dataesr/scientific-paragraphs-categorization huggingface dataset:
2V08S 1216357 to 1220881 Neutral ceramidase-like isoform 1 [Glycine max]; IPR006823 (Neutral/alkaline nonlysosomal ceramidase) ATP-dependent DNA helicase, putative n = 7 Tax = Trypanosomatidae RepID = E9BR42_LEIDB; IPR010339 (TIP49, C-terminal), IPR027238 (RuvB-like), IPR027417 (P-loop containing nucleoside Aradu. 188J4 1225601 to 1228083 triphosphate hydrolase); GO:0000166 (nucleotide binding), GO:0003678 (DNA helicase activity), GO:0005524 (ATP binding), GO:0017111 (nucleoside-triphosphatase activity), GO:0043141 (ATP-dependent 5'-3' DNA helicase activity) Aradu. X1L7N 1229461 to 1233773 Armadillo repeat-containing protein 8-like [Glycine max]; IPR016024 (Armadillo-type fold); GO:0005488 (binding), GO:0005515 (protein binding) Aradu. CH4M9 1233738 to 1235758 Chaperonin-like RbcX protein; IPR003435 (Chaperonin-like RbcX) LRR and NB-ARC domain disease resistance protein; IPR000767 (Disease resistance protein), Aradu.
8247R 1242781 to 1253120 IPR013057 (Amino acid transporter, transmembrane), IPR025875 (Leucine rich repeat 4), IPR027417 (P-loop containing nucleoside triphosphate hydrolase); GO:0006952 (defense response), GO:0043531 (ADP binding) Aradu. 1K902 1254064 to 1256589 Transmembrane amino acid transporter family protein; IPR013057 (Amino acid transporter, transmembrane).
3FH81 1292398 to 1292610 Transmembrane protein, putative Aradu. FX37I 1294555 to 1304080 BTB/POZ domain-containing protein; IPR011333 (BTB/POZ fold); GO:0005515 (protein binding) Aradu. XJ0L1 1305965 to 1306534 BTB/POZ domain-containing protein; IPR011333 (BTB/POZ fold); GO:0005515 (protein binding) Aradu. XLV7R 1311374 to 1312674 Heavy metal transport/detoxification superfamily protein, putative n = 1 Tax = Theobroma cacao RepID = UPI00042B042A Aradu. JRV68 1314901 to1315584 Late embryogenesis abundant (LEA) hydroxyproline-rich glycoprotein family; IPR004864 (Late embryogenesis abundant protein, LEA-14).
This is particularly true for the models of anisotropic diffusion in the Galactic magnetic field  (Giacinti et al. 2018 ). Direct, model-independent identification of the Galactic diffuse γ-ray+neutrino emission signal would help to clarify the peculiarities of the cosmic ray propagation in the multi-PeV energy range around the knee of the cosmic ray spectrum. Such identification is not possible with the IceCube data alone because of the low statistics of the signal: only several tens of neutrinos are detected by IceCube in the energy range above 30 TeV. One straightforward possibility is to use the γ-ray signal counterpart to isolate the Galactic neutrino flux component. Indeed, the pion decay γ-rays with energies in the 10-100 TeV range could not reach telescopes on the Earth from extragalactic sources because of the effect of absorption on the extragalactic background light  (Gould & Schréder 1966; Franceschini et al.
(  2015 ) and in the through-going muon neutrino mode from  Aartsen et al. (2016). The thick horizontal short-dashed line shows yearly exposure attainable with Fermi/LAT  Atwood et al. (2009). The thick horizontal long-dashed and solid lines show the exposure achievable with the MST sub-array of CTA and with a dedicated wide-FoV IACT system for the event selection with the same cuts as in the HESS electron spectrum analysis. EASs via electron-positron pair production, meaning that the electron-and γ-ray-induced EASs develop in an identical way starting from the second generation of the EAS particles. Thus, the minimal possible residual charged cosmic ray background for the diffuse γ-ray flux measurements with IACT is the full cosmic ray electron+positron background shown by the red and blue data points in Fig.
(2017) ;  Kerszberg (2017)  (shown by thin light blue and red data points). The thin dark grey data points below 3 TeV show Fermi/LAT measurements of the Galactic diffuse flux from the Galactic latitude region |b| > 7 • , extracted in the same way as in the analysis of  Neronov & Semikoz (2019). Yellow and green butterflies show IceCube astrophysical neutrino flux spectra derived from the analysis of cascade and through-going muon neutrino  (Williams 2019 ) event selections. Green data points show the neutrino spectrum reported by IceCube Collaboration (2017). diffuse Galactic γ-ray flux above energies of several TeV in the Galactic Ridge (|l| < 30 • , |b| < 2 • ) region; see Figs. 3  and 4. A multi-year exposure of HESS could be sufficient for detection of the diffuse emission even from regions of higher Galactic latitude.
2. However, this is not the case with SikaForce: the water-cured samples lead to a glass transition temperature of 18. 7 � C, which is therefore within a relevant temperature range for the North Sea, as shown by Fig. 3. Thus, the glass transition temperature is reduced by curing and storing under water. The glass transition temperature of 40 � C given in the data sheet (air-cured) is approximately the same as measured here (36. 1 � C). Subsequently, water absorption by the adhesives was investigated. For this purpose air-cured adhesive samples (square, 60 mm � 60 mm, 1 mm thick) with a defined initial weight in accordance with ISO 62:2008 were stored in distilled water. Using a precision balance (accuracy �0. 01 mg), the weight increase (and thus the water absorption) of the samples were measured after various periods of time, as shown in Fig.
Coatings Two coatings of the company Hempel, which are already used in the offshore sector, were considered. Their principal properties, according to the data sheet as well as further investigations, are listed below. � Hempadur 35620, short H35620, is a two-component, solvent-free, polyamine adduct cured epoxy paint that cures to a stiff coating with good resistance to seawater and fresh water. It can also be used on components exposed to highly corrosive environments. The coating cures after 7 days at 20 � C. Since fasteners should be bonded directly onto the coatings later, it is important to determine the strength of the coating itself, in order to obtain the possible upper bonding limit of the substrate. The strength of the two coatings was determined using a so-called Pull-off test (acc.
Acknowledgements This research was supported by the  German Federal Ministry of Economics & Energy  through the  German Federation of Industrial Research Associations (AiF)  as a part of the program for promoting industrial cooperative research (project  IGF 1393 N of the Research Association for Steel Application -FOSTA ). We thank our colleagues  T. Marquardt  and  AW. Momber  from  Muehlhan AG  who provided insight and expertise concerning offshore coatings that greatly assisted the research.
Acknowledgments The genesis of this Special Issue relies upon studies in history of science (physics, mathematics, chemistry), applied science and technology, technical education, within detailed historical contexts and nature of science. We warmly express our appreciation-and-pleasant gratitude to the libraries; and contributing authors for their activities to produce papers of interest and of high quality. We also address our acknowledgments to  Diederik Aerts & Sandro Sozzo  (Editors in-Chief) and their staff for their good job-and-positive reception of our project to publish a special issue on James Joule's bicentenary in the prestigious Foundations of Science.
Previously characterized by the presence of a dual relation between chemotherapy drugs and tumors as defined by the organ or tissue of origin, the topology of medical oncology is increasingly defined by molecular alterations and pathways, high-throughput technologies, molecularly targeted drugs, a renewed understanding of drug action, and interpretation devices to match drugs and gene variants as part of therapeutic decision-making. Sequencing results in the identification of tumor-specific variants whose functional significance must first be established, and then interpreted, prioritized, and summarized in relation to the published literature, clinical trials, and databases  (Good et al. 2014) , to form the basis for the prescription of approved, but also off-label or experimental targeted therapies.
Rather than procuring upstream components such as elements of chemical manufacturing, the ecosystemic approach strives for functional integration of products and services that contribute to the expansion of the ecosystem  (Mottola 2017). It is therefore not surprising to learn that Roche, a leading pharma company that successfully marketed posterchild targeted therapies such as trastuzumab (Herceptin) and bevacizumab (Avastin), also commercializes an information technology platform called NAVIFY to "optimize decision-making for cancer treatment" by streamlining TB operations  (Krupinski et al. 2018) , namely by bringing together "electronic health records, laboratory, pathology, and imaging information systems, genomics, and administrative datasets"  (Versel 2018). Initially designed to support more traditional TB activities, most recently Roche added two new modules -a Mutation Profiler and a Therapy Matcher -"to support comprehensive genomic profiling in cancer".
But there is more: In addition to the marketing of molecularly targeted therapies and the development of decision-support devices, Roche's inroad into the new world of genomics included the acquisition of two start-ups, namely Foundation Medicine and Flatiron Health  (Plüss 2019). The former develops and sells oncology genomic profiling panels using nextgeneration sequencing technology. The latter investigates real-world, longitudinal clinical data from electronic medical records. Combining these two companies' assets-a far from trivial task-has led, for instance, to the establishment of "a clinico-genomics database, in which Flatiron linked deidentified electronic health records from 30,000 patients treated at more than 200 US cancer centers with anonymized results from genomic tests performed by Foundation Medicine"  (Ray 2018 ; for a more recent initiative along similar lines see Hopkins 2020).
This kind of database can be embedded in decision-support tools such as NAVIFY. In short, to borrow a catchphrase from Roche, "pharmaceuticals, diagnostics, data & analytics within one company". Although no single organization can control the multiple, heterogeneous components of the broader oncology ecosystem, the fact that a major pharma corporation has entered this domain is a bellwether of a profound transformation, beyond major academic centers, of diagnostic practices and clinical decision-making in the cancer domain.
Ethical Standards The data supporting the findings herein are available upon reasonable request from the corresponding author. The said author accepts responsibility for the reliability of all study data to which full access was provided, including data analysis. The trial protocol was approved by the local research ethics committee (CPP Ouest II, Angers, France; EudraCT identification number: 2014-A01614-43 and CPP identification number 2014/35) and was implemented as per the most recent amendments to the Declaration of Helsinki and good clinical practice guidelines. Written informed consent was obtained from all patients prior to enrolment. The GOCAPXE study was registered with Clinicaltrials. gov on 6 March 2017 (NCT 03070860) and has been overseen by an independent data safety and monitoring committee.
Clinical and Biological Assessment Data collected from both PXE patients and HVs included: age; sex; BMI; AHT; smoking habits; DM; dyslipidemia; family/personal medical history of cardiovascular disease (MI); stroke; lower extremity PAD. ABI was measured according to existing guidelines  [15]. PAD was defined as ABI ≤ 0. 90 or >1. 40  [15]. Laboratory blood analysis from PXE patients and HVs was compared. Total LDL/HDL-cholesterol, triglyceride and blood-glucose levels were measured from fasting blood samples using standard laboratory techniques. CVR factors were defined as follows: (1) AHT: SBP > 140 mmHg and DBP > 90 mmHg and/or antihypertensive medication; (2) DM: fasting plasma glucose ≥ 7. 0 mmol/L (≥126 mg/dL) and/or random plasma glucose ≥ 11. 1 mmol/L (≥200 mg/dL) and/or HbA1c ≥ 6.
Multiplex Immunoassays Using Luminex ® Technology Associations of change in functional assessment were investigated using biological assays of a set of circulating blood factors. Plasma samples from 23 PXE patients and 23 HVs were obtained from the Angers University Hospital BRC. 46 chemokines, cytokines, growth factors, lectin adhesion molecules, osteogenic factors, matrix metalloproteinase and fibrogenic factors were quantified in PXE patient and HV sera using Luminex assay kits following manufacturer instructions (R&D Systems). Samples were analyzed using a Luminex 200 analyzer and Bio-Plex Manager version 6 software. The following substances were analyzed: CCL2, CCL3, CCL4, CCL5, CCL17, CCL18, CCL22, CXCL10, IFNγ, IL-1Ra, IL-1β, IL-4, IL-6, IL-8, IL-10, IL-12p70, IL-17a, TNFα, TGF β, G-CSF, M-CSF, GM-CSF, VEGF, HGF, PDGF-BB, E-selectin, P-selectin, L-selectin, BMP-2, BMP-4, OA, OPN, ON, fetuin-A, OPG, RANKL, MMP-1, MMP-2, MMP-3, MMP-7, MMP-8, MMP-9, MMP-10, MMP-12, endothelin and PAI-1.
PET-CT and CT-Scan Imaging Techniques PXE patients underwent all-body 18F-FDG/18F-NaF-PET-CT and CT-scans. Spared regions such as the popliteal arteries (vascular investigation)  [1]  or the lumbar region (skin investigation) were regarded as negative controls in these patients. Patients fasted for at least 6 hours prior to intravenous 225 ± 56 MBq (3 MBq/kg) injection of 18F-FDG. Data were acquired on a dedicated PET-CT Discovery-690 system (LYSO scintillation PET detector; 16-slice CT; GE ® , Buc, France) with an acquisition time of 2 min/bed position. The PET images were reconstructed using: an OSEM 3D algorithm (3 iterations, 8 subsets, FOV 700 mm, 192 × 192 matrix, 3. 65 mm pixels, 3. 27 mm slice thickness, post-reconstruction Gaussian 4 mm filter); a VPFX TOF algorithm; PSF correction (Sharp IR).
Image Analysis: 18F-FDG/18F-NaF-PET-CT Each image dataset was analyzed by a nuclear medicine physician on an Imagys ® workstation (Keosys ® , Saint-Herblain, France). Maximum intensity projection PET-CT images were assessed visually for evidence of radiotracer accumulation in the femoral or popliteal artery walls, as previously described  [18]. In semi-quantitative analysis, maximum SUV was determined by manually drawing an individual ROI 1 cm 3 around the most fixed arterial segment (Figure  1 ) that included: the left and right carotid arteries, aorta (ascending aorta, aortic arch, descending aorta, abdominal aorta), left and right iliac arteries, damaged left and right femoral arteries and spared left and right popliteal arteries, as shown on coregistered transaxial PET-CT findings. The ROI was adjusted to the vascular wall using coronal and sagittal PET-CT images.
Image Analysis: CS in Lower Limb Arteries Each PXE patient was submitted to a non-contrast-enhanced-64-row-multidetector-CT scan (Brillance 64, Philips HealthCare, Dest, The Netherlands) of the lower limbs, from the iliac crest to the tips of the toes, without injection of contrast medium  [23]. Investigators blinded to patient clinical status calculated CS using automated 3D image-analysis software (Synapse 3D, Fujifilm Medical Systems, Greenwood, SC, USA). ROIs were divided into 3 segments for each individual leg: (1) the femoral segment (common and femoral arteries), extending from the iliac crest to the adductor magnus opening; (2) the popliteal segment (from adductor magnus opening to origin of anterior tibial artery); (3) the sub-popliteal segment (anterior and posterior tibialis and fibular arteries from their origin to malleolar region)  [23].
Data Processing and Statistical Analysis Peak lists were generated as mzXML files using rgw MSConvert software (ProteoWizard 3. 0). Mass spectrometric data were searched using X!TandemPipeline software version 0. 2. 38 developed by the PAPPSO facility  [14]. Peptide searches were performed with the following parameters: enzymatic cleavage by trypsin digestion with one possible miscleavage, precursor mass tolerance of ±10 ppm, fragment mass tolerance of 0. 5 Da, static modifications of carbamidomethylated cysteine, and potential modification of oxidized methionine. The Uniprot KB/SwissProt uniprot_human_organism_9606 database (2019) and a homemade contaminant database (trypsin, keratine, etc. ) were used. The identified proteins were filtered with a minimum of two different peptides with a peptide E-value < 0.
05 and a protein E-value (product of unique peptide E values) < 10 -5. Combine analysis mode with all the samples was performed, and the results were collected from the grouping proteins. Within each group, proteins with at least one specific peptide relative to other members of the group were reported as subgroups. One subgroup represents one specific protein. Proteins are characterized with their spectral number. The false discovery rates (FDR) obtained for the peptide and protein identifications with a decoy databank were 0. 05% and 0%, respectively. The label-free comparative quantification of proteins was achieved through spectral counting (SC) and eXtracted Ion Current (XIC) analysis following alignment by Mass ChroQ version 2. 2. 12  [15].
Statistical Analysis Statistical analysis was performed using the MassChroqR package developed by the PAPPSO team (R Studio version 1. 0. 153). After checking the normality and homogeneity of the SC data, proteins showing less than 5 spectra in any of the injections or showing a variation between the minimal and the maximal mean abundance below 1. 5 in their number of spectra were removed. For XIC analysis, the peptide intensities measured as peak areas were automatically log10-transformed. Analysis included the following steps: checking the homogeneity of all runs in terms of the chromatography and signal (discarding peptides-mz with an RT > 20 s and chromatographic pics > 200 s) and normalizing the data based on the median. The RT method, keeping only peptides showing a reasonable distribution, eliminating shared peptides, eliminating peptides with more than 10% missing values and imputing missing values for peptides and proteins.
This is consistent with our recent results, showing that Kcnk3 deficiency in rats is associated with significant alteration in PA tone, including the impairment of NO-induced relaxation  [8]. Limitations: Due to the low capability of mass spectrometry to identify hydrophobic channel proteins, which are particularly nonpolar and present in a very limited amount, unfortunately we did not detect a large amount of ion channel families' proteins. However, 33 ion channels or transporters in hPAECs and 28 in hPASMCs (data not shown) were identified without any changes in their expression in the absence of KCNK3. In the future, the expression of other newly identified signaling pathways will be further investigated by Western blot or PCR analysis in the context of the KCNK3 loss of expression as well as in the more general context of PAH.
Funding: This study was supported by grants from the  French National Institute for Health and Medical Research (INSERM) , the  Université Paris-Saclay , the  Marie Lannelongue Hospital , and the  French National Agency for Research (ANR)  (grant no. ANR-18-CE14-0023  (KAPAH). H. L. R is supported by  ANR-18-CE14-0023. M. L. is supported by the  Therapeutic Innovation Doctoral School  ( ED569 ). The  Region Ile de France  has co-funded proteomic instruments (convention n •  EX024607 ).
The climate-proxy linkage may also vary as a function of timescale. For example corals might have a different relationship with climate on annual, interannual and decadal timescales  (Gagan et al. , 2012). 2. The calibration data do not fully explore the range of proxy/climate behaviours (with few exceptions such as coral archives). This is the so-called 'no modern analogue' problem and can be reduced by increasing the calibration dataset size, or by using mechanistic models of proxy/climate behaviour. 3. A weak relationship between proxies and climate, which may occur where proxies or climate variables are poorly chosen and can be accounted for using a probabilistic modelling approach (such as the Bayesian inverse approach) where the models are sufficiently flexible so that weak relationships yield large uncertainties in reconstructed climates.
, 2002; Ortega et al. , 2015) , partial least squares, elastic net and random forest  (Breiman, 2001; Zou and Hastie, 2005). Michel et al. (2020)  evaluated the strengths of these different methods to reconstruct the NAO over the last millennium using the PAGES 2K database. They showed that the random forest provides the best scores, which may be related to the capability of this method to account for non-linear linkages between the mode and proxy records, although we must be careful of overfitting with non-linear methods. Additionally, recent initiatives applying the inverse regression approach to reconstruct modes of variability are appearing  (Hernández et al. , In Review; Sánchez-López, 2016). The use of pseudo-proxy approaches within climate modelling can then further help to evaluate the capability of these approaches to appropriately reconstruct the variability modes.
For each pairwise correlation the degrees of freedom were corrected to account for the timeseries autocorrelation. All pairwise correlations were performed between 1000 CE and 1850, or in the period of overlap between the two reconstructions if some of them were shorter. The industrial era (1850 onwards) was excluded to ensure that the calibration period of both timeseries was not included. All timeseries were interpolated to decadal resolution prior to the computation of the correlations. All Spearman´s rank pairwise correlation coefficients for each mode and their associated p-values as well as links to original dataset sources are included in the supplementary material.
Other studies, however, have found similar AMV patterns  (Mjell et al. , 2016)  and spectral peaks (50-80 years)  (Moffa-Sanchez et al. , 2015)  in past flow reconstructions in deep components of the AMOC, hence hinting at past AMV-AMOC linkage over the recent millennia as suggested in the last millennium models  (Lohmann et al. , 2015). However, coeval changes in SST and in other reconstructions of deep flow strength in the North Atlantic are not always found (e. g. Mjell et al. , 2015). Continuous reconstructions of the AMV over the entire Holocene are sparse due to the limited availability of subdecadally resolved climate reconstructions to study a multidecadal mode (Fig. 4 ). Spectral analysis of seven palaeoclimatic datasets from around the North Atlantic exhibit similar quasi-periodic oscillations to the AMV (55-70 year) with latitudinal variability in the timing of the stronger peaks across the last 8 ka  (Knudsen et al.
For a comprehensive review of the wide range of responses of marine, terrestrial and freshwater ecosystems to NAO variability, see  Wanner et al. , (2001). The NAO is typically defined through the leading Principal Component of gridded winter monthly Sea Level Pressure (SLP)  (Portis et al. , 2001; Stephenson et al. , 2003) , which leads to limits in its time extension since a sufficiently wide dataset on SLP mainly covers the last century. Over the past decades, there has been interest in documenting and understanding the NAO variability on annual to multidecadal timescales, by extending estimates of the NAO index as far back in time as possible (Fig. 5 ). The NAO variability within the instrumental period has been examined in the form of normalised pressure differences that reflect changes in the atmospheric pressure gradient between the so-called Icelandic Low and the subtropical northern Atlantic with suitably located instrumental SLP records (Stykkisholmur, Akureyri, Reykjavik; Gibraltar, Lisbon, Ponta Delgada).