dataesr/scientific-paragraphs-categorization huggingface dataset:
Across models, extinction was set to zero, either constant or linearly covarying with time or temperature. We subsequently ranked models according to their AIC values. We also independently explored dynamics of diversification using the program BAMM 40 using two independent runs (Supplementary Methods). Temporal dynamics of bioclimatic diversification were visualized by plotting the climatic disparity through-time  72  , as well as by calculating the absolute values of standardized independent contrasts of climate values across the phylogeny and regressing it against the associated node ages  73. Reporting summary. Further information on research design is available in the Nature Research Reporting Summary linked to this article.
Acknowledgements We are grateful to numerous students, field assistants and technicians who supported field and laboratory work, and to  G. Jones  for useful comments on the manuscript. This study was supported by the  Deutsche Forschungsgemeinschaft (DFG)  to M. V. and  J. M. ( VE 247/11-1/MU 1760/9-1 ), and to L. R. in the framework of the  "TaxonOmics" priority program  ( VE 247/16-1 -HO3492/6-1 ). J. G. -P. and I. I. were supported by  Juan de la Cierva  fellowships from the  Spanish 'Ministerio de Economía y Competitividad'  ( FJCI-2014-20380  and  IJCI-2016-29566 ), D. S. by the ' Rita Levi Montalcini' program  for recruitment of young researchers at the  University of L'Aquila, M. A. C. by project  NORTE-01-0145-FEDER-000007 , B. S. and D. B. M. by the  US-National Science Foundation Emerging Frontiers program  ( EF-1241848 ), J.
Data availability RNA-Seq data are available from the Sequence Read Archive (SRA Bioproject PRJNA543749), DNA sequences from GenBank (MN015052-MN015359, MN030176-MN030252), and phylogenetic datasets, microCT scans, and physiological experiment raw data in Figshare (DOIs: https://doi. org/10. 6084/m9. figshare. 8150690. v1/ https://doi. org/10. 6084/m9. figshare. 8866271. v1/https://doi. org/10. 6084/m9. figshare. 8863520. v1). The source data underlying Fig. 2b -e and Supplementary Fig. 17a, b  and Supplementary Fig. 13  are provided as a Source Data file.
2 (Fig. 2 22 Fig. 2Associations between environmental temperature, physiology, and molecular substitution rates of lacertids. a Time-calibrated phylogeny derived from partitioned ML analysis of the combined dataset for 262 lacertid species. Colors represent character state reconstruction for yearly hours >30 °C of the species' ranges computed from an occurrence record database. b-d Scatterplots among T pref and IWL, and root-to-tip path (a proxy for molecular substitution rate) against a bioclimatic variable (yearly hours >30 °C) derived from distribution range information (all phylogenetic regressions significant; fitted regression lines calculated using a phylogenetic linear model, see main text and test statistics in Supplementary Information). e Plot of R 2 vs. slope clues for regressions of root-to-tip paths vs.
Data collection Data were collected through three sessions of fieldwork in February 2017, August/September 2017 and March 2018. The sample of interviewed producers was defined at the beginning of the first fieldwork. We first selected six of the twenty-three municipalities where producer associations were located in order to obtain interviews from producers who were members of the four different associations. The municipalities are São José dos Ausentes and Bom Jesus for the APROCAMPOS association; Jaquirana for the APROJAC association; São Francisco de Paula for the APROSÃOCHICO association and Lages and Painel for the APROSERRA association. The sample was defined thanks to the help to the extension agents of the six municipalities. We chose the extension services because it is the only institution which knows most of the producers as it is the only one which reaches them direct on the farm.
Computational methods Kinetic modeling was implemented in Wolfram Mathematica 9 software. The rate constants were defined as functions of the fractional free volume f, and the reactions of the photopolymerization mechanism were expressed as a set of differential equations, which was numerically solved with the NDSolve function  [84]. Conversion was directly calculated with the values of the acrylic double bond concentration [C=C] at zero and t time (Eq. 4) and Rp was calculated after numerical resolution with Eq. 3. Conv (%) = [C=C] 0 -[C=C] t [C=C] 0 × 100 (4).
Comparison with the experiment The analysis of divertor power load footprint of pellet-triggered and spontaneous ELMs on the outer divertor target plate for the JET shot 84690 is reported in [Frigione 2015]. This analysis was performed with the aid of a fast resolution infra-red (IR) camera. The time resolution of this instrument was 100-300 µs, depending on the view area, while the spatial resolution on the region of interest was 1. 6mm  [Eich 2011 , Balboa 2012]. The IR camera is located at a toroidal angle of 90 o from the pellet injection system (the angle coordination is defined as the clockwise direction from the top view of the tokamak) as shown in Fig. 21. There are two infrared diagnostics (KL9B, KL3B) available in JET [Balboa 2012] but for this particular experiment only one of them provided good quality data for the analysis, and additional comparison using the two cameras can be put as part of the future work.
Acknowledgement The work of S. F. is supported by a  Ramón y Cajal grant  from the  Spanish Ministry of Economy and Competitiveness  ( RYC-2014-15206 ). This work has been carried out within the framework of the  EUROfusion Consortium  and has received funding from the  Euratom  research and training programme 2014-2018 and  2019-2020  under grant agreement No  633053. The views and opinions expressed herein do not necessarily reflect either those of the  European Commission. The author thankfully acknowledges the computer resources of  PRACE (Partnership for Advanced Computing in Europe)  and  RES (Spanish Supercomputing Network) at MareNostrum  and the technical support provided by  Barcelona Supercomputing Center , and the support from  Marconi-Fusion , the  High Performance Computer at the CINECA headquarters in Bologna (Italy)  for its provision of supercomputer resources.
Bacteroidetes were shown to be differentially impacted depending on host sex, resulting in higher abundance in males and lower abundance in females after DE-71 exposure. This, associated to an increase of Firmicutes in exposed males led to a decreased Firmicutes/Bacteroidetes in males while the ratio increased in females. Functional profiling of metagenomics data highlighted reduced bacterial activities associated to metabolism of vitamins, carbohydrates, lipids and aromatic compounds in both sexes while protein metabolism was increased. Host physiological status in the intestine was analysed through measurement of biomarkers for neural signalling, epithelial barrier integrity, oxidative stress and detoxifying capacity in the intestine. Substantial changes in biomarker responses were observed in intestines from males exposed while no significant effects occurred in females.
SERS Activity of 4-Mercaptobenzoic Acid (4-MBA) For the SERS measurement, 10 µ L of the samples were coated on a silicon wafer (~1 cm 2 ). The 4mercaptobenzoic acid solution (4-MBA solution, 10 μM concentration, and 10 μL quantity) was prepared and drop casted on a silicon wafer and then dried in room temperature. These stock solutions were gradually diluted with de-ionized water to obtain various concentrations of analytes. A confocal Raman spectrometer (WITec alpha 300RA) with a 532 nm excitation wavelength was for SERS measurements of hence prepared samples. The SERS data were collected over the span of 200-2000 cm -1 with 10 s as an integration time. The relative SERS enhancement capabilities of the Au-GO nano-hybrids were measured using 4-mercaptobenzoic acid (4-MBA) as the probe molecule, which is highly Raman active and adsorbed on the surface of these hybrid nanostructures.
SERS Activity of 4-Mercaptobenzoic Acid (4-MBA) For the SERS measurement, 10 µL of the samples were coated on a silicon wafer (~1 cm 2 ). The 4-mercaptobenzoic acid solution (4-MBA solution, 10 µM concentration, and 10 µL quantity) was prepared and drop casted on a silicon wafer and then dried in room temperature. These stock solutions were gradually diluted with de-ionized water to obtain various concentrations of analytes. A confocal Raman spectrometer (WITec alpha 300RA) with a 532 nm excitation wavelength was used for SERS measurements of hence prepared samples. The SERS data were collected over the span of 200-2000 cm -1 with 10 s as an integration time. The relative SERS enhancement capabilities of the Au-GO nano-hybrids were measured using 4-mercaptobenzoic acid (4-MBA) as the probe molecule, which is highly Raman active and adsorbed on the surface of these hybrid nanostructures.
Acknowledgements This perspective piece was conceived by participants at the UV4Plants 2nd Network Meeting in Bled, April 2018 and builds on discussions arising with the participants in that meeting. Financial support was provided by: the  Academy of Finland decision 304519  and  266523  to TMR;  Ministerio de Economía y Competitividad of Spain (MINECO)  and  Fondo Europeo de Desarrollo Regional (FEDER)  Project  CGL2014-54127-P  to JM-A; the  Polish National Science Centre  grants  UMO-2016/22/E/NZ3/00326  to AKB and  UMO-2017/25/B/NZ3/ 01080  to JŁ; bursaries from UV4Plants and the  Doctoral Programme in Plant Science of the University of Helsinki  to CCB and NR;  Deutsche Forschungsgemeinschaft (DFG)  project  359552155  to SN; the  Region Haute-Normandie GRR-TERA SCALE ,  UFOSE  Project to MP;  Ghent University and The Research Foundation Flanders (FWO ,  G000515N ) to FV; and  Science Foundation Ireland  project  16-IA-4418  to MAKJ.
Routine microbiological analysis was negative for all samples. Genome sequencing, assembly and annotation of Clostridium neonatale isolates Five C. neonatale strains-all from Marseille and isolated in a previous work-were sequenced and analysed  [7]. Four were NEC-associated isolates (NEC25, NEC26, NEC32, NEC86) and one was from a control neonate (C25). Strains were cultured on 5% Columbia sheep-blood agar (Becton Dickinson®, USA) at 37°C for 48 h under anaerobic conditions before DNA extraction using an EZ1 DNA Tissue Kit (QIAGEN, Germany). Genomic DNA was sequenced with MiSeq Technology (Illumina Inc. , San Diego, CA, USA) using the paired-end applications. Strain NEC86 was additionally sequenced by MinION technology (Nanopore, Oxford, UK)  [12, 13]. SPAdes software was used for NEC86 reads assembly obtained from both sequencing methods  [14].
Reads of the other C. neonatale genomes were mapped against the NEC86 dataset using the CLC genomics workbench 7 (Qiagen Inc. , Valencia, CA, USA). Coding DNA sequences (CDSs) and annotation were procured using Prokka software  [15]. Finally, sequenced genomes were deposited in the European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), under accession numbers: NEC25 (UWJD01000001-01000003), NEC26 (UICU01000001-01000003), NEC32 (UICW01000001-01000003), NEC86 (UICR01000001-01000003), and C25 (UICQ01000001-01000003) (Table  2 ). Further analysis and comparison were conducted by introducing genome sequences from two strains isolated from a Canadian NICU (LCDC99A005: GCA_001458595. 1 and LCDC99A006: GCA_002553455. 1)  [8, 11].
Design of specific qPCR for Clostridium neonatale detection As previously performed for the detection of C. butyricum  [3] , we designed a specific qPCR targeting the rpoB gene of C. neonatale. First, we verified that a unique copy of the rpoB gene was present in the C. neonatale genome (see above). Second, these sequences were aligned with those of four pathogenic species using MEGA7 software  [16]. Other Clostridium genomes included in this analysis were C. butyricum E4 str. BoNT E BL5262 (GCA_000182605. 1), Clostridium botulinum A str. (GCA_000017025. 1), Clostridium perfringens ATCC 13124 (GCA_000013285. 1) and Clostridioides (Clostridium) difficile QCD-66c26 (GCA_000003215. 1) as an outgroup at the class level (Clostridia). Primers and probe were designed to detect specifically the C.
Statistical analysis Statistical analysis was performed using SPSS® statistics 2016 (IBM, NY, USA). Mean and standard deviation were used to describe continuous variables. Percentage and number of events were used for quantitative variables. The Student t-test or Mann-Whitney U test were used to perform two-group comparisons for quantitative variables. The χ-square (Mantel-Haenszel) test was used to perform two-group comparisons for qualitative variables, or the Fisher exact test was used when the expected count was <5. A multivariate analysis using logistic regression was performed to identify independent risk factors for NEC. Variables clinically relevant and associated (p < 0. 10) with NEC in univariate analysis were used in the model. A p value < 0. 05 was considered statistically significant.
Draft genome-based and core-genome phylogeny For draft genome-based phylogeny, only mapped genomes were included. Scaffolds were concatenated, and aligned using the MAFFT software  [18]. For core genome analysis, a dataset comprising seven genomes was generated. Orthologous proteins were obtained from ProteinOrtho software using the following parameters: identity 50%, coverage 60% and E-value 1. 10 -10. CDSs of core genes were inferred from the pangenome, then concatenated and aligned using a Python script. The phylogenetic trees were generated using the maximumlikelihood method within PhyML  [19]  and edited by Tree-Graph 2 software  [20]. BLAST was used to identify haemolysin (A, B, C), β-haemolysin sequences, dlt operon (dlt A, B, C, D) and the clusters of orthologous groups (COG) identification (E-value 1e -03 , coverage 0,7 and identity percentage 30%).
However, the classic CGA is time-and resource consuming and as such is not feasible for every patient. Screening tools such as the G8, validated on 1,435 patients  16  , have been developed to identify patients who may benefit from CGA. In addition, the value of the G8 as a predictive tool has been demonstrated for survival  16 17  and suggested for FD (using univariate analysis)  18. Consequently, we decided to evaluate the importance of FD in terms of outcome and to consolidate data on the predictive value of G8 at the beginning of treatment. We first evaluated, by selecting early deaths as the targeted event, whether FD is a major determinant of the outcome. We then searched for predictors of FD, including G8 among other clinical and biological factors routinely available for oncologists, but voluntarily excluding CGA.
MATERIALS AND METHODS The study population comprised of patients aged ≥70 years, scheduled to receive first-line chemotherapy for various types of cancer (colon, pancreatic, stomach, ovarian, bladder, prostate, lung, non-Hodgkin lymphoma [NHL], or cancer of unknown primary origin). Twelve centers across France participated in this study. Additional details can be found in Hoppe et al. Journal of Clinical Oncology 2013. Full clinical staging was performed according to routine clinical practice depending on each cancer type, and patients were classified according to the usual prognostic factors including Eastern Cooperative Oncology Group (ECOG) performance status (PS)  19. Comorbidities were collected using the Cumulative Index Rating Scale-Geriatric (CIRS-G) validated in oncology  20 21. Basic clinical (age, sex, tumor site, tumor extension) and biological (platelets count, creatinine clearance, albumin levels, C-reactive protein [CRP], neutrophil count) data were prospectively recorded for each patient and classified as below and above normal value.
05). For FD analysis, prognostic factors studied for univariate analysis included the same factors and G8 result (abnormal ≤ 14 or normal >14). Variables significant in the univariate analysis at the 20% level were included in the logistic multivariate model. We constructed the final model using a backward selection approach. The final model was adjusted for age and sex. We reported odds ratios (ORs) with 95% confidence intervals (CIs) for statistically significant associations (P value <0. 05). We performed all analyses using SAS software (version 9. 3, SAS Institute, Cary, NC).
We decided to focus on ADL and to document it as early as the second course of chemotherapy, with a small threshold (0. 5 point). Indeed, our objective is to document FD early enough to allow the referring physician to adapt treatment and avoid complications. Early FD is defined here as an independent predictor of early death in cancer patients, which validates it as a pertinent outcome measure for further clinical trials  35 36 37. In Kenis et al. study, the univariate analysis parameters included CGA, factors associated with FD in ADL were baseline IADL dependency and abnormal nutritional status (MNA-SF ≤ 11). Our data are consistent with these findings. In our study, we chose to assess only routinely available clinical and biological factors in order to be highly reproducible in clinical practice.
Acknowledgments We thank  Marianne Fonck ,  Jean-Frédéric Blanc ,  Joel Ceccaldi ,  Yves Imbert ,  Laurent Cany ,  Jérôme Dauba ,  Nadine Houédé ,  Anne Floquet ,  Marie-Noëlle Fabry ,  Alain Ravaud , for patients' recruitment in the study. We thank  Dr. Ravi Nookala , of  Institut Bergonié  for the medical writing service.
No OS benefit was seen for PVT patients, with an OS disfavoring SIRT (RR of 1. 19), even in the SARAH trial. 15 It should, however, be emphasized that response rate and tolerance was significantly better with SIRT. 15, 16 e results of a fourth randomized Phase III study, namely the STOP-HCC study (NCT01556490), comparing glass microspheres associated with sorafenib versus sorafenib alone are still awaited and should be made available in the course of 2019. Several parameters possibly related to trial failure have been discussed in the meantime, such as absence of dosimetric endpoints and inclusion of too-severely advanced patients. 18 The ITT approach used is similarly a matter of debate, given that excessive lung or digestive shunting are recognized contra-indications rather than ITT failures, with an abnormally high ITT failure rate in the SIRT arm (between 26 and %, depending on the studies).
13 ] [65]  Two systematic reviews looked at the use of conventional PDT against other therapies. A Cochrane Library systematic review searched databases up to March 2011, identifying 83 RCTs covering 18 AK therapies, including PDT. 66  Whilst the primary outcome 'participant complete clearance' significantly favoured four field-directed topical treatments compared to vehicle or placebo, it favoured the treatment of individual AK lesions with PDT compared to placebo-PDT with ALA using blue light, ALA using red light, and MAL with red light. ALA-PDT was also significantly favoured compared to cryotherapy. Based on investigator and participant evaluation, imiquimod and PDT resulted in better cosmetic outcomes than cryotherapy and 5-fluorouracil. A further systematic review performed in 2013 undertook to compare the evidence of the effectiveness of PDT compared with other therapies, restricted to RCTs with at least 10 participants.
Mitochondrial calcium release through VDAC1 mitochondrial channel and mPTP directly induced Schwann cell demyelination via MAPK and c-Jun activation. Decreasing mitochondrial calcium release through VDAC1 silencing or TRO19622 blocking prevented MAPK and cJun activation and demyelination. VDAC1 opening with Methyl Jasmonate induced these cellular mechanisms in absence of nerve injury. Taken together, these data indicate that mitochondria calcium homeostasis through VDAC1 is instrumental in the Schwann cell demyelination process and therefore provide a molecular basis for an anti-demyelinating drug approach.
CARS imaging and Image Analysis Four days after MJ injection or nerve crush, animal were sacrificed and their sciatic nerves were collected, washed by PBS and fixed for 1h in 4% PFA solution at room temperature. All CARS images were obtained as described previously  (37)  with a two-photon microscope LSM 7 MP coupled to an OPO (Zeiss, France) and complemented by a delay line (53). A ×20 water immersion lens (W Plan Apochromat DIC VIS-IR) was used for image acquisition. At least 3 wide-field images were acquired per nerve and per condition. For each image, the number of myelin ovoids and the percentage of degenerated fibers were counted using ZEN software (Zeiss).
Cell culture and transfection Mouse Schwann cells MSC80 (ExPASy, CVCL_S187) were grown in DMEM (Dulbecco's modified Eagle's medium) (Gibco Life Technologies) supplemented with 2 mM L-glutamine, 100 U/ml -1 penicillin/streptomycin and 5% (v/v) heat-inactivated fetal bovine serum (all supplements were from Invitrogen). Cells were maintained at 37°C in an atmosphere of 5% CO2, and were passaged when they were 80-90% confluent, twice a week. Five 15 cm dishes of 70 -80 % confluent mouse Schwann cells were separately transfected with 30 μg of pLKO. 1-puro vector containing five commercial VDAC1 shRNA (Sigma-Aldrich, sh1#TRCN0000012388, sh2#TRCN0000012389, sh3#TRCN0000012390, sh4#TRCN0000012391 and sh5#TRCN0000012392) using 80 μl of Lipofectamine 2000 (Invitrogen) and 1,5 ml of Opti-Mem (Gibco Life Technologies).
6E. Data are represented as mean ±SD. Statistical significances were determined using a two-tailed Student's t-test. n= 5 (No Crush, Cont sh), 4 (Crush, Cont sh) and 4 (Crush, VDAC1 sh) mice. G-Representative CARS images of sciatic nerves collected and fixed by a 4% PFA solution in non-injured control animals (Control), in animals 4 days after crush nerve injury and after vehicle (Crush + vehicle) or TRO19622 (Crush + TRO) treatment or in animals 4 days after injection of MJ in the sciatic nerve (No Crush + MJ). Scale bars= 20M. H-The number of ovoid per field (left) and the percentage of demyelinated fibers per field (right) were measured on the CARS images. Data are presented as mean ±SEM. n=5 (Crush + vehicle), 5 (Crush + TRO) and 4 (No Crush + MJ) animals. Statistical analysis shows one-way ANOVA followed by a Tukey's post hoc test.
ACKNOWLEDGMENTS We thank  H. Boukhaddaoui  ( Montpellier RIO Imaging Platform ) and the  Animal Facility of the INM  for help and technical assistance. We would like to thank  Dr. J. C. Jonas  ( Université Catholique de Louvain, Belgium ) for mito-sypHer probe,  Dr. X. Wang  ( Peking University, China ) for mito-GCaMP2 probe and  Dr G. Lenaers  for his support. This work was supported by the  European Research Council  grant ( FP7-IDEAS-ERC 311610 ) and an  INSERM -AVENIR  grant to NT and The  Neuromuscular Research Association Basel, Swedish StratNeuro program ,  Swedish Research Council  grant (# 2015-02394 ) to RC.
Image Analysis The gels were scanned after silver staining on a flatbed scanner (Epson perfection V750), using a 16 bits grayscale image acquisition. The gel images were then analyzed using the Delta 2D software (v 4. 7). Spots that were never expressed above 100 ppm of the total spots were first filtered out. Then, significantly-varying spots were selected on the basis of their Student T-test p-value between the treated and the control groups. Spots showing a p-value lower than 0. 05 were selected. The false discovery rate was controlled by a combination of approaches, including the classical Benjamini-Hochberg FDR  [59]  or the more recent Sequential Goodness of Fit approaches  [60, 61]. Global analysis of the proteomic results was carried out by the PAST statistical software  [62].