dataesr/scientific-paragraphs-categorization huggingface dataset:
Netherlands  Genomics Initiative (NGI) /  NOW  project nr. 050-060-810  ( Netherlands Consortium  for Healthy Ageing; NCHA). The authors thank the members of the  Genomics Lab  and the ERGO support team for their help in sampling the data and in creating the database, the study participants, the staff of the  Rotterdam Study  and the participating general practitioners and pharmacists. The  Rotterdam Study  is funded by  Erasmus Medical Center  and  Erasmus University, Rotterdam ,  Netherlands Organization for the Health Research and Development (ZonMw) , the  Research Institute for Diseases in the Elderly (RIDE) , the  Ministry of Education, Culture and Science, the Ministry for Health, Welfare and Sports , the  European Commission (DG XII) , and the  Municipality of Rotterdam. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
The absolute quantification of TgVps35, TgVps26 and TgVps29 was carried out using three proteotypic peptides per protein (Supplementary Data 2). This approach yielded a stoichiometry of B1:1 for TgVps35 relative to TgVps26 and 3:1 between TgVsp35 and TgVps29 (Supplementary Table  1 ). This stoichiometry between TgVps35 and TgVPS29 is in contrast to the formation of a functional core retromer complex at a ratio of 1:1:1, as in mammalian and yeast cells  20. However, this discrepancy may also be explained by the fact that TgVPS29 may associate with TgVPS35 at a much lower affinity than TgVPS26, thus leading to the reduced levels of TgVPS29 identified by co-immunoprecipitations. In addition, 17 retromer-interacting proteins were identified in the interactome (Fig. 1c ) and ranked according to the following filtering criteria: protein common to at least two co-immunoprecipitations, absent in the control and identified with at least two unique peptides (Supplementary Data 1).
2a. We selected three positive clones from the emerging stable parasite population and the genome editing of these clones and TgVsp29-cMyc as described in a probed with rat specific anti-TgSORTLR antibodies. (I, input) corresponds to total detergent protein extracts from TgVps35-HA, TgVps26-HA and TgVps29-cMyc knock-in parasites, respectively; (U) unbound lysates to the anti-HA or anti-cMyc beads and (E) eluates corresponding to co-immunoprecipitates. The blots were simultaneously incubated with rat anti-TgSORTLR and rabbit anti-HA or rat anti-TgSORTLR and rabbit anti-cMyc antibodies. Protein markers (kDa) are also shown on left. IgG h means heavy chain of IgG, IgG L means light chain of IgG. (c) Retromer interactome was constructed by analysing the co-immunoprecipitates of TgVsp35-HA, TgVps26-HA and TgVps29-cMyc validated by immunoblotting in a and mass spectrometry (Supplementary Data 1).
gondii. Towards this goal, we characterized the retromer interactome that includes TgVps35, TgVps29 and TgVps26 proteins. We failed to identify homologues of nexins (SNX) in the immunoprecipitates of T. gondii using all three retromer components, confirming that no SNX proteins can be pulled down in association with the retromer cargo-selective trimer  39. However, we also noticed the paucity of nexin-like proteins in the genome databases of T. gondii, and this may also explain our inability to pull down recognizable nexin-like proteins in the parasite. Rather, we identified a singular retromer complex typified by the TgVps35-TgVps29-TgVps29 trimer. This complex interacts with TgSORTLR, N-ethylmaleimide-sensitive protein, Rab5B, Rab11B and the TBC1D5A homologue, a member of the Rab7-GTPase-activating proteins known to negatively regulate the retromer complex through Rab7 dissociation from endosomal membranes  22.
Confocal microscopy. Extracellular or intracellular parasites were fixed with 4% paraformaldehyde in phosphate-buffered saline for 20 min and processed as described  17, 50  using the indicated antibodies. The sources, origins and dilutions of all antibodies used for immunofluorescence assays were listed in Supplementary Table  5. Samples were observed with a Zeiss Confocal or Apotome microscope, and images were processed using ZEN software (Zeiss). Structured illumination microscopy. SIM was used to obtain high-resolution images using an ElyraPS1 microscope system (Zeiss) with a Â 100 oil immersion lens (alpha Plan Apochromat Â 100, NA 1. 46, oil immersion). The resolution was measured using beads with a diameter of 100 nm (Tetraspeck multicolor). The point spread function was calculated using the metroloJ plugin (ImageJ, NIH), which gave an x-y resolution of 125 nm and a z resolution of 500 nm.
A voxel size of 0. 050 Â 0. 050 Â 0. 150 mm 3 was used for the measurement. Three lasers (405, 488 and 561 nm) were used for excitation. SIM images were acquired with an EMCCD camera (Andor Technology Ltd, UK) and processed with ZEN software, exposure times varied between 100 and 120 ms. Three-dimensional images were generated using a z-step of 150 nm (total thickness B5 mm), while reconstructions and co-distributions were determined with IMARIS software (Bitplane). For co-distribution analysis, we used the colocalization module implemented in the IMARIS software. To process the images, we first applied a threshold for each channel (threshold adapted according to the labelling). For the Alexa488 channel, we used a threshold fixed at 15,000. For the red channel, the threshold varied between 8,000 and 25,000, depending on the dye used.
The percentage (%) of volume B (green channel) above the threshold that colocalized (colocalized volume B above threshold/total volume B above threshold) and thresholded Mander's coefficient B and Pearson coefficient were calculated. The acquisition was performed sequentially using 43HE, 38HE and BP 420-480 Zeiss filter sets, and 15 frames were acquired to reconstruct one image (five rotations Â three phases, with a SIM grating period of 51 mm for the blue channel, 42 mm for the green channel and 34 mm for the red channel). Beads with a diameter of 100 nm were imaged to measure the chromatic misalignment of our system (fit procedure by the ZEN software), and these parameters enabled further correction of the alignment on each acquired multi-channel stack. Image reconstruction was achieved using ZEN software with the following parameters: Noise Level -4, Sectioning 99-83-83 and Frequency Weighting 1.
Specifically, iKoTgVps35 mutants transiently transfected were treated with ATc or left untreated for 24 h or 48 h, fixed and stained with primary specific antibodies and either Dylight594-or Alexa488-conjugated secondary antibodies. Forty eight hours of ATc treatment corresponds to the time point where optimal effects on rhoptry and microneme biogenesis were observed and expression of TgVps35 protein was completely ablated as demonstrated by western blots and IFA. Therefore, all other experiments were then performed at this time point in this study. For GRASP-RFP expressing parasites, the fluorescence signal was directly visualized by SIM. Colocalization was quantified as overlap between green and red images using the IMARIS software for 90 intracellular parasites from 7 to 8 vacuoles. Electron microscopy.
All data files (*. raw) collected were processed with a specific workflow designed in Proteome Discoverer 1. 4 (Thermo Fisher Scientific). MS/MS data was interpreted using two search engine Mascot (version 2. 4. 1, Matrix Science, London, UK) and Sequest HT (Thermo Fisher Scientific). Searches were performed against T. gondii (TGVEG, TGME49 and TGGT1 stain) protein sequences downloaded from www. toxodb. org at the 11th December 2014 (18,954 entries). The Mascot ion score were 420 and Sequest HT XCorr 41. 5. The target-decoy database search allowed us to control and to estimate the false positive identification rate  51. Nanoscale liquid chromatography and tandem mass spectrometry. For nanoscale liquid chromatography coupled to tandem mass spectrometry (NanoLC-MS/MS), samples were electrophoresed onto 12% SDS-PAGE and stained overnight with colloidal Coomassie Brilliant Blue.
Mass correction was achieved by recalibration of acquired spectra to the applied lock masses hexakis (2,2,3,3,-tetrafluoropropoxy) phosphazine ( [M þ H] þ ¼ 922. 0098 m/z)]. For tandem MS experiments (CID), the system was operated with fixed cycle time of 3 s in the range of 150-2,200 m/z. MS/MS scan speed was monitored in function of precursor intensity from 4 to 25 Hz. Ions were excluded after acquisition of one MS/MS spectra and the exclusion was released after 1 min. The complete system was fully controlled by Hystar 3. 2 (Bruker Daltonics). Bioinformatics and protein identification. Mass data collected during nanoLC-MS/MS analyses were processed, converted into '. mgf' files with Data Analysis 4. 0 (Bruker Daltonics) and interpreted using MASCOT 2. 5. 1 algorithm (Matrix Science, London, UK) running on a local server.
Searches were performed without any molecular weight or isoelectric point restrictions against an in-house generated protein database composed of protein sequences of T. gondii (ToxoDB database, October 2014) and known contaminant proteins such as human keratins and trypsin. All proteins were concatenated with reversed copies of all sequences (49,328 entries) with an in-house database generation toolbox https://msda. unistra. fr  53. Trypsin was selected as enzyme, carbamidomethylation of cysteine ( þ 57 Da) was set as fixed modification, oxidation of methionine ( þ 16 Da) were set as variable modification and both precursor and fragment mass tolerances were adapted according to instrumental mass accuracy. Mascot results were loaded into the Proline software (Proline Studio Release 1. 0) and filtered to obtain a false discovery rate of o1%.
Time-scheduled SRM method targeted the pairs of isotopically labelled peptides/ endogenous peptides in ±5 min retention time windows within a cycle time of 3 s. Mass data collected during LC-SRM were processed with the Skyline open-source software package 3. 1. 1 (ref. 55). Area intensity ratios of the heavy and the light forms of each peptide were manually checked. The endogenous peptide amount calculation was performed by using the most suitable calibration curve. The mass spectrometry and LC-SRM data were deposited to the ProteomeXchange  56  Consortium via PRIDE  57  partner repository, and the peptide atlas SRM experiment library (PASSEL), respectively. Production of recombinant glutathione S-transferase (GST)-TgHP12 and specific antibodies. The DNA corresponding to C-terminal sequence of 254 amino acids long from 1,051 to 1,812 nucleic acid was amplified by PCR using the following primers: sense 5 0 -CCGGGGATCCGTAGAAAAGCCTACAACGGTG GGG-3 0 , and antisense, 5 0 -CCGGGCGGCCGCTCACAATCTGTCAAGTCTTCCT CCAGTC-3 0.
Protein markers (kDa) are also shown on left. IgG h means heavy chain of IgG, IgG L means light chain of IgG. (c) Retromer interactome was constructed by analysing the co-immunoprecipitates of TgVsp35-HA, TgVps26-HA and TgVps29-cMyc validated by immunoblotting in a and mass spectrometry (Supplementary Data 1). The interactome identified TgVps35, TgVps29 and TgVps26 (red) and TgSORTLR (blue) in addition to the putative phosphatidylinositol synthase (PPS), transporter major facilitator family protein (TMFFP), putative N-ethylmaleimide sensitive fusion protein (NSF), multi-pass transmembrane protein (MTP), Rab5, Rab11B, Rab7-GTPase-activating protein (GAP) regulator TBC1D5A homologue and nine parasitespecific HP. (d) Confocal imaging of TgVps35, TgVps26 and TgVps29 that co-localize with TgSORTLR, proM2AP and vacuolar protein 1 (VP1) using intracellular tachyzoites of the respective knock-in parasites stained with anti-HA or anti-cMyc antibodies followed by probing with anti-TgSORTLR, anti-proM2AP and anti-VP1 antibodies, respectively.
Acknowledgements L. O. S. would like to thank  Thomas Mouveaux ,  Pasteur Institute of Lille ;  Etienne Dewailly ,  University of Lille ;  Joelle Duflot ,  Pasteur Institute of Lille  for excellent technical assistance and  Pierre Julien Sloves ,  Pasteur Institute of Lille  for his early guidance. This work was supported by the following grants:  Laboratoire d'Excellence (LabEx) ParaFrap  from the  National Agency for Research   ANR-11-LABX-0024  and the  ANR-14-CE14-0002-01. We also acknowledge additional financial support from the  INSERM, Pasteur Institute of Lille  and  CNRS. PhD and Post-doc fellowships were from ' Metropole Europeenne de Lille' (MEL)  to L. O. S. and ' FEDER-Region ' for T. D. A. M. A. H is supported by the  European Research Council  ( ERC Consolidator  grant no. 614880 ).
ACKNOWLEDGEMENTS This work was supported by the  National Research Foundation  ( NRF-2013R1A2A1A01016914 ,  NRF-2013R1A1A2011750 ) of the  Ministry of Education , the  Industrial Strategic Technology Development Program (10041878)  of the  Ministry of Knowledge Economy , the  Climate Change Research Hub of KAIST  (Grant No. N01150041 ), and the  GRC  project of  KAIST Institute  for the NanoCentury. The authors wish to thank  Soo Kun Jeon  and his colleagues ( Semicon Light Co. , Ltd. , Republic of Korea)  for their help with the device fabrication process.
Conclusion Despite some study limitations, Smit et al. have to be commended for performing an elegant clinical trial on routine procedures that had so far never undergone rigorous testing under randomized, controlled conditions. The results of their much larger "Optimal Oxygenation in the Intensive Care Unit (O2-ICU)" trial (ClinicalTrials. gov NCT02321072) comparing high-normal vs. low-normal (120 vs. 75 mmHg) PaO 2 targets in ICU patients is therefore eagerly awaited.
6214-INSERM U1083, Université Angers, PRES L'UNAM, Angers, France Full list of author information is available at the end of the article See related research by Smit et al. , http://ccforum. biomedcentral. com/articles/10. 1186/s13054-016-1240-6 © 2016 The Author(s). Open Access This article is distributed under the terms of the Creative Commons Attribution 4. 0 International License (http://creativecommons. org/licenses/by/4. 0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons. org/publicdomain/zero/1. 0/) applies to the data made available in this article, unless otherwise stated.
8 Å  [28]  and showed high similarity Table  1  List of D. radiodurans DNA repair proteins for which high-resolution structural data is available. The list includes the name of the proteins, their associated open reading frame (ORF), the repair pathway they are involved in (BER, NER, DSB or MMR), their function and the references to the structural studies. In the case of drUNG, structures of both the apo-and the DNA-bound form have been determined. Structures of the individual drRecO and drRecR proteins and of the drRecOR complex have been determined. In the case of drRecD2 and drRecQ, only partial structures of the proteins have been solved, while the quasi-atomic structure of intact drRecN was assembled using high-resolution crystal structures of three overlapping regions. to previously determined structures of human  [35] , herpes simplex virus  [36] , E.
Difficulties in producing and characterising several repair systems from E. coli (notably NER and DSB repair proteins) have been largely overcome with the study of D. radiodurans proteins. In particular, all the structural information currently available for the RecFOR system comes from studies of D. radiodurans targets. These studies have thus provided new, valuable data that have largely contributed to deciphering some of the molecular mechanisms underlying DNA repair. Several structural and functional studies of D. radiodurans proteins have also revealed that seemingly conserved enzymes actually exhibit differences in structure and/or enzymatic activity. This is particularly striking in the case of BER enzymes that are highly homologous to their E. coli counterparts in terms of sequence and structure and yet possess altered substrate specificities or increased catalytic activities (Table  3 ).
Acknowledgements For the work presented in this review, J. T. and E. M. received financial support from: the  Research council of Norway  (FUGE, SYNKROTRON and FRIBIO programmes), the  CEA ('Radiations ionisantes' programme) , the  CNRS (ATIP-Avenir programme) , the  European Synchrotron Radiation Facility  ( ESRF; Inhouse research programme ), the  Fondation ARC  (Project  N°SFI20111203907  and  N°PJA20151203255 ), the  FP7 Marie Curie action  ( Intra-European Fellowship ) and the  FCT  (Projects:  SFRH/BPD/97493/2013 , post-doc fellowship;  PTDC/QUI/BIQ/100007/ 2008 ,  R&D  project;  UID/CBQ/04612/2013 , MostMicro unit). Provision of beamtime on the structural biology beamlines at  ESRF, Grenoble, France , are gratefully acknowledged. J. T. and E. M. are very grateful to  Dr. S. McSweeney  for initiating the structural genomics project on D.
Acknowledgments This study was initiated by the  Serology Group of the French National Reference Center for Toxoplasmosis  ( Centre National de Référence de la Toxoplasmose ) and funded by the  Department of Infectious Diseases ,  French Institute for Public Health Surveillance (InVS), Saint-Maurice, France. We would like to thank the members of the National Reference Center for Toxoplasmosis:  A. Totet  and  C. Damaini  ( Hospital and University Centre Amiens );  B. Cimon  ( Hospital and University Centre Angers );  E. Scherrer  ( Hospital and University Centre Besançon );  I. Accoceberry  ( Hospital and University Centre Bordeaux );  M. Demar  ( Hospital and University Centre Cayenne );  F. Botterel-Chartier  ( Hospital and University Centre Créteil );  B. Cuisenier ,  F. Dalle  and  S. Valot  ( Hospital and University Centre Dijon );  M.
12-Months Post-randomization The primary purpose of the 12-month follow-up will be to obtain the health-economic assessment (see section below); however, we will also collect data on the primary outcome measures and the CGI so that we can assess longer-term physical functioning, fatigue, and change in overall health and CFS. The following information will be collected via questionnaires sent in the mail with a stamped addressed envelope for return: CFQ, SF-36 PF, CGI, EQ-5D, and CSRI.
After an SAE or SAR, the center leader will make a decision as to whether the participant should be withdrawn from either randomized treatment or from the trial, or if an alteration in their SMC is needed; arrangements will be made for further assessment and management as required. The trial manager will provide the center leader with monthly follow-up reports until resolution. These reports will be communicated to the Data Monitoring and Ethics Committee (DMEC), and other appropriate authorities via the trial manager. A risk assessment has been undertaken and we have concluded that the therapies are of low risk to participants. NSAEs will be reported en bloc to the DMEC on a regular basis, according to the usual regulatory requirements.
Measures Used for Economic Evaluation Quality of life and function will be measured using the EQ-5D and the WSAS. The EQ-5D will also be used to generate quality-adjusted life years (QALYs) and linked to costs measured using data collected with the CSRI. The IPAQ will determine PA participation before and after the intervention, and the TSK-F will determine beliefs about exercise at baseline. Participants will be asked about their current employment status and whether they have had to reduce/stop work due to their CFS/ME. The physiotherapist will record the number of contacts and the length of each contact, and during the final guidance session, will measure adherence to the GES guided support. Other service use during the trial will be reported by participants completing the CSRI at follow-up, including use of primary and secondary care services, use of other self-help approaches such as the Internet, books or voluntary sector support, medication, therapy outside of the trial, complementary healthcare, and care from family/friends.
Non-Responders If a returned form is incomplete, the researcher will contact the patient, usually by telephone, to acquire any missing data. In the event that no outcome data is completed or returned after 2 telephone attempts spaced 1 week apart, the researcher will email or text the participant to ask for answers over the telephone or via email solely for the 2 primary outcomes and the CGI. The researcher will make a file note that the outcome data were collected in this way. If a participant withdraws from the treatment, but not the trial, data will be collected in the usual way. If the participant is not willing to provide all follow-up data, a request will be made to complete only the primary outcome and CGI; if the participant agrees, these will be completed immediately.
Data Entry and Analysis Data will be double entered by a dedicated data-entry researcher. The analysis and presentation of the trial will be in accordance with CONSORT guidelines including a flow diagram of enrollment, allocation, follow-up, and analysis  [26, 44]. We plan to use descriptive statistics to compare characteristics of invited individuals who did or did not agree to take part and eligible individuals who were randomized or not randomized (pending ethical approval). We will also examine differences between trial arms in important baseline participant characteristics.
Descriptive Statistics for Primary and Secondary Outcomes Box plots will be used to assess the data distribution of continuous measures. Descriptive statistics will be broken down by intervention group at baseline and follow-up. Normality of the scales and regression residuals will be explored using diagnostic plots, and if the assumption of normality is violated, the data will be transformed. We will present means and standard deviations for all normally distributed measures, and medians and quartiles for nonnormal measures. Discrete outcomes will be described using both number and percentage.
Analysis for Hypothesis 1 Our primary intention-to-treat analysis will compare the SF-36 PF and CFQ at 12 weeks between groups adjusted using multivariable linear regression analyses  [45]. Intention-to-treat (ITT) analyses will be conducted on data from all randomized participants with information at follow-up (ie, modified ITT) regardless of any departure from the allocated treatment arm. We will adjust for our stratification factors (depression, center, and severity of disability) as well as baseline values of outcomes and treatment arm. A secondary analysis will explore the association between treatment arm and having achieved a clinically useful improvement on the SF-36 PF (ie, an 8-point increase) and the CFQ (ie, a 3-point decrease) using chi-squared analysis. Analysis of the secondary outcome, the CGI, will compare the proportions scoring "much" or "very much" better (1 and 2), the proportions scoring "a little better," "no change," or "a little worse" (3 to 5), and the proportions scoring "much" or "very much" worse (6 and 7) across treatment arms, using an ordinal logistic regression adjusting for our stratification variables.
Sensitivity Analysis Sensitivity analysis will be conducted to assess the impact of missing data on our results. We will estimate whole-scale missing data due to loss to follow-up using multiple imputation by chained equation. This will allow us to conduct a strict ITT for all respondents who took part at baseline. Following recent guidelines, we will also conduct a sensitivity analysis that will take into account the partially nested design of the study and, therefore, assess the potential impact of the "therapist effect" on our results  [46]. Further analysis will be conducted to adjust for potential confounders, including sex and age. A per-protocol analysis will serve as a further sensitivity analysis to investigate the robustness of the conclusions of the primary analysis, following departures from the randomized intervention policies.