dataesr/scientific-paragraphs-categorization huggingface dataset:
Cell survival measurement Nalm-6 and Reh cells were seeded onto a 48-well plate at 1×10 6 /mL cells per well (BD Falcon TM , BD Biosciences®, Le Pont de Claix, France), stored under normoxic or hypoxic conditions for 24 h, then treated with different concentrations of MTX or PRD under the same conditions and harvested at 24, 48 and 72 h. Cells were subsequently treated with one of 2 solutions: propidium iodide to determine the number of non-viable cells; detergent to determine the total number of cells. The viable cell density (total cell number multiplied by percentage of viable cells) and percentage of viable cells were read with an ADAM series automatic cell counter (Labtech®, Palaiseau, France). All data from cell survival measurements are presented as the mean ± the standard error of the mean (S.
To quench the staining reaction, 5 volumes of ice-cold culture media were added directly to the cell suspension and left for 5 min on ice. Cells were centrifuged at 1500 rpm during 5 min and the pellets resuspended with fresh culture media a total of three times. After diffusion into the cytoplasm of the leukemic cells CFDA SE was measured with a flow cytometer with 488 nm excitation and the data analysed using FlowJo software (TreeStar, Oregon, USA, Version 9. 6). Acquisition based on 10,000 events (cells) was performed for each analysis.
Analysis Analysis was performed on Mapix Software (Innopsys®). Background and non-specific binding was subtracted from total signal intensity for each spot. RPPA data were expressed as a Z score and values below or above two standard deviations away from the mean were analyzed. For Heatmap representations, a hierarchical clustering (Ward method) was performed on an open source software R. The hierarchical clustering calculation was based on an Euclidean distance method. Western blot Western immunoblotting analyses were done using material from 5 × 10 5 to 10 × 10 6 cells. Briefly, cells were washed in PBS, harvested, and solubilized in aforementioned lysis buffer and kept on ice for 20 min. Lysates were centrifuged at 10,000 g for 15 min at 4 °C and stocked at -80 °C. Protein lysates were dosed with BCA protein assay kit (Thermo Scientific®, Illkirch, France,  [26].
Hypoxia inhibits chemotherapy-induced cell death pathways in leukemic cells To understand how hypoxia can protect leukemic cells from cell death induced by chemotherapies, apoptotic pathways were screened by RPPA in both cell lines. RPPA is an innovative technology allowing a screening of several molecular pathways on numerous samples. In this experiment, apoptosis pathways and proliferation / survival pathways were screened by RPPA. Nalm-6 and Reh cells were either untreated or treated with several concentrations of MTX (10nM -100 μM) and PRD (10nM -10 μM) over 24 h in both environments. In Nalm-6 cells treated with MTX, a shift in protein expression profile was observed in hypoxia toward normoxia (Data not shown). In normoxia, the expression profile of pro-apoptotic proteins was increased in a dose-and timedependent manner.
Study Design and Subjects Survey data were collected from a citizen and producer population in Flanders (the northern region of Belgium). Flanders was chosen as study area because 84% of Belgian poultry production is located in that region. The citizen sample was selected from a panel available from a market research agency, and reflects the adult population, including a number of farmers (Table  1 ). For the citizen sample, data were collected through self-administered web-based questionnaires during November 2011. Questionnaires were distributed after completing a pre-testing phase. Once a sample of 500 respondents was reached, data collection was ceased. The time gap between reaching 500 respondents, the decision to remove, and the removing of the link resulted in collection of more than 500 responses (n = 541).
Control groups were run systematically with larvae exposed to 1 ml of ethanol (for temephos) or 1 ml of tap water (for Bti). No food was provided to larvae during the bioassays, which were run at 28 ± 2 °C and 80 ± 10% relative humidity. Mortality was determined after 24 h of exposure to the insecticide. Mortality rates were corrected with Abbott's formula  [43]  when the mortality of controls was > 5%. All data were analysed with Win DL v. 2. 0 software  [44]. Lethal concentrations (LC 50 and LC 95 ) were calculated with their 95% confidence intervals (CIs). Resistance ratios (RR 50 and RR 95 ) were calculated by comparing the LC 50 and LC 95 for each species with those of susceptible strain, as RR 50(95) = LC 50(95) of studied population/LC 50(95) susceptible strain and RR 95 = LC 95(95) of studied population/LC 95(95) reference strain.
The susceptibility of the mosquitoes was classified according to the WHO criteria  [45]  as susceptible when mortality was > 97%, resistant when mortality was < 90% and possibly resistant when mortality was 90-97%. Surviving females were killed and stored individually at -80 °C in Eppendorf tubes (according to insecticide); dead mosquitoes were stored in silica gel. As in the larval bioassays, Win DL software version 2. 0 was used to estimate the KdT 50 and KdT 95 and their 95% CIs. Screening of kdr mutation in Aedes aegypti and Aedes albopictus DDT-and deltamethrin-resistant specimens of Ae. aegypti and Ae. albopictus were examined for the presence of kdr mutations. The total DNA of each surviving specimen was extracted with the 2% cetyl trimethyl ammonium bromide protocol described by Morlais et al.
Total protein and other enzyme systems were analysed in two replicates. The volume of supernatant was 20 μl for MFO and 10 μl for GST, αand β-esterases and total proteins. Absorbance was measured in a spectrophotometer for microplate readers (TECAN, Sunrise™) with Magellan version 7. 0. software. The ratios of the specific activities of enzymes to the protein content of individual homogenates were determined in the Bradford assay  [50]. Thus, 10 μl of each homogenate was mixed in a microtitre plate well with 140 μl of Bradford reagent (Sigma-Aldrich, St Louis, USA), and the mixture was incubated at room temperature for 5 min. The end-point absorbance was read at 595 nm. Protein values were calculated from a standard curve of absorbance of bovine serum albumin.
Biochemical data analysis Mean absorbance values of replicate wells for each tested mosquito were converted into enzyme activity and divided by the protein values. The mean activity of each sample was calculated and the distributions of enzymatic activities from wild mosquitoes were compared to those of reference strain mosquitoes (Ae. aegypti SBE) using Mann-Whitney tests (nonparametric) with GraphPad Prism version 5. 00 software and Mann-Withney U-test with MedCalc version 15. Statistical significance was assumed at P < 0. 05. Mann-Whitney test or Kruskal-Wallis test as appropriated was performed with STATA/IC version 11 (StataCorp College Station, Texas 77845) to assess the association between resistance status and enzymes activities in wild specimens but also to the reference strain, and P-values < 0.
160 ms. Under these conditions the resonance intensity attenuation of the slowest diffusive species (TPA) at 48 G/cm was approximately 10% of the value obtained at 1 G/cm. For each data set, 8192 complex points were collected for each increment step with a relaxation delay of 5 s. A total of 50 increments varying gradient were used. The number of scans was adapted to the state of dilution of the sample (n times 16 scans). The total experiment time ranged from 1 to 89 h per sample. DOSY spectra were generated by using the GIFA program  [78].
160 ms. Under these conditions the resonance intensity attenuation of the slowest diffusive species (TPA) at 48 G/cm was approximately 10% of the value obtained at 1 G/cm. For each data set, 8192 complex points were collected for each increment step with a relaxation delay of 5 s. A total of 50 increments varying gradient were used. The number of scans was adapted to the state of dilution of the sample (n times 16 scans). The total experiment time ranged from 1 to 89 h per sample. DOSY spectra were generated by using the GIFA program  [78]  implemented in the DOSY Module of NMRNotebook software and consist of chemical shifts on direct f 2 dimension ( 1 H NMR spectrum) and Gaussian distribution of self-diffusivity on indirect f 1 dimension (plot of peaks corresponding to diffusion coefficient values).
The density of the HydraVitis network thus provides the opportunity to assess the capability of radar products to document a heavy rainfall event at local scale  [39]. In this study, HydraVitis is therefore taken as reference for the capture of rainfall at local scale. The main aim is to assess the quality of QPE in PAN-THERE and ANTILOPE radar-based products, during a heavy rainfall event. First, total rainfall for the 24-hour event was assessed at both mesoscale and local scale. The second analysis focuses on hourly, local scale rainfall patterns. In the following sections, the heavy rainfall event occurring on November 3 to 4, 2014, is presented, and the two reference rain gauge network datasets (Météo France and HydraVitis) are described. The main characteristics of the radar products are explained, as is the method for comparing point and gridded products.
The Study Event and the Reference Rain Gauge Networks Specifications This case study is a 24-hour rainfall event, from 9. 00 pm on November 3 to 8. 00 pm on November 4, 2014. An unstable rainy disturbance was moving slowly southeastward across France, generating strong rainfall accumulations along axis oriented SSW/NNE  [40]. Rainfall data for this event were collected at both mesoscale (150 km radius) and local scale (28 km 2 ). The interest of this particular event is that the rainy front presented both stratiform and convective particularities  [40]. This exceptional event generated the equivalent of a month of rainfall in 24 hours, with accumulations ranging from 70 to 110 mm  [41]. Many floods resulted from this event and a state of natural disaster was recognized for 40 towns in the Saône-et-Loire administrative area ("departement" in French).
The average distance from an MFRN gauge to its nearest neighbor is 14. 4 km. One of these rain gauges is located within the study area covered by the high-resolution HydraVitis network. The second network, HydraVitis, is composed of 45 tipping-bucket rain gauges (RAINEW 111, RainWise5 Inc. ), covering an area of 28 km 2 (Figure  1(b) ). Based on Humphrey et al. [42] , rain gauge average measurement error ranged from 0. 6% to 4. 2%, from the lowest (2 mm) to the highest (200 mm) rainfall intensity  [38]. The gauge implementation was based on Météo France recommendations, deployed at a minimum distance of four times the height of the nearest obstacle. Each gauge was linked to a Hobo Pendant UA-002-64 event temperature logger (Onset5 Corp. ). This device records rainfall data every second, with a 0.
Method for Comparing Networks and Gridded Products The PANTHERE and ANTILOPE radar products (pixel grids) were compared with the MFRN and HydraVitis rain gauge networks (points) at two different scales. For mesoscale comparison, the 122 MFRN 24-hour cumulated rainfall measurement points were individually compared to the relevant PANTHERE QPE grid-pixel (Figure  1(a) ). As ANTILOPE is partly composed of spatialized MFRN data, this comparison was only conducted on the PANTHERE data to avoid interdataset dependency. Local scale comparison was based on HydraVitis data. Only one rain gauge measurement point was used for a given grid-pixel; the nearest rain gauge to the pixel center was systematically selected. Data from 21 rain gauges were therefore compared with 21 grid-pixels from each radar product, at an hourly time step (Figure  1(b) ).
Such merging provides useful products to estimate hourly QPE fields at local scale, even in situations where considerable attenuation is expected. Hourly precipitation data from the HydraVitis network are well correlated with both radar and merged products. High-resolution rainfall fields are crucial for hydrological applications, especially flood event prediction. Composite products, such as ANTILOPE, provide a viable alternative to high-density rain gauge networks, which are practically and financially difficult to deploy and exploit. Careful consideration of the quality and representativeness of the rain gauge network should be considered in conjunction with refinements to mathematical techniques when developing rain gauge radar merging products  [36]. (c) Improving radar rainfall products requires high density and quality ground data for validation  [48, 50].
Data Acquisition Before each experiment subjects were asked to execute few warm-up exercises and some VSJs to obtain a correct execution of the movement. They were subsequently asked to perform a maximum VSJs in 3 trials. Five optical markers were placed, on the gleno-humeral joint (shoulder), the great trochanter (hip), the lateral condyle of the femur (knee), the lateral malleolus (ankle), and the fifth metatarsal (toe) (e. g. ,  Aragón-Vargas and Gross, 1997). Subjects were filmed on the right sagittal plane with a camcorder (JVC © , GR-DVL 9200) at a distance of 7 m. The angle between the optical axis of the camcorder and the plane of movement was 90 •. The video sequences have been deframed with the software Adobe Première © to obtain an image frequency of 50 Hz. Video images were digitized using self-developed software.
The coordinates for the markers were obtained from digitization of the central point of the landmarks and the coordinates, as function of time, were smoothed by using a moving average of order 1. The anthropometric values of the segments required for the analysis of the data were obtained from  Winter (1990;  see Supplementary Material 1 and Supplementary Figure  1 ). To ensure the pertinence of Winter's proportional model in the present study the measure of h (for each subject) was also obtained with a force platform (AMTI © OR6-7-2000; frequency of acquisition: 500 Hz/software BioAnalysis © see also Supplementary Material 2). This measurement was compared to that obtained from the video analysis using the anthropometric tables of  Winter (1990)  (see Supplementary Material 2).
Basic Characteristics of the VSJs The most correct execution among 3 VSJs, for each subject, was chosen for analysis. The decision was made on the respect of the instructions given to execute the jump (initial stabilization of a semi-squatted position, arms akimbo during the jump, and initialization of the push-off without countermovement). This was systematically determined from the recorded videos of the jumps. As a further control, the measured h-values of the VSJ were compared to those obtained in other studies with skilled jumpers realizing maximal VSJs (e. g. ,  Bobbert et al. , 2008). The heights of the jumps were measured as defined in Figure  1  and Supplementary Material 2 and the time length of the push-off phases as in Supplementary Material 3. To confirm the measurements the VSJ height from each subject was obtained with a force platform (see Section Data Acquisition).
The first module (PING_gc), which determines the KIR gene copy number, is used to inform the second module (PING_allele), which generates allele data (Figure  1A  and Figure  S1 ). Each module is split into two sub-modules. KIR Filter Fish (KFF), which is used in both main modules, probes the KIR sequence data with specific sequence search strings and determines which genes (KFFgc) or alleles (KFFallele) are present. The function served by KFF is equivalent to genotyping with sequence-specific oligonucleotide probes (SSOPs). 33 To complement KFF, MIRAgc (based around the program MIRA)  34  and Son of SAMtools (SOS; based around SAMtools)  35  create alignments to reference sequences in order to determine the gene and allele content, respectively. The output is designed to comply with the genotype list (GL string) format that is used for reporting HLA and KIR data by clinical transplantation laboratories.
36 We validated the typing obtained from the complete capture, NGS, and bioinformatics method (hereafter referred to as the capture/NGS method) by using standard molecular techniques, and we further tested the bioinformatics component by using existing datasets from whole-genome sequencing experiments. A summary of the data generated or otherwise obtained is shown in Figure  1B. KIR and HLA class I allele sequences used for probe design and as reference data were obtained from the Immuno Polymorphism Database (IPD; see Web Resources). 15 Throughout this paper, any unique DNA sequence that spans a coding region (coding DNA sequence [CDS]) is considered a distinct allele. An explanation of KIR and HLA nomenclature is given in Appendix A.
44 with no history of chronic disease, were studied. These samples were selected at random from a larger dataset (n ¼ 500) developed as controls for genome-wide association studies (GWASs) of multiple sclerosis (MIM: 126200). 46 These samples were used because their high-resolution HLA-A, HLA-B, and HLA-C genotypes had been determined by Sanger sequencing. 46  validate the PING pipeline, we used existing sequenceread data from an additional two sources, described below. To extract KIR-specific sequences from these datasets, we used SAMtools 0. 1. 18. 35  ) is an analysis independent of any alignment or assembly and uses virtual probes to mine the raw data. The second arm (MIRAgc and SOS) performs filtering and alignment of reads to reference sequences. Thus, copy-number and allele genotypes are each derived by two independent methods.
The techniques are described fully in the Material and Methods. (B) Data generated by the method described herein (1-3) and those obtained from other sources (4). The table shows the number of individuals or cell lines used for validation, the genotyping results to be validated, and the independent laboratory method used for this purpose. or an unallocated chromosome 19 region (GenBank: GL000209. 1) corresponding to an alternative KIR haplotype. 4. 15 KhoeSan individuals. 47 These individuals had also been genotyped for KIR genes via standard lowerthroughput methods of pyrosequencing and Sanger sequencing. 16. The 1000 Genomes Project data. 48 ll 2,532 of the whole-exomesequenced individuals described in the May 2013 release were targeted. 48 To ensure sufficient quantity of sequence reads for the analysis, we excluded samples if fewer than 25 reads mapped to exon 3 of KIR3DL2 or KIR3DL1/2v (see Appendix A).
Design of Capture Oligonucleotide Probes To account for variation in the gene content of the KIR region, we targeted a panel of independently generated reference KIR haplotypes  6, 14  that together represent all of the 13 recognized KIR genes. First, we designed probes against the two complete KIR haplotypes (GenBank: FP089703 and FP089704) that were generated from the PGF cell line, which was the source of the human reference sequence for the KIR region. 6 We used end-to-end tiling with strand swapping to design non-overlapping 80-mer probes to match these reference sequences. We then designed a similar set of probes by using a further 27 complete KIR haplotype sequences  6, 14  and all KIR sequences included in the January 2013 release of the IPD-KIR database. 15 In this second stage, probes that differed by more than three nucleotides from the corresponding segment of the initial reference haplotypes were selected for use.
We did not mask any repetitive elements in the target haplotypes. The KIR genomic region targeted by the probes is equivalent to that covered by chr19: 55,228,188-55,383,188 (UCSC Genome Browser hg19) and an unmapped chromosome 19 region (GenBank: GL000209. 1), which are the two KIR haplotypes present in the hg19 reference genome. In a similar manner to the KIR probes, we designed probes against the alleles of the classic HLA class I genes present in the PGF cell line, which was also the source of the human reference sequence for the HLA region. 1, 14 These probes were supplemented with probes designed against the 6,795 HLA class I sequences reported in the January 2013 release of the IPD-HLA database. 15 A total of 10,456 capture probes were used.
Bioinformatics Methods: PING Pipeline Harvesting KIR-Specific Reads For sequence data obtained by the capture/NGS method, sequence reads specific to the KIR region were identified and harvested with Bowtie 2. 50  We concatenated the 29 sequenced KIR haplotypes and all KIR alleles from the IPD-KIR database  6, 14, 15  to create a single reference file for this purpose. The equivalent of 70,000 reads (at 2 3 300 bp) that passed this filter stage were taken per sample for KIR genotyping. KIR-Gene-Content Module: PING_gc This module is divided into two complementary components: the first (KFFgc) is based on string searches of raw data, and the second (MIRAgc) is based on read depth following alignment to reference sequences. Determining KIR Gene Content with Virtual Probes: KFFgc. The sequence-read files specific to the KIR region were first processed with the ''FASTQ Quality Trimmer'' function of the FASTX-Toolkit v.
A ''hit table'' was generated with the original allele alignment and bespoke R scripting (allgenos_hit_ table_2. R). The hit table was passed on to a random-forest algorithm in the ''RandomForest'' package of the R statistical software. 55 This algorithm ranks the probes according to the amount of information they contribute to the final answer. The purpose of the random-forest step is to obtain the most efficient subset of probes, thereby increasing the computational speed of genotype assignment. The output consists of a series of probe subsets that have an increasing proportion of the total set (5%, 10%, 15%, etc. ). Empirical testing found that the most efficient subset is usually the 40% most informative probes. We applied the final probe The ratio of reads mapping to a specific KIR gene to those mapping to KIR3DL3 can be used for calculating KIR copy number.
The results from 97 samples are shown and sorted by ratio. KIR2DL4 (left) was present in one, two, or three copies per individual in the sample set, and KIR2DL5 (right) was present in zero, one, two, three, or four copies. subset to the original allele alignment to produce a hit table of the expected probe pattern for all possible genotypes (again with allge-nos_hit_table_2. R). The number of exact matches to each probe sequence or its reverse complement in the forward and reverse files (read1. fastq and read2. fastq, respectively) for each sample was then counted. Aggregate counts above a threshold of 10 were considered positive, and the results were compared with the genotype hit table with a bespoke R script (KFFsums. R) for assigning the KIR allele genotype. KIR Sequence-Alignment Genotype by SOS.
Data used for generating filters and reference sequences were obtained from the IPD-KIR database (release 2. 6. 1, 17 February 2015) and the set of 29 complete KIR haplotype sequences. 6, 14, 15 For each given KIR gene, all available allele sequences were selected for use as a positive filter, and all allele sequences of all other KIR genes were used as a negative filter. We selected sequence reads specific to the given KIR by mapping them to the positive filter with Bowtie 2. 50  We performed this mapping non-stringently (R97% nucleotides matched) to allow for the detection of unknown SNPs. All reads that aligned to the positive filter were retained, and those that did not were excluded. The retained reads were mapped stringently (R99% match) to the negative filter, and in this case, those that aligned were excluded.