dataesr/scientific-paragraphs-categorization huggingface dataset:
Halo mass An alternative, widely used method to evaluate a galaxy's environment is by the halo mass of the group to which it belongs (see, e. g. Muldrew et al. 2012; Fossati et al. 2015). The halo mass is obtained from abundance matching techniques between the halomass function and the stellar mass (or luminosity) of the most massive galaxy identified within the group (see e. g. Yang et al. 2007 Yang et al. , 2008 Yang et al. , 2009)). We correlated our cz < 10 000 km s -1 catalogue with the one by  Yang et al. (2007) , which extends much further out than our local sample, although excluding the local supercluster and the Virgo cluster (cz > 3000 km s -1 ). We found 21608 matches in the shared redshift range between the two catalogues. Only 427 galaxies in the Yang catalogue have no counterpart in our database, and a visual inspection revealed them to be primarily extranuclear H II regions, not galactic nuclei.
In Fig. 12 , we show the completeness as a function of the r-band magnitude (top panel) and of the stellar mass log(M star /M ) (bottom panel). The blue lines represent SDSS-only spectra, and the black lines include spectra taken from the SDSS and other sources. Along with the completeness of the SPRING catalogue compared to SDSS-only data (thick straight lines, left y-axis), the actual numbers of galaxies with nuclear spectra for both samples is displayed as well (dashed lines, right y-axis). The addition of non-SDSS spectra to our flux-and volumelimited sample dramatically increases the completeness at the high-mass end of the catalogue (or, similarly, at the bright end), which is known to suffer a residual incompleteness in the SDSS database. Only 361 targets (∼1%) in the SPRING catalogue remain without nuclear spectra 3.
EWHα versus [NII]/Hα diagnostic In addition to the BPT diagnostics, the classification of the nuclear activity based on optical emission-lines is also performed following the two-line WHAN classification scheme. It is a less demanding diagnostic than the BPT, as it only requires the intensities of two lines (Hα and [NII]λ6584), and is based on the [NII]/Hα ratio combined with the strength of the Hα line corrected 4  for underlying stellar absorption. Owing to this twoline diagnostic, even the red-channel spectra such as the majority of those obtained at Loiano  (Gavazzi et al. 2011 (Gavazzi et al. , 2013b (Gavazzi et al. , 2018) )  contribute to increasing the number of known AGN, especially those associated with nearby bright galaxies, most affected by the residual incompleteness of the SDSS spectral database.
Summary In this work we present the SPRING catalogue, a complete photometric database (r < 17. 7 mag) of local galaxies in the northern spring sky (10 h < RA < 16 h ; 0 • < Dec < 65 • , cz < 10 000 km s -1 ) by merging the Portsmouth emissionline table by  Thomas et al. (2013)  extracted from the SDSS and the NASA-Sloan atlas  (Blanton et al. 2011). To further reduce the bright-end incompleteness, we complemented our sample with the updated Zwicky catalogue (UZC)  Zwicky et al. (1961) ,  Falco et al. (1999) , and with the UGC catalogue  Nilson (1973). We got the available nuclear spectroscopy from the SDSS, and integrated it with optical spectra taken by other surveys  (Zwicky et al. 1961; Nilson 1973; Ho et al. 1993 Ho et al. , 1995 Ho et al. , 1997;; Falco et al. 1999; Gavazzi et al. 2011 Gavazzi et al.
Acknowledgements. The authors thank the anonymous referee for their constructive comments and suggestions. We are grateful to  Paolo Franzetti  and  Alessandro Donati  for their contribution to GoldMine, the Galaxy On Line Database (Gavazzi et al. 2003) extensively used in this work (http:// goldmine. mib. infn. it). We thank  Andrea Macció  for useful discussion. We also thank the coordinator of the  TAC Giovanna Stirpe  for the generous time allocation at the 1. 52 m Cassini Telescope, run by  INAF-Osservatorio Astrofisico e Scienza dello Spazio di Bologna at Loiano. This research has made use of the  NASA /IPAC Extragalactic Database (NED), which is operated by the  Jet Propulsion Laboratory, California Institute of Technology , under contract with the  National Aeronautics and Space Administration.
Abstract. The latest Intergovernmental Panel on Climate Change (IPCC) report describes an increase in the number and intensity of marine heatwaves (MHWs) and a decrease in marine cold spells (MCSs) in the global ocean. However, these reported changes are not uniform on a regional to local basis, and it remains unknown if coastal areas follow the open-ocean trends. Surface ocean temperature measurements collected by satellites  (from 1982-2022)  and 13 coastal buoys  (from 1990-2022)  are analyzed in the northeastern Atlantic and three subregions: the English Channel, Bay of Brest and Bay of Biscay. The activity metric, combining the number of events, intensity, duration and spatial extent, is used to evaluate the magnitude of these extreme events. The results from in situ and satellite datasets for each of the studied regions are quite in agreement, although the satellite dataset underestimates the amplitude of activity for both MHWs and MCSs.
Buoy data The in situ SST data are from autonomous coastal buoys that take continuous high-frequency measurements from 10 min to 1 h (Fig. 1a ). These buoys are from different European organizations, detailed below and in Smart, SMAR, https://doi. org/10. 17882/86020) and in the Bay of Biscay (Molit, MOLI, https://doi. org/10. 17882/46529; Arcachon, ARCA). The Met Office (https://www. metoffice. gov. uk, last access: 2 January 2023) manages several buoys and also offshore sites. The buoys used here are located in the English Channel, on the southern coast of England, at Seven Stones (SEVE), Channel (CHAN) and Greenwich (GREEN). The Western Channel Observatory (WCO; https://www. westernchannelobservatory. org. uk, last access: 4 April 2023), situated within the western English Channel, operates two oceanographic moorings.
In the Bay of Brest, we also observe a similar increase but with larger activity in in situ observation as the intensity of extreme events is underestimated by the satellite in this semi-enclosed bay. The use of in situ observation limits the length of the analyzed time series. However, we can observe larger activity in recent years from both datasets. For most cases, the most active years are detected with in situ observations and satellite data. Considering coastal stations over the observed periods, we see a more pronounced increase in MHW activity from 2010. https://doi. org/10. 5194/os-19-1339-2023 Ocean Sci. , 19, 1339-1355, 2023 The English Channel and the Bay of Biscay in situ stations highlight the year 2022 as the most active year exceeding 140 • C d. In the Bay of Brest, the impact of the 2022 MHWs is less pronounced, in agreement with satellite observation (Fig.
, 2018; Oliver et al. , 2021). In addition, we found a positive trend for the MHW activity parameter using both satellite data and the four buoys in the Bay of Biscay and for the duration and occurrence using satellite data. The trends are quasi-similar considering only the two buoys on the southern coast of the Bay of Biscay (GIJO and BILB) and the two on the western coast of the Bay of Biscay (ARCA and MOLI; not shown) and are marked by the high activity present in the more recent summers. This evolution in the occurrence and duration of MHWs was not seen in  Izquierdo et al. (2022b)  using two buoys in the southern coastal Bay of Biscay over the period 1998-2018, which could be explained by local processes or the studied season (March to August). The results from in situ and satellite datasets for each of the studied regions are quite in agreement, although the satellite underestimates the amplitude of activity for both MHWs and MCSs.
This is explained by an increase in both the mean and variance of SST. Conversely, a decrease in MCS activity was detected, with almost no events after 2000, more clearly shown with the satellite data due to the longer time series (40 years) compared with the in situ data (20 to 30 years). These changes are fast for the three subregions, with the English Channel being the subregion with the most drastic growth. In the northeastern Atlantic, MHWs are more frequent and longer and extend over larger areas, while the opposite is seen for MCSs. For both MHWs and MCSs, the mean intensity shows only weak changes over the last 4 decades. Moreover, we found that the satellite dataset used is in good accordance with in situ data in the northeastern Atlantic, except for the fact that satellites underestimate the amplitude of both hot summer and cold winter marine extreme events in the coastal areas.
Acknowledgements. We thank  Oregan Segalen  for fruitful discussions. We thank  Tim Smyth  for providing data from the  Western Channel Observatory. We acknowledge the COAST-HF (http: //www. coast-hf. fr, last access: 2 January 2023) national observing network component of the ILICO national research infrastructure. Additionally, we express our gratitude to the two reviewers and editor for their valuable feedback, which has greatly contributed to improving the quality of our work. Financial support. This work was partially supported by national funds through  FCT (Fundação para a Ciência e a Tecnologia, Portugal)  for the project  ROADMAP  (grant no. JPIO-CEANS/0001/2019 ). This research has been supported by the regional project ( Contrat de Plan État-Région)   ObsOcean/ROEC-ILICO  and the regional  COXTCLIM  project funded by the  Loire-Brittany Water Agency , the  Brittany region and Ifremer.
Data availability. All datasets included in the present study are accessible from the following publicly available repositories. Satellite dataset OISST is available on ftp://ftp2. psl. noaa. gov/ Datasets/noaa. oisst. v2. highres/, last access: 24 January 2023 and ERA5 reanalyses on https://www. ecmwf. int/en/forecasts/dataset/ ecmwf-reanalysis-v5, last access: 25 August 2023. Buoy in situ datasets are available on http://data. coriolis-cotier. org, last access: 2 January 2023 for COAST-HF data, https://www. westernchannelobservatory. org. uk, last access: 4 April 2023 for the Western Channel Observatory, and https://emodnet. ec. europa. eu, last access: 2 January 2023 for other datasets. Supplement. The supplement related to this article is available online at: https://doi. org/10. 5194/os-19-1339-2023-supplement.
So, the second goal was to analyze changes in the redox enzyme expression during the activation of polyamine catabolism in HepaRG cells. Previously we showed that the activation of polyamine catabolism by treatment with N 1 ,N 11 -diethyl-nor-spermine (DENSpm) induces dedifferentiation that resembles epithelial-mesenchymal transition  [21]. However, despite the transcriptomic analysis performed in that paper, we did not assess the differences in the transcription levels of redox enzymes and regulatory proteins or the enzymes of polyamine and related metabolic systems. So, the current study fills this gap through the targeted re-analysis of that RNAseq dataset.
Preparation and Transcriptome Sequencing of cDNA Library The cDNA library was prepared using the TruSeq RNA Library Preparation Kit v2 (Illumina, San-Diego, CA, USA) according to the vendor's protocol. mRNA was isolated using magnetic beads with (dT)-oligomers. After isolation, the mRNA was fragmented and then converted into double-stranded cDNA that was ligated with adapters and amplified. The quality of the final cDNA libraries was assessed using quantitative PCR reaction on a Rotor-Gene Q Instrument (Qiagen, Hinden, Germany). The sequencing was performed as described previously  [21]. The raw FASTQ Illumina sequence data has been deposited to the Sequence Reading Archive (SRA) (accession number PRJNA494568).
25 mm, 0. 25 µm) (Agilent Technologies, Santa-Clara, CA, USA). The oven temperature was kept at 60 • C for 1 min, ramped to 325 • C at 10 • C/min, and held for an additional 10 min at this temperature. The injector, transfer line, and ion source temperature were set to 250 • C, 290 • C, and 230 • C, respectively. After 8 min of solvent delay, the MS data were acquired in full scan mode from m/z 50-600. Raw spectra were analyzed using Chromatec Analytic software (version 3. 0. 0. 2). The quantification of amino acids, including glutamate, proline, and pyroglutamate, was performed in SIM mode using the target ion and retention time for each metabolite. These data were obtained by analyzing their standards prepared using the same derivatization protocol, analytical parameters, and instruments.
ROS-Producing Enzymes First, we assessed the levels of expression of ROS-producing enzymes in Huh7. 5 and HepaRG hepatoma cells in normal conditions and during the activation of polyamine catabolism in an RNAseq dataset previously published in  [21]. These enzymes included NADPH-oxidases (NOX), cytochrome P450 (CYP), and various catabolic enzymes. The NOX/DUOX family of NADPH-oxidases comprises seven members: NOX1, NOX2, NOX3, NOX4, and NOX5, as well as dual oxidases 1 and 2 (DUOX1, DUOX2)  [33]. These transmembrane proteins are capable of transferring electrons across cell membranes, while reducing molecular oxygen to superoxide anion or hydrogen peroxide. We also analyzed the mRNA levels of two more members of the NADPH oxidase multiprotein complex, the activator of the NOX1 isoform, NOXA1, and the cytoplasmic protein NCF2 (neutrophil cytosolic factor 2).
5 line, while in HepaRG cells, the levels of their transcription remained very low. These data were verified by reverse-transcription and quantitative PCR (RT-qPCR), using the cDNA of PHH as an additional control. As one can see in Figure  1c , the levels of the transcriptions of NOX1 and NOX4 were indeed elevated in tumor Huh7. 5 cells compared to non-tumor HepaRG or PHH. For DUOX2, no statistically significant differences in RT-qPCR tests were observed. However, the levels of its mRNA were close to the limit of detection (Ct values >30). This correlated with our previous observation that the quantification of transcripts that are present in RNAseq data at levels below 3 cpm is difficult when using RT-qPCR. Ero1α showed no significant differences for both cell lines. The transcripts of all other enzymes were expressed to a significantly stronger level in HepaRG cells (Figure  1 ).
Calcium Transporters and Their Regulatory Proteins The final aim of the work was to analyze the expression of various calcium ion transporters on the plasma membrane, endoplasmic reticulum, and mitochondria, as calcium homeostasis is tightly linked with redox status of a cell. The results are shown in Figure  6. One can see that Huh7. 5 and HepaRG lines differ both in the mRNA levels of the ORAI calcium channel proteins and in the mRNA levels of their STIM adapter proteins (Figure  6a ). In hepatoma cells, ORAI1 and STIM2 adapter protein were the predominant forms, while in HepaRG cells, transcription of ORAI3 and STIM1 was much higher, as revealed in RNAseq dataset and by real-time PCR (Figure  6a, d ). Activation of polyamine catabolism triggered a significant drop in the level of ORAI3 mRNA.
g. life traits of humans, recent hospitalization events and/or antimicrobial intake, caring of animals in households, husbandry practices, water and waste management; see File S2, available as Supplementary data at JAC Online). This study was conducted in accordance with the Malagasy law and approved by the ethical committee on biomedical human research (Comité d´Ethique de la Recherche Biomédicale de Madagascar) under the reference N° 031-MSANP/CERBM.
Core genome analyses Core genome analyses were performed by mapping the reads to the E. coli O157:H7 Sakai strain complete reference genome (NC_002695. 1) using the 'very-sensitive' option of Bowtie2 aligner. 34 PCR duplicates were removed using Picard tools (http://broadinstitute. github. io/picard/). SNPs were called with GATK UnifiedGenotyper  35  and conserved only if: (i) the proportion of high-quality bases supporting the call was >90%; (ii) the coverage was >15; (iii) the mapping quality of reads was >20; and (iv) the distance from another SNP was >10 bp. Consensus bacterial genomes were then constructed by introducing high-confidence SNPs within the reference genome and replacing both filtered-out variants and uncovered sites (depth = 0) by 'N's. We used Gubbins 36 to detect regions acquired via horizontal gene transfers and excluded them to generate a recombinationfree SNP alignment from which a maximum likelihood phylogeny was constructed using RAxML 8.
2. 4 37 with a rapid bootstrap analysis, general time-reversible model of evolution with a four rate categories γ distribution (GTRGAMMA) and 1000 iterations. The tree was rooted using an Escherichia fergusonii strain isolated within the course of this study (but excluded from other analyses). Visualization of the phylogenetic tree, along with metadata was performed using custom scripts sourcing the ape  38  and ggtree  39  packages of the R software environment. 40 STs and phylogroups were inferred for each strain using stringmlst  41  and ClermonTyping 42 software, respectively. Non-random distribution of STs and phylogroups amongst hosts was assessed using the chi-square test with simulated P values using the chisq. test R function. Pairwise genetic distances between each sequenced strain were computed using the 'distTips' function of the adephylo R package.
ESBL-Ec transmission clusters Transmission clusters were inferred using a phylogenetic clustering tool designed to negate the need for arbitrarily defined cluster divergence thresholds. 44 Requiring only the phylogenetic tree as input, Phydelity infers putative transmission clusters through the identification of groups of sequences that are more closely related than the ensemble distribution under a statistically principled framework. For each transmission cluster, we computed the number of SNPs between each pair of samples composing the cluster and the mean and maximum observed values. Because the total genetic diversity in our dataset was very high (mean number of SNPs between samples was 2914), Phydelity could group samples with a significant divergence in the same 'transmission' cluster.
Mobilome and resistome analysis De novo assembly of Illumina reads was performed using Unicycler  46  with the option-normal for balance between completeness and reliability. Each contig was then analysed with the mob-typer component of the MOB suite software  47  to retrieve putative loci of origin of replication, relaxase and incompatibility groups with a BLAST-based approach, followed by a clustering of plasmids based on the MOB database. The resistome of each sample was determined with Resfinder 48 and its associated database using a mapping approach performed directly with raw Illumina reads. This direct mapping approach was chosen because de novo assembly in the absence of long reads technology is prone to misassembly even for small circular genomes. 49 Statistical association between the distribution of ESBL resistance genes/alleles and the different hosts was tested using chi-square tests with simulated P values.
Core genome analyses Sequencing all the 510 ESBL-Ec showed a prominent level of genetic diversity composed of seven phylogroups and 84 different known STs (Figure  2 ). Phylogroup A and ST3489 were the most represented (70. 6% and 11. 6%, respectively). Interestingly, 4. 1% of strains were unknown from the searched ST database because they exhibited new allelic combinations unknown from the searched database (Table  S1 , available as Supplementary data at JAC Online). Those new STs accounted for most of the genetic diversity in the environment (water) and several animal hosts including pigs, ducks and geese. Phylogroups (chi-square test, P = 0. 48) and STs (chi-square test, P = 0. 17) were homogeneously distributed amongst hosts but marginally associated with households (chi-square test against phylogroups, P = 0.
Of those, 28/43 (65. 1%) included pairs of strains both from animal sources, 7/43 (16. 3%) from human/animal sources, 5/43 (11. 6%) both from human sources, 2/43 (4. 7%) from water/human sources and 1/43 (2. 3%) from water/animal sources. Fifteen of 104 clusters (14. 5%) were restricted to a single household, and 67/70 households (95. 7%) hosted at least one sample involved in a cluster. Host distribution amongst clusters did not show statistical deviation from an expected random distribution calculated from the total dataset (multinomial test, P > 0. 05). The composition of each cluster was independently compared with the global distribution and none showed significant departure from either global host or household composition (multinomial tests, all P > 0. 05) (File S4).
Mobilome and resistome analysis Among the samples 23 ESBL genes were identified (Figure  5 ). Among those, bla CTX-M-15 was the only one identified in all compartments (Figures  3a  and 5 ) and represented 69. 0% of all ESBL genes identified in the study. Multiple ESBL genes cooccurred on the same genomes, with up to four in a single sample (Files S1 and S3). We also screened for the presence of known antibiotic resistance-conferring mutations in gyrB and parC genes and found them in 26. 3% and 12. 0% of samples, respectively. Interestingly, we report the presence of SHV-13 in 20 ESBL-Ec isolated from the three compartments (File S1), an enzyme that has previously only been detected in clinical Klebsiella pneumoniae isolates. Globally we confirmed the absence of host-specific resistance genes structure in our dataset (chi-squared test with simulated P value = 0.
It is also expected that alternative paths of dissemination are used by ARB to colonize their hosts. Notably, food routes of ESBL-Ec and ARB should be explored in LMIC to better enlighten patterns of transmission as hypothesized in Cambodia 29 and in a systematic review. 50  Screening the whole set of 510 detected ESBL-Ec revealed a high diversity of ESBL AMR genes in each compartment while highlighting the absence of any host-specific structure. Amongst the β-lactamase detected genes, bla CTX-M-15 identified in all compartments was the most frequent, in accordance with a previous report from Madagascar. 59  As formerly described,  65  we observed multiple ESBL genes co-occurring in the same genomes (File S3). Investigating our dataset at the plasmid level, we gathered information on putative associations between resistance genes, incompatibility loci, the bacterial ST and the EBSL-Ec carrier hosts.
49  Although we can be confident in the overall observed content of resistance genes and incompatibility loci in each putative plasmid, we are far less confident in the reality of their associations when plasmid assemblies are fragmented. Nonetheless, we have provided extensive supplementary material for anyone willing to investigate these lower-level associations further. Our study has several limitations. First, for each pair of samples, we measured the genetic distance between two randomly drawn ESBL-Ec among the gut microbiota, potentially missing any direct link between samples harbouring recently transmitted bacteria. This could lead to a systematic underestimation of the transmission events between and among compartments. Although the effect of this bias on the observed absence of genetic structure in our dataset is not straightforward to assess, we hypothesize that our observations are an underestimation of the bacterial network's connectedness.
Acknowledgements We thank  Dr Laurence Baril , head of the  Epidemiological Unit of Institut Pasteur de Madagascar , for ethics committee support, and the  Andoharanofotsy community  (mayors, heads of fokontanys) and  Dr Lys Hélène Rahantanirina  for help with household participant inclusion. Computational work was performed on the  CIRAD HPC data centre of the SouthGreen bioinformatics platform  (http://www. southgreen. fr/).