dataesr/scientific-paragraphs-categorization huggingface dataset:
Background: A better understanding of the ecology and spatial-temporal distribution of malaria vectors is essential to design more effective and sustainable strategies for malaria control and elimination. In a previous study, we analyzed presence-absence data of An. funestus, An. coluzzii, and An. gambiae s. s. in an area of southern Benin with high coverage of vector control measures. Here, we further extend the work by analysing the positive values of the dataset to assess the determinants of the abundance of these three vectors and to produce predictive maps of vector abundance. Methods: Positive counts of the three vectors were assessed using negative-binomial zero-truncated (NBZT) mixed-effect models according to vector control measures and environmental covariates derived from field and remote sensing data.
s. ) in an area with high coverage of vector control measures  [13]. Here, we used positive values of the dataset (i. e. only when at least one vector was collected) to assess the determinants of the abundance of these three vectors when their presence was confirmed and to produce predictive maps. Then, we discussed similarities and differences between the environmental determinants of presence-absence (previous binomial models) and of abundance (the zero-truncated models produced here) to assess the pertinence of using this two-stage procedure.
funestus, An. coluzzii, and An. gambiae s. s. were assessed according to a set of environmental covariates using a negative-binomial zero-truncated (NBZT) mixed-effect model with nested random effects at the village and house levels. Environmental data used for the analysis are summarised in Table  1. Their definitions, sources and methods of production have been fully described in Moiroux et al. [13]. All covariates act at the village level except the distance from the collection houses to the village perimeter (house level). Meteorological data (rainfall, temperature), Normalized Difference Vegetation Index (NDVI), terrain data (elevation, slope, count of sinks, theoretical flow accumulation), land cover data, and soil data derived from satellite images or maps were averaged in a 2-km radius buffer zone defined around each village.
Domestic breeding site data and covariates describing attractiveness and penetrability for malaria vectors (number of neighborhoods, population density, distance from the collection houses to the perimeter, and spin and depth indices) were produced at the village perimeter scale. Village perimeters were extracted by on screen digitalization using visual interpretation of the Satellite Pour l'Observation de la Terre (SPOT) image used to produce the land cover map  [13]. We used the 'R' software  [22]  and the additional 'glmmADMB'  [23]  package for the analysis. The selection process of the covariates was the same as that described in  [13] :  (1)  univariate selection of the continuous and stratified covariates, (2) analysis of collinearity, and (3) backward selection of the selected covariates in multivariate models.
The models were adjusted for the vector control intervention and the collector's position (indoor or outdoor). The structure of the final multivariate models was evaluated by 8-fold cross-validation with the data of each survey successively used for validation. The procedure involves (1) re-fitting the selected statistical models to a subset of the dataset which excludes, in turn, data from each of the 8 surveys (training data), and (2) comparing the predictions of the model to each of the excluded datasets (validation data). Our model's ability to estimate the spatiotemporal pattern of malaria vector abundance was assessed by graphically comparing the model predictions to the observed number of Anopheles. Moreover, to compare the predictive performance of our models, we calculated the relative error of the predictions (REP) in each village during each survey.
Results In the 19 villages during 2,432 human-nights of collection, 2,379 malaria vectors were collected: 1,091 were An. funestus, 1,063 were An. coluzzii, and 225 were An. gambiae s. s. Over 1,216 catches (two human-nights per site per survey), 252, 323, and 114 were positive for An. funestus, An. coluzzii, and An. gambiae s. s. , respectively and were used for the NBZT analysis. An. funestus, An. coluzzii, and An. gambiae s. s. were collected in 15, 19, and 17 of the 19 villages, respectively. Details about entomological data (spatial coordinates of the villages, proportion of catch positives for each species, and numbers of vectors collected per villages) are available in  [13]. Covariates that were kept in the final multivariate NBZT models, their incidence rate-ratios and 95% confidence intervals are presented in Table  2  (An.
We also observed a negative correlation between the abundance of An. coluzzii and the edge density of herbaceous landscapes. This observation may reflect a barrier effect of edges between open and closed landscapes against the dispersal of An. Coluzzii, as 84% of herbaceous landscape edges were common with shrubs or trees strata (data not shown). Indeed, low dispersal distances were previously observed in An. gambiae in forest areas  [30]. This difficulty to move in closed landscapes could explain the low vagility of An. coluzzii compared to An. gambiae s. s. as reported in Cameroon  [31]. An. gambiae s. s. abundance was negatively correlated with the nocturnal temperatures recorded during the week of the catch. Because people have trouble sleeping under a net on hot nights  [32, 33] , they are more likely to use bednets when nocturnal temperatures are low  [34]  and fewer hosts are therefore available for vectors.
Acknowledgements We thank populations of the villages for their kind support and collaboration. We also thank all the  field and laboratory  staff for their strong commitment to this project. We thank the French ministry of foreign affairs through the  SCAC programme and IRD  for their financial support. NM thank  Mr François Lacoste  and  Mrs Paule Hamploy  for their financial support. This study was partially funded by  EU  grant  FP7-261504  EDENext and is catalogued by the  EDENext Steering Committee as Edenext202  (http://www. edenext. eu). The contents of this publication are the sole responsibility of the authors and don't necessarily reflect the views of the European Commission. We thank the  ISIS programme of CNES  for providing us the SPOT image.
Fluo-4-AM loaded P. falciparum merozoites were treated with cAMP or Ca 2+ modulating agents and transferred from IC to EC buffer. Fluorescence signal from Fluo-4 in merozoites under different conditions was measured by flow cytometry using FACSCalibur (Becton Dickinson, USA) and analyzed using CellQuest software. Briefly, Fluo-4-AM loaded merozoites were excited at 488 nm and fluorescence signal was detected with a 430 nm/30 nm band pass filter for periods of 2-3 mins. Merozoites were gated on the basis of their forward scatter and side scatter. The mean fluorescence intensity (MFI), which reflects cytosolic Ca 2+ levels in merozoites, was plotted against time using FlowJo software. Erythrocyte invasion assay by P. falciparum merozoites P. falciparum merozoites isolated as described above were either mock-treated or treated with 50 mm KH7 (Calbiochem, USA), 100 mm ACTZ (Sigma, USA), 25 mM ESI-05 (Biolog, Germany) or 25 mM ESI-09 (Biolog, Germany) for 15 min at 37uC, washed with IC buffer, resuspended in EC buffer and incubated with erythrocytes in EC buffer at 37uC under mixed gas environment for 2 h to allow invasion.
The research leading to these results has received funding through a  Program Support Grant  from the  Department of Biotechnology (DBT), Government of India  and the  European Community 's  Seventh Framework Programme  ( FP7/2007-2013 ) under grant agreements No 242095 (EVIMALAR) & 223044 (MALSIG). GL acknowledges INSERM,  CNRS  and  Labex ParaFrap   ANR-11-LABX-0024  for support. SS is a recipient of an  Innovative Young Biotechnologist Award  (IYBA) from  DBT. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Data Management and Analyses Data were entered in Epidata freeware (www. epidata. dk, Odense, Denmark) and cross-checked against original data sheets. Analyses were carried out with Stata software. Chi 2 or Fisher's exact test were used to assess associations between categorical variables as appropriate, and Student's t-test for two normally distributed continuous variables. P#0. 05 was considered significant. Associations with the willingness to recommend condom use by religious leaders were initially measured using univariate analysis for different variables (age, sex, years in the position, education, specific training on HIV, information source, knowledge on HIV and STI transmission and prevention, previous contact with PLHIV, Church denomination). Multivariate analyses was then conducted introducing into the model the variables significantly associated with condom recommendations with p-values ,0.
Acknowledgments This work was part of a master's study by '' Institut Francophone pour la Medecine Tropicale'' (IFMT, Vientiane, Laos). We thank IFMT teachers for their help. We thank the Malagasy national and regional health authorities and  Julio L-C Rakotoniana  for their support. We thank  Percy Aaron  and  Leila Srour  for kind editing,  Sophie Goyer  and  Laurent Ferradini  for helpful advices. We thank all the people who participated in the surveys. We thank  Monseigneur Samoela Jaona Ranarivelo ,  Pastor Perline Cooper , Pere  Ratsimbazafy Jean Simon ,  Dr Andre  ´Richard, for facilitating the relationship with the church leaders linked to FFKM. We thank  IFMT  for their financial support.
Statistics Continuous variables were expressed as median [25th to 75th percentile] and were compared using the nonparametric unpaired test (Mann-Whitney test) or the non-parametric paired test (Wilcoxon rank test). Statistical significance was set at P <0. 05. The Cohen kappa coefficient is the gold standard to assess agreement of qualitative data and is often used for pairwise comparison of sleep scoring  [25]. A kappa coefficient >0. 8 is indicative of excellent agreement and of good and reasonable agreement when it is between 0. 61 to 0. 80 and 0. 41 to 0. 60, respectively. To measure interscorer agreement for continuity parameters, we calculated the intraclass coefficient (ICC), an equivalent of kappa coefficient for quantitative data. For each patient, sleep continuity parameters were calculated from the two scorings.
Acknowledgements The authors deeply thank  Karoline Lode-Kolz  and  Ala Covali-Noroc  for reviewing the manuscript,  Francoise Zerah  and  Laurent Margarit  for technical support and  Jeffrey Arsham  for his review and editing of the original English-language manuscript on behalf of  CHU de Poitiers. This work was performed at APHP,  Hospital Henri Mondor , Creteil, France. Parts of these results have been presented in abstract form at the APSS annual meeting,  June 2013 ,  Baltimore MD ,  USA.
Ethics statement The protocol was approved by the ethic commitee ''Comite Ćonsultatif pour la Protection des Personnes se pretant ala Recherche Biomedicale'' (CCPPRB nu 1933) of Paris-Cochin Hospital, and the data protection board ''Commission Nationale de l'Informatique et des Libertes'' (CNIL nu 901230). Participants provided their written informed consent to participate in this study. The current analyses included 2,263 subjects for whom baseline PFA were available.
Assessment of PFA profile and data collected at baseline Data on gender, age, smoking status, existing hypertension, diabetes or dyslipidaemia, n-3 supplementation and medication use were collected at baseline via a questionnaire. Dietary intake (especially fish consumption) and alcohol consumption were assessed using a Food Frequency Questionnaire. Body mass index (BMI in kg/m 2 ) was calculated from the standardized measurements of height and weight. Blood pressure was recorded by trained staff for each patient in the sitting position, after a 5-min rest. Venous blood samples were drawn after at least a 5-hour fast. Measured biological parameters included cholesterol (total, LDL, and HDL) and triglycerides (measured by enzymatic method with the use of C8000 System Abbott, Rungis, France), fasting blood glucose concentrations (enzymatic method) and total homocysteine (measured by a competitive immunoassay with direct chemiluminescence detection).
Statistical analysis In each trial the effect size or the standardised response mean for continuous measures and ORs for dichotomous measures were determined to assess the magnitude of the treatment effect. Where possible, pooled effect size, pooled standardised response mean and pooled OR were calculated by meta-analysis, using the inverse of variance method. RevMan V. 5. 2 (Review Manager, Copenhagen, The Nordic Cochrane Centre, The Cochrane Collaboration, 2012) statistical software was used. Statistical heterogeneity was tested by Q test and I 2 test. All meta-analyses were carried out using random-effects models in cases of statistical heterogeneity.
After separation, UV spectra of the complexes in the aqueous phase were compared to those of the original aqueous solutions, and D 7. 4 values were calculated as the mean of [absorbance (original solution)/absorbance (aqueous phase after separation) -1] obtained in the region of λ ≈ (250-290 nm). Circular dichroism (CD) and UV-vis spectra under physiological conditions (0. 02 M phosphate buffer, pH 7. 40 with 0. 1 M KCl) were recorded on a Jasco J-815 spectrometer in an optical cell of 2 cm path length (l) in the wavelength range from 220 to 600 nm. The analytical concentration for the CD measurement of the complexes was 400 μM in aqueous solution. CD data are given as the differences in molar absorptivities between left and right circularly polarized light, based on the concentration of the ligand (Δε = ΔA/l/c complex ).
Ferrocene was used as an internal standard. Crystallographic Structure Determination. X-ray diffraction measurements were performed on a Bruker X8 APEXII CCD diffractometer. Single crystals were positioned at 40 mm from the detector, and 1348, 1526, 1100, 2183, 961, 2191, 1606, and 1391 frames were measured, each for 30, 30, 80, 20, 10, 60, 30, and 30 s over 1 (or 0. 5°for 4) scan width for 1-8, respectively. The data were processed using SAINT software. 26 Crystal data, data collection parameters, and structure refinement details are given in Tables  1  and 2. The structures were solved by direct methods and refined by fullmatrix least-squares techniques. Non-hydrogen atoms were refined with anisotropic displacement parameters. H atoms were inserted in calculated positions and refined with a riding model.
■ ACKNOWLEDGMENTS We thank  Alexander Roller  for collection of X-ray data and  Ricarda Bugl  for support in acquisition of the mass spectra. We are also indebted to the  Austrian Science Fund (FWF)  and the  Agence Nationale de Recherche (France)  for financial support of the bilateral Project  I374-N19  and  ANR-09-BLAN-0420-01  (VILYGRu), respectively. The  PHC Amadeus and OEAD  (Project No. FR01/2012 ), as well as the  Hungarian Research Foundation   OTKA 103905  are also acknowledged for their support.
Ethics statements Experimental infections involving human subjects were approved by the Cameroonian National Ethical Committee (statement 099/CNE/SE/09). Children identified as gametocyte carriers were enrolled as volunteers after their parents or legal guardians had signed an informed consent form. Collection of human blood on filter papers was approved by the National Ethics Committee of the Senegal Ministry of Health (October 2008; 0084/MSP/DS/CNRS, ClinicalTrials. gov ID: NCT01545115). Oral and written informed consent was obtained from the children's parents or legal guardians.
Fragment ions generated by CID were detected at the linear trap. Normalized collision energy of 35 eV and activation time of 30 ms were used for CID. All Spectra were recorded under positive ion mode using the Xcalibur 2. 0. 7 software (Thermo Fisher Scientific). Spectra were acquired with the instrument operating in the informationdependent acquisition mode throughout the HPLC gradient. The mass scanning range was m/z 400-2000 and standard mass spectrometric conditions for all experiments were: spray voltage, 2. 2 kV; no sheath and auxiliary gas flow; heated capillary temperature, 200°C; capillary voltage, 40 V and tube lens, 120 V. For all full-scan measurements with the Orbitrap detector, a lock-mass ion from ambient air (m/z 445. 120024) was used as an internal calibrant as described  [54].
All MS/MS spectra were searched for against the Insecta entries of either SwissProt or TrEMBL databases (http:// www. uniprot. org/; v 2012_07) using the Proteome Discover software v 1. 3 (Thermo Fisher Scientific) and Mascot v 2. 3 algorithm (http://www. matrixscience. com/) with trypsin enzyme specificity and one trypsin missed cleavage. Carbamidomethylation was set as fixed cystein modification and oxidation was set as variable methionine modification for searches. A peptide mass tolerance or 5 ppm and a fragment mass tolerance of 0. 5 Da were allowed for identification. Management and validation of mass spectrometry data were carried out using Proteome Discoverer software v 1. 3 (p < 0. 01 for 2 peptides or more/protein).
Peptide design The design of potential immunogenic peptides was investigated using an in silico approach. The putative B-cell epitopes were identified with the BcePred  [55] , ABCpred  [56] , BepiPred  [57]  and SVMTrip databases  [58]. The sequences were aligned with the Blastp program in the Vectorbase database  [59]  and the UniProtKB database to compare the peptide sequences with known genomes or EST libraries. The peptides were selected when at least three to four algorithms predicted the same epitopes.
Peptide design and antigenicity of selected peptides as potential candidate biomarkers Aiming to optimize Anopheles specificity and to circumvent the limitations in the production of recombinant protein and batch-to-batch variations, peptides from the four previously selected proteins were designed (the gSG1b, long form D7, SG5, TRIO proteins) so as to assess their antigenic properties. Bioinformatic tools were used to predict potential epitopes for each protein. The comparison of data generated by the four algorithms defined two peptides for gSG1b (gSG1b-P1 and gSG1b-P2), seven peptides for long form D7 (D7-P1 to D7-P7), five peptides for SG5 (SG5-P1 to SG5-P5) and two peptides for the TRIO protein (TRIO-P1 and TRIO-P2), 18-27 amino acid residues long (Table  3 ). All these peptides were aligned using the Blastp program in Vectorbase to search for similarities with other hematophagous arthropods and the Blastp program in UniProtKB to search for similarities with human infectious organisms, to avoid immune cross-reactivity.
Acknowledgments We thank  M. N. Lacroix  at  Laboratoire de lutte contre les insectes nuisibles (Montpellier, France ) for the mosquito collection. We are grateful to volunteers from Mfou primary schools and their parents or guardians for participating in this study, to the medical team from the Mfou hospital for assistance in the field, and to the technical staff of the OCEAC for P. falciparum infections. We are particularly grateful to  Etienne Onana  from the OCEAC for mosquito rearing and salivary gland dissections. We acknowledge  J. P. Brizard  at the  UMR 5096  ( IRD ) for his advice on the proteomic experiments. We thank  Linda Northrup  for the English revision of the manuscript. This work was funded by the  Institut de Recherche pour le Développement (IRD)  and the  European Community's Seventh Framework Programme (FP7)  (grant agreement No.
Measurement of clinical effectiveness or harm 11a Single study-based estimates: Describe fully the design features of the single effectiveness study and why the single study was a sufficient source of clinical effectiveness data The effect of treatment should be assessed on the core set outcomes for rheumatology studies (pain, functional ability [using a validated disease-specific QoL instrument] and patient global assessment [PGA]). Adverse events should be reported using the OMERACT common toxicity criteria. 11b Synthesis-based estimates: Describe fully the methods used for the identification of included studies and synthesis of clinical effectiveness data Relevant outcome measures should be selected using the GRADE system.
Thus, the design of the study should be outlined, e. g. , whether it was an RCT or pragmatic design or if it was a data extraction from a general practice database or a mathematical model synthesising data from several sources including meta-analyses. As stated in item 11 of CHEERS, attention should be paid to fulfilling other applicable reporting requirements (CONSORT for RCTs and pragmatic designs  [32, 37] ; STROBE for observational designs  [38]  and PRISMA for metaanalyses  [39] ). Although the use of a single RCT as a data source for economic analysis may be questionable  [40] , the data obtained from such studies can be instructive on an initial basis for decision making especially during early clinical drug development. If the analysis concerns modelling of economic data, then the model structure, as outlined in item 15 of CHEERS, should be detailed, taking account of existing good practice guidelines  [41, 42].
It is important that any adverse effects are accurately captured by the QoL measure. Not often measured as an outcome parameter, given the relatively short duration of most clinical studies, mortality data should be obtained in retrospective observational studies and, separated where possible into OA-related death and non-related, used to populate models having lifetime horizons. There are no validated surrogate end points in OA. Proposed definitions of "time to treatment failure" or "need for joint replacement surgery" based on the structural changes and symptomatic thresholds have been made; however, a convincing algorithm that combines the various components has yet to be found  [63]. A validated surrogate end point could prove critical for the development of DMOADs, since their economic attractiveness will be in delaying this end point.
Study Quality We adopted an approach similar to that used by the Cochrane Collaboration to develop a standardised quality assessment form for assessing the risk of bias in randomised studies  [14]. We identified items within three quality domains to reflect the potential for selection bias, misclassification of receptor status, and availability of data on key correlates of receptor status. A list of items for each one of the three domains was developed. For each item, papers were allocated a score ranging from 0 (if it did not meet the criteria or if the information provided was unclear) to a maximum of 2 or 4, depending on the item, with more weight given to items in the selection bias and misclassification domains. Items in the selection bias domain included study design/case selection (score 0 if unclear; 2, if opportunistic case series; 4, if consecutive or population-based case series) and percentage of patients with known receptor status (score 0, if unclear; 2, if , 70%; 4, if $70%).
The proportion of ER+ tumors varied markedly between studies, ranging between 0. 40 and 0. 80 in North Africa and between 0. 20 and 0. 70 in sub-Saharan Africa. Among prospectively collected samples (samples collected specifically for receptor-status testing; studies that determined the receptor status of breast cancers using stored samples reported a lower proportion of ER+ disease than studies that used prospectively collected samples), the overall pooled proportions of ER+ and triple negative tumors were 0. 59 and 0. 21, respectively. What Do These Findings Mean? Although these findings highlight the scarcity of data on hormone receptor and HER2 status in breast cancers in indigenous African populations, they provide new information about the distribution of breast cancer subtypes in Africa.