dataesr/scientific-paragraphs-categorization huggingface dataset:
The signal was visualized using Odyssey Infrared Imaging System (Li-Cor Biosciences, Bad Homburg, Germany). Calculation of Western blots densitometry was analysed by using the Image J analysis software (NIH). Calculation of the Mean Myofiber Diameter H&E-labeled 10 mm frozen cross sections derived from five FSHD patients and five age-matched healthy controls were used to calculate myofiber diameters as previously described by Spuler et al. [23]. Ten images (206magnification) for each FSHD and control subject were captured using a light microscope (Leica Microsystems, Leica DM LB2). Thousand myofibers were chosen to compute mean myofiber diameter. The smallest diameter of myofiber was manually selected and calculated in mm. All computation was done by using the Image J software (version 1. 36r; Java 1.
Statistics RNA expression levels are presented as median, 25th and 75th percentiles and range. Group comparisons were analyzed by using non-parametric Mann-Whitney U and Wilcoxon's rank tests (GraphPad Prism version 4. 0 software, San Diego, California, USA). For the distribution pattern of myofiber diameters (mm) of FSHD patients and healthy controls mean values are given. At least 10 slide fields for each examined subject were selected and examined at a magnification 20x on a Light Microscope (Leica Microsystems, Leica LB2). Group and subject comparisons were analyzed by Wilcoxon test using R: A language and environment for statistical computing (R-Version R-2. 15. 2, R Foundation for Statistical Computing, Vienna, Austria)  [24]. The Histogram was made by use of ggplot2 (Version 0. 9. 3, Wickham et al.
The T 2 R-TTL-apo and -ADP structures were determined by the difference Fourier method using the phases of the T 2 R-TTL-AMPPCP complex in the absence of ligands and solvent molecules (Protein Data Bank accession no. 4I4T;  Prota et al. , 2013)  as a starting point for the refinement. The models were first fitted by several cycles of rigid body refinement followed by simulated annealing and restrained refinement in Phenix  (Adams et al. , 2010). The resulting models were further improved through iterative model rebuilding in Coot  (Emsley and Cowtan, 2004)  and refinement in Phenix. NCS restraints were applied in initial refinement stages and then omitted in the final cycles of refinement to account for structural variations between the ncs-related copies of -and -tubulin. The quality of the structures was assessed with MolProbity  (Davis et al.
After transfer to nitrocellulose membranes and staining with Ponceau S, -and -tubulin bands were cut out and incorporated l-[ 3 H]-tyrosine was quantified using a Tri-Carb 2910 TR scintillation counter and QuantaSmart software (PerkinElmer). To set up optimal reaction conditions for this activity assay, we determined the linear range of catalysis for variable molar ratio TTL/tubulin in 45-min time course measurements. Initial speeds were derived for each series, and plotting these speeds against TTL/tubulin ratios demonstrated that for TTL/tubulin ratios between 1:1,000 and 1:200 the reactions were under nonsaturating conditions. Thus, we decided to use a TTL/tubulin ratio of 1:500 (final TTL concentration in the assay: 900 µM) for all further assays. To compare the activities of TTL with tubulin or the T 2 R complex, we performed the incorporation assay using either free tubulin or T 2 R (molar ratio of tubulin/RB3 of 1:1.
Next, cells were washed three times with PBS for 5 min and incubated with secondary antibodies in GDB for 1 h at room temperature and washed three times in PBS. Finally, coverslips were mounted using Vectashield (Vector Laboratories). Confocal images of fixed neurons were acquired using a confocal laser microscope (model A1R; Nikon) equipped with 40× oil Plan-Fluor NA 1. 3 and 60× oil Plan-Apo NA 1. 4 objectives and Nikon's NIS-Elements imaging software. Using maximum projection, z-series of images were converted into a single image. Analysis of neuron morphology was performed using SynD  (Schmitz et al. , 2011). Analyses of staining intensities (TTL and tyrosinated -tubulin) were performed using MetaMorph image analysis software (Universal Imaging Corp. ). Using the projection images, somas were traced of the transfected neuron (one per image) and a nontransfected neuron in the same image.
Accession numbers Coordinates have been deposited in the Protein Data Bank with accession numbers 4IIJ (T 2 R-TTL-apo), 4IHJ (T 2 R-TTL-ADP), and 4I4T (T 2 R-TTL-AMPPCP). Online supplemental material Fig. S1  shows the data for T 2 R binding and the tyrosination assay, and additional structural considerations of the TTL-tubulin interaction. Fig. S2  shows a multiple sequence alignment of TTL orthologues together with selected TTLLs. Fig. S3  shows the hippocampal neuron data that were used to quantify tubulin tyrosination levels. Fig. S4  shows the electron density of the active site of TTL in the T 2 R-TTL complex and illustrates the comparison with ATP-grasp family enzymes. Fig. S5  shows the electron density of TTL in the apo and tubulin/AMP-PCP bound states. Table  S1  reports the x-ray data collection and refinement statistics.
Online supplemental material is available at http://www. jcb. org/ cgi/content/full/jcb. 201211017/DC1. Additional data are available in the JCB DataViewer at http://dx. doi. org/10. 1083/jcb. 201211017. dv. We are indebted to F. Winkler for critical reading of the manuscript and to N. Gold for technical assistance. We thank V. Olieric and M. Wang for.
(C) Close-up view of the active site of TTL in the T 2 R-TTL complex in stick representation. A water molecule and two magnesium ions are depicted as red and green spheres, respectively. (D) Superimposition of the active site of TTL (blue) bound to the nonhydrolyzable ATP analogue AMPPCP and the tail of -tubulin (light gray) onto the one of glutathione synthase (green; Protein Data Bank accession no. 1M0W) bound to the nonhydrolyzable ATP analogue AMPPNP and gamma-glutamylcysteine (3GC; dark gray). Key residues are shown in stick representation. For simplicity only residue side chains are shown. Spheres depict magnesium ions. See Fig. 2 for additional information on labels, symbols, and color code.
Figure6. Molecular mechanism of tubulin tyrosination by TTL. (A and B) Superimposition of TTL in the tubulin-bound (blue) and -unbound (gray; Protein Data Bank accession nos. 3TIG and 3TII, respectively) states in cartoon representations, and in the absence (A) or presence (B) of nonhydrolyzable ATP analogues. In B, the 11-5 loop and a large portion of the central domain of TTL, structural elements that get structured upon binding of both tubulin and adenosine nucleotide, are highlighted in pale green. (C) Enzymatic cycle of TTL. (1) Binding of TTL-ADP (ground state) to detyrosinated tubulin (Detyr-tubulin) and exchanging ADP (in yellow sphere representation) by ATP induces the structuring of the 6-7 and 11-5 loops of TTL (indicated by pale green dashed lines). As a result, the ATP molecule gets buried and an extended cavity is formed, which specifically recognizes the incoming C-terminal tail of -tubulin (highlighted in orange).
Country uptake of innovations In the 11 countries, country informants recorded 35 innovations in countries, 39% of a possible 88 markets (data available in Supplementary Table  S1 ). The representatives at the workshops did not necessarily know enough about all the eight innovation projects to make informed comments themselves and the responses were incomplete for some markets. The innovation most frequently identified with having impacts was Child Safety Action Plans (CSAP), in seven countries (Austria, Cyprus, Finland, Malta, Romania, Slovakia and UK). A reason frequently noted in country workshop reports was that Child safety action plans (CSAP), while only a single-year project, laid foundations also for later collaborative projects-including a 4-year second phase (also funded by the Health Programme) called TACTICS.
European System of Urban Health Indicators (URHIS) gave importance to urban health data in Latvia; stimulated research in Slovakia; was used for city health profiles in Slovenia and assisted within and trans-national comparisons in UK. Four innovations were reported to have uptake across a smaller number of countries. European Alliance Against Depression (EAAD) contributed at different levels in four countries. It was: used in primary care services at a local level in Finland; used in two counties in Ireland; noted for the national health plan in Italy and influential in expert advice in Slovenia. Vaccine European New Integrated Collaboration Effort (VENICE) was identified by three countries: in Latvia it stimulated development of vaccination programmes; in Malta it informed policy decisions of the national immunization committee and in Slovenia it provided information for the national strategy.
). However, it is not possible from the existing information systems to track research programmes specifically related to the eight tracer projects, so that there could be duplication. Table  3  Innovations reported to have academic impacts EUCID was noted to have published Journal Articles using the relevant data. In Austria, a Master's Thesis analysed the process of the CSAP project. In Finland, the final report of EAAD had been produced as a university course book. Also, EAAD had been used as a case study in Ireland in a European booklet identifying projects that have impacted on policy and practice. In Slovakia, URHIS had generated investment by PJ Safarik University in Kosice, Faculty of Medicine, Institute of Public Health for two researchers to further investigate the topic. In Italy, discussion of VENICE noted that 40 million Euros per year were spent on vaccination programmes, yet only about 15 000 Euros are allocated to secondary research, data collection and data analysis.
Microarray data analysis Data analysis was performed as described in David et al. [33]  except that genes showing a t test P value,0. 05 and an expression ratio. 1. 5-fold in either direction were considered differentially transcribed. In our screen, only genes overexpressed in steroidogenic tissues with an expression ratio. 1. 5-fold were further considered. As a control, a calibration experiment was performed in which two aliquots of labelled aRNA derived from the same sample were co-hybridized to two arrays with dye-swap. As expected, none of the gene probes came out significantly differentially transcribed, supporting the statistical approach described above (data not shown). All microarray data have been deposited at ArrayExpress (E-MTAB-1697).
Gene cloning Total RNA was isolated with Trizol reagent (Invitrogen) from vitellogenic ovaries and reverse transcribed with M-MLV reverse transcriptase (Promega). The A. gambiae genome is sequenced and genomic data are available on the website http://www. Ensembl. org/. Full length cDNA sequences of Agcyp314a1, Agcyp307a1, Agcyp6n1, Agcyp4g16 were amplified from total cDNAs by PCR with specific primers (see Table  S1 ). cDNAs were gel purified, cloned into pIB/V5-His (TA cloning, Invitrogen) and insert sequences verified (Genome Express; GenBank Accession numbers KF656700, KF656701, KF656702). Egfp (described in  [51] ) was cloned into pGEM-T Easy vector (pGEM-GFP) with specific primers (Table  S1 ).
In vitro culture and ecdysteroid quantification Cultures were performed according to the method described in Pondeville et al. [26]  except that ovaries were incubated for 3 h at 25uC. After incubation, culture medium was collected and stored at 220uC until ecdysteroid quantification. Ecdysteroids were quantified by EIA, with 20-hydroxyecdysone-2-succinate coupled to peroxidase as a tracer (dilution 1:80,000) and either the L2 antiserum (a generous gift from Dr. M. De Reggi, dilution 1:40,000) or the EC19 antiserum (a generous gift from Dr. J. -P. Delbecque, dilution 1:10,000). The L2 antibody recognizes both E and 20E, as calculated from the comparison of reference standard curves (data not shown). The EC19 antibody recognizes only 20E. Calibration curves were generated with E or 20E (3. 6 to 500 pg/tube) diluted in Schneider's medium and the in vitro production was expressed in E or 20E equivalents.
Under these conditions, detection limits are 7 pg E equivalents for the L2 antibody and 5 pg 20E equivalents for the EC19 antibody. Ecdysteroids secreted by tissues were measured directly on incubation media. For each sample, measurements were performed in duplicate and the results are expressed as mean values 6 S. E. M. of several (n = 20) independent ovary pairs. All experiments have been repeated on 2 independent cohorts mosquitoes. Data were subjected to statistical analysis using Mann-Whitney test.
Results Generation of steady-state mRNA and polysomal mRNA datasets across the P. falciparum asexual cycle To investigate differences between transcription and translation during the erythrocytic cycle of P. falciparum strain 3D7, we isolated both steady-state mRNA and polysome-associated mRNA at different stages throughout the parasite's cell cycle. Parasites were harvested directly after the invasion of the red blood cell at the early ring stage (0 h), as well as at the trophozoite (18 h) and schizont (36 h) stages. For steady-state mRNA, we first isolated total RNA from the parasites, followed by mRNA purification using poly-A selection. Based on the amounts of mRNA isolated per flask of parasites, high abundance of transcripts was observed during the trophozoite and schizont stages of the erythrocytic cycle (Table  1 ).
5% proteins with unknown functions and 2. 0% contaminants (Table  S1  in Additional file 1), indicative of a high purity of our polysome fractions. Both steady-state and polysomal mRNA fractions were treated with DNase to remove genomic DNA contamination. Even though steady-state mRNA contains all of the polysomeassociated mRNA, the polysomal fraction is presumed to be highly enriched for actively translated mRNA and is thus considered a different mRNA population. Using next-generation sequencing (Illumine HiSeq 2000), we obtained an average of 7. 1 and 3. 0 million high quality reads per stage for the steady-state mRNA and polysomal mRNA datasets, respectively, corresponding to an average of 21. 5X and 6. 6X exome-wide coverage (Table  1 ). We  Considering the fact that microarray and RNA-Seq data only agree well for genes with medium expression levels  [19] , the correlation coefficients that we obtained for our datasets further validate our sequencing results.
Cluster analysis of steady-state and polysomal mRNA profiles across the asexual cell cycle We detected a total of 4,633 expressed genes (85. 0% of all protein-coding genes) in our datasets, albeit at very low levels for some genes, which is comparable to previous expression analyses in P. falciparum  [3, 4]. Genome-wide, both steady-state mRNA levels and polysomal mRNA levels varied over five orders of magnitude, while expression levels for individual genes across the cell cycle ranged within three orders of magnitude. Median variation in expression levels between different time points of the cell cycle were 3. 8-fold for steadystate mRNA and 3. 6-fold for polysomal mRNA. Of the genes that were present in both the steady-state mRNA and the polysome-associated mRNA datasets, 4,007 genes (73.
5%) were cell cycle-regulated (defined as more than two-fold difference in expression levels across the cell cycle). Both the steady-state and the polysomal transcript abundance data were independently clustered based on expression profiles, resulting in five steadystate mRNA and six polysomal mRNA clusters (Figure  2 ). Most transcripts accumulated or were actively translated exclusively in one stage (clusters 1, 2, and 5 of the two datasets). However, for both the steady-state mRNA and polysomal mRNA datasets, we also identified a substantial number of genes with expression profiles overlapping the trophozoite and schizont stages (clusters 3 and 4). For most of these genes, expression peaked in one of the two stages with lower expression levels in the second stage. In addition, we observed a cluster of 171 genes that were associated with polysomes in both the schizont and the ring stage (cluster B.
Differences in mRNA landscape between steady-state mRNA and polysomal mRNA To identify mechanisms that may be involved in translational control, we compared genome coverage of sequence reads between our steady-state mRNA and polysomeassociated mRNA datasets throughout the parasite cell cycle. The steady-state and polysomal mRNA landscapes were strikingly different (Figure  3 ). For steady-state mRNA, more than 85% of sequence reads mapped to coding sequence (CDS) regions, while between 29 and 50% of the polysomal mRNA reads mapped to introns, untranslated regions (UTRs) or other intergenic sequences. In particular, the low level of translation at the 0 h time point may allow us to detect non-annotated transcripts from intergenic regions present at very low levels, which could be overshadowed by highly translated genes at the later time points.
Control of translation by upstream open reading frames In the polysomal mRNA dataset, a coverage plot of the start region averaged across all genes showed an increased coverage of the 5′ UTR region in combination with a lower coverage in the CDS (Figure  4A ). In total, 409 genes showed more than two-fold read coverage in their 5′ UTR as compared to their CDS (Figure  4B ). For three genes, this increased 5′ UTR coverage was validated by semi-quantitative RT-PCR, indicating that this phenomenon is unlikely to be the result of a bias introduced by the library preparation or sequencing reaction (Figure  S3A  in Additional file 2). In addition, reverse transcription using directional primers showed that mRNA covering the 5′ UTR was transcribed in the sense direction (Figure  S3B  in Additional file 2).
A similar pattern was previously observed in ribosome-protected fragments from cycloheximide-treated cells  [20]. In contrast, apicoplast-encoded genes that are translated in the apicoplast by 70S ribosomes did not show this peak in sequence coverage at the translation start site (Figure  4A ). Since 70S ribosomes are insensitive to cycloheximide inhibition  [21] , excess coverage at the ATG start codon in our polysome-associated mRNA dataset is likely to be the result of cycloheximide-induced ribosome stalling, indicating that even though our mRNA was not nuclease-digested, the binding sites of ribosomes, initiation factors or RNA binding proteins may be enriched in our sequencing data. If binding of ribosomes or proteins indeed influences gene coverage profiles, the high coverage in 5′ UTR regions in this subset of genes may be explained by protection of this region.
falciparum, thereby expanding the number of alternative splice variants that are currently annotated or have previously been described in multiple independent RNA-Seq datasets from the same stages  [4, 18, 53]. In addition, we also observed that a large proportion of genes contained sequence reads that mapped to introns. Since the majority of introns were completely devoid of reads, this is unlikely to be caused by DNA contamination of our mRNA samples. Intron coverage can be the result of intron retention in the transcript, or the transcription of overlapping RNAs, either in a sense or anti-sense direction, as is known to occur in P. falciparum  [53, 54]. Alternatively, introns are known to contain many non-protein-coding RNAs (ncRNAs)  [55] , that can be independent transcripts or be derived from the pre-mRNA.
Formic acid (5% final) was added to stop the reactions. The sample was loaded on split-triple-phase fused-silica microcapillary column  [61]  and placed in-line with LQT Velos Pro mass spectrometer (Thermo Fisher Scientific), coupled with quaternary Agilent 1260 series high-performance liquid chromatography. A fully automated 10-step chromatography run (for a total of 20 hours) was carried out, as described in  [62]. Each full mass spectrometry (MS) scan (400 to 1,600 m/z) was followed by 10 datadependent tandem MS (MS/MS) scans. The number of the micro scans was set to 1 for both MS and MS/MS. The dynamic exclusion settings used were as follows: repeat count 2; repeat duration 30 s; exclusion list size 500 and exclusion duration 90 s, while the minimum signal threshold was set to 500. The MS/MS dataset was searched using SEQUEST  [63]  against a database of 72,358 sequences, consisting of 5,487 P.
89% and 0. 26%, respectively. To estimate relative protein levels and to account for peptides shared between proteins, Normalized Spectral Abundance Factors (dNSAFs) were calculated for each detected protein, as described in  [65]. Lists of all proteins that were detected in our sample and individual peptide/spectral counts are provided in Table  S1  in Additional file 1. The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium [66] via the PRIDE partner repository  [67]  with the dataset identifier PXD000553. The MS. RAW files,. ms2 files created by RawDistiller, the. sqt files generated by SEQUEST, and the DTASelect output files for this analysis are also available to download from The Stowers Institute Original Data Repository  [68].
mRNA isolation and cDNA preparation To remove potential DNA contamination, RNA samples were treated twice with 1 U DNase I (Life Technologies) per 10 μg of RNA for 30 minutes at 37°C, followed by inactivation of the DNase I enzyme. The absence of DNA was confirmed by performing a 40-cycle PCR on P. falciparum gene PF05_139450 using 200 to 500 ng total RNA as input. Messenger RNA was then purified from total RNA samples using the GenElute mRNA Miniprep kit (Sigma-Aldrich) according to the manufacturer's instructions. The preparation of double-stranded cDNA from steady-state mRNA and polysome-associated mRNA samples was adapted from a previously published method  [69]. Up to 500 ng of mRNA was diluted 1:5 in RNA storage solution (Life Technologies) and was fragmented by a 50 minute incubation at 98°C.
Data normalization For each gene, the number of reads mapping to its exons was calculated (Bedtools). Exon read counts per gene were normalized for GC content and gene length using the open-source Bioconductor R package EDASeq  [78]. In our experience, expression values of short genes with low read counts (<5 reads per gene) are highly inflated using this package. To minimize overestimating expression levels of such genes, genes that did not reach five mapped reads at any time point in both steady-state mRNA and polysomal mRNA were removed from the datasets before applying the normalization algorithm. For genes with annotated alternative splice variants, only the first variant (annotated with. 1 in its gene name) was included. Non-protein coding transcripts (annotated as 'transcript', not 'mRNA' in PlasmoDB-9.
Finally, for both steady-state mRNA and polysomal mRNA datasets, genes that were not expressed were excluded from further analysis. Nonexpressed genes were defined as having <15% of the median counts per kilobase of exon model (18. 9 counts for the steady-state mRNA dataset and 4. 0 counts for the polysomal mRNA dataset) at all stages. Because of differences in library sizes, RPKM cutoff values differed for each library, but were at least 0. 7. An overview of exon read counts before, during, and after the different normalization steps is provided in Additional file 5.