dataesr/scientific-paragraphs-categorization huggingface dataset:
13. There is no additional freshwater runoff, that is, all calving icebergs are assumed to be transported and melt outside the regional domain. We start our simulation without sea ice and sea ice does not form until the end of the model simulation. For the passive tracer representing mCDW, initial tracer concentrations are set to 1. 0 for the region north of 74. 24°S with potential temperature higher than 1. 0°C, similar to ref. 13  , and no tracer restoring is applied. Particle release experiments are conducted offline using hourly outputs of ocean current using Octopus (https://github. com/jinbow/Octopus) and particles are released along 74. 24°S at the depth of the 27. 75 kg m -3 isopycnal. Two other sensitivity experiments are also conducted. For the TIDE case, tidal currents from the CATS2008A inverse barotropic tide model  41, 42  are superimposed on the ocean lateral boundary condition.
For the NOMELT case, heat and salt transfer coefficients at the interface between ice shelf and ocean are set to zero for all ice shelves in the model domain. The comparison of model and data [e. g. ,  [9] [10] [11] [12] [13] [14] [15] 31, 32, 34, 35, 51  ] is shown in the main text and supplementary. Some of the fi ures are created with software Paraview and Ocean Data View  52, 53.
Acknowledgements The research was carried out at the  Jet Propulsion Laboratory, California Institute of Technology , under a contract with the  National Aeronautics and Space Administration (NASA). Support was provided by an appointment to the  NASA   Postdoctoral Program ; the  NASA   Cryosphere program ; and the  NASA Modeling, Analysis , and Prediction program. Computations were carried out at the  NASA Advanced Supercomputing facilities. This work was also supported by the  fund from Grant in Aids for Scientific Research  ( 19K23447 ) of the  Japanese Ministry of Education, Culture, Sports, Science and Technology. We thank  Peter Davis ,  Keith Nicholls ,  Karen Heywood ,  Ben Webber ,  Adrian Jenkins ,  David Shean ,  Susheel Adusumilli ,  Stan Jacobs  for their support for finding and accessing observational datasets.
6 (SD = 0. 88). Power calculations indicated that for a mean difference in arthritis score of 2 points to be detected with 90% power at this time point with a one-sided significance level of 5%, 5 mice in each treated group were required (calculation made with R software, epi R package). The average and standard deviation of clinical scores were similar for each group in each experiment (n = 5). To standardize the monitoring of the therapeutic effect of ECP on arthritis development, we calculated for each mouse and each day a relative CIA score, by subtracting the value of CIA score at the beginning of the treatment to the measured CIA score. Hence, on day 0, when the first injection was performed, all mice have a relative CIA score of zero. Arthritis score was measured every day, and the relative arthritis score was calculated.
Acknowledgements We are grateful to  F. Blanquet  and  Dominique Paris , and to all the technical staff of the  Grenoble Plateforme de Haute Technologie Animale  for expert animal care, and of the Besançon animal facility. We thank all the staff in UMR 1098, and in  EFS R&D laboratory , and especially  Emmanuelle Grasso  and  Jean-Paul Molens  for their help. We thank  Philippe Saas  for his support.
For these experiments, we used wild-type mice having undergone drill injury, which produces severe BBB leakage, as a positive control. With these tracers, we similarly found no leakage (Additional file 1: Figure  S6 ). We also examined pericytes in the WM of CADASIL mice, where fluorescent co-staining techniques allow us to more accurately assess the pericyte coverage of capillaries. We used two different markers of pericytes, PDGFR-β and aminopeptidase-N (also referred to as CD13), to ensure reliable quantification. We found no difference in the capillary coverage of pericytes (Fig. 5ad, e, g ), or in the number of pericyte cell bodies in either the anterior or posterior CC (Fig. 5f, h ). These data together show that there is no evidence of BBB leakiness and pericyte loss in the "pure" WMLs of CADASIL mice, supporting our findings in the WM from CADASIL patients.
Acknowledgements We are grateful to the  GIE-NeuroCeb brain bank (Paris, France) , the  Edinburgh Brain and Tissue Bank (UK) , and  Newcastle Brain Tissue Resource (NBTR, UK)  for human brain samples. The NBTR is funded in part by a grant from the  UK MRC  ( G0400074 ), by the  Newcastle NIHR Biomedical Research Centre in Ageing and Age Related Diseases award  to the  Newcastle upon Tyne Hospitals NHS Foundation Trust , and by a grant from the  Alzheimer's Society and Alzheimer's Research as part of the Brains for Dementia Research.
Funding This work was supported by  Fondation Leducq  ( Transatlantic Network of Excellence for the Study of Perivascular Spaces in Small Vessel Disease ,  16 CVD 05 ) and the  National Research Agency, France  ( ANR-16-RHUS-0004 ). RNKs work is supported by grants from  Alzheimer's Research UK (ARUK ,  PG2013-022 ) and the  Medical Research Council  ( MRC ,  G0500247 ),  Newcastle Centre for Brain Ageing and Vitality (BBSRC, EPSRC ,  ESRC  and  MRC, LLHW).
The column (Nucleosil® C18, 150 mm × 4. 6 mm, 3 μm particles size and 100 Å porosity) was thermostated at 40 °C using a Croco-cil (1267) oven. Data acquisition and injection control were performed by the Azur software (version 5. 0, Datalys®). The isocratic mobile phase consisted on a binary mixture of acetonitrile and 0. 1 % trifluoroactic acid aqueous solution (25/75, V/V). The injection volume was 20 μL. The detector was set at a wavelength of 555 nm and the pump at a flow rate of 1. 0 mL min -1.
Nanoparticle characterization Colloidal gold nanoparticles were characterized after synthesis without any dilution step. UV-vis spectrophotometer (UV-1800 Shimadzu) was used for spectra recordings and absorbance measurements. Molar absorbance value for AuNP was ε = 1. 2 x 10 7 M -1 cm -1  [25]. The hydrodynamic diameter (Dh) and zeta potentiel (ζ) of AuNP were measured at 20 ± 1°C using a Zetasizer Nano ZS (Malvern Instruments, UK). Transmission Electron Microscopy (TEM) images were recorded using a Philips CM20 instrument with a LaB6 cathode at 200 kV. DigitalMicrograph software was used to determine AuNP core diameters by measuring 200 individualized nanoparticles. Energy dispersive X-ray spectroscopy (EDS) was performed on a part of a grid.
4 except the isocratic mobile phase which consisted on a mixture of methanol and 10 mM citrate ammonium buffer pH = 7. 4 (80/20, V/V). The column was thermostated at 40 °C using a Croco-cil oven and the injection volume was 100 μL. The detector was set at a wavelength 330 nm and the pump at a flow rate of 1. 0 mL. min -1. Data acquisition and injection control were performed by the Azur software (version 5. 0, Datalys®). The reduction of DPPH • into DPPH2 by immobilized AuNP was studied in triplicate. The samples were placed in the dark and in a water bath at a temperature of 37°C and a stirring of 50 rotations per min. Chromatography analyses were performed at t = 0, 0. 25, 0. 5, 1, 2, 4 and 5 h. In parallel, controls at the same dilution of DPPH • were realized as follow: with GSH (as a reference antioxidant positive control (ca.
5 µJy). The surface density of IRAC red sources was computed in a circle of radius 1 around SPIRE source ID 1 (which is the brightest red source in the Herschel-SPIRE field and central to the structure of bright Herschel sources selected for the ALMA pointings). The resulting surface density estimate is 14. 6 arcmin -2. When compared to the field value derived from the Spitzer ultra deep survey (SpUDS) data at the same depth, which has a mean source density of 9. 2 arcmin -2 (and a standard deviation of 2. 2 arcmin -2 ), this corresponds to an overdensity of approximately 2. 5 σ  (Martinache et al. 2018). The ALMA detections have a match in at least the channel-2 image (Fig. 3 ), apart from galaxy ID 14, where there is emission in the Spitzer channel-2 map, but not significant enough to claim a detection.
WISE Additional mid-IR data were obtained from the AllWISE catalogue  (Wright et al. 2010; Mainzer et al. 2011 ) using a search radius of 3. Six galaxies are detected in the W1 (3. 4 µm) or W2 (4. 5 µm) bands, one in the W3 (12 µm) band, and none in the W4 (22 µm) band (for details see Table  A. 1). A&A proofs: manuscript no. ALMA_G073_pub   1. The black dashed line indicates a colour of -0. 1 (red sources are defined to have colours above this value), the red line indicates the median colour of IRAC red sources within 1 of SPIRE source 11 (0. 14 mag), and the blue line indicates the median colour for the ALMA sources matched to IRAC red sources (0. 27 mag). The dispersions around these median values are 0. 15 and 0. 13 mag, respectively (the latter is indicated by the blue region). The solid black line indicates the colour of a single stellar population formed at z f = 5, passively evolved to redshift z = 1.
Pan-STARRS We also searched the Pan-STARRS (grizy) DR1 data 4  (Chambers et al. 2019), since even upper limits can provide additional constraints to the fits. The upper limits in AB mags are g = 23. 3, r = 23. 2, i = 23. 1, z = 22. 3, and y = 21. 4. Only ALMA ID 4 is detected in the r, i, z, and y bands. The full set of available photometric data is reported in Table  A. 1.
Acknowledgements. We thank the referee for valuable suggestions that improved the paper. MP acknowledges financial support from  Labex OCEVU , CM acknowledges the support provided by  FONDECYT  postdoctoral research grant no. 3170774 , and RH and DS acknowledge support from the  Natural Sciences and Engineering Research Council of Canada. This work has been carried out thanks to the support of the  OCEVU Labex  ( ANR-11-LABX-0060 ) and the A *  MIDEX  project ( ANR-11-IDEX-0001-02 ) funded by the  'Investissements d'Avenir' French government  programme managed by the  ANR. This work is mainly based on the following ALMA data: ADS/JAO. ALMA#  2013. 1. 01173. S. ALMA is a partnership of  ESO  (representing its member states),  NSF (USA) , and  NINS (Japan) , together with  NRC (Canada) ,  NSC , and  ASIAA (Taiwan) , and  KASI (Republic of Korea) , in cooperation with the  Republic of Chile.
Additional funds for the construction of SCUBA-2 were provided by the  Canada Foundation for Innovation. The Pan-STARRS1 Surveys ( PS1 ) and the PS1 public science archive have been made possible through contributions by the  Institute for Astronomy , the  University of Hawaii , the Pan- STARRS  Project Office, the  Max-Planck Society  and its participating institutes, the  Max Planck Institute for Astronomy, Heidelberg  and the  Max Planck Institute for Extraterrestrial Physics, Garching , The  Johns Hopkins University, Durham University , the  University of Edinburgh , the  Queen's University Belfast , the  Harvard-Smithsonian Center for Astrophysics , the  Las Cumbres Observatory Global Telescope Network Incorporated , the  National Central University of Taiwan , the  Space Telescope Science Institute , the  National Aeronautics and Space Administration  under Grant No.
Maternal Dietary Assessment During the recruitment visit at 36-40 weeks gestation maternal baseline data were collected, including history of allergic disease, education, ethnicity, parity, and pet ownership (cat, dog, or both), and a maternal diet semi-quantitative food frequency questionnaire (SQFFQ) was administered  [38, 39]. The SQFFQ was developed and analyzed by The Cancer Epidemiology & Intelligence Division, Cancer Council Victoria, Australia, and reported frequency of 101 individual foods, mixed foods, and beverages that were regularly eaten over the previous month (32-36 weeks of gestation). The SQFFQ was used to calculate the total dietary fiber intake measured in grams per day (g/day) for each woman participant. The amount of the total dietary fiber in each single food item was then calculated as total dietary fiber (gram) in 100 g of each food item (g/100 g) and the dietary fiber sub-types (insoluble fiber, soluble fiber, prebiotics, and resistant starch) for each single food item was calculated.
For soluble fiber and insoluble fiber three sources were used: (1) latest dietary fiber values published by the Australian Bureau of Statistics (ABS) data (AUSNUT 2011-13) from Food Standards Australia New Zealand (FSANZ) (FSANZ, 2019)  [40, 41] , (2) food industry provided dietary fiber composition data published by FSANZ (FSANZ, 2013), and (3) the published dietary fiber data by the FSANZ in "Composition of Foods", Australia, 1989  [42]. For resistant starch, the maternal dietary intakes from each food item (g/100 g) was calculated using data from the food industry provided dietary fiber composition data (FSANZ, 2013) and the FSANZ publication "Composition of Foods", Australia, 1989  [42]. The Australian online nutritional analysis software programs FoodWorks  [43]  and Foodzone  [44]  were also used to cross check and complete the data.
Statistical Analysis All statistical analyses were performed using SPSS software (version 21. 0 for Macintosh, SPSS Inc. , Chicago, IL, USA). We used a binary (present or absent) classification to separately classify each of the allergic disease clinical outcomes. Total dietary fiber, soluble dietary fiber, insoluble dietary fiber, prebiotic fiber, resistant starch, as well as total dietary fiber from fruit, vegetables, green vegetables, grains, and gluten rich food were not normally distributed and were analyzed using non-parametric tests and results expressed as median and interquartile ranges (IQR). Univariate analyses were performed to determine the non-nutrient characteristics (demographics and environmental factors) associated with the clinical outcomes by using logistic regression. The final multivariable model included a comprehensive set of environmental and demographic risk factors which Nurmatov et al.
Study Population Characteristics A total of 930 mothers were initially recruited into this observational study. Four women were excluded from this current analysis due to missing baseline demographic data, 142 women were excluded due to missing SQFFQ data, and 22 women were excluded due to reported energy consumption data falling out of the pre-defined cut-offs. In total, 639 mother-infant pairs had infant allergy clinical outcome data available from the follow-up visit at 12 months of age, as 123 infants did not complete the follow-up assessments. The study population maternal and infant demographic data are summarized in Table  1. a median (IQR); b number (percentage); c mean ± SD.
Studies showing clinical or immunomodulation effects of prebiotic fiber intakes and associated increased SCFA production have had higher reported intakes or specific supplementation with prebiotics  [60] [61] [62] [63] [64]  and these studies have been limited to the postnatal period. This adds to the need for clinical trials in pregnancy to better characterize the effects of dietary fiber sub-types on the maternal microbiome, and associated effects on the metabolome (of mother and infant) and developing infant immune function. Investigation of any effects on breast milk composition may also provide another pathway through which maternal dietary fiber and prebiotics specifically may influence infant immune programming and allergy risk. To directly address this, we are currently undertaking two randomized controlled trials (in Australia ACTRN12615001075572 and in Europe NCT03183440) that will assess the effects of maternal prebiotic fiber supplementation during pregnancy on infant allergic disease outcomes.
Acknowledgments: We would like to sincerely thank the participating families and acknowledge the research nurses and research assistants involved with this cohort study. The authors thank  Graham Giles  of the  Cancer Epidemiology & Intelligence Division ,  Cancer Council Victoria , for permission to use the Dietary Questionnaire for Epidemiological Studies (Version 3. 2), Melbourne:  Cancer Council Victoria ,  1996. Conflicts of Interest: R. A. P. declares no conflict of interest. M. B. reports the following:  Scientific Advisory Board  from the  French Society of Nutrition, Paris, France. Research grants and speaker's fees from  Biostime Institute Nutrition and Care (BINC) ,  Geneva , Switzerland; from the  French Society of Allergy, Paris, France ; from the  French Society of Nutrition, Paris, France ; from the  French National Research Agency, Paris, France ; from the  Research, Education and Innovation program Food for Tomorrow/Cap Aliment , the  Pays de la Loire Region, France ; from interregional clinical research hospital program, France.
Funding: This research was funded by the  National Health and Medical Research Council (NHMRC) of Australia: Project Grants  ( APP1002381  and  APP1046036 ) and  NHMRC Fellowships  for D. J. P. APP1144544 and S. L. P. APP572503. R. A. P. is funded by an  Australian   Postgraduate Award and Safety Net Top-up scholarship  from the  University of Western Australia. The publication fee for this manuscript was funded by the  Telethon Kids Institute Fellowship Support Allowance  for D. J. P.
Transcriptomics Analysis The human PBMC transcriptomics dataset analyzed in this study was recently published  (3, 4)  and deposited at EBI Array express database (ID: E-MTAB-4890). This dataset was generated by Illumina Human Ref-8 v2 microarrays and included PBMC transcriptomes of 23 PP-MS and 40 healthy controls (HC). Raw data were processed in R using Limma package. Background was subtracted by nec method, data were normalized using cubic spline procedure, and batch effects were corrected by Combat. Probes correlating with age in the healthy population were removed. Probes with a mean intensity value lower than 100 in all experimental groups were filtered out.
Statistical Analysis Normality of data distribution was assessed by D'Agostino and Pearson statistics. Unpaired t-test (in case of normal distribution) or non-parametric Mann-Whitney U-test (in case of non-normal distribution) was performed to compare means between independent groups. Welch's correction was applied to the t-test in case of significantly different variances. All the p-values were two-sided and subjected to a significance threshold of 0. 05.
RESULTS Transcriptional profiles of peripheral blood mononuclear cells (PBMC) from 40 healthy subjects and 23 primary progressive multiple sclerosis patients were retrieved from our transcriptomics dataset published in Srinivasan et al. (3, 4). Interestingly, expression levels of the CD161 gene were significantly lower in progressive MS compared to the healthy population (Figure  1A ). Considering that this marker may be expressed by distinct immune cell subsets, including T lymphocytes and natural killer (NK) cells, we checked CD161 protein levels in PBMC from a new cohort of sex-and age-matched healthy and primary progressive MS subjects (Supplementary Table  1 ) by multiparametric flow cytometry. As shown in Figure  1B , the overall frequency of CD3 positive T lymphocytes, CD19 positive B lymphocytes and CD56 positive NK cells did not differ between healthy and diseased individuals.
PP-MS 19. 85 ± 1. 57 vs. PP-MS: 14. 82 ± 1. 62, p-value 0. 046) which was paralleled by 32. 5% reduction in the CD161 expressing effector memory CD8 T cell population (Mean ± SEM Ctrl vs. PP-MS 39. 92 ± 4. 87 vs. 27. 08 ± 3. 60, p-value 0. 043, Figure  1C ). We then queried our transcriptomics dataset for the expression of transcription factors regulating T cell differentiation, activation and maintenance. While the probe for Tbet/TBX21 [implied in Th1 differentiation and CD8 T cell effector function  (12) ] did not display detectable signals to be analyzed, those for GATA-3 [implied in Th2 differentiation and CD8 T cell survival,  (12, 13) ], Foxp3 [expressed by CD4 and CD8 regulatory T cells  (14, 15)  and RORA [a master gene for IL17 production  (16, 17) ], displayed equal expression in PBMC of healthy and PP-MS subjects (Figures  2A-C ).
This model predicts a process qq → γG (Fig. 1 right) , where G represents one or more Kaluza-Klein gravitons, each of which can have any mass up to M D. Since the gravitons escape detection, this process leads to the monophoton final state. In this paper we describe a search for an excess of monophoton events over the SM prediction. Data collected by the CMS experiment in 2016, corresponding to an integrated luminosity of 35. 9 fb -1 , are analyzed. Results are interpreted in the context of the three processes represented in Fig. 1. The primary irreducible background for the γ + p miss T signal is the SM Z boson production associated with a photon, Z(→ νν)+γ. Other SM background processes include W(→ ν)+γ (where the charged lepton escapes detection), W → ν (where is misidentified as a photon), γ+jets, quantum chromodynamic (QCD) multijet events (with a jet misidentified as a photon), γγ, tγ, ttγ, VVγ (where V refers to a W or a Z boson), and Z(→ )+γ.
For each event, hadronic jets are clustered from these reconstructed PF candidates using the anti-k T algorithm  [17, 18]  with a distance parameter of 0. 4. The jet momentum is determined as the vector sum of all particle momenta in the jet. Because of the large number of additional pp interactions within the same or nearby bunch crossings (pileup), particles emerging from multiple interactions can be clustered into a jet. To mitigate this effect, charged candidates associated with vertices other than the primary one are discarded from clustering, and an offset correction is applied to the p T of the jet to subtract the remaining contributions  [19]. Jet energy corrections are derived from simulation to bring, on average, the measured response of jets to that of particle level jets. Measurements on data of the momentum balance in dijet, photon + jet, Z + jet, and multijet events are used to account for any residual differences in jet energy scale in data and simulation.
Event selection The integrated luminosity of the analyzed data sample is (35. 9 ± 0. 9) fb -1  [22]. The data sample is collected with a single-photon trigger that requires at least one photon candidate with p T > 165 GeV. The photon candidate must have H/E < 0. 1 to discriminate against jets, where H/E is the ratio of HCAL to ECAL energy deposits in the central calorimeter tower corresponding to the candidate. The photon energy reconstructed at the HLT is less precise relative to that derived later in the offline reconstruction. Therefore, the thresholds in the trigger on both H/E and E γ T , are less restrictive than their offline counterparts. The trigger efficiency is measured to be about 98% for events passing the analysis selection with E γ T > 175 GeV. From the recorded data, events are selected by requiring p miss T > 170 GeV and at least one photon with E γ T > 175 GeV in the fiducial region of the ECAL barrel (|η| < 1.
First is the selection efficiency correction factor ρ, which accounts for subtle differences between simulation and observation in the reconstruction and identification efficiencies for various particle candidates. The value of ρ typically lies within a few percent of unity. The second factor is the higher-order QCD correction, which matches the distribution of the generator-level E γ T to that calculated at NNLO in QCD using the DYRES program  [30]. The third factor further corrects the E γ T distributions to account for NLO EW effects, and is taken from Refs. [31, 32] , updated using the LUXqed17 PDF set  [33]. Four sources of systematic uncertainties considered for E γ T distribution ratios among the V+γ processes are PDFs, higher-order QCD corrections, higher-order EWK corrections, and datato-simulation correction factors ρ.