dataesr/scientific-paragraphs-categorization huggingface dataset:
Quantitative RT-PCR For quantitative reverse transcription PCR (qRT-PCR) analyses of gene expression, we used Primer3 software to design specific primer pairs. Real-time PCR was performed with the Bio-Rad iQ system and iQ SYBR Green supermix (Bio-Rad), according to the manufacturer's instructions. The thermocycling protocol was as follows: denaturation at 94 C for 10 min, 40 cycles of amplification and quantification (95 C for 15 s, 60 C for 1 min with a single fluorescence measurement) and a melting curve program (55 C to 95 C, in increments of 0. 5 C). Each assay was performed at least in duplicate, with two independently prepared total RNA samples. The relative expression data obtained were analysed with the optimized amplification efficiency protocol derived from the ÁÁCt method, with the 5S gene used as a reference gene  (42).
The identification of a Rho-independent terminator beginning 240 bp downstream from the stop codon of the afaD gene suggests that the afaD mRNA has a long 3 0 UTR. Another Rho-independent terminator was found 25 bp downstream from the afaE stop codon. In a previous study, the $230-nt SQ109 sRNA gene was identified between the afaD and the afaE genes (6). This sRNA was renamed AfaR (afimbrial adhesin small RNA), as its location suggested a probable role in regulating the expression of the afa-8 gene cluster. BLASTN analysis against the GenBank database (24 January 2012) revealed that the sequence and synteny of the afaR gene were conserved in all sequenced afa-8 gene clusters from E. coli isolates (239KH89, AL511 and AL862 strains) but that this gene was absent from all other afa family gene clusters.
AfaR interacts with the afaD mRNA via an antisense mechanism Our working hypothesis is that AfaR is an antisense RNA that regulates AfaD production. We therefore used intaRNA software  (45)  to analyse in silico the likelihood of AfaR forming double-stranded antisense pairs with other afa-8 gene mRNAs. One significant putative antisense pairing was predicted between nucleotides U 92 to C 130 of AfaR and nucleotides G À37 to A +1 of the afaD mRNA 5 0 UTR, which contains the ribosome-binding site (RBS) (Figure  2A ). A second predicted pairing involved the 3 0 UTR of the afaD mRNA (residues T 490 to G 695 ), which perfectly matched the last 206 nt of the AfaR sequence (data not shown). This putative pairing was predicted on the basis of the presence of afaD and the 3 0 end of the afaR gene in the same DNA locus, but in opposite orientations.
The pairing of the afaR and afaD mRNAs is dependent on Hfq In E. coli, most antisense sRNAs make use of the Hfq protein to capture their mRNA targets  (46). We assessed the contribution of Hfq to the AfaR-mediated regulation of afaD mRNA in vivo by comparing the levels of afaD transcripts in the hfq-depleted strain JW4130-1 and the isogenic BW25113 strain, both carrying pILL1320. The relative level of afaA mRNA in the hfq mutant was one tenth that in the wild type, as shown by qRT-PCR, indicating that Hfq affected the transcription of the afa-8 gene cluster (data not shown). When the pTX381 plasmid (carrying the E. coli hfq gene) was introduced into the JW4130-1+pILL1320 strain, afaA mRNA levels were restored to wild-type values (data not shown). We therefore normalized gene expression with respect to afaA in qRT-PCR analyses, to evaluate the transcription-independent effects of Hfq (Figure  5A ).
Crystal data Hydrogen-bond geometry (A ˚, ). Symmetry code: (i) Àx þ 1; Ày þ 2; Àz. Data collection: APEX2  (Bruker, 2009) ; cell refinement: SAINT-Plus  (Bruker, 2009) ; data reduction: SAINT-Plus; program(s) used to solve structure: SHELXS97  (Sheldrick, 2008) ; program(s) used to refine structure: SHELXL97  (Sheldrick, 2008) ; molecular graphics: ORTEP-3 for Windows  (Farrugia, 2012) ; software used to prepare material for publication: PLATON  (Spek, 2009)  and publCIF  (Westrip, 2010).
Computing details Data collection: APEX2  (Bruker, 2009) ; cell refinement: SAINT-Plus  (Bruker, 2009) ; data reduction: SAINT-Plus  (Bruker, 2009) ; program(s) used to solve structure: SHELXS97  (Sheldrick, 2008) ; program(s) used to refine structure: SHELXL97  (Sheldrick, 2008) ; molecular graphics: ORTEP-3 for Windows  (Farrugia, 2012) ; software used to prepare material for publication: PLATON  (Spek, 2009)  and publCIF  (Westrip, 2010). where P = (F o 2 + 2F c 2 )/3 (Δ/σ) max < 0. 001 Δρ max = 0. 56 e Å -3 Δρ min = -0. 55 e Å -3.
Related literature (i) Àx þ 2; Ày þ 1; Àz. Data collection: APEX2  (Bruker, 2009) ; cell refinement: SAINT  (Bruker, 2009) ; data reduction: SAINT; program(s) used to solve structure: SHELXS97  (Sheldrick, 2008) ; program(s) used to refine structure: SHELXL97  (Sheldrick, 2008) ; molecular graphics: ORTEP-3 for Windows  (Farrugia, 2012) ; software used to prepare material for publication: PLATON  (Spek, 2009)  and publCIF  (Westrip, 2010).
3x10 -10 M -Rat) [176], [ 3 H ]ketanserin (Antagonist) (2x10 -10 -2. 9x10 -9 M)  [166, 198]  [ 3 H]LSD (Agonist, Full agonist) (2. 1x10 -9 M)  [198] , [ 3 H]mesulergine (5x10 -9 -1x10 -8 M), [ 3 [ 125 I]LSD, [ 3 H]5-CT [ 3 H]5-CT (Agonist), [ 125 I]SB258585 (Antagonist) (1x10 -9 M) [156], [ 3 H]LSD (Agonist, Full agonist) (2x10 -9 M) [125], [ 3 H]Ro 63-0563 (Antagonist) (5x10 -9 M) [126] [ 3 H]5-CT (Agonist) (4x10 -10 M) [207], [ 3 H ]SB269970 (Antagonist) (1. 2x10 -9 M)  [207] , [ 3 H]5-HT (Agonist, Full agonist) (1x10 -9 -7. 94x10 -9 M)  [118, 206] , [ 3 H]LSD (Agonist, Full agonist) (2. 51x10 -9 -3. 16x10 -9 M)  [206]  Comments: Tabulated pKi and KD values refer to binding to human 5-HT receptors unless indicated otherwise. Unreferenced values are extracted from the NC-IUPHAR database (www.
in altered striatal signalling [63]. S. P. H. Alexander et al. The Concise Guide to PHARMACOLOGY 2013/14: G Protein-Coupled Receptors. British Journal of Pharmacology (2013) 170, 1459-1581 Searchable database: http://www. guidetopharmacology. org/index. jsp Orphan GPCRs 1464 Full Contents of Concise Guide: http://onlinelibrary. wiley. com/doi/10. 1111/bph. 12444/full.
H. Alexander et al. The Concise Guide to PHARMACOLOGY 2013/14: G Protein-Coupled Receptors. British Journal of Pharmacology (2013) 170, 1459-1581 Searchable database: http://www. guidetopharmacology. org/index. jsp Orphan GPCRs 1465 Full Contents of Concise Guide: http://onlinelibrary. wiley. com/doi/10. 1111/bph. 12444/full.
-S. P. H. Alexander et al. The Concise Guide to PHARMACOLOGY 2013/14: G Protein-Coupled Receptors. British Journal of Pharmacology (2013) 170, 1459-1581 Searchable database: http://www. guidetopharmacology. org/index. jsp Leukotriene, lipoxin and oxoeicosanoid receptors 1523 Full Contents of Concise Guide: http://onlinelibrary. wiley. com/doi/10. 1111/bph. 12444/full.
Acknowledgements We are extremely grateful to the long list of collaborators who assisted in the construction of the Concise Guide to PHARMACOLOGY 2013/14 and to the website www. guidetopharmacology. org,, as well as to the Guides to Receptors and Channels. We are also extremely grateful for the financial contributions from the  British Pharmacological Society , the  International Union of Basic and Clinical Pharmacology  and the  Wellcome Trust  ( 099156/Z/12/Z ]), which support the website.
jsp Orphan GPCRs 1466 Full Contents of Concise Guide: http://onlinelibrary. wiley. com/doi/10. 1111/bph. 12444/full Comment GPR45 GPR45, Q9Y5Y3 - - Gi/Go -S. P. H. Alexander et al. The Concise Guide to PHARMACOLOGY 2013/14: G Protein-Coupled Receptors. British Journal of Pharmacology (2013) 170, 1459-1581 Searchable database: http://www. guidetopharmacology. org/index.
jsp Orphan GPCRs 1467 Full Contents of Concise Guide: http://onlinelibrary. wiley. com/doi/10. 1111/bph. 12444/full Nomenclature HGNC, UniProt Principal Comment transduction MRGPRG MRGPRG, Q86SM5 - - S. P. H. Alexander et al. The Concise Guide to PHARMACOLOGY 2013/14: G Protein-Coupled Receptors. British Journal of Pharmacology (2013) 170, 1459-1581 Searchable database: http://www. guidetopharmacology. org/index.
Searchable database: http://www. guidetopharmacology. org/index. jsp 5-Hydroxytryptamine receptors 1471 Full Contents of Concise Guide: http://onlinelibrary. wiley. com/doi/10. 1111/bph. 12444/full H. Alexander et al. The Concise Guide to PHARMACOLOGY 2013/14: G Protein-Coupled Receptors. British Journal of Pharmacology (2013) 170, 1459-1581 Nomenclature 5-HT2A receptor 5-HT2B receptor 5-HT2C receptor HGNC, UniProt HTR2A, P28223 HTR2B, P41595 HTR2C, P28335 Principal transduction Gq/11 Gq/11 Gq/11 Selective agonists (pKi) DOI (7. 4 -9. 2) [131,185,205] Ro 60-0175 (8. 3) [166], BW723C86 (7. 3 -8. 6) Ro 60-0175 (7. 7 -8. 2) [165-166], DOI (7. 2 -8. 6) [119,166,201], DOI (7. 6 -7. 7) [169,185,201],.
jsp Adhesion Class GPCRs 1478 Full Contents of Concise Guide: http://onlinelibrary. wiley. com/doi/10. 1111/bph. 12444/full Comment LPHN1 LPHN1, O94910 - LPHN2 LPHN2, O95490 - LPHN3 LPHN3, Q9HAR2 - , Q7Z7M1 -S. P. H. Alexander et al. The Concise Guide to PHARMACOLOGY 2013/14: G Protein-Coupled Receptors. British Journal of Pharmacology (2013) 170, 1459-1581 Searchable database: http://www. guidetopharmacology. org/index.
-S. P. H. Alexander et al. The Concise Guide to PHARMACOLOGY 2013/14: G Protein-Coupled Receptors. British Journal of Pharmacology (2013) 170, 1459-1581 Searchable database: http://www. guidetopharmacology. org/index. S. P. H. Alexander et al. The Concise Guide to PHARMACOLOGY 2013/14: G Protein-Coupled Receptors. British Journal of Pharmacology (2013) 170, 1459-1581 Searchable database: http://www. guidetopharmacology. org/index.
Searchable database: http://www. guidetopharmacology. org/index. jsp Metabotropic glutamate receptors 1530 Full Contents of Concise Guide: http://onlinelibrary. wiley. com/doi/10. 1111/bph. 12444/full S. P. H. Alexander et al. The Concise Guide to PHARMACOLOGY 2013/14: G Protein-Coupled Receptors. British Journal of Pharmacology (2013) 170, 1459-1581 Nomenclature mGlu4 receptor mGlu6 receptor mGlu7 receptor mGlu8 receptor HGNC, UniProt GRM4, Q14833 GRM6, O15303 GRM7, Q14831 GRM8, O00222 Principal transduction Gi/o Gi/o Gi/o Gi/o Endogenous agonists (pKi) - - - L-SOP (pIC50 6. 2-7. 2) [1224,1254].
Observations We have obtained more than 2000 high resolution (R 115000) and high signal to noise (S/N) spectra of our targets with the fiber-fed spectrograph Harps  (Mayor et al. , 2003)  at the La Silla 3. 6m telescope. In the case of β Pictoris, we used in addition to our data, a few data available in the archive and obtained with the same set-up. The spectra cover a wavelength range between 3800 and 6900 Å. During our runs, we usually recorded two consecutive spectra for each telescope pointing. In the follow-ing, one pointing will be refered to as one "epoch". As our main goal was to look for short period planets (100 days or less), we recorded several spectra of each target during each run whenever possible. In addition, we also recorded whenever possible spectra at two or three different epochs during one night, to identify possible high-frequency RV variations.
RV measurements The RV were computed using SAFIR, a tool dedicated to measure accurate RVs on fast rotators, described in  Galland et al. (2005) , and based on the Fourier interspectrum method developed by  Chelli (2000). SAFIR has been extensively used, in particular in RV surveys of rapidly rotating stars  (Lagrange et al. , 2009a). SAFIR input data are the extracted 2D spectra provided by the Data Reduction Software (DRS) pipeline, and the related wavelength calibration coefficients. SAFIR takes care of the blaze correction as well as bad-pixel correction  (Galland et al. , 2005). The errors associated to the individual RV measurements range between typically 1. 5 m/s for the slowly rotating stars to typically 30-40 m/s for the fast rotating stars. The values obtained for slowly rotating stars are similar to those obtained by the HARPS DRS; these values show that the instrument internal errors are very low.
1 ). Most of the data are compatible with a single spot with a period of 4. 88 days, as checked by fitting the RV data by a set of two signals with periods 4. 88 and 2. 44 days, which leads to a correlation between RV and BVS. However, the data recorded between JD 2454343 and JD2454348 lead to a more complex (RV,BVS) diagramme, with an additional, more inclined and off-centered contribution. The RV variations between JD 2454343 and JD2454348 are nonetheless still compatible with a period of about 4. 8 days. The comparison with spot simulations shows that the observed (RV, BVS) characteristics can be reproduced only when assuming a small star inclination, of the order of 10-20 degrees with respect to pole-on. If we do not consider the data taken between JD 2454343 and JD2454348, the observed RV are compatible with a spot with a projected surface of about 1% at 30 degrees from the star pole.
5 M Jup for periods of 100 days. Stars with intermediate RV jitters, which are the most representative of our sample, have much lower detection limits. For the well monitored HD105690, with a RV rms of 60 m/s, we obtain a detection limit of 1. 2 M Jup for a period of 100 days, and of 2 M Jup for periods around 800 days. HD183414, with RV rms of 60 m/s, has sub-Jupiter mass limits up to 100 days. Finally, HD181327, which has a lower RV jitter of 15 m/s, has a detection limit between less than 0. 1 M Jup and 0. 2 M Jup for periods up to 40 days, and 0. 3 M Jup for a period of 100 days. Note that the periods considered here are limited only by the time spans of the data available. Additional data would allow to increase the range of periods to be considered. We conclude that when enough and well-sampled data are available, it is possible to find giant planets down to very low masses, down to 1 M Jup or below, orbiting these active young late-type stars, up to long periods.
(2007)  and  Boisse et al. (2011). This is also seen in Appendix B in a number of examples. Departures from a linear correlation such as inclined "eightshapes" or even more complex structures can be observed. The amount of departure from a simple linear dependance depends on the star v sini , on the star orientation with respect to the line of sight sin i and on the spots parameters. We focused on the three active stars with the largest number of data and for which a good (RV, BVS) correlation trend (hereafter slope) could be determined, namely (with the measured RV jitter and v sini in parenthesis): HD141943 (235 m/s, 35 km/s), HD181327 (15 m/s, 17. 9 km/s) and HD183414 (67 m/s, 11. 1 km/s). The slopes of the (RV, BVS) correlation are indicated in Table  2. After correction of the RV using the (BVS, RV) correlation, the RV jitters are significantly reduced, as well as the detection limits (see Fig.
Towards a full exploration of young stars giant planet population We have shown that RV monitoring with an appropriate observing strategy and data analysis can allow to detect giant planets around young nearby stars despite their activity. The separations of detectable planets with RV techniques are however limited to a few AU. To get a complete view of planetary systems, it is necessary to complement RV data with other types of data: astrometric ones, e. g. Gaia, for typical separations of 2-5 AU  (Sozzetti, 2011) , and, above all, direct imaging data which can provide detection limits at much larger separations. Direct imaging is particularly interesting for young systems as the contrasts between young planets and their parent stars are more favorable than for older systems. The combination of these techniques therefore offers a unique opportunity to explore the giant planet population on a same class of stars.
We illustrate in this section the potential of the coupling of RV and AO deep imaging data, using the example of Harps and NaCo, and Sphere data. We consider three stars of our sample for which we have both Harps RV and NaCo imaging data, and which could be considered as prototypes for such complementary studies, namely HD183414, HD181327, and HD188228. The G-type star HD183414 is an example of medium activity-level star, with a jitter of 67m/s; it is located 35 pc away. The F-type star  HD181327, located at 51 pc, has a low activity level (jitter=15 m/s). The pulsating A-type star HD188228, located at 32 pc, has a jitter of 127 m/s (amplitude of 2 km/s). We plot in Fig. 9  the RV and imaging detection limits expressed in Jupiter masses for these three stars. The deep imaging detection limits are either those measured on NaCo data  (Rameau et al.
0 0. 2 2. 0. The complementarity of HARPS and NaCo in terms of separation ranges is obvious. However, gaps are still present. This is particularly true for HD183414, for which the available RV data are spread over 189 days only. On the contrary, for HD188288, which is located at a similar distance, there is an excellent overlap because we dispose of RV data spread over about 2000 days. Finally, the gap observed for HD181327 is smaller than that of HD183414 because the available RV data span is much larger (560 days), even though the star is located further away. We note the important impact of forthcoming imagers like SPHERE on the VLT: with inner working angles smaller than 0. 15"-0. 2", they will allow the detection of planets much closer to the stars than current imagers such as NaCo; this will fill the gap between RV data and imaging ones for stars closer than typically 30 pc; this will also significantly contribute to reduce the gap for stars located further away.
Concluding remarks We have shown that RV data allow the detection of giant planets around stars in close-by, young associations. Given the available data, we could explore different separations ranges, up to more than 2 AU for some stars of our sample. For low to moderately active stars, detection limits of a few Neptune masses are obtained. The best detection limits are obtained for low to moderate v sini in the range 10-30 km/s, which are generally observed for stars older than 30 Myr, although there are some exceptions. Early-type stars are generally pulsating, and averaging over the high frequency variations reduces considerably the achievable detection limits. Values well within the giant planet domain are obtained. Finally, we have illustrated the tremendous interest of coupling RV and deep AO data using Harps and NaCo data, and, even more, future Sphere data.
Acknowledgements. We acknowledge support from the  French CNRS  and the support from the  Agence Nationale de la Recherche  ( ANRBLANC10-0504. 01 ). We are grateful to the  ESO  staff for their help during the observations, and to the  Programme National de Planétologie (PNP, INSU). These results have made use of the SIMBAD astronomical database, operated at the  Centre de Donnes Astronomiques de Strasbourg, France , and NASAs Astrophysics Data System. We also thank  Gérard Zins  and  Sylvain Cètre  for their help in implementing the SAFIR interface.
g. , IMPROVE  (Chow et al. , 1993) , IMPROVE A, NIOSH  (Peterson and Richards, 2002; Chow et al. , 2007a) , and EUSAAR-2  (Cavalli et al. , 2010). A recent review of evolved carbon methods is given by  Chow et al. (2007b). The analytical protocol, however, is an essential part of the data and must be documented in metadata of the databases. While evolved carbon methods agree within < 10 %  (Schmid et al. , 2001)  or 0. 22 (±0. 12) µg m -3 (ten  Brink et al. , 2004)  in determining the total mass of particulate carbonaceous material, the selectivity of separating "elemental carbon" from the bulk of carbonaceous matter varies strongly with the analytical protocol  (Schmid et al. , 2001; Cavalli et al. , 2010; Chow et al. , 2011; Pio et al. , 2011)  and with impurities that may modify the oxidation behavior of the carbonaceous fraction  (Schmid et al.
Recommended terminology and related measurement methods In consideration of the inadequate definitions available in the literature, and in order to overcome this unsatisfying situation, we propose the following consistent terminology that is built along the line of targeted material properties. Table  2  summarizes the recommended terminology and includes related measurement methods and specific instruments. Reporting procedures for the World Data Centre for Aerosols are found at http://www. gaw-wdca. org/. Total carbon (TC) mass is used to describe the mass of all carbonaceous matter in airborne particles. Total carbon mass is a well-defined property that can be measured with precision better than 10 % by evolved carbon methods. Black carbon (BC) is a useful qualitative description when referring to light-absorbing carbonaceous substances in atmospheric aerosol; however, for quantitative applications the term requires clarification of the underlying determination.
It is recommended to report data from evolved carbon methods and aerosol mass spectrometry methods as EC. Additionally, data from Raman spectroscopy, which addresses the graphite-like structure of carbon atoms, should be reported as EC. Data from any future methods that address the amount of carbon atoms contained in the analyzed sample of particulate matter should also be reported as EC. Refractory black carbon (rBC) should be used instead of black carbon for measurements derived from incandescence methods. For methods based on laser-induced incandescence, like LII, SP2 and SP-AMS, it is recommended to report data as refractory black carbon, rBC, since these methods mainly address the thermal stability of the carbonaceous matter and require light-absorbing efficiency of the analyzed particulate matter.
Acknowledgements. The authors gratefully acknowledge valuable contributions from  R. Hitzenberger  ( Univ. Vienna, Austria ),  T. Kuhlbusch  ( Univ. Duisburg, Germany ),  E. Lewis  ( Brookhaven National Laboratory, USA ),  T. Onasch  ( Aerodyne Research, USA ), and  M. Schultz  ( Forschungszentrum Jülich ) during the preparation of the manuscript. Helpful comments and suggestions received during the review process from the referees  D. Baumgardner  and  H. Moosmüller , the editor  N. Donahue , as well as from  J. Schwarz ,  G. Močnik , and  O. Popovicheva  are acknowledged as well. The service charges for this open access publication have been covered by a  Research Centre of the Helmholtz Association. Edited by:  N. M. Donahue.
For meteoric water,  Dansgaard (1964)  explained successfully through the atmospheric distillation process the linear relation between the isotopic composition of precipitation and the local temperature at the precipitation site (the so-called "temperature effect") observed in many mid-to high latitude regions on Figures Earth. Given the magnitude of Arctic warming over the past decades, climate change should be recorded in the isotopic composition of meteoric waters (or natural archives) in boreal regions of the Northern Hemisphere. Back Close Full Unfortunately, isotope records of present-day boreal precipitation are sparse and discontinuous. For Russia,  Kurita et al. (2004)  have reviewed the modern isotope climatology. Data from 13 Russian monitoring sites sampled during the period 1996-2000 depict a negative zonal isotopic gradient over Russia, which is explained by the gradual rain-out of moist, oceanic air masses, which are transported towards and over Russia by westerly winds.
(2011)  have shown that the simulation of water isotopes in precipitation clearly improves with increased horizontal and vertical model resolution. Thus, for this study, we choose a horizontal model resolution of T63 in spectral space (horizontal grid size of approx. 1. 9 Back Close Full • × 1. 9 • ), and a vertical resolution of 31 levels on hybrid sigma-pressure coordinates. Local ECHAM5-wiso results for GNIP stations (discussed further below) were obtained by bilinear interpolation to the station coordinates. To ensure a most realistic simulation of present-day climate variability, the model is forced with prescribed yearly values of present-day insolation and greenhouse gas concentrations  (IPCC, 2000) , as well as with monthly varying fields of sea-surface temperatures and sea-ice concentrations according to ERA-40 and ERA-Interim reanalysis data  (Uppala et al.