dataesr/scientific-paragraphs-categorization huggingface dataset:
Microbiome Composition among Treatments We investigated the impacts of the different treatments performed in the present work on the taxonomic composition of both prokaryote and fungal communities. Among the prokaryote dataset, the proportion of archaea over bacteria varied according to the soil considered, i. e. , Manziat versus Serail (Table  S1 , Figure  3A ). Archaea constituted, on average, 10. 9% of the total sequences in Manziat, while they represented only 8. 7% of the sequences in Serail soil. More precisely, 14 phyla of archaea and bacteria represented 98. 95 to 99. 64% of the total sequences across the samples, with minor classes grouped among the minor phyla. Proteobacteria were the most abundant phyla. They were slightly enriched in Serail soil, where they accounted for 27. 28 to 28.
55, 18. 56, 11. 99, and 4. 26% of the sequences in the Serail dataset, respectively, compared to only 26. 13, 1. 94, 9. 05, and 3. 51% of the sequences in Manziat soil (Figure  3B ). Using discriminant analysis, we found clear differences in the most abundant fungal genera (>0. 04% of total sequence abundance) between Manziat and Serail soil (Figure  4B ). Some genera were more specifically associated with one soil type, such as uncultured Pyronemataceae, uncultured Ascomycota, and Solicoccozyma, which were mostly retrieved in Manziat soil, whereas Fusarium, Colletotrichum, and Oculimacula were more specifically associated with Serail soil. A clear shift in fungal abundance was observed between unplanted soil and lettuce planted soil, evidencing a rhizosphere effect. In addition, some genera were found in abundance after procyanidin amendment, such as Podospora in Serail soil and Solicoccozyma in Manziat soil.
On the other hand, the C/N ratio and/or N tot were related to the distribution of Agaricomycetes and Saccharomycetes, while Pezizomycetes were related to sand. Other groups such as Thaumarchaeota or Chloroflexi were related to OM and/or OC content. Figure  6. Canonical correspondence analysis (CCA) between nine physicochemical characteristics measured during the experiment (sand, silt, clay, organic carbon (OC), organic matter (OM), total nitrogen (N tot ), C/N ratio (C/N), calcium (Ca), and cation exchange capacity (CEC)) and the most abundant prokaryotic and fungal phylum/classes (>5% of sequences in their respective dataset). Bac: bacteria; Arc: archaea; F: fungi.
Prediction of Fungal and Prokaryotic Ecological Functions Unsurprisingly, among the 3551 KEGG categories inferred from the prokaryotic dataset, numerous categories were different between soils (Manziat versus Serail). Specifically, 56 categories were statistically enriched in Manziat soil, while 55 categories were enriched in Serail soil based on an LDA score >2 (Table  S3 ). Among the 56 categories related to Manziat, five were related to nitrogen metabolism, including nifHDK (nitrogen fixation) and nrfA (nitrite reductase), while two in Serail were related to the N cycle, namely narG/narZ (nitrate reductase) and nxrA (nitrate oxidoreductase). In Serail, it should be noted that three categories were related to the biosynthesis of siderophores and nonribosomal peptides and two categories were related to multidrug efflux pump, which were absent in Manziat soil.
Supplementary Materials: The following are available online at https://www. mdpi. com/article/ 10. 3390/microorganisms9071406/s1, Table  S1 : Effect of lettuce and procyanidins amendment on 16S rRNA gene abundance in Manziat (A) and Serail (B). The analysis was performed using a Permutational Multivariate Analysis of Variance (PERMANOVA), Table  S2 : Relative abundance of Archaea and Bacteria in bulk soil in Manziat and Serail (BSM and BSS, respectively), for Lettuceplanted conditions without and with procyanidins amendment in Manziat soil (L0M and LPM) and in Serail soil (L0S and LPS), Table  S3 : Prokaryotic functional inference and KEGG assignment. Statically enriched functions in Manziat versus Serail were determined so as LDA score > 2, Table  S4 : Global network statistics for microbial networks from the root-adhering soil of lettuce plants unamended and amended with procyanidins, Figure  S1 : Rarefaction curves for each sample were calculated on prokaryotic 16S rRNA gene (A) and fungal ITS datasets (B), Figure  S2 : Trophic mode of fungal community retrieved form amended and unamended Manziat and Serail soils with procyanidins.
Acknowledgments: This work was supported by  Auvergne-Rhône-Alpes region  ( ARC 2016-2019 ) for thesis subvention for W. Galland and the  French National Research Agency  ( ANR-18-CE32-0005  DIORE). Field experiments were performed at the  Serail Experimental Station. Soil physicochemical analysis was performed at  Centre Scientifique Agricole Regional, Ceyzeriat, 01250 Ain, France , and high-throughput sequencing was performed by  Biofidal (Vaulx -en-Velin, France  (http://biofidal-lab. com) (accessed on  27 June 2021 ).
Topographic data We collected or computed all digital elevation models available from HRSC, CTX, and HiRISE stereopairs. HRSC Digital Terrain Models (DTMs) were downloaded from the ESA Planetary Science Archive server  (Gwinner et al. , 2010). CTX DTMs were produced by using the NASA Ames stereo pipeline  (Beyer et al. , 2018)  in the MarsSI platform  (Quantin-Nataf et al. , 2018). HiRISE DTMs were produced with the SOCET SET software following the method presented in the work of  Kirk et al. (2009). We were able to produce complete coverage of the landing site study area with CTX DEMs and images and, by the end of the landing site selection process, almost complete coverage of the study area with HiRISE images. HiRISE DEMs covered a much smaller part of the study area. The DTMs used in the article are listed in Supplementary Table  S2.
Deciphering the formation environments for such diverse Noachian rocks will fulfill the requirement of the ExoMars Rover. Moreover, the scientific targets are well distributed within the large landing site ellipse. Apart from the exposures of the dark resistant unit, wherever the rover will land, it will be landing on the exposures of Noachian deposits related to the aqueous activity. More than 70% of the landing site ellipse corresponds to the clay-bearing unit, as mapped by spectral criteria with both CRISM and OMEGA data  (Carter et al. , 2016). Given that the probability of landing is higher at the center of the landing ellipses, the chance of landing on clay-rich material is even higher, as the ellipses are centered on a large exposure of clay-bearing material. Clay minerals are known to provide catalytic surfaces that can facilitate the synthesis of some organic compounds needed for the emergence of life (e.
Funding Information The research leading to these results has received funding from the  European Research Council  under the European Union's  Seventh Framework Program  (FP7/2007-2013)/  ERC  Grant agreement No. 280168 ,  ANR  project  ANR-18-ERC1-000  and from the  French space agency (CNES). Lu Pan  was supported by  Marie Sklodowska-Curie Actions  grant agreement No. 751164. Peter Gringrod  and  Joel Davis  were supported by the  UK Space Agency  grants  ST/ L00254X/1 ,  ST/J005215/1 ,  ST/L006456/1 ,  ST/R002355/1 ,  ST/S005064/1 , and  ST/T001747/1. Matthew Balme  and  Peter Fawdon  were supported by  UK Space Agency  grants  ST/L00643X/1 ,  ST/R001413/1 ,  ST/R001383/1 , and  ST/ V001965/1.
Author contributions: All the authors have accepted responsibility for the entire content of this submitted manuscript and approved submission. Research funding: G. L. acknowledges financial support by  ANR  through the  NANOPAIR  project ( ANR-18-CE92-0043 ). C. D. A. and G. L. acknowledge the  National Research Council Joint Laboratories program , project  SAC. AD002. 026 (OMEN). CDA acknowledges the  Italian Ministry of University and Research (MIUR)  through the  PRIN  project  NOMEN  ( 2017MP7F8F ). I. S. acknowledges the french RENATECH network.
Bacterial Isolates and Clinical Data Two to five monomicrobial urine cultures (named I-V) of P. aeruginosa (regardless of the level of leucocyturia) were prospectively and consecutively collected from seven patients (A-G) over a 27-month period (from June 2016 to August 2018), with up to five isolates per sample (1-5), representing a total of 108 isolates (Table  1  and Figure 1 ). Isolates from the first sample collected were considered as early isolates while those from samples obtained at the subsequent times were considered as late isolates. Clinical data were collected from computerized medical and biological records of the hospital in parallel with the collection of the urinary isolates. According to the French regulation on observational database analyses, this study did not need specific informed consent requirements; it was registered by the Directorate of Clinical Research and Innovation of the Rouen University Hospital Centre under the number 2018/413/OB.
(2004) , using KMA software version 1. 2. 12  (Clausen et al. , 2018)  with default settings 3  , and the online database (updated on 2019-03-18) of the Center for Genomic Epidemiology  (Larsen et al. , 2012). Phylogenetic analysis of the 108 Illumina and PacBio assemblies produced by SPADES was performed using Parsnp software version 1. 2  (Treangen et al. , 2014)  with default parameters using the A-I-1 strain as reference. The iTOL software  (Letunic and Bork, 2019)  was used to visualize and edit the phylogenetic tree and identify phylogenetic clusters (bootstrap of 100) inside the P. aeruginosa urinary population. Illumina reads were aligned against every PacBio reference sequences using Snippy software version 4. 4. 0 (available on https: //github. com/tseemann/snippy/). Clone type SNPs (ctSNPs), bounded by at least 50 exact base-pair matches on both sides, were extracted from the alignments using a custom script 4.
SNPs Analysis An intra-patient SNPs analysis was performed using Snippy software, by mapping Illumina reads to their corresponding PacBio reference sequence. This intra-patient mapping approach was chosen over the fast Parsnp analysis of genome assemblies (well fit for inter-patient scaled phylogenies) because it allowed a fine-scale analysis of the SNPs from raw reads, and maximized the size of the intra-patient core genomes. SNPs analysis was manually curated. When SNPs were found in all the isolates sequenced by Illumina, they were considered specific to their common PacBio reference sequence even though we cannot exclude that some were in fact artifacts due to the use of distinct sequencing approaches (PacBio vs. Illumina). Snippy called the SnpEff software  (Cingolani et al. , 2012)  to annotate and predict the effect of each mutation.
To identify the corresponding PAO1 locus tags, gene sequences from each PacBio reference genome were blasted against all PAO1 gene sequences retrieved from https://www. pseudomonas. com/. Gene sequences that with no blast hit against PAO1 were classified as "hypothetical, unclassified, unknown. " Genes where SNPs occurred were classified into functional categories using PseudoCAP available on the Pseudomonas Genome Database 6. SNPs were classified as low (e. g. , synonymous mutations), moderate (e. g. , missense mutations), and high effect (e. g. , stop gained). SNPs that were not identified in early isolates (collected from the first urine sample for each patient) but present in at least two of late isolates were further described as "late stage SNPs. " The core alignments produced by Snippy software for each patient were used to infer within-host phylogenies: Neighbor Joining trees were produced using MEGA version X  (Kumar et al.
Characterization of Genomic Deletions Genomic deletions were visualized using CGView software  (Stothard and Wishart, 2005) , based on the core alignments produced by Snippy. Deletions were also identified using KMA software version 1. 2. 12 (see text footnote 3), with Illumina reads as query and the CDS identified by pgap from their corresponding PacBio reference genome as database. The proportion of the core and accessory genome were calculated based on the core alignments produced by Snippy. To identify the corresponding PAO1 locus tags, gene sequences from each PacBio reference genome were blasted against all PAO1 gene sequences retrieved from https://www. pseudomonas. com/. Gene sequences that with no blast hit against PAO1 were classified as "hypothetical, unclassified, unknown. " The deleted genes were classified into functional categories using PseudoCAP available on the Pseudomonas Genome Database (see text footnote 6).
1% crystal violet. After 15 min of incubation at room temperature, the plate was rinsed thrice with water by submersion and dried for 2 h. Cells were washed and resuspended in 50% (v/v) ethanol. OD 590nm of the resuspended biofilm was determined and normalized to the OD 600nm of the corresponding planktonic cells. All experiments were performed at least three times. The P. aeruginosa strain PA14 was used as a positive control and fresh medium as a negative control for each experiment. All data were expressed as percent of biofilm formation relative to the positive control. Isolates forming less than 50% of biofilm compared to PA14 were considered as low biofilm-producers, whereas isolates forming more than 50% were considered as high biofilm-producers. Statistical analyses were performed by Kruskal-Wallis test on R © software (v.
Clinical Data During a 27-month period, seven hospitalized patients (A-G) with more than one urine sample positive to P. aeruginosa were included in this study (Figure  1 ). Chronic asymptomatic bacteriuria (AB) was observed for two patients (B and D) while chronic UTI was observed for one patient (C). A switch from UTI to AB (patients A and E), from AB to UTI (patient F) or successive switches from UTI and AB (patient G) were identified (Table  1 ). Of note, four patients (B, C, F, and G) required long term urinary catheterization. Six patients had urinary disorders, including benign prostate hypertrophy (C, D, G), urinary tract diversion (B, F), and kidney transplant (E). All patients received at least one antibiotic treatment during the 6 months before urine collection, and five of them (A, B, C, E, and G) also received antibiotics in the interval of their urine samples (Table  1  and Figure 2A  and Supplementary Table 2 ).
Indeed, one late isolate (D-II-1) was phylogenetically related to the early isolates, and did not share any SNP with the other four late isolates that clustered separately. Illumina reads were mapped to the corresponding PacBio reference using Snippy software. The total number of positions investigated in each intra-patient core genome is indicated. The mean number of SNPs/year (mutation rate, in square brackets) was calculated for isolates from each urine culture, based on the time elapsed since the previous urine culture. Interestingly, no mutation was detected in DNA mismatch repair genes (like mutS or mutL) but 2 SNPs were identified in genes involved in DNA replication, recombination, modification and repair (a missense SNP, Asp559Asn, in uvrA, and a nonsense SNP at position 309/530 in the gene homologous of PA1405 at locus tag H7Q90_28210).
Single nucleotide polymorphisms were identified in genes involved in virulence for isolates collected from patient D, F, and G. For D-isolates, eight SNPs were identified in genes involved in motility and adherence (fleS, fimT), in type III and VI secretion systems [exsA (nonsense SNP), icmF1, hsiG3], in ferric uptake regulator (FUR) regulon (PA2094 and PA2402), or in stringent response (antitoxin higA). For F-isolates, three SNPs were identified in genes involved in alginate biosynthesis or alginate regulation and biofilm formation [algG, algB, and mucA (nonsense SNP)]. These isolates presented a mucoid morphotype after 48 h of culture (data not shown), which could be explained by mucA inactivation (an anti-sigma factor of the algU gene involved in alginate biosynthesis). Finally, one SNP was observed in the fecI sigma factor of the FUR regulon in G-isolates.
PseudoCAP manually assigned functions A-isolates D-isolates F-isolates A-and F-isolates Percent of deleted genes per gene function are presented here. PseudoCAP functions are available on the Pseudomonas Genome Database (https://www. pseudomonas. com/). A convergent evolution by deletion was identified in a common region between A-and F-isolates. Percent of deleted genes per gene function are indicated by "A-and F-isolates. " When over than 5% of genes for a given PseudoCAP function were affected (except for "Hypothetical, unclassified, unknown" function), values were indicated in bold. the intra-patient reference sequence to limit the phylogenetic distance between isolates and the reference genome while CF studies usually use a reference sequence (P. aeruginosa DK2 or PAO1)  (Marvig et al.
Genome sharing between cancer and normal tissues might imply a similar susceptibility to chemotherapy toxicity. The present study aimed to investigate whether curative potential of doxorubicin, bleomycin, vinblastine, and dacarbazine (ABVD) is predicted by the metabolic response of normal tissues in patients with Hodgkin lymphoma (HL). METHODS: According to current guidelines, 86 patients with advanced-stage (IIB-IVB) HL, prospectively enrolled in the HD0607 trial (NCT00795613), underwent 18 F-fluorodeoyglucose PET/CT imaging at diagnosis and, at interim, after two ABVD courses, to decide regimen maintenance or its escalation. In both scans, myocardial FDG uptake was binarized according to its median value. Death and disease relapse were recorded to estimate progression-free survival (PFS) during a follow-up with median duration of 43.
Study Design The selection of studied patients exploited the database of the HD0607 trial  [2]. This study included 782 patients with histopathologic diagnosis of classic HL, aging 18 to 60 years, Ann Arbor stage IIB to IVB, measurable international prognostic score (IPS), and able to sign the written informed consent form. The exclusion criteria were: concomitant or previously treated (<5 years) neoplasia, psychiatric disorder, impaired cardiac (ejection fraction < 50%) and renal (creatinine clearance < 60 mL/min) functions, HIV or any other active uncontrolled infection, pregnancy, and uncompensated diabetes. According to the study design, all patients were submitted to staging PET/CT (baseline PET) before chemotherapy. Treatment started with two ABVD cycles (administered at standard doses) and was followed by an early PET/CT evaluation (interim PET) acquired using the same scanner of the baseline evaluation.
To this purpose, the continuous variables MTV, myocardial SUV, and psoas muscle SUV were binarized according to the 50th percentile. Since OS was only predicted by DSS at interim PET/CT, multivariate analysis was only performed considering PFS. To this purpose, all variables were tentatively included in a multivariate Cox's model by means of a step-back (backward) procedure, based on the likelihood ratio test; a p-value < 0. 15 was required for the inclusion of a variable in the model. A p-value < 0. 05 was considered statistically significant. The used statistical software was SPSS Inc. , Advanced Models 15. 0 (Chicago, IL, USA).
Study Approval We reviewed the clinical research forms of the HD0607 trial (Eudract code 2007-007168-94, Clinicaltrial. gov (accessed on 1 July 2021) identifier NCT00795613)  [2]. The protocol of the study was approved in 1 June 2008 by the Santa Croce e Carle Hospital institutional review board (identification number Emato 16). The study was conducted in accordance with the International Conference on Harmonization for Good Clinical Practice guidelines and the Declaration of Helsinki; it requested the preliminary signature of the written informed consent, and it was approved by the ethics committees of all the participating centers.
Clinical Characteristics and Follow-Up Data Among the 782 subjects included in the original database, we selected the datasets of the 86 patients with image format compatible with the software used for analysis. As shown in Table  1 , the main clinical characteristics of the population included in the present sub-analysis were representative of the entire cohort. Images with DSS 1-3 were observed in 67/86 (78%) patients, who thus prosecuted ABVD regimen. By contrast, a 4-5 DSS escalated the subsequent regimen to BEACOPP in the remaining 19 (22%) patients.
Limitations The main limitation of the present study is represented by the small number of studied patients. This was caused by the need to select images stored with a format compatible with our software. However, this technical constraint provided us with a population whose features at the enrollment were remarkably similar with respect to the original database. Likewise, OS and PFS were comparable between our study and the previous large-scale one. As a second consideration, the retrospective nature of our investigation did not permit the application of a standardized diet regiment to avoid the interference of nutritional condition on myocardial FDG uptake. However, the invariance of tracer retention in the skeletal muscles strongly indicates a negligible role of the interference of dietary regimen on measured cardiac SUV.
Nevertheless, optimizing the clinical potential of this analysis would probably need to precede all PET/CT scans in HL patients by a lipid-rich dietary regimen in order to switch off myocardial glucose consumption in a standardized fashion  [30]. A similar consideration applies to the potential interference by the intercurrent treatment with cardioactive therapies. However, criterion for study entry was the absence of cardiac disease in the clinical history, as well as the evidence of left ventricular dysfunction, thus potentially reducing the impact of this confounding factor. Accordingly, these limitations do not permit the consideration of myocardial SUV at interim PET as a parameter able to modify therapeutic planning in the clinical setting. To this purpose, reproducing this observation in a larger database would be needed.
Context. Spiral arms in protoplanetary disks could be shown to be the manifestation of density waves launched by protoplanets and propagating in the gaseous component of the disk. At least two point sources have been identified in the L band in the MWC 758 system as planetary mass object candidates. Aims. We used VLT/SPHERE to search for counterparts of these candidates in the H and K bands, and to characterize the morphology of the spiral arms. Methods. The data were processed with now-standard techniques in high-contrast imaging to determine the limits of detection, and to compare them to the luminosity derived from L band observations. Results. In considering the evolutionary, atmospheric, and opacity models we were not able to confirm the two former detections of point sources performed in the L band.
Global description The disk of MWC 758 is quite bright, hence, it is already visible in raw data and stacked images, without any ADI processing (referred as no-ADI). Subtracting the stellar residuals with the coronagraphic images of a reference star (RDI) that were obtained in similar conditions reveals the signal of the disk as close as ∼ 0. 1. Several stars were considered as references observed in the same night in the same configuration, however, here we show the one that provides the best result in terms of the detection of the disk. From these data, we measured F disk /F ≈ 0. 017 in the H2 and H3 filters integrating the disk signal between 0. 12 1 Other targets observed the same night with the same observing mode, which do not necessarily match the color and magnitude of MWC 758   (5 , top)  and narrower field of view  (1.