dataesr/scientific-paragraphs-categorization huggingface dataset:
This definition does not include 'the time elapsed from the date of referral of the general practitioner to the date of specialist assessment' (in some countries referred to as 'outpatient waiting time'). Inpatient waiting times were collected for all 'publicly-funded patients' that received treatment either by publicly or privately (non-profit and for-profit) owned providers. We do not focus on privatelyfunded patients since waiting time data for these patients are generally not collected on a routine basis through administrative data. 2. Referral-to-treatment waiting times (from family doctor referral) of patients treated in a given year (publicly funded patients) 11. Referral-to-treatment waiting times refer to "the time elapsed from the family doctor (General Practitioner) referral to the date patients added on the non-emergency (elective) surgery waiting list were admitted to an inpatient or day-case surgical unit for the procedure".
16. Eight countries provided inpatient waiting times data for patients treated; six for inpatient on the list. Only one country (Denmark) provided data on referral to treatment for patients treated (measure 2). No country could provide data on referral to treatment for patients on the list (measure 4). Note that referral-to-treatment waiting times are collected in England but not by surgical procedure (only by specialty or for all specialties; see Siciliani, Borowitz and Moran, 2013, chapter 2, for a general discussion and example of different measures). We did not attempt to collect data at specialty level (ophthalmology, orthopaedics, etc. ) since definitions of specialties across OECD countries may differ significantly.
To classify the surgical procedures, we follow the international classification system ICD-9-CM. If you are not able to provide the data according to the ICD-9-CM format, please specify which classification (national or international) you have used and, if possible, provide cross-classification (codes of your national system and corresponding codes to ICD-9-CM). The inpatient waiting times should refer to all 'publicly funded patients'. More precisely, the inpatient waiting times refers to all 'publicly funded patients' that received the treatment either by publicly or privately (non-profit and for-profit) owned providers. Publicly funded patients include "the patients whose expenditure is incurred by public funds (OECD Health data definition, 2010). Public funds are state, regional and local Government bodies (included are non-market, non-profit institutions that are controlled and mainly financed by government units) and social security schemes.
Provinces submit data for wait times for hip replacements, knee replacements, Coronary Artery Bypass Graft (CABG), cataract surgery, radiation therapy, MRI and CT scans. This data is from provincial registries or chart audits. Some provinces such as Prince Edward Island and Newfoundland and Labrador do not have registries. The reference period for the data is April 1st through September 30th of each year or the nearest 6 month proxy for provinces unable to produce data for the reference period. Coverage: Data coverage includes most provincial institutions or outpatient clinics where procedures are performed. Population inclusions and exclusions are noted below for each procedure. CIHI calculates provincial volumes for each procedure and cross-checks with volumes provided by provinces to ensure coverage matches definitions agreed to.
Estimation: The median waiting time is an estimation of weighted median for all procedures. The 10 provinces provide CIHI with summary level data and volumes. Using the volumes and summary level data we calculate an "all Canada" median wait for hips, knees, CABG, cataracts, and radiation. Waiting times are based on the ICD-10-CA/CCI Classification system. The codes are based on inclusions and exclusions to the procedure definitions. Provinces will use the coding to link provincial registry data with the DAD for quality checks.
Knee replacement (includes the revision of knee replacement): NGB. Further information: www. thl. fi Ireland Source of data: National Treatment Purchase Fund. Database: Patient Treatment Register. Reference year is mid-year (end of June). Estimation: Waiting times are estimated using the following ICD-9-CM codes: Cataract surgery:13. 1-13. 7 & 13. 90. Percutaneous transluminal coronary angioplasty (PTCA): 36. 04-36. 09. Coronary bypass:36. 1. Prostatectomy: 60. 2-60. 6 & 57. 71. Vaginal hysterectomy:68. 5. Total and partial hip replacement (includes the revision of hip replacement): 81. 51-81. 53. Knee replacement (includes the revision of knee replacement): 81. 54-81. 55. Further information: www. ptr. ie.
information: http://www. nza. nl/ New Zealand Source of data: National Health Board, Ministry of Health. Reference period for data is the calendar year. Data for waiting times of patient on the list is as at December in each given year. Estimation: Waiting times are estimated using the following ICD-9-CM codes: Cataract surgery:13. 1-13. 7 & 13. 90. Percutaneous transluminal coronary angioplasty (PTCA): 36. 04-36. 09. RECENT RELATED OECD PUBLICATIONS CANCER CARE -ASSURING QUALITY TO IMPROVE SURVIVAL (2013) A GOOD LIFE IN OLD AGE? MONITORING AND IMPROVING QUALITY IN LONG-TERM CARE (2013) STRENGTHENING HEALTH INFORMATION INFRASTRUCTURE FOR HEALTH CARE QUALITY GOVERNANCE (2013) WAITING TIME POLICIES IN THE HEALTH SECTOR, WHAT WORKS? (2013) OECD REVIEWS OF HEALTH CARE QUALITY -DENMARK (2013) OECD HEALTH DATA 2013 (Database available from http://www.
Further information: http://www. nza. nl/ New Zealand Source of data: National Health Board, Ministry of Health. Reference period for data is the calendar year. Data for waiting times of patient on the list is as at December in each given year. Estimation: Waiting times are estimated using the following ICD-9-CM codes: Cataract surgery:13. 1-13. 7 & 13. 90. Percutaneous transluminal coronary angioplasty (PTCA): 36. 04-36. 09. RECENT RELATED OECD PUBLICATIONS CANCER CARE -ASSURING QUALITY TO IMPROVE SURVIVAL (2013) A GOOD LIFE IN OLD AGE? MONITORING AND IMPROVING QUALITY IN LONG-TERM CARE (2013) STRENGTHENING HEALTH INFORMATION INFRASTRUCTURE FOR HEALTH CARE QUALITY GOVERNANCE (2013) WAITING TIME POLICIES IN THE HEALTH SECTOR, WHAT WORKS? (2013) OECD REVIEWS OF HEALTH CARE QUALITY -DENMARK (2013) OECD HEALTH DATA 2013 (Database available from http://www.
pyrosequencing of fecal bacterial 16S rRNA gene V3 region Fecal genomic DNA extraction, amplification of 16S rRNA gene V3 region and pyrosequencing of PCR amplicons were performed as described previously  (Zhang et al. , 2010 (Zhang et al. , , 2012b)). PCR primers are listed in Supplementary Table  S2. Bioinformatics and statistical analysis of 454 pyrosequencing data High-quality sequences were extracted, aligned in Greengenes (release 11_4) to remove sequences with o75% identity with Bacteria and then clustered using Cluster Database at High Identity with Tolerance (CD-HIT) to obtain representative unique sequences. Unique sequences were then subjected to RDP classifier to determine the phylogeny with a bootstrap cutoff of 50% (RDP database version 10. 28). Operational taxonomic units (OTUs) were classified with Distance-Based OTU and Richness.
Statistical analysis of physiological and biochemical data To test differences in physiological and biochemical values for statistical significance, normally distributed data were analyzed by analysis of variance followed by Tukey post hoc test (SPSS Inc. , Chicago, IL, USA). Data that did not meet the assumptions of analysis of variance were analyzed by the Mann-Whitney test (MATLAB R2010a). Differences were considered significant when Po0. 05. Correlations between gut microbial composition (PCoA coordinate scores and OTU abundances) and individual host parameters of obesity, glucoseinsulin homeostasis and inflammation were identified using Spearman's correlation  (MATLAB R2010a). Correlations between PCoA coordinates and host parameters were considered significant when Po0. 05. False discovery rate control was used to account for multiple comparisons when evaluating correlations between OTUs and host parameters in Matlab software, and correlations were deemed significant at false discovery rateo0.
Acknowledgements We thank ChloeBeal for technical help on RT-qPCR of probiotic strains,  M Zhang  for statistics expertise and  G Wang  and  J Wang  for 454 pyrosequencing data extraction and submission. The Yakult Intestinal Flora-SCAN (YIF-SCAN) technology, developed by  Yakult  and operated under licence, was used in this study to quantify the live probiotics in feces with RNA-based retro-transcription quantitative PCR. This work was supported by a grant from  Danone Research, National Natural Science Foundation of China program  grants  31121064  and  81100632.
We also set a lower threshold of 1, such that if the number of drugsensitive infected cells and virus falls below this threshold, while resistant populations are at 0, we assume the infection cleared and stop the simulation. One challenge in using a stochastic approach is the issue of units. The model parameters were estimated to fit viral titer data expressed in TCID 50 /mL of nasal wash. With the stochastic component of our approach, we need to convert to the total number of infectious virions at the site of infection. Handel et al. [28]  estimated a conversion factor between 10 2 and 10 5 , which takes into consideration the volume of respiratory tract as well as the fact that there is probably more than one infectious virion in one TCID 50 and that the virion concentration at the site of , which transition at rate k into productively infected cells, I 2 and J 2.
Acknowledgments We thank  Andreas Handel  ( University of Georgia ),  Craig Rayner  ( Roche Pharmaceuticals, Clinical pharmacology, Melbourne, Australia ),  Patrick Smith  ( D3 medicine, Nutley, NJ, USA ),  Stephen Toovey  ( F. Hoffmann-La Roche Ltd. , Pharmaceuticals Division, Basel, Switzerland), Mohamed Kamal (F. Hoffmann-La Roche Inc, Modeling & Simulation, Nutley, NJ, USA ) and  Micaela Reddy  (Modeling and simulation group,  DMPK department, Roche Palo Alto ) for their kind advice. We would also like to thank  Anders Boyd  ( INSERM UMR S707 ) for his insightful comments.
This work was supported by grants from the  European Union   FP7  project  FLUMODCONT  (no. 20160 ), from the  French Ministere de l'Enseignement Superieur et de la Recherche , the  National Institute of Health  ( OD011095 ) and  NIH  contract  HH5N272201000055C. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
To test this assumption we utilized acridine orange, an acidotropic dye that is widely used as an indicator of acidification. LNCaP cells stained with acridine orange exhibited green fluorescence with a few red puncta in basal medium. Serum starvation induced accumulation of red puncta, indicating an increase in autolysosomes number. In contrast, ML-9-treated cells showed an accumulation of enlarged vesicles emitting in both green and red, indicating an increase in intraorganellar pH (Figure  3b ). This effect of ML-9 could be explained by its weak base properties (pKa ¼ 8. 04, calculated using the Marvin software by ChemAxon, Budapest, Hungary). Thus, it seems that ML-9 behaves like a lysosomotropic agent which is accumulated in the lysosomes and leads to an increase in lysosomal pH. We confirmed these results by assessing Lamp1 immunofluorescence in LNCaP cells transfected with mCherry-GFP-LC3B.
ML-9 visibly increased the size of Lamp1-positive vesicles/ puncta (Supplementary Figure  S6a ). In addition, ML-9 induced accumulation of mCherry-GFP-LC3B puncta, which were largely colocalized with Lamp1-positive vesicles/puncta (Supplementary Figure  S6b ). Altogether these data suggest that ML-9 represents a 'two-in-one' compound, which stimulates autophagosome formation (by downregulating Akt/mTOR pathway) and inhibits their degradation (by acting like a lysosomotropic agent and increasing lysosomal pH). ML-9 stimulates autophagy via both Vps34-dependent and -independent mechanisms. Next, we assessed the levels of another important autophagy protein Beclin1 upon treatment with ML-9. Western blot analysis showed that ML-9 induced an increase in Beclin1 levels (Figure  4a ). To test whether Vps34-Beclin1 complex is important in ML-9-induced accumulation of autophagic vacuoles, we treated LNCaP cells with ML-9 or serumstarved medium, followed by the addition of 100 nM Wortmannin (an inhibitor of Vps34) for 1.
The membranes were blocked in a 5% fat-free milk containing TNT buffer (Tris-HCl, pH 7. 5, 140 mM NaCl and 0. 05% Tween-20) for 1 h at room temperature. The membranes were next incubated overnight at 41C with primary antibodies, and then for 1 h at room temperature with secondary antibodies conjugated to horseradish peroxidase. After washing, the membranes were processed for chemiluminescence detection using Luminata Western HRP substrate (Millipore, Billerica, MA, USA). Image J software (NIH, Bethesda, MD, USA) was employed for quantitative analysis. Immunocytochemistry and fluorescence microscopy. LNCaP-GFP-LC3 cells were grown on glass coverslips. Following treatments cells were rinsed with PBS, fixed with 4% paraformaldehyde-1 Â PBS for 15 min. After three washes with PBS the slides were mounted with Mowiol (81381, Sigma-Aldrich) on glass slides and subjected to subsequent fluorescence analysis using Zeiss Axiovert microscope (Carl Zeiss S.
When the pH inside the acidic organelles increases, acridine orange fluorescence switches from red to green. Confocal microscopy. Live-cell images were obtained using confocal laser scanning microscope (LSM 700, Carl Zeiss MicroImaging GmbH, Jena, Germany) with a Plan Apochromat 40 Â /1. 3 numerical aperture oil immersion objective and equipped with a CO 2 and thermocontrolled chamber. The images were analyzed in Zeiss LSM Image Browser software (Carl Zeiss MicroImaging GmbH) and prepared for publication in Adobe Photoshop. Calcium imaging. Ratiometric dye Fura-2/AM was used as a Ca 2 þ indicator. LNCaP cells were loaded with 2 mM Fura-2/AM for 45 min at 371C and 5% CO 2 in RPMI medium and subsequently washed three times with external solution containing (in mM): 140 NaCl, 5KCl, 1 MgCl 2 , 2 CaCl 2 , 5 Glucose, 10 Hepes (pH 7.
4). The coverslip was then transferred in a perfusion chamber on the stage of Nikon Eclipse Ti microscope (Nikon, Champigny-sur-Marne, France). Fluorescence was alternatively excited at 340 and 380 nm with a monochromator (Polychrome IV, TILL Photonics GmbH, Gra ¨felfing, Germany) and captured at 510 nm by a QImaging CCD camera (QImaging, Surrey, BC, Canada). Acquisition and analysis were performed with the MetaFluor 7. 7. 5. 0 software (Molecular Devices Corp. ). Statistical analysis. Data were analyzed using Origin 7. 0 (Microcal Software Inc. , Northampton, MA, USA). Statistical analysis was performed using Student's t-test, and Po0. 05 was considered as significant. Asterisks denote *Po0. 05, **Po0. 01 and ***Po0. 001.
Acknowledgements. We thank  Professor Terje Johansen  for the pDest-mCherry-eGFP-LC3B plasmid,  Professor Geert Bultynck  for the pcDNA3. 1(-)-GFP-LC3plasmid and  Professor Cristophe Biot  ( University Lille 1 ) for the valuable discussions. We acknowledge financial support from the  INSERM, la Ligue Nationale Contre le Cancer, le Ministere de l'Education Nationale , the  Region Nord/ Pas-de-Calais. Artem Kondratskyi  was supported by fellowship from  FRM (Fondation de Recherche Medicale). Maya Yassine  was a recipient of a PhD scholarship from  Erasmus Mundus. Kateryna Kondratska  was an IonTrac Project fellow.
The specimen was scanned with the SkyScan 1173 high energy spiral X-ray microtomograph with a tube voltage of 130 kV (61 mA current and a projection each 0. 2u of rotation) and a resolution of 10 mm. In order to facilitate processing, the volume was re-sampled to a voxel size of 40 mm. The m-CT data set of #Ish25 can be downloaded at a resolution of 20 mm following this URL: http://africanarchaeology. natural sciences. be/archaeological-sites/dem. -rep. -congo-zaire/Ishango/IV. %20Collections/2. %20Human%20Remains/c. %20Files%203D/ teeth/ishango-25. Threshold values between segmented tissues were determined following the half-maximum height methods  [72] [73]  using Aviso 6. 1 (www. vsg3d. com). The two-dimensional dental tissue proportions of #Ish25 were taken on the virtual mesial cross-section of the tooth following the method developed by Martin  [74]  and using ArteCore (ß2004-2006 ART+COM AG).
Three-dimensional data were recorded following the protocols defined by Kono  [64] , Tafforeau  [75]  and Olejniczak  [76]  using Amira 5 (ß2008 Visage Imaging, Inc. ). The cervical plane (to measure coronal dentine and coronal pulp) was computed following the definitions of Olejniczak  [62, 76]. Regarding the comparative sample, the taxonomic attributions of Australopithecus and early Homo M 1 follow Wood & Engelman  [20] , Wood  [77] , Quam et al. [60]  and Clarke  [78]. Comparative assessment of #Ish25's external crown dimensions and proportions was performed using classical linear measurements  [79]  and the method described by Quam et al. [60]. The comparative data were compiled from published data and original fossils (Texts S4. 1 and S4. 2 in File S1). The mean and range of variation of the comparative groups are given in Table  S1  (in File S1) and Table  S2  (in File S1).
Acknowledgments We are grateful to the following institutions and persons that gave permission to study the comparative material. In the following cases, the institution was the legal repository for the fossil material: Archeologie andennaise,  Belgium  ( D. Bonjean ),  Senckenberg Research Institute (F. Schrenk and O. Kullmer), Croatian Museum of Natural History  ( J. Radovc  ˇic),  Ditsong National Museum of Natural History (S. Potze), Institut de Paleontologie Humaine (H. de Lumley, D. Grimaud-Herve), Institutul de Antropologie ''Francisc I. Rainer'' (A. D. Soficaru) ,  Max Planck Institute for Evolutionary Anthropology  ( J. -J. Hublin) ,  Museo Nacional de Ciencias Naturales (A. Rosas) ,  Musee d'Angouleme (J. -F. Tournepiche) ,  Musee d'Archeologie Nationale, National Museums of Kenya (E.
t t and t tW ± at NLO and NLO+PS In order to study the top charge asymmetry at NLO for both t t and t tW ± , we employ MadGraph5_aMC@NLO, a framework  [38]  which allows to automatically generate the code needed to compute the cross section and any other observable for these (and any other SM) processes at LO, NLO and NLO+PS. We present results computed using the MSTW 2008 (N)LO PDF set  [39]  with five massless flavors. The pole mass of the top quark is set to 173 GeV and the W -boson mass to 80. 41 GeV. The renormalization and factorization scales are kept fixed and set to µ f = µ r = 2m t , and the corresponding uncertainty is obtained by varying the two scales independently in the interval [m t , 4m t ]. PDF uncertainties are calculated following the Hessian recipe given in Ref. [39]. As we have found that they are negligible in the case of A t c (at the level of 0.
The light axigluon is chosen to have universal couplings and a fixed width Γ G = 50 GeV, while the heavy axigluon is chosen to have non-universal couplings and of opposite sign between the light and top quark couplings. The model used for the light axigluon is available from the FeynRules model database  [48, 49]  though it has been slightly modified in order to include non-universal couplings for the heavy axigluon. For the light axigluon (m G = 200 GeV, Γ G = 50 GeV) the scenarios considered are: Left-handed (I) : g u L = g d L = 0. 5g s , g u R = g d R = 0 , Axial (II) : g u L = g d L = -0. 4g s , g u R = g d R = 0. 4g s. For the heavy axigluon (m G = 2 TeV) the decay width is calculated internally  [50]  considering the decays of the axigluon to quarks (and using α S (m G)) the scenarios are: Left-handed (III) : g u L = g d L = -0.
Acknowledgements We are thankful to  Josh McFayden ,  Tamara Vazquez Schroeder  and  Elizaveta Shabalina  for drawing our attention to features in ttW ± MC simulations that inspired this investigation. We thank  James Wells  for useful remarks and discussions. This work has been supported in part by the  ERC  grant  291377  " LHC Theory ", by the  Research Executive Agency (REA)  of the  European Union  under the Grant Agreement numbers PIT-GA-2010-264564 (LHCPhe-noNet) and PITN-GA-2012-315877 (MCNet). The work of FM and IT is supported by the IISN "MadGraph" convention 4. 4511. 10,by the  IISN "Fundamental  interactions" convention 4. 4517. 08,and in part by the  Belgian Federal Science Policy Office  through the  Interuniversity Attraction Pole   P7/37. The work of MZ has been partly supported by the  ILP LABEX  ( ANR-10-LABX-63 ), in turn supported by  French  state funds managed by the  ANR  within the  "Investissements d'Avenir" programme  under reference  ANR-11-IDEX-0004-02.
Translators were used when necessary. Household socio-economic data. A relative index of household socioeconomic status (SES) was derived based on dichotomous variables (durable goods and assets such as TV sets, cars, housing infrastructure, etc) using principal components analysis (PCA). Information on ownership of these assets was used to generate an index of long-run wealth which is thought to explain the maximum variance and covariance in the asset variables  [19]. For many economists, household income or consumption expenditure are the indicators of choice for socioeconomic status. However, the pilot study as well as discussions with locals showed that it would be difficult to collect such data through direct questioning, particularly since LAV officers are government employees. To overcome this and ensure that the questionnaire does not become too long, it was decided to use information on assets owned by household members and characteristics of the house to develop an indicator of SES.
This is a method also described by Filmer and Pritchett  [18]. The wealth index derived using asset variables has been shown to be a good proxy for long-run economic status. To confirm whether this wealth index could provide a good picture of the SES of different households we compared our data with that provided by other sources. In the first instance, our survey showed that the East of the Island was significantly poorer than the rest of La Reunion which is in accordance with previous results on unemployment and the economic situation in La Reunion. When comparing ownership of specific assets (e. g. car, washing machine) the data collected in this study were comparable to figures provided in previous censuses. For instance the percentage of households having at least one car was 69. 9% in the 2009 census compared to 71.
Data analysis Analysis was performed using STATA/SE v11. 0 (StatCorp, College Station, TX). Descriptive information on behaviour, knowledge, and perceptions related to mosquitoes in our study sample was extracted using univariate and bivariate analyses. However, extrapolating from a simple average expenditure per household, as well as the relationship between expenditure per household and Breteau index, could be confounded by other household-or zone-level cofactors (presence of mosquitoes at home, wealth index, education amongst others), resulting in biased estimates at the Island level. In light of this we decided to analyse the influence of household-and zone-level characteristics on expenditure on protective measures (i. e. direct expenditure at the household level) using multivariate regression analysis.