dataesr/scientific-paragraphs-categorization huggingface dataset:
Patients were categorized according to CKD stage  [12] : stage 1,. 89 mL/min/1. 73 m 2 ; stage 2, 60-89 mL/min/1. 73 m 2 ; stage 3a, 45-59 mL/min/1. 73 m 2 ; and stage 3b-5: ,45 mL/min/1. 73 m 2. CKD-EPI was selected since data suggest that it may be more accurate than other creatininebased formulae when applied to a population of patients in which a large proportion have eGFR. 60 mL/min/1. 73 m 2  [11]. Patients with CKD stages 3b, 4 and 5 (eGFR,45 mL/min/1. 73 m 2 ) were grouped since it was anticipated that there would be small numbers with stages 4 or 5 in particular. The prevalence of renal dysfunction and the differential characteristics of these patients are described. Management of these patients is also depicted. In order to explore medication use further, an analysis of how many patients received all cardiovascular preventive measures was performed.
Data for each renal function group were analysed according to the number (%) of patients who received 'all secondary preventive measures', defined as taking at least one medication from all three of the following drug categories: (i) antiplatelet, (ii) statin, and (iii) ACE inhibitor or angiotensin receptor blocker (ARB). Comparisons between the renal function groups were made using either one-way analysis of variance or the Kruskal-Wallis test for continuous data, depending on the distribution of the data, or the chi-square test for categorical data. Univariate and multivariable logistic regression analyses were also performed to ascertain the relationship between renal dysfunction and management. Analyses were performed to examine the effect of renal dysfunction on the use of ACE inhibitors and then separately the use of ARBs.
Discussion Published data on the prevalence of CKD in patients with stable CAD are scarce. The CLARIFY study population represents a unique, contemporary, global cohort of patients with stable CAD. In our study, where 22,272 patients were included, CKD (defined as eGFR ,60 mL/min/1. 73 m 2 ) is seen in just under one-quarter of patients with CAD and is associated with increasing age, female sex, cardiovascular risk factors, overt vascular disease, other comorbidities, and higher systolic but lower diastolic blood pressure. Severe CKD (eGFR,45 mL/min/1. 73 m 2 ), which has previously been shown to be associated with poor prognosis, is as common as AF (6. 9% and 7. 3%, respectively). Table  3. Drug treatment for all patients with available data according to eGFR group calculated using the CKD-EPI.
6% exhibiting CKD stages 3-5  [14]. In the Canadian study  [13] , the prevalence of comorbidities such as hypertension and diabetes mellitus was greater in those with CKD, but no real difference in lipid profile (excepting triglycerides) was seen. A similar finding in relation to lipid profile was seen in our population, where no meaningful clinical difference in lipids levels was seen across the CKD stages. The United States National Health and Nutrition Examination Survey dataset show a total crude CKD prevalence estimate for adults aged $20 years to be 16. 8%, of which 5. 4% were in CKD stage 3 and 0. 4% in stages 4 or 5  [15]. The prevalence of renal disease was significantly associated with age. The finding that almost one-quarter of subjects in the current study had CKD is likely to be explained in part by age but also by the high presence of comorbidities in patients with CAD, when compared with the general unselected population.
For example, the finding that wider pulse pressure, a marker of increased vascular stiffness  [16] , was more apparent in subjects with CKD could lead to the conclusion that it may underlie (at least in part) the renal dysfunction; yet it is equally plausible that it might be secondary to it (or perhaps both). It is hoped that the prospective nature of the CLARIFY study, with annual data collection, may help to tease out some of these complex relationships in more detail. Secondary prevention was generally very good across all categories of renal function with no meaningful differences in use of beta-blockers. This is a major difference when the current data are compared with historical datasets, most of which were obtained in an acute or subacute care setting  [8, [17] [18] [19]. These findings were consistent across subgroups of patients, such as those with a history of MI or CABG.
This study has a number of limitations. For example, there are no data available with respect to albuminuria, and data on left ventricular function (e. g. from echocardiogram) were not systematically required for the study. The current study population comprises 68% of the total CLARIFY population, due to insufficient baseline data being available in the remainder. In some countries ethnicity data were not collected due to legal or ethical reasons (hence eGFR could not be calculated) and not all subjects had recent local laboratory data available (not mandated for the study). Whilst CKD per se was not an exclusion criterion, it is plausible that subjects with more severely impaired renal function may have been excluded on the basis of this being considered as hampering the collection of 5-year follow-up data.
It is acknowledged that in clinical practice, decision-making regarding medical treatment by the responsible clinician is most likely to be influenced by serum creatinine and/or eGFR (e. g. in several countries MDRD-derived eGFR is routinely reported by laboratories). We believe that these potential limitations are overcome by the large size of the described cohort and the fact that the key findings are consistent irrespective of the method used to analyse renal function (in general qualitatively similar results with the MDRD formula [data not shown]). The data presented relate to 'current treatments' (i. e. those being taken when the patients were assessed at baseline). Owing to the nature of an observation study, it is not possible to ascertain whether patients were actually taking their prescribed medications.
In summary, baseline data from the CLARIFY study show that CKD is common in patients with stable CAD and is associated with age and comorbidities. Secondary prevention on the whole appears to be good, with high use of antiplatelet agents, statins, and beta-blockers. Around three-quarters of patients were prescribed either an ACE inhibitor or ARB, irrespective of renal function. In patients with severe CKD, there is lower use of ACE inhibitors, whereas ARBs are increasingly used. Yet the study shows opportunities for improvement in terms of increasing the proportion of patients taking all three evidence-based therapies for cardiovascular prevention. Many questions regarding the relationship between CKD and CVD remain unanswered. We believe that prospective data from the CLARIFY study will, in due course, help shed further light on this by permitting evaluation of the association of renal function on cardiovascular outcomes and mortality.
23 To strengthen the conclusion of the similarities between physiological variables measured at the end of the two exercises, we applied two others regressions: the Deming and the Passing-Bablok regressions. 26, 27 ilcoxon tests were used to determine whether maximal Borg rating symptoms (range 0-10) were different at the end of the 6MWT and 3CRT. Finally, baseline parameters were tested as predictive factors of the 3CRT-12 and 3CRT-20 results with a multivariate linear regression model using stepwise backward elimination to select the significant parameters. All statistical tests were done with Stata 12 (StataCorp LP, College Station, TX, USA), except for the comparison of methods, which was performed with the R package MethComp (Bland-Altman, Deming, and PBreg). 28.
Gene expression At baseline, month 2 or 3, month 12, and month 24 and yearly in the follow-up study, blood for analysis of mRNA expression was collected using the PAXgene system (Pre-AnalytiX GmbH, Hombrechtikon, Switzerland). Samples were also taken at CDMS if diagnosis occurred before month 24. Gene expression profiles of whole blood were measured using Affymetrix HGU 133 plus 2. 0 (affymetrix, Santa Clara, CA, USA) arrays according to the manufacturer's protocol. Raw data were RMA robust multi-array analysis background corrected,  17  quantile normalized,  18  and transformed with a logarithm to base 2. Probe sets were mapped and summarized to their respective Ensembl gene ID using custom cdf "HGU133Plus2_Hs_ENSG" version 15. 1. 0 (downloaded from http://brainarray. mbni. med. umich. edu/Brainarray/Database/CustomCDF/15.
Statistics To model the number of GELs as a function of 25(OH)D levels (both as continuous and dichotomized [<50 nmol/ L vs. ≥50 nmol/L] variables), IFNB-1b, and other covariates, generalized linear mixed models were applied using proc glimmix in SAS version 9. 2 (Cary, NC, USA), which account for the within-person correlation of the repeated measurements. A compound symmetry structure was used to model these correlations. Estimators were exponentiated to give risk ratios (RR). To determine whether 25 (OH)D or IFNB-1b was associated with gene expression, generalized linear models were used to model gene expression as a function of 25(OH)D levels, or IFNB-1b, adjusting for age, sex, treatment at the time of 25(OH)D measurement, and the interaction of 25(OH)D level and IFNB-1b. All time points were analyzed together in order to reflect and capture the time-dynamic variation of mRNA and maximize the power of the analysis.
Gene set analysis Gene Set Enrichment Analysis (GSEA) was done with the JAVA implementation of the GSEA preranked tool, as described previously. 22 Briefly, GSEA is a weighted modification of the Kolmogorov-Smirnov test, testing whether the distribution of test scores within a specific gene set significantly differs from the null distribution. Previously published gene sets for comparison were identified from the Molecular Signatures Database version 3. 1,  22  by searching for genes annotated with the gene ontology (GO) terms GO:0071305cellular response to vitamin D; GO:0070563negative regulation of VDR signaling pathway; GO:0070564positive regulation of VDR signaling pathway; GO:0070562regulation of VDR signaling pathway; or GO:0070561 -VDR signaling pathway and from two recently published studies on VDR-mediated gene expression.
23, 24 A description of each 25(OH)D gene set identified and their respective references are in Table  1. Gene-specific beta estimators quantifying the  association of a particular gene with GEL count or the association of 25(OH)D level or IFNB-1b with expression of a particular gene, estimated from the general linear models described above, were used as input vectors in the GSEA tool. For functional gene classification, the Database for Annotation, Visualization, and Integrated Discovery (DAVID)  25  was used as follows: the Affymetrix HGU Plus 2. 0 platform was selected as background and default  DAVID gene sets were tested with the exception of "Functional_Categories" and "Protein_Domains. ".
Promoter analysis Using the Multiple Em for Motif Elicitation (MEME) Suite of motif-based sequence analysis tools,  26  two vitamin D-responsive elements (VDRE) positional weighted matrices (PWMs) were inferred from VDR-ChIP sequencing data recently published by Heikkinen et al. 23  and Ramagopalan et al. 24  (see Fig. S1 ). Subsequently, we used the Find Individual Motif Occurrences (FIMO) tool with the inferred VDRE PWMs, the VDRE PWM available from the JASPAR database (ID MA0074. 1),  27 and the consensus Interferon Stimulated Response Element (ISRE) PWM published by Levy et al. ,  28  to screen for either of these motifs with a P-value detection threshold of 10 À4 in the upstream sequences database provided by FIMO. Of note, all three VDRE PWMs are highly similar. However, we screened for all three of them, since this will somewhat account for natural and context-dependent variability of the PWM which is not reflected using point estimates of base frequencies.
For example, plastic debris is accumulating at the shorelines of even the most remote islands and in the deep sea  [36]. Johan Rockstro ¨m and colleagues  [37]  claim that human actions have accelerated to such an extent that they might push the Earth beyond its ''planetary boundaries''. The term planetary boundary refers to thresholds between alternate states of the global system. Once crossed, the system enters a new state, and irreversible environmental change might be unavoidable. By now, the existence of thresholds has been posited for numerous ecological and social-ecological systems, including the marine realm (see the thresholds database of the Resilience Alliance and the Santa Fee Institute, http://www. resalliance. org/index. php/ thresholds_database). The world has entered a geological new era: the Anthropocene.
A genetic approach was also used to estimate pre-whaling abundance of Eastern Pacific gray whales. The results substantially differed from population reconstructions based on catch records, which had considered the population to be fully recovered  [91]. Both examples clearly demonstrate the relevance of molecular tools in defining baselines for management of marine species, and the recovery of depleted populations. Molecular tools also have an enormous potential to contribute to the discussion on detangling natural and anthropogenic drivers of change. A recent study using genetic data from the harbor porpoise (Phocoena phocoena) in the Black Sea was able to reconstruct the demographic expansion of this species some 5,000 years ago as a result of natural environmental changes, as well as its population collapse due to recent anthropogenic activity  [92].
Advancing methods for written documents and oral history The provenance of documents traditionally frames modes of inquiry in the history discipline. Port records, log books, tax ledgers etc. are typical sources of quantitative information, while interviews, written memories or newspaper coverage can provide both quantitative and qualitative information. Witness testimonies, especially, are increasingly used to acquire information on past and contemporary marine environments and fisheries. Through testimonies, individuals or groups share their perceptions and opinions about past events or experiences. Oral history helps to gather these accounts of the past, and to make use of traditional and local environmental knowledge that resource users have accumulated  [93]. If oral histories have been recorded or written down, the time span for which this kind of data can be used extends far beyond living memory.
Acknowledgements. This work was supported by the  Spanish Ministry of Economy and Competitiveness (MINECO)  (grant numbers  SAF-2010-17004  and  CSIC-201020I003  to M. L. A. ), the  Generalitat de Catalunya  (grant number  2009SGR1464 ), the  Fondo de Investigacion Sanitaria-Instituto de Salud Carlos III, Spain  (to MV, JB and CP), and the  I3 Program  from the  MINECO  (to CP). MJB was supported by the  CIBERER  and by the program  JAE DOC-CSIC/European Social Fund , and AL was supported by an  FI grant  ( AGAUR, Generalitat de Catalunya ). We express our gratitude to  Erika Ramı  ´rez and  Annabelle Parent  for their technical assistance, to  Sı ´lvia Miralles ,  Ma Carmen Badosa  and the personnel of the PRBB and PRAAL-PCB animal facilities for taking care of the mice, and to  Mark Sefton  for editorial assistance.
"SPARC Report No. 1 -Trends in the vertical distribution of ozone"  (SPARC, 1998)  provided a comprehensive summary of available data and methods for trend analysis at that time. Its main objectives were to understand the limitations of the data, to assess the consistency between various data records and create a reference database for the analysis of long-term ozone changes as a function of altitude. One of the main reasons for this approach was to avoid misinterpreting instrument drifts as actual ozone changes. Trend analysis is made more complex by the addition of new satellite records (e. g. Aura, Envisat, Odin, and SCISAT), where each covers a shorter time period than the traditionally used long-term records (e. g. ozonesondes, Umkehr, lidars, SAGE, HALOE). Adding to the problem, some of the long-term platforms have ceased taking measurements (e.
Such artifacts, like those introduced by changes of sonde type, can be removed through the use of transfer functions derived from intercomparisons in the laboratory or field. Most station long-term records are currently being re-evaluated and homogenized under the Ozonesonde Data Quality Assessment activity of the SI 2 N Initiative (H. G. J. Smit, personal communication, 2013). This should both reduce overall uncertainties and allow increased confidence in trends derived from ozonesonde data in future assessments. Ozonesonde profiles are archived by the World Ozone and Ultraviolet Radiation Data Center (WOUDC), the Network for the Detection of Atmospheric Composition Change (NDACC) and the Southern Hemisphere Additional OZonesondes network (SHADOZ) (see Table  1d  for more details).
The forward model used to process Brewer Umkehr data (O3BUmkehr v. 2. 6, http://www. o3soft. eu/o3bumkehr. html) was adapted from the UMK04 model taking into account the different optical characteristics of the Brewer instrument  (Petropavlovskikh et al. , 2011, see Table 1d). The Umkehr method uses a technique that minimizes systematic errors of instrumental drifts by normalizing to one of its measurements. Other methods are used to track instrument stability, such as once a month checks of wavelength registration by using standard discharge lamps, ratio of measurements at several spectral channels (for Brewer instruments, daily), and optical wedge calibration produced during Dobson intercomparisons (every 4 years). These methods track degradation of the optical system. Effects of ozone cross-section values and uncertainties of stray light effects on Dobson and Brewer Umkehr ozone profiles are discussed in  Petropavlovskikh et al.
(2011) and WMO (2008). The replacement of an instrument at the station can cause a step change in the Umkehr record due to the difference in the out-of-band contribution that is specific to each instrument. Thus, additional homogenization of the record may be required  (Zanis et al. , 2006; Miyagawa et al. , 2009). In addition, interference from optically thick aerosol loading (volcanic) at Umkehr spectral channels results in systematic errors that can be as large as 10-15 %. Therefore, about two years of data are typically removed after the Pinatubo (1991) and El Chichon (1982) volcanic eruptions. Data from 28 stations with current Umkehr measurements and of 58 stations with historical Umkehr measurements are archived at WOUDC, Toronto, Canada (see Table  1d  for the URL).
http://daac. gsfc. nasa. gov/ UARS MLS Version 5 was the last major public release of UARS MLS O 3 data  (Livesey et al. , 2003)  The official public distribution location for UARS MLS data is at the NASA GES-DISC Mirador website: (not available yet) http://mirador. gsfc. nasa. gov Aura MLS v2. 2 The official public distribution location for Aura MLS data is at the NASA GES-DISC Mirador website: the solid purple line represents the KIT retrieval, and the dash-dotted purple line represents the Bologna retrieval. The oscillating altitude resolution of the MIPAS KIT profile is a consequence of the evaluation of the averaging kernels on a vertical grid finer than the tangent altitude spacing: the vertical resolution is best at the tangent altitudes and coarsest between the tangent altitudes. Retrieval resolution for the Oxford and ESA processors is comparable to the KIT results; however, a courser grid is used for the retrieval and thus it does not show the oscillating features of the KIT processor.
For more detail on the different MIPAS retrievals see Sect. 3. 3. 4. However, measurement stability can be affected by instrumental artifacts such as alignment error, changes in the intensity of the lidar signals due to varying laser power, or changes in weather conditions  (Godin-Beekmann et al. , 2003). There are twelve stratospheric ozone lidar instruments operational globally at this point (see Fig. 1 ), with the longest continuous records starting in the late 1980s  (Steinbrecht et al. , 2009). Data are archived in the NDACC database (see Table  1d  for the URL).
This work was extended up to 2009 in the WMO 2010 ozone assessment report  (WMO, 2011)  for five European stations (28 • N to 79 • N). A current update up to 2012 is ongoing, involving additional stations, including stations in the Southern Hemisphere. The spectroscopic database has been changed to HITRAN 2008  (Rothman et al. , 2009) , and an additional effort of homogenization has been made in contrast to the work described in  Vigouroux et al. (2008) ; all stations are using a priori information from the model WACCM. The length of the FTIR ozone time series varies by station (see Fig. 1  for the geographical distribution of the stations); the longest time series available starts in 1995, and the shortest in 2002 (Fig. 2 ; Table  1c ). In the coming years, more recently established observatory stations (e.
g. Reunion Island: measurements started in 2009; Toronto: regular data containing the 1000-1005 cm -1 range started in 2010) or stations that have not yet reprocessed their retrievals using the optimized common strategy (e. g. : Eureka, Bremen) could be included in ozone trends studies. The FTIR data not yet available on the NDACC database (see Table  1d  for the URL) can be acquired by direct contact with the responsible principal investigator. There are currently 17 active long-term NDACC FTIR sites. An additional long-term site (Kitt Peak, AZ, USA (31. 9 • N, 111. 6 • W)) has data from 1978-2005, but operations have unfortunately ceased.
Ozone and other minor gas vertical profiles were retrieved by applying both the onion-peeling method and the nonlinear least-squares fitting method. Version 5. 20 ILAS and version 1. 4 ILAS-II ozone profiles were validated by comparing with various data sources  (Sugita et al. , 2002 (Sugita et al. , , 2006)). These validations showed that ILAS ozone data agreed with other data sets within ±10 % with a few exceptions between 11 and 64 km  (Table 1a, b). ILAS-II ozone data agreed with.
B. Hassler et al. : Ozone profile measurements other data sets within ±10 % at altitudes between 11 and 40 km for the Northern Hemisphere. Above 41 km, a negative bias between the NH ILAS-II ozone data and the other data increased, reaching 30 % at 61-65 km. Southern Hemisphere ILAS-II ozone data agreed with other data sets within ±10 % at altitudes between 11 and 60 km. Since the solaroccultation technique is used with both ILAS and ILAS-II, the instruments are self-calibrated by measuring 100 % and 0 % intensity of the sun each time before and after the atmospheric measurement. ILAS ozone data are archived at the ILAS and ILAS-II webpages (see Table  1d  for URLs).
For the ozone retrieval, spectral features between 984 and 1190 cm -1 are used. The spectroscopic parameters on which the calculations are based are derived from the HIgh-resolution TRANsmission (HITRAN) molecular absorption database 2004 line list  (Rothman et al. , 2005). The version 2. 2 ozone updated (herein v2. 2) data set was validated extensively by  Dupuy et al. (2009). In comparisons with ozonesondes and satellite limb sounding instruments, a small positive bias of +1 to +8 % (+5 % on average) was found between 16 and 44 km. At altitudes above 45 km, larger differences of up to +40 % (+20 % on average) are found for the v2. 2 ozone profiles. The current version of the ACE-FTS data set is version 3. 5  (Boone et al. , 2013). Waymark, et al. (2013)  have evaluated the differences between the well-validated v2.