dataesr/scientific-paragraphs-categorization huggingface dataset:
Synthesis General aspects. Since the phosphanes PCy 3 , PCyp 3 and P i Pr 3 are sensitive towards oxidation, mononitrosyl complexes with these ligands were prepared under inert-gas atmosphere. In contrast to the mononitrosyls containing PPh 3 or PPh 2 Bn as ligands, the complexes of the stronger reducing phosphanes were isolated as {RuNO} n mixtures with n = 6-8 (several signals in the NMR spectrum and several peaks in the region assignable to coordinated nitrosyl in the IR spectrum). Therefore no data derived from elemental analysis are provided except in two cases for which a yield could be specified, as the elemental analysis of the product is in agreement with a formulation of the product as a pure {RuNO} 7 compound. The m/z ratio of the mass spectra of the {RuNO} n mixtures are calculated with regard to a {RuNO} 7 compound of the formula [RuX 2 (NO)-(PR 3 ) 2 ].
Acknowledgments Bicoll members dedicate this article to  Prof. Dr. Joachim Treusch , on the occasion of his 70th birthday. The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was partly supported by research grants from  German Federal Ministry of Education and Research (BMBF ,  0315012A  and  0315944A ) and by the  EuroTransBio/OSEO  grant No. PRESAGE 37149.
Statistical analysis Data are expressed as the mean ¡ standard deviation (for normal distribution) or as the median with range (for non-normal distribution). Quantitative variables were analysed using Mann-Whitney U-test. Genotypic frequencies of GSTM1 and GSTT1 were compared between cases and controls using a chi-squared (262 table) test with Yates' correction. Analyses were performed using SPSS version 13. 0(SPSS Inc. , Chicago, IL). A value of P,0. 05 was considered statistically significant.
Statistical analysis A sample size calculation was not determined but based on a similar phase IIb study  [48, 49] , a sample size of 25 patients per arm was considered adequate to demonstrate the disposition of AS, dihydroartemisinin (DHA), AQ and DAQ of the two formulations and to model the rate corrected QT intervals. Treatment efficacy was determined with PCR correction of recurrent parasitaemia and excluded all patients who did not complete followup to D28. The safety analysis included all patients who had received at least one dose of the study drug. Data were described as frequencies (proportion), median (range) or mean (standard deviation Population PK modelling of AQ/DAQ was reported elsewhere  [50]. Concentrations below the LOQ were removed from the database. AS and DHA concentrations were fitted simultaneously, as it was the case for AQ/DAQ.
63-point increase in the objective function (P = 0. 01, 1 degree of freedom). At each step, the goodness of fit was evaluated by use of a graph of the weighted residuals versus time after administration of the dose (time) or versus the predicted concentrations. The accuracy and robustness of the final population models were assessed by normalized prediction errors and visual predictive checks. The final population model parameters were used to perform 200 simulations of the database. The 2. 5th and the 97. 5th percentiles as well as the 50th (median) of simulated concentrations were plotted against observed concentrations. Individual Bayesian estimates of the PK parameters were used to calculate individual areas under the curve (AUC) and elimination half-lives (T½). Individual AUC values of AS and DHA, expressed in μmol*h/L, were combined in order to obtain DHA equivalents (DHAeq).
ECG data A total of 363 ECGs recorded were analysed. Because there were no statistically significant differences in the mean QTcB, median PR and QRS intervals, and mean/ median changes between the two arms at any time point, the QTcB data were combined for analysis. QRS intervals remained within the normal range at all time points (Table  5 ). At D2 + 4 hours, the mean increase in the QTcB over baseline was 9. 02 milliseconds (ms) (95% confidence intervals: 2. 72-15. 31 ms (p = 0. 0059). The nonlinear mixed effects modelling identified heart rate (inverse relationship), DAQ concentrations (positive relationship) and female sex (positive relationship) as significant, independent, explanatory variables for the QTcB over time (Table  6 ).
Acknowledgements We are grateful to the patients for participating in the study and the study nurses for their invaluable help. We thank  Dr Piero Olliaro  for helpful discussions during protocol development;  Dr Julie Simpson  for help with the population PK sampling; Cardinal Systems for data management and analyses;  SYNEXEL Research International SAS  for the bioanalytical report;  Sanofi-Aventis (now Sanofi)  for supplying both ASAQ formulations; Quintiles for reading the ECGs and writing the ECG report and  Susan Wells ,  Karly Louie  and  Graciela Diap  for valuable editorial contributions to this manuscript. DNDi thanks the following donors for supporting this study: the  Department for International Development (DFID), UK ;  Spanish Agency for International Development Cooperation (AECID), Spain ;  Dutch Ministry of Foreign Affairs  (DGIS), The Netherlands;  Médecins Sans Frontières, International ;  French Development Agency (AFD), France.
Russmann et al. describe spontaneous reports of drug-induced liver injury after rivaroxaban to the Swiss pharmacovigilance system  [1]. They also found a similar signal in large spontaneous report databases (EMA, USFDA, WHO UMC monitoring centre). The causality of rivaroxaban in these cases is plausible, and rivaroxaban may indeed be associated with liver injury, as most drugs are. However caution may be warranted in the interpretation of these findings, and especially before any firm conclusions are drawn or actions suggested. Ten of the fourteen reported cases occurred after surgery, mostly total knee replacement, which involves anaesthetics and other drugs that may be hepatotoxic. Surgery itself may result in hepatic injury through transient low output syndrome in these often elderly patients.
Looking at other reporting databases is useful to support a signal. However, the WHO UMC database includes information from other databases, since it simply compiles data sent by individual countries. As such it is a secondary database, not a primary one. It would duplicate Eudravigilance data, and the FDA data. The FDA database itself includes cases occurring within the US, and industry-reported cases from outside the US: these may also be found in Eudravigilance, and in the WHO database. A very small number of cases may become an epidemic. These databases show that cases may exist, but the actual number of cases and their meaning are uncertain. Careful analysis of the individual cases might help identify duplicate reports in the different databases and give a clearer vision of real numbers of individual reports.
Trial design We planned a three-arm parallel-group RCT with a sample of representative abstracts of RCTs of pharmaceutical treatment indexed in PubMed, each reported with 1) no mention of the funding source or authors' financial CoI, 2) the funding source only or 3) the funding source and CoI. We obtained ethics approval from the Institutional Review Board of Paris Descartes University, Paris, France (no. 2012-A00032-41), and the protocol is registered at ClinicalTrials. gov (NCT01679873). The study was funded by a grant from the Fondation pour la RechercheMédicale (EquipeEspoir de la Recherche, 2010). The funders were not involved in the study design; data collection, analysis, or interpretation; the writing of the article; or the decision to submit for publication.
Exclusion criteria were investigation of nonpharmaceutical treatments (that is, medical devices, patient education), equivalence or noninferiority trials, safety trials, trials assessing different pharmacological procedures, and abstracts reporting a negative or neutral conclusion. One researcher (CB), who is an assistant professor in primary care, screened all retrieved abstracts and selected abstracts following these inclusion criteria. In cases of doubt regarding the inclusion of an abstract, a second researcher (IB) evaluated the abstract to achieve consensus. From the selected reports, the reviewer systematically extracted the industry funding source and all authors' financial CoI. If these data were not reported in the abstract or full-text article, the abstract was excluded. Of the 2,797 citations screened, reports of 75 RCTs were selected [see Additional files 2 and 3].
Abstract construction The abstracts for all selected RCTs were standardized and modified. The journal name, date and registration number at ClinicalTrials. gov were deleted. Authors' names were substituted by names randomly selected among the 200 names most common in the United Kingdom [see Additional  file 4]. Treatments were referred to as 'experimental treatment A' or 'experimental treatment B'. Acronyms used for the study were deleted and dates in the text were modified to avoid trial recognition. Furthermore, each abstract was translated into French. As a quality procedure, three GPs read all abstracts to ensure the quality of the translation and the relevance of the abstracts for GPs. The abstract for each RCT was reported in three formats as follows: -Abstract with no mention of the funding source or CoI.
15%, 96. 97% and 98. 87% for the same samples respectively. Concentration-time data were analysed by use of the first-order conditional estimation method with interaction of the non-linear mixed effects modelling program NONMEM (version VI, version 2. 0, double precision)  [13, 15]. Three structural PK models (one, two, and three compartment models), with first-order absorption and first-order elimination from the central compartment were investigated. The estimated pharmacokinetic parameters were the absorption rate constant (ka), the apparent elimination clearance (CL/F, F being the bioavailability), the apparent central distribution volume (Vc/F) and, if relevant, apparent peripheral distribution volumes (Vp/F for a 2-compartment model, Vp 1 /F and Vp 2 F for a 3-compartment model) and distribution clearances (Q/F for a 2-compartment model, Q 1 /F and Q 2 /F for a 3-compartment model).
A covariate was retained in the model if it produced a minimum decrease in the objective function of 3. 64 units (P =0. 05, 1 degree of freedom) and if its effect was biologically plausible. An intermediate multivariate model that included all selected covariates was then obtained. A covariate was retained in the final multivariate model if its deletion from the intermediate model led to a 6. 63-point increase in the objective function (P =0. 01, 1 degree of freedom). At each step, the goodness of fit was evaluated by use of a graph of the weighted residuals versus time after administration of the dose (time) or versus the predicted concentrations. Normalized predictions errors (NPDE) versus time and predicted concentrations were used to assess the lack of bias of the final model. NPDE are computed as the quantiles of the observations in the predicted distribution, obtained for each observation by simulating 1000 datasets using the model and the design of the original dataset.
The computation also involves a decorrelation step to account for the correlation induced by the multiple observations within one subject. The distribution of the NPDE under the assumption that the model describes appropriately the observed data is the standard Gaussian distribution, and graphs of NDPE versus time and versus predicted concentrations can be used to evaluate this assumption  [16]. The accuracy and robustness of the final population models were assessed by a visual predictive check. The final population model parameters were used to perform 1000 simulations of the database. The 5 th and the 95 th percentiles as well as the 50 th (median) of simulated concentrations were plotted against observed concentrations. Bayesian estimates of the individual pharmacokinetic parameters (obtained in NONMEM output) were used to calculate individual MQ elimination half-life, the individual area under the curve from time zero to infinite (AUC), and MQ concentration at D7 (C7) and D28 (C28).
Acknowledgements Clinical trials were monitored by  GVK (India) , and the bio-analytical determinations were performed by  Sitec Labs, Mumbai (India). We thank the following for their contribution in conducting the clinical study:  N G Dubhashi  ( Goa Medical College and Hospital, Bambolim ),  B H Krishnamoorthy Rao  ( Wenlock District Government Hospital, Mangalore ),  Ashwani Kumar  ( National Institute of Malaria Research -Field Unit, Panjim ),  S K Ghosh  ( National Institute of Malaria Research, Bengaluru ),  Jai Prakash Narayan Singh  and  A P Dash  (both of  National Institute of Malaria Research, New Delhi ). We thank patients for participating in the study and the local health personnel who contributed to the study execution, and acknowledge the assistance of  Susan Wells  (DNDi) in editing the manuscript.
Nanoparticle uptake/binding For NP-uptake/binding studies, we first tested dye-loaded NPs on the RBE4 cells. For this, NPs without Ps80 coating (Dye NPs) and with Ps80 coating (Dye NPs + Ps80) were incubated in different concentrations of 40, 4 and 0. 4 µg/ well. The cells were incubated at 37°C for 120 minutes followed by cutting of the insert membranes, fixing the cells, and mounting on slides. Fluorescence microscopy and intensity analysis: Fluorescence photomicrographs were taken using a DMI 6000 B microscope (Leica Microsystems, Wetzlar, Germany) using Leica Application Suite Advanced Fluorescence software. Pictures were taken with a 2. 5× optical zoom lens objective using an L5 blue excitation filter (450±64 nm) with a pixel resolution of 1,392×1,024.
Acknowledgments This study was supported by  European regional development funds of the European Union  funded through the  Foundation of Polish Science  (grant  MPD4-5071 ). Also, we would like to thank the  Laboratory of Electron Microscopy at Nencki Institute  for their help. YM acknowledges the support of the  French National Research Agency (ANR ;  VECtoBrain  project). MK acknowledges support from the  National Center for Scientific Research (CNRS) ,  Aix-Marseille Université (AMU) , and grants from the  ANR (TIMPAD, VECtoBrain , and PREVENTAD). Finally, we would like to thank  COST Action ECMNet  ( BM1001 ) for providing STSM fellowship for MC's stay in UMR 7259 -CNRS Marseille, France.
Data analysis Data are reported as mean ± standard deviation or standard error of the mean. The response curves were fitted and analyzed using the sigmoid dose-response function of a computerized graphics and statistics software package (Graph-Pad Prism, version 4. 0, 2003, Graph-Pad Software Inc. , San Diego, CA, USA). The dose-response curves were fitted using a fourparameter log-logistic model. Statistical comparisons between parameters of fitted curves (EC 50 and maximal Table  5  The EC 50 and maximal transcriptional activity of the traditional Chinese medicine (TCM) and its 18 components that were determined in the HELN-ERα and HELN-ERβ cell lines The EC 50 values of the herbal medicine and the 18 components are expressed as percentages and correspond to dilutions of the TCM or component (1% = 100-fold dilution).
Proscillaridin A reduces tumor growth in vivo To highlight in vivo anti-tumoral effect of proscillaridin A on GBM development, we first achieved preliminary experiments on healthy nude mice in order to set up a treatment protocol. Briefly, daily doses (range: 0. 5-20 mg/kg body weight) were evaluated for 7 days to exclude lethal doses. In this way, the dose of 7 mg/kg body weight was determined as the maximum tolerated dose in mice, and then kept for all the treatments applied in this study. At that dose, treatment was generally well tolerated as evidenced by an absence of weight loss or change in animal well-being as compared with vehicle (Dimethyl Sulfoxide (DMSO)) -injected mice (data not shown). For GBM6 subcutaneous tumors, 5 mice were treated with proscillaridin A and 5 control mice were injected with vehicle from 4 to 8 weeks after cells injection.
The ATP1A1 transcript was analyzed by RT-qPCR using a LightCycler ® 480 and the LightCycler 480 SYBRGreen I Master (Roche Applied Science, Meylan, France). Ribosomal 18S and glyceraldehyde-3-phosphate-dehydrogenase (GAPDH) were used as reference genes. Forward and reverse primers for each transcript were designed using Primer express 3. 0 software and are listed below: ATP1A1: 5a-tcgtcagtatcgtggtggtg-3a, 5a-gggcagtaggaaaggaaagc-3a; 18S: 5a-ctaccacatccaaggaaggca-3a, 5a-tttttcgtcactacctccccg-3a; GAPDH: 5a-caaattccatggcaccgtc-3a, 5a-cccactygattttggaggga-3a. PCR conditions were as follows: 5 min at 95°C, followed by 45 cycles of 15s at 95°C and 30s at 65°C, 67°C and 65°C for ATP1A1, 18S and GAPDH respectively. Efficiencies were calculated from the given slopes in the LightCycler 480 software using serial dilutions of human total RNA reference (Stratagene, Massy, France).
The reduced formazan was dissolved in DMSO and absorbance was measured at 562 nm with an Elx800 microplate reader (Bio-Tek, France). The cell viability was expressed as a percentage as compared to DMSO control cells. A concentration of proscillaridin A required to inhibit 50% of cell viability after 72h of drug incubation (IC 50 ) was deduced for each cell line using CalcuSyn software. The experiments were carried out 3 times in triplicate.
DNA fragmentation and cell cycle analysis DNA fragmentation and cell cycle analyses using flow cytometry (FACS Calibur, BD Biosciences, Le Pont de Claix, France) were performed by propidium iodide (PI) staining. GBM cells were seeded at 150 000 cells/ well into previously poly-DL-ornithin-coated 6-well plates (GBM6 and GBM9) or not (U87-MG and U251-MG) and treated with IC 50 concentration of proscillaridin A or DMSO for 72h. Cells were trypsinized and resuspended into 0. 1% trinatriumcitrat-dihydrat pH 7,4, 0,1 % triton X10 and 100 μg/ml PI for at least 2h on ice. A total of 10 000 events were counted for each sample. Results were harvested with the CellQuest Pro Software (BD Biosciences) and analyzed using FlowJo software choosing the Dean-Jet-Fox model analysis.
ACKNOWLEDGEMENTS This work was supported by  Institut National Contre le Cancer  grant ( INCa-DGOS-Inserm 6038 ) and  PACA Canceropole  and also funded by the  Groupement des Entreprises Françaises dans la Lutte contre le Cancer (GEFLUC). E. Denicolaï  is supported by the  Association pour la Recherche sur les Tumeurs Cérébrales (ARTC-Sud). We would like to thank  M. Cayol  for mice handling,  F. Frassineti  for paraffin sections as well as  R. Berges  and  P. Weber  for technical advices. Pr JF Pellissier  is specially acknowledged for his expertise in electron microscopy analyses.
Recombinant protein production The plasmid (pGST-GFP (GenBank JN232535. 1)) has been described in detail previously  (Urbanowski and Piper, 1999)  and was a kind gift from Professor Robert Piper (University of Iowa, USA). For protein expression, pGST-GFP was transformed into E. coli MC1061 (Invitrogen, Paisley, UK) and grown overnight (to saturation) in 2xYT media containing 25 mg/ml ampicillin with or without deuterium oxide in place of water. The latter was used to produce partially deuterated protein. The saturated 10 ml overnight culture was used to inoculate 1000 ml of 2xYT media containing 25 mg/ml ampicillin, which was grown at 37 C shaking at 180 rpm for 4 h. Gene expression was induced by adding IPTG (1 mM), and continuing to incubate the culture for a further 4 h at 37 C shaking at 180 rpm.
Assessment of particle composition using small angle neutron scattering (SANS) SANS experiments to assess the diameter of the silica and silicaadsorbed protein (Section 2. 4) were performed on instrument D11 (lowest momentum transfer and lowest background instrument) at the Institut Laue -Langevin, Grenoble, France. The scattering was measured in 2 mm Hellma cells placed within a rotating rack, to obviate the slow settling that occurs within these systems. Three sample detector distances (1. 2, 8 and 39 m), with appropriate collimation, were employed, using incident neutrons with wavelength 8 Å. Data were normalised by reference to a flat scatterer (1 mm H 2 O at ILL, flood source at ISIS) and then adjusted to absolute scattering cross sections by reference to a standard sample. The data describing the myristic acid coated, antigen adsorbed silica (Section 2.
The variance from the in silico data (from GenBank JN232535) is very likely due to GST-GFP missing the Nterminal methionine and the 69 C-terminal amino acids, which would give a mass of 53,600. 00 Da versus the observed mass of 53600. 22 Da. Given that the missing portion of the protein was derived from Plasmodium spp. , rather than from GFP, the omission was deemed of no consequence to this study. The fluorescence emission spectrum of GST-GFP was identical to the published spectra of GFP  (Pollok and Heim, 1999)  (data not shown).
2 ), requiring both deuterated and hydrogenated GST-GFP. Contrast variation allowed the relative scattering from the core particle and protein coat to be independently varied. The multiple datasets were then simultaneously fitted to a single parameterised model to greatly increase the delineation of the quantities returned in the fitting. Taken together, the SANS data has shown that the protein coated silica particles appeared discrete, (i. e. not aggregating), with a corona of adsorbed protein measuring 120-160 Å (12-16 nm). The absolute intensities are entirely consistent with these dimensions and the known composition of the system, suggesting a water content within the protein layer of some 30-40% (w/v). The thickness of the protein layer is approximately double the theoretical GST-GFP radius of gyration (8.
3 (panel b )). After myristic acid coating, protein remained adsorbed to the silica surface at pH 3. 6 and pH 5 and was released at pH 8. 8 (7% (w/v) after 2 h at 37 C (Fig. 4  (panel a)). Released protein was Fig. 2. Fig. 2  shows the characterisation of the VDS described herein by SANS. Panel (a) defines a series of contrast matching experiments used to define the protein corona adsorbed onto the silica particles. Panel (b) records the SANS data and "mathematical fits" i. e. a core-shell model,  (Guinier and Fournet, 1955)  describing the experiment previously outlined (in panel a). Panel (c) describes the SANS experiment designed to measure the extent of protein coating, utilising both deuterated and hydrogenated GST-GFP. Panel (d) describes the SANS data and the associated modelling of the "mathematical fit" that best describes the diameter of the VDS after myristic acid coating using 437 mM of myristic acid/g silica.
These data describe a particle with mean diameter 6600 AE 290 Å and a protein corona of 120-160 Å. The myrisitic acid may be measured as a disordered phase approximately 20 Å deep extending beyond the protein corona. 4  documents the release of GST-GFP from VDS in response to pH. Panel (a) records release over 24 h. Protein detection was performed by immunoblotting using an anti-GFP polyclonal primary antibody. As was recorded, protein was released from the VDS into the supernatant at pH 8. 8 after 2 h. Panel (b) shows protein release from the VDS at pH 8. 8 over 24 h. These data show approximately 15% protein release from the myristic acid coated protein (1 mM myristic acid/g silica) adsorbed silica. Fig. 4 (panel c ) shows the CD spectra from: protein released from protein-adsorbed myristic acid coated silica (--), the native, unformulated protein (GST-GFP) (.