few micrometers (determined by the accuracy of the microscope's manual xy translation stage) and an accuracy in the distance from the glass substrate of ~10 mm (determined from the repeatability in z positioning by the stepper motor of the AFM head). At least three force curves were collected per position. Data were corrected for linear thermal drifts in the cantilever deflection, and force versus distance curves were computed using established methods  (31)  implemented in JPK data-processing software. Fits of contact mechanics models (such as the Hertz model; vide infra) to force curves were also performed with the JPK data-processing software, with the measured forces around the contact point d ¼ 0 averaged and offset to zero.
For in vivo expanded matrix, it adds another 200 mm to the total thickness. For in vitro expansion, the cell-free coat remains appreciable but its thickness reduces by 50%, indicating that factors in the follicle that are not present in vitro might play an important role in the formation of this part of the matrix. To map the dimensions of the COC matrix laterally, H mech and H opt were measured as a function of the distance from the oocyte center. These results are also shown in Fig. 4  A and summarized in Fig. 4  B, in which the results of the correlative analysis of micromechanical and optical data are reflected in schemes that depict the extensions of the cumulus-containing and cumulus-free parts of matrix, the oocyte, and the cumulus cells drawn to scale. The sharp drops in H mech and H opt between 200 and 250 mm distances for in vivo expanded matrix, and between 150 and 200 mm distances for in vitro expanded matrix, indicate that the lateral extension of the coat is not diffuse but is clearly delimited, and that the cell-free coat lining the immobilized COC matrix laterally is very thin.
ACKNOWLEDGMENTS We thank  Luis Yate  ( CIC biomaGUNE ) for the preparation of gold-coated glass coverslips, and  Lionel Bureau  ( Laboratory of Interdisciplinary Physics ) and  Jessica Kwok  ( University of Leeds ) for fruitful discussions. This work was supported by the  European Research Council Starting  Grant  JELLY (FP7-ERC-2012-StG-306435  to R. P. R. ), the  Spanish Ministry for Economy and Competitiveness  ( MAT2011-24306  to R. P. R. ), and Unit Funding from the  UK Medical Research Council  (to D. G. J. ).
In Situ Apoptosis RPE flat mounts were fixed in 4% paraformaldehyde (PFA) and permeabilized with 0. 1% Triton X-100 and 0. 1% sodium citrate for 7 min followed by incubation in sodium citrate buffer (10 mM sodium citrate, 0. 5% Tween 20, pH 6. 0) for 1 min at 86 °C. Apoptosis was detected by the terminal deoxynucleotidyl transferase dUTP nick end labeling (TUNEL) method using the In Situ Cell Death Detection Kit (Roche Diagnostics). DNA was stained with DAPI (4′,6-diamidino-2-phenylindole  (Stohr et al. , 1977) , 1 μg/ml, Sigma-Aldrich). Apoptotic signals were visualized under fluorescence microscopy (Microscope BX60F5, Olympus Optical Co. LTD) and quantified by the image analysis system software Pro-Plus (Media Cybernetics Inc. ).
Detection of Intracellular ROS The in situ production of ROS in the RPE was assessed using dihydroethidium (DHE, structure is provided in Supplemental Fig. 1a ) staining. RPE flat mounts were fixed in 4% PFA and mounted on gelatin-coated slides. In a dark chamber, RPE was loaded with 5 μM DHE for 30 min at room temperature and then washed thrice in PBS. RPE was mounted on glass slides with VECTASHIELD® mounting medium with DAPI, and the slides were analyzed without delay using a LSM 510 confocal laser-scanning microscope. Images were obtained using an Apo-406 objective. The same acquisition settings were used for all experiments to allow direct comparison of RPE flat mounts. Digital images were processed using free ImageJ software (V. 1. 36, National Institutes of Health). Only cropping of images was performed; there was no adjustment of brightness.
Conventional PCR For the PCR reaction, specific sense and antisense primers were selected (Table  1 ), based on GenBank TRP sequences, using GeneJockey II (Biosoft, Cambridge, UK). Each sample was amplified using Maxima SYBR Green/ROX qPCR Master Mix (Thermo Scientific, Auburn, AL) in an automated thermal cycler (Bio-Rad CFX96 Real-Time System; Bio-Rad Laboratories, Hercules, CA). DNA amplification conditions included an initial 7-min denaturation step at 95 °C (which also activated the AmpliTaq Gold) and 40 cycles of 30 s at 95 °C; 30 s at 57 °C for the PRL receptor, 60 °C for TRPM2, and 57 °C for glyceraldehyde-3-phosphate dehydrogenase (GAPDH); 40 s at 72 °C, and a final elongation of 7 min at 72 °C. The RT-PCR samples were electrophoresed on a 1. 5% agarose gel and stained with ethidium bromide (0.
Ca 2+ Imaging For Ca 2+ imaging studies, ARPE-19 cells at confluence were plated onto round coverslips covered with poly-L-lysine (10 μg/ml, Sigma Chemical) and incubated in the dark with 10 μM fluo 8-AM (Invitrogen) dissolved in the extracellular buffer containing: 150 mM NaCl, 20 mM HEPES, 0. 1 mg/ml bovine serum albumin, 1. 0 mM EGTA, adjusted to pH 7. 4 with NaOH. Loaded cells were transferred into a perfusion chamber located on a microscope adapted to an epifluorescence system (Eclipse E600FN; Nikon Melville, NY). Cells were constantly perfused with oxygenated extracellular buffer at a rate of 15-17 ml/min and at 29-30 °C. Excitation of the fluorophore (at 488 nm) was performed with a light source controlled by a Lambda LS illuminator (Sutter Instruments, Novato, CA). Images were acquired with a cooled digital camera (Cool-SNAP-ES, Roper Scientific, Tucson, AZ) using the RS image software (Photometrics; Roper Scientific).
Statistical Analysis In general, all results were replicated in three or more independent experiments. The number of replicates (n) in each experiment and how often it was independently repeated (N) is indicated in each figure legend. Serum PRL levels are reported as mean ± S. D. and all others as mean ± S. E. M. ; all data showed normal distribution or equal variance according to D'Agostino-Pearson omnibus and Levene's tests, respectively. Statistical differences between two groups were determined by a two-tailed Student's t-test, among three groups with one variable by one-way ANOVA followed by Bonferroni's post-hoc comparison test, and among four groups with two variables by two-way ANOVA followed by Bonferroni's post-hoc comparison test (Sigma Stat 7. 0, Systat Software Inc. , San Jose, CA).