dataesr/scientific-paragraphs-categorization huggingface dataset:
1 (Roche Applied Science). Standard curves were obtained using DNA from B. cenocepacia J2315, whose genome contains one acdS copy, after diluting in triplicate from 5 × 10 -9 to 5 × 10 -15 g DNA μL -1. PCR efficiency was derived from standard curves as E = 10 (-1/slope). All five samples for rhizosphere or bulk soil treatment were assessed, and data expressed in g μL -1 were converted into numbers of acdS copies computed as [DNA (g) × Avogadro's number (molecules mol -1 )]/[number of DNA base pairs in PCR template × 660 (g mol -1 )], based on an average of 660 g mol -1 per base pair. acdS sequencing from rhizosphere DNA Primer specificity was assessed by Illumina MiSeq sequencing of acdSF5/acdSR8 amplicons (size ~133 nt), using bulk soils and rhizosphere soils from tomato and six Poaceae cultivated in cropped or meadow soil.
DNA extracts were sent to MR DNA laboratory (www. mrdnalab. com; Shallowater, TX) for acdS sequencing. The qPCR primers acdSF5/acdSR8 were used for the sequencing library, the forward primer carrying a barcode. The 30-cycle PCR (done five times, hence 150 cycles in total) used the Hot-StarTaq Plus Master Mix Kit (Qiagen, Valencia, CA) with 94 °C for 3 min, followed by 28 cycles of 94 °C for 30 s, 53 °C for 40 s, and 72 °C for 1 min, and a final elongation at 72 °C for 5 min. Samples were pooled together in same proportions, purified with calibrated Ampure XP beads and the DNA library was obtained with Illumina TruSeq DNA library protocol. Sequencing was carried out on a MiSeq following the manufacturer's instructions. Sequence data were treated with MR DNA pipeline. Briefly, sequences were depleted of barcodes, sequences < 120 bp or > 160 bp or with ambiguous base calls removed, the remaining sequences denoised, operational taxonomic units (OTUs; defined at 3% divergence threshold) generated, and chimeras removed.
OTUs were then classified using BLASTn and a curated acdS database (described in acdS database supplemental material). Briefly, the acdS in-house database (see the "Identification of acdS primers" section) developed to define the qPCR primers was adapted to exhibit only the 133 nt corresponding to the amplified PCR fragments. Moreover, when different accessions presented 100% identity in nucleotide sequences and were affiliated to a same bacterial species, only one sequence was kept, reducing the database entries to 1304 different sequences (named core-acdS database; see acdS database supplemental material) representing the phylogenetic diversity of ACC deaminase producers defined based on published data  [18] [19] [20] 50]. Dataset without singletons was used to generate rarefaction curves and Shannon, Simpson, and Chao diversity indices (calculated using sequencing subsample data for which each sample had the same number of sequences).
Acknowledgements We are grateful to  D. Abrouk  ( iBio platform, UMR CNRS 5557 Ecologie Microbienne ) for helpful discussion,  J. P. Magnière  ( Ferme expérimentale, La Côte Saint André, France ) for the choice of soil, and  Florence Gérin  for technical help. This work made use of Serre and DTAMB plateforms of  FR3728 BioEnviS at Université Lyon 1.
Quantification of SeCys and Validation Strategies The completeness of proteolytic digestion was verified by SEC-ICP MS of the digest where no residual high-molecular fraction could be observed. Therefore, selenocysteine can be quantified by the method of standard additions using CAM-SeCys standard. The recovery data at three levels are presented in Table  2. The limits of detection were 19 ng of SeCys (as Se) per gram of dry sample and the typical relative standard deviation of 6-7%. The slope of the calibration curve is similar to that obtained by standard additions of selenomethionine and quantification of the latter. These slopes are also identical to that of a calibration curve established by analyzing different concentrations of SeMet in water. These results allow the conclusion that the isocratic elution allows the use of selenomethionine standard to quantify any Se-containing compound eluting within the period of the isocratic elution.
The multistep immuno-labeling protocol didn't detect membrane expressed or internalized KCC2-pH int (Figure  3B ). Altogether these data show that leptin reduces the expression of KCC2 and its plasma membrane stability in cultured hippocampal neurons. The membrane expression and transport activity of KCC2 strongly depend on the phosphorylated state of its intracellular C-terminus domain  (Medina et al. , 2014). Phosphorylation on the threonine 906 and 1007 residues (T906, T1007) inhibits KCC2 activity and enhances KCC2 endocytosis, while phosphorylation of the serine 940 residue (S940) enhances KCC2 activity  (Medina et al. , 2014). We therefore assessed the phosphorylated state of KCC2 following leptin treatment in neuronal cultures. We found that the total amount of phospho-T906 KCC2 (pKCC2 T906), phospho-T1007 KCC2 (pKCC21007) and phospho-S940 KCC2 (pKCC2S940) protein were decreased in leptintreated neuronal cultures (Figure  3C ).
Blots were probed with antibody against KCC2 (1:2000; rabbit, US Biological) and tubulin (1:10. 000; ß-tubulin, mouse, Sigma). After washing with TBST, membranes were incubated with HRP-conjugated secondary antibodies diluted in TBST containing 3% BSA for 60 min, washed with TBST, and then developed using the G:BOX gel imaging system (Syngene). Expression levels were estimated by ImageJ software.
Real-time qRT-PCR Whole hippocampi were obtained from P6 mice as described above. RNA was isolated and quantified by reading the absorbance at 260 nm (NanoPhotometer, IMPLEN) using Mini RNeasy kit (Qiagen), then converted to cDNA using 1 µg RNA and a QuantiTect Reverse Transcription kit (Qiagen) according to manufacturer's instructions. PCR was carried out with the LightCycler 480 SYBR Green I Master (Roche Applied Science) with 1 µL cDNA using the following oligonucleotides (QuantiTect Primer Assays, Qiagen): NKCC1 (Slc12a2; QT00197785), KCC2 (Slc12a5; QT00145327) and glyceraldehyde-3-phosphate dehydrogenase (GAPDH, QT001199633). Quantitative RT-PCR was performed with a Roche LC480 Light Cycler (Roche Applied Science) following the manufacturer's instructions. Relative mRNA values were calculated using the LC480 software and GAPDH as the housekeeping gene.
Optical sections were digitized (1024 x 1024 pixels) and processed using ImageJ software (National Institutes of Health, http://rsb. info. nih. gov/ij/). Analysis of the intensity of the distribution of KCC2 fluorescence was performed at high magnification (×63 objective) using the Image J program. The same straight line length (3µm) was applied from the nucleus to the external cell compartment. The Plot profile values were analyzed and we normalized the fluorescence intensity to the highest intensity of the control condition. The intensity of KCC2 staining in neuronal cells was expressed as the mean ratio of KCC2/Neurotracer staining intensity.
Acknowledgments We thank  Dr. Y. Ben-Ari  for helpful support and suggestions during this study;  Drs. R. Cossart  and  N. Kourdougli  for reading of the manuscript and  Drs. E. Cherubini ,  C. Rivera  and  E. Sernagor  for helpful critical comments on the study. This work was supported by the  Ministère de la Recherche et de l'Enseignement Supérieur, Neurochlore (CD)  and the  National Institutes of Health  (Grant  MH086032 , GW).
Affinity kinetics of purified IgG for leptin was determined by surface plasmon resonance (SPR) on a BIAcore 1000 instrument (GE Healthcare) as previously published  15. Human recombinant leptin (Sigma, St. Louis, MO, USA) was covalently coupled on a CM5 chip (GE Healthcare) using the amine coupling kit (GE Healthcare) resulting in immobilized leptin in the amount of 2000 resonance units (RU). The affinity kinetic data were analyzed using BiaEvaluation 4. 1. 1 software (GE Healthcare). For fitting of kinetic data, the Langmuir's 1:1 model was used and the sample values were corrected by subtracting the blank values resulting from the injection of HBS-EP buffer. The association rate (Ka), the dissociation rate (Kd) and the dissociation equilibrium constant (KD) were obtained by the analysis of the fitted sensorgrams.
Data were analyzed and the graphs were plotted using GraphPad Prism 6. 0 (GraphPad Software Inc. , San Diego, CA). Normality was evaluated by Shapiro-Wilk test. Data are presented as median or mean according to the normality of variables. Outliers have been identified based on ROUT method (Robust regression and Outlier removal). Intergroup comparisons were performed using the nonparametric analysis of variance (ANOVA) Kruskal-Wallis (K-W) followed by Dunn's multiple comparisons post-hoc test. Individual groups were compared using Mann-Whitney test. Spearman's correlation (rho) was performed to evaluate potential associations of levels and affinity kinetics of leptin-reactive IgG with clinical markers of obesity and diabetes. A p-value < 0. 05 was considered significant.
First Experiment Data for all variables and starch samples was available, except for solubility and swelling power in one of the waxy genotypes. Although 30 waxy starch clones were evaluated (except for granule size) individual data is presented from 18 of them. These 18 genotypes were selected because they properly illustrate the kind of phenotypic variation (e. g. , maximum and minimum values) observed in the entire set of clones and characteristics evaluated. All 30 clones, however, were used in statistical analyses of variance. The 30 waxy starch genotypes were derived from 16 different families (identified by the first six digits in the pedigree). The 18 waxy clones from which data is presented represent 10 of these families. Table  2  and 3 present the results from the ten clones producing wildtype (containing amylose) starch.
8 and À605. 8 cP, Table  5 ). In the case of wildtype starches (Table  3 ) environment and genetic effects were significant, but that was not the case for their interaction. The same conclusions can be drawn for waxy starches (Table  5 ). Finally, CS was smaller in waxy (62. 2 and 59. 5 cP, Table  5 ) than in wildtype starches (158. 3 and 219. 3 cP, Table  3 ), due to the retrogradation of amylose during cooling. Environment had a strong and significant effect among wildtypes, whereas the effect on waxy clones was negligible. GxE effects were not significant. Table  6  presents the correlation coefficients among the different variables evaluated taking into consideration data from both locations. Correlations among the same variables but for LA or IA environments were also measured (data not presented).
| DATA AND METHODS The data used for this analysis were collected in the early 1980s as part of a comprehensive research project on the relationships between nutritional status and mortality among preschool children. This dataset is large and comprehensive and has been used for comparative studies. The project has been described in details elsewhere  (Briend, Garenne, Maire, Fontaine, & Dieng, 1989; Briend, Maire, Fontaine, & Garenne, 2012; Garenne et al. , 2009; Garenne, Maire, Fontaine, & Briend, 2006 , 2012; Garenne, Maire, Fontaine, Dieng, & Briend, 1987 , 2000). In brief, the study was conducted in a rural community of about 25,000 people living in 30 villages near Niakhar, Fatick region, in central Senegal. This population was living on farming, growing millet and peanuts, and raising cattle, sheep, and goats.
Data Collection After obtaining written consent, an interviewer administered a face-to-face questionnaire to the parent. It collected demographics (age, gender, country of birth, migration and residential trajectories, marital status, number of children), socio-economic characteristics (level of education, financial support, occupational status, professional experiences, housing history since the first episode of homelessness, number of accommodation moves since the beginning of the most recent episode of homelessness, social relationships, social support, and understanding of the French language). Food insecurity was measured using the Household Food Security Scale Measure (HFSSM), a scale created by the US Department of Agriculture (USDA)  [26] , the French translation of which was previously used in Québec  [27]  and in France  [22].
Acknowledgments: This survey received financial support from the  Agence régionale de santé d'Ile-de-France (ARS) ,  Cancéropôle Ile-de-France ,  Caisse nationale des allocations familiales (CNAF) ,  Fondation de France ,  Fondation Macif ,  Fondation Sanofi Espoir ,  Institut national de prévention et d'éducation pour la santé (INPES) ,  Institut de recherche en santé publique (IReSP) ,  Institut de veille sanitaire (InVS) ,  Ministère de l'Intérieur ,  Procter et Gamble ,  State Street , Observatoire national de l'enfance en danger (ONED). We thank all the families involved in this study, and  Lauren Dalecky  for the English editing and revision of the manuscript.
After completion of the imaging procedure, a terminal blood sample was withdrawn under isoflurane anesthesia from the retro-orbital sinus vein and the animals were sacrificed by cervical dislocation. Blood was measured for radioactivity in a gamma counter (Wizard 1470, Perkin-Elmer, Wellesley, MA, USA). PET Data Analysis. The 60 min dynamic emission PET data were sorted into 23 frames, which incrementally increased in time length from 5 s to 10 min. Images were reconstructed using Fourier rebinning of the 3D sonograms followed by twodimensional filtered back projection with a ramp filter, resulting in an image voxel size of 0. 4 × 0. 4 × 0. 796 mm. A standard data correction protocol (normalization, attenuation and decay correction) was applied to the PET data. The PET units were converted into units of radioactivity concentration by applying a calibration factor derived from imaging of a cylindrical phantom with a known 11 C-radioactivity concentration.
Using the image analysis software Amide  [23] , whole brain was manually outlined on the PET images, and time-activity curves, expressed in standardized uptake value ((radioactivity per g/injected radioactivity) × body weight), were derived. Individual brain-toblood concentration ratios (K b,brain ) were calculated by dividing the brain radioactivity concentration in the last PET frame (50 to 60 min after radiotracer injection) by the corresponding blood radioactivity concentration as determined by the gamma counter measurements. Quantitative PCR. Mice were sacrificed by cervical dislocation. After quick intracardial perfusion with 10 mL icecold PBS, one hemisphere of each brain was snap-frozen in liquid nitrogen within 3 min after death. Brains of 100-day-and 200-day-old wild-type male mice (3 and 4, respectively) and hABCB1 male mice (5 each) were preserved using Allprotect W Tissue Reagent (Qiagen, Germany).
Data were recorded with a Waters Xevo W TQ-S mass spectrometer (Waters, Manchester, UK). Measurements were performed by using positive electrospray ionization (ESI) with ion spray capillary voltage at 2. 80 kV. Drying gas temperature was set to 650 °C at a flow rate of 800 L/h. Detection was performed in multiplexed SRM mode by using three transitions per native or labeled peptide. Skyline software  [30, 31]  was used for the optimization of the specific transition parameters (i. e. , collision energy [CE] and peak integration). The area ratios light to labeled peptide were exported from Skyline, and the quantification was performed from calibration curves. Each sample contained two hemi cortices from different mice. It was digested in triplicate, and each triplicate was injected once. Therefore, the calculated concentrations (Table  1 ) take into account the experimental and biological variability.
5 ng template DNA in a total volume of 12. 5 μL. PCR reactions including 0. 3 μM of each PCR primer, 200 μM dNTPs, 1. 5 mM MgCl 2 and 0. 02 U/μL KAPA2G Robust polymerase. 35 cycles were run for each PCR with an initial denaturation step of 180 s at 95 °C followed by 35 cycles with a denaturation step for 20 s at 95 °C, an annealing step at 61 °C for 20 s, an elongation step for 100 s at 72 °C and a final elongation step at 72 °for 45 s. Excess dNTPs and primers were removed from PCR reactions and Sanger sequencing was performed. All primers used are listed in Supplementary Table  1. Amplification, primer design, and sequencing were realized by Microsynth AG (Switzerland). DNA Accessibility. Hotspots for DNA accessibility have been extracted from the ENCORE database. DNAse-seq data sets used were as follows: ENCSR337EDG, ENCSR179PIH, ENCSR358ESL, ENCSR469VGZ, ENCSR292QBA, and ENCSR767AJS.
ATAC-seq data from ENCFF386CJN. Chromatin immunoprecipitation sequencing (ChIP-seq) data were extracted from ENCBS139ENC. Data Availability. The data sets generated during and analyzed during the current study are available on reasonable request. Correspondence and requests for materials should be addressed to M. K. (markus. krohn@medisin. uio. no), J. P. (jens. pahnke@medisin. uio. no), W. L. (wolfgang. loescher@tihohannover. de), or O. L. (oliver. langer@ait. ac. at). All ENCODE data sets are publicly available at www. encodeproject. org.
The alien DNA containing the 5′-loxP site is situated -413 bp to -492 bp from TSS, thereby disrupting intron 1 of Abcb1a and possibly interfering with promoter elements. Thus, we searched the ENCODE database for information about DNA accessibility of this region  [37, 38]. Several DN-Ase-seq (DNase I hypersensitive sites sequencing) data sets (deposited after generation of this mouse model) derived from adult mouse brains revealed hotspots in the region of interest. The combined hotspot region (covered by at least 5 data sets) reaches from about 200 bp upstream of exon 1 until about 160 bp downstream of exon 2 (Figure  5 ). ATAC-seq (Assay for Transposase-Accessible Chromatin sequencing) data generated from postnatal mouse forebrains revealed a hotspot of about 690 bp reaching until exon 2 (Figure  5 ).
[21] ). Intriguingly, murine Abcb1a mRNA is still present at wildtype levels in the humanized mice's brain (Figure  2 ) indicating the expression of a truncated Abcb1a gene product starting downstream of exon 2. In silico translation analysis of the Abcb1a coding sequence and qPCR revealed the possibility of a protein being expressed that lacks at least the first 37 amino acids and thus the cytoplasmic N-terminus up to transmembrane helix 1 (Figure  3 ). However, mouse ABCB1A/B proteins were not detectable at all in hABCB1 mice (Table  1 ). Since the human CDS has been inserted correctly and this strategy was employed successfully to introduce a canine ABCB1 earlier  [33, 34] , the main question is: what caused the lack of expression in both (Taconic and genOway) humanized mouse models? A review of the canine ABCB1 mouse data points to an answer.
The overlap of several hotspots of DNA accessibility extracted from ENCODE data sets within the region of CDS insertion reinforces its importance in gene regulation. Interestingly, the lack of two-thirds of intron 1 and all of exon 2 in human ABCB1 -/-mice restored mouse ABCB1A protein expression to about 50% of wild-type levels according to QTAP results. However, Western blot results corroborate PET imaging data and QTAP results but, confusingly, do not reveal truncated protein variants. The lack of a visible shift in protein size might be due to the extremely weak signals though and a lack of resolution of the chosen gel matrix. One could speculate that recombination of the locus restores some regulatory features partly located in intron 2 that have been disrupted by insertion of the CDS.
Acknowledgments. The authors thank  Sandra Noack ,  Ivan Eiriz Delgado ,  David Gomez-Zepeda ,  Meryam Taghi ,  Wang-Qing Liu ,  Cerina Chhuon ,  Michel Vidal , and  Ida-Chiara Guerrera  for their assistance. They also thank genOway S. A. for their openness in discussing the findings and all members of the  ENCODE Consortium and Portal  for providing the valuable data sets.
In contrast, the use of antihypertensive medicines and lifestyle change to reduce blood pressure in those with elevated levels would reduce the prevalence of raised blood pressure by acting on the high-blood-pressure tail of the distribution, and hence change the shape of the distribution with a relatively small impact on its mean. An important question that can inform strategies for meeting the global target and reducing the burden of raised blood pressure, is to what extent regional differences and changes over time in the prevalence of raised blood pressure are driven by variations in the mean SBP and DBP versus by the shape of the distribution. We used a database of population-based studies with global coverage conducted over three decades to investigate contributions of population mean and high-blood-pressure individuals to worldwide trends and variations in raised blood pressure.
Study design We first used population-based data to estimate the association between the prevalence of raised blood pressure, defined as SBP ! 140 mmHg or DBP ! 90 mmHg, and population mean SBP and DBP among men and women aged 20 to 79 years in nine regions of the world, from 1985 to 2016. We used a linear mixed effect model to quantify the association between the prevalence of raised blood pressure and mean blood pressure. Our statistical model, described below, allowed the prevalence of raised blood pressure at any level of mean SBP and DBP to differ by age group, region and time period. We then used the fitted association to estimate the contributions of changes in the population mean blood pressure versus changes in the shape of its distribution (represented by how the prevalence-mean association varied over region and time), to the changes in the prevalence of raised blood pressure in different regions.
Data sources We used data from NCD Risk Factor Collaboration (NCD-RisC) database, which contains studies that had measured blood pressure in representative samples of the national populations or of one or more sub-national regions and communities. NCD-RisC is a worldwide network of health researchers and practitioners whose aim is to document systematically the worldwide trends and variations in NCD risk factors. 2] [23] [24]  In summary, the database was collated through multiple routes for identifying and accessing data. We accessed publicly available populationbased multi-country and national measurement surveys as well as the WHO STEPwise approach to Surveillance (STEPS) surveys. We requested, via WHO and its regional and country offices, ministries of health and other national health and statistical agencies to identify and access population-based surveys.
Requests were also sent via the World Heart Federation to its national partners. We made a similar request to the co-authors of an earlier pooled analysis of cardiometabolic risk factors,  [25] [26] [27] [28]  and invited them to reanalyse data from their studies and join NCD-RisC. To identify major sources not accessed through the above routes, we searched and reviewed published studies, and invited all eligible studies to join NCD-RisC. Finally, NCD-RisC members are periodically asked to review the list of sources from their country, to suggest additional sources currently not in the database and to verify that the included data from their country meet the inclusion criteria as listed in the Supplementary data (available at IJE online) and that there are no duplicates. Here, we analysed data collected from 1985 to 2016 on men and women aged 20-79 years, in 10year age groups from 20-29 years to 70-79 years.