dataesr/scientific-paragraphs-categorization huggingface dataset:
The B1 and DC2 channels (>1 MeV electrons) both clearly show field-aligned distributions which persisted during the entire record-mode data period, except maybe during one Galileo spin at 07:36. However, the persistent >1 MeV electron field-aligned distributions are not clearly seen at DC3 >10 MeV energies (Figure  3g ). The DC3 channel instead mostly shows pancake distributions (e. g. , at 07:05-07:06, 07:09, 07:12, 07:15-16) and a second type of PADs with two flux maxima at pitch angles near 90° and 180° (e. g. , at 07:12, 07:15, 07:19, 07:25, 07:29, 07:32, 07:42). The DC3 >10 MeV PADs with two maxima are further investigated with Figure  5  which shows selected electron PADs throughout the 1996-310 record-mode period. The >10 MeV PADs seem to repeatedly show a field-aligned component superimposed on a pancake distribution.
At R ∼ 26 Rj, M = 25-60 Galileo-EPD collected MeV electron PADs during 5 time periods at a radial distance around 26 Rj (Figure  1 ). In 1997-126, Galileo remained at distances larger than 0. 5 Rj from Callisto, while the four other time periods include a close encounter with Callisto (C3, C9, C10, and C30 encounters). Table  4  presents the shape of energetic electron PADs observed by Galileo-EPD, and a detailed analysis of magnetospheric record-mode data for each independent period of time is provided in Supporting Information S1. Flux units are cm -2. s -1. sr -1. keV -1 for E0 and cm -2. s -1. sr -1 for the DC2 and DC3 integral channels. For 15-42 keV electrons,  Mauk and Saur (2007)  identified true 'auroral' electron beams in 1996-126 (no fly-by) and during the C3 and C9 encounters, and we find another case during C30.
At 11:42, two successive Galileo spins (two right columns of Figure  6 ) also show B1 and F2 scattered beams. The shape of low-energy PADs observed during these two spins does not resemble higher-energy field-aligned distributions, so it is hard to conclude if a common mechanism is responsible at this time for the PAD of 10s of keV electrons, 100s of keV electrons, and MeV electrons. The origin of the persistent MeV electron field-aligned distributions can be high-latitude auroral acceleration, outward adiabatic transport or absorption by Callisto (a large-scale macro signature or a drifting micro signature). The sparse and limited dataset collected by Galileo-EPD is sufficient to detect for the first time this transient characteristic of MeV electrons at 26 Rj but is too limited to firmly establish the origin of the MeV electron field-aligned components.
Summary, Conclusions, and Discussions The The present study focused on the shape of energetic electron PADs in the magnetosphere of Jupiter. During close encounters with Europa, Ganymede, or Callisto, a particular attention has been put forth to try to disentangle as best as possible the local influence of the moon environments on electron distributions from the magnetospheric PADs that this article focuses on. Despite the fact that our analysis relied on an extremely sparse dataset, clear characteristics of MeV electron PADs are identified. Figure  7  summarizes the PAD shapes observed for MeV electrons during the record-mode type periods. We detail hereafter the implication of the observed PADs on our understanding of MeV electrons in the magnetosphere of Jupiter. 1. The MeV electron PADs observed by Galileo-EPD are relatively isotropic from M = 9 to M = 60, with the peak-to-peak flux anisotropy being lower than 3 when EPD scanned different pitch angles.
, 2018). However, the relatively large aperture of the EPD telescopes may smooth out the beamness of the keV to MeV field-aligned beams encountered by Ganymede and Callisto  (Mauk & Saur, 2007). Future work may investigate the effect of transient field-aligned beams of electrons on the bombardment and weathering of the two icy moon surfaces. We however note that the Galileo sparse dataset does not constrain the occurrence rate of field-aligned bursts bombarding the moons near the magnetic equator, something which can be investigated with Juno data in the <1 MeV energy range. For the assessment of radiation hazard, the quasi-isotropic characteristic of MeV electron fluxes implies that a direction-resolved flux taken in any direction of the sky would likely inform on the harmful omnidirectional flux.
We note that, similarly, the origin of energetic electron isotropic distributions in the outer magnetosphere of Saturn remains a mystery  (Clark et al. , 2014). 5. Scattered field-aligned distributions and butterfly distributions are observed for 20 keV to >10 MeV electron PADs close to Ganymede at M ∼ 15. We cannot firmly conclude if these distributions reveal local perturbations of Ganymede on electron distributions or if they show transient characteristics of the Jovian magnetosphere at M ∼ 15. Juno observations can be used to further investigate this topic in the <1 MeV energy range. The 1996-310 field-aligned distributions may be evidence of two distinct phenomena that cannot be distinguished with the limited Galileo-EPD dataset. First, the field-aligned distributions may be evidence that high-latitude auroral acceleration mechanisms supply the middle magnetosphere with trapped MeV electrons.
However, the F channels that observed 93-884 keV electrons are unreliable at M ∼ 9 and provide limited counts during a 20-s Galileo spin at M > 15. These limitations prevent us from computing the aforementioned direction-averaged and direction-resolved spectra, as done with 11-min EPD omnidirectional measurements by  Kollmann et al. (2018). We also acknowledge that electron PADs have been studied in this article without considering the dynamics of the magnetosphere. In particular, injection events may transiently create pancake PADs which would be detected at the spacecraft location with an energy-drift dependent timing. Finally, the occurrence rate of the different PAD shapes as a function of L and local time could not be constrained with the limited Galileo-EPD record-mode dataset. Using Juno <1 MeV electron data,  Ma et al.
Future Observations of MeV Electron PADs in the Jovian Magnetosphere Understanding the origin and dynamics of >1 MeV electrons at Jupiter is critical to our understanding of magnetospheres and particle acceleration in the solar system and beyond. The first step toward this objective is the accumulation of reliable electron spectra and PADs. Here, we have presented the first analysis of the dataset of MeV electrons PADs collected by Galileo-EPD. However, the dataset is very sparse in space and time. In addition, MeV electrons were observed only by three integral channels that may mix up different electron energy ranges. Finally, the EPD telescopes had relatively large opening angles of 15° and 45° that could not resolve the loss cone at the equator and may have smoothed out field-aligned beams.
17 of Socha (  2021 )). The observation of MeV electrons by JUICE-RADEM-ESD may significantly improve upon the Galileo-EPD dataset for three reasons. First, as an engineering sensor, RADEM will always be switched on, unlike the record-mode of Galileo-EPD, and will therefore provide larger coverage in time and space than EPD. Secondly, the 15° opening angle of RADEM-ESD will better resolve the anisotropy of >10 MeV electrons than the corresponding 45°-wide EPD telescope. Thirdly, the 6 RADEM integral channels that will observe MeV electrons will cover a larger energy range than Galileo-EPD. However, JUICE will be a 3-axis stabilized spacecraft, so JUICE-RADEM-ESD will most of the time not inform on the anisotropy of >1 MeV electrons. During JUICE roll maneuvers (for instance for magnetometer calibration), MeV electron PADs will be accumulated in a manner similar to what Cassini did at Saturn, with one spacecraft rotation possibly taking hours.
Acknowledgments We thank  Drew Turner  ( JHU-APL ) for discussions on the possible origins of pancake distributions. We thank  Dimitrios Millas  ( University College London ) for discussions on equatorial magnetic curvature scattering. Q. Nénon acknowledges support from the  ESA postdoctoral  fellowship, which funded the research presented in this article. The work of  L. P. Miller  was funded by  NASA  contract  80NSSC18P2239  for the  Planetary Data Archiving , Restoration, and Tools (PDART)  program. L. Liuzzo  acknowledges  NASA   Solar System Workings  Grant  80NSSC21K0152  and  NASA   New Frontiers Data Analysis Program  Grant  80NSSC21K0823.
Data Availability Statement Galileo-EPD and ancillary data used in this work can be accessed in the archive available at https://github. com/ fundamental-technologies-llc/galileo-issues-repository. This github repository contains in particular all numerical values of electron fluxes and pitch angles presented in this article. The individual Galileo spin plots of electron pitch angle distributions (PADs) generated in the present study, PAD spectrograms and count rate time series are available in the repository published at https://doi. org/10. 6084/m9. figshare. 20180222. v1.
EPD experiment onboard NASA's Galileo mission observed from 1995 to 2003 the PAD of 20 keV to >10 MeV electrons in the magnetosphere of Jupiter. MeV electron PADs were accumulated only when the high cadence acquisition mode of the instrument (known as the "record mode") was activated, that is, during short 1-2 hr time intervals. Specifically, MeV electron PADs have been collected at radial distances of 9 Rj (M ∼ 9), 15 Rj (M ∼ 15-18), 18-19 Rj (M ∼ 20-25), and 26 Rj (M ∼ 26-60). The collected dataset of MeV electron PADs has therefore a limited temporal and spatial coverage, yet it remains unprecedented because Galileo-EPD is the only experiment ever designed to observe the anisotropy of MeV electrons at Jupiter. In this article, the first analysis of MeV electron PADs observed by Galileo-EPD has been presented.
4c  and Supplementary Fig. 5a ). IL-1β deficiency also impaired MDSC accumulation into the tumors of mice under HFHCD (Fig. 4c ), but did not impair MDSC function as they retained a high to even greater Representative microphotographies of tumor sections after hematoxilin/eosin coloration. e Quantification of CD45 + leukocytes in the tumor, by flow cytometry (n = 8 mice/group for evaluation at day 3, 5, 7 and n = 8/group at day 9. Data were pooled from three experiments). Flow cytometry analysis of f main subsets of leukocytes (%) in tumors at the time of sacrifice (n = 13 in CD group and n = 10 in HFHCD group), g and of M-MDSC (CD11b + Ly6C hi ), PNM-MDSC (CD11b + Ly6C lo Ly6G + ) and TAM (CD11b + Ly6C lo Ly6G -F4/80 + ) among CD11b + cells in the tumor (n = 13 in CD group and n = 10 in HFHCD group, pool of two independent experiments) (left), and t-SNE plots representing an overlay of total CD45 + cells (gray) and M-MDSC (red), PNM-MDSC (blue) and TAM (purple) (right).
h gMFI of MHC II and (%) CD206 + MHC II lo in macrophages (M2 markers) in tumor and spleen (n = 9 in CD group and n = 7 in HFHCD group, unpaired t-test). i Expression of CD44 (%) and granzyme B (%) among CD8 + and NK cells in the tumor and spleen (n = 9 in CD group and n = 7 in HFHCD group). j B16-F10 proliferation was measured by 3H-Thymidine incorporation. B16-F10 were cultured, for 24 h, alone (n = 3) or with CD45 + cells isolated from CD (n = 5) or HFHCD tumors (n = 3). k Ki-67 immunohistochemistry staining was performed on FFPE tumor. (left) Quantification of % DAB staining and (right) representative picture of Ki-67 staining in the CD group (n = 9) and in the HFHCD group (n = 8). Scale bar = 100 µm. Data are expressed as mean ± s. e. m. Analysis of difference within groups were performed with Mann-Whitney t-test, and with one-way ANOVA with Bonferroni's multiple adjustment test.
Under HFHCD, infiltrating myeloid cells control tumor growth via VEGF-A production We performed a transcriptome analysis of total tumors in response to HFHCD: 1935 genes were differentially expressed, 1076 upregulated, including Vegf-a (fold change 3. 4, p = 0. 018) and 859 downregulated in tumors from HFHCD group (Fig. 5a , top 100 differentially expressed genes are shown in heatmap in Supplementary Fig. 6  and data file is available through GEO Series accession number GSE211392). Interestingly, despite the use of tumor bulk transcriptomes, "regulation of myeloid leukocyte differentiation" and "negative regulation of myeloid leukocyte differentiation" pathways were enriched (p = 0. 013 and 0. 015 respectively), as well as several metabolic pathways ("low-density lipoprotein particle remodeling", "glycerolipid metabolic process", "phospholipid metabolic process") and autophagy (Top genes are colored in Fig.
For intracellular staining, after surface staining, cells were permeabilized using the FoxP3/transcription Factor staining buffer set (eBiosciences) according to manufacturer's protocol, then stained with intracellular mAb. For intracellular cytokines staining, cells were first incubated 4 h at 37 °C in the presence of Golgistop (Monensin) and Golgiplug (Brefeldin A) (both from BD Biosciences) in complete medium, then staining for surface molecules and intracellular staining as described above (Supplemental Table  2 ). Dead cells were excluded using live/dead fixable aqua dead cell kit (Invitrogen). Samples were acquired on Fortessa X20 and on a LSR Fortessa Analyser (BD Biosciences) and analyzed with FlowJo software (V10). For Dimensionality reduction using t-SNE and automatic clustering: CD45 live cells were manually gated from multicolor flow cytometry and exported in a FCS file.
Gene expression analysis For the transcriptomic analysis, 4 tumors per group were harvested from mice fed with CD or HFHCD at Day 9 post injection of B16-F10 melanoma cells. Tumors were minced and lysed into RLT buffer containing 1% β-mercaptoethanol. RNA was extracted using Qiagen RNeasy kit according to the manufacturer's instructions. Analysis of gene was done by Affymetrix MouseGene2. 0ST array at the GENOM'IC core facility (Cochin Institute). P-values were obtained by a two-sided Student's t-test with group variance within limma package. Complete analysis is provided through GEO Series accession number GSE211392 (https://www. ncbi. nlm. nih. gov/geo/ query/acc. cgi?acc=GSE211392). Genes with p-value < 0. 05 were used for enrichment pathway analysis with R library clusterProfiler with Gene Ontology knowledgebase  51.
All immunoassays were performed according to manufacturer's protocol and analyzed on Bio-Plex 200 V6. 1 (Bio-rad). The analytes concentration was calculated using a standard curve (5 PL regression), with Bioplex 200 manager software (Bio-Rad). Non-detectable or non-relevant cytokines were not presented. TNF-α, IL-12, IL-10, IL-1β were evaluated by ELISA (R&D system) for BMDM supernatant. VEGF-A concentration was evaluated by ELISA (mouse VEGF DuoSet, R&D system) or by beadbased multiplex immunoassay (R&D Biotechne) in tumors lysates and in plasma. For ELISA, analysis were done on Spectrostar microplate reader (BMG labtech), analytes concentration was calculated using a standard curve with linear regression (R 2 > 0. 99) with MARS Data Analysis Software V5.
Primary antibodies were incubated overnight (anti-Ki67: 1/200, anti-CD31: 1/ 2000 and anti-αSMA: 1/2000) in humidify chamber. Secondary antibody is a ready-to-use HRP micro-polymer conjugated goat anti-rabbit and he was incubated 15 min at room temperature. Finally, the DAB chromogen/substrate of detection kit was used to reveal the secondary antibody location and sections were counterstained with hematoxylin and then cover-slipped. The quantification of DAB staining was performed with ImageJ (FIJI) through a color deconvolution. Then, the software is able to detect and measure stained pixels. The quantification of DAB staining is obtained by dividing the section pixel measure by the stained pixels measure.
Acknowledgements This work was supported by grants from the  ARC ("Association pour la recherche sur le cancer")  and the "Ligue contre le cancer" foundations (SP). Tartour's laboratory is tanksful to  Labex Immuno-Oncology, SIRIC CARPEM, INCA PL Bio, Fondation ARC, Foncer. Tartour's laboratory  is supported by the  "Ligue contre le cancer" foundation (ET). In vivo imaging was performed at the  Life Imaging Facility of Paris Descartes University (Plateforme Imageries du Vivant-PIV ), supported by  France Life Imaging  (grant  ANR-11-INBS-0006 ) and  Infrastructures Biologie Santé. We are thankful to  Pr Bertrand Tavitian  and  Dr Thomas Viel  for their expertise in molecular imaging. We thank  Agnes David  for her expertise in lipidome analysis. We thank  Pr Christian Stockmann  for providing LysMCre +/-/ VegfA f / f mice.
In spite of human impact becoming increasingly pronounced in locally shaping habitats and ecosystems either directly or indirectly, to predict sh assemblage composition and structure at continental scales only catchment level attributes independent of human activity need to be taken into account. Consequently, to estimate macroscale habitat composition we selected key macroscale environmental characteristics, representing an array of environmental processes responsible for freshwater habitat creation at the catchment scale. These are: river slope, stream order, catchment size, altitude, catchment geology, and bio-climatic zone. By combining these attributes and referencing them to pan-European sh survey data at undisturbed reference sites, we created the rst sh macrohabitat classi cation model for Europe to estimate expected sh community structure under natural conditions (Figure  1  and 2 ).
Anticipated Fish Responses To Impoundment Aquatic organisms, including sh, are typically well adapted to speci c habitats occurring at certain locations and time periods. Fish habitat preferences vary in terms of available feed, substrate for spawning, ow characteristics, pelagic versus demersal or benthic lifestyles, and tolerance to physiochemical (oxygen) and habitat changes  22. Using data from the available literature about habitat preferences for each Habitat Use Guild, we developed response scores re ecting each guild's sensitivity to habitat changes caused by impoundment. Results showed a gradient of response, from intolerant rheophilic species to highly tolerant generalist species (see Methods for details). Knowing the expected guild structure at a given location, we were subsequently able to predict aggregate sh community sensitivity to impounding across Europe (Figure  3 ).
Projected River Habitat Loss Across Europe Based on our macrohabitat typology and barrier impacts framework, we make a rst attempt at assessing the impact of river barriers at the European scale. Since habitat alteration by impounding with culverts, fords and ramps is a magnitude lower than with other barriers, we further focused only on barriers creating substantial impoundments. For the 92,167 identi ed dams, weirs, and sluices with recorded height data in the AMBER Barrier Atlas 8 , we estimate a total impoundment length of just over 67,000 km, of which around 30,100 km (45%) still provides useable habitat for sh, thus translating to a net loss of approximately 36,900 km (55%) of river habitat. (Table  2 ). On a per barrier basis, severe habitat loss is mainly concentrated in coastal areas of western Norway and southern portions of Austria (Figure  5 ), though this may be down to comparatively more complete national barrier databases in these areas.
Our study forms a fundamental basis for further assessment of river barrier impacts. Certainly, more comprehensive barrier data is needed to derive further estimates of habitat loss for different sh communities and barrier types. Yet at present, most national inventories are far from complete, especially for the large number of smaller barriers, such as culverts, fords, and ramps. Furthermore, key structural information, like barrier height, is often missing and few databases account for natural barriers. This can have signi cant consequences for management decisions, leading to costly expenditure for low to moderate ecological bene t. Clearly, more complete and more detailed barrier data as well as novel barrier prioritization tools capable of accounting for data uncertainty would go a long way toward enhancing barrier impact assessment and river restoration planning.
Overview This paper presents a riverine macrohabitat typology to support barrier impact assessment and evaluates management and restoration efforts in compliance with the EU WFD. It builds on the notion of a template riverine habitat composition to support an expected sh community structure. The typology can further be used to predict the level of "deviation" of freshwater communities from their predicted baseline. The habitat templates are predicted from broad physio-geographic and environmental features and validated with sh catch data. The following steps were performed to develop the macrohabitat typology: Identify sh Habitat Use Guilds from sh biological data collected at undisturbed sites with unmodi ed or least modi ed habitat conditions. These guilds serve as proxies habitat preferences.
Fish data The source of shery data is the European Intercalibration database gathered between 2006 and 2011 under the auspices of the European Commission Joint Research Centre (JRC) to support implementation of the Water Framework Directive  37. This database contains information on 4561 sh survey sites in 22 countries. The database consists of several tables describing basic physical parameters for each site, details of each shing campaign, and catches obtained by electro shing surveys. Data on anthropogenic pressures, including impounding, are available, thereby enabling distinction between reference and disturbed sites. The Intercalibration database was used with the permission of JRC and data owners from 19 EU member states involved. A similar dataset for Poland, gathered during the autointercalibration process  38  , was used with the permission of the Chief Inspectorate for Environmental Protection, Poland.
The nal database containing 5497 survey sites was subsequently ltered based on pressure criterion to select anthropogenically undisturbed sites. Pressures were grouped into ve categories: i) connectivity, ii) hydrological alteration, iii) morphological alteration, iv) water quality, and v) navigation, recreation and biological pressure from invasive species. Sites least impacted were considered references for the purpose of river ecosystem quality assessment. Of the 1315 sites (river reaches) meeting criteria for being least impacted, a subset of 1099 in 17 countries was identi ed considering data use limitations and data quality issues (i. e. , precision of the site location referenced to the river network database, discussed below). The location of shing sites is presented in Extended Data Figure  1.
Fish Habitat Use Guilds Fish surveys across a large region are affected by variability due to different surveyors, sampling methodology, seasonality, and year of survey. This affects the accuracy of sh community prediction models. To account for this, predicted sh distributions can be t into generic distribution patterns such as those used in biocomplexity models  39. The Target Fish Community approach 40 uses a model of ranking relative abundance of species observed during a survey, which can, in turn, be used to calculate expected proportions according to a biocomplexity formula. Fish catch data were subject to this procedure to level out the in uence of natural variability on sh catch data. To further reduce regional variability between samples, it has been proposed to group species into Habitat Use Guilds and estimate the structure of a guild assemblage rather than species.