dataesr/scientific-paragraphs-categorization huggingface dataset:
The parameters a, b, c n and d n of Eq. (1) were fitted to zonal monthly means of 10 • latitude bands of the MIPAS ozone time series covering 1 July 2002 to 8 April 2012 to assess the linear variation during that period. An example of the fit is shown in Fig. 1 , showing the ozone monthly means as well as the fit and linear variation at 0 to 10 • N and 30 km altitude. The bias between the two data blocks is quite obvious and it is reasonably accounted for during the fit process. A semi-annual oscillation and a QBO signal can also be identified in the data, which are satisfactorily reproduced by the fit. Before analysing derived trends, a potential drift in MI-PAS ozone data must be identified and accounted for. To estimate the drifts against other instruments, the difference of MIPAS minus the reference instrument was calculated for each data point and the related time series were fitted by the same method as just introduced.
The drifts are far smaller than -0. 3 ppmv decade -1 at lower altitudes and seem to become slightly more negative with altitude. At shorter wavelengths, a larger ageing effect is predicted. This explains the sudden increase of the effect above 35 km. In the data version used, ozone lines of the MIPAS AB band (1120-1170 cm -1 ) were used in addition to the A band (685-970 cm -1 ) above 33 km, while below only lines from the A band were used.
Coincidence criteria To account for varying data coverage, two different coincidence criteria were used, depending on the availability of data from the respective instrument. For instruments with dense data coverage, measurements which are closer than 250 km radial spatial distance and 6 h temporal difference to the MIPAS measurements are taken into account. Weaker criteria of 1000 km and 24 h were applied to instruments with sparser coverage and/or fewer measurements to still obtain a sufficiently large number of measurements to compare in the drift analyses. In both cases the distance is calculated relative to the nominal geolocation of the MIPAS profile, which is the tangent point of the 30 km tangent altitude limb view. Table  2  summarizes these criteria for the different instruments and lists the total number of profiles which matched these criteria.
Application of the MIPAS averaging kernel: on an altitude grid In most cases the vertical resolution of the reference instrument was better than that of MIPAS in certain altitude regions. For the lidars this region is rather the lower end of the profile. Their vertical resolution is certainly not better than that of MIPAS above 40 km, but as already mentioned measurements above approximately this altitude should be treated with care. The reason for applying the MIPAS averaging kernels is primarily the vertical resolution peak around 30 to 35 km in version V5R_O3_220 and V5R_O3_221 of MIPAS data from the second time period of the MIPAS mission. In the case of ACE-FTS the worst-case assumption on the vertical resolution, based on the field of view, is about 3-4 km, which is very similar to that of MIPAS.
Application of the MIPAS averaging kernel: on a pressure grid As mentioned above, the conversion of ozone profiles from a pressure grid to an altitude grid relies on ECMWF temperatures which might have a drift in themselves. This would cause an artificial drift in ozone at a given altitude. In order to avoid related problems, for instruments whose native altitude coordinate is pressure (MLS, ACE-FTS), the drift analysis has also been performed on pressure coordinates. Even for MIPAS, whose profiles are usually reported on an altitude grid, the representation on a pressure grid is more robust, since the MIPAS altitudes are based on the hydrostatic approximation involving one ECMWF data triple (altitude, pressure, temperature) per profile. While the altitude resolution of MIPAS and ACE-FTS ozone profiles is comparable over a wide altitude range, a direct comparison is justified (cf.
Acknowledgements. The retrievals of IMK/IAA were partly performed on the HP XC4000 of the  Scientific Supercomputing Center (SSC) Karlsruhe  under project grant MIPAS. IMK data analysis was supported by  DLR  under contract number  50EE0901. MIPAS level-1b data were provided by  ESA. We acknowledge support by  Deutsche Forschungsgemeinschaft and Open Access Publishing Fund of Karlsruhe Institute of Technology. The  Atmospheric Chemistry Experiment (ACE) , also known as SCISAT, is a Canadian-led mission mainly supported by the  Canadian Space Agency and the Natural Sciences and Engineering Research Council of Canada. Work at the  Jet Propulsion Laboratory, California Institute of Technology , was carried out under contract with the  National Aeronautics and Space Administration. The service charges for this open access publication have been covered by a  Research Centre of the Helmholtz Association.
We present here the results of this transit search. Unfortunately, we did not detect any other transiting planets. Assuming that GJ 1214 hosts a habitable planet larger than Mars that has an orbital period smaller than 20. 9 days, our global analysis of the whole Spitzer dataset leads to an a posteriori no-transit probability of ∼ 98%. Our analysis allows us to significantly improve the characterization of GJ 1214 b, to measure its occultation depth to be 70±35 ppm at 4. 5 µm, and to constrain it to be smaller than 205 ppm (3-σ upper limit) at 3. 6 µm. In agreement with the many transmission measurements published so far for GJ 1214 b, these emission measurements are consistent with both a metal-rich and a cloudy hydrogen-rich atmosphere.
2004 , Demory et al. 2011 , 2012) , and its heliocentric orbit making possible the continuous observation of most of the stars during weeks or months. The continuous observation of GJ 1214 over three weeks would probe the entire HZ of the star assuming an outer limit of 1. 37 au for the HZ of the Sun  (Kasting et al. 1993 ) and using an inverse-square law in luminosity to extrapolate the outer limit for GJ 1214 (0. 0033L ⊙ , C09) to be ∼0. 08 au. A survey of this kind should be sensitive to planets as small as Mars for a single transit, or even smaller for multiple planets. This was the main concept of our Warm Spitzer program 70049 for which we present here the results of the transit search. We also present the results of the global modeling of the entire GJ 1214 Spitzer dataset supplemented by ground-based data.
This extensive dataset includes 21 transits and 18 occultations of GJ 1214 b, allowing us to derive strong constraints on the planet's radius and emission at 3. 6 µm and 4. 5 µm, and on the periodicity of its transits. Our detailed study of the Warm Spitzer transits of GJ 1214 b, and its implications for the transmission spectrum of the planet were presented in a separate paper  (Fraine et al. 2013; hereafter F13). Our data and their reduction are described in Sect. 2. Our global analysis is presented in Sect. 3, and our search for a second planet is described in Sect. 4. We discuss our results in Sect. 5 and give our conclusions in Sect. 6.
Spitzer photometry In the context of our program 70049, Spitzer monitored GJ 1214 continuously from 2011 April 29 03h36 UT to 2011 May 20 01h27 UT, corresponding to 20. 9 days (502 hr) of monitoring and to the outer limit of the star's HZ (G11). Practically, the program was divided into Astronomical Observation Requests (AORs) of 24 hr at most, some of them being separated by a repointing exposure. As mentioned in F13, some of the data were clouds in the atmosphere of GJ1214 b. Still, its composition remains unknown. irretrievably lost during downlink to Earth because of a Deep Space Network (DSN) ground anomaly. These lost data correspond to 42 hr of observations acquired between 12 and 14 May. The surviving data consist of 12383 sets of 64 individual subarray images divided in 20 AORs gathered by the IRAC detector at 4.
5 µm with an integration time of 2 s, and calibrated by the Spitzer pipeline version S18. 18. 0. In compensation for the lost observations, we were granted 42 new hours of observation that took place from 2011 November 06 11h54 UT to 2011 November 08 5h47 UT. We chose to perform these new observations in the 3. 6 µm channel, mostly to assess the dependance of the transit depth on the wavelength. These data were grouped into two AORs and consist of 1166 sets of 64 individual subarray images obtained here too with an integration time of 2 s, and calibrated by the Spitzer pipeline version S19. 1. 0. Our Spitzer data are available on the Spitzer Heritage Archive database 3. We complemented our data set with all the other Spitzer data publicly available on the Spitzer Heritage Archive database for GJ 1214 b, including two transits observed respectively at 3.
6 µm and 4. 5 µm in the program 542 (PI  Désert, Désert et al. 2011) , and six occultations (three at 3. 6 µm and three at 4. 5 µm) observed in the program 70148 (PI Madhusudhan). The logs of our photometric data set are given in Table  1. We used the following reduction strategy for all the Spitzer data. We first converted fluxes from the Spitzer units of specific intensity (MJy/sr) to photon counts, and then we performed aperture photometry on each subarray image with the IRAF/DAOPHOT 4  software  (Stetson, 1987). We tested different aperture radii and background annuli, obtaining better results with an aperture radius of 2. 5 pixels and a background annulus extending from 11 to 15. 5 pixels from the point-spread function (PSF) center. For the first two 3. 6 µm AORs taken in program 70148, we obtained a better result with an aperture of 2.
TRAPPIST variability photometry In addition to the seven transits mentioned above, TRAPPIST monitored GJ 1214 regularly from 2011 April 19 to 2011 May 19. These observations consisted of blocks of a few exposures taken in the Ic filter, their goal being to assess the global variability of the star during the Spitzer survey. The resulting photometry was not used as input data in our global analysis described in the next section. The reduction procedure was similar to the one used for the transits. Six comparison stars were carefully selected on the basis of their stability during the covered month. For each comparison star, we determined a red noise value on a timescale of 24 hr by following the procedure described in  Gillon et al. (2006) , as was done by  Berta et al. (2011)  in their study of the variability of GJ 1214.
6 µm or 4. 5 µm, t is the time, T 0 and P are the time of inferior conjunction and the orbital period of GJ 1214 b, and the parameters A i and O i are the semi-amplitude and phase offset of the phase curve. As no phase effect could be detected with this simple function (see below), we did not test more sophisticated phase curve models. After election of the baseline model for each light curve, we performed a preliminary global MCMC analysis of our extensive data set, following the procedure described in  Gillon et al. (2012). A circular orbit was assumed for GJ 1214 b. The parameters that were randomly perturbed at each step of the Markov chains (called jump parameters) were -the stellar mass M * , assuming a normal prior distribution corresponding to 0. 176 ± 0. 009M ⊙ , the value and error recently presented by Anglada-Escudé et al.
The rms of the residuals was compared to the mean photometric errors, and the resulting factor β w were stored; β w represents the under-or overestimation of the white noise of each measurement. The red noise present in the light curve (i. e. , the inability of our model to represent the data perfectly) was taken into account as described by  Gillon et al. (2010) , in other words, a scaling factor β r was determined from the rms of the binned and unbinned residuals for different binning intervals ranging from 5 to 90 minutes, the largest values being kept as β r. In the end, the error bars were multiplied by the correction factor CF = β r × β w. The values of β w and β r derived for each light curve are given in Tables  1  and 2. One can notice that most β w are smaller than 1. For Spitzer, each of our measurements is the mean of 64 individual measurements, and our selected photometric errors are the errors on this mean.
12 and √ e sin ω = -0. 10 ± 0. 17 deduced from the analysis of the new HARPS dataset. The corresponding distributions for e cos ω and e sin ω are, respectively, 0. 00 ± 0. 02 and -0. 02 +0. 03  -0. 06. The results of this second analysis are given in Table  3  (MCMC 2). It can be seen that the derived parameters for the system are in good agreement with the ones deduced under the circular orbit assumption, but some are less precise because the uncertainties on e and ω propagate to the parameters a/R * , ρ * , R * , and R p. We note, however, that our adopted results are the ones from the analysis assuming a circular orbit, based on the absence of observational evidence for a significant eccentricity (∆BIC = -20 in favor of the circular model).
Analysis allowing for transit timing variations In a final MCMC analysis, we let the timings of the transits present in our Spitzer + TRAPPIST dataset be jump parameters. Our goal was to benefit from the strong constraints brought by the global analysis on the transit shape and depth to reach the highest possible sensitivity on possible transit timing variations (TTVs,  Holman & Murray 2005 , Agol et al. 2005 ) due to another unknown object in the system. In this analysis, we assumed a circular orbit for GJ 1214 b, and normal prior distributions based on the results of our adopted analysis (Table  3 , MCMC 1) for the jump parameters P and T 0. Table  4  presents the derived transit timings. A linear regression using these timings and their epochs as input led to the following transit ephemeris: 2454980.
The accuracy of our derived parameters The values deduced in our adopted analysis (MCMC 1 in Table  2 ) for the physical parameters a/R * and i that define the tran-Fig. 6. T op: Transit search periodogram obtained from the analysis of the photometric residuals (Sect. 4). Bottom: Spitzer residuals folded on the ephemeris of the most significant transit signal found by our transit search algorithm (P=0. 4157 day), and binned per intervals of 15 mins. sit shape (see, e. g. , Winn 2011) are in good agreement with the values reported in the GJ 1214 b detection paper (C09), but disagree with several values reported afterwards and based on high-precision photometry from the ground  (Berta et al. 2011)  or from space  (Berta et al. 2012). Notably, the agreement with our own results presented in F13 is rather poor, while both analyses were based on the same dataset.
9 d) in search of a planet as small as Mars. Because of a DNS failure, we could not probe the entire inner HZ, but still we covered about 94% of it. After having presented in a first paper (F13) our detailed study of the Spitzer transits of GJ 1214 b, and its implications for the transmission spectrum of the planet, we have reported here the results of our transit search and of our global analysis of a very extensive photometric dataset combining all the Spitzer data acquired for GJ 1214 to new ground-based transit light curves. Unfortunately, we did not detect a second transiting planet. Assuming that GJ 1214 hosts a habitable planet larger than Mars and with P < 20. 9 d, our global analysis of the whole Spitzer dataset leads to an a posteriori no-transit probability ∼ 98%. Still, our analysis allowed us to significantly improve the characterization of GJ 1214 b, notably by detecting at 2-σ its 4.
number PBGEP2-145594. TRAPPIST is a project funded by the FNRS under grant FRFC 2. 5. 594. 09. F, with the participation of the Swiss National Science Fundation (SNF). The TRAPPIST team is grateful to Gregory Lambert and to the ESO La Silla staff for their continuous support. N. Madhusudhan acknowledges support from Yale University through the YCAA postdoctoral prize fellowship. A. Zsom was supported by the German Science Foundation (DFG) under grant ZS107/2-1.
Acknowledgements. This work is based in part on observations made with the  Spitzer Space Telescope , which is operated by the  Jet Propulsion Laboratory, California Institute of Technology , under a contract with  NASA. This research has made use of the  NASA Exoplanet Archive , which is operated by the  California Institute of Technology , under contract with the  National Aeronautics and Space Administration  under the  Exoplanet Exploration Program. M. Gillon  and  E. Jehin  are Research Associates of the  Belgian Fonds National de la Recherche Scientifique (FNRS). L. Delrez  is FRIA PhD student of the  FNRS. A. H. M. J. Triaud  is a  Swiss National Science Foundation  fellow under grant.
T he pulp of the fruit produced by the açaí palm (Euterpe olera- cea), endemic to eastern Amazonia, is a staple of the diet of a considerable part of the local population where it is consumed in the form of a raw paste. The açaí fruit has a rich microbiota, which plays a role in the spontaneous fermentation of the fruit during transport, notably lactic fermentation  (1). We have isolated from the mesocarp of the açaí fruit a strain of Lactococcus lactis, AI06, a lactic acid bacterium with Generally Recognized as Safe (GRAS) status. L. lactis presents genomic diversity and can be found as endophytes in some plant species but is also an important species for the dairy industry, where it is used for starter cultures. Most L. lactis genomes available in GenBank are dairy culture strains, with the exception of the strains KF147 (CP001834) isolated from mung bean sprouts (2), IO-1 (AP012281) isolated from a kitchen sink (3), CV56 (CP002365) isolated from human vaginal microbiota (4), and NCDO 2118 (CP009054) isolated from frozen peas.
67 Mbp; N 50 , 125. 0 kbp; N 90 , 31. 2 kbp; max length, 365. 3 kbp). These contigs were then automatically annotated using the X-base server (http:// www. xbase. ac. uk/annotation/) which uses Glimmer  (7)  for gene prediction, and tRNAscan-SE  (8)  and RNAmmer (9) for RNA prediction. Contig ordering and synteny evaluation was carried out using Gepard  (10)  with the L. lactis KF147 genome (CP001834) as reference. Redundant contigs with identical annotation were discarded, a scaffold was built, and gaps were closed by reiteratively aligning reads to contig ends as described previously  (11). L. lactis AI06 presented a chromosomal inversion between coordinates 900 kbp and 1,633 kbp relative to KF147. Read coverages at these points were Ͼ15ϫ. Manual curation of all features was carried out by blasting against the GenBank NR database.
We identified 2,197 protein coding sequences, 61 tRNA genes, and 19 rRNA genes in L. lactis AI06. Further analysis of this genome will shed light on the genes necessary for an endophyte lifestyle and on the potential of this strain as a probiotic. Nucleotide sequence accession number. The complete genome of L. lactis strain AI06 has been deposited in DDBJ/EMBL/ GenBank under the accession no. CP009472.
ACKNOWLEDGMENTS This work was supported by the  Centro de Inovações Tecnológicas do Instituto Evandro Chagas ,  SVS/MS, Ananindeua, Pará, Brazil. J. A. M. was supported by  Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)  grant  2013/12107-4. P. J. P. -C. was supported by  FAPESP  grant  2012/20915-0. We have no conflicts of interest to declare.
DNA methylation is negatively associated with transposon expression, but not gene expression We next examined the relationship between DNA methylation and expression using an RNA-seq dataset generated from the same biological samples (FLM and FB) used for the methylation analysis. Since gene methylation is generally low, we expected a weak association with gene expression. Not surprisingly, we found essentially no correlation between gene (promoters and gene bodies) methylation and gene expression (Figure  S8  in Additional file 1). In contrast, we found a significant negative correlation between TE expression and TE methylation levels in both FB and FLM (Figure  2 ; Figure  S9  in Additional file 1), where highly expressed TEs were found to be significantly less methylated than lowly expressed TEs.
Phylogenetic analysis Predicted amino acid sequences of putative DMTs from bacteria, viridiplanta and metazoa  [7]  and from a susbset of fungi were used for phylogenetic analysis. Accession numbers are reported in the Figure  7  legend, except for the sequences from Aspergillus spp. (A. nidulans (GenBank: EAA58167. 1), Aspergillus fumigatus (GenBank:EDP47610. 1), Aspergillus niger (GenBank:XP_001396716. 1), Aspergillus oryzae (GenBank:BAE61916. 1); viridiplanta (A. thaliana MET1 (GenBank:NP_199727) and CMT3 (GenBank: NP_177135. 1), Oryza sativa MET1 (GenBank:B1Q3J6. 1) and CMT3 (GenBank:NP_001049442. 1), Selaginella moellendorffii MET1 (GenBank:EFJ35559. 1), Physcomitrella patens MET1 (GenBank:XP_001758167), Chlorella variabilis MET1 (GenBank:EFN59320. 1) and CMT3 (GenBank: EFN55234. 1)); metazoa (Mus musculus DNMT1 (GenBank: P13864), puffer fish DNMT1 (Swiss-Prot:Q4RHE4), Apis mellifera Dnmt1 (GenBank:XP_001122269.
1)); and bacteria (Escherichia coli EcoO109IM (GenBank:BAH79224. 1), Azoarcus sp. BH72 (GenBank:YP_932275. 1)). The third putative DMT of A. immersus (Masc3) was retrieved at the US Department of Energy Joint Genome Institute [55] by a BLASTP search using Masc1 and Masc2 as queries. Conserved domain composition was deduced by an RPS-BLAST search  [56]. Phylogenetic analysis was performed with MEGA version 5  [57]. Amino acid sequences of predicted RID-like proteins and DMT catalytic domains were aligned with MUSCLE; maximum likelihood, using a substitution model with evolutionary rate variation among sites (Gamma distributed with five categories), was employed for phylogeny reconstruction. A parallel phylogenetic analysis, which yielded an essentially identical tree topology for both RID-like and DMT-like proteins, was conducted with neighbor-joining using uniform rates among sites.
Acknowledgments This work was supported by grants from the  Fondazione Cariparma  and the  Ministry of Education, University and Research (MIUR)  to SO and by a grant from the  Institute for Genomics and Proteomics at UCLA  to MP. We thank  Michael Freitag  ( Department of Biochemistry and Biophysics, Oregon State University, Corvallis, USA ) for insightful discussions and two anonymous reviewers for constructive criticism.
© 2014 Fend et al. ; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons. org/licenses/by/4. 0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The Creative Commons Public Domain Dedication waiver (http:// creativecommons. org/publicdomain/zero/1. 0/) applies to the data made available in this article, unless otherwise stated.
Several epidemiological studies have been evaluating the correlation between HB vaccination and MS in adults for a decade. Most of these publications found the absence of a link  [2] [3] [4] [5] [6]  or a slightly increased risk, but not sufficiently significant on the statistical level  [7] [8] [9]. However, different opinions have also been formulated. A study aiming at quantifying underreporting in Fourrier's article  [8]  was conducted by D. Costagliola on request of the French pharmacovigilance. This unpublished study showed by the ''capture-recapture'' method that the real number of MS cases linked to HB vaccine was 2-2. 5 higher than the officially registered number  [10]. This additional calculation makes Fourrier's publication  [8]  clearly significant. Another case-control epidemiological study was conducted to evaluate serious post-vaccination adverse events registered in the United States through a spontaneous reporting system in the VAERS database.