dataesr/scientific-paragraphs-categorization huggingface dataset:
BODIPY-FL FAs binding to recombinant Fabps Stock 2 mM solutions of BODIPY-FLC 5 or BODIPY-FLC 12 in ethanol were diluted in PBS prior to mixing and incubating with purifi ed proteins for a few minutes. Prior to binding assays , the proteins were delipidated in batch using hydroxyalkoxypropyldextran (Sigma-Aldrich) chromatography, equilibrated with 50 mM Tris-HCl, pH 7. 4, at 37°C for 45 min. The proteins were then diluted at the working concentration with 30 mM Tris HCl, pH 8. 3, sample buffer. Five microliters of 20 µM BODIPY-FLC 5 or BODIPY-FLC 12 were mixed with 20 µl 5. 6 µM recombinant zebrafi sh Fabp1b. 1, 12 µl 4. 3 µM tropomyosin A (TPMA) from Echinococcus granulosus (GenBank: AAB65799. 4), or 6. 6 µl 7. 5 µM BSA. A 12 µl sample of 20 µM BODIPY-FLC 5 or BODIPY-FLC 12 was mixed with 20 µl 30 µM recombinant zebrafi sh Fabp2.
The slides were then immersed in a solution of To-Pro 3 iodide (TP3) or 4',6'-diamidino-2-phenylindole (DAPI) (1:4,000) to label the nuclei were detected in the liver, together with very small amounts of fabp2 mRNA, while fabp1b. 2 transcripts were not detected ( Fig. 1  ; data not shown). Zebrafi sh fabp1b. 2 transcripts were also detected in ovaries, testicles, kidneys, and heart, and trace amounts of fabp2 transcripts were found in kidneys. in ethanol and supplemented with 10 µl loading sample buffer used for loading on the native polyacrylamide gel. Under these conditions, the unlabeled FAs were in ‫ف‬ 100-fold molar excess (i. e. , 0. 35 mM) over the labeled FA and protein used. The following competitor ligands assayed were oleic acid (C18:1w9), linoleic acid (C18:2w6), and DHA (C22:6w3).
Tandem MS Stained PAGE bands were faded, excised, and in-gel digested with trypsin in the appropriate buffer. The peptides resulting from the proteolytic digestion were identifi ed by peptide mass fi ngerprinting and collision-induced dissociation using a 4800 MALDI-TOF-TOF mass spectrometer (Applied Biosystems). The MS data were analyzed using Mascot software (Matrix Science Ltd. , London, United Kingdom) and searching the NCBInr and ZFIN zebrafi sh databases.
Statistics Variations in transcription levels (normalized by reference genes) were analyzed for statistical signifi cance using REST-384version 2 software for multiple reference genes (http://rest. genequantifi cation. info/) and/or a nonparametric Mann-Whitney test (GraphPad InStat v3. 5, GraphPad Software). The signifi cance level was set at 0. 05. Data are presented as mean ± SD. The same test was used to check for variations in normalized ef1 ␣ / ppiaa values.
Tissue-specifi c distribution of zebrafi sh fabp1b. 1 , fabp1b. 2 , and fabp2 transcripts Qualitative RT-PCR detected fabp1b. 1 and fabp1b. 2 transcripts in total RNA extracted from the anterior intestine in adult zebrafi sh, irrespective of the animals' nutritional status ( Fig. 1A  ). qRT-PCR indicated similarly high levels of transcripts for fabp1b. 1 and fabp2 in the anterior intestine, by comparison with normalizing genes eef1a1 ( Fig. 1B, D  ) and ppiaa (data not shown). The fabp1b. 2 mRNA levels were around 3-fold lower ( Fig. 1C  , data not shown). The normalized level of fabp1b. 2 transcripts was very high in brain ( Fig. 1C  , data not shown). Trace amounts of fabp2 transcripts were also expressed in adult brain while fabp1b. 1 transcripts were not detected. By contrast, fabp1b. 1 transcripts There were no signifi cant differences in fabp1b.
1 and fabp2 transcript levels between nourished and unnourished 5 dpf eleutheroembryos when normalized with the two reference genes, while a slight upregulation of fabp1b. 1 was detected when using ppiaa only (×1. 15-fold, P = 0. 026). Transcripts levels of fabp1b. 1 and fabp2 were also signifi cantly upregulated after feeding in whole 15 dpf zebrafi sh larvae homogenates, irrespective of the reference gene used ( Fig. 3  ). The fabp1b. 1 transcript levels were 1. 41 ( P = 0. 026) and 1. 54 ( P = 0. 0022) higher, respectively, when eef1a1 and ppiaa were used as reference transcripts. REST software using the two reference transcripts at the same time gave a P value of 0. 001. The fabp2 transcripts levels were 1. 59 ( P = 0. 026) and 1. 71 ( P = 0. 0022) higher, respectively, when eef1a1 and ppiaa were used as reference transcripts.
REST software using the two reference transcripts at the same time gave a P value of 0. 004. The effect of diet composition on the level of fabp1b ( fabp1b. 1 + fabp1b. 2 ) and fabp2 transcript levels was then studied by whole-mount in situ hybridization ( Fig. 4  ). An upregulation of fabp1b and fabp2 hybridization signals between starved and fed conditions was detected, and the signal was apparently modulated according to the lipid composition of the diet. Larvae (15 dpf) nourished with FD experienced a high induction of the signal after feeding, while larvae fed with dried CEY or OO were in an intermediate state ( Fig. 4  ).
1 and fabp2 transcript levels occurred in the zebrafi sh adult intestine and liver after feeding. As indicated in Fig. 2  , transcript levels of fabp2 ( P = 0. 0087) were upregulated by 1. 59-fold and fabp1b. 1 by 1. 36-fold (not signifi cant) in the anterior intestine when the reference gene used was eef1a1. REST software, using both ppiaa and eef1a1 as reference transcripts, gave P = 0. 021 for fabp2. This upregulation was not observed in the liver ( Fig. 2  ). A similar study was then conducted at early developmental nutritional stages (i. e. , fi rst feeding at 5 dpf) and at the start of the exogenous nutritional phase of larval development (i. e. , 15 dpf) ( Fig. 3  ). Fig. 2. qRT-PCR analysis of fabp1b. 1 and fabp2 transcript expression in the dissected anterior intestine (ai) and liver (l) of adult zebrafi sh.
A: fabp1b. 1. B: fabp2. After a period of over 24 h fasting (fasted group, fa) or 22 h fasting followed by 2 h feeding (fed group, fe), organs from 6 individuals were sampled and analyzed independently, in triplicate. The number of eef1a1 transcripts was also quantifi ed and used to express the results as a number of copies of fabp1b. 1 or fabp2 divided by the number of copies of the normalizing gene. Very similar results were obtained with ppiaa , used as another normalizing gene (data not shown). Data are means ± SD. ** P < 0. 01, signifi cant difference between fa and fe groups for the organ examined using the nonparametric Mann-Whitney test. A differential expression pattern of fabp genes along the anterior-posterior axis of the gut was demonstrated by wholemount in situ hybridization ( Fig.
The apex of the villi is positioned at the bottom in each image. B, G are enlargements of the indicated large area from A, I, respectively. Inserts in A, F are enlargements of the indicated small area focused on an enterocyte nucleus with a strong BODIPY-FLC 12 signal. The selected nucleus has been surrounded by a yellow line after using the threshold and wand tool options of ImageJ software (see supplementary Fig. 9  for an enlarged view of these panels). Yellow intracytoplasmic granulation indicates an overlap between Fabp1b and BODIPY-FLC 12 (I, J, red arrow in G). Some nuclei with more condensed chromatin had low BODIPY-FLC 12 intranuclear labeling while the pink granules indicate intranuclear Fabp1b (white arrowhead in G). White and red asterisks indicate goblet cell and putative red blood cell nuclei, respectively, free of any Fabp1b and BODIPY-FLC 12 labeling (B, G).
Acknowledgements We thank  Sonia Varela  ( Animal Facilities, Sorbonne Paris Cité Université Paris 13 ), and  Béatrice Marmey  ( Centre de Recherche des Cordeliers, Université Paris 6 ) for their outstanding technical assistance. Elodie Poirier  is recipient of a Master's scholarship provided by the  Société Française de Dermatologie. 1 INSERM, UMR 1125, 93017 Bobigny, France. 2  Sorbonne Paris Cité Université Paris 13 , 74 rue  Marcel Cachin , 93000 Bobigny, France. 3 Present address:  INSERM UMRS 1138 Equipe 13 ,  Centre de Recherche des Cordeliers, 75006 Paris, France. 4 INSERM U1082 ,  Pôle Biologie Santé ,  CHU Poitiers, BP 633, Poitiers 86022, France. 5Assistance Publique-Hôpitaux de Paris, Avicenne Hospital, Rheumatology Department, 93009 Bobigny, France. 6Institut de Pharmacologie et de Biologie Structurale (IPBS) CNRS-Université de Toulouse III, 31077 Toulouse, France.
Later the mononuclear (MNC) cells were washed again with PBS with 0. 01 % NaN3 and suspended in 500 µL of FACS flow (Becton-Dickinson; USA). For data acquisition and analysis the Facs Calibur flow cytometer (Becton-Dickinson; USA) with Cell-Quest software (Becton-Dickinson; USA) was used. The results were given as the percentage of cells presenting the expression of the investigated protein.
Analysis of marker expression in control and BRCA1-mutated breast tissue Expression of several markers was analyzed by IHC in histologically normal breast tissues from 28 women selected as controls (BRCA1 +/+ ) and 22 women with BRCA1 mutations (BRCA1 mut/+ ). Characteristics of patients bearing BRCA1 mutations are described in Table  1. Proliferation marker Ki67 was quantified in luminal epithelial cells of breast tissues. The Ki67-positive cell percentage was similar between the control (4. 7 ± 1. 3%) and mutated breast tissues (4. 6 ± 1. 2%) (p=0. 974, data not shown). However, when women were sorted according to their menopausal status, we observed that Ki67 expression was significantly reduced in the post-menopause group compared to the pre-menopause group, among patients with BRCA1 mutations (p=0.
019) (Figure  1a ). Similar results were observed in lobular and ductal structures of breast tissues when analyzed independently (Figure  1b ). As this result suggested a different sensitivity to gonadal hormones in BRCA1 mutated tissues compared to control tissues under different ovarian hormonal stimulation, hormone receptor levels were analyzed. Overall, the percentages of ER-positive epithelial cells were not significantly different between BRCA1 mut/+ tissues (41. 67 ± 2. 9%) and control BRCA1 +/+ tissues (33. 5 ± 3. 3%) (p=0. 078, data not shown). When analyzed according to menopause status, ER-positive cells were elevated in post-menopausal BRCA1 mut/+ tissues in comparison to control tissues (p=0. 0162, Figure  2a ). A similar profile of expression was observed in lobular and ductal structures (Supplementary Figure  1a ).
PR levels were also measured. The percentage of PR-positive cells were not significantly different in BRCA1 mut/+ breast tissues (29. 52 ± 3. 3%) compared to the control group (35. 8 ± 2. 6%) (p=0. 13, data not shown). However, pre-menopausal BRCA1 mut/+ breast tissues appeared to have a slightly lower percentage of PRpositive cells compared to control tissues (p=0. 075, Figure  2b ). We also observed that PR expression was significantly reduced in the lobules from pre-menopausal BRCA1 mut/+ group (p=0. 042) but not in the ducts (Supplementary Figure  1b ). PR levels in lobular structures were reduced after menopause in the control group (p=0. 017) but not in the BRCA1 mut/+ group (Supplementary Figure  1b ). The ER/PR ratio was calculated for each patient breast tissue. This ratio was significantly elevated in the BRCA1 mutated group compared to the control group: 2.
ACKNOWLEDGMENTS We thank  Drs Michele Resche-Rigon ,  Andre Ulmann  and  Erin Gainer  ( HRA Pharma, Paris ) for helpful discussions, provision of the antiprogestin  UPA , and analytical contributions on mice serum UPA concentrations. We are very grateful to  Sylvie Dumont  and  Fatiha Merabtène (Plateforme d'Histomorphologie UMS30 -LUMIC (UPMC) Hôpital Saint Antoine Paris France)  for their technical assistance in immunohistochemistry, and to  Jacqueline Chung  and  Kishanda Vyboh  for their work editing the publication.
The quality and performance indicators in the laboratory were monitored continuously on a routine basis as described before  [9]. The data were entered into a Microsoft Excel (Version 11. 0 developed by Microsoft for Windows) spreadsheet and cross verified by a statistician. The number of C and D specimens received was enumerated and, the proportion of cultures retrieved, contaminated and nontuberculous mycobacteria isolated from NSP and PT cases, were calculated. A Zproportion test was done to determine the significance of observed differences between the proportions. A two-way table, comparing culture grades of paired specimens from 1518 NSP and 894 PT patients, was created after excluding patients who produced a single specimen. Kappa statistics was performed to find the agreement between C and D specimens.
Discussion The guidelines for drug resistance surveillance and testing in laboratories were developed as early as 1969  [10]. Later, to have the comparable global data on drug resistance, WHO framed guidelines to carry out a global drug resistance surveillance program through its collaborating centers for bacteriology of TB  [6, 11]. The guidance is to collect two sputum samples from smear-positive patients enrolled under national TB control programs and to perform DST in quality assured reference laboratories. Accordingly, in Tamil Nadu survey, two additional sputum specimens were collected from Ziehl-Neelsen-positive patients and transported to the central laboratory to carry out culture and susceptibility testing. This retrospective analysis of DRS was done to determine the adequacy of single sputum specimen over the current recommendation of two (one spot and one morning) sputum specimens in the TB DRSs.
Acknowledgments The authors gratefully acknowledge the excellent technical support provided by the staff in the department of bacteriology; the contractual staff under  Model DOTS  ( Directly Observed Treatment-Short Course ) project;  Director of State TB Demonstration and Training Centre, Microbiologist of Intermediate Reference  Laboratory, District TB Officers, Senior TB  Laboratory Supervisors  and  Lab Technicians  of the participating districts in the state of  Tamil Nadu , and the financial support by The  United States Agency for International Development through World Health Organization, South-East Asia Regional Office, New Delhi.
Introduction A goal of the European Habitats Directive is to protect biodiversity through the conservation of habitats (Council Directive 92/43/EEC). The Directive establishes the designation of protected areas to be included in the Natura 2000 network. The implementation of this network requires the monitoring and management of habitats and stresses the urgent need for updated information on habitat conservation status. Remote sensing can provide useful data for mapping and monitoring protected habitats  [1] [2] [3] [4] [5]  and assessing vegetation cover at detailed scales using aerial ortho-images, or high resolution airborne or satellite imagery such as Quickbird, Ikonos  [6] [7] [8] [9] [10] , or the most recent Worldview and Geo-Eye satellites  [11] [12] [13] [14] , and to establish a relationship between vegetation cover, type or biological crust, and its phenological state using satellite data  [15, 16].
Material and Methods Figure  2  summarizes the methodology followed to integrate field and satellite data. Two field campaigns were conducted during the summers of 2007 and 2008, based on a georeferenced database of vegetation  [48, 57]. Surveys were done in summer, when perennial halophytes reach maximum photosynthetic activity. Field radiometry campaigns were synchronized with satellite images. Xero-halophilous (salt-tolerant shrub formations of dry ground in low-precipitation areas  [55] ) scrubs (Arthrocnemum macrostachyum, Suaeda vera subsp. braun-blanquetii, Limonium latebracteatum) and Lygeum spartum, predominate in saline soils and occupy high topographic positions. Annual plants (Frankenia pulverulenta, Sphenopus divaricatus, Halopeplis amplexicaulis, Salicornia patula, Microcnemum coralloides) frequently pioneer the playa-lake floor.
The reflectance of samples in four CropScan channels (485, 561, 660, and 830 nm) was directly compared with that of the corresponding Quickbird bands, with centers and bandwidths of 488 nm (430-545), 542 nm (466-620), 650 nm (590-710), and 817 nm (715-918). The raw data from Ocean Optics were pre-processed using SAMS (Spectral Analysis Management System) software originally developed at the University of California Davis Center for Spatial Technologies and Remote Sensing (CSTARS). The pre-processed continuum spectra, exported to the ENVI ® spectral library, were sampled into the Quickbird discrete bands using the Spectral Library Resampling tool. We sampled the band 4 (NIR) within the range 775-795 nm to eliminate noisy absorption values. NDVI [(NIR ´VIS)/(NIR + VIS)] was calculated from the field spectra (NDVI Field ).
Ground Photography and Auxiliary Field Data A vertical photograph (18 mm camera lens) of the ground was taken on a tripod at 1. 3 m height with a similar nadir to the spectrometer in 2008, simultaneous with each spectral measurement (Figure  2 ). The photographs, covering 167 cm ˆ111 cm on the ground, were classified with Can-Eye software  [58]  by supervised classification to obtain the fraction of vegetation cover (fCover)  [59]. The reflectance of control samples with four different percent covers of vegetation (0%, 25%, 50%, and 100%) prepared by visual comparison with Munsell standards was recorded. At each sampling point we took a visual estimation of plant cover, the Munsell soil color hues, and the gravimetric soil moisture of the two first centimeters of soil. For this purpose we determined the difference in weight after drying the soil samples at 40 ˝C according to  [60].
Satellite Images and Data Processing Two Quickbird images were acquired in summer (July 2007 and 2008) scheduled in correspondence with the field campaigns. Due to the 16. 5 km-limited Quickbird width-imaging swath, three sub-images were acquired between two dates (spanning 18 days) to complete the entire study area in July 2007. A single Quickbird image was acquired for 2008 survey, adapted to the surveyed area. We checked the radiometric homogeneity of the field sites on the georeferenced Quickbird image and we selected only the most homogeneous points with vegetation or bare soil, i. e. , the pure points. The fCover, estimated from the ground photographs, was related to NDVI from field spectra (NDVI Field ) which was related to the NDVI calculated from the Quickbird image (NDVI QB ) (Figure  2 ).
Furthermore, the effects of spatial and spectral resolution on the identification of the studied vegetation were analyzed by comparing Landsat and ASTER summer images with Quickbird and field spectral data. Landsat and ASTER images were processed similar to QB images. The dry summer of 2007, with absence of rains before the capture of these images, guaranteed similar soil surface conditions for all data sources. The characteristics of the satellite images are summarized in Table  1. Satellite image processing included radiometric, atmospheric, and geometric corrections. Radiometric corrections and conversion of image brightness to Top of Atmosphere (TOA) reflectance were made using ACORN5 software (ImSpec, Palmdale, CA, USA) based on the MODTRAN4 (MODerate resolution atmospheric TRANsmission) algorithm.
Spectral Characteristics of Soil and Vegetation Data of sampling points with spectrometer Ocean Optics are summarized in Table  S1. Mean soil reflectance ranges from 30% to 40% in the visible (VIS) and near infrared (NIR) spectra, respectively, and reaches 50% in soils with efflorescence (Figure  3 ). Dry soils without efflorescence show continuously increasing reflectance from the VIS to NIR. The soil surface frequently exhibited light colors, with Munsell values of 7 and 8, due to the soil composition. Gypsum and carbonates are ubiquitous in the landscape due to the parent material; the 0-15 cm soil layer is characterized by 10% to 91% of gypsum and 12% to 45% of calcium carbonate  [61]. Satellite image processing included radiometric, atmospheric, and geometric corrections. Radiometric corrections and conversion of image brightness to Top of Atmosphere (TOA) reflectance were made using ACORN5 software (ImSpec, Palmdale, CA, USA) based on the MODTRAN4 (MODerate resolution atmospheric TRANsmission) algorithm.
Acknowledgments: This study was funded by the  Spanish Ministry of Economy and Competitiveness (MINECO)  under the projects  AGL2012-41000  and  BASIL  ( PCIN-2014-106 ). Manuela Domínguez-Beisiegel  was given a grant by the  Spanish Government (INIA). We thank the  Centre d'Etudes Spatiales de la Biosphère (CESBIO, Toulouse, France ) for the support during the stage of  Manuela Domínguez-Beisiegel  and the use of the field radiometer. We acknowledge the comments and helpful suggestions of the five referees.
Descriptions and limitations of previous methods used to assess the trend of measurements 2. 3. 1. Four-quadrant plots. Four-quadrant plots, first described for CO measurements,  [7]  demonstrates changes between the test and RMs used to measure CO. The plot is divided into 4 quadrants around the Xand Y-axes that intersect at the center (0,0). After exclusion of points considered to represent clinically insignificant changes or the imprecision of the method (defined as the central zone), concordance analysis is performed by counting the number of remaining data points situated within the 2 quadrants of agreement (upper right and lower left quadrants). A concordance rate is then calculated and a line of identity Y = X is depicted. The limitations of this method are (i) calculation of exclusion of the central zone has not been standardized (exclusion criteria based on absolute values are situated below an arbitrary limit or below a percentage change, e.
Dataset We simulated 300 variations of measurements for 150 patients (3 values and 2 changes for each patient). The data points were obtained in 3 ranges of values (2. 5, 3. 5, and 5 units) using R Software version 3. 1. 0 (R Core Team, R Foundation for Statistical Computing, Vienna, Austria). One hundred values were simulated for each of the 3 ranges using 3 multivariate normal distributions, as follows:. The variance-covariance matrices were chosen so that the variance of the measurements decreased with their absolute values. The R script is available in Appendix 1, http://links. lww. com/MD/B40, and the simulated data are available in Appendix 2, http://links. lww. com/MD/B41. We then applied the proposed method to the complete original data published by de Wilde et al. [13]  This study compared CO measurements by 5 different arterial pulse contour techniques (Wesseling's method, LiDCO, PiCCO, Hemac method, and Modelflow) in comparison with the 4-bolus pulmonary artery thermodilution as RM.
Statistical analyses The number of simulated data was empirically set at 300 before starting the analysis. Trend interchangeability (i. e. , the proportion of interchangeable variations) was then calculated, expressed as number (percentage), and was considered to be excellent (≥95%), good (≥ 90%), poor (75%-90%), or not clinically relevant (<75%) according to its value. First data (used to calibrate the 5 pulse contour methods), and missing data were not used. A chisquare test was performed to compare the interchangeability rate between the 5 tested devices. A P value <0. 05 was considered to be statistically significant and all P values were 2-tailed. Statistical analyses were performed with Excel version 14. 4. 8 (Microsoft Corporation, Redmond, Washington), and R software version 3. 0. 1 (www.