dataesr/scientific-paragraphs-categorization huggingface dataset:
| METHODS THEMIS (NCT01991795) is a Phase 3b randomized, double-blinded, placebo-controlled trial of ticagrelor vs placebo, on top of low dose aspirin (75-150 mg) unless contraindicated or not tolerated. The primary hypothesis of the trial is that twice daily ticagrelor when added to aspirin will reduce the risk of CV death, MI, or stroke in patients with DM and stable coronary artery disease. Patients were initially randomized to 90 mg twice daily of ticagrelor or matching placebo (Figure  1 ). Partway through the trial, the dose in the ticagrelor arm was lowered to 60 mg twice daily to be consistent with updated product labeling of ticagrelor in response to external clinical trial data in patients with an MI more than 1 year previously. 14 Specifically, in PEGASUS, the efficacy profiles of ticagrelor 90 mg twice daily and 60 mg twice daily administered with low-dose ASA were similar to each other.
All endpoints were adjudicated by a blinded academic clinical endpoint committee. 6] [17]  To ensure data integrity, there was a firewall maintained between the clinical endpoint committee (CEC) and the data monitoring committee (DMC). Specifically, the DMC statistical data analysis center (SDAC), handling all unblinded study data, was located at Duke Clinical Research Institute (DCRI). The primary efficacy endpoint will be tested at a 4. 96% significance level (two-sided), adjusted for 1 planned efficacy interim analysis with family-wise error controlled at 5%. The one planned efficacy interim analysis occurred on the 29th of March 2017. The recommendation from the DMC was to continue the study according to the protocol. The estimated annual event rate in the placebo arm was 2. 5%. An effect size of 16% relative risk reduction was hypothesized, with 1385 primary endpoint events needed to provide 90% power.
14 e baseline characteristics of the THEMIS population suggest that it is very representative of daily practice in the care of DM patients. Thus, the results of THEMIS should be quite generalizable to the large number of patients with DM and stable coronary artery disease worldwide. Furthermore, the background medical therapy, such as statin use, is excellent, and therefore any observed benefits would truly be an incremental advance. Furthermore, THEMIS is the largest randomized trial of patients with DM performed to date. Beyond the randomized question being addressed, the THEMIS database will allow several important hypotheses to be tested in observational analyses using a large, wellcharacterized population of patients with coronary artery disease and DM. Limitations include the lowering of dose that occurred partway through the trial from ticagrelor 90 mg twice daily to ticagrelor 60 mg twice daily, which reduces the statistical power to examine either dose alone.
There is extensive debate regarding the protective effect of 3-hydroxy-3-methylglutaryl-coenzyme A reductase inhibitors (statins) on colorectal cancer (cRc). We aimed to assess the association between CRC risk and exposure to statins using a large cohort with prescription data. We carried out a casecontrol study in Catalonia using the System for Development of Primary Care Research (SIDIAP) database that recorded patient diseases history and linked data on reimbursed medication. the study included 25 811 cases with an incident diagnosis of CRC between 2010 and 2015 and 129 117 frequencymatched controls. Subjects were classified as exposed to statins if they had ever been dispensed statins. Analysis considering mean daily defined dose, cumulative duration and type of statin were performed. Overall, 66 372 subjects (43%) were exposed to statins.
Methods Data source. Subjects were selected from the Information System for Development of Primary Care Research (SIDIAP) database (www. sidiap. org)  21 , which comprises clinical information routinely collected by primary care professionals of the Catalan Institute of Health. This database includes information from 5. 8 million people in Catalonia (almost 80% of the population) that have ever contacted the public health system since 2005. The data retrieved included routine clinical data, such as diagnoses and health measurements, and was linked to information on dispensed prescriptions generated by pharmacies' claims for reimbursement by the Catalan Health System. Drugs were coded according to the Anatomical Therapeutic Chemical (ATC) classification system  22  , and the date and quantity of the drug withdrawn from the pharmacy were recorded.
Irreversible encoding of patient identifiers ensured anonymization of the information in the SIDIAP study database. The quality of SIDIAP data has been previously documented, and it has been used to study the epidemiology of health outcomes  23. All procedures performed in the study involving data from human participants were in accordance with the ethical standards of the institutional research committee, and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards. No informed consent was requested to the participating individuals, since this study was based on anonymized data routinely collected. No variables with potential to identify specific individuals were retrieved. The study protocol was approved by the Ethics Committee for Clinical Research of IDIAP Jordi Gol and all applicable regulatory requirements were fulfilled.
Study design. A population-based case-control study nested within the cohort of subjects receiving primary care from the Institut Català de la Salut was conducted. The flow chart of the study is described in Fig. 1. The cohort of subjects registered in SIDIAP with at least one healthcare interaction in last 3 years (n = 5 830 562) was limited to adult population, aged 18 to 90 years (n = 4 664 450). Cases identified with a recorded incident diagnosis of colon or rectum (codes C18, C19, and C20 of the International Classification of Diseases 10th Revision [ICD-10]) within the period January 1, 2010 to December 31, 2015 were identified. Those cases with a diagnosis of appendix cancer (C18. 1) were excluded to avoid the inclusion of carcinoid tumours which are more frequent in that location. A random stratified selection of controls was obtained using the same SIDIAP database.
For each case, five controls were randomly selected from the set of all subjects in the database without prior CRC and alive at the time of diagnosis of the case, with the same age (±5 years) and sex and living in the same region defined by the primary healthcare centre catchment area. For cases, the disease onset date, defined as the earliest CRC diagnosis date registered, was set as the index date. For controls, the index date of their matched case was applied. Information regarding comorbidities and drug use was truncated to that recorded prior to the index date for cases and controls.
Exposure variables. Patients were classified as exposed to statins if they had retrieved at least one dispensation with an Anatomical Therapeutic Chemical code beginning with "C10AA"; otherwise, they were classified as unexposed. We also obtained exposure data for nonsteroidal anti-inflammatory drugs (NSAIDs) including aspirin (M01A, N02BA, N02BB, and B01AC06) as they potentially could confound the association between statin use and cancer risk, and other lipid lowering drugs (C10AB, C10AC, C10AD, C10AX). Daily defined doses (DDD) for each dispensed prescription were calculated by multiplying the container pills by dose (in mg) and dividing by the World Health Organization defined DDD (in mg) for each individual drug  22. The average dose for each of these duration categories was established, dividing the sum of DDD by the interval length.
Statistical analysis. Odds ratios (OR) and 95% confidence intervals (95% CI) were calculated from unconditional logistic regression models. We compared the effect of no use to any use of drug and assessed effects of dose (DDD) and duration of statin use. We also explored the effect of the type of the statin (potency and lipophilicity). Subgroup analyses were performed according to sex, age groups, NSAID use and cancer location (colon or rectum). Missing data for body mass index (BMI) was imputed using the prediction of a linear model according to age, sex and, outcome status (63% had complete data). To avoid models with many parameters, an adjustment score was built from the predictions of a logistic regression model for CRC that included all potential confounding covariates, without selection strategies.
Discussion In this study, based on the SIDIAP database, which is representative of the Catalan population, we found a high prevalence of exposure to statins, above 40% both in cases and controls. We observed that exposure to statins was not significantly associated with the overall risk of CRC, but might be associated to a modestly reduced rectal cancer risk. For colon cancer or the combination of colon and rectal cancer (colorectal), there was no decrease in risk associated with statin use. There were no consistent associations observed for duration and cumulated dose of statin exposure and rectal cancer, while the protective association was similar for diverse statin types. Besides, exposure to acid bile sequestrants showed an increase of risk of 33%. Previous case-control and cohort studies have suggested that statins could play a role in cancer chemoprevention  12, 13.
However, data from clinical trials have not confirmed the protective effect seen in observational studies  14. Recently, two meta-analyses and one systematic review including 40, 42, and 59 individual studies, respectively  14, 15, 20  , reported a modest reduction in risk of CRC among statin users. In contrast, previous studies that linked pharmacy and cancer registry databases found no associations between statin use and CRC risk  [27] [28] [29] [30] [31] [32] [33] [34]. Our study adds further evidence to the lack of a relevant effect of statins on the risk of incident CRC, supporting that any effect, if present, is of marginal magnitude. Our observation of a significant 11% increase of risk related to statin exposures shorter than 5 years is isolated, not found in other analysis such as the one exploring tumour location, and thus is of uncertain value.
Regarding exposure, we used actually dispensed prescriptions at pharmacies. Though there is no way to prove that dispensed prescriptions were actually consumed, data on dispensed drugs is more reliable than electronic prescriptions, which may overestimate exposure at the expense of prescriptions that are never dispensed at pharmacies. Another limitation was that we could not adjust for some risk factors for CRC like physical activity, diet or family history of CRC, because these data were not available or did not reach usable quality. Finally, we have observed in our population that a lower BMI was associated with CRC. This is a typical finding in case-control studies, because the BMI data is registered close to the cancer diagnosis, in order to objectivize weight loss caused by the CRC as a part of the diagnostic procedures, while controls may have BMI recorded more often when obesity is requiring a clinical intervention by primary care physician.
The strengths of this study include the large sample size, and the high representativeness of the population, since SIDIAP includes data on roughly 80%% of the Catalan population. Because SIDIAP contains data collected in routine practice conditions, the likelihood of observer bias is minimized. The use of electronic medical records and invoicing databases allowed us to overcome memory bias. Despite the study period was limited to 2010-2015, individual medication data was available from 2005 onwards, which allowed us to study a long period of exposure, ensuring a minimum of 5 years before the CRC diagnosis. This is of paramount importance when studying diseases with long latency such as cancer, and, in fact short exposure time is a major criticism to statin randomized trials. In conclusion, this study adds further evidence about the lack of a relevant association between statin utilization and risk of incident CRC.
Statistics Continuous variables are reported as mean ± standard-deviation (SD), and range: [minmax]. The Gaussian distribution of the continuous variables was assessed using the D'Agostino-Pearson test, particularly the WSS values in all patients' groups. Categorical data were analyzed using the Chi-squared test when appropriate. Continuous variables (arterial diameters, BFVel, BFVol and WSS,) were analyzed with a one-way ANOVA according to the score of surgery (CCR0 or CCR1-3) and stability or recurrence/progression of the disease. In both cases, when ANOVA was significant, differences between groups were evaluated with post-hoc Student-Newman-Keuls and unpaired Student t-test. In all case, power of the tests were verified and considered as significant when >80% (http://www. anastats. fr, ANASTATS, Rilly Sur Vienne, France)  [28].
A receiver operating characteristics (ROC) curve of Doppler measurements was built and cut-off values were calculated to discriminate: between patients who had severe active progressive disease (Group-3) from those with slowly progressive disease (Group-2). Sensitivity, specificity and areas under curves (AUC) with their 95% confidence intervals (95%CI) were calculated. Cut-off for WSS values was computed. (MedCalc® Statistical Software version 18. 2. 1, MedCalc Software bvba, Ostend, Belgium). Only P values <0. 05 were considered significant  [29].
Results The data events are analyzed in three exclusive channels, according to the number of jets in the final state. The expected signal and background estimation shown in Table  1 , and the systematic uncertainties described in Section 10 are used to construct a binned likelihood (Eq. (  4 )) as. 5-5% - - - -ISR 2-3% - - - -FSR 0-9% 0-12% - - -Color reconnection 0-3% - - - -b jet fragmentation 0-3% 0-5% - - -b hadron branching fraction 3% 2. 5-3% - - Weak correction δ QCD δ W 0-0. 2% (Y t =2) - - - a product of the Poisson probabilities from all bins in (M tt ,|∆y tt |). From this, we construct a profile likelihood ratio test statistic q(Y t ) = -2 ln L(Y t , θ)/L( Ŷt , θ) , where θ in the numerator denotes the value of the estimator θ that maximizes the likelihood for a specific Y t , i.
e. , it is the conditional maximum-likelihood estimator of θ (and thus is a function of Y t ). The denominator is the maximized (unconditional) likelihood function, i. e. , Ŷt and θ are the values of the estimators that simultaneously maximize the likelihood. The statistical procedure to extract the parameter of interest is detailed in Ref. [62]. The distributions of M tt and |∆y tt | after performing the combined likelihood fit are shown in Fig. 10. The analysis covers the phase space from the production threshold in M tt (which is ≈200 GeV at the detector level for events with three reconstructed jets) up to 2 TeV. Fit yields Data  We measure the top quark Yukawa coupling by scanning the likelihood function with respect to Y t. The likelihood scan distributions can be found in Fig. 11. The expected and observed results are presented in Table  3.
Individuals have received support from the  Marie-Curie program  and the  European Research Council and Horizon 2020  Grant, contract Nos. 675440  and  765710  ( European Union ); the  Leventis Foundation ; the A. P. Sloan Foundation; the  Alexander von Humboldt Foundation ; the  Belgian Federal Science Policy Office ; the  Fonds pour la Formation à la Recherche dans l'Industrie et dans l'Agriculture (FRIA-Belgium) ; the  Agentschap voor Innovatie door Wetenschap en Technologie  ( IWT-Belgium ); the  F. R. S. -FNRS  and  FWO (Belgium)  under the  "Excellence of Science -EOS" -be. h project n. 30820817; the  Beijing Municipal Science & Technology Commission, No. Z181100004218003 ; the  Ministry of Education, Youth and Sports (MEYS)  of the Czech Republic; the  Lend ület ("Momentum") Program  and the  János Bolyai Research Scholarship of the Hungarian Academy of Sciences , the  New National Excellence Program ÚNKP , the  NKFIA  research grants  123842 ,  123959 ,  124845 ,  124850 ,  125105 ,  128713 ,  128786 , and  129058  (Hungary); the  Council of Science and Industrial Research, India ; the  HOMING PLUS program  of the  Foundation for Polish Science , cofinanced from  European Union, Regional Development Fund , the  Mobility Plus program of the Ministry of Science and Higher Education , the  National Science Center (Poland) , contracts Harmonia  2014/14/M/ST2/00428 ,  Opus 2014/13/B/ST2/02543 ,  2014/15/B/ST2/03998 , and  2015/19/B/ST2/02861 , Sonata-bis  2012/07/E/ST2/01406 ; the  National Priorities Research Program  by  Qatar National Research Fund ; the  Programa Estatal de Fomento de la Investigaci ón Científica y Técnica de Excelencia María de Maeztu , grant  MDM-2015-0509  and the  Programa Severo Ochoa del Principado de Asturias ; the Thalis and Aristeia programs cofinanced by  EU-ESF  and the  Greek NSRF ; the  Rachadapisek Sompot Fund for Postdoctoral Fellowship, Chulalongkorn University  and the  Chulalongkorn Academic into Its 2nd Century Project Advancement Project (Thailand) ; the  Welch Foundation , contract  C-1845 ; and the  Weston Havens Foundation (USA).
4) and adding manganese dioxide to oxidize ABTS. The absorbance for standard curve and samples was measured at 734 nm with a Spectro UV-VIS RS 1166 (Labomed Inc. , USA). The results were expressed as μmol of Trolox equivalent antioxidant capacity (TEAC) kg -1 fresh weight (FW). Statistical analysis was performed using software SigmaPlot, version 11. 0 (Systat Software Inc. , USA). Descriptive statistic was done for each group of measurement. Standard errors of the means were calculated and they are stated in the tables. Differences between treatments were estimated by a two-way ANOVA/MANOVA procedure Statistica 99 (StatSoft Inc. , USA), and the Student's t-test was used to determine the significant differences between the means.
, 2017). Comparison between cherry and large fruits showed that in both optimal and drought conditions fruits of cherry tomato had a higher total carotenoid content than large fruits, mainly due to higher content of lycopene and phytoene (Tables  4  and 5 ). In this study, the effect of drought stress was more expressed on β-carotene accumulation than lycopene that could be indirectly connected to their role in the biosynthesis of plant water-stress related hormones as abscisic acid  (Riggi et al. , 2008). Tomatoes are characterized by high fruit antioxidant capacity, and many literature data indicated that this trait is genotype specific (Nour et al. , 2013; Klunklin, Savage, 2017). Our study showed that long term moderate drought stress induced the increase of total antioxidant capacity in all analysed genotypes, but this effect was more expressed in cherry than in large tomato fruits (Table  6 ).
495, p ≪ 0. 005). Genome size is significantly smaller in holometabolous insects than in nonholometabolous insects (one-way ANOVA, p = 0. 0001). Using the ape package v. 4. 1  [46]  for R  [47] , we tested for correlation between TE content and genome size using phylogenetically independent contrasts (PIC)  [48]. The test confirmed a significant positive correlation (Pearson product-moment correlation, ρ = 0. 497, p = 0. 0001, corrected for phylogeny using PIC) between TE content and genome size. Additionally, genome size is correlated with TE diversity, that is, the number of different TE superfamilies found in a genome (Spearman, ρ = 0. 712, p ≪ 0. 005); this is also true under PIC (Pearson, ρ = 0. 527, p ≪ 0. 005; Additional file 2: Figure  S1 ).
We were able to reach these conclusions by relying on two essential non-standard analyses. First, our annotation strategy of de novo repeat library construction and classification according to the RepBase database was more specific to each genome than the default RepeatMasker analysis using only the RepBase reference library. The latter approach is usually done when releasing a new genome assembly to the public. The second difference between our approach and the conventional application of the RepBase library was that we used the entire Metazoa-specific section of RepBase instead of restricting our search to Insecta. This broader scope allowed us to annotate TEs that were previously unknown from insects, and that would otherwise have been overlooked. Additionally, by removing results that matched non-TE sequences in the NCBI database, our annotation becomes more robust against false positives.
Genomic data sets We downloaded genome assemblies of 42 arthropod species from NCBI GenBank at ftp. ncbi. nlm. nih. gov/genomes (last accessed 2014-11-26; Additional file 4: Table  S2 ) as well as the genome assemblies of 31 additional species from the i5k FTP server at ftp://ftp. hgsc. bcm. edu:/I5K-pilot/ (last accessed 2016-07-08; Additional file 4: Table  S2 ). Our taxon sampling includes 21 dipterans, four lepidopterans, one trichopteran, five coleopterans, one strepsipteran, 14 hymenopterans, one psocodean, six hemipterans, one thysanopteran, one blattodean, one isopteran, one orthopteran, one ephemeropteran, one odonate, one archaeognathan, and one dipluran. As outgroups we included three crustaceans, one myriapod, six chelicerates, and one onychophoran.
Construction of species-specific repeat libraries and TE annotation in the genomes We compiled species-specific TE libraries using automated annotation methods. RepeatModeler Open-1. 0. 8  [94]  was employed to cluster repetitive k-mers in the assembled genomes and infer consensus sequences. These consensus sequences were classified using a reference-based similarity search in RepBase Update 20140131  [95]. The entries in the resulting repeat libraries were then searched for using nucleotide BLAST in the NCBI nr database (downloaded 2016-03-17 from ftp://ftp. hgsc. bcm. edu:/I5K-pilot/) to verify that the included consensus sequences are indeed TEs and not annotation artifacts. Repeat sequences that were annotated as "unknown" and that resulted in a BLAST hit for known TE proteins such as reverse transcriptase, transposase, integrase, or known TE domains such as gag/pol/env, were kept and considered unknown TE nucleotide sequences; but all other "unknown" sequences were not considered TE sequences and therefore removed.
Validation of Alu presence To exemplarily validate our annotation, we selected the SINE Alu, which was previously only identified in primates  [67]. We retrieved a Hidden Markov model (HMM) profile for the AluJo subfamily from the repeat database Dfam  [96]  and used the HMM to search for Alu copies in the genome assemblies. We extracted the hit nucleotide subsequences from the assemblies and inferred a multiple nucleotide sequence alignment with the canonical Alu nucleotide sequence from Repbase  [95].
Genomic TE coverage and correlation with genome size We used the tool "one code to find them all"  [97]  on the RepeatMasker output tables to calculate the genomic proportion of annotated TEs. "One code to find them all" is able to merge entries belonging to fragmented TE copies to produce a more accurate estimate of the genomic TE content and especially the copy numbers. To test for a relationship between genome assembly size and TE content, we applied a linear regression model and tested for correlation using the Spearman rank sum method. To see whether the genomes of holometabolous insects are different than the genomes of hemimetabolous insects in TE content, we tested for an effect of the taxa using their mode of metamorphosis as a three-class factor: Holometabola (all holometabolous insect species), non-Eumetabola (all non-holometabolous hexapod species, with the exception of Hemiptera, Thysanoptera, and Psocodea;  [99] ), and Acercaria (Hemiptera, Thysanoptera, and Psocodea).