dataesr/scientific-paragraphs-categorization huggingface dataset:
Statistical analysis Statistical analyses were performed using the SAS version 9. 3 software package and R version 3. 0. 2. The outcome of interest was death due to melanoma; survival time was calculated from the date of diagnosis to the date of death or last follow-up. Outcome results were stratified by disease stage. The effect of sex and age at diagnosis on death due to melanoma was evaluated two ways. First, the predicted log hazards were estimated in a Cox proportional hazards model that included sex, age as a continuous variable, and their interaction. The nonlinear effect of age was modeled using a penalized smoothing spline with a pspline basis. Forty-year-old females were chosen as the reference in the graphical display of relative risk of death due to melanoma versus age  [26]. Second, stratified by the three prespecifed age groups, melanoma-specific survival was estimated separately for males and females using the Kaplan-Meier method and Cox models were fit to evaluate the association between sex and death due to melanoma.
Results From 1992 to 2011, 201,719 cases of melanoma of the skin were identified in the SEER database. Patient exclusions as defined above were for a diagnosis of melanoma in situ (n = 75,634), a history of prior cancer (n = 17,331), no pathology confirmation of melanoma (n = 519), diagnosis solely from a death certificate or autopsy report (n = 12), unknown cause of death was unknown (n = 509), and survival time of 0 months or not available (n = 1203). Our final study population consisted of 106,511 patients with invasive cutaneous melanoma (Table  1 ). Of these patients, 55. 2% were male and 44. 8% were female. Of the melanoma cases identified in females, the greatest number of cases (44. 8%) was identified in the postmenopausal group, followed by the premenopausal (36. 0%) and perimenopausal age groups (19.
Discussion Many studies have found a female survival advantage among patients with melanoma which is independent of differences in detection or diagnosis. As no biological rationale for this advantage has been fully identified, we analyzed melanoma-specific survival between males and females for different stages of disease and different age groups to explore whether there might be an association with hormonal status. Although previous studies using the SEER database have suggested a female survival benefit in patients with melanoma of the head and neck and in non-Hispanic patients under the age of 40, neither of these studies analyzed survival in regards to age and tumor stage as was done in this study  [8, 27]. Our results confirmed the female survival benefit among patients treated for early stage melanoma, namely localized (stage I and II) and regional (stage III) disease; however, not for patients with distant (stage IV) disease.
Our results seem contradictory from a recently reported analysis of three large European clinical trials showing that females with distant disease maintained a survival benefit compared to male patients  [7]. While both our study and the European study looked at patients over similar time periods, we used the SEER database and included patients who received any treatment for distant disease, whereas the previous study looked only at patients who received one of four possible chemotherapies, all of which included an alkylating agent such as dacarbazine or temozolomide. Their results may have been confounded by the fact that women respond better to both dacarbazine and temozolomide compared to men  [28, 29]. Similar to our findings, the female survival advantage seemed to decrease in patients with higher metastatic tumor burden  [7].
Since immune checkpoint agents have only recently been FDA approved for melanoma, it is unlikely that patients taking immune checkpoint inhibitors are represented in this study. With more patients being treated with these therapies, it will be important to look for sex differences in survival and side effect profiles in this population. We are limited in that our dataset only allowed us to evaluate age and not actual menopausal status to address the role of menopause in mediating melanoma survival. Additionally, hormone use, patient comorbidities, treatment preferences and other possible factors that influence survival were unavailable with the SEER database. Due to the fact that the AJCC staging system was only implemented into registries in 2003, we elected to use the SEER historic stage for all patients.
We performed additional analyses regarding the association between sex and death due to melanoma for localized and regional disease patients stratified by melanoma characteristics such as Breslow depth, histopathological subtype, and anatomic site. These limitations should be weighed against the strengths of the SEER including population-based data, referral bias elimination, detailed tumor information and large sample size to adequately power analyses. Nevertheless, we believe that this study provides a rationale for further studies investigating hormonal-and sex-based differences in the outcome of malignant melanoma and the effect of sex on response to melanoma therapies. In summary, this study utilizes the SEER database to study the female survival advantage not only in localized and regional melanoma, but also in patients presenting with distant disease.
Material The material for the present study was collected at various Indo-Pacific localities in a series of shallow water expeditions to New Caledonia  (Expedition Montrouzier -1993) , the Loyalty Islands  (Atelier Lifou -2000) , Vanuatu  (SANTO 2006)  and Papua New Guinea  (PAPUA NIUGINI 2012 , KAVIENG 2014). This core dataset was supplemented by molecular-grade specimens obtained in 2008 in the Central Philippines (Cebu-Bohol area) from bulk lumun-lumun nets  (Seronay et al. 2010) , and in the Society Islands in the course of the Moorea Biocode Project (http://mooreabiocode. org/). Live specimens for molecular analysis collected before 2012 were anaesthetized in an isotonic solution of MgCl 2 and fixed in 96% ethanol. Specimens collected in later expeditions were processed with a microwave oven: the living mollusks in small volumes of sea water were exposed to microwaves for 7-12 seconds, depending on the specimen size.
A set of COI and 16S raphitomid sequences accessed from GenBank was used to root the tree and assess affinities of the Hemilienardia ocellata species complex. Phylogenetic analyses were performed using MrBayes  (Huelsenbeck et al. 2001) , running two parallel analyses, each consisting of six Markov chains of 20 000 000 generations with a sampling frequency of one tree each 1000 generations, with a chain temperature of 0. 02. Parameters of the substitution model were estimated during the analysis (6 substitution categories, a gamma-distributed rate variation across sites approximated in four discrete categories and a proportion of invariable sites). A different model of substitution was applied for each codon position of the COI gene. Trees from the first 5 000 000 generations (25% of the total number of generations) were discarded as burn-in prior to the construction of consensus trees.
Acknowledgements Most molecular material in this paper originates from shore-based expeditions conducted by  MNHN  and  Pro-Natura International  as part of the Our Planet Reviewed programme. Funders and sponsors include the  Total Foundation , the  Prince Albert II of Monaco Foundation , the  Stavros Niarchos Foundation , and the  Richard Lounsbery Foundation. We are thankful to  Gustav Paulay  (FLMNH) and  Chris Meyer  (USNM), who provided sequences of the specimens  BMOO 17147  and  BMOO 10646  sampled in the course of the Moorea Biocode Project; and to  Jean Letourneux  (Tahiti), who contributed Hemilienardia specimens from the  Society Islands , including the holotype of H. pardus sp. nov. We are thankful to  Baldomero 'Toto' Olivera  ( University of Utah ) for providing access to the lumun-lumun material sampled at Panglao Island in 2008.
We also thank  Yuri Kantor  ( IPEE RAS ) for the radula preparation of Hemilienardia ocellata. We are also grateful to  Catherine Rausch  (SEM facility, MNHN) and  Dr. Jiri Kucerik  ( University Landau ) for their assistance while working with SEM and ESEM. The authors also thank  Virginie Héros ,  Barbara Buge  and  Julien Brisset  for their help in curating the specimens. This project was partly supported by the  Service de Systématique Moléculaire  ( UMS 2700 CNRS-MNHN ), by the  CONOTAX  project, funded by the  French ANR  (grant number  ANR-13-JSV7-0013-01 ), and by a grant from the  Russian Science Foundation  ( RSCF 16-14-10118 ).
Extended X-ray absorptionf ine structure (EXAFS) Ag K-edge (25. 510 KeV) EXAFS spectra were collected at the Dutch-Belgian Beam Line (BM26A-DUBBLE) at the European Synchrotron Radiation Facility (ESRF). [67] The energy of the X-ray beam was tuned by ad ouble-crystal monochromator operating in fixedexit mode using aS i( 111) crystal pair. T he samples were measured in ac losed-cycle He-cryostat (Oxford Instruments) at 80 Kt om inimize the noise induced by the thermal Debye-Waller factor. E XAFS spectra were collected in fluorescence mode using a9 -element Ge detector (Ortec Inc. ), whereas reference spectra of the metallic Ag foil were collected at liquid nitrogen in transmission mode using Ar/He-filled ionization chambers. The EXAFS spectra were energycalibrated, averaged and further analysed using GNXAS (the details about data analysis are reported in the SI file).
These parameters were estimated using an iterative non-linear regression procedure. The initial parameter estimates were obtained by the procedure described in the next section. The Residual Sum of Squares (RSS) between the theoretical and the experimental data was set as the objective function to be minimized: RSS = n ∑ i=1 C exp,i -C theo,i 2 (21) where n refers to the considered experimental data set. For given initial conditions, the MATLAB subroutine "ODE15S" was used to solve the system of ordinary differential equations. Then, the optimum kinetic parameters were determined by minimizing the objective function, using the MATLAB subroutine "LSQCURVEFIT" (Levenberg-Marquardt). The parameter estimation was performed by following a built-in option, i. e. , by using the last estimation result as a starting point for the next one.
Acknowledgments: This work has been performed, in partnership with the SAS PIVERT, within the frame of the  French Institute for the Energy Transition (Institut pour la Transition Energétique (ITE) P. I. V. E. R. T. www. institutpivert. com)selected as an Investments for the  Future ("Investissements d'Avenir "). This work was supported, as part of the Investments for the Future, by the  French Government  under the reference  ANR-001-01.
Metabolomics Central metabolites are mostly polar. Therefore, to better understand the connection between primary and secondary metabolism in glandular trichomes, nontargeted profiling for polar and semipolar metabolites was performed separately using two liquid chromatography-mass spectrometry (LC-MS) methods and one gas chromatography-mass spectrometry (GC-MS) method (see Methods). Unless indicated, all metabolomics data discussed below showed significant fold changes based on pairwise t testing at a significance level of P < 0. 05. For details, see Supplemental Data Sets 1 to 3.
Intermediates of Secondary Metabolite Precursor Pathways Are Overrepresented in Trichomes Since GTs of LA4024 and LA1777 in particular produce terpenoids from both the mevalonate (MEV) and the 2-C-methyl-D-erythritol 4-phosphate (MEP) pathways, metabolites of these pathways were measured, when possible. 3-Hydroxy-3-methylglutaryl-CoA, an intermediate of the isoprenoid biosynthesis via the MEV pathway, also showed increased levels in the trichomes of both species (2. 5-fold [LA1777] and 4. 3-fold [LA4024]) versus leaves (Supplemental Data Set 3). In LA1777, intermediates of the MEP pathway showed up to 7-fold higher levels in trichomes than in leaves (Supplemental Data Set 3) and are major contributors to the group separation between leaves and trichomes of both species (Figure  3A ). Correspondingly, signals for cytidyl nucleotides, which are required for this pathway  (Caspi et al.
Transcriptomics, Proteomics, and 13 C-Labeling To correlate our metabolomics data with gene expression, we performed transcriptomic and proteomic analysis on the same samples. The transcriptomics data were generated with a customdesigned microarray based on RNA-seq data that were produced for this project (see Methods). We report quantile-normalized transcriptome data and proteome data of biological triplicates of isolated trichomes and trichome-free leaves (Supplemental Data Set 5). Unless indicated, all data discussed below showed significant fold changes at a significance level P < 0. 05. A global overview of the relative transcript and protein levels in trichomes and trichome-free leaves with regards to cellular metabolism is provided in Figure  4  (transcriptomics of LA1777) and Supplemental Figures  6  and 7  (transcriptomics and proteomics of LA4024 and proteomics of LA1777).
GTs possess chloroplasts. This raises the question of whether carbon fixation takes place in these cells and, if so, to what extent it contributes to the carbon supply of the GTs or if they depend on leaves as their main carbon supplier. To answer these questions, we examined our transcriptomics and proteomics data. First, analysis of the transcriptome data of genes involved in sucrose degradation showed that several cell walls and cytosolic invertases as well as sucrose synthases were significantly (P < 0. 05 with t test statistics) overrepresented in trichomes compared with leaves (Figure  5 ). This is particularly clear for sucrose synthases where the cumulative expression of the two major isoforms is 7. 5 and 7. 4 times higher in GTs in LA1777 and LA4024, respectively. Conversely, the cumulated expression of invertase inhibitors is 10.
Both at the transcript and protein levels, enrichment analyses revealed strong leaf-specific overrepresentation of signals within the MapMan ontology groups 1. 2 PS-photorespiration and 1. 3 PS. CBB-cycle (Supplemental Data Set 6). Furthermore, transcripts of carbonic anhydrase showed leaf-specific expression and higher protein abundance in leaves than in trichomes (LA1777, 2. 8-fold; LA4024, 8. 5-fold, P < 0. 05). The color scale (bottom right hand corner) corresponds to log 2 -fold changes for trichome versus trichome-free leaves with red being significantly overexpressed in trichomes and blue overexpressed in leaves (P < 0. 05, Fisher exact t test). White squares: log 2 -fold changes between 21 and 1 or t test, P > 0. 05. Paralleling lower ADP-glucose levels in GTs, glucose-1-phosphate adenylyltransferase, a unidirectional starch biosynthesis enzyme, showed significantly lower transcript (2-and 3-fold) and protein (13-and 57-fold) levels in GTs of both species compared with their leaves (Figure  7 ; Supplemental Data Set 5).
Accordingly, high expression of genes and proteins of the MEV and MEP pathways as well as high levels of metabolic intermediates of these pathways could be measured (Supplemental Data Set 3). In LA1777 GTs, we note the particularly high levels of methylerythritolcyclodiphosphate (MEcPP), an intermediate of the MEP pathway, which supplies precursors for the highly abundant sesquiterpene carboxylic acids produced in this species (Figures 3; Supplemental Data Set 3). Since the genes of both the MEV and MEP pathways are overexpressed in GTs, exchange of isoprenyl diphosphate precursors between compartments is unlikely but cannot be excluded.
Detailed chromatography and mass spectrometry parameters are provided in Supplemental Table  3 , Supplemental Table  4 , and Supplemental Data Set 9. For analysis of volatile metabolites, surface extracts were collected from six leaflets of ;5 cm length by adding 2 mL n-hexane and shaking for 1 min. The hexane was transferred to a clean tube and centrifuged at 16,000g for 90 s to remove debris. The hexane extract was then directly injected in the GC.
Metabolite Profiling Detection Approach, Data Matrix, and Data Normalization Nontargeted ion detection in LC-MS was achieved using an Acquity UPLC (Waters) and a TripleTOF 5600 mass spectrometer using the software Analyst 1. 6 TF (Sciex). Hydrophilic metabolites were separated by ion pairing chromatography (Supplemental Table  3 ), and semipolar metabolites were separated by reverse-phase UPLC  (Balcke et al. , 2014). TOF-MS 1 mass features were assayed between 65 and 1250 D simultaneously with an array of nontargeted QToF-MS 2 scan experiments by sequential window acquisition of all theoretical fragment-ion spectra (SWATH)-QToF-MS/MS  (Hopfgartner et al. , 2012). During the latter, the transmission range for precursor ions in the Q1-quadrupol was set for 20 ms to mass windows of 33 D and was incremented from m/z = 65 to 1250.
Simultaneously, CID fragmentation was acquired in relation to each SWATH transmission window. Thus, compromising between Q1 dwell times and MS 2 spectra purity, LC-SWATH-MS/MS measurements allow for rapid assessment of MS 1 and MS 2 spectra with cycle times of below 1 s. In total, LC-SWATH-MS/MS resulted in 8308 MS 1 distinct mass/retention time features with reliable CID fragmentation (3833 aqueous phase; 3475 from the organic phase). Out of all LC-MS features, we assigned the structure of 243 metabolites by comparison to the retention time, exact mass (MS 1 ), and CID fragmentation pattern (MS 2 ) of authentic standards (Supplemental Data Sets 1 to 3). All data presented were normalized to dry weight. Since secondary metabolites of GT contribute significantly to the dry weight of GTs, which is not the case in leaves, normalization based on dry weight to compare different plant organs may bias the conclusions made.
Therefore, other normalization approaches were tested including normalization to the total nitrogen content thought to represent the total pool of proteins and nucleic acids. Based on this normalization, however, similar trends were observed and we chose to present the data normalized to dry weight. If authentic standards were not available, we predicted the metabolite identity or affiliation to a class of secondary metabolites by exact mass, isotopic distribution of carbon in MS 1 spectra, CID fragmentation patterns, and the plausibility of the metabolite appearance and retention time in the chromatogram of aqueous or organic extracts. All LC and MS parameters and a list of used authentic standards are given in Supplemental Data Sets 1 to 3 and 9, and Supplemental Tables  3  and 4. Volatile metabolites were measured from 1 mL of the hexane supernatant by GC-MS on a Trace GC Ultra gas chromatograph coupled to an ISQ mass spectrometer (Thermo Scientific).
Peptide and Protein Identification and Quantification Peptide spectral matches (PSMs) were generated with Mascot software v2. 4. 0 from Matrix Science linked to Proteome Discoverer v1. 4 (PD) from Thermo Fisher Scientific. A signal-to-noise threshold of 1. 5 was used to filter ion signal peaks from MS full scans. The International Tomato Annotation Group (ITAG) release 2. 3 of the tomato proteome database amended with common contaminants (34,727 sequences; 11,956,401 residues) was searched with a precursor ion tolerance of 7 ppm, a fragment ion tolerance of 0. 8 D, enzyme setting trypsin, two tolerated missed cleavages, and carbamidomethylation of cysteine as a fixed modification. The family-wise PSM error rate was controlled via the false discovery rate (FDR/q-values) using the target/decoy database model for estimating false positive PSMs with the target decoy PSM validator module in PD.
Quantitative Real-Time PCR First-strand cDNA from three biological replicates was synthesized from 150 ng DNase-treated total RNA using a mix of oligo(dT)18 and random hexamer primers with the ProtoScript II First Strand cDNA Synthesis Kit (New England Biolabs). Samples were then prepared for the Fluidigm FLEXsix chips according to the manufacturer's manual, and RT-qPCR was performed in technical triplicates on a Fluidigm Biomark HD system. qPCR primers for the target genes were designed using the Primer3 program  (Koressaar and Remm, 2007; Untergasser et al. , 2012) , and sequences can be found in Supplemental Table  1. Data were analyzed using the Fluidigm Real Time PCR Analysis Software v. 4. 1. 2, and relative expression to the control gene serine/threonine-protein phosphatase 2 (Solyc05g006590) was calculated using the 2 (DCt) method  (Livak and Schmittgen, 2001).
Thereafter, these biological replicates were further divided into three aliquots of 25 mg dry weight each, which were extracted and measured independently as technical replicates. The plant material was kept frozen throughout the entire procedure and stored overnight at 225°C to let the dry ice and liquid nitrogen evaporate. Further storage occurred at 280°C. Metabolite extraction was performed as described above. Each pool was extracted in triplicate, resulting in hexuplicate determinations. For LC-MS/MS analysis of the aqueous extraction phase by ion pairing chromatography, a special multiple reaction monitoring method was used where isotopolog isoforms of selected metabolites were recorded using a Sciex 6500 QTRAP and the software Analyst 1. 7 (Sciex) (Supplemental Table  4 ).
Metabolomics Data Peak quantification of known compounds by area was done using the software Multiquant 3. 0 (Sciex). Retrospective extraction of m/z and retention time features from untargeted LC-TOF-MS 1 runs was performed using the software MarkerView 1 (Sciex). PCA and PLS analysis on dry weight-normalized data was conducted using SIMCA 13. 0. 3 (Umetrics). For this, each individual metabolite signal of interest was first divided by the average of the corresponding signal in the leaf samples of LA1777. Then, the data ratio was log 10 transformed and finally Pareto-scaled. This way, up-and downregulated signals of any intensity are normally distributed but relative changes between trichome and leaf are emphasized. We arbitrarily chose GT of LA1777 to normalize all data. R2X[1] is the cumulative sum of squares of the entire X that can be explained by principal component 1 (X = log-normalized peak heights relative to LA1777 leaf matter).
ACKNOWLEDGMENTS We thank  Gerd Hause  for assistance with electron microscopy ( Biozentrum, Martin-Luther Universität Halle-Wittenberg ) and  Mario Bauer  at the  Helmholtz-Centre for Environmental Research  for providing access to the Biomark HD system. We thank  Michael Hahn  and coworkers of  Elektrochemie Halle  for the collaborative development of a prototype for 13 C-phytolabeling. This work was funded in part by the  Deutsche Forschungsgemeinschaft  (Grant  TI 800/1 ) to A. T.
DATA SOURCES For each species of interest, we initially used a custom script to download data with permission from the USDA GRIN germplasm database. Where there were multiple mass measurements for one accession, these are summarized as the arithmetic mean, so that each datum represents a single accession. Where there were insufficient data to allow a comparison, seed accessions were ordered and weighed. Seed crops were largely obtained from GRIN, except for mung bean (Vigna radiata (L. ) R. Wilczek), which came from the Australian AusPGRIS collection. Additional sources of seed crop data and materials are listed in Tables  1  and 2. Data and seeds of root crops were sourced from: r The USDA GRIN/NPGS database (http://www. ars-grin. gov/ npgs/). r IPK Gatersleben (http://gbis. ipk-gatersleben.