dataesr/scientific-paragraphs-categorization huggingface dataset:
Glenton C, Colvin C, Carl se n B, Swartz A, Lewin S, Noyes J, Rashidian A. Barriers and facilitators to the implementation of lay health worker programmes to improve access to maternal and child health: qualitative evidence synthesis. Cochrane database of systematic reviews 2013, Issue 2. Art. No. : CD010414. doi: https://doi. org/10. 1002/14651858. CD010414.
Material and Methods Images are acquired with the clinac 23iX aS-1000 imager (Varian) and a 6MV beam. To compensate for the lack of uniformity of the detector response and to take into account the influence of the backscattered photons coming from the robotic gantry, a pre-treatment is applied to the portal images. A calibration step is then performed to transform the gray levels of the pixels into absorbed dose in water via a response function. Correction kernels are also used in this step to redistribute the absorbed dose according to the field size and to take into account the penumbra. The next step is the retro-projection of the dose into the patient for all EPID parallel plans with a 1 mm resolution, for each gantry angle. Our algorithm, developed with Matlab version R2015b takes into account the photons scattered into the patient, the attenuation, the beam hardening with depth, the build-up effect, and the beam's divergence into the patient.
Finally, the total dose is obtained by summing the 3D dose associated for each gantry angulation. The estimated dose from the EPID was compared to the one calculated by the TPS (Treatment Planning System) with a local and global gamma index of 3% and 3mm also developed with Matlab. Our algorithm has been tested for 20 IMRT and VMAT prostate and head and neck treatments in a homogeneous phantom (cylinder of 25 cm diameter).
Material and Methods The LINACs: 1) CLINAC 2100 with Millenium MLC with 6 MV and an EPID with 512x384 pixels, 2) Elekta Synergy with Agility MLC, 6 MV and EPID with 1024x1024 pixels. Field size used is 20x20 cm. A jig is made with a Bearing ball (BB) in its centre and 4 moving radiopaque discs. The jig is aligned with the crosshair light projection over the EPID, the discs are placed inside and tangent the light field. The moving discs allow to work with nominal field size and permit the images to be acquired in clinical mode and exported from the network easily. The images are analysed with an In-House Software (IHS): -Rotation correction of the image is performed (when angle > 0. 1º). -Radiation field limits are obtained with the 50 % pixel value (PV). -3 profiles parallel to every field edge are acquired.
The density of W is given by f GIG (x) = ψ χ λ 2 x λ-1 2K λ √ χψ exp - 1 2 χ x + ψx , (3. 7) where K λ denotes the modified Bessel function of the third kind. Observe that there exist different ways of parametrising generalised hyperbolic distributions and in our analysis we used the (λ, ᾱ, µ, Σ, γ) parametrisation. One can easily switch from (λ, χ, ψ, µ, Σ, γ) to (λ, ᾱ, µ, Σ, γ) by setting k = χ ψ K λ+1( √ χψ) K λ ( √ χψ) , ᾱ = √ χψ, Σ = kΣ and γ = kγ. The reparametrisation in the opposite direction can be done by setting ψ = ᾱ K λ+1 ( ᾱ) K λ ( ᾱ) and χ = ᾱ2 ψ , while the remaining parameters stay the same. We used the R package ghyp provided by  [Breymann, 2011]. We ranked distributions according to the Akaike information criterion (AIC) in ascending order, so the first one gives the best fit.
Data description Our set of wind production data corresponds to the spot and futures prices data, i. e. we used the data from five energy providers (four from Germany and one from Austria) between 1 January 2013 and 3 August 2015. The data were obtained from the websites: German Netztransparentz 3  and Austrian Power Grid 4. We were interested only in the global production, so we aggregated energy generated on-and off-shore as well as by all five providers. We also needed the global volumes of produced electricity, available on the EPEX SPOT website. All data were aggregated to daily values. In.
Comparison of models Measuring the model performance is a difficult task. We decided to compare the model without wind energy production data (Section 3) with different variations of the model including renewables data. We defined the distance between "true" (so resulting from the split described in Section 3) and simulated processes Y (t) as a sum of squared differences between first "true" moments and moments averaged from 1000 Monte Carlo simulations performed using the R package yuima (distance 1 ). We used different numbers of moments, from 3 to 20. Note that this definition closely resembles squared maximum mean discrepancy (see e. g. [Gretton, 2012] ) with the feature map φ(x) = x, x 2 ,. , x k , where k denotes the number of the highest moment, and a radial kernel. The squared differences were further normalised by the value of the appropriate "true" moment to reduce the influence of the large variability of higher moments on the total distance (distance 2 ).
Chromatographic data was developed using HP Chemstation software (Agilent, USA). A C18-ARII Cosmosil 5-μm C18-ARII column (150 × 4. 6) at 25 °C and a 5-μm C18-ARII pre-column (10 × 4. 6, Waters) were used for separation in the reverse phase. An isocratic method with a mobile phase consisting of 10 mM K 2 HPO 4, pH 5. 5, and methanol (15:85, v/v) was used. Samples of 50 μL were injected on the column every 30 min at a flow rate of 1 mL/ min. The wavelength for detecting S1P derivatives was 340 nm for excitation and 455 nm for emission. S1P concentration was calculated on the basis of the peak surface area of the internal standard C17-S1P.
Setting and participants Data collected by the Clinical Investigation Center Antilles-Guyane during a KABP study of HIV and migrants in 2012 was used. It consisted of a multicentric observational cross-sectional study carried out French Guiana. The target population was sexually active migrants in French Guiana in underprivileged neighborhoods in one of the 3 main cities -Cayenne, Kourou, and Saint Laurent du Maroni.
Data collection The data were collected from an anonymous structured questionnaire of 108 questions, translated into five languages (French, English, Portuguese, Spanish and Haitian Creole) and administered in an individual interview setting. After the interview, a prevention kit was provided that included male and female condoms, lubricant gel, an information brochure on HIV and STIs in the context of French Guiana, and a gift coupon to compensate for the time spent on answering questions. The study was based on BSS questionnaires produced by Family Health International and followed their criteria. This KABP study was delivered by trained local interviewers specialized in administering surveys to vulnerable populations.
Availability of data and materials There is no personal identification risk within this anonymized raw data, which is available after notification and authorization of the competent authorities. In France, all computer data (including databases, in particular patient data) are protected by the National Commission on Informatics and Liberty (CNIL), the national data protection authority for France. CNIL is an independent French administrative regulatory body whose mission is to ensure that data privacy law is applied to the collection, storage, and use of personal data. As the database of this study was authorized by the CNIL, we cannot make available data without prior agreement of the CNIL. Additionally, interested researchers may contact Mathieu Nacher with data accession requests at the following email address: mathieu.
This contributes to the reported great variability in vascular patterns of the CAM, in addition to other known effects such as temperature or stretch inhomogeneities in Supplementary Figure  3. The primary images were acquired with Stingray monochrome HD firewire camera from Allied Vision Technology (frame rate 15 Hz), or with a Basler CMOS monochrome HD USB camera (frame rate 42 Hz). A A V V V A V The binocular was a Leica Macroscope F16 APO. The basic principle consists in averaging a movie. Supplementary Fig. 1  shows one typical plate in a movie of CAM imaging and the image obtained after processing the data. The basic tool is the Z-Project tool in the software Image J by which multiple images in a stack can be projected. In our case, we either average plates or generate the image containing all minima at each pixel.
This is why we developed two macros, one which discards blurred images, and one which discards images which are too different from a chosen reference image in the stack (a neat crispy one). The blurred images are discarded in the following way. Generally, blurred images arise from the oscillatory behavior of the heartbeat and of the embryo. With proper positioning of the objectives, the ROI will be acceptably focused for 50% of the time, and out-of-focus 50% of the time, due to the oscillation. We therefore need to discard approx. 1 out of 2 plates (whenever possible, we keep more). When a sharp feature gets out of focus, the light is diffused away, so that typically a sharp dark spot will become lighter in color (gray scale). We therefore select a crisp dark area in one sharp image, follow its gray level image-by-image and discard 50% of the images having a less sharp area, as deduced from measuring the gray level with the "measure" macro in ImageJ macro language.
The finite element method needs to expand the solution onto a basis of polynomials. Lagrange polynomials of degree 2 for pressure and of degree 3 for velocity have been used leading to a stable numerical scheme and a good convergence. All calculations have been performed by using the commercial numerical code "Comsol Multiphysics" Results of computations: The flow in the first part is a good test to benchmark the quality of the mesh and the accuracy of the expected values for pressure gradient and wall shear stress. When the stream reaches the end of the tube the pressure gradient (absolute value) is increased by a factor of almost 18. The wall shear rate is increased by a factor of 4 along the curved part of the wall and of 8 along the plane side. Such results could predict an enhancement of stress and mechanotransduction upon the material of the wall.
Data availability Examples of the datasets generated during the current study, are available on the academic website of the author at: http://www. msc. univ-paris-diderot. fr/~vfleury/ data-Nature-Comm-Biol-2018. Considering that each image in a T-L movie is obtained by processing about 300 HD (2 Mb) images, the size of the original data for 10 h of T-L on a 5 min interval basis is in the 75 Gb range. Complete datasets are available from the corresponding author on reasonable request.
Flow cytometry Cells from TB patients and related controls from HS (2 × 10 5 cells) were labeled as described above and acquired in a FACSAria II cytometer (BD Biosciences). The monocyte-macrophage population was gated according to its forward scatter (FSC) and size scatter (SSC) proprieties. The percentage of positive cells and the median fluorescence intensity (MFI) were analyzed using FCS Express V3 software (De Novo Software, Los Angeles, CA, USA). In the context of macrophage activation programs, the CLR expression was analyzed by flow cytometry using antibodies (general dilution of 1:400) against DC-SIGN and Dectin-1 from R&D Systems, and MRC1 from BD Pharmingen (San Diego, CA, USA). Concerning the cellular content in PE fluid from TB patients, DC-SIGN expression was also analyzed by flow cytometry in mononuclear cells, gating within the CD14 + population and using human anti-DC-SIGN (R&D Systems).
qrT-Pcr analysis The amplification of RNA was performed with an ABI Prism 7500 Sequence Detector (Applied Biosystems) using the PCR SYBR Green sequence detection system (Eurogentec, Seraing, Belgium). Primers are listed in Table  S4  in Supplementary Material. Data were analyzed using the software supplied with the Sequence Detector (Applied Biosystems). The mRNA content was normalized to the metastatic lymph node protein 51 (MLN51) mRNA and quantified using the ΔΔCt method. semi-Quantitative cytokine/chemokine antibody array assay and Quantitative elisa Control and DC-SIGN-depleted M(IL-4) macrophages were infected with Mtb at MOI of 3. Supernatants were harvested at 4 and 18 h p. i. , centrifuged (2,000 g) for 10 min, passed through filters (0. 22 µm pores) and stored at -80°C. With the use of the Human Cytokine Antibody Array C Series 1000 (RayBiotech), we assessed the supernatant content in terms of cytokine and chemokines following the manufacturer's instructions, as previously described  (33).
In the case of M(IL-4) macrophages, our findings on DC-SIGN should be taken within the immunosuppression context given that the nature of these cells is that of wound healers and tissue remodelers  (22). In spite of these limitations, our study dealing with primary human cells in a TB context provides relevant data improving our knowledge on DC-SIGN. We first described the presence of DC-SIGN-expressing macrophages in the pleural cavity of patients and in the lung tissue of NHP with active TB. The identification of a humanCD14 + macrophage population displaying high cell-surface levels of DC-SIGN, MRC1, and CD163, is supported by our previous finding describing the presence of the CD16 hi CD163 hi MerTK hi immunosuppressive macrophages in the pleural cavity of patients with active TB  (25) , and by our first report on DC-SIGN-expressing alveolar macrophages isolated from the bronchoalveolar lavage in patients with pulmonary TB  (19).
FUnDing This work was supported in part by  ECOS-Sud  ( A14S01 ),  Laboratoire International Associé  (LIA, No. 1167 ), the  Centre National de la Recherche Scientifique , the  Université Paul Sabatier , the  Agence Nationale de la Recherche  ( ANR 2010-01301 ,  ANR14-CE11-0020-02 ,  ANR16-CE13-0005-01 ,  ANR-11-EQUIPEX-0003 ), the  Fondation pour la Recherche Médicale  ( DEQ2016 0334894 ;  DEQ2016 0334902 ), the  Fondation Bettencourt-Schueller , and the  Argentinean National Agency of Promotion of Science and Technology  ( PICT-2015-0055 ). FV acknowledges support from  Aeras (Rockville, MD, USA ). GL-V acknowledges support by  FRM  ( SPF20110421334 ).
The cells were allowed to rest for more than 2 h at 37 °C and 5% CO 2 before use. Follwoing the protocol described by Dexter et al. 55  , the cells were stored in long-term bone marrow culture (LTBMC) medium, which consists of 75% Iscove's modified Dulbecco's medium (IMDM; Life Technologies Inc. , Carlsbad, USA) supplemented with 12. 5% FCS, 12. 5% horse serum (both Stemcell Technologies Inc. , Vancouver, Canada), 2 mM L-glutamine, 100 U/ml penicillin/streptomycin (Life Technologies) and 0. 05% hydrocortisone 100 (Sigma-Aldrich Co. , St. Louis, USA). Non-viable cells were removed by staining with propidium iodide before the final analysis by flow cytometry, implying the purity of CD34 + cells is >95%. Each data point presented was collected from 30-50 cells from 3 donors, and the representable trajectories were shown in each polar plots.
1 s. From the average height and standard deviation of heights in each pixel, adhesion was detected when (a) the pixel lay within the cell contact area enclosed by the interference fringe pattern and (b) the standard deviation of heights was smaller than the noise. Time-lapse imaging of HSPC migration was performed on a Keyence BZ-9000 (Keyence, Osaka, Japan) equipped with a humidified and temperature controlled chamber. For each experimental condition, we selected 1-2 positions and recorded phase contrast images using a Plan Fluor air objective (40×/0. 6) over 6 h (frame rate: 25 mHz). All data sets were analyzed using self-written routines in Matlab 7. 7. 0 (R2008b) and ImageJ.
Acknowledgements The authors thank the  German Research Foundation (Collaborative Research Center ,  SFB 873 B07 ),  A. Lenze  for technical supports and  NOXXON Pharma AG, Berlin , for providing the oligonucleotides. M. T. thanks  JSPS  (No. 17H00855 ) and  MEXT  (No. 16H00802 ), and A. D. H. thanks the  Thiele-Stiftung  and the  German Ministry of Education and Research ("Systems Biology of Erythropoietin ", No. 0316182d ) for supports. M. T. is a member of  German Excellence Cluster "CellNetwork". C. M. thanks "CellNetworks" , and A. S. B. thanks the  Baden Württemberg State Foundation and Helmholtz International Graduate School  for fellowships.
Background: Imputation involves the inference of untyped single nucleotide polymorphisms (SNPs) in genome-wide association studies. The haplotypic reference of choice for imputation in Southeast Asian populations is unclear. Moreover, the influence of SNP annotation on imputation results has not been examined. Methods: This study was divided into two parts. In the first part, we applied imputation to genotyped SNPs from Southeast Asian populations from the Pan-Asian SNP database. Five percent of the total SNPs were removed. The remaining SNPs were applied to imputation with IMPUTE2. The imputed outcomes were verified with the removed SNPs. We compared imputation references from Chinese and Japanese haplotypes from the HapMap phase II (HMII) and the complete set of haplotypes from the 1000 Genomes Project (1000G).
Results: The accuracy was highest for all populations when using the HMII reference, but at the cost of a lower yield. Thai genotypes showed the highest accuracy over other populations in both HMII and 1000G panels, although accuracy and yield varied across chromosomes. Imputation was tested in a clinical dataset to compare accuracy in gene-related regions, and coding regions were found to have a higher accuracy and yield. Conclusions: This work provides the first evidence of imputation reference selection for Southeast Asian studies and highlights the effects of SNP locations respective to genes on imputation outcome. Researchers will need to consider the trade-off between accuracy and yield in future imputation studies.
Many studies have validated the accuracy and reliability of imputation  [5] [6] [7] , but most of these studies focused on populations of European descent  [5, 7]. One study showed that the accuracy of using a publicly available database varied across human populations with Europeans having the highest accuracy and Africans having the lowest  [6]. Because Asian populations have some unique genetic characteristics  [8] , it is not always possible to directly adapt information about genetics or genomics from studies in Caucasian populations  [9]. Several types of software are currently available for performing genotype imputation  [10] [11] [12] [13]. Similarly, many publicly available genetics databases are accessible for public use  [14, 15]. One of these is the Pan-Asian SNP genotyping database (PanSNPdb), which collects SNPs and copy number variations from 1719 samples in 71 populations from China, India, Indonesia, Japan, Malaysia, the Philippines, Singapore, South Korea, Taiwan, and Thailand  [16, 17].
The genotyping process was performed using the Affymetrix GeneChip Human Mapping 50 K Xba Array. Most of the studies on imputation have looked at the overall outcome of all SNPs  [5, 18] , and a few have focused on a particular region within a gene, not the whole genome  [19, 20]. We proposed two objectives for the current study. The first was to identify the most preferred reference for imputation in Southeast Asian populations. Using two publicly available haplotype databases, the International HapMap Project (HMII) and the 1000 Genomes project (1000G), we compared the accuracy and yield of imputation in several Southeast Asian populations. Additionally, we looked at imputed results using genotyped samples from a study of a Thai genome cohort. The second objective was to evaluate the imputation results of different regions in the human genome using a real dataset from the Thai dengue study as a model.
Methods This study was divided into two parts. The first part aimed at showing the difference in imputation accuracy by using different criteria for selecting a reference database. Additionally, using data from populations within the Southeast Asian region illustrated the variation in accuracy when going from one population to another. The second part used real genotype data in all autosomes to classify SNPs into different groups according to their location within genes. Imputation accuracy, GWAS significance and allele frequency were then correlated with the classification.
Sample datasets We performed the first part of our analysis using data from PanSNPdb  [16]. To illustrate the imputation accuracy in Southeast Asian populations, we selected all available samples from Indonesia (ID, n = 288), Malaysia (MY, n = 217), the Philippines (PI, n = 125), Singapore (SG, n = 90), and Thailand (TH, n = 245). Only SNPs that were polymorphic in all populations were used in this study (n = 52,160). The second part was imputation accuracy and yield in a patient dataset in which we had access to phenotypes because the phenotypes allowed us to observe the effect of imputation on subsequent association tests. The subjects were 609 Thai dengue patients who were 1-15 years-old from Siriraj, Ramathibodi, and Khon Kaen hospitals. A total of 468,987 SNPs from Illumina Human Hap610 array (Illumina Inc.
, San Diego, CA) passed the quality control requirements (QC). The accuracy of imputation was tested for each SNP from the dengue dataset by first randomly choosing half of the SNPs from the genotyping panel to create a mutually exclusive set of SNPs: Set 1 and Set 2. Then, Set 1 SNPs were used to impute Set 2 to create a complete SNP panel. Set 2 was also used to impute Set 1 to create a complete SNP panel. Based on our results in the previous section, HMII data were used as a reference for imputing the SNPs from the dengue dataset. The total number of SNPs after imputation was 1,417,081. Post-imputation QC reduced these numbers to 858,480.
Quality control and multidimensional scaling For all of the sample datasets, QC was performed in PLINK v1. 07  [12]  using standard procedures for GWAS  [21]. We included all markers with a call rate > 0. 95, a minor allele frequency (MAF) > 0. 01, and a Hardy-Weinberg equilibrium (HWE) > 10 -7. Samples with call rates < 0. 95 were excluded from the analysis along with samples that had first-degree relationship agreement, as evaluated by expected IBD sharing in PLINK v1. 07. Multidimensional scaling (MDS) of Southeast Asian populations from PanSNPdb was performed in PLINK v1. 07. This method allowed for visualization of principle components in the admixed population. Plotting of the MDS was conducted in R version 3. 0. 2 (http://www. rproject. org/).
Imputation procedure In the first part of the study, each population from PanSNPdb was analyzed independently. Five percent of SNPs were randomly selected and removed. The same SNPs set of the removed SNPs were applied to all populations. SHAPEIT version 2 software was used to pre-phase the SNPs  [22]. Imputation was accomplished with IM-PUTE2 to recover the removed SNPs  [23]. Each population was phased and imputed using both references in turn. According to guidelines from IMPUTE2, we imputed each chromosome separately and used windows of 5 Mb with an additional 250 kb buffer region on both sides of the analysis interval. The options used in the program were -buffer 1000, -iter 30, -burnin 10, and -k 80. The processes for random removal, phasing, and imputation were repeated five times. The second part of our study used all the autosomal SNPs from the dengue dataset.
Half of the autosomal SNPs from Thai dengue patients were removed by every second SNP (Set 1). Another dataset (Set 2) was then created in which the other half of the SNPs (Set 1) were removed. In this way, all SNPs were imputed once. Imputation was performed with HMII as described above. After imputation, SNPs were filtered using a QC process similar to the initial filtering of raw genotypes. Post-imputation QC excluded SNPs with MAF < 0. 01, call rate < 0. 95, and HWE < 5 × 10 -.