dataesr/scientific-paragraphs-categorization huggingface dataset:
Variation in LD across ethnicities could also have reduced our power to detect associations. More research is needed to determine if associations in these regions can be generalized to different ethnic groups based on larger sample size. These efforts could make meaningful contributions to addressing disparities in health between populations. Power to detect associations is also relevant when considering our primary analyses involving subjects of European ancestry. Our initial investigation using the GAME-ON and GECCO data set identified 33 regions and 190 variants that we further examined in replication data sets. We were able to replicate the associations for four of these regions. Since our replication datasets sample sizes were often smaller than that of our discovery (GAME-ON/GECCO) set (depending on cancer site), we may have insufficient power to replicate true associations particularly for less common variants, underlining the importance of sample size for investigations of pleiotropy.
In summary, using data from the GAME-ON initiative and GECCO, we have found four regions that show associations with multiple cancers, including a novel association between genetic variation at 1q22 and breast cancer and lung squamous cell carcinoma. This is the largest study to date examining pleiotropy across multiple cancer sites. There are likely more loci that are associated with multiple cancers but these will require additional efforts with larger data series for detection. Our results provide important insights into common carcinogenesis across multiple major cancers and highlight the value of pleiotropy analysis. Results for rs1057941 (A) Regional plot showing P values from overall meta-analysis at region 1q22 using GAME-ON/GECCO discovery set data. The top breast cancer hit (rs3814316) and top squamous cell carcinoma hit (rs4072037) are also highlighted.
Survey The survey contained 39 questions and took about 20 min to complete. The complete survey in English is available in the Additional file 1. The survey topics included questions about demographics, living with bipolar disorder, Internet use, online information seeking, and participation in online support groups. Questions 21-35 about online information seeking were analyzed here. The questions on Internet access were analyzed previously  (Bauer et al. 2016). The survey was translated into 12 local languages: Chinese, Danish, Finnish, French, German, Hebrew, Italian, Japanese, Polish, Portuguese, Spanish, and English (versions for US/Canada, UK and Australia). Duplicate data entry was used for quality control with the paper-based surveys  (Kawado et al. 2003; Neaton et al. 1990). Automated logic checking of numeric fields was implemented as appropriate.
Online medical data may be combined with other data for health risk predictions  (Dixon and Gellman 2014) , combined with genetic data for commercial research  (Seife 2013) , and de-identified data may be re-identified using very large, high-dimensional databases  (Narayanan et al. 2016). Even though the legal framework is changing, such as with the general data protection regulation (GDPR) to be implemented by 2018 for the EU (European Parliament News 2016), patients of all search skill levels need to understand the data policies of websites they visit regularly for information on mental health.
Genes down-regulated after muscle injury then up-regulated afterwards Cluster I contained 2069 unique genes which expression decreased after muscle injury and then increased at day 30 post-injury when new myofibres were formed. Contrasting to genes found in clusters III and IV, expression of genes found in cluster I was lower at day 30 postinjury than that observed in controls (non-injured muscles). 1646 genes from cluster I were eligible for analysis using DAVID software tools and were subsequently used for functional analysis. Gene Ontology of cluster I using DAVID revealed a very high enrichment in functional categories related to the generation of precursor metabolites and energy (P < 1. 1. 10 -4  , 123 genes), oxidative phosphorylation (P < 3. 10 -16 , 41 genes), glycolysis (P < 6. 6.
3b ). Thus, a large part of the transcriptional program underlying stratified muscle hyperplasia is reactivated during fish muscle regeneration, especially when regenerating myofibres are forming. Using a DAVID analysis, we found that the most enriched functional categories inferred from genes common to the muscle hyperplasia signature and to cluster III were related to nuclear mRNA splicing via the spliceosome (P < 6. 1. 10 -1  , 37 genes), DNA metabolic process (P < 1. 5. 10 -14 , 71 genes), DNA replication (P < 2. 7. 10 -13 , 39 genes), RNA processing (P < 2. 2. 10 -12 , 70 genes), RNP complex biogenesis (P < 2. 7. 10 -11 , 35 genes), protein folding (P < 1. 4. 10 -9 , 32 genes), macromolecular complex assembly (P < 2. 2. 10 -9 , 72 genes), and monosacharide metabolic process (P < 3. 2.
Validation of the microarray gene expression data In order to confirm the significance of differential mRNA expression pattern observed in the microarray data, Real time PCR analysis was performed on selected genes (MyoD1a, myogenin and cadherin 15 (M-cadherin)) that exhibited distinct temporal profile during muscle regeneration. For the three genes tested, the temporal expression patterns revealed by microarray and real time PCR data were very similar (Additional file 8).
Microarray slides Microarray experiments were performed using an Agilent-based microarray platform with 8 × 60K probes per slide This platform (GEO platform record: GPL15840), which notably provides the sequence of all the oligonucleotides spotted on the slide with corresponding identifier, is based on a rainbow trout resource designed by Salem et al. [26]  and was enriched with oligonucleotides designed using recent NGS data from trout (http://ngspipelines-sigenae. toulouse. inra. fr:9064/). The microarray gene annotations were reanalysed by Sigenae (Institut National de la Recherche Agronomique, Toulouse, France). Microarray data sets have been submitted to the GEO-NCBI with the accession number GSE77223.
Data acquisition and analysis Hybridised slides were scanned with the Agilent DNA Microarray Scanner using the standard parameters for a gene expression 8x60K oligoarray (3μm and 20 bits). The data were extracted using the standard procedures contained in the Agilent Feature Extraction (FE) software version 10. 7. In particular, following AGILENT instructions, a feature was validated when background substracted signal was greater than background standard deviation x2. 6. The arrays were normalised (scale normalisation) and log-transformed using GeneSpring software (version 12. 6. 1). An ANOVA analysis (Benjamini-Hochberg (BH) corrected pval < 0. 05) and a >4-fold expression change in each of the ten possible comparison were used as the criteria for defining genes as differentially expressed during muscle regeneration.
Real-time PCR analysis The expression of MyoD1a, myogenin and Cadherin 15 (M-cadherin) that exhibited distinct temporal expression pattern as revealed by microarray experiment, was analysed by qPCR using a real-time PCR kit incorporating a SYBR® Green fluorophore (Applied Biosystems). The relative abundance of target cDNA within the sample set was calculated from a serial dilution (1:1-1:256) (standard curve) of pool cDNA using StepOneTM Software V2. 0. 2 (Applied Biosystems). Subsequently, real-time PCR data were normalised by dividing the raw data by the eF1α gene expression value.
Availability of data and materials Gene expression data supporting the results of this article are available in the Gene Expression Omnibus. (GEO) repository under the accession number GSE77223. http://www. ncbi. nlm. nih. gov/geo/query/acc. cgi?token=odkpcisgxfufner& acc=GSE77223. Also phylogenetic data have been deposited to TreeBase repository and are accessible via the URL: http://purl. org/phylo/treebase/phylows/study/ TB2:S19807.
Background Everolimus, a mammalian target of rapamycin (mTOR) inhibitor, has demonstrated efficacy in treating subependymal giant cell astrocytomas (SEGAs) and other manifestations of tuberous sclerosis complex (TSC). However, long-term use of mTOR inhibitors might be necessary. This analysis explored long-term efficacy and safety of everolimus from the conclusion of the EXIST-1 study (NCT00789828).
Procedures In the core phase, patients were randomly assigned 2:1 to receive either everolimus or placebo until the last patient randomly assigned had been treated for 6 months  [13]. After positive results were observed in the double-blind core phase (database cutoff, March 2, 2011), the study continued in a preplanned extension phase in which all patients remaining in the study at the end of the core phase could receive open-label everolimus until the last patient randomly assigned had been treated for 4 years. Everolimus was initiated at a dose of 4. 5 mg/m 2 /day based on body surface area and titrated to blood trough concentrations of 5-15 ng/mL, with adjustments allowed based on toxicity. Trough concentrations were monitored at each visit. Brain MRI and kidney computed tomography /MRI (for patients with 1 target renal angiomyolipoma, 1.
Statistical Analysis A detailed discussion of the methodology has been described previously  [13, 21]. The current analyses included all patients who received 1 dose of everolimus. Descriptive statistics were used to summarize baseline data at everolimus initiation. Changes of volume from baseline with exact 95% confidence intervals (CIs) were calculated for SEGA response and renal angiomyolipoma response. The 95% CIs were also calculated for skin lesion response rate. Summary statistics from the Kaplan-Meier curve determined median duration of SEGA response and median time to SEGA progression, with statistics given as point estimates with 95% CI. Height and weight were summarized using standard deviation scores (SDSs), taking into account the Centers for Disease Control and Prevention (CDC) growth charts.
Competing Interests: Dr. Franz received support from Novartis for other research at his institution, was consultant to Novartis (payments to employer CCHMC), received honoraria from Novartis and Lundbeck Pharmaceuticals, has been reimbursed by Novartis and Lundbeck Pharmaceuticals for travel costs for lectures, and performed legal work in reviewing medical malpractice cases, occasionally in giving expert testimony for various attorneys. Dr. Belousova received honoraria as speaker from Novartis and served as principal investigator on 2 research studies funded by Novartis Oncology. Dr. Sparagana received honoraria as a speaker for Novartis, served as site principal investigator on this and another research study funded by Novartis Oncology, serves on professional advisory board of Tuberous Sclerosis Alliance (TSA), and has received travel funds from the TSA related to role on the TSC Natural History Database Steering Committee.
Aerosol Index (AI) data (i. e. , AI is the product of MODIS AOD and the MODIS Ångström exponent) were collocated with the TRMM and CloudSat data. TRMM echo-top heights increased with increasing AI over the Amazon and Africa, and decreased over the equatorial Atlantic and southwest United States. Differences in CloudSat maximum reflectivity means of clean and dirty congestus were statistically significant at the 99 % level below 4 km over the Amazon, and at 4-5 km over Africa, but not at higher altitudes. It is important to note that changes in particle radius due to changes in aerosol also result in IWC profile perturbations, even in the absence of convective invigoration. Morrison and Grabowski (2011)  used a two-dimensional cloud-system resolving model to investigate aerosol indirect effects for pristine, polluted, and highly polluted conditions during a 6-day period of active monsoon conditions.
DARDAR profiles  (Delanoë and Hogan, 2008, 2010)  are a joint radar-lidar retrieval using CloudSat radar reflectivity and CALIOP lidar observations at 532 nm. We carry out our calculations over several years  (2007) (2008) (2009) (2010) , individual regions and seasons, in order to build up statistics. Section 2 discusses the data used in our study, Sect. 3 discusses the Methodology which is applied in a similar manner to the AOD, AAOD and CO data, and results are presented in Sect. 4. A discussion of the results and conclusions are presented in Sect. 5.
Data Ice water content vertical profiles are from the v2. 1. 0 DARDAR (raDAR/liDAR) data archive (http://www. icare. univ-lille1. fr/drupal/archive/) of the ICARE Thematic Center. The DARDAR cloud product is derived using the Varcloud algorithm  (Delanoë and Hogan, 2008)  and utilizes CloudSat reflectivity, and CALIOP lidar backscatter at 532 nm to jointly retrieve the properties of ice clouds (e. g. , IWC, visible extinction, effective cloud particle radius). There is one DARDAR profile, with a vertical resolution of 60 m, for every CloudSat radar profile and therefore an along-track horizontal resolution of 1. 7 km. Cloudsat  (Stephens et al. , 2002)  and the CALIOP lidar (on the CALIPSO satellite,  Winker et al. , 2010)  were launched in tandem in 2006 as part of the A-Train. We analyze data from all months of 2007 through 2010.
For this reason the combination of the two measurements improves the retrieval of cloud properties compared to single instrument retrievals. The DARDAR data focus on ice particles, so our analysis is restricted to altitudes above 5 km. Deng et al. (2013)  found reasonable agreement between CloudSat-CALIPSO (2C-ICE) and DARDAR retrieval products. IWC values from 2B-CWC-RO, 2C-ICE, and DAR-DAR generally are in good agreement, while 2B-CWC-RVOD radii were 40 % larger than the 2C-ICE and DARDAR radii. One stated concern in aerosol-indirect effect studies is that it is difficult to measure aerosol optical depths near clouds using nadir view satellite instruments. A cloud away from an observation point scatters light from the cloud towards the nadir observation point, which is then scattered towards the satellite sensor.
Varnai and Marshak (2009)  quantified how MODIS reflectance is enhanced as a function of distance to the nearest cloud. The reflectance is enhanced by ∼ 10 % when clouds are 5 km away from clear sky footprints at a wavelength of 0. 68 µm. Zhang et al. (2005)  compared AERONET and MODIS MOD04 AODs. They demonstrate that MODIS AODs are enhanced at cloud edges, with differences between MODIS and AERONET AODs increasing as the cloud fraction increases, while the AERONET values stay relatively constant. We address this concern in our calculations by using the latest V6 MODIS aerosol data that include a parameter indicating the average pixel distance from a measured AOD to the nearest cloud feature. MODIS version 6 MYD04 data files are used to specify daily aerosol optical depth fields. In particular, we utilize the "Optical_Depth_Land_and_Ocean" AOD values at 0.
Averages of the PDFs are indicated at the top of the panels. The arithmetic means of the PDFs are less for the AAOD and CO data than for the AOD data, with positive means for the AOD data, and negative means especially for the CO data. These results are supportive of the assertion that absorptive aerosol tends to inhibit cloud development. Figure  14  presents average IWCreg derivatives for AOD, AAOD, and CO data over ocean and land for all regions, excluding the largest derivatives. For legibility purposes, 1σ confidence limits of the determination of the means are given by the horizontal lines. The CO means over land and ocean are negative for the 7-15 km altitude range. Finally, Fig. 15  is similar to Fig. 14  except that average shape derivatives are presented. The AAOD and CO shape derivative means are less than the AOD means both over ocean and land for the 9-15 km altitude range.
In Fig. 15  there is a stark contrast between the positive AOD derivatives above 9 km altitude, and the negative CO derivatives. A portion of the contrasting positive and negative results reported in the literature is likely due to whether or not absorptive aerosol is absent or present in a particular set of observations. by the NASA Goddard Earth Sciences Data and Information Services Center (http://disc. sci. gsfc. nasa. gov/Aura/ data-holdings/OMI/omaeroe_v003. shtml and http://disc. sci. gsfc. nasa. gov/Aura, respectively).
De novo identification of repetitive sequence families in Taraxacum The RepeatExplorer pipeline via a Galaxy interface was applied to our datasets in order to cluster and assemble consensus sequences (contigs) of highly repeated fractions of the genome  [27]. The five accessions were analysed separately. Read clustering criteria included 55 % minimum overlap and 90 % minimum similarity in the overlapping region. All clusters containing at least 0. 2 % of the input reads were examined manually to identify clusters that required merging following recommendations and parameter settings from Kelly et al. [28]. Clusters were annotated according to similarity searches against the RepeatMasker Viridiplantae Database  [29] , the Conserved Domain Database  [30]  and GenBank non-redundant genomic database  [31].
TE family genomic content and level of transcription From a previous study, we developed Illumina transcriptomic resources for these same T. officinale Macranthoides accessions  [26]. For each accession, contigs assembled through the RepeatExplorer pipeline were used as a new TE database to which genomic and transcriptomic Illumina reads were mapped. This analysis enabled exploration of the most abundant TE family transcription activity at the cluster level. Both genomic and transcriptomic single reads were aligned and read abundance estimated per cluster using the Trinity pipeline, including Bowtie2 and RSEM methods  [36] [37] [38]. A quality score was given for each alignment and the best one was kept for abundance estimation. Log ratios of FPKM normalized values (as described by  [39] ) were used to quantify transcription for each cluster.
Combining variant calls from both Watson and Crick strands allowed for distinguishing genetic from epigenetic variation  [44]. Resulting variants were merged into two files: one for single methylation polymorphisms, the other for genetic polymorphisms using custom-made scripts freely available in github. The methylation output file included information on location and level of methylation for each cytosine position called. Methylation proportions were calculated as number of reads with methylated position divided by total number of reads matching that same position. Following analyses were based on a subset of highly confident positions called in all 5 accessions with a minimum of 50x coverage. Out of the 40,456 cytosines in the RRBS data, 4733 were found in CG context. Those positions were occurring on 623 RRBS loci.
DMRs were called using the same qualitative thresholds as for DMPs. Using BLAST, homologous sequences corresponding to all filtered loci and the DMR subset were retrieved from the genomic TE database, reference transcriptome and subsequent RNA-Seq data  [26]. We were thus able to annotate each loci as TE, functional transcripts or unknown. For each locus annotated as TE, transcript level was retrieved in all accessions.
Relationship between TE content and transcriptional activity To look at the relationship between TE genomic content and transcriptional activity, we used the newly made TE database to map previously generated RNA-Seq data  [26]. Regression analyses showed weak but positive relationships between RNA and DNA content for several accessions which were statistically significant for accessions 8 and 11 (Fig. 2 ). Conversely, no relationship was observed in accessions 12 and 13. The absence of a positive trend in these two accessions is at least partially However, TE families with highly homogeneous copies do not exhibit higher transcriptomic activity (Additional file 6). Using reduced representation bisulfite sequencing, out of 623 filtered loci we identified 111 DMRs, that showed a range of variation from low to intermediate methylation or from intermediate to high methylation between accessions, and we detected 7 "true" DMRs that ranged from low to high methylation between accessions.
The genomic proportions of highly repetitive DNA varied among accessions, ranging from 27. 4 to 38. 6 %. Except for DIRS, Penelope retrotransposons and TIR transposons, all superfamilies of TE known in plants were retrieved in the datasets [1]. Most widely distributed were Ty1/Copia and Ty3/Gypsy retroelements with Maximus/SIRE and Chromovirus lineages respectively, hAT transposons, Tandem repeats and ribosomal DNA. Only few LINE elements and other transposon families were found among the five accessions. The T. officinale genome is dominated by Class I LTR retrotransposons ranging from 21. 4 % (185. 2 Mb) to 31. 5 % (272. 4 Mb) depending on the accession. Ty1/Copia content was more constant among accessions (ranging from 9. 8 to 11. 7 %) than Ty3/Gypsy retroelements (9. 0-17. 7 %). Compared with Class I LTR retrotransposons, non-LTR retrotransposons and DNA transposons were relatively infrequent.
6 We have data on the local loop distances for each firm in the UK. It is worth noting immediately that these local loop distances did not affect the performance of the telephone 7 , so is unlikely to have affected the historic choice of firms of where to locate compared to the telephone exchange. The effect of distance on broadband speeds is also apparent only for a short-time These two features of the telephone network, enablement of exchanges for ADSL and local loop lengths, generate two sources of variation in access to broadband networks that predict firm broadband adoption. Our preferred analysis focuses on the latter as a single instrument, that is, firm-specific variation in local loop lengths (i. e. variation in ADSL broadband speeds) within the area of enabled exchange areas. That the time period we study coincides with rollout of ADSL across the UK offers a potential alternative instrument with which to test for the effect of broadband on firm-export decisions.
However, we do not focus on this approach out of concern that the timing of ADSL rollout may not satisfy the exclusion restrictions necessary for instrument validity. The ordering in which exchanges were enabled did not occur randomly, it was a commercial decision by BT. Exchanges with the greatest commercial return, greater numbers of potential customers and shorter average local loops, were therefore more likely to be enabled early on in the rollout programme. 9 The timing of enablement is potentially correlated with agglomeration economies, which will affect the performance of firms including its ability to export. We use this to instrument for firms' decisions to use broadband to test for the effects of broadband technology on the extensive and intensive margins of service exports. The data we employ is from three main sources.
Our source of firm level data is from the UK Office for National Statistics (ONS). Data on firm service trade transactions is from the International Trade In Services Inquiry (ITIS) and firm location and characteristics is from the Annual Respondent's Database (ARD) and Business Structure Database (BSD). These are the primary sources of UK firm-level data and have been used by Bloom et al (2012) and Breinlich   6 This was explained as being disqualified due to poor line quality. This could also occur for customers with a local loop length of less than 3. 5km if the line was deemed incapable of holding a broadband connection of sufficient speed. 7 A telephone call could be maintained for up to 16 kilometres and at least 5 kilometres from the exchange  (Macassey, 1985). 8 This was also known as 'extended reach ADSL'.