dataesr/scientific-paragraphs-categorization huggingface dataset:
Overall, these findings demonstrated that HTLV-1 leukemic cells are characterized by significative perturbation of exon content of multiple transcripts, characteristic that is also found upon HBZ expression. Subsequently, we assessed the existence of a possible correlation between alternative splicing and gene expression. In fact, 765 and 764 genes were identified to be alternatively spliced and differentially expressed in ATL-2 (Figure  5A , left panel) and Jurkat-HBZ cells (Figure  5A , right panel), respectively (Supplementary Data 4-1,2). Thus, about half of the genes that undergo alternative splicing are also differentially expressed in ATL-2 cells (54%; 765/1408). A consistent number of transcripts harboring ASE were also differentially expressed in Jurkat-HBZ cells (38%; 764/1987). By comparing ATL-2 and Jurkat-HBZ cells, 108 genes were still in common between the two cells at the splicing and expression level.
Introduction The so far existing CREp online calculator for in situ cosmogenic 10 Be and 3 He exposure age calculations  (Martin et al. , 2017 ; https://crep. otelo. univ-lorraine. fr/) is a versatile tool with advantageous characteristics. It has a user-friendly web interface combined with a high computation speed and a permanent link to the ICE-D production rate database, permitting to account for the most recent production rate calibrations (http://calibration. ice-d. org/). It also allows the choice between global, regional or local production rates, several scaling schemes, atmospheric pressure models, and Virtual Dipole Moment database. Chlorine-36 ( 36 Cl) is currently the only in situ cosmogenic nuclide applicable in carbonate environments, and it is now quasi-routinely analyzed in Ca-and K-rich silicate rocks and minerals.
(2009) , (see Appendix A and B in  Schimmelpfennig et al. , 2009  for equations adapted from  Gosse and Phillips, 2001, and Phillips et al. , 2001) , and we included the following improvements. -The site-specific, time-dependent scaling is automatically calculated. Users have the same choices as for 10 Be and 3 He calculations, i. e. they can select between the two scaling methods Lm  (Lal, 1990; Stone et al. , 2000; Balco et al. , 2008)  and LSD  (Lifton et al. , 2014)  combined with the choices between two atmospheric pressure models (US standard atmosphere;  NOAA, 1976; and ERA-40, Uppala et al. , 2005)  and several Virtual Dipole Moment databases. The scaling method LSD is nuclide-specific andin the case of 36 Cl -target element-specific, and was implemented following the model integrated in the CRONUS-Earth online calculator  (Marrero et al.
• two atmosphere models: (1) the one based on the ERA-40 data-base  (Uppala et al. , 2005) , and (2) the standard atmosphere (N. O. A. A, 1976). • three geomagnetic databases according to (1)  Muscheler et al. (2005) , (2)  Lifton et al. (2014), (3)  Lifton (  2016 ), or import their own geomagnetic database for paleomagnetic corrections. Tab 2 Samples (Fig. 2 ): By clicking on "Download template", users download an excel file that has to be filled with all sample-specific information before loading it on the CREp web page. All sample input is then displayed for verification. Note that there are 51 columns for data input per sample (see Appendix), which can be verified on the display by scrolling to the right. This technical note is a non-peer reviewed preprint submitted to EarthArXiv Tab 3 Production Rates (Fig.
Work in progress The existing 36 Cl production rate calibration data is currently being implemented in the ICE-D calibration data base with the objective to connect it to CREp 36 Cl, similar to the current functioning of 10 Be and 3 He calculations. This will allow for 1) regularly updates on global elemental production rates, whenever new calibration date will be added, and 2) potentially for the choice of local production rates. However, it must be noted that 36 Cl production rate calibrations are still much scarcer than those of the other nuclides, in particular with regard to mono-elemental production rate material. Further work in progress concerns the implementation of an updated muon production models that are relevant for 10 Be and 3 He calculations at depth (<20 cm) and the addition of a new Virtual Dipole Moment database, which will be applicable to all nuclides in CREp.
Since September 2008, if we look at the average price of each nutrient collected in the Illinois cost of production dataset, the following increases may be noted; anhydrous ammonia (+118%), urea (+101%), liquid nitrogen (+84%), DAP (+50%), MAP (+61%), and potash (+61%) (https://www. fb. org/market-intel/too-many-tocount-factors-driving-fertilizer-prices-higher-and-higher (accessed on 13 December 2021)). However, breeding for NUE has not yet been extensively mainstreamed into practical breeding programs for many crops. NUE is a complex trait to assess and it is also very much influenced by the soil conditions, so it is difficult to control. In terms of breeding, at the rooting system level, the objective would be to improve the N uptake efficiency  [48]. Breeding under low nitrogen conditions would allow the selection of plants with the best N uptake and root distribution over the soil profile  [127].
Funding: This research was partially funded by the  BREEDCAFS  project, which was supported by the  EUROPEAN COMMISSION  under the  Horizon 2020-Research and Innovation Program ,  H2020-SFS-2016-2 , Grant Agreement Number:  727934  (www. breedcafs. eu(accessed on  30 June 2017 )). Informed Consent Statement: Informed consent was obtained from all subjects involved in the study.
Quantitative Real-Time PCR (RT-qPCR) In order to determine the TERRA expression level from total RNA and DNA-RNA hybrid samples obtained from the patient and control groups; cDNA synthesis was performed using the EvoScript Reverse Transcriptase cDNA synthesis (Cat No: 07912374001, Roche, Mannheim, Germany) kit. The cDNA samples of the total RNA and DNA-RNA hybrids of the patient and control groups obtained were determined in the Roche Light Cycler ® 480 Real Time PCR (Mannheim, Germany) device using previously reported  [43]  primers RNase HII (F: GACCCTATTGGAGAGCGAGC and R: TATTTGACCCGCCCAAG-CAT), Rad51 (F: GGCCATTAGCCCTTCACCAT and R: TCTGCAAGTGGGACTTTCCT) and GAPDH as the house-keeping gene. All samples were normalized using the data 2 -∆Ct method after a double study  [44].
Statistical Analysis The suitability of the data for normal distribution was evaluated by histogram, q-q graphs, and Shapiro-Wilk test, and Variance homogeneity with Levene's test. A two-sample t-test was applied to compare the differences in telomere lengths and TERRA expression of lesional and non-lesional tissues among patients. A One-Way ANOVA test was used to multiply compare Telomere lengths and TERRA expressions between patients and the control group. The relationships between quantitative data were evaluated by Spearman correlation analysis. Data were treated using Graphpad Prism (version 8. 0. 1, San Diego, CA, USA) software. P values were considered statistically significant as <0. 05. One-way ANOVA analysis of peak annotation data were carried out using the SPSS Statistics for Windows version 19.
Peak Finding To identify significant peaks, we looked for genome-wide enriched peaks. This analysis aimed to efficiently visualize the peaks in terms of genomic region characteristics. The results are consistent between replicates, confirming that the technique is generally very reliable (see Figures  5 6 7 8 ). To find enriched peaks and regions associated with nearby genes and genomic features in the genome using Homer, "findPeaks -o auto" called out was used to perform peak calling and transcript identification analysis. Then to annotating regions in the genome "annotatePeaks. pl" called for performing peak annotation. FDR cutoff of 0. 001 used for significant peaks identification. Annotated positions for different regions plotted. The percentage of significant peaks located in each genomic region is visualized.
Acknowledgements We thank  Anatoly Khina  and  Trang-Anh Nghiem  for helpful discussions. Support for this research was provided by the  CNRS  through  Unité Mixte de Recherche (UMR)  8023, the  Swiss National Science Foundation Sinergia Project  ( CRSII5_173728 ), grants from the  Israel Science Foundation  (Grant Nos. 1319/13 ,  1978/13 , and  1745/18 ), the  Gatsby Charitable Foundation , and the  William N. Skirball Chair in Neurophysics.
Resources availability. The data we analyze were reported and discussed by  Lalazar et al. (2016). Data are publicly available at https://osf. io/u57df/. Numerical simulations and data analyses were carried out with custom codes written in Julia  (Bezanson et al. , 2017) , with the DrWatson project assistant  (Datseris et al. , 2020). The custom code will be made publicly available upon manuscript acceptance.
We present GLADE+, an extended version of the GLADE galaxy catalogue introduced in our previous paper for multimessenger searches with advanced gravitational-wave detectors. GLADE+ combines data from six separate but not independent astronomical catalogues: the GWGC, 2MPZ, 2MASS XSC, HyperLEDA, and WISExSCOSPZ galaxy catalogues, and the SDSS-DR16Q quasar catalogue. To allow corrections of CMB-frame redshifts for peculiar motions, we calculated peculiar velocities along with their standard deviations of all galaxies having -band magnitude data within redshift  = 0. 05 using the "Bayesian Origin Reconstruction from Galaxies" formalism. GLADE+ is complete up to luminosity distance   = 47 +4 -2 Mpc in terms of the cumulative -band luminosity of galaxies, and contains all of the brightest galaxies giving half of the total -band luminosity up to   250 Mpc.
GLADE+ contains ∼ 22. 5 million galaxies and ∼ 750 thousand quasars (compared to ∼ 3 million galaxies and ∼ 300 thousand quasars in GLADE) as a result of cross-matching GLADE with the WISE×SuperCOSMOS Photometric Redshift Catalogue (WISExSCOSPZ) and updating the quasar database of GLADE with the SDSS-DR16Q quasar catalogue. To allow corrections of CMB-frame redshifts for peculiar motions, we calculated peculiar velocities along with their standard deviatons of all galaxies having -band magnitude data within redshift  = 0. 05 using the "Bayesian Origin Reconstruction from Galaxies" formalism  (Mukherjee et al. 2021c ). We estimated stellar masses and binary neutron star merger rates with all GLADE+ galaxies with 1-band magnitude data and included these in the catalogue. The aim of these improvements is to continue serving the purposes mentioned above and potentially serve new ones, especially in light of the ongoing preparations for the fourth observing run of the LIGO-Virgo-KAGRA network scheduled for 2022  (Abbott et al.
The order of magnitude of the threshold is also consistent with that of previous GLADE cross-matches, note however that in previous applications we could take other parameters of the galaxies into account as well, such as luminosity distances and  magnitudes  (Dálya et al. 2018). The GLADE catalogue incorporated the SDSS-DR12Q quasar catalogue, which, in GLADE+, we replaced entirely with the more recent and extended SDSS-DR16Q catalogue. This catalogue contains data for ∼ 750, 000 quasars (including the ∼ 300, 000 quasars published in SDSS-DR12Q), which makes it the largest selection of spectroscopically confirmed quasars to date. Cross-matching and updating the catalogues resulted in the GLADE+ catalogue containing 23,181,758 objects from which 22,431,348 are galaxies and 750,410 are quasars.
DESCRIPTION OF THE GLADE+ CATALOGUE The GLADE+ catalogue is available as a txt file on the GLADE website 9. Columns of each line of the file contain the following data (where available) for each GLADE+ object: The completeness in terms of the normalized integrated -band luminosity of galaxies in GLADE+ (blue) and its constituent catalogues (i. e. GLADE v2. 4 shown in orange and WISExSCOSPZ shown in green) within luminosity distances indicated on the -axis. The normalization is carried out with the integrated -band luminosity calculated from an average -band luminosity density of a complete catalogue of homogeneously distributed galaxies (see  Kopparapu et al. 2008  for details). The completeness value exceeds 100 percent within 47 Mpc due to a local overdensity of galaxies around the Milky Way.
CONCLUSIONS The GLADE+ galaxy catalogue is an extended version of the GLADE catalogue we have optimized for multimessenger searches with advanced GW detectors. It contains more than 23 million objects from which more than 22 million are galaxies and ∼750,000 are quasars. As the effects of peculiar motions are important for nearby galaxies for both the EM follow-up and cosmological analyses, we have estimated the peculiar velocities along with their standard deviations for galaxies in GLADE+ with -band magnitude data having redshifts  ≤ 0. 05 using the forward modelling method. GLADE+ is complete up to   = 47 +4 -2 Mpc in terms of the cumulative -band luminosity of galaxies, and contains all of the brightest galaxies giving half of the total -band luminosity up to   250 Mpc. As according to theoretical models the stellar mass of galaxies strongly correlates with the merger rate of colliding binaries, we have calculated the stellar masses and the BNS merger rates (together with their errors) of each galaxy having WISE magnitudes.
These parameters can help to rank the galaxies in a given GW localization volume, thereby possibly reducing the number of pointings and the total integration time needed to find the EM counterpart. the project 2020-05143 -"Deciphering the Dynamics of Cosmic Structure". We acknowledge the use of following packages in this analysis: Astropy  (Astropy Collaboration et al. 2013 , 2018) , IPython  (Pérez & Granger 2007) , Matplotlib  (Hunter 2007) , NumPy  (van der Walt et al. 2011), and SciPy (Jones et al. 2001). for the brighter half of galaxies. Note, that we have only used the brighter half of all the galaxies for this plot, so even if the completeness is 100 percent or above at a given distance, GLADE+ can still lack fainter galaxies.
ACKNOWLEDGEMENTS This paper was reviewed by the  LIGO Scientific Collaboration  under LIGO Document P. The authors would like to thank  Simone Mastrogiovanni ,  Surhud More  and  John Peacock  for fruitful discussions throughout the project. The authors thank  Bence Bécsy  for useful comments on the manuscript. We are grateful for the  Wide Field Astronomy Unit (WFAU)  for providing the WISExSCOS and 2MPZ data used in creating GLADE+. We acknowledge the usage of the HyperLeda database (http://leda. univ-lyon1. fr). GD is supported through the  ÚNKP-19-3 New National Excellence program  of the  Hungarian Ministry of Human Capacities  and the iBOF-project  BOF20/IBF/124. Research at Perimeter Institute  is supported in part by the  Government of Canada  through the  Department of Innovation, Science and Economic Development Canada  and by the  Province of Ontario  through the  Ministry of Colleges and Universities.
The work of BDW is supported by the  Labex ILP  (reference  ANR-10-LABX-63 ) part of the  Idex SUPER , received financial state aid managed by the  Agence Nationale de la Recherche , as part of the  programme Investissements d'avenir  under the reference  ANR-11-IDEX-0004-02. The  Center for Computational Astrophysics  is supported by the  Simons Foundation. This work was supported by the  ANR   BIG4  project, grant  ANR-16-CE23-0002  of the  French Agence Nationale de la Recherche. A part of the analysis was carried out at the  Horizon cluster hosted by Institut d'Astrophysique de Paris. We thank  Stephane Rouberol  for smoothly running the Horizon cluster. This work was granted access to the  HPC resources of CINES (Centre Informatique National de l'Enseignement Supérieur)  under the allocation A0020410153 made by  GENCI.
The CRPSS and correlation for simulations with analogs of NCEP are almost identical to those with ERA5, as shown in Table  4. Therefore, we focused on SWG simulations with analogs from the NCEP reanalysis in the sequel as both  NCEP and ERA5 (1950-2019)  have the same skill, as shown in Table  4 , and because NCEP is easier to handle due to its lower horizontal resolution. The computations were made using observations of precipitation from the ECAD  (Klein Tank et al. , 2002 ) and E-Obs  (Haylock et al. , 2008)  databases. We found the same results because the ECAD and E-Obs are highly correlated (by the construction of E-Obs). In summary, we made the forecast of the precipitation using K = 20 analogs computed from Z500 over the [30 • W-20 • E; 40-60 • N] domain (red rectangle in Fig. 1b ).
Acknowledgements. This work is part of the  EU International Training Network (ITN) Climate Advanced Forecasting of subseasonal Extremes  (CAFE). We thank  Linus Magnusson  and  Florian Pappenberger  for helpful discussions on the ECMWF data. Financial support. This work is part of the  EU International Training Network (ITN)  " Climate Advanced Forecasting of subseasonal Extremes " (CAFE). The project receives funding from the  European Union 's  Horizon 2020 research and innovation program  under the  Marie Skłodowska-Curie Grant  (agreement no. 813844 ). Review statement. This paper was edited by  Chiel van Heerwaarden  and reviewed by two anonymous referees.
However, it would be a mistake to think that animal models cannot provide a vital step in the translational pathway as they do provide important pathophysiological insights into disease mechanisms particularly on a organ and systemic level. While stem cell-derived human models have the potential to become key in testing toxicity and effectiveness of new drugs, we need to be realistic, and carefully validate all new human-like disease models. In this position paper, we highlight recent advances in trying to reduce the number of animals for cardiovascular research ranging from stem cellderived models to in situ modelling of heart properties, bioinformatic models based on large datasets, and improved current animal models, which show clinically relevant characteristics observed in patients with a cardiovascular disease.
Standardization would allow increasing data robustness and quality, extracting new data from previous studies, reducing the number of animals, and be in compliance with the 3R policy. 174 Along the same line, an additional step forward would be establishing repositories of samples from rodent models, with biobanks maximizing tissue usage from euthanized animals. While a particular organ might be the target of a specific study, the remaining tissues could serve the goal of research groups focusing on other organs and systems, thereby reducing the number of research animals and replacing living animals with stored samples. Again, the critical aspect here is assuring that organs, tissue or cells are collected and preserved according to established protocols, to ensure high-quality samples, paired with controls and accurately linked to comprehensive databases providing relevant information.
220, 223 Structural assessment provides analysis of cellular and ECM organization, In addition, specific biomolecules can easily be labelled and visualized. Biochemical assessment can also be used to assess LMS genomic and proteomic signatures. 224, 225 ovel biomimetic technologies allow LMS to be maintained in vitro in a highly functional state and cultured in stable conditions for extended periods,  226, 227  this allows for novel areas of cardiovascular research to be unravelled. Unique therapeutic research applications may utilize longterm efficacy prediction, RNA-based target evaluation, cell-based regeneration and high-content analysis by RNA-seq. With standard couriers being used for tissue specimens or LMS movement, it is likely that laboratory networks will soon be formed to share human material that will reduce waste of tissue and increase data collection.
The development and use of an animal registry and/or preclinical network represent a possible solution for minimizing publication bias. To this end, two platforms (www. preclinicaltrials. eu  315 and www. animalstudyregistry. org 316 ) were recently launched for preregistration of animal studies to increase transparency and reproducibility of bioscience research and to promote animal welfare. The registration form helps scientists plan their study thoroughly by asking detailed questions concerning study design, methods, and statistics. Although most researchers are in favor of more transparency, major disadvantages of preregistration exist, especially intellectual property (IP) issues and administrative burden. St present, these are the moste likely reasons why there is only a limited number of preregistered studies.
Several solutions are currently being incorporated to circumvent these obstacles. One example is when registering a study, it automatically receives a digital object identifier (DOI) that marks it as the original research idea of the investigator. In addition to this, the users can decide to restrict the visibility of their registered studies for up to 5 years. The Consortium for Preclinical Assessment of Cardioprotective Therapies (CAESAR)  317  and Mouse Phenome Database (https://phenome. jax. org/) are examples of networks in which experienced laboratories work together and share data on rodent models. The implementation of an independent and prospective animal registry and preclinical network can, therefore, support the researcher in enhancing the quality of the study, as it requires addressing blinding, randomization, sample size calculation and power.
Patient registries, biobanking, -omics studies & imaging Further acceleration of clinical cardiovascular research will only be possible if networks are created across institutes and countries to facilitate collaborative data science. In particular, the implementation of (trans)national networks across institutes using similar data models and harmonized clinical care pathways will facilitate patient recruitment in targeted clinical trials and enable genotype-phenotype association studies with appropriate statistical power, for example, in cardiomyopathy patient groups. Furthermore, it would provide a framework for a learning healthcare system through benchmarking, cross-validation of novel strategies and artificial intelligence algorithms in both research and routine care. Unsupervised learning allows for the clustering, structuring and compressing of the information content for a high-dimensional dataset of important features or main components.
328 Instead of sharing data within a huge central datastorage (data-to-code), the algorithms will be distributed across centers (code-to-data) without any actual data sharing. The created statistical models and its parameters can subsequently be validated across different clinical settings, patient characteristics (e. g. , age, sex and ethnicity) and countries to ensure that those algorithms are generalizable or calibrated to the individual patient in front of us. The importance of such an infrastructure is clearly illustrated by the COVID-19 pandemic. Already existing networks such as REMAP-CAP (Randomized, Embedded, Multifactorial Adaptive Platform Trial for Community-Acquired Pneumonia, www. remapcap. org) and newly founded networks like CAPACITY-COVID (www. capacity-covid. eu) initiated by the crossinstitutional Dutch CardioVascular Alliance (www.