dataesr/scientific-paragraphs-categorization huggingface dataset:
Quantitative real-time PCR RNA (1 μg) was spiked with 25 pg of bacterial AraB RNA from E. coli (GE Healthcare Bio-Sciences Freiburg, Germany), used as an external standard for normalization, as the expression of conventionally used house-keeping genes proved to be variable between developmental stages. RNA was reverse transcribed using the iScript Reverse Transcription Supermix (Bio-Rad, Hercules, CA, USA). Protocols for qRT-PCR performed with the LightCycler FastStart-DNA Master SYBR Green I kit in the LightCycler® 1. 5 Instrument (Roche Diagnostics GmbH, Mannheim, Germany), data analysis, and statistics have been described previously  [15]. The number of biological replicates used was sufficient to assess a statistical significance for a Log 2 FC ad value of 1 with a statistical power averaging 95% (alpha error level set at 0.
Results and discussion Combined analysis of gene expression data by Affymetrix microarray, Illumina RNA-sequencing, and qRT-PCR The expression level of selected genes was assessed in E19, P2, and adult rat lateral ventricular choroid plexus using Affymetrix microarrays, and in E15 and adult lateral ventricular choroid plexus by Illumina RNA-Seq analysis. Combining the two techniques enabled the inclusion of a larger number of genes in the study as some of these genes were identified by either Affymetrix or Illumina technology only. Some choroidal transcripts of special relevance to possible brain protection, but not represented on the arrays, were analyzed by qRT-PCR. For each gene, the adult stage included in all methods of analysis served as a reference to normalize the data set. Individual developmental profiles were built from the Log 2 FC ad mean values calculated at each stage.
The profiles are grouped and interpreted for families of genes with similar functions. To optimize the reliability of the data generated by microarrays, mRNA samples were prepared from two separate pools of choroid plexuses, each being collected from several animals. The choroidal tissue was carefully controlled with a stereomicroscope to verify the absence of contaminating tissue. Performance of the amplification/labeling reaction and of hybridization was assessed by external spike-in controls (exogenous RNAs added to the mRNAs samples before amplification, and biotinlabeled cRNA added prior to hybridization). The perfect alignment of signals detected for these spikes along the line of identity on plots comparing duplicate microarrays validates the technical reproducibility of the data (not shown).
The duplicate choroidal mRNA populations analyzed for each stage were highly similar as the expression level of 99. 4% of all genes detected at level above a background of 100 fluorescence units as defined by Affymetrix software differed by less than a factor of two between samples (not shown). Finally, the expression levels of the neuroprotective genes reported in this study differed only by 12. 4 ± 1. 4% (mean ± SEM) between the two matching samples. The qRT-PCR and Illumina RNA-Seq methods have some advantages over the microarray technology. Being both based on the relative quantification of the number of mRNA copies, they generate similar fold-changes  [35, 36]. They offer a larger dynamic and linear range of expression levels and are in theory more accurate for quantifying gene expression.
Slc15, Slc28 and Slc29 transporters The Slc15 subfamily comprises proton-coupled oligopeptide transporters  [66]. Among these, Slc15a2 transports peptidomimetic drugs such as the antiviral agent aciclovir or the β-lactam antibiotic cefadroxil. Slc15a2 protein was shown by immunocytochemistry to distribute at the apical and subapical domain of rat choroid plexus epithelial cells in culture  [67]. Accordingly, Slc22a12 was detected at E15, but not in adult by Illumina RNA-Seq method. (D) shows gene expression profiles for Slc15, Slc28, and Slc29 genes. Strongly expressed genes are indicated in bold. Genes indicated in parentheses have an apparent very low expression level in adult choroid plexus. Abbreviations, data analysis, and data expression as in Figure  2. studies using knock-out mice indicated that this transporter removes peptide substrates from CSF into the choroidal tissue  [66].
Acknowledgements The research leading to these results has received funding from the  European Union   Seventh Framework Program  ( FP7/2007-2013)  under grant agreement n°HEALTH -F2-2009-241778  and from the  National Health and Medical Research Council, Australia. SAL is funded by the  American-Australian Association. The authors thank  Catherine Rey  and the  ProfilXpert platform (Lyon)  for their technical help.
Refinement Approximate positions for all the H atoms were first obtained from the difference electron density map. However, the H atoms were situated into idealized positions and the H-atoms have been refined with the riding-model approximation. The applied constraints were as follow: C aryl -H aryl = 0. 95 Å; N aryl -H aryl = 0. 88 Å and U iso (H aryl ) = 1. 2 U eq (C aryl ). (Farrugia, 2012)  and DIAMOND  (Brandenburg & Berndt, 2001) ; software used to prepare material for publication: WinGX  (Farrugia, 2012)  and CRYSCAL (T. Roisnel, local program).
Crystal data (i) Àx þ 1; y þ 1 2 ; Àz þ 1; (ii) Àx; y À 1 2 ; Àz; (iii) x þ 1; y; z. Data collection: APEX2  (Bruker, 2012) ; cell refinement: SAINT  (Bruker, 2012) ; 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)  and PLATON  (Spek, 2009) ; software used to prepare material for publication: publCIF  (Westrip, 2010). Supplementary data and figures for this paper are available from the IUCr electronic archives (Reference: KP2451).
Computing details Data collection: APEX2  (Bruker, 2012) ; cell refinement: SAINT  (Bruker, 2012) ; data reduction: SAINT  (Bruker, 2012) ; 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)  and PLATON  (Spek, 2009) ; software used to prepare material for publication: publCIF  (Westrip, 2010). Refinement. Refinement of F 2 against ALL reflections. The weighted R-factor wR and goodness of fit S are based on F 2 , conventional R-factors R are based on F, with F set to zero for negative F 2. The threshold expression of F 2 > σ(F 2 ) is used only for calculating R-factors(gt) etc. and is not relevant to the choice of reflections for refinement. R-factors based on F 2 are statistically about twice as large as those based on F, and R-factors based on ALL data will be even larger.
3 mmol), and 4-dimethylaminopyridine (catalyst) in 5:1 tetrahydrofuran/triethylamine was stirred for 10 h at 60 °C. The solvents were removed to yield the desired triazole urea (85 mg; 0. 24 mmol; 78%) as a mixture of N2-and N1-carbamoylated regioisomers. The regioisomers were separated by silica gel chromatography (3:1 hexanes/ethyl ace-tate 3 ethyl acetate), and the major (N2-) isomer was characterized and used for subsequent biological experiments. 1  Amino Acid Sequence Alignments and Molecular Phylogeny Analyses-Sequences used in this study have all been obtained from the EuPathDB database  (42)  or GenBank TM database. Multiple alignments of full-length APT1 protein sequences were computed using MUSCLE  (43). Before PhyML analysis, all gap-containing sites were removed from the alignment.
Then the plates were analyzed with a Spectramax Gemini XS microplate fluorometer (Molecular Devices, Sunnyvale, CA) using an excitation wavelength of 530 nm and an emission wavelength of 590 nm. Data were analyzed using the software Softmax Pro (Molecular Devices). A decrease of fluorescence (ϭinhibition) was expressed as the percentage of the fluorescence of control cultures and plotted against the drug concentrations. From the sigmoidal inhibition curves, the IC 50 values were calculated. Inhibitor Target Pulldown-T. gondii parasites were treated with 25 M compound 5 or an equivalent volume of DMSO for 20 min at room temperature. Parasites were washed with PBS to remove excess probe and then resuspended at a concentration of ϳ1 mg of total parasite protein in 1 ml of PBS containing 0. 2% Triton X-100.
We cannot exclude that other enzymes, below the detection limit of this experiment, might be affected upon treatment with the inhibitors. TgASH1 Is Encoded by a Close Homologue of hAPT1-As a means to determine the identity of the inhibitor targets, a mod-ified version of the FP probe containing biotin in place of rhodamine was used to pull down probe targets on streptavidin beads. Proteins contained in the bands that correspond to inhibitor targets identified in the FP-Rh/inhibitor competition experiments above were then analyzed by MS. Three proteins that contain ␣/␤-hydrolase domains were identified (Table  2  and supplemental Fig. 1 ). Furthermore, a search of the T. gondii genome database for ␣/␤-hydrolase domain-containing proteins revealed 20 genes that could act as serine hydrolases and potentially exhibit an APT activity (Table  3 ).
Two candidates identified in the MS experiment (TGME49_ 028290 and TGME49_054690) and two further top candidates from the list in Table 3 (TGME49_023510 and TGME49_ 062490) were subjected to phylogenetic analysis along with their putative homologues in Apicomplexa, human APT1 and APT2 and their homologues in diverse eukaryotic species (Fig. 3 , A and B, and supplemental Fig. 2A ). TGME49_028290, which we have called ASH1 (GenBank accession number KC473455), identified by MS is the only one of the four genes that clusters with hAPT1 in the phylogenetic tree (Fig. 3A ) and exhibits 33% identity and 46% similarity at the amino acid level (supplemental Fig. 2B ). ASH1 is found only in the coccidian subgroup of the Apicomplexan phylum and hence is absent in the malaria parasite P. falciparum. However, putative APT homologues are well represented in other lower eukaryotic species, being present in kinetoplastids, amoeba, and ciliates (supplemental Fig.
2 ). The amino acid sequence alignment of ASH1 and hAPT1 (supplemental Fig. 2B ) highlights a highly charged region of low complexity that sits between the catalytic serine, aspartate, and histidine residues of ASH1. This insertion is also present in the ASH1 sequence of different T. gondii strains as well as in other Coccidia (ToxoDB). Homology modeling of ASH1 using hAPT1 (Protein Data Bank code 1fj2) as a template suggests that this large insertion can exhibit different conformations or even be disordered (one model with a helix/loop conformation ("insert 1") is shown in Fig. 3C , top). Similar regions in proteins with a known crystal structure tend to be flexible or disordered. However, according to the alignments/models, the insert is far away from the active site and leaves the catalytic residues undisturbed.
To gain further information, the three genes most closely related to TgASH1 and present across Apicomplexa were characterized. TGME49_054690 (TgASH2; GenBank accession number KF114274) was identified in the MS of the inhibitor targets (supplemental Fig. 1  and Table  2 ), whereas TGME49_023510 (putative TgASH3; Gen-Bank accession number KF114275) and TGME49_062490 (putative TgASH4; GenBank accession number KF114276) were annotated as containing ␣/␤-hydrolase domains and clear sequence similarity to TgASH1 (supplemental Fig. 2A  and Table  3 ). Transgenic parasites were generated to tag the proteins at the endogenous locus, and clones were analyzed by Western blot. The three genes were expressed at levels comparable with that of TgASH1 in the tachyzoite stage (Fig. 7A ), and IFAs revealed distinct subcellular localizations (Fig.
Plaque assays were performed with knock-out strains, and no growth defect was detected over 10 days (data not shown). Furthermore, neither stimulated egress (Fig. 8D ) nor intracellular growth (Fig. 8E ) of these strains was negatively impacted, although the ash3-KO strain appeared to grow slightly faster than the control over the 24-h period (Fig. 8E , right panel). Several attempts were made to disrupt TGME49_062490 (Fig. 8 , B and C); however, all attempts failed. To investigate whether Following precipitation of proteins and performing the click reaction to add the biotin to the compound 5-target complex, inhibitor targets were enriched on streptavidin beads and analyzed by Western blot. TgGAP45 and catalase (TgCAT) were used as negative controls, and a second sample that was treated with DMSO only instead of compound 5 was run.
supplemental Figs. 1 and The nucleotide sequence(s) reported in this paper has been submitted to the Gen-Bank TM /EBI Data Bank with accession number(s)  KC473455 ,  KF114274 ,  KF114275 , and  KF1142761  Supported by  FP7-funded Marie Curie Initial Training Network Project 215281-InterMal Training  and  Swiss National Foundation  Grant  FN3100A0-116722. 2 Supported by the  Swiss National Centre for Competence in Research: Chemical Biology  and the  Fonds der Chemischen Industrie. 3A   Howard Hughes Medical Institute senior international scholar.
Confocal acquisition, 3D reconstruction and quantification Confocal acquisitions were performed using a spinning-disk Perkin-Elmer Ultraview RS Nipkow Disk, an inverted laser-scanning confocal microscope Zeiss Axiovert 200 M with an Apochromat 63Â/1. 4 oil objective and a Hamamatsu ORCA-II-ER camera (Imagopole, Institut Pasteur). Optical slices were taken every 200-nm interval along the z-axis covering the whole depth of the cell, at resolution of 1. 024/1. 024 pixels. 3D reconstruction was achieved using the IMARIS software (Bitplane). Fluorescence quantification was done using a singleimaging frame collection and ImageJ 1. 34-s software (post-acquisition analysis). For each sample, 50 cells were analysed from three independent experiments.
Real-time quantitative polymerase chain reaction Total RNA was isolated from HeLa cells using the RNAeasy Mini kit (Qiagen), treated with DNaseI (Qiagen), then reverse transcribed using Superscript Õ III Reverse transcriptase (Invitrogen). Real-time quantitative polymerase chain reaction (RT-qPCR) was performed using Power Sybr Green PCR Master Mix (Applied Biosystems), and the rate of dye incorporation was monitored using the StepOne TM Plus RealTime PCR system (Applied Biosystems). Three biological replicates were used for each condition. Data were analysed by StepOne Plus RT PCR software v2. 1 and Microsoft Excel. TATA box binding protein transcript levels were used for normalization of each target (=ÁCT). RT-PCR C T values were analysed using the 2 ÀÁÁCt method to calculate the fold expression  (29).
mtDNA content analysis by quantitative polymerase chain reaction The quantification of mtDNA was performed by quantitative polymerase chain reaction (qPCR) amplification on 200 pg of total DNA using the StepOne TM Plus RealTime PCR system (Applied Biosystems) and Power Sybr Green PCR Master mix (ABI) following the manufacturer's instruction. Human mtDNA accession number: NC012920. 1. The region tested on mtDNA was included in the 12S gene. When indicated, a region within 7S (primers A, B1) and a larger downstream region that also contain 7S (primers A, B2) were analysed, as described  (27). The nuclear encoded 18S rRNA gene was used as an endogenous reference. The level of mtDNA was calculated using the ÁC T of average C T of mtDNA and nDNA (ÁC T = C T nDNA À C T mtDNA) as 2 ÁCT (30). Primers used for amplification are listed in Supplementary Table  S2.
Protein extraction and western blot Cells were lysed by lysis solution [20 mM Tris, 18 mM NaCl, 0. 5 % Lauryl b Maltoside, 1 mM MgCl 2 , 200 mM Na 4 P 2 O 7 , 1 mM ethylene glycol tetraacetic acid (EGTA), 20 mM NaF, 2 mM NaVO 4 , 1 mM Pefabloc (Sigma), 1 mM Aprotinin (Sigma), 1 mM Leupeptin (Sigma)]. Protein content was determined with the Bradford reagent (Sigma), and 30 mg of protein were loaded for sodium dodecyl sulphate-polyacrylamide gel electrophoresis. After blotting, Hybond ECL nitrocellulose filters were probed with anti-Polg and anti-TFAM antibodies. Detection was performed using Odyssey Infrared Imaging system scanner and Odyssey application software v3. 0 (LI-COR Biosciences).
Identification and quantification of mtDNA processing markers in single cells We recently developed an imaging approach, mitochondrial Transcription and Replication Imaging Protocol (mTRIP) that is a combination of DNA FISH and RNA FISH, and which can be also combined to immunofluorescence, as the treatment does not destroy proteins  (28). With mTRIP, we performed 3D confocal acquisitions of the fluorescent signal of either DNA probes or protein immunomarkers, or both in colabelling experiments, and measured the intensity of fluorescence of each marker per cell. The measurement was performed in the entire cell area, defined in the 2D rendering file, which results from 3D reconstruction of z-stacks (Figure  1A ). 3D reconstruction and 2D rendering were obtained with the software Imaris and fluorescence intensity quantification with the software ImageJ.
Data analysis The slides were scanned on an Agilent G2505C DNA Microarray Scanner at a resolution of 5 mm, using default parameters. Acquisition of signals from the resulting scanned images and normalization were performed using the Feature Extraction v10. 5. 1. 1 software (Agilent Technologies), using default parameters. Normalized data were re-centralized using a custom script, then analyzed using CGH Analytics v3. 4. 40 software. The ADM-2 algorithm of CGH Analytics V3. 4. 40 software (Agilent) was used to identify DNA copy number anomalies at the probe. A low-level copy number gain was defined as a log 2 ratio >0. 25 and a copy number loss was defined as a log 2 ratio <0. 25. A high-level gain or amplification was defined as a log 2 ratio >1. 5. DNA copy number anomalies were plotted by the aCGH software package v1.
10. 0  13  using the R statistical language. No clustering analysis was done due to the small sample size. The UCSC human genome build version hg18 of March 2006 was used for all the genomic coordinates [http://genome. ucsc. edu]. Raw data have been submitted to the Array Express database with the accession number E-TABM-584. A Welch's T-test was performed to compare the CGH array profiles of these 28 samples to the CGH profiles of 106 breast cancer samples from the US,  11  using the R statistical environment v2. 8. 0 [http://cran. r-projetc. org]. Moreover we likewise compared specifically the CGH array profiles of 16 triple negative samples from Mali to the CGH profiles of the triple negative samples from the US already studied by Andre F et al. 11.
Multiannual satellite measurements of tropospheric NO 2 columns are used for evaluation of CO 2 emission changes in China in the period from 1996 to 2008. Indirect top-down annual estimates of CO 2 emissions are derived from the satellite NO 2 column measurements by means of a simple inverse modeling procedure involving simulations performed with the CHIMERE mesoscale chemistrytransport model and the CO 2 -to-NO x emission ratios from the Emission Database for Global Atmospheric Research (EDGAR) global anthropogenic emission inventory and Regional Emission Inventory in Asia (REAS). Exponential trends in the normalized time series of annual emissions are evaluated separately for the periods from 1996 to 2001 and from 2001 to 2008. The results indicate that the both periods manifest strong positive trends in the CO 2 emissions, and that the trend in the second period was significantly larger than the trend in the first period.
son of our indirect top-down estimates of the CO 2 emission changes with the corresponding bottom-up estimates provided by the EDGAR (version 4. 2) and Global Carbon Project (GCP) glomal emission inventories reveals that while acceleration of the CO 2 emission growth in the considered period is a common feature of both kinds of estimates, nonlinearity in the CO 2 emission changes may be strongly exaggerated in the global emission inventories. Specifically, the atmospheric NO 2 observations do not confirm the existence of a sharp bend in the emission inventory data time series in the period from 2000 to 2002. A significant quantitative difference is revealed between the bottom-up and indirect top-down estimates of the CO 2 emission trend in the period from 1996 to 2001 (specifically, the trend was not positive according to the global emission inventories, but is strongly positive in our estimates).
(2010)  for studying NO x emission trends in megacities. Accordingly, our estimates of CO 2 emission changes are obtained by merging the top-down estimates of NO x emission changes and bottom-up estimates of the NO x -to-CO 2 emission conversion factors. Such CO 2 emission estimates can therefore be considered either as indirect top-down or hybrid estimates combining the top-down and bottom-up information. Since CO 2 emission trend estimates obtained in this study are based on observations (even though some emission inventory data are also involved), they are to a significant extent independent from similar estimates provided by emission inventories. Taking this into account, we believe that our indirect top-down (or hybrid) CO 2 emission estimates can be helpful for detecting and elucidating possible uncertainties and/or inconsistencies in alternative bottom-up emission estimates and in inventory data that are used to relate NO x and CO 2 emissions in our analysis.
, 2005; He et al. , 2007; Kim et al. , 2006 Kim et al. , , 2009;; Konovalov et al. , 2008 Konovalov et al. , , 2010)). The initial nominal horizontal resolution of the GOME measurements is 320 × 40 km 2 , and almost global coverage is achieved within three days. The SCIAMACHY measurements have a higher nominal horizontal resolution of 60 × 30 km 2 , but a longer global coverage period of about six days. Preprocessing of the "standard" monthly datasets included several steps described below. First, the global data were regridded to a 0. 5 • × 0. 5 • regional grid focusing on China. Second, "empty" grid cells (in which measurements are missing, e. g. , because of clouds) in each of the monthly datasets were filled in by means of a temporal or spatial interpolation. Specifically, an empty grid cell in a given monthly dataset was assigned with either the average over the two nearest months or (if the data for those months are also missing) the average over the eight closest grid cells of the same month.
Data of emission inventories We used annual emission data from several emission databases, including the Emission Database for Global Atmospheric Research, version 4. 2 (EDGAR v4. 2), the Global Carbon Project (GCP) international inventories, the Regional Emission Inventory in Asia (REAS), and a new global data product for CO 2 emission by combustion processes (PKU-CO2) compiled at Peking University. CO 2 and NO x emissions are available from the EDGAR v4. 2 (EC-JCR/PBL, 2010) database both as the national totals and on a grid with the resolution of 0. 1 • ×0. 1 •. GCP (GCP, 2010) provides only total national carbon emission estimates. The data from the EDGAR v4. 2 gridded and GCP country-averaged emission inventories cover the whole period addressed in this study  (1996) (1997) (1998) (1999) (2000) (2001) (2002) (2003) (2004) (2005) (2006) (2007) (2008).
Details can be found elsewhere  (Wang et al. , 2013). The emission inventory data outlined above are considered below in comparison with corresponding estimates based on satellite measurements. Focus is given to the data of the global emission inventories (EDGAR and GCP) that have direct implications for climate change research. Data of the regional emission inventories (REAS and PKU-CO2) are used in this study mainly for sensitivity tests and as a source of supportive information. A thorough comparative analysis of the different global and regional emission inventories is beyond the scope of this paper.