dataesr/scientific-paragraphs-categorization huggingface dataset:
Quotas by age were established as a preliminary to yield the control group similar to the case group in terms of age in order to achieve frequency matching (5 year age group). Quotas by socioeconomic status (SES) were also set a priori to control for potential selection bias arising from differential participation rates across SES categories. These quotas by SES were calculated from the census data available in the département of Hérault, in order to obtain a distribution by SES among controls identical to the SES distribution among general male population, conditionally to age. A total of 1098 cases and 1109 controls were eligible, of which 819 and 879, respectively, were included in the study representing a participation rate of 75% for cases and 79% for controls.
Data collection Trained clinical research nurses conducted face to face interviews of cases and controls using a standardized questionnaire based on a CAPI system (Computer-Assisted Personal Interview). Detailed information on socioeconomic characteristics, personal medical history and drugs use, family history of cancer, diet, tobacco, and alcohol consumption, physical activity, and residential and occupational history were gathered. Cases and controls were asked about their lifetime aspirin and NA-NSAIDs consumption, and more specifically about the name, the frequency, and the duration of the specific NSAID they used. They were also asked about the reason of NSAID use and if the use was under medical prescription or over the counter. For prostate cancer cases, medical information such as Gleason score or PSA at diagnosis had been extracted from their medical record or from the Hérault Cancer Registry.
Statistical analysis All analyses were performed using SAS 9. 4 software (SAS Institute Inc. , Cary, NC). NSAIDs were divided into three categories: overall users (all-NSAIDs), aspirin users (aspirin), and nonaspirin NSAID users (NA-NSAIDs). All-NSAIDs users were defined as users of aspirin or NA-NSAIDs at least once a month. Men who never took, or less than once a month, any kind of NSAIDs were considered as nonusers (reference class). The frequency of use (<1/day, =1/day, ≥1/day), duration of use (<5 years, 5-10 years, >10 years), and recency of use (former, current) were analyzed for all-NSAIDs, aspirin, and NA-NSAIDs users. We also classified NSAIDs according to their anti-COX-1 or anti-COX-2 preferential activity based on the known COX-1/COX-2 ratio of each NSAID. Coxib, diclofenac, etodolac, and oxicams inhibit preferentially COX-2 (ratio <1), while aspirin, propionates, and indometacin inhibit preferentially COX-1  [11].
After the selection process, we compared the distribution by SES between our control group and the male general population of the département of Hérault and found no significant difference, indicating that no major selection bias by SES had occurred. To minimize misclassification of exposure, data were collected by a trained research clinical nurse using a standardized questionnaire. Many details on former and current use of NSAIDs with exhaustive questions on name of the drug, indication, prescription by a doctor or over the counter, frequency, recency, and duration of use were collected. In our study, prevalence of exposure to all-NSAIDs was 31% among controls which was similar to other studies using questionnaires  [19, 27]. Recall bias is often an issue in case-control studies. Nevertheless, the use of a standardized questionnaire, a face to face interview by a research clinical nurses, and the fact that cases and controls were interviewed under the same conditions minimize the possibility of such bias.
Acknowledgments We would like to thank the clinical research nurses who were in charge of participants' interview, anthropometric measurements, and biological sample collection ( Anne-Laure Astolfi ,  Coline Bernard ,  Oriane Boyer ,  Marie-Hélène De Campo ,  Sandrine Margaroli ,  Louise N'Diaye ,  Sabine Perrier-Bonnet ). We also would like to thank  Christian Prad  and  Nadine Soller  for help with patient medical data collection within the  Hérault Cancer Registry  ( Registre des tumeurs de l'Hérault, Montpellier, France ). Finally, we are grateful to the  EPICAP study group. Urologists:  Drs Didier Ayuso ,  Bruno Ségui ,  Vincent Abd El Fattah  ( Centre Hospitalier Bassin de Thau, Sète, France );  Alain Guillaume ,  Jean-Paul Constans ,  Olivier Delbos ,  Pierre Lanfray ,  Damien Rizet ,  Etienne Cuénant  ( Cabinet Urologie du Polygone, Montpellier, France );  Michel Locci  ( Centre Hospitalier, Béziers, France );  Etienne Cuénant  ( Clinique Ste Thérèse, Sète, France );  Nicolas Drianno ,  Bernard Marc ,  Paulo Soares  ( Polyclinique Saint Privat, Béziers, France );  Antoine Faix ,  Samer Abdel Hamid ,  Bruno Ségui  ( Service urologie ,  Clinique Beau Soleil , Montpellier, France);  Samer Abdel Hamid  ( Clinique Saint Louis, Ganges, France );  Thibaut Murez ,  Grégoire Poinas ,  Laurent Cabaniols ,  Maxime Robert ,  Rodolphe Thuret  ( Centre Hospitalo-Universitaire Hôpital Lapeyronie, Montpellier, France ).
Biomedical and economic data are collected along the study to assess medical and cost impact of the device between the two arms. The other arm keeps usual care (Fig. 1 ). Telemonitoring device (Fig. 2 ) Tele-monitoring device available for use by type 2 diabetes patients in their own homes includes three educational software applications  [13] [14] [15]  focusing on a balanced diet and physical activity, available on tablets, and biomedical data sensors (scales with impedancemetry, actimeter, blood glucose monitor). Educational software Patients in the telemonitoring arm will have a tablet at home which they can use to access 3 interactive educational software applications: Nutri-Educ, Nutri-Kiosk and Acti-Kiosk. Nutri-Educ is a personalized nutritional educational software application that meets international clinical trial recommendations  [16].
It allows patients for whom a profile and nutritional requirement record has been created to enter their meals (in the form of photos with various portions of food), to establish whether or not their meals are balanced and to obtain one or more suggestions for improving the nutritional balance (Fig. 3 ). These meals can be recorded and used in the patient telemonitoring process. Based on feedback from the teaching units in our department of Diabetology, we assessed that asking for the description of six meals per month is the most feasible. Patients are asked to enter 2 breakfasts, 2 lunches and 2 dinners per month as a minimum requirement. Nutri-Kiosk is a series of quizzes which test patients' nutritional knowledge. EDUC@DOM patients are advised to use it at least once a month. Acti-Kiosk is a software application that allows patients to assess their physical activity/sedentary behavior.
It gives tips on how to start up a physical exercise program (warm-ups, stretching, adjusting the bicycle saddle, etc. ) in the form of videos. Connected health devices In addition to these education software applications, connected health devices form part of the telemonitoring system: connected blood glucose monitor to record blood glucose readings taken by patients, a connected scale with impedancemetry to monitor weight (with fat mass and lean mass) and an actimeter to monitor physical activity (number of steps taken, climbing stairs or hills, intensity of the activity). Some of the connected devices such as the scales do not require any intervention on the part of the patient to send the data, whilst others require data to be downloaded (blood glucose monitor) or the device has to be positioned next to the tablet (actimeter).
Specifically for the intervention group, assessment of the evolution of parameters collected with the telemonitoring device. Fig. 2  Telemonitoring devices available for the patient at home. A telemonitoring device with educational tools is given to people with type 2 diabetes at their home. It is composed of three software applications available on a tablet to improve eating habits, a self-monitoring blood glucose device, a connected scale to measure weight and fat mass, and a pedometer to evaluate physical activity. Secured web services are used to send and store data and to deliver a synthesis to patients and health professionals Fig. 3  An example of meal with a proposition of correction to improve the nutritional balance. Nutri-Educ is an interactive, educational, nutrition software application that provides personalized help in the composition of meals.
Sample size The sample size was calculated using the approach proposed by Frison and Pocock  [19]. The calculation is based on the comparison between the two study arms of the mean of 4 post-treatment measurements during the 1st year of follow-up (at 3, 6, 9 and 12 months). Assuming a standard deviation of 2 points of HbA1c, a correlation of 0. 4 between the pre-and post-randomization measurements, and a correlation of 0. 5 between the postrandomization measurements, 117 patients are required per arm (234 patients in all) to detect a difference of 0. 5 points of HbA1c with a power of 80%, a two-sided type I error of 5%. This calculation was computed using Stata SE 11. 2 software. To avoid any loss of power due to patients lost to follow-up, the cohort obtained is increased by 20% to give a total of 282 patients to be enrolled (141 per arm).
Data collection method Data are collected by the investigators, study staff and by patients called PROs (patient report outcomes) PROs. Hba1c levels, serum lipid profile, clinical exam and questionnaires were recorded on an e-crf (e-clinical report form) by single data entry. Quarterly, the CRAs (clinical research associate) call the patients, over the 2-year period, to obtain protocolrelated information: result of the HbA1c assay, medical treatments and adverse events. Data obtained using biomedical sensors will be retained. Range checks were implemented to limit data entry mistakes on the e-crf. All the data obtained from the various sources (biomedical sensors, tablet, data entered by the clinicians, data entered by the CRA) will be merged into a single complete database. A simple input will be made on an input mask with logical controls for the clinical data.
The data will be validated according to the data management plan defined jointly by the coordinating investigator and the epidemiology department (methodologist and statistician). The data will be frozen after the last logical and coherence checks carried out at the beginning of the statistical analysis. Once all the CRFs have been entered and validated, and all the steps of the Data Management have been locked, the Data Manager can proceed to freeze the database, a certificate of which will be issued to the Project team. The database will then be provided to the Statistician for analysis in accordance with the statistical analysis plan.
French legislation were obtained for this study: Agence Nationale de Sécurité du Médicament (ANSM) (authorization dated 10/05/2013), Comité Consultatif sur le Traitement de l'Information en matière de Recherche dans le domaine de la Santé (CCTIRS) (Approval Granted on 22/05/2013), Comité de Protection des Personnes (CPP) Sud-Ouest et Outre-Mer (SOOM) (Approval Granted on 27/05/2013), Commission Nationale Informatique et Libertés (CNIL) (Approval Granted on 22/10/2013). This study has been assigned the following numbers: ClinicalTrials No. NCT01955031 and ID-RCB number: 2013-A00391-44.
Acknowledgements We are grateful to all of the participants who have taken the time to take part in this study. We wish to extend our grateful thanks to the clinical teams at the  University Medical Centers of Grenoble, Lyon, Nantes, Nîmes, and Medical Centers of Cahors, Corbeil-Essonnes, Lannemezan, Tarbes, Clinics Ambroise-Paré (Toulouse), Claude Bernard (Albi), Pasteur (Toulouse)  and our 2 colleagues practising in independent medical office.
Genitalia were prepared by maceration of the abdomen in boiling 10% KOH, dissection in 10% ethanol, and pieces dehydrated by passing through 30%, 60%, and 100% ethanol and mounted in Euparal. DNA barcoding was conducted on total DNA isolated from a single leg of the paratype in the Canadian Centre for DNA Barcoding, University of Ontario, Guelph, Canada following  Ivanova et al. (2006). The barcode sequence (available in the Barcode of Life Database, BIN number: BOLD:ACS2287) was analyzed through the Basic Local Alignment Search Tool (BLAST), Barcode of Life Data System Identification tool  (Ratnasingham and Hebert 2007) , CLC Sequence Viewer and SnapGene 3. 3. 4. Barcodes for comparisons were taken from BOLD. Description. Alar expanse: 16-19. 5 mm. Body length: 9. 5-12 mm. Head: antenna 6-6.
Acknowledgements The first author received funding through a doctoral scholarship registration number  2016/20/T/NZ8/00541  from the  National Science Centre in Poland. This study was partially funded by task funds no. DS 530-L140-D242-17  and  DS 530-8645-D691-17. The  ClearWing Foundation for Biodiversity  made a financial contribution to this study. I thank  Economic Planning Unit  and the  Department of Wildlife and National Parks, Malaysia  for giving research permission and especially  Badmanathan Munisamy  for being my Malaysian counterpart. Microscopic photographs were taken in the  Department of Invertebrate Zoology and Parasitology, University of Gdansk, Poland. Our sincere thanks to  Marco Selis  for identifying Coeleumenes burmanicus. Thank you to  Dr Franz Pühringer  for providing the barcode sequence of P.
This uncertainty (and the steepness of the profile in the inner part of the cluster) is generally averaged out once one takes into account the angular resolution of the experiment, but one needs to specify the profile nonetheless to make the theoretical prediction. Focusing on the Perseus cluster and the signal from the core (z = 0. 0179, r s = 164 h -1 kpc, d = 70 Mpc), where analysis of the XMM-NEWTON and Chandra data seem to indicate an excess (unlike Hitomi's), one should then find a flux of polarised 3. 5 keV photons of φ P erseus pol, 3. 5keV ∼ 10 -6 ∆ νs CP ph cm -2 s -1 , (30) (depending on the exact FoV, here assumed to be about 1 arcmin 2 ) for a mixing angle of sin 2 (2θ) ∼ 7 × 10 -11 (corresponding to a decay rate of Γ νs 1. 63 10 -28 s -1 ), as suggested in Ref. [42]. 5 We note a factor 2 with respect to  [41].
Cross-section and polarization fraction for electron scattering on the lightest neutralino as a function of the energy of the electron, with a cut-off on the energy of the photon at 5 GeV. Computations were done using the Madgraph5 aMC@NLO package  [44]. M χ 1 =437. 79 GeV E γ >5 GeV M ẽR =670 GeV M ẽL =874 The photon spectra resulting from the χe -→ χe -γ elastic scattering collisions are shown in Fig  3  for three electron energies (294. 08, 500, 653. 48) GeV. For each of them, we show the total spectrum, corresponding to the sum of the two polarisation components (red curve), the spectrum associated with the positive circular polarisation (blue curve) and that associated with negative circular polarisation (green curve). The polarisation fraction is shown for each case (see lower panel associated with each plot).
Acknowledgements We thank  Ryan Wilkinson  with whom CB started the work on sterile neutrino polarisation, as well as  A. Ibarra ,  P. Jean ,  T. Lacroix  for illuminating discussions. OM would like to thanks the  CERN TH division  for its hospitality. ACV is supported by an  Imperial College London Junior Research Fellowship. CB was supported by the  DFG cluster of excellence Origin and Structure of the Universe  (www. universe-cluster. de). OM is a fellow of the  Belgian Pole d'attraction Inter-Universitaire  ( PAI P7/37 ).
2×10 5 THP-1 cells were plated in 6-well tissue culture plate in 1 ml antibiotic-free growth medium supplemented with fetal bovine serum (FBS). Cells were transfected according to standard protocol (Santa Cruz Biotechnology) with siRNA specific for RNA pol III 1 (sc-76188) and RNA pol III 2 (sc-36292), for cGAS (sc-95512) and control siRNA (sc-37007), using siRNA transfection reagent (sc-29528) and siRNA transfection medium (sc-36868). Six hours posttransfection with siRNA, cells were transfected with 500 ng of MT-COI DNA using jetPRIME. At 24 h, RNA was extracted, cDNA synthesized and A3A expression quantified by real time polymerase chain reaction (PCR). Data were normalized to the expression levels of the housekeeping reference gene RPL13A. Approximately 1. 5 × 10 6 THP-1 cells were transfected using jetPRIME (Polyplus transfection reagent) with 500 ng of MT-COI DNA in quintuplicate.
At 24 h posttransfection supernatants were grouped together and clarified by centrifugation. One ml of supernatant was incubated with 2 g or 10 g/ml of antibody against IFN␣, or IFN␤, or IFN␥ for 1 h and added to 1. 5 × 10 6 fresh THP-1 cells. At 24 h RNA was extracted, cDNA synthetized and A3A expression quantified by real time PCR. Data were normalized to the expression levels of the housekeeping reference gene RPL13A. THP-1 cells were transfected using jet-PRIME (Polyplus transfection reagent) with 500 ng of MT-COI DNA or V1V2 DNA. Two hours post-transfection, cells were incubated with RNA polymerase III inhibitor (ML-60218) and were collected 22 h post-incubation. Total RNA was extracted, cDNA synthetized and A3A expression quantified by real time PCR. Data were normalized to the expression levels of the housekeeping reference gene RPL13A.
FACS analysis for DNA double stranded breaks Twenty-four hours post-transfection, THP-1 cells were washed with PBS, fixed in 2% ice-cold paraformaldehyde (Electron Microscopy Sciences) for 15 min and permeabilized in 90% ice-cold methanol (Sigma) for 30 min. After two washes with PBS, cells were incubated for 1 h with 1:100 diluted Alexa Fluor 488-conjugated mouse monoclonal anti-␥ H2AX (N1-431) antibody (BD Pharmingen). All incubation steps were performed on ice. Cells were analyzed on MACSQuant Analyzer (Miltenyi Biotec) using the MACsQuantify™ Software (Miltenyi Biotec) or FlowJo software (Tree Star, Inc. , version 8. 7. 1). For each sample 10 000 cells were counted.
Real-time PCR and SYBR Green quantitative PCR Total RNA was extracted from THP-1 cells using RNeasy Plus Mini Kit (Qiagen) according to the manufacturer's instructions. Synthesis of cDNA was performed with 1 g RNA using the Quantitec Reverse Transcription Kit (Qiagen). Quantitative PCR was performed using cDNA samples and TaqMan Universal PCR Master Mix (Applied Biosystems) for human A3A to A3H. Primers and PCR condition were described before  (35). Data were normalized to the expression levels of the housekeeping reference gene RPL13A. For the real-time PCR based on SYBR Green, quantitative PCR was performed using DNA samples. Conditions were 10 min at 95 • C then 20 s at 95 • C, 20 s at 55 • C and 2 min at 68 • C for 40 cycles.
Quantification of histology markers For quantitative analysis of immunohistochemical markers, sections were photographed into JPEG images (Nikon Eclipse E1000 microscope and the Nikon DS-Ri1 camera system). For the quantification of α-SMA and VEGFR-2 the number of pixels marked above a threshold by each marker was measured using the ImageJ program (National Institute of Health) and calculated as the percentage of the total area covered by DAPI. For assessment of DLK, PCK and PCNA, positive cells were counted in each field.
Out of the 100 exons sequenced (two for each sample), we found one SNP (rs17553512) in the CD300b gene that affects nucleotide position 484 (G/A) and results in a synonymous substitution (isoleucine 120 to isoleucine). The frequency of both alleles (A 58-G 42%) was similar to the described for the European population in the NCBI SNP database (www. ncbi. nih. gov). In the case of CD300f, we identified two different SNPs in samples from MS patients. The first was a missense SNP (rs35489971) affecting nucleotide 22 (valine 22 to alanine). The distribution of both alleles (G 77-A 23%) was close to that described for the European population (G 82-A 18%). The second SNP (rs141171369), identified in a single patient, produces the missense mutation R33Q (Fig. 5A ) and it was described in European, South American and African populations with a very low frequency (0.
In fact, even the substitution of both glutamic acid 32 and arginine 33 by alanine and glycine, respectively, did not impair the capability of CD300f to form complexes (data not shown). Functional effect of SNP rs141171369 on CD300f expression. In order to determine whether the heterozygous substitution R33Q in CD300f could affect the function of the receptor, we first analyzed by flow cytometry the level of expression of CD300f on the surface of peripheral blood circulating monocytes from the MS patient in which the substitution was identified. As shown in Fig. 6A , whereas CD300f was on the cell surface of 100% of healthy control monocytes, only 6% of monocytes from patient LF6105 expressed CD300f. To determine whether the R33Q mutation was responsible for the low levels of CD300f surface expression detected on monocytes, COS7 cells were transfected with wt and R33Q mutant CD300f constructs.
The use of the 3DLigandSite tool allowed us to define some regions on the extracellular domain of CD300b as potential binding sites. 3DLigandSite utilizes protein-structure prediction to provide structural models for proteins that have not been solved, as in the case of CD300b. Ligands bound to structures similar to the query are superimposed onto the model and used to predict the binding site  27. Five binding clusters were obtained as a result of our query, using the sequence of human CD300b IgG domain. The data generated by mutating residues defining clusters 2, 3, 4 and 5 seem somehow confusing. First of all, mutation of residues glutamic acid 28 and glutamine 29 in cluster 5 is able to disrupt the formation of complexes of CD300b with itself and with other family members, whereas the disruption of cluster 3 did not change the binding capability of CD300b.
Flow cytometry. Cell surface expression of the desired molecules was tested by direct or indirect immunofluorescence following standard techniques  32. Analysis was performed using a FACSAria cell sorter (Becton Dickinson) instrument and Flow Jo software (Tree Star Inc. , Ashland, OR, USA). Immunoprecipitation and western blot analysis. Cells were lysed at 4 °C for 20 min using 1% Triton X-100 (Tx-100)-containing buffer described previously  3. Cell lysates were clarified by centrifugation at 16,000 × g for 15 min at 4 °C. Crude lysates were pre-cleared for 1 h at 4 °C using 20 µL of IgG Sepharose 6 Fast Flow (GE Healthcare Life Sciences, Chicago, IL, USA). Two additional pre-clearings were conducted for 30 min at 4 °C. For immunoprecipitations, pre-cleared lysates were incubated with 30 µL of Protein G-Sepharose beads (GE Healthcare) and 1 µg of Ab for 3 h at 4 °C.
Proteins in the crude lysates (2%) and immunoprecipitates were separated by SDS-PAGE and transferred onto polyvinylidene difluoride (PVDF) filters (Millipore, Billerica, MA, USA). Filters were blocked with 5% skim-milk and then probed with the indicated Abs at appropriate dilutions. Bound Abs were detected using West Pico Supersignal kit (Pierce-Thermofisher). Densitometric quantification was performed by using ImageJ software. Luciferase assays. RBL-2H3 transfectants were transiently electroporated with a luciferase reporter plasmid (pT81Luc) containing three tandem copies of the distal NFAT/AP-1 site of the murine IL-2 promoter 3 (0. 5 µg/10 6 cells) and a TK Renilla construct (Promega, Madison, WI, USA) (0. 1 µg/10 6 cells). Twenty-four hours post transfection, 1. 5 × 10 6 cells were stimulated for 7 h with the indicated antibodies using the murine mastocytoma P815 cell line as the presenting cell (1 × 10 6 ).
Acknowledgements This work was supported by grants from  Fondo de Investigaciones Sanitarias  ( PI1100045 ) and  Fundació "La Marato  de  TV3" 110532. HP  and LN received funds from the  Comisión Sectorial de Investigación Científica (CSIC-UDELAR) ,  Uruguay ,  Agencia Nacional de Investigación e Innovación (ANII) ,  Uruguay ,  PEDECIBA ,  Uruguay , and  FOCEM (MERCOSUR Structural Convergence Fund) ,  COF 03/1111.