dataesr/scientific-paragraphs-categorization huggingface dataset:
Analyses of Peru Margin iTAG Sequence Data The R1 and R2 iTAG sequences for Peru Margin were quality controlled using the Trim Galore! version 0. 3. 7 1. Default values were applied. The R1 and R2 reads that survived quality trimming were merged using FLASh  (Magoc and Salzberg, 2011). Sequence clustering at 97% similarity level was performed using uclust  (Edgar, 2010)  in QIIME pipeline  (Caporaso et al. , 2010). The taxonomic assignment of the representative sequences of each cluster was performed using BLASTN  (Altschul et al. , 1990)  against Silva 111  (Quast et al. , 2013). A heat map was generated for the two replicates of the two Peru Margin samples using the heat map function included in the OMICS module of XLStat (Addinsoft). Normalized read abundances were used for clustering of samples applying hierarchical clustering based on Euclidian distances.
Illumina Library Preparation and Sequencing For the Canterbury poly-A-enriched cDNA library preparations, paired-end 2 × 150 bp Illumina Hi-Seq sequencing was performed at the University of Delaware Sequencing and Genotyping Center (Delaware Biotechnology Institute). The Peru Margin and Canterbury Basin metatranscriptome library preparations that were successful (replicate RNA-Seq libraries for Peru Margin 6 and 95 mbsf, and replicate RNA-seq libraries for Canterbury Basin 12 and 345 mbsf, as well as a single poly-A-based library for Canterbury Basin 345 mbsf) were sent to Georgia Genomics Facility 3  for library preparations and paired-end 2 × 150 Illumina NextSeq sequencing. The metatranscriptome sequence data are deposited in the GenBank SRA accession number SRP072032 (Canterbury Basin poly-Abased library) and accession number SRP072233 (Canterbury Basin and Peru Margin RNA-seq data).
Analyses of Peru Margin and Canterbury Basin Metatranscriptome Data The R1 and R2 reads were filtered using Trimmomatic  (Bolger et al. , 2014) , which performs a "sliding window" trimming, cutting once the average quality within the window (eight nucleotides used here) falls below a threshold (set to 12). The length of the trimmed sequences was set to be at least 50 nucleotides. The trimmed reads surviving quality control were assembled into contigs using Trinity  (Grabherr et al. , 2011)  release r20140717. Metapathways 2. 5  (Konwar et al. , 2013 (Konwar et al. , , 2015) )  was used for open reading frame predictions using Prodigal  (Hyatt et al. , 2010). Functional annotation of the contigs used LAST  (Kiełbasa et al. , 2011)  against the RefSeq non-redundant database  (Pruitt et al. , 2005)  update 2014-01-18, and visualization of metabolic pathways used Pathway Tools  (Karp et al.
, 2010). Additionally for the poly-A-enriched libraries BLASTX analyses were run through the Blast2Go platform  (Conesa et al. , 2005)  using an e-value of 10 -3 and fungal taxonomy filter (fungi nr subset database). Contigs were then mapped and annotated to clusters of gene ontologies (GO) using an e-value of 10 -6 and fungal taxonomy filter (fungi nr subset database). For the taxonomic annotation of the contigs BLASTX (e-value10 -3 ) against nr and MEGAN v. 5 10 7 were used. To estimate the abundance of each transcript within a library a Burrows-Wheeler Aligner (BWA-based) version of the RPKM calculation  (Li and Durbin, 2010)  was applied as described in  Konwar et al. (2015). RPKM calculates the proportion of number of reads mapped to a sequence section normalized for sequencing depth and transcript length.
Comparison of Overall Community Metabolism in Peru Margin and Canterbury Basin Samples Metatranscriptomics have been widely used in microbial ecology as a proxy for microbial activity (e. g. ,  Frias-Lopez et al. , 2008; Stewart et al. , 2010; Damon et al. , 2012; Raychoudhury et al. , 2013). However, the extraction and sequencing of mRNA remains challenging for low biomass environments such as the deep marine subsurface. Only one study so far  (Orsi et al. , 2013a)  has used this approach to report gene expression from anoxic Peru Margin sediments up to 159 mbsf (Site 1229). Here we analyzed sediments from the same Peru Margin site as well as aerobic sediments from Canterbury Basin (Site U1352) in order to expand on those first data on subsurface gene expression for the whole community, and to evaluate whether transcript expression is distinct at comparable depths in these two very different habitats.
For this reason the reads from both replicates were combined and co-assembled for analysis. The relative transcript abundances from these combined datasets are discussed below. Transcripts assigned to hypothetical or uncharacterized proteins were excluded from downstream analysis. The number of transcripts is low but we believe that this reflects the low diversity of the subsurface. It is noticeable that the retrieved transcripts decrease with depth (e. g. , the CB 12 m b and CB 345 m a samples have similar numbers of raw reads as well as reads that survived quality control, but the assembled transcripts were 3x more in the shallow sample). Not surprisingly, transcripts encoding housekeeping genes (polymerases, ribosomal proteins, t-RNA synthetases, transcriptional regulators, translation initiation/elongation factors) were abundant in all samples.
Pili are hair-like appendages found on the surfaces of many bacteria that can not only be the attachment site of bacteriophages, but can be involved in bacterial adherence, conjugation, and movement  (Shi and Sun, 2002). Greater expression of genes for these proteins was observed in our 6 mbsf vs. 95 mbsf sediments from Peru Margin, and expression was roughly similar in shallow and deep Canterbury Basin sediment samples. Adhesin proteins -which are found on bacterial cell surfaces or appendages, facilitate attachment to other cells or surfaces and are, therefore, another sign of interactions between cells and their environment -were detected in samples from both Peru Margin depths. Collectively, these data all suggest that the heterogeneous nature of subsurface sediments may allow for cellular motility when adequate porosity exists and a sufficient supply of electron donors and acceptors permits metabolic rates that can support motility.
Eukaryote-Focused Metatranscriptome Analysis of a Canterbury Basin Sample from 345 mbsf To examine the functional repertoire of the Fungi, a poly-A targeted metatranscriptomic approach was employed. Fourteen poly-A enriched metatranscriptome libraries were constructed and sequenced in total (Supplementary Table  S1 ). Out of these, only one (Canterbury Basin 345 mbsf sample) produced high quality sequences and will be discussed below. For this sample the de novo assembly using 5,250,985 quality-trimmed reads generated 11,389 contigs with an average length of 1,705 bp. Nine hundred and thirty sequences were unambiguously assigned to fungal taxa, indicating that fungi appeared metabolically active in this deep subseafloor sample. As fungal databases improve, a larger fraction of our "unassigned" sequences may be possible to assign to fungi.
Nonetheless, a wide diversity of fungal transcripts involved in different functions was represented in the dataset based on Gene Ontology term analysis (Supplementary Tables  S4-S6 ). Preliminary analyses indicated that GO term levels 2 and 3 were not informative enough. Final analysis was therefore conducted at the GO term level 4. The three descriptive ontologies "cellular components, " "molecular function, " and "biological process" were analyzed (Figure  4A ). Gene expression from fungal communities was mainly assigned to metabolic and biosynthetic processes, e. g. , amino acid, fatty acid, peptide, and ATP biosynthetic processes, but also responses to stress, and cell and membrane functions, e. g. , ergosterol biosynthetic process, cell wall and septum formation. These results provide further support for the notion of fungal activity in the deep subseafloor at record depths, extending the previously known depth limits of eukaryotic functions from 159 to 345 mbsf.
Nitrate reduction has been reported to occur in the deep subseafloor with Alphaproteobacteria and Betaproteobacteria as predominant actors  (Orsi et al. , 2013b). Those authors argued that the resulting nitrite was probably reduced by fungi, Gammaproteobacteria, and Firmicutes. Indeed, transcripts involved in nitrite reduction were reported in our poly-A enriched Canterbury Basin metatranscriptome dataset, supporting the idea of syntrophic interactions in the deep subseafloor. These results are also supported by previous studies that report the potentially active role of fungi in denitrification within marine sediments  (Jebaraj et al. , 2010; Mouton et al. , 2012). Fungal expression of genes for biosynthesis of the secondary metabolites asperthecin, penicillin, and emericellamide was detected.
FUNDING This work was supported by  Deep Carbon Observatory  subaward # 48550  to VE, and  NSF Center for Deep Energy Biosphere Investigations (CDEBI)  grant  OCE-0939564  to VE and GB. GB was also supported by the European project  MaCuMBA (Marine Microorganisms: Cultivation Methods for Improving Their Biotechnological Applications ,  FP7 , Grant agreement number  311975 ). This is CDEBI contribution number  323.
Flow cytometry assay HEK 293 cells were grown on 100-mm Petri dishes. About 10 6 cells were harvested and resuspended in Annexin V binding buffer. Then cells were incubated with Annexin V-FITC (BD Biosciences) and propidium iodide (PI) (Biolegend) for 15 min in the dark at room temperature. Cells were washed and fixed with 3. 7% formaldehyde solution for 10 min and subjected to a flow cytometric analysis using FACScan flow cytometer (Becton Dickinson). Results were analyzed with FCS Express 5 software (De Novo Software).
Statistical analysis Results are expressed as mean 7 SEM of at least 3 independent experiments. Comparisons between different treatments have been analyzed by a one-way ANOVA test. Values with po0. 05 were considered statistically significant for a post-hoc Tukey's test. All statistical tests were done using the software Graph-Pad Prism version 6. 0. Degrees of significance are indicated in the figure captions as follow: *po0. 05; **po0. 01; ***po0. 001, ****po0. 0001, n. s¼ not significant.
Cytotoxicity of CdCl 2 on HEK 293 cells Cytotoxicity of CdCl 2 on HEK 293 cells was assessed by MTT assay (Fig. 1 ). The estimated CC50 value (cytotoxic concentration that reduced cell viability by 50%) was 30 mM for 24 h of treatment. The relative cell viability evaluated by Trypan Blue staining was similar to that obtained by MTT assay (data not shown). The administration of high doses of CdCl 2 (Z40 mM) caused cytotoxicity and reduced dramatically cells metabolic activity and viability. At concentrations lower than 10 mM, there was no significant difference in terms of cell viability and cell morphology between the non-treated control cells and the CdCl 2 treated cells. Thus, concentrations of CdCl 2 up to 10 mM were considered non-cytotoxic and were used for further experiments.
Effect of apoptosis on SINV growth To determine if apoptosis inhibition could contribute to the reduction of SINV growth, cells were exposed to ZVAD-fmk, a pancaspase inhibitor. Treatment with ZVAD-fmk (30 mM) protected cells from SINV-mediated cells death (Fig. 2A ) through reduction of caspase 3/7 activity (Fig. 2B ). SINV progeny production in supernatant of HEK 293 cells were examined after treatment with ZVAD-fmk 2 h post infection. No significant reduction of viral progeny was observed in the presence of ZVAD-fmk (30 mM) (data not shown). These results suggested that inhibition of apoptosis does not impact SINV growth in HEK 293 cells.
As a matter of fact, shortening and extension in the retroarc sector may vary not only in time (i. e. , with major "cycles" of mountain building and orogenic collapse, respectively) but also in space, due to the variable transmission of horizontal compressive stress away from the orogen. Low-temperature (low-T) thermochronological systems are ideally suited for reconstructing thermal histories of rocks in the uppermost part of the crust because they record time and rates of cooling related to exhumation of the first kilometers of the crust. Presently, a rather extensive apatite fission track and apatite (U-Th)/He (AHe) dating database is available for the axial part of the orogen  [Thomson et al. , 2010; Guillaume et al. , 2013; Folguera et al. , 2015]. However, such type of data are completely lacking from the broken foreland area.
About 30% of these faults-arguably syndiagenetic in origin-preserve kinematic indicators in the form of striae and/or mineral (dominantly calcite) shear fibers on slickenside surfaces. When slickenlines were present, their pitch has been measured together with sense of shear. These data (Figure  6c ) have been used to obtain information on the strain field controlling the development of the fault set, using the P-B-T technique  [Angelier and Mechler, 1977]. The P-B-T method, based on plane orientation, slip orientation, and kinematics of each single fault, furnishes the three principal axes of strain: P (direction of maximum shortening), T (direction of maximum stretching), and B (intermediate axis, orthogonal to the P-T plane). In order to calculate the orientation of each strain axis, this method uses a common defined fracture angle θ for all fault-slip data.
P-B-T axes were determined using FaultKin v. 7. 4. 3 software  [Marrett and Allmendinger, 1990; Allmendinger et al. , 2012] , which utilizes the right dihedra geometrical method of paleostress analysis of  Angelier and Mechler [1977]  and  Pfiffner and Burkhard [1987]  (for small-offset faults such as those analyzed in this study, and accepting the Wallace-Bott hypothesis that the slip is parallel to the resolved shear stress  [Wallace, 1951; Bott, 1959] , the obtained strain axes can be assumed to approximate infinitesimal strain and therefore to represent paleostress principal axes). The analysis unraveled an extensional tectonic regime characterized by a subvertical P axis and a subhorizontal, SW-NE trending T axis (Figure  6d ). Bilmes et al. , 2013; Orts et al. , 2015; Echaurren et al.
After He extraction, Nb baskets were placed into a single-used polypropylene vials. Apatite grains were dissolved for 3 h at 70°C in a 50 μL HNO 3 5 N¬ solution containing a known content of 235 U, 230 Th, and 149 Sm, and additional 50 μL HNO 3 5 N and then filled with 0. 9 mL of ultrapure MQ water. The final solution was measured for U, Th, and Sm concentrations by quadrupole inductively coupled plasma (ICP)-quadrupole mass spectrometry (CCT Thermo-Electron at LSCE (Gif/Yvette; France). The analysis was calibrated using external age standards, including Limberg Tuff and Durango apatites. A mean AHe age of 16. 0 AE 1. 4 Ma and 31. 1 AE 2. 1 Ma has been measured for the Limberg Tuff and yellow Durango apatite, which are in agreement with published data (i. e. , 16. 8 AE 1. 1 Ma and 31. 0 AE 1.
0)  [Kraml et al. , 2006; McDowell et al. , 2005]. An error at 10% at 1σ should be considered, reflecting the sum of ejection factor F T correction and standard dispersion. The HeFTy software  [Ketcham, 2005]  was used to generate an inverse thermal modeling based on AHe data of four representative samples (G07, G13, G15, and G22), in order to test plausible thermal histories. We chose three samples belonging to the broken foreland area, for which there is a complete lack of low-T thermochronological studies, and one from the Precordillera. Two to three AHe replicates were used for each modeled sample. The RDAAM model of  Flowers et al. [2009]  was adopted for the calibration of kinetic parameters, and  Ketcham et al. [2011]  was considered for the approximation of stopping distances. However, similar results would have been obtained by the use of the damage and annealing model from  Gautheron et al.
, 2009; Flowers et al. , 2009; Djimbi et al. , 2015]. Based on the AHe data, it may be inferred that the samples from the foreland area stayed in the HePRZ since at least ~110 Ma, with a final exhumation phase at ~30-50 Ma. More information could be extracted from thermal modeling performed using the HeFTy software. Figure  7  shows the possible scenarios of thermal paths experienced by samples G07 and G15 (Mamil Choique Fm. ), G13 (Cañadón Asfalto Fm. ), and G22 (North Patagonian Batholith). The first two samples consist of Paleozoic basement rocks that, based on stratigraphic constraints  [Lizuaín and Silva Nieto, 2011] , probably experienced burial since ~250 Ma. These two samples show similar path envelopes characterized by a long residence in the HePRZ (between 40 and 80°C), and possibly below it, followed by slow exhumation since ~120 Ma (Figures  7a  and 7c ).
Acknowledgments Thoughtful and constructive reviews by  Bruno Scalabrino  and an  Anonymous Referee  and the useful comments by Associate Editor  M. Jolivet  and Editor  C. Faccenna  are thankfully acknowledged. Funding for this work was provided by the  University of Padova (Progetto di Ateneo 2015 ,  CPDA158355 ) to  E. Savignano  and  M. Zattin ; the  University of Naples Federico II (Fondi Ricerca Dipartimentale)  to  S. Mazzoli ; and the  Universidad Nacional de Río Negro  ( PICT-FONCyT 2013-2916 ,  PIP-CONICET 330 ,  U. N. Comahue ) to  M. Arce  and M. Franchini. We are grateful to  Pan American Silver  for the precious collaboration and fruitful discussion of data and for allowing the survey activity in the Navidad area. S. Boesso ,  R. Pinna , and  L. Bordier  are thanked for AHe sample preparation, analysis of  U-Th chemistry , and for assisting during ICP-MS measurements at LSCE ( Gif-sur-Yvette ).
Chemistry-Emission Coupled Model The purpose of this section is to describe the chemistry-emission coupled model for 67P. We use the spherically symmetric expansion model of  Haser [1957]  to estimate the number densities n i (r) of the ith parent species at a cometocentric distance r from the nucleus. The water production rate from the surface of 67P near perihelion has been estimated at 4 × 10 27 s -1 for July 2015, while the velocity of the escaping volatiles has been measured to be 700 m s -1 using the data of the Comet Pressure Sensor, part of the ROSINA experiment. We consider the primary volatile elements detected by the ROSINA/DFMS spectrometer, H 2 O, CO 2 , CO, and O 2. The average CO and CO 2 abundances relative to water have been estimated at 25% and 8. 3% for the month of July 2015.
The different total cross sections relative to water, carbon monoxide, carbon dioxide, and molecular oxygen are taken from the PHIDRATES database (see http://phidrates. space. swri. edu/) which is based on the work of  Huebner and Mukherjee [2015]. The solar UV flux is mostly absorbed in the spectral range between 60 and 100 nm with an absorption average of about 12. 5% between the top of the atmosphere and at 10 km above the comet, with a maximum at 90 nm with 17% of absorbed flux. Above 100 nm, the solar UV flux is mostly absorbed until 130 nm mainly because of the presence of water and O 2 with an average absorption of about 5%. a The photolysis rate coefficients are given at the top of the atmosphere and the differences between the top of the atmosphere and at 10 km altitude are indicated in parentheses.
The production rates coefficients for an atomic state a, i. e. , O( 1 D) or O( 1 S) from the photodissociation of the considered species i, i. e. , water, carbon dioxide, molecular oxygen, and carbon monoxide, are computed using the following equation: k a (z) = ∫ 𝜆 𝜎 i a (𝜆)F(𝜆, z)d𝜆 (2) where  i a (), are the partial cross sections leading to the photoproduction of the atomic states O( 1 D) and O( 1 S), also taken from the PHIDRATES database for water, carbon dioxide, and carbon monoxide. There is still, however, an ongoing discussion regarding the O( 1 S) production through the photodissociation of water. For the sake of comparison, we follow here the approach used by  Bhardwaj and Raghuram [2012] , assuming a 0. 5% yield at 121. 6 nm. Regarding the production of O( 1 S) from CO 2 , the considered partial cross section is obtained by multiplying the total cross section of CO 2 by the yield recommended by  Huestis et al.
[2010]. Regarding the production of O( 1 S) from the photodissociation of CO, we also follow the approach from  Bhardwaj and Raghuram [2012]  since no partial cross-section data are available in the PHIDRATES database. The computed production rate coefficients at the top of the cometary atmosphere are summarized in Table  1 , for a heliocentric distance of 1. 35 AU. With the number densities prevailing in 67P's atmosphere, the solar flux is attenuated in such a way that there is a difference of about 2. 7-3% between the production rate coefficients from water at the top of the atmosphere compared to 10 km altitude. The solar UV flux is more absorbed for wavelengths between 70 and 90 nm, leading to a more pronounced decrease of the production rates from CO 2 and CO of about 8% and 12%, respectively.
The presence of O 2 is taken into account here for the first time in such modeling. The photodissociation of O 2 follows three principal channels for the wavelengths of interest. Above 177 nm, only the O( 3 P) ground state is produced. For the wavelength range from 115 nm to 177 nm, the photoproducts are O( 1 D) and O( 3 P) and the production yield is taken from  Lee et al. [1977]. Below 115 nm down to 90 nm, photodissociation results in O( 1 S) and O( 3 P), and the recommended cross section from the ATMOCIAD database is used  [Gronoff et al. , 2011]. This set of cross section, available upon request, has been widely used within an aeronomic context for modeling the Mars airglow  [Gronoff et al. , 2012a [Gronoff et al. , , 2012b]] , in a cometary studies context for the comet Siding Spring  [Gronoff et al.
G/R ratio profile for 67P from 10 to 10 4 km for a line of sight crossing the projected cometocentric distance according to different cross section data sets for CO 2 , using PHIDRATES (black) and ATMOCIAD (red). The G/R ratio profile is calculated with a water production rate of 4 × 10 27 s -1 for 25% CO, 8. 3% CO 2 , and 4% of O 2 abundances relative to water at 1. 35 AU heliocentric distance. dioxide in our model. The first is the one used in the previous section. As a second cross-section data set, we consider the recommended values from the ATMOCIAD database. The O( 1 S)/O( 1 D) ratio goes from 0. 53 using the values provided in Table  1  to 6. 98 using the cross sections from the ATMOCIAD database. The latter ratio is computed using photoreaction rates of 3. 97 × 10 -7 s -1 and 5. 68 × 10 -8 s -1 for O( 1 S) and O( 1 D), respectively, for a distance of 1.
35 AU. Using such parameters, the computed emissions are estimated at 639 R and 571 R for O( 1 D) and O( 1 S), respectively, for z = 10 km. At this distance, the G/R ratio increases up to 0. 89, compared to 0. 73. Figure  9  displays the projected G/R ratio from 10 km to 10 4 km, using both cross-section data sets for a solar UV flux corresponding to an F 10. 7 index of 104 (black lines). The lack of knowledge regarding the CO 2 cross sections thus leads to an important uncertainty on the computed G/R ratio and emphasizes the need for accurate CO 2 cross-section measurements.
The variability compared to quiet solar conditions can reach more than 1000% in the XUV spectral range between 0 and 20 nm, 100% in the EUV (20-120 nm), and 10-20% in the FUV (120-200 nm). Figure  10  displays the different computed G/R ratios according to the different solar activity levels. We still consider both cross-section data sets regarding the production of O( 1 D) and O( 1 S) through the photodissociation of CO 2. The ratio generally increases for higher solar activity. With the ATMOCIAD database as inputs, the G/R ratio is of 1. 55 for z = 10 km, while it is 1. 08 using the PHIDRATES database for the X-17 solar flare. Observations of the red-doublet and green line emissions during a powerful solar flare could eventually help to constrain the reaction rates of the photodissociation of CO 2.