dataesr/scientific-paragraphs-categorization huggingface dataset:
Alternative analyses, such as flexible additive models, have been proposed in order to overcome troublesome timeseries data  156, 157. The use of additive models on datasets from Kassjön and Loch Coire Fionnaraich 156 demonstrated that these models allow the effects of co-variates through time to be separated, evaluated and compared. The flexibility in the additive models allows for their application to regular and irregular timeseries (as found in sediment cores). Additive models can also provide robust results in cases where the palaeolimnological record is complemented by long-term monitoring data. An example from Esthwaite Water (UK) provided a rare opportunity to undertake such analyses, with climate and water quality data extending back to 1945 CE. The use of these data in conjunction with sedimentary diatom records, gave a unique insight into the role of climate and nutrients on a lake ecosystem  44.
Palaeolimnological study design The ideal palaeolimnological study is conducted on continuous, undisturbed sediment sequences with reliable chronologies. However for many lake cores, these conditions are not necessarily met, where the cores are exposed to issues related to mixing, sediment focusing (see Box 2) or human disturbance of the record (dredging for example)  173, 174. A well-designed study, with careful site selection can often negate some of these effects  175. What is desirable, however, is the use of a multiproxy, multidisciplinary, multi-site approach to analysing sediment records, allowing some of the ambiguity regarding the interpretation of the records to be circumnavigated. Ideally, when undertaking statistical analyses of sediment cores to apportion the relative contribution of human or climate drivers, the proxy response data would be coupled with a compatible time series of measured or monitored drivers.
g. ship records and missionary diaries pertaining to weather) quantitative data are seldom available, rather they are qualitative in nature. Despite this, sparse and often ad hoc records can provide excellent insights (and independent climate records 179 ); notable examples come from missionary diaries from East Africa  180, 181. In the absence of millennial timeseries data, the most common way of collecting data on the drivers of ecosystem change comes from the sediment cores themselves, but we must be wary of circularity and ensure that all the data used are independent. For example, we may have to be clear about using biological indicators as response data, and not using them as a proxy for the driver. It would not be appropriate to use a proxy indicator to infer a driver of change (e. g.
CONCLUSION Aquatic ecosystems, globally, are currently under threat from both climatic and anthropogenic forcing of the environment. Lake sediments are an important archive of how these drivers of change have altered in time and the impact that these changes have had on lake ecosystems. Given the limited spatial and temporal extent of measured changes in lake state, and the fact much of this is done on already impacted systems, palaeolimnology provides a crucial tool to aid management of future freshwater resources. The need for such work is clear given the complexities of lake systems discussed here, and the numerous potential drives of, and responses to, change. Careful research design and data analysis is needed to allow us to begin to pick apart the complexity of the signals recorded in lake sediments.
ACKNOWLEDGEMENTS This work is, in part, a result of a number of meetings of the  Past Global Changes (PAGES) Working Group Aquatic Transitions. The authors wish to thank  PAGES  for their financial support of two workshops, during which time ideas surrounding this topic have been discussed in depth. The authors would also like to thank  Peter Rasmussen  ( GEUS)  for the use of his data from  Gudme Sø. Neotropical palaeolimnological examples arise from projects funded by  CONACYT 252148  and  PAPIIT-UNAM IA100317  (to  Liseth Perez  and  Julieta Massaferro. Keely Mills  publishes with the approval of the Executive Director,  British Geological Survey (NERC ).
EXPERIMENTAL PROCEDURES RNA-seq and ChIP-seq Data RNA isolation was performed using miRNeasy kits from Qiagen, and an in-column DNase treatment was included. RNA was measured using a Nanodrop (Thermo), and integrity was confirmed in a 6000 Nano chip Bioanalyzer (Agilent). We then used the TruSeq Stranded mRNA Sample Prep Kit v2 (Illumina) to obtain a paired-end strand-specific RNA-seq library. See Table  S2  for further details of conditions. Cell Systems 2, 391-401, June 22, 2016 399 ChIP-seq of RNAP (TAP-tagged; see  Ku ¨hner et al. , 2009)  was performed as previously described  (Yus et al. , 2012).
TSSs and Manual Annotation of Operons and Sub-operons We identified all mRNA TSSs from their associated tssRNAs  (Yus et al. , 2012). We distinguished productive promoters from short tssRNAs as explained previously  (Llorens-Rico et al. , 2015). Regarding 3 0 sites, we used strand-specific deep sequencing and tiling array data to define approximately their positions  (Gu ¨ell et al. , 2009). We then used these data to refine our previously published operon map  (Gu ¨ell et al. , 2009)  (updated map in Table  S1 ). Real-Time qPCR of Regions Encompassing Distinct Operons Cells were collected in the indicated conditions, and RNA was purified as described above. Retrotranscription and real-time qPCR of $800 base long regions were done in one step with the GoTaq 1-Step RT-qPCR System (Promega).
Intrinsic Terminators and RPODs Potential intrinsic terminators were defined as a RNA hairpin immediately followed by a U tract. RNA hairpins were identified as described previously  (Mathews et al. , 1999). RPODs were identified by the presence of significant peaks (see Supplemental Experimental Procedures) in the ChIP-seq data of the RNAP a-subunit (gene MPN191) at 6 and 96 hr. RNA Half-Lives RNA half-lives were determined using a DNA gyrase inhibitor (novobiocin), which alters the chromosomal supercoiling releasing the RNAP, thus stopping transcription  (Dorman, 2011). After novobiocin treatment, RNA was extracted at different time points, and RNA-seq was performed to determine transcript levels. Half-lives were estimated by fitting RNA decays using an exponential function.
ACKNOWLEDGMENTS I. J. is supported by an  ATIP-Avenir grant  ( Centre National de la Recherche Scientifique ). E. B. U. was co-funded by  Marie Curie Actions. This work was supported by  Fundacion Marcelino Botin  and the  Spanish Ministerio de Economı ´a y Competitividad  ( BIO2007-61762 ). This project was financed by  Instituto de Salud Carlos III  and co-financed by  Federacion Espan ˜ola de Enfermedades Raras  under grant agreement  PI10/01702  and the  European Research Council and European Union 's  Horizon 2020 research and innovation program  under grant agreements  634942  (MycoSynVac) and 670216 (MYCOCHASSIS). The Centre for Genomic Regulation  acknowledges the support of the  Spanish Ministry of Economy and Competitiveness , '' Centro de Excelencia Severo Ochoa   2013-2017 ,''  SEV-2012-0208.
Yet, the poor prognostic value of HER3 and/or heregulin-1ß remains controversial in other cancers such as bladder cancer  [15] , uveal melanoma  [16]  and lung adenocarcinoma  [17]. Data regarding the HER3 status in HCC are scarce. Available data have been essentially obtained from populations of Asian patients with viral hepatitis. A Japanese study reported that 64 out of 84 HCC were positive for cytoplasmic HER3 by immunohistochemistry  [18]. The transcriptomic profile of 37 hepatitis B virus (HBV)-related HCC showed that HER3 mRNA was one of the most frequently induced  [19]. More recently, a Taiwanese group reported that upregulation of HER3 mRNA was associated with HBV etiology, microvascular invasion, early recurrence and poor clinical outcome in 71 patients with HCC  [20]. No data are available regarding heregulin-1ß expression in HCC.
Accordingly, we observed that HER3 mRNA levels were low in HCVrelated HCC. Altogether, these data suggest that the expression of HER3 mRNA is regulated differentially by the viral factors contributing to HCC. Fold induction for HER3 mRNA expression was also higher in well/moderately differentiated tumours than in poorly differentiated ones. In the same setting, studies conducted on a large panel of hepatoma cell lines showed that HER3 expression was higher in cell lines with an epithelial phenotype than in those with a mesenchymal phenotype  [29, 30] , suggesting that HER3 is rather a marker of epithelial traits in HCC. Autocrine expression of heregulin-1ß has been reported to be a predictive biomarker for response to anti-HER3 antibodies, even in tumours showing no significant prognostic association between heregulin-1ß and OS or PFS  [31, 32].
Migrated cells were enumerated by microscopy following nucleic acid staining with DAPI. b Huh7 cells were submitted to a wound-healing assay by scraping cell layer with a p200 pipet tip and were treated for 48 h with 10 -8 M insulin and/or 50 ng/ml heregulin-1ß. The wound closure (% of H0) was measured liver-disease etiology. Altogether these data suggest that HCC patients may not derive significant clinical benefit from HER3-directed monotherapies. There is no standardized method for HER3 detection by immunohistochemistry and information regarding HER3 staining in HCC are limited. The sole extensive study was published with the clone 2F12, which showed frequent HER3 cytoplasmic staining in HCC  [18]. In our hands, this clone (and two other ones) did not give signals while the clone RTJ1 yielded cytoplasmic staining but was not reproducible in terms of intensity.
ACKNOWLEDGEMENTS We would like to acknowledge the help and inspiration for the following people:  Remi Bellia  for providing information of pescatourism in France and in Algeria,  Christian Decugis  for providing information of FLAGS activities related to pescatourism and  Nikolas Michailidis , from the  Fisheries Department of Cyprus , providing information on most recent pescatourism initiatives in this country. We also thank  Ozkan Anil ,  Volker Gries ,  Jolanta Kiełpińska ,  Maciej Kiełpiński ,  Chris Lawrence ,  Tonino Morra ,  Piotr Nowakowski , and  Martin Rurik  from allowing us to use their photographs. I appreciate the assistance of  Milana Długopolska  in clarifying some Italian legal statements.
Several other additional imaging methods, such as lung volumetry, 3D ultrasound and Doppler studies of the pulmonary vascularization, have been shown in individual series to be prognostic for pulmonary hypertension, the need for extracorporeal membrane oxygenation (ECMO) and survival  [8]. All of these remain research tools, how-ever, but may ultimately improve the predictive value of prenatal testing. An experienced tertiary center with a high case volume ( ≥ 6 CDH patients per year) is the optimal environment for the delivery and neonatal treatment of prenatally diagnosed CDH fetuses  [9, 10]. Prenatal intervention by fetal endoscopic tracheal occlusion (FETO) has been proposed to promote lung growth  [11]. Therefore, FETO is being evaluated in two randomized clinical trials both in moderate (first interim analysis stage reached; >100 patients randomized) and severe cases (>25 patients randomized) in centers in Europe, Australia and Canada (TOTAL trial  [12]  ; NCT01240057).
Delivery The timing and preferred mode of delivery in CDH pregnancies are still controversial. Hutcheon et al. [14]  showed that neonatal and infant mortality significantly decreased with advancing gestation, from 25 and 36% at 37 weeks of gestation, respectively, to 17 and 20% at 40 weeks of gestation, respectively. Moreover, a study from Odibo et al. [15]  among 107 CDH cases found that gestational age at delivery was inversely correlated to the need for ECMO. However, Safavi et al. [16]  found no difference in mortality when dividing gestational age at delivery categorically as under 37 weeks, 37-38 weeks and 39 weeks or beyond. Neither did they find a difference in mortality between vaginal and cesarean delivery  [16]. In the absence of true convincing data it seems intuitive to schedule delivery (induced delivery or cesarean section) carefully in the best possible conditions also dependent of maternal indications, i.
At the same time, WACMOS-ET is a direct contribution to GEWEX LandFlux, sharing the long-term goal of achieving global closure of surface water and energy budgets. The project objectives strive to (a) develop a reference input data set consisting of satellite observations, reanalysis data and in situ measured meteorology, (b) run a group of selected evaporation models forced by the reference input data set, and (c) perform a cross comparison, evaluation, and validation exercise of the evaporation data sets that result from running this group of models. Four algorithms that are commonly used by the research community have been tested: the Surface Energy Balance Model (SEBS;  Su, 2002) ; the Penman-Monteith approach that sets the basis for the official Moderate Resolution Imaging Spectroradiometer (MODIS) evaporation product, hereafter referred to as PM-MOD  (Mu et al.
Input data One of the objectives of the WACMOS-ET project has been to correct for a recurring issue in inter-product evaluations of global evaporation: due to inconsistencies in the forcing data behind current evaporation products, it is difficult to attribute the observed inter-product disagreements to algorithm discrepancies  (Jiménez et al. , 2011; Mueller et al. , 2013). Consequently, one of the first steps in WACMOS-ET has been to compile a reference input data set that has been used to run all models in a consistent manner. This consistency applies to both local-scale runs (in Part 1) and regional and global runs (in the present study). On the other hand, since neither the required input variables nor the models' sensitivity to these input variables and their uncertainties are the same for all models (see Table  1 ), it is not possible to fully attribute observed differences in performance to internal model errors.
The target grid resolution of WACMOS-ET is 25 km, the domain is global and the study period spans 2005-2007. A 3-hourly temporal resolution maximizes the links with the work undertaken by the GEWEX LandFlux initiative to produce sub-daily evaporation estimates  (McCabe et al. , 2016). The present Part 2 evaluates the outputs after aggregating them to daily, monthly, and annual scales, while the skill of the models to resolve the diurnal cycle of evaporation is explored in Part 1. Although the internally generated input data sets were originally derived at a relatively fine (< 5 km) spatial resolution, critical inputs not generated within the project were only available at 75-100 km (see below). Consequently, all input data sets have been spatially resampled to match the 25 km target resolution and reprojected onto a common sinusoidal grid before using them to run the evaporation models.
Internally developed products include the fraction of photosynthetically active radiation and leaf area index, which are derived to a large extent from European satellites (see Part 1). Data access, product descriptions, and user guidelines for these data sets are available to interested parties upon request via the project website. Whereas PM-MOD and PT-JPL apply these internally generated data sets to characterize vegetation phenology, GLEAM uses observations of microwave vegetation optical depth as a proxy for vegetation water content; these are taken from the data set of  Liu et al. (2011)  based on the Advanced Microwave Scanning Radiometer -Earth Observing System (AMSR)-E at 0. 25 • spatial resolution. The remaining products comprising the reference input data set have been selected from the pool of available community data sets.
Despite its relevance for plant-available water and interception loss, precipitation is not a direct input for most global satellite-based evaporation models. The same applies to surface soil moisture, which can also be observed from space. From the WACMOS-ET models, only GLEAM uses observations of precipitation and surface soil moisture as input. In the reference input data set, precipitation data come from the Climate Forecast System Reanalysis for Land (CFSR-Land;  Coccia et al. , 2015) , which uses the Climate Prediction Center (CPC,  Chen et al. , 2008)  and the Global Precipitation Climatology Project (GPCP,  Huffman et al. , 2001)  daily data sets and applies a temporal downscaling based on the CFSR  (Saha et al. , 2010). For soil moisture, we use the satellite product of combined active-passive microwave surface soil moisture by  Liu et al.
Discharge data and watershed boundaries are obtained from the Global Runoff Data Centre (GRDC). Run-off data have been converted from cubic metres per second to millimetres per year using the area of each catchment as reported by the GRDC; basins where the absolute difference between the GRDC-reported area and the area calculated from basin boundaries exceeded 25 % have been excluded from the analyses. Precipitation for the target period 2005-2007 is taken from GPCP  (Huffman et al. , 2001)  and the Global Precipitation Climatology Centre (GPCC) v6  (Schneider et al. , 2013). Two versions of GPCC v6 are processed by applying relative gauge correction factors according to  Fuchs et al. (2001)  and  Legates and Willmott (1990)  to the native GPCC products as recommended by the producers. We further discard basins with (a priori) low-quality precipitation due to the low density of rain gauges (< 0.
Global magnitude of terrestrial evaporation The global mean annual volume of evaporation has been intensively debated in recent years (see, e. g. ,  Wang and Dickinson, 2012) , with the range of reported global averages in current Coupled Model Intercomparison Project Phase 5 (CMIP5) models being large  (Wild et al. , 2014)  and observational benchmark data sets also differing significantly  (Mueller et al. , 2013). In this section, we aim to give some context to the global magnitude of evaporation that results from the WACMOS-ET analyses by contrasting the results with alternative evaporation data sets and existing literature. Unless otherwise noted, results come from aggregating the outputs of the 3-hourly global runs based on the 25 km spatial resolution of the reference input data set for the period 2005-2007.
9 × 10 3 km 3   (Miralles et al. , 2011a) , 71 × 10 3 km 3  (Baumgartner and Reichel, 1975) , 73. 9 × 10 3 km 3  (Wang-Erlandsson et al. , 2014) , and 74. 3 × 10 3 km 3  (Zhang et al. , 2015). We note again that some of these studies considered the poles and desert regions, while others did not. Further, the study period considered in WACMOS-ET is 2005-2007, while previously reported annual averages may be based on different periods. In Fig. 2  the multiannual (2005-2007) mean evaporation is displayed for the different products, including also MTE and ERA-Interim for comparison. All five data sets capture the expected climatic transitions well, although disagreements on the regional scale are still considerable (see below). Lat-itudinal averages are illustrated in the right panel of Fig. 2.
Once more, it is interesting to see how the independent evaporation data sets, i. e. ERA-Interim and MTE, perform in this comparison; both products correlate well with the P -Q estimates, although the overall higher values of ERA-Interim (and lower of MTE) are again highlighted, together with the tendency to overestimate evaporation in dry catchments and underestimate it in wet ones, which is shared by all five data sets. As mentioned above, the use of P -Q as a benchmark for evaporation depends on the validity of several assumptions. First, the catchment needs to be watertight (no subsurface leakage to other catchments) and its geographical boundaries must be well defined. Second, the entire volume of river water that is extracted for direct human use must return to the river, and it should do so upstream of the staff gauge location.
Conclusions The ESA WACMOS-ET project started in 2012 with the goal of performing a cross comparison and validation exercise of a group of selected global observational evaporation algorithms driven by a consistent set of forcing data. With the project coming to an end, this article has focussed on the global and regional evaluation of the resulting evaporation data sets. The three main models scrutinized here were the Penman-Monteith approach from the official MODIS evaporation product  (Mu et al. , 2007 (Mu et al. , , 2011 (Mu et al. , , 2013)) , GLEAM  (Miralles et al. , 2011b; Martens et al. , 2016) , and the Priestley-Taylor JPL  (Fisher et al. , 2008) ; the SEBS model  (Su, 2002) , which was analysed on the local scale in Part 1 (revealing good performance in terms of correlations but a systematic overestimation of evaporation), was not evaluated in this contribution.
The spatiotemporal magnitude and variability of the resulting global evaporation products were compared to analogous estimates from reanalysis (ERA-Interim) and eddy-covariance-based global data (MTE). The representation of evaporation dynamics during droughts, the model skill to close the water balance over 837 river basins world-wide, and the partitioning of evaporation into different components have also been explored. Despite our efforts to create a homogeneous forcing data set to run the evaporation models, the input requirements of each model are different, which implies that the resulting inter-product disagreements are the result of both internal differences in the models and uncertainties in forcing and ancillary data. This prevents us from making strong claims about the quality of the models.
Acknowledgements. This work was undertaken as part of the  European Space Agency (ESA)  project  WACMOS-ET  (Contract No. 4000106711/12/I-NB ). Discharge data were provided by the  Global Runoff Data Centre, 56068 Koblenz, Germany. We thank  Ulrich Weber  and  Eric Thomas  for processing the catchment data. D. G. Miralles acknowledges the financial support from The  Netherlands Organization for Scientific Research  through grant  863. 14. 004 , and the  Belgian Science Policy Office (BELSPO)  in the framework of the  STEREO III  programme, project  SAT-EX  ( SR/00/306 ). A. Ershadi  and M. F. McCabe acknowledge funding from the  King Abdullah University of Science and Technology. J. B. Fisher  acknowledges funding under the  NASA Terrestrial Hydrology Program. Edited by:  P. Gentine.
EULAR response is calculated based on the pre-and post-treatment DAS28 and is widely used in clinical research and practice. Models were evaluated based on the predictive accuracy in a held-out test data set containing 591 anti-TNF-treated RA patients from a separate cohort (Supplementary Table  1 ). This represents the most comprehensive set of data available to address this question. Statistical assessment of study power. The feasibility of developing SNP-based predictive models given this collection of data was determined in three steps. First, the genetic contribution to overall variance in treatment efficacy was estimated. Significant SNP-heritability estimates were identified via variance component modelling  17, 18  of common SNPs (minor allele frequency (MAF)Z0. 01) within the primary cohort consisting of 2,706 patients from 13 studies 6 (SNP-h 2 ¼ 0.
In this range, dimensionality reduction through literature or database curation could extract information even when strong, genome-wide significant associations are not observed. More sophisticated simulations using similar sample and disease characteristics suggest that the power estimates presented here may be conservative  8. Despite smaller sample sizes, we estimate slightly increased power to build clinically meaningful predictors in the subset of patients treated with anti-TNF MABs. While the number of true underlying loci that contribute to genetic risk for anti-TNF response is unknown, an assumption of tens of loci is supported by observations of small numbers of loci associated with other treatment response traits  [24] [25] [26]  and has the added advantage of approaching the number of loci that are practical to include on a clinical diagnostic panel.