dataesr/scientific-paragraphs-categorization huggingface dataset:
01 to 10 mM GSH. The apparent K m and k cat values were calculated by nonlinear regression using the Michaelis-Menten equation (r 2. 0. 99). Data are represented as mean 6 S. D. (n63). ND: Not Detected. The detection limit was estimated at 0. 5 mUI. doi:10. 1371/journal. pone. 0080298. t003 GSTFuAs were able to bind ANS, but some properties, i. e. number and position of the binding sites, varied on the different isoform (Figure  5 ). The number of ANS binding sites, determined by fitting data of saturation experiments to Equation 1 detailed in material and methods section, is approximately equal to 1 for PcGSTFuAs, whereas CcGSTFuAs exhibited values below 0. 7 suggesting a lower affinity of these C. cinereus isoforms for the probe. The ANS binding site onto PcGSTFuA1 has been shown to overlap the glutathione binding site  [8].
Addition of benzoic acid induced genes involved in aromatic compound metabolism/ xenobiotic detoxification, such as cytochromes monooxygenases, The apparent K m values were determined using a concentration range of 100-800 mM in absence (2GSH) or presence of 5 mM GSH (+ GSH). The apparent K m and k cat values were calculated by nonlinear regression using the Michaelis-Menten equation (r 2. 0. 99). Data are represented as mean 6 S. D. (n63). ND: Not Detected. The detection limit was estimated at 0. 5 mUI. doi:10. 1371/journal. pone. 0080298. t004 while addition of vanillin is responsible for the activation of fungal metabolic pathways of phenolic compounds  [33]. However, vanillin is not a nutrient substrate but rather acts as a chemical stress on fungal cells  [31]. Altogether, these observations demonstrate the existence of a xenobiotic stress-derived metabolic response system towards compounds resulting from lignin degradation.
This work was supported by  Convention industrielle de formation par la recherche (CIFRE)  and the  French National Research Agency  through the ( ANR-09-BLAN-0012 ) grant and the  Laboratory of Excellence ARBRE  ( ANR-12-LABXARBRE-01 ) grant, the  Ministere de l'Enseignement Superieur, de la Recherche et de la Technologie , the  Institut National de la Recherche Agronomique (INRA) , and the  Centre National de la Recherche Scientifique (CNRS). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Donor solutions containing model drug and CPE dissolved were applied to the skin surface for 12 h. Model drug was quantified in skin layers using a validated HPLC-UV method. The enhancing ratio of fatty acid on model drug's penetration was calculated. In order to demonstrate the penetration of CPE into human skin, MSI was applied after in vitro skin penetration studies. Among the various techniques aiming to map the surface of the sample, MSI is the only analytical method capable of providing in a single run the spatial distribution of a wide range of molecules over the surface of a biological sample  [30]. Time-of -flight secondary ion mass spectrometry (TOF-SIMS) is a technique of choice for MSI and to our knowledge there is no published data on any attempts to visualize exogenously applied fatty acids penetration and distribution in human skin till now.
TOF-SIMS imaging of human skin sections for CPE penetration visualization and ion imaging Circle full-thickness skin specimens, obtained after in vitro skin penetration experiments, were immediately frozen at -60°C and stored until cryosectioning procedure. Skin specimens were embedded in OCT medium and sections of 12 μm thick were cut at -20°C using a CM3050-S cryostat (Leica Microsystèmes SA, Nanterre, France) and immediately deposited on a silicon wafer (2-in. -diameter polished silicon wafers, ACM, Villiers-Saint-Frédéric, France). The samples were dried under vacuum at a pressure of a few hectopascals for 15 min before analysis. Optical images were recorded with an Olympus BX51 microscope (Olympus, Rungis, France) equipped with lenses ×1. 25 to ×50 and a ColorView I camera, monitored by Cell B software (Soft Imaging System, GmbH, Münster, Germany).
In this case, the sample is moved step by step to record three successive patches of 0. 5 mm × 0. 5 mm each. The number of pixel was 750 × 250, each pixel having a size 2 × 2 μm 2. Under these conditions, the fluence (also called primary ion dose density) is maintained to 5 × 10 11 ions/cm 2 , which is below the so-called static SIMS limit  [45]. Because of the very low kinetic energy distribution of the secondary ions, the relationship between the time-of -flight and the square root of m/z is always linear over the whole mass range. The calibration was always internal, and signals used for initial calibration were those of H -, C -, CH -, CH 2 -, C 2 -, C 3 -, and C 4 H -for the negative ion mode. The data acquisition and processing software was SurfaceLab 6. 2 (ION-TOF GmbH, Münster, Germany).
Ion trap mass spectrometry The LC/MS/MS experiment was performed on a 1100 Series LC/ MSD ion Trap VL with an atmospheric pressure chemical ionisation (APCI) interface and a LCMS Chemstation software from Agilent Technologies (Palo Alto, CA, USA). The ionization mode was positive. The interface and MSD were as follows: nebulizer pressure, 60 psi (N2); dry gas, 5 L/min (N2); dry gas temperature, 350 • C; spray capillary voltage, 4000 V; corona needle, 4000 nA; collision-induced dissociation, 1 V. Collision gas in the trap was helium with a pressure of 6 × 10 -6 mbar.
Kinetics Kinetic parameters (K m and V max ) were obtained from at least two separate experiments after the addition of increasing amounts of vit K>O (0. 003-0. 2 mM) to the standard reaction. The estimation of the kinetic parameters was achieved by the incubation of at least nine different concentrations of vit K>O. Incubations were performed in duplicate. Data were fitted by nonlinear regression using the Michaelis-Menten model using the curve fitter R-fit program  [33].
4a ). When incubation of vit K 1 >O was performed in the presence of Y139C-, Y139F-, or Y139S-rVKORC1, two different reaction products were detected, corresponding, respectively, to 3-OH-vit K 1 and vit K 1 (Fig. 4b ). Formation of 2-OH-vit K 1 was not detected for rVKORC1 mutated in position 139. The 3-OH-vit K 1 production in the presence of Y139C-, Y139F-, or Y139S-rVKORC1 was linear according to the incubation time and to the concentration of proteins (data not shown). The reaction rates of recombinant rVKORC1 mutated in position 139 for the production of 3-OH-vit K 1 followed the Michaelis-Menten model allowing the determination of kinetic parameters (Table  2 ). The K m values of recombinant Y139C-, Y139F-and Y139S-rVKORC1 evaluated for the production of 3-OH-vit K 1 were identical to those determined for the production of vit K 1.
Statistical analysis All patients consulting one of the two health centres and satisfying the inclusion criteria were enrolled after written informed consent, regardless of their age. Two age groups were constituted: ≤5 years old and >5 years old. Moreover, the residence of the patients was classified as urban (patients consulting Tenrikyo health centre) or suburban (patients consulting Madibou health centre) area. Clinical and parasitological data were entered into preprogrammed Excel spreadsheet provided by the Department of Global Malaria Programme, WHO (Geneva, Switzerland) with the possibility to analyse PCR-uncorrected and PCR-corrected responses. Proportions and 95% confidence interval (95% CI) were calculated using Epi-info 6. 04 (Centers for Disease Control and Prevention, Atlanta, USA).
Acknowledgements We thank the patients, parents of sick children, and the medical staff of Tenrikyo and Madibou health centres for participation in the study and for their support. Field study was funded the A 20789 project of the  Special Programme for Research and Training in Tropical Diseases  ( TDR, World Health Organization, Geneva, Switzerland ) and  Programme PAL + (Action 2002 ) of the  French Ministry of Research. Laboratory research was funded by  Central African Network on Tuberculosis, HIV/AIDS  and  Malaria (CANTAM Network ), jointly funded by the  European and Developing Countries Clinical Trials Partnership (EDCTP)  and the Netherlands-African partnership for capacity development and clinical interventions against poverty-related diseases (NACCAP).
High performance liquid chromatography (HPLC) analysis of COL The amount of Berberine hydrochloride, Magnolol and Honokiol in the COL, was analyzed with HPLC (Waters, USA). 1mL sample of COL was extracted with methanol (15mL), by ultrasonic at room temperature for 30min. , then dilute with methanol to 25mL. Data acquisition and quantification were performed using Millenium 2. 10 version software (Waters). Symmetry reversed-phase column (C 18 , 250 mm×4. 6 mm; particle size 5μm, Waters, USA), was maintained at 30 °C. The mobile phase was filtered through a Millipore 0. 45μm filter and degassed prior to use. Berberine hydrochloride: The mobile phase was a mixture of acetonitrile-water (47:53), pumped in isocratic mode with a flow rate of 1mL/min. The mobile phase was filtered through a Millipore 0.
Nuclear Magnetic Resonance Spectroscopy (NMR). Polymers were solubilised in deuterated chloroform (CDCl 3 ) and 1 H-NMR spectra were obtained on a Bruker Ultrashield Av-400 spectrometer, operating at 400. 13 MHz, employing a 5 mm high-resolution broad-band ATMA gradients probe. Spectra were recorded using the zg30 pulse program with P 90 = 14. 5 μs covering a sweep width of 20. 7 ppm (8278 Hz) with 64 k time domain data points giving an acquisition time of 3. 95 s, Fourier transformed using 128 k data points and referenced to an internal TMS standard at 0. 0 ppm.
Micelles Characterization. Particle Size Analysis. Particle size distribution was determined by dynamic light scattering (DLS), otherwise known as photon correlation spectroscopy (PCS),  [25] [26]  using a Malvern Zetasizer Nano-series (Malvern Instruments Zen 3600, Malvern, UK). Each sample was diluted 10-fold with ultra-pure water before measurement and analyzed in triplicate at 25 °C. The particle size distribution data were generated using the DTS nano software (version 5. 2). The micelle size polydispersity was expressed by the polydispersity index, PDI. Zeta Potential. The zeta potential was determined using a Malvern Zetasizer Nano-series (Malvern Instruments Zen 3,600, Malvern UK) and measurements were performed at least three times after dilution in water. The zeta potential was calculated from the electrophoretic mobility applying the Helmholtz-Smoluchowski equation.
The column used was a LiChrospher RP C18 column (5 µm, 15 cm × 0. 46 cm) (Supelco, Bellefonte, USA). The separation was carried out using a mixture of methanol and water (96:4 v/v) as the mobile phase at a flow rate of 1. 6 ml min -1. The eluent was monitored at 292 nm and peaks were recorded using the chromatography data system software provided by Agilent. The column was equilibrated for 30 min with a minimum of 30 column volumes. The column was washed after use using water -acetonitrile mixture (50:50 v/v) for 60 min. This HPLC analytical method was validated (data not shown). Transmission Electrom Microscopy (TEM). TEM observation was carried out according to a previously reported protocol. 28 Briefly, an aliquot of the micelle solution was diluted 10-fold using ultrapure water and a drop of the diluted sample was placed onto a carbon-coated copper grid.
It will further develop the database of contacts in European pharmacy education. PHAR-QA works in parallel with other initiatives in healthcare disciplines (Table  1 ). There is collaboration between PHAR-QA and the "Medical Education in Europe-MEDINE" group who are currently developing the third stage of their project  [12]. The two groups representing the dental profession, the Association for Dental Education in Europe [13] and the Council of European Dentists [14], are working on a joint position on competences for dentists. PHAR-QA has contacts with these groups. The PHAR-QA consortium will propose foundation and advanced level competences for pharmacy practice and for specialized activities in hospital, industrial  [15]  and/or laboratory medicine settings. These will be validated by an iterative Delphi [16] interaction with the pharmacy departments in the PHAR-QA network.
Acknowledgments The authors acknowledge the valuable assistance of their co-workers:  C. Empsen ,  Lea Noel  (VUB), L. R. Manrique ,  J. M. Aranda  (UG),  P. Macheras ,  S. N. Politis ,  B. Papathanasiou  ( UoA ),  D. Volmer ,  K. Teder  (UT),  N. Katajavuori ,  H. Huhtala  (UH),  I. M. Rascan ,  A. Obreza ,  S. Menard ,  T. Kadunc  ( UL-FFA ),  S. Polak ,  A. Mendyk ,  M. Kozlowska  (JUMC),  D. Lupuleasa ,  F. S. Radulescu ,  C. Rais ,  V. Anuta  (UMFCD),  A. Marcincal  (EAFP). PHAR-QA is funded by the  European Union  [20]:  527194-LLP-1-2012-1-BE-ERASMUS-EMCR. The authors thank the reviewers for their useful comments.
Equipment NMR data for the isolated compounds were recorded on Bruker AVANCE 400 and AVANCE III 400 NMR spectrometers, both operating at 9. 4 T. 1 H and 13 C nuclei were observed at 400. 13 and 100. 61 MHz, respectively. The spectrometers were equipped with either a 5 mm multinuclear direct detection probe with z-gradient or a 5 mm multinuclear inverse detection probe with z-gradient. One-bond and long-range 1 H-13 C correlations from HSQC and HMBC NMR experiments were performed with average coupling constants 1 J (H,C) and LR J (H,C) optimized for 140 and 8 Hz, respectively. The NMR chemical shifts are given in ppm related to the TMS signal at 0. 00 ppm as internal reference. The UHPLC-ESI-(+)-HRMS and UHPLC-ESI(+)-HRMS/MS analyses were performed using the Accela system (San Jose, CA, USA) equipped with a binary pump, autosampler, online vacuum degasser, and temperature-controlled column compartment.
To verify their identities, HRMS/MS, generated by a newly developed data compound-dependent method for PA, were recorded. The resulting retention times, exact mass of protonated molecular ions, and characteristic fragment ions are summarized in Tables  1  and 3. In the full scan (TIC), six peaks with protonated molecular ions ([M+H] + ) were observed at m/z 300. 1805 (3. 05 min, lycopsamine; 12), 316. 1755 (3. 36 min, lycopsamine N-oxide, 13),  302. 1962 (3. 38 min, dihydrolycopsamine, 14), 318. 1911 (3. 75 min, dihydrolycopsamine N-oxide, 15), 342. 1911 (4. 62 min, acetyl-lycopsamine, 16 ), and 358. 1860 (4. 83 min, acetyllycopsamine N-oxide, 17). In the HRMS/MS experiment, these six peaks showed the characteristic retronecinetype specific diagnostic fragment ion at 138 m/z (Table  3 ). Of these six alkaloids identified, only two peaks were related to the dihydroPA form of lycopsamine and its N-oxide, which were not characterized as carcinogenic or hepatotoxic.
Evaluation process of OHRQol For this study, OHRQol was assessed using the GOHAI questionnaire and data were collected during interviews. First, the validity of the GOHAI for this sample was controlled. The interviewer performed calibration beforehand and the reliability of this calibration was tested on five participants. GOHAI comprises 12 items grouped into three fields: (1) the functional field (eating, speaking, swallowing), (2) the psychosocial field (concerns, relational discomfort, appearance), (3) the pain or discomfort field (drugs, gingival sensitivity, discomfort when chewing certain foods). The method used in this study was the cumulative method (GOHAI-Add), which consists in adding the scores obtained for each of the 12 GOHAI questions. Each question is given a score between 1 and 5.
Data acquisition and analysis Statistical analysis was performed using SPSS 20 software (SPSS Inc. , Chicago, IL). Before analysis, the validity of the study sample was verified. The purpose of the analysis was to verify that oral treatment would improve OHRQoL and level the difference between the degrees of tooth loss. Data from the GOHAI questionnaire before and after implant treatment were analyzed using a General Linear Model procedure (GLM) (variable: GOHAI parameters; fixed variable: type of oral treatment). A Student Newman-Keuls Post Hoc test (SNK) was applied to discriminate the impact of the type of treatment (α = 0. 05). The same method was used to measure possible impacts of age, gender, primary periodontal treatment and tobacco habits on GOHAI scores before and after treatment.
Discussion The main objective of this study was to highlight the impact of dental implant treatment on the OHRQoL of a group of patients. The data collected showed that OHR-QoL was improved after implant treatment, regardless of the GOHAI fields measured. The evaluation tool used most commonly in many studies conducted on the OHRQoL of patients is the OHIP (Oral Health Impact Profile)  [1, 24, 25]. However, the OHIP has not been validated in French and therefore could not be used for this study. For similar reasons, the Visual Analogue Scales (VAS) used in many studies to assess the OHRQoL of patients could not be used in the present study. However, a validated French version of the GOHAI was available  [18]. The GOHAI simply consists in a series of clear and concise questions grouped in twelve items which allow accurate analysis of the functional and psychosocial domains and of discomfort and pain.
In the 3 rd column, the same field is examined in polarized light to see the aspect of the abrasive powder (excepted for Parodontax ® , whose abrasive particles were dissolved during the washing steps, the image correspond to the polarization aspect of the 1 st column). Note that abrasive particles can be birefringent or not mirror combines with the light reflected from the sample to produce interference fringes (known as interferogram) where the best-contrast fringe occurs at best focus. The light and dark fringes are used in combination with the wavelength of the light to determine height difference between each fringe. A piezo-electric stage moves the sample vertically with a nanometer precision, which produces phase shifts in the interferogram. Interferograms were digitized using a CCD camera and data were analyzed to produce topographic surface maps at a magnification of 5x.
For each block, 3 images (1. 0x1. 3 mm) were obtained in the 4 quadrants of the brushed surface (internal, medium and outer position). The software Vision™ (release 4. 10, Wyco) was used to acquire the data and compute the mean roughness (Ra, expressed in µm) on each image. For each block, the values were averaged on the 12 images and the mean value obtained on the 3 blocks was considered; so for each trial, the analyzed surface was 46. 8 mm 3.
Statistical analysis Statistical analysis was performed using the Systat statistical software release 13. 0 (Systat Software Inc. , San José, CA, USA). All data were expressed as mean ± standard deviation. Differences between groups were analyzed by a non-parametric ANOVA test (Kruskall-Wallis) with the Conover-Figure  3 -Scanning electron microscopy of the abrasive grains contained in the different types of dentifrices and obtained after extensive washing and centrifugation. The EDX spectrum of each type of particle appears on the right. All images were obtained at the same magnification (500x) and the white bar stands for 10 µm. Note the considerable differences in shape and composition of the abrasive particles contained in the six dentifrices. The NaHCO 3 particles of Parodontax ® , having being solubilized during the preparation steps, are not figured Inman post-hoc test.
Examples of specific items and their codes can be seen in Figure  1. Personal factors are not yet listed within the full classification. The ICF and the ICF-CY form part of the WHO Family of Classifications and are designed to be compatible with the International Classification of Disease (ICD)  [22]. The ICD is an exhaustive list of human disease and the ICF was developed in part to remedy the reductive nature of such an approach. An ICF-Checklist has been developed by the WHO for standardised data collection, which consists of a list of 153 items considered to be the most relevant ICF categories for clinical purposes  [23]. The ICF Checklist has been modified for use in many different domains and disciplines to collect holistic data regarding human functioning  [24] [25] [26] [27] [28] [29] [30].
The objectives were: N To collect data using the ICF-CY from a population of persons under 16 years of age referred to special care or paediatric dental services in a prospective, cross-sectional, multinational study. N To describe the sociodemographic, medical and dental profile of this population. N To describe the most common problems of body structure, function, activity and participation encountered by this population. N To describe the most common environmental factors impact- ing on this population.
The study population This study used the ICF-CY Checklist for Oral Health to describe the medical, functional, social and environmental context of children and adolescents referred to special care or paediatric dental services. This population was chosen for data collection, as it was assumed that these children accumulate a higher prevalence of potential risk factors for poor oral health than the general child population. Children are generally referred to services because they are dentally fearful, because of a disability that directly or indirectly affects their oral health  [41] , or because of the magnitude of treatment required, either in terms of quantity or severity of oral pathology  [46]. Under the assumption of an equal effects model (EEM)  [47] , a power (1-b) of 0,8 and a level of significance (a) of 0,05 a sample size of 194 individuals was necessary in order to determine frequencies of ICF items with a precision of 10%.
The aim was therefore to recruit a convenience sample of 200 children or adolescents referred to Paediatric or Special Care Dental Units in France, Sweden, Ireland and Argentina. The inclusion criteria were: i) Patient under 16 years of age on the day of data collection. ii) Patient referred to a Paediatric or Special Care Dental Unit. iii) Patient with a signed consent form. Informed consent was sought from patients and/or their legal representatives for anonymous data collection and analysis.
Data collection All patients fulfilling the inclusion criteria were recruited consecutively, in order of presentation to the service on the days when the investigator was present, except in Ireland where a 'gatekeeper' system was imposed by local ethical committee regulations. In this centre potential participants had to be informed of the study by a gatekeeper and agree to be approached prior to contact from the investigator. The ICF-CY Checklist for Oral Health was completed by the investigator based on a structured interview with the patient and/or primary carer, from direct observation of the patient, and from information in the medical/dental records. In case of discrepancy between carer report and direct observation of the child's ability, the investigator used clinical judgement as to the degree of impairment or activity limitation.
Data entry and analysis Central, double, data entry was performed using Microsoft ExcelH. Descriptive statistics were used to describe the study population and to examine the frequency of problems recorded by the ICF-CY Checklist for Oral Health using SPSSH. For the ICF-CY components Body Functions, Body Structures and Activities and Participation absolute frequencies and relative frequencies (prevalence) of impairment/limitation in the study population were calculated. For Environmental Factors, absolute frequencies and relative frequencies (prevalence) of items entered as either a barrier or facilitator were reported. The frequency with which an item was reported for each country was compared using a x 2 test.