dataesr/scientific-paragraphs-categorization huggingface dataset:
Asterisks refer to a significant difference (*p < 0. 05, **p < 10 -2 ). In brackets, the number of mosquitoes tested. The map was created using software the CorelDraw X5 software (http://www. coreldraw. com/br/). to the mosquito salivary glands. Interestingly, AL-GOI was less susceptible to YFV than the other two mosquito populations. Like Ae. aegypti, Ae. albopictus were similarly susceptible to the former YFV 74018-1D lineage and the new viral lineage 4408-1E (Table  3 ). Aedes mosquitoes from an African YFV-endemic country were similarly susceptible to American as well as African YFV genotypes. To test whether Ae. aegypti and Ae. albopictus from Congo were competent for both Brazilian and West African YFV strains, mosquitoes were infected with the three YFV strains. The population AE-CON and AL-CON showed IR ranging between 25% (when infected with 74018-1D) and 38.
Mosquitoes were exposed to blood meals at a titer of 10 6 PFU/mL. Engorged females were maintained in laboratory conditions until days 14-21 post-infection. Mosquitoes were processed as previously described to calculate the infection rate (IR), the disseminated infection rate (DIR) and the transmission rate (TR). Asterisks refer to a significant difference (*p < 0. 05, **p < 10 -2 ). In brackets, the number of mosquitoes tested. The map was created using software the CorelDraw X5 software (http://www. coreldraw. com/br/). that transmission implicates urban vectors, mainly Ae. aegypti. Imported cases from Angola were later confirmed in China  33  stressing the risk of spread outside Africa in Aedes-infested countries through non-immunized travelers. All four mosquito species, Ae. aegypti, Ae.
Statistical analysis. Rates (infection, disseminated infection, and transmission) were described using median and inter-quartile range (IQR). The effect of species, population, YFV strain and duration on the rates was investigated using logistic linear regression models. Two-by-two interaction between species, population, YFV strain and duration was systematically investigated. Statistical analyses were conducted using the Stata software (StataCorp LP, Texas, and USA). P-values < 0. 05 were considered significant.
38squito populations challenged with YFV. dechlorinated tap water, supplemented with yeast powder renewed every 2-3 days. In the case of Hg. leucocelaenus, we added senesced leaves besides yeast powder in water. We reared ~100 larvae/pan for Ae. albopictus and Ae. aegypti, and ~50 larvae/pan for Hg. leucocelaenus and Sa. albiprivus. The emerged F 0 adults were morphologically identified36maintained in insectaries (27 ± 1 °C; 80 ± 10% RH; 16 h:8 h light:dark cycle) and supplied with both 30% sucrose and/or honey solutions. Ae. albopictus,Ae. aegypti, and Sa. albiprivus females were fed three times a week on anesthetized mice to produce eggs. Mosquitoes were challenged with three YFV isolates: two belonging to the South America genotype I, isolated from Brazil, corresponding to two distinct lineages FIOCRUZ 74018/MG/01 (YFV-74018), isolated from a human fatal case in 2001, belonging to the lineage 1D37, and IEC-4408 (YFV-4408), isolated from a howler-monkey in 2008, from the lineage 1E (GenBank KY861728), and one strain [S79-P4 (YFV-S79)] from the West African lineage, isolated from a human case in Senegal in 197938.
Acknowledgements This study was funded by the  Institut Pasteur , the  French Government 's  Investissement. d' Avenir program ,  Laboratoire d'Excellence "Integrative Biology of Emerging Infectious Diseases " (grant  n°ANR-10-LABX-62-IBEID ) and the  PTR  (grant  n°528 ), the  CAPES-COFECUB  (grant  799-14 ), and the  FAPERJ-Fundação Carlos Chagas Filho de Amparo à Pesquisa do Estado do Rio de Janeiro  (grant  E-26/102. 351/2013-CNE ). We are grateful to  André Yébakima  as well as to  Tacilaine Divina Cardoso ,  Paulo Leite ,  Marcelo Santalucia ,  Tayssa Pereira dos Santos ,  José Bento Lima ,  Alessandro Romano  and  Cristiano Fernandes  for their help in collecting mosquitoes in Congo and Brazil, respectively. We also thank  Thais Chouin-Carneiro  and  Rosilainy S. Fernandes  for their assistance in the experiments, and  Heloisa Dinis ,  Leonidas Leite  and  Roberta Carvalho  for their help in making the maps.
Brain magnetic resonance imaging Brain MRI acquisition methods were previously described  [25]. Brain MRI acquisitions were performed on 1. 5 T (n = 47) or 3 T (n = 16) Philips systems. All subjects were scanned with a routine whole brain T1weighted 3D sequence. These images were acquired with a resolution of either: sequence 1: 0. 6 × 0. 6 × 0. 7 (interpolated) in sagittal plane (n = 10); sequence 2: 0. 94 × 0. 94 × 1. 00 in axial plane (n = 37); sequence 3: 0. 88 × 0. 88 × 1. 1 in sagittal plane (n = 16). Since there were three different MRI acquisition sequences, the MRI acquisition method was added as a covariable in the multivariate analyses. The different acquisition sequences were not statistically different in men and women and in patients with or without ELA. The segmentation of the hippocampus was performed using the fully automatic SACHA software  [43] [44] [45] [46].
Information on treatment for hypertension, diabetes and dyslipidaemia was also gathered. Collected lifestyle behaviours were smoking status and level of physical activity expressed as weekly energy expenditure in metabolic equivalent task minutes per week (METs min/week), based on self-reported data from the International Physical Activity Questionnaire (IPAQ)  [14, 15]. Specific inclusion criteria for this particular study were also defined. Flowchart of participants who met inclusion criteria were described (see Additional file 1: Figure  S1 ). First, 138 participants with non-reliable reporting in the FFQ and outlying values on nutrient intakes were excluded. Then, since relationships between dietary habits and CVRF may be biased by participants who had a serious cardiovascular event (n = 327) and/or who are under diet (n = 312), those individuals were excluded.
Formalization of cluster analysis Let X = (X 1 , …, X n ) be the dataset of n = 2298 individuals to be clustered where X i is a 45-dimensional vector containing the 45 standardized food group intakes of the i-th individual. A clustering algorithm A with a predefined number of cluster k constructs a solution Y of the data set X into k clusters (Y := A k (X)). This solution Y is represented by an n-dimensional vector of labels Y = (Y 1 , …, Y n ) where Y i = v if the i-th individual is assigned to cluster v (v ∈ {1, …, k}).
The measure of stability Cluster stability exploits the fact that when multiple datasets are sampled from the same distribution, the clustering algorithm is expected to behave in the same way and produce similar results. Based on this idea, Lange et al. introduced a stability measure computed on the comparison of solutions obtained on different datasets drawn from the same source  [8]. This stability measure was then compared across clustering methods and numbers of clusters to select the model associated with the most stable solution. Since this concept and its use in practice were previously described in detail  [8] , the method is only summarized below. Briefly, considering a solution Y := A k (X), the method consists in assessing its stability by randomly splitting the data X into two independent half sets X tr (training dataset) and X te (test dataset), and comparing the solutions obtained for these halves (Y tr := A k (X tr ) and Y te := A k (X te )).
However, since dataset X tr and X te are disjoint, clustering solutions are not directly comparable. To make these solutions comparable, a solution transfer mechanism allows extension of the clustering solution Y tr of the dataset X tr to the dataset X te. Technically, the training dataset (X tr ,Y tr ) is used to construct a classifier ɸ which is then used to predict label of individuals from the test sample X te. Consequently, the two clustering solutions A k (X tr ) and A k (X te ) are made comparable by comparing ɸ (X te ) and A k (X te ). The stability measure between the two solutions is then computed as the empirical misclassification rate  [8]. Lower misclassification rates indicate higher stability. In order to reduce the effect of random splitting, the algorithm was repeated 20 times and the estimates of stability for a given solution were computed as the average of the 20 corresponding estimates.
Description of dietary patterns According to the stability indices values, the optimal clustering method for describing dietary patterns in our dataset was K-means with a number of clusters equal to 3. Clusters were described with mean of daily food intakes relative to corresponding overall mean intake. Cluster names were assigned based on food groups with high consumption. Clusters were also presented according to nutrient intake, socio-demographic and lifestyle factors. Continuous variables were presented as mean ± standard deviation (SD). Since most of the variables describing food and nutrient intake were not normally distributed, differences across clusters were evaluated using Kruskal-Wallis test. Categorical variables were presented as percentages (%) and differences were tested by the Chi-square test.
However, it is highly likely that other more sophisticated methods would have been more appropriate  [3]. Indeed, clustering methods considered in this study were really simple and others methods with higher flexibility regarding cluster's characteristics are more likely to identify real complex structure. In addition, although K-means was found as the most appropriate method for describing dietary patterns in adults living in the Greater region, it may not be the case with other datasets. Indeed, group structures from other populations are likely to be different. Therefore, this should be explored in additional datasets across different populations. In the field of dietary pattern analysis, we are aware of only two studies comparing different clustering methods. Like us, Lo Siou et al. assessed stability of solutions obtained with different clustering methods and number of clusters and also showed that K-means was the most appropriate method  [3].
Availability of data and materials The data that support the findings of this study cannot be made publicly available for ethical and legal reasons. In fact, we are not authorized to share our NESCaV dataset with external researchers, as this condition had not been requested in the informed consent signed by the participants in 2007-2011. In addition, the NESCaV project is an interregional study that has been run in three different neighbor regions (Wallonia, Lorraine and Luxembourg). The current collaboration convention does not allow sharing the data with another party. However, any aggregated data in tables can be provided in case of request.
Image reconstruction The acquired data are reconstructed using k-Wave package  [22]. The echoes initially received by the linear probes are expressed in the Fourier domain and then resampled to beamform the image. The used sampling in the Fourier domain is defined by: k t 2 ½0; p=dt k x 2 ½0; cp=dx k ¼ ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi ffi k 2 t þ k 2 x q 8 > < > : ð4Þ where dt being the sampling time, dx being the lateral spatial sampling, c is the speed of sound, k t and k x are the temporal and spatial wave numbers. The focalisation of received echoes is processed by re-sampling the spectra. Hence, for each spatial line of the spectra, an interpolation is made from the k t axis on the modified k axis. This way, the echoes are focused and a better reconstruction from PA signals as compared to the delay-and-sum algorithm is obtained  [22].
Discussion The imaging performance of CMUT and PZT probes was quantitatively assessed and compared in a PA experimental set up. In vitro images of custom designed bimodal phantoms were achieved using four different CMUT and PZT probes and two US scanners. By using the proposed calibration procedure, the data acquired with the two different scanners were made comparable. The characterization in pure reception showed that the CMUT probes, which are both provided with high-input-impedance voltage buffers integrated in the probe handle, exhibit a low-pass frequency response, resulting in an increased sensitivity at lower frequencies and a greater fractional bandwidth as compared to the PZT probes. Moreover, the CMUT ACULAB probe showed an increased peak sensitivity as compared to the CMUT Vermon probe.
In fact, on each scanner, the SNR and CNR computed on the images reconstructed from the data acquired with the CMUT probe were higher. In the PVA phantom experiments, in particular, the detection and correct reconstruction of the coloured inclusion was possible only using the CMUT probe. The proposed study suffers from some limitations. First, to compare the signals received on the four probes, a calibration step has been conducted in a photoacoustic experiment. Based on a custom-built adaptor, it allows to acquired on a single US scanner the PA signals received on all probes. For the comparison between two probes, the acquisitions have been conducted on the same phantom. The position was not changed during the experiment and the laser excitation was set at the same location. However, note that for the comparison study we chose to keep connected the probes to their native scanners in order to get the benefits of the settings parameters adapted to each scanner.
Acknowledgments This work was supported by the  LABEX CELYA  ( ANR-10-LABX-0060 ) and  PRIMES  ( ANR-11-LABX-0063 ) of  Universitéé de Lyon , within the program " Investissements d'Avenir"  ( ANR-11-IDEX-0007 ) operated by the  French National Research Agency (ANR). The CMUT probe from Vermon was part of the program  ANR BBMUT of Université de Lyon. The CMUT probe from ACULAB was part of the collaborative research agreement between the  Department of Engineering of Roma Tre University and CREATIS, University of Lyon. This work was also partially supported by  ITN - FP7 OILTEBIA.
More recently, it appeared that 5-HT 6 R is involved in memory  (Meneses, 2014) , cognitive processes  (Benhamù et al. , 2014)  and regulation of food intake  (Heal et al. , 2011) , reinforcing its status as an emerging target for anti-dementia and anti-obesity therapeutic agents. According to the United States and European trial databases, more than 20 clinical studies of 5-HT 6 R are currently open or have been recently completed, evidencing that 5-HT 6 R antagonists have a symptomatic efficacy profile that can be differentiated from that of currently used agents (cholinesterase inhibitors and the NMDA-antagonist, memantine)  (Benhamù et al. , 2014; Claeysen et al. , 2015). Despite the fact that 5-HT 6 R functionality is much more complex than initially thought, it is now quite evident that this receptor has great pharmaceutical potential in terms of cognition enhancement.
To assess the reproducibility and specificity of the tracer, a test-retest reliability study was performed. Finally, the effects of pre-injection with the 5-HT 6 R antagonist SB258585 were investigated. All these experiments has the aim to demonstrate that the radiopharmacological profile of [ 18 F]2FNQ1P is suited to studies in human subjects, as 5-HT 6 R exhibits a high degree of interspecies homology between macaques and humans (present data and  Hirst et al. , 2000; Marazziti et al. , 2012 Marazziti et al. , , 2013;; Becker et al. , 2014).
k on. B avail /k off. So BP ND is linked to the available receptor density and the affinity of the radioligand for its specific receptor. As previous data from Parker and collaborators  (Parker et al. , 2012 (Parker et al. , , 2015) )  support the use of the cerebellum as a region of reference for high affinity 5-HT 6 R ligands, the cerebellum (excluding vermis) was used as the reference area for both models. Regional parametric values were obtained by modeling the mean regional kinetics, extracted in the native PET spaces with the MAXPROB method. Whole-brain parametric images were obtained by modeling kinetics at the voxel level. Parametric images were transformed to the common template space.
ACKNOWLEDGMENTS The authors wish to thank  J. -L. Charieau  and  F. Hérant  for expert animal care. The authors also thank  F. Lavenne  and  B. Vidal  for participation in data collection. This work was performed within the framework of the  LABEX PRIMES  ( ANR-11-LABX-0063 ) of  Université de Lyon , within the program " Investissements d'Avenir"  ( ANR-11-IDEX-0007 ) operated by the  French National Research Agency (ANR).
falciparum lactate dehydrogenase (pfLDH) gene. At delivery, demographic and clinical data were collected on mothers and new-borns. Information regarding reproductive history, current pregnancy, and infant health was also collected. Additional details of the studies have been published elsewhere and is summarized in Supplementary Information. Women in both studies were enrolled after obtaining signed informed consent. The current and parent studies were approved by institutional review boards at Institut de recherche pour le développement in France, Science and Health Faculty (University of Abomey Calavi) in Benin, Liverpool School of Tropical Medicine, Malawian National Health Science Research Committee, and University of North Carolina at Chapel Hill. All methods were carried out in accordance with the approved guidelines and regulations.
All sequences have been submitted to GenBank (GenBank accession numbers: MF061812-MF061963). Validation of Haplotype Determination. We conducted a validation study using pools of reference genomic parasite lines to ensure that our assay and clustering algorithm were appropriate and accurate. We mixed seven reference parasite lines (3D7, FCR3, 7G8, DD2, K1, RO33, and V1/S) from BEI resources (formerly known as MR4, Manassas, VA) in varying frequencies (1-50%) in five pools and subjected them to the above amplification and analyses pipeline. Details of mixture generation are in the Supplementary Information. We estimated the component parasite lines for each pool and their relative frequency. We then compared the "expected" results to de novo clustering and reference-guided clustering (determined by aligning individual sequencing reads to the known reference sequence for each strain ascertained by primer walking and Sanger sequencing done at Eton Biosciences, RTP, NC) to determine "observed" haplotype frequencies.
All measures of genetic relatedness and selection (F ST , PCoA, π, Tajima's D) were calculated in R using the adegenet  57  and PopGenome 67 packages. Phylogenetic trees were generated in MEGA6 using the maximum composite likelihood method where genetic distances were calculated through the Tamura-Nei model  68. The phylogenetic trees were bootstrapped 1000 times to compute branch support and provide precision in the clustering detected. Bootstrap values of greater than 80% were used as cutoff point to identify significant distinct clades. All phylogenetic trees were visualized using the APE package for R  69. Associations of VAR2CSA clade with delivery outcomes. We examined associations between clades and birth outcomes to identify pathogenic clades. Outcomes of interest were infant birth weight, LBW, and SGA.
Acknowledgements We thank  Stephen Rogerson  ( University of Melbourne ) and  Catherine R. Lesko  ( Johns Hopkins University ) for helpful discussion and  Sujata Balasubramanian  and  Stephanie Doctor  ( University of North Carolina ) for laboratory assistance. We also thank the field study team of the parent studies for their hard work. Ultimately, we are indebted to the women and infants who participated in the study. This work was supported by  National Institutes of Health  and the  National Institute of Allergy and Infectious Diseases  under award number  R56 AI106129 01A1  (to SRM) and by the  National Evolutionary Synthesis Center (NESCent) Evolutionary Medicine Fellowship  (to JCP). The trial in Malawi was supported by the  Malaria in Pregnancy Consortium , which is funded through a grant from the  Bill & Melinda Gates Foundation  to the  Liverpool School of Tropical Medicine  (to FOtK).
01 m (see Figure  1c, d ). Also, two values of the parameter t are considered, which means that the thickness of the ribs equals either 0. 2 or 0. 28. In all cases, the value of the rib length L was constant and resulted from the length of the side of a regular hexagon inscribed in the circle of radius equalling 1. On the basis of the length L and the angle α = 15 • , the dimensions of the cell L x and L y are calculated. All these values are collected in Table  1. All numerical calculations were performed by means of FEM software (Comsol Multiphysics, Stockholm, Sweden). The finite-element mesh consisted of over 29,000 triangle elements for the thickness of ribs equal to 0. 20 and over 40,000 for thickness equal to 0. 28 (maximum mesh element size was 0. 005). Optimization control variable shape functions were defined as bilinear Lagrange polynomials, while quadratic Lagrange polynomials were used as shape functions for displacement field components in-plane stress Navier's equation.
The value of the penalization parameter of the SIMP model is p = 3. Also, two values of the parameter t are considered, which means that the thickness of the ribs equals either 0. 2 or 0. 28. In all cases, the value of the rib length L was constant and resulted from the length of the side of a regular hexagon inscribed in the circle of radius equalling 1. On the basis of the length L and the angle α = 15°, the dimensions of the cell Lx and Ly are calculated. All these values are collected in Table  1. All numerical calculations were performed by means of FEM software (Comsol Multiphysics, Stockholm, Sweden). The finite-element mesh consisted of over 29,000 triangle elements for the thickness of ribs equal to 0. 20 and over 40,000 for thickness equal to 0. 28 (maximum mesh element size was 0.
In all cases, the value of the rib length L was constant and resulted from the length of the side of a regular hexagon inscribed in the circle of radius equalling 1. On the basis of the length L and the angle α = 15°, the dimensions of the cell Lx and Ly are calculated. All these values are collected in Table  1. All numerical calculations were performed by means of FEM software (Comsol Multiphysics, Stockholm, Sweden). The finite-element mesh consisted of over 29,000 triangle elements for the thickness of ribs equal to 0. 20 and over 40,000 for thickness equal to 0. 28 (maximum mesh element size was 0. 005). Optimization control variable shape functions were defined as bilinear Lagrange polynomials, while quadratic Lagrange polynomials were used as shape functions for displacement field components in-plane stress Navier's equation.
On the basis of the length L and the angle α = 15°, the dimensions of the cell Lx and Ly are calculated. All these values are collected in Table  1. All numerical calculations were performed by means of FEM software (Comsol Multiphysics, Stockholm, Sweden). The finite-element mesh consisted of over 29,000 triangle elements for the thickness of ribs equal to 0. 20 and over 40,000 for thickness equal to 0. 28 (maximum mesh element size was 0. 005). Optimization control variable shape functions were defined as bilinear Lagrange polynomials, while quadratic Lagrange polynomials were used as shape functions for displacement field components in-plane stress Navier's equation. The value of the penalization parameter of the SIMP model is p = 3. FEM together with the method of moving asymptotes (MMA) was used to find the optimal distribution of two positive materials in the composite.