dataesr/scientific-paragraphs-categorization huggingface dataset:
Improvement After Optimization Figure  3  shows the impact of assimilating the different FAPAR data sets on the simulated fluxes and FAPAR for scenarios A3 (phenology parameters, P3) and A2 (extended parameters, P2). In all cases, apart from scenario A2 applied only to in situ FAPAR measurements, the seven phenological parameters of Table  1  have been optimized (section 2. 3. 3). The assimilation significantly corrects the discrepancies in the magnitude between the prior model and the various FAPAR products, as measured by the decrease of the RMSEs (around 40% in most cases). However, some features can still not be represented after optimization. For Fontainebleau, the model underestimates the measured in situ FAPAR values in winter. ORCHIDEE also remains unable to reproduce the very high in situ FAPAR values in the summer measured at the two sites, the change in magnitude being capped by the imposed maximum vegetation fraction (90% at Puechabon).
Concerning the agreement of the model to the flux data (NEE and LE), assimilating FAPAR produces contrasting results depending on the product used (in situ or satellite), the fluxes (NEE or LE), the site considered, and the set of parameters optimized. The change in the simulated fluxes is mainly proportional to the difference in magnitude between the prior ORCHIDEE FAPAR simulations and the observations. For the LE, the assimilation of satellite-derived FAPAR improves the fit to the flux data at both sites, while using in situ FAPAR degrades it. This is because the necessary decrease of leaf area (section 3. 4. 2) for fitting SPOT or MERIS FAPAR observations induces a decrease in the modeled LE. The impact on the NEE may be more or less detrimental depending on the FAPAR data set used. The use of in situ FAPAR does not result in much change of NEE at either site.
For Fontainebleau, the use of additional model parameters related to photosynthesis (scenario A2 with set of parameters P2) leads to an overestimation of the carbon uptake in summer and hence increases the model-data mismatch. Only marginal changes are observed in winter after the assimilation of in situ FAPAR because the NEE is principally driven by soil and litter respiration not impacted by FAPAR data. There is only a small improvement for Puechabon early in the season. Fitting satellite FAPAR results in an even stronger negative impact on the simulated NEE than in situ data. Especially, the assimilation of MERIS FAPAR with low values during summer time largely degrades the fit to the NEE. The apparent inconsistency between FAPAR products in summer and the magnitude of NEE measured on the site will be further discussed in sections 4.
Normalization of FAPAR Data Given the issues described above, this study proposes a better use of FAPAR products by only constraining the timing of the growing season through the optimization of a limited set of phenological parameters (consistent with  Knorr et al. [2010] ). For deciduous canopies with pronounced seasonal cycle, we found that the assimilation conducted with normalized FAPAR time series still improves the model-data agreement with respect to FAPAR and mostly reduces the degradation of the model-data fit for NEE and LE. In addition, the normalization of the FAPAR time series decreases the differences between the different satellite products and reduces the strong uncertainties attached to the magnitude of the FAPAR data. parameters that improved the model-data fit with respect to each data stream.
Note that we performed an additional test at Fontainebleau using original FAPAR data in the joint assimilation which resulted in an improvement similar to that obtained when using normalized FAPAR values (results not shown). This indicates that different sets of parameters, within physical ranges, are able to provide a reasonable fit to the observed NEE and to different LAI values (constrained through FAPAR). Optimizing the model with only one data stream may thus potentially lead to non-optimal parameters. The fit resulting from the joint assimilation (in terms of RMSE) is a compromise between the cases where the two data streams are considered independently and always results in an improvement of the model. Satellite FAPAR products helped to better characterize some critical parameters controlling the phenology of ORCHIDEE (turnover of the leaves, time of leaf onset), parameters that are less constrained by NEE/LE data alone.
The differences in the estimated parameter values (in particular the phenology parameters) when the FAPAR and flux data are combined in the assimilation, as compared to when they are assimilated independently, reveals some levels of complementarity between the data streams. This result highlights the importance of combining several data streams. It may strongly impact the model predictions as different parameter sets will lead to different carbon balance trajectories in the future. Given the correlations between the model parameters, a joint assimilation seems preferable to a stepwise approach which may penalize the retrieval of parameters unless these correlations are properly accounted for. The benefit of combining FAPAR products with flux measurements was confirmed by the temporal validation experiments where the optimized model was evaluated with respect to ancillary flux data outside the calibration period.
Conclusion In the context of increasing availability of in situ flux data and satellite observations of vegetation activity, we have investigated the benefit of combining the two data streams in a data assimilation framework for optimizing the parameters of the ORCHIDEE process-based vegetation model. In doing so, we have highlighted the main difficulties that need to be worked out before being able to fully exploit such remote sensing products. The upcoming new generation of satellite observing systems, including the ESA Sentinel-2 mission, will monitor the Earth's surface at both spatial and temporal high resolutions and should therefore permit significant improvements of our knowledge of the vegetation dynamics. However, the uncertainty of derived products such as FAPAR or LAI may limit the potential benefits of future satellite observations.
Reducing the observation uncertainty becomes even more crucial for evergreen vegetation with low seasonality as the magnitude of the satellite products becomes the only information that can be used in an assimilation framework. We need to prepare advanced land surface data assimilation systems capable of assimilating these new satellite data, in combination with in situ local measurements, and other data streams (such as atmospheric CO 2 concentration data, biomass data, and surface temperature). The complementarity of FAPAR and flux data demonstrated in this study raises hopes that current process-based models are capable of the task, but we must see whether the result holds for more ecosystems and a wider array of data.
Acknowledgments The authors are very grateful to  Serge Rambal  and  Jean Marc Ourcival  for providing the in situ flux and FAPAR measurements at Puechabon and to  Jean-Yves Pontallier  and  Guerric le Maire  for the data at Fontainebleau. The satellite data presented in this article are available from the authors on request. In situ measurements can be obtained upon request to the persons listed above. This study was partly financed by the  European Space Agency  under the  CAMELIA  project ( 20050/06/NL/HE ). P. J. Rayner  is in receipt of an  Australian Professorial fellowship  ( DP1096309 ). The authors thank the computer team at  LSCE  for the computing support and resources. Finally, the author would like to thank two anonymous reviewers and the Editor ( A. Desai ) for their comments, questions, and suggestions, which significantly contributed to improve this paper.
ODB1-dependent introns are two out of several hydrolytically spliced introns in mitochondria To further elucidate the role of ODB1 in mitochondrial transcript splicing we investigated common properties of the two introns whose excision was affected in odb1 mutants. Both introns are classified as group II introns  (35). Aligning their sequences showed 86% sequence identity in structural domains dV and dVI (Figure  3 ); neither intron displayed a comparable degree of identity with any other mitochondrial intron in these domains according to BLAST searches (http://blast. ncbi. nlm. nih. gov). Sequence identity between nad1 intron 2 and nad2 intron 1 in domains dV and dVI as well as in other domains and the intron structural core has been previously noted in the genus Oenothera, and a common evolutionary origin of the two introns has been proposed  (44).
FUNDING Centre National de la Recherche Scientifique ;  French National Research Agency  ( ANR-07-Blan-0207-01 ), the  Ministère de l'enseignement supérieur et de la recherche (program 'Investissements d'Avenir' LABEX ,  ANR-11-LABX-0057  MITOCROSS); Humboldt University (Gleichstellungsfonds). Funding for open access charge: Humboldt University, CNRS.
1. 2 AN. 18, Village Neuf, France). The GSS was constituted, from upstream to downstream, by a filter, a 1 m length -5. 3 mm diameter tube, the IRGA (LI-7200, LI-COR, Lincoln, Nebraska), a mass flow controller (Vögtlin MC-50SLPM-D-I/5M-5IN Gaz, Aesch, Switzerland) driven by a computer, a buffer in order to dampen pump fluctuations and, finally, the pump. Concentrations measured by the IRGA were sampled at 20 Hz and the data were collected and stored on a computer. Experiments were repeated four times, one time without filter and three times with different filters: ACRO 50 1 µm (PALL, Port Washington, NY, USA), Swagelok FW 2 µm (Swagelok, Solon, OH, USA) and PALL Open Face filter holder with 2 µm membrane (PALL, Port Washington, NY, USA). In each experiment, one filter was installed at the system inlet and the mass flow was varied step by step from 1 to 28 L min -1.
Immunoblots were scanned, and the signals were quantified using ImageJ software. Cellular models and treatments. Hepatocytes from mouse liver were isolated by a two-step collagenase procedure, as we previously described. 46 solated cells were resuspended in Medium I (Williams' Medium E) supplemented with 10% fetal bovine serum (PAA Laboratories, Villacoublay, France), 100 units/ml penicillin, 100 μg/ml streptomycin, 2 mM L-glutamine, 0. 02 UI/ml insulin (Humulin, Lilly, Fegersheim, France). Viability was evaluated by trypan blue exclusion (Sigma, St. Louis, MO, USA). Hepatocytes were incubated for 4 h at 37 °C in a humidified atmosphere with 5% CO 2. For culture, Medium I was renewed with Medium II (a fetal bovine serum-free Medium I, supplemented instead with 0. 5% bovine serum albumin). Hepatocytes were also pretreated with TUDCA (500 μg/ml) for 48 h or with Z-YVAD-fmk (25 μM) for 1 h in Medium II.
Acknowledgements. This work was supported by grants from  INSERM (France) , the  University of Nice , the  Programme Hospitalier de Recherche Clinique  ( Centre Hospitalier Universitaire Nice ) and charities ( Association Française pour l'Etude du Foie (AFEF)/Aptalis ,  Société Francophone du Diabète (SFD/MSD) ,  Benjamin Delessert ,  Fondation Recherche Médicale (FRM)  to BBM;  EFSD/Lilly European Diabetes Research Programme, SFD ,  SFD/Roche Pharma , AFEF/LFB to PG). This work and CL were funded by the  French Government (National Research Agency, ANR)  through the  'Investments for the Future' LABEX SIGNALIFE: program  reference # ANR-11-LABX-0028-01. We thank  Dr. Sandrine Marchetti  and  Dr. Jean-Louis Nahon  for scientific discussions. We thank the  C3M Animal Facility team  for their assistance with animal care.
urticae genome. All sequencing reads were collected with standard Sanger sequencing protocols on ABI 3730XL capillary sequencing machines at the Department of Energy Joint Genome Institute (DOE-JGI; Walnut Creek, CA, USA). The final assembly contains 640 scaffolds that cover 89. 6 Mb of the genome with a contig L50 of 212. 8 kb and a scaffold L50 of 3. 0 Mb  [10]. A total of 8,435 regions ranging from 413 to 720 bp were identified. Among them 546 and 1389 included di and tri-nucleotide repeats respectively (as analysed using QDD  [12] ). The exact position of the selected sequences was recorded according to the whole genome sequence from individual scaffolds of the T. urticae (London strain) genome available through GenBank under accession numbers HE587301 to HE587940 (see also http://bioinformatics.
psb. ugent. be/orcae/overview/ Tetur). Primers design was done with the program QDD  [12]. Sequences longer than 80 base pairs (bp) and containing perfect microsatellites of at least five repetitions for any motif of 2-6 nucleotides were selected for further analyses. PCR primers were designed using QDD with the following stringent criteria: (1) target microsatellites had at least five repetitions, (2) length of PCR products were between 90 and 300 bp, (3) flanking regions did not contain either any homopolymer stretch of more than four bases or any di-hexa base pair motifs of more than two repetitions, (4) annealing temperatures of primer pairs were optimized to 55°C and (5) microsatellites were not compound or interrupted. We selected a subset (n = 54) of sequences for which primers were designed for PCR amplification.
Acknowledgements We thank  Stephane Rombauts  from the  VIB Department of Plant Systems Biology, UGent, Belgium , for providing files with repeated motifs sequences and  Miodrag Grbic  from the  University of Western Ontario, London, Canada , for his contribution as leader of the T. urticae whole genome project. We thank  Elodie Flaven  for technical advice at an early stage of project. Data used in this work were (partially) produced through molecular genetic analysis technical facilities of the  labex "Centre Méditerranéen de l'Environnement et de la Biodiversité " Funding was provided by the  French Agence Nationale de la Recherche , grants to MN:  ANR 2010 BLAN 1715 02  and  ANR-14-JFAC-0006-01. This work beneficiated from information retrieved from the genome and transcriptome sequencing projects which were funded by the  Government of Canada through Genome Canada  and the  Ontario Genomics Institute  ( OGI-046 ),  JGI Community Sequencing Program  grant  777506  to  M.
Here we present a new spatially-explicit, regional-scale, reconstruction of the paleofire history in eastern North America covering the last 7000 years. From this reconstruction, we differentiate the role of human activities, climate and vegetation in relation to regional biomass burning at millennial time-scales. Regional biomass burning was inferred from 64 well-dated lacustrine charcoal records (Fig. 1  and Supplementary Fig. 1 ) and compared with (i) climate reconstructions (temperature and precipitation) issued from two general circulation models (HadCM3 and CCSM3 experiments), (ii) new quantitative reconstructions of vegetation biomass for eastern North America based on a modern analogue technique applied to pollen series and actual tree taxa biomass estimated from remote sensing analyses, and (iii) human population density extracted from the HYDE database  19.
Methods Charcoal sites selection. We used 52 charcoal records located in eastern North America from the Global Charcoal Database version 3 and 12 additional published records not yet included in the database from Ali et al. 16  and Oris et al. 30  , for a total of 64 charcoal records (Fig. 1 ). Sites were classified into the four vegetation zones according to potential vegetation maps produced by Ramankutty & Foley  51  and the classification used by Girardin et al. 10. Ramankutty & Foley 51 used a single potential vegetation class, evergreen/deciduous mixed forest/woodland, to describe both open coniferous woodlands located above the closed boreal coniferous forest in the north and the boreal mixedwood forests located to the south. To correct for this bias, we assigned charcoal sites located north of the closed boreal coniferous forest belt to the open coniferous forest/tundra class and the sites south of it were assigned to the boreal mixedwood forest.
The modern pollen database we used was the North American Surface Sample Dataset by Whitmore et al. 55. From this dataset we extracted Canadian modern samples located east of 100 °W and estimated the biomass only for eastern main tree genera i. e. Abies, Acer, Betula, Picea, Pinus and Populus. In this analysis we only considered the genus or family level depending on pollen taxa, in order to down-weight pollen identification bias. In order to establish a correspondence between modern pollen assemblages and tree biomass, we used vegetation maps produced by Beaudoin et al. 22. These maps consisted of tree biomass estimates at 250 × 250 m across Canada derived from classification algorithms applied to satellite images. Prior to MAT, we estimated the optimal distance for compiling biomass for each taxa by calculating the predictive R-squared value between tree biomass and modern pollen percentages for increasing distances such as radius= 1, 5, 15,…, 150 km.
The distances that maximized the predictive R-squared were 30 km for Abies, 15 km for Acer, 15 km for Betula, 20 km for Picea, 120 km for Pinus, and 15 km for Populus. These distances are consistent with empirical studies of pollen source-area  56  and models of pollen dispersal  57. We used these distances for compiling the average biomass for each tree genus around each modern pollen sample. We used these biomass values for reconstructing MAT transfer functions and evaluated their performance by looking at predicted vs observed biomass distribution, associated correlation coefficients and Root-Mean-Square Error of Prediction (RMSEP, Supplementary Fig. 4 ). The number of analogues needed to reconstruct past biomass (k) for each genus was evaluated by bootstrap re-sampling the modern dataset split into training and test sets  58, 59.
The MAT transfer functions were then applied to fossil pollen assemblages extracted from the Neotoma database that were primarily aggregated to the same taxonomic levels we used for the modern dataset (see Table  A2  for the full citation list of the Neotoma sites). Age-depth models in the Neotoma database were corrected according to Blois et al. 60. Fossil pollen sites were selected according to their location, i. e. we only included sites located less than 100 km apart from a charcoal site. In order to evaluate the temporal trends in tree biomass, we used the same procedure as biomass burning that involved: (i) resampling tree biomass within 10 years overlapping windows, (ii) resampling these series using a bootstrap procedure 999 times, (iii) smoothing the resampled series using a locally weighted scatterplot smoother with a window half width of 500 years (a 200-year scatterplot smoother was also calculated to highlight the short-term trends in the data), and (iv) calculating composite mean and 90% confidence intervals from the smoothed and bootstrapped series.
Human population density. Population density estimates and land use changes were obtained from the History Database of the Global Environment (HYDE 3. 1) database covering the period 12,000 BP to present  19. HYDE population data consisted of the total population count for 5′ resolution pixels located worldwide. For each date available in the HYDE database, we summed the population for all pixels located in a radius of 100 km around each lake (corresponding to an area of c. 31,400 km 2 ). Then we calculated the average population density (i. e. pop count/area) around charcoal sites for each vegetation zone during the last 7000 years.
e. , 1000 years), and normalizing data (zero mean) by region (total sample size N = 4 regions * 8 millennia= 32). The semipartial correlation analysis was redone after substituting the HadCM3 data with CCSM3 data. The null hypothesis of no relationship between aboveground tree biomass and regional biomass burning from 7000 BP to present was to be rejected when p < 0. 05. The semipartial correlation test was done iteratively after substituting the dependent variable with another one until all variables were tested for their unique contribution. The significant explaining variables brought about by the correlation analysis were further analyzed using partial least squares regression in order to explore the functional form of the relationship between regional biomass burning and the climatic or vegetation forcing factors.
Data sources. The North American Surface Sample Dataset 55 was obtained from http://www. geography. wisc. edu/faculty/williams/lab/Downloads. html. Fossil pollen sites were obtained from the Neotoma database http://www. neotomadb. org. Actual vegetation biomass rasters  22  were obtained from Canada's National Forest Inventory Service https://nfi. nfis. org. Human population data were obtained from the HYDE 3. 1 database  19  available at http://themasites. pbl. nl/tridion/en/themasites/hyde/. HadCM3 paleoclimatic simulations were obtained from http://www. bridge. bris. ac. uk/resources/simulations; CCSM3 paleoclimatic simulations were obtained from http://ccr. aos. wisc. edu/resources/data_scripts/. Charcoal data were obtained from the Global Charcoal Database available at http://gpwg. org.
The expression and the specificity of the two cell types are now characterized in sheep species  [11]. Nevertheless, until now no studies had been able to describe the gene expression changes that occur during early follicular growth and in each compartment of the follicle. Consequently, the aim of the present study was to: 1-focus and decipher gene expression and functions that might be associated with early folliculogenesis from a developmental point of view (from primordial, primary, secondary and small antrum follicles) in sheep species, and 2-produce a set of biomarkers that are able to predict early follicular growth and could be used as in vivo signatures of early folliculogenesis. For this purpose, we used the previous dataset of 15,349 gene expressions obtained by RNAseq technology  [12]  in order to analyze the spatio-temporal gene expression.
RNA-seq experiment This study was carried out in strict accordance with the institutional guidelines for research studies. The protocol was approved by the prefecture de la Haute Garonne (animal experimentation authorization no 31-297). We briefly described the dataset previously published  [11] : -The lambs were euthanized at birth (<1 day). The ovaries were removed and embedded in O. C. T. embedding matrix, frozen in liquid nitrogen and stored at -80°C until use. Frozen sections were fixed and stained before laser capture microdissection  [11]. -The follicular compartments (i. e. granulosa cells (GCs)) and oocytes (O) were selected for each follicular stage as a function of follicular diameter (primordial (PD<35μM), primary (PM: 35-50μM), secondary (SC: 60-120μM) follicles and small antral follicles (SA: 250-500μM), captured by laser capture microdissection and extracted using the PicoPure RNA Isolation Kit.
Statistical analysis The significance of differential gene expression was determined using the DESeq package  [14]  of R software for multi-factorial design (R 2. 14. 0; DESeq release 1. 6. 1). Our experimental design included two factors: "stage" (with four levels: PD, PM, SC and SA) and "compartment" (two levels: O, GCs)  [12]. To establish the differential expression profile throughout early follicular development we identified the genes whose intra-compartment variance was differentially expressed during at least one of the stages (nbinom GLM Test). For this, we specified two models: the stage model (count ~stage) and the reduced model (count ~1) and applied them to each compartment dataset. For each compartment, the expression value of each gene was then compared between each follicular stage using pairwise comparison (nbinom Test).