dataesr/scientific-paragraphs-categorization huggingface dataset:
The PCRs were initiated by incubating the sample at 95°C for 10 min followed by 40 cycles at 95°C for 15 s and 66 to 70°C (depending of the set of primers used) for 34 s. To check the specificity of real-time PCRs, a DNA melting curve analysis was performed by holding the sample at 60°C for 60 s, followed by slow ramping of the temperature to 95°C. Baseline and threshold values were determined by the StepOnePlus software. C T values were normalized with respect to rrnA1 mRNA (encoding 16S rRNA). The relative changes in gene expression were quantified using the Pfaffl method (32) and REST software  (33). The corresponding real-time PCR efficiency (E) of one cycle in the exponential phase was calculated according to the equation (E ϭ 10 (Ϫ1/slope) (34) using 5-fold dilutions of genomic DNA ranging from 0.
ACKNOWLEDGMENTS This work was supported by the Spanish Ministerio de Economía, Industria y Competitividad (grants BIO2013-42983-P and PCIN-2016-190 to J. F. A. ), an F. P. U. contract of the Ministerio de Educación, Cultura y Deporte (FPU13/01537 to A. D. P. ), and a contract from the Junta de Castilla y León cofinanced by the European Social Fund (to E. G. B. ). The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication. We declare that we have no conflict of interest.
Thermal behavior As a consequence of the surface modification suggested by FTIR, C. I. and zeta potential (Table  1 ) values, the particles could show very different properties, once these parameters are critically important to define particle behavior in suspension and its thermal behavior. The thermal stability of the samples was investigated by thermogravimetric analysis. The obtained thermograms are shown in Figure  4  and the related data reported in Table  2. Firstly, a higher amount of water present in the nanometric samples is observed. This can be explained by the higher surface area of this particles, providing more available -OH groups with which water molecules can interact. As suggested by contact angle measurements (Table  1 ) and FTIR, CNC-t is more hydrophobic than other nanocellulosic samples, showing a lower water content.
Acknowledgements The authors gratefully acknowledge the  Brazilian National Council for Scientific and Technological Development (CNPq)  and  "Ciência Sem Fronteiras" (CsF) program  for the financial support (PhD fellowship of M. M. ). LGP2 and LRP are part of the  LabEx Tec 21  ( Investissements d'Avenir -grant  agreement n°  ANR-11-LABX-0030 ) and of the  PolyNat Carnot Institut  ( Investissementsd'Avenir -grant  agreement n°  ANR-16-CARN-0025-01 ). This research was made possible thanks to the facilities of the  TekLiCell  platform funded by the  Région Rhône-Alpes  (ERDF: European regional development fund).
Methods The current prospective study was approved by Comit e de Protection des Personnes (No. CPP27-06 CPP de Paris -Ile de France VI, Groupe Hospitalier Piti e Salpetriere Paris, France) on 12 April 2006, and was carried out between the 2 January 2007 and 15 November 2011. All patients provided informed written consent. The study was conducted according to Good Clinical Practice standards and the Helsinki Declaration. The study has been registered (NCT00822549).
Study design This was a single centre prospective study. Patients were recruited to the study during the pre-operative appointment with the anaesthesiologist (at least 48 h before surgery). The following data were recorded: patient characteristics, including age, sex, BMI, personal history and medical treatment, ASA class. A pregnancy test was performed in women of childbearing age. Pre-operative biological measurements included haemoglobin, creatinine, liver enzymes, platelets counts, prothrombin and partial activated thromboplastin time.
This analysis was also performed separately in each period, in the PACU and on the surgical ward. The same process as above was used to obtain final multivariable models. We calculated the odds ratio (OR) and its 95% CI. Hosmer and Lemeshow's tests were performed to check the calibration of logistic models. Sensitivity analyses were also performed by excluding patients who required rescue analgesic and those who did not require morphine titration in the PACU to test whether these exclusions could change conclusions. All P values were two-tailed and a P value of less than 0. 05 was considered significant. SAS V9. 2 (SAS Institute, Cary, North Carolina, USA) was used to perform the statistical analysis.
Pain management in the postanaesthesia care unit Median VAS score on arrival in PACU was 70 (80 to 100). Morphine was titrated in 358 (89%) patients with a mean time of 25 (20 to 35) min to reach VAS score 30 or less. The mean morphine dose required in the PACU to achieve pain relief was 15. 7 AE 8. 8 mg (0. 22 AE 0. 12 mg kg À1 ). There was no significant change in cardiovascular variables (data not shown). There was failure of the morphine titration to achieve a VAS score < 30 in 97 (24%), and thus, additional analgesics were required. Ketamine was the preferred addition to the morphine regimen in the PACU (n¼94, 97% of patients requiring rescue analgesia). Morphine-related adverse events were observed in 161 (47%) patients (SPD, http://links. lww. com/EJA/A142). Table  2  depicts the concentrations of morphine, M3G and M6G at the end of intravenous morphine titration.
Acknowledgements relating to this article Assistance with the study: we thank  David Hajage  et  Said Lebbah  for their help with the statistical analysis and  Dr David Baker , DM, FRCA, ( Department of Anaesthesiology and Critical Care, Hopital Necker-Enfants Malades, Paris ) for reviewing the article. Financial support and sponsorship: support was provided solely from institutional and/or departmental sources. The study was supported by the  D el egation R egionale de la Recherche Clinique  (no. AOR050328 ;  P051035 ,  GENEDOL ,  EUD2006-002507-14 ),  Assistance Publique-Hopitaux de Paris (Paris, France ).
Statistical analysis Nonlinear curve fits for extracting vulnerability curve parameters were conducted using the NLS function in R (R Core Team, 2015). Data were tested for normality using the Shapiro-Wilk test in R. Log transformations were used to meet assumptions of normality for h s,x and k l,max,x. We evaluated bivariate trait relationships between mean values of species with Pearson productmoment correlation using the HMISC package in R. Phylogenetic independent contrasts (PICs) were calculated using the PIC function in the APE package in R. The pruned tree (Fig. S4 ) was generated in phylocom  (Webb & Donoghue, 2005) , using the stored Angiosperm tree  (Zanne et al. , 2014) ; alpha was set at 0. 05 for all comparisons. Multiple comparisons were corrected using the False Discovery Rate (FDR) method to avoid inappropriately increasing the number of null hypotheses that are wrongly rejected  (Pike, 2011).
We used an FDR of 5% to calculate FDRadjusted P-values using the Graphically Sharpened Method  (Benjamini & Hochberg, 2000). FDR-adjusted P-values are reported in the Results section, Figs 1-4, and Table  2. We ran a Principal Component Analysis (PCA) of all measured traits using the dudi. pca function in the ADE4 package in R  (Dray & Dufour, 2007). To better understand the global context of our data as compared to drier sties and to test whether there is declining cavitation resistance with increasing moisture availability, we also plotted our P 50 data vs the Xylem Functional Trait (XFT) Database  (Choat et al. , 2012)  made available via the TRY Plant Trait Database  (Kattge et al. , 2011).
The first axis accounted for 47. 8% of all variation, and was dominated by WD, h s,x , e x and other sapwood pressure-volume curve parameters (Fig. 4 ). The second axis accounted for 17. 6% more of the variation and was dominated by a x , A l : A s and midday Ψ l (Fig. 4 ). Thus, the score of a species on the first axis is a composite of sapwood pressure-volume curve parameters and WD where low scores indicate dense wood, low h s,x , high e x and high RWC tlp,x (B. prouacensis), and high scores indicate opposite traits (J. copaia) (Fig. 4 ). The second axis reflects several other traits that are orthogonal to the main axis of WD and sapwood pressure-volume curve parameters, and high scores indicate steep slopes of the xylem vulnerability curve (high a x ) and high A l : A s. Relative to the XFT Database, our P 50 values showed relatively low cavitation resistance compared to drier sites, consistent with the overall trend of decreasing cavitation resistance with increasing mean annual precipitation (Fig.
Within  the context of the XFT Database, we also show reduced cavitation resistance as annual precipitation increases across the globe. We did not find evidence of a significant relationship between maximum xylem conductivity per unit sapwood area (k s,max,x ) and xylem water potential at 50% loss of conductivity (P 50 ), indicating that the safety vs efficiency trade-off is not a strong constraint at this site. Instead, much of the variation in hydraulic traits was related to PCA axis 1, demonstrating that these species vary along an axis with strategies marked by high xylem efficiency and high capacitance on one end of the spectrum and low water potential at turgor loss point on the other. Our results show coordination between k l,max,x and k s,max,x , with sapwood capacitance at full turgor (C ft,x ), suggesting that greater connectivity of the xylem network provided by high specific hydraulic conductivity could allow greater recharge of capacitive water, a greater buffering capacity, or rapid rehydration during transient low vapour pressure deficit events, such as passing rain showers or clouds.
Moreover, the lack of the hydraulic safety vs efficiency trade-off in this study is consistent with our finding that within the context of the XFT Database, as annual precipitation increases across the globe there appears to be declining selection for physically resistant xylem (Fig. 5 ). Thus, the reduced importance of resistant P 50 values in wet forests such as Paracou places weaker constraints on the coordination between safety vs efficiency, whereas drought avoidance traits such as C ft,x show stronger coordination and play a large role in determining hydraulic strategies. Fig. 4  Principal components analysis of hydraulic parameters for 13 traits and 14 Amazonian canopy rainforest tree species from Paracou, French Guiana. Each point represents data for a single species. Our finding that Eastern Amazonian canopy tree species exhibit high C ft,x , which functions as a benefit on the low wood density end of the spectrum, raises questions about the benefits of dense wood in this ecosystem, because dense wood is not correlated with greater cavitation resistance at this site.
Acknowledgements We would like to thank  Benoît Burban  and  Jean-Yves Goret  for laboratory support,  Jocelyn Cazal  and  Valentine Alt  for skillfully climbing trees for samples,  Aurelie Dourdain  for database support, and  Clement Stahl ,  John Sperry ,  Sean Gleason ,  Todd Dawson ,  Steve Davis ,  Jos e Luiz Silva ,  Aleyda Acosta Rangel  and three anonymous reviewers for comments and discussions on the data presented. The study has been supported by the TRY initiative on plant traits (http://www. try-db. org). The TRY initiative and database is hosted, developed and maintained by  J. Kattge  and  G. Boenisch  ( Max Planck Institute for Biogeochemistry, Jena, Germany ). TRY is currently supported by  Future Earth/ bioDISCOVERY  and the  German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig.
To this end, a technique is required that fulfills three criteria: (i) comprehensive coverage of proteins engaged in a complex; (ii) compatibility with a biological system in which a trigger (stimulus) can be applied; and (iii) a quantitative readout. Therefore, we have developed a quantitative method based on TAP in cell cultures to study protein complex dynamics in Arabidopsis thaliana. Label-free quantification (LFQ) is applied to determine shifts in the levels of protein complex members in a trigger-dependent manner, thus mapping the dynamics of the protein complexes. We used the MaxLFQ algorithm integrated into the MaxQuant software  (Cox et al. , 2014). This comparison of proteome samples avoids stable isotope labeling, of which the metabolic version is somewhat restricted in plants due to very high costs or labeling efficiency issues  (Gruhler et al.
MS/MS Data Processing All raw files were processed with the MaxQuant software (version 1. 4. 1. 2)  (Cox and Mann, 2008). The derived data were searched with the built-in Andromeda search engine against the Arabidopsis thaliana forward/reversed version of the TAIR10_pep_20101214 database containing also sequences of frequently observed contaminants, including human keratins, bovine serum proteins, or proteases. Carbamidomethylation of cysteines was selected as the fixed modification, whereas variable modifications were set to oxidation and acetylation (protein N-term). Trypsin\P was selected as enzyme setting. Cleavage was allowed when arginine or lysine was followed by proline with two missed cleavages permitted. Matching between runs was enabled with a matching window time of 30 s. Relative, LFQ of proteins was selected by means of the MaxLFQ algorithm integrated into MaxQuant.
With the minimum ratio count set to 1, the FastLFQ option was enabled, LFQ minimum number of neighbors was set to 3, and the LFQ average number of neighbors to 6, as per default. Proteins identified with at least one unique peptide were retained. The false discovery rate (FDR) for peptide and protein identifications was set to 1%, and the minimum peptide length was set to 7 amino acids. Detailed MaxQuant search parameters can be found in Supplementary Table  2. The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium via the PRIDE  (Vizcaino et al. , 2016)  partner repository with the dataset identifier PXD009083.
Data Analysis After MS data processing, LFQ values from the "proteinGroups. txt" output file of MaxQuant were further analyzed in the Perseus software (version 1. 5. 3. 2). First, the reverse database hits, contaminants, and proteins identified only by modified peptides were filtered out. Then, log 2 values were taken from the LFQ intensities, whereafter samples were grouped in 'mock' and 'treatment. ' Proteins that did not contain at least four valid values in at least one group were filtered out and missing LFQ values were imputed/replaced by values from a normal distribution that were slightly lower than the lowest (log) value measured, as described  (Smaczniak et al. , 2012b; Wendrich et al. , 2017). All the imputed missing values can be found in the Supplementary Data Sheet 1. For normalization on the bait level, the intensity values from the "proteinGroups.
Quantitative TAP Reveals Changes in the SMXL7 Protein Complex Compositions To examine the dynamics of the protein complexes formed around SMXL7 and their role in strigolactone signaling, we carried out TAPs in Arabidopsis cell cultures expressing GS rhinotagged SMXL7 or SMXL7 (see Materials and Methods). After the LC-MS/MS analysis of the TAP samples, spectra were searched with the MaxQuant software and resulted in the identification of 299 proteins for SMXL7 and 347 for SMXL7. MaxLFQ was then used to quantify the identified proteins between the tested conditions over the four replicates. Further analysis was performed with the Perseus software as described  (Smaczniak et al. , 2012b). Changes in protein abundances were expressed after log 2 transformation of protein LFQ intensity values. Proteins that were not assigned LFQ values in the MaxQuant search, because their abundance was below the detection limit under that specific condition or replicate, were assigned a value based on a normal distribution centered around the lowest detection limit of the measured intensities as described  (Smaczniak et al.
, 2012b ) (Supplementary Data Sheet 1). To evaluate the reproducibility of the analysis, scatter plots were made to calculate the correlations of LFQ values between replicates. Noteworthy, consistency between replicates is crucial for downstream statistical analysis. In our experiment, the Pearson correlation coefficients for all replicate pairs ranged from 0. 765 to 0. 959 for SMXL7 and from 0. 891 to 0. 976 for SMXL7, indicating a good to very good reproducibility (Supplementary Figure  2 ). Given the fast degradation of the SMXL7 protein (Figure  1A ), TAP analysis was performed after 10 min of rac-GR24 treatment. To test the influence of this treatment, bait protein levels were compared between the conditions. The intensity of the SMXL7 protein was significantly lower in the hormone-treated samples than that in the mock samples (Supplementary Figure  3 ).
Soma-axon model We used a simple neuron consisting of a soma (20 ϫ 30 m, 6 segments) and an axon (1 ϫ 50 m, 10 segments) available on ModelDB (access number: 135839), described by  Yu et al. (2008). See Figure  8A  for sample schematics of the shape of the neuron. The simulation was controlled from Python using the Neuron-Python interface  (Hines et al. , 2009).
Linear source approximation To estimate the extracellular potentials we used the linear source approximation (LSA) method, which calculates the summed potential generated by currents originating from line sources with known sizes and positions. This method is known to be more precise than approximating the currents by point sink and sources  (Holt, 1997; Wilson and Bower, 1992). We then applied the LSA estimation to cylinders obtained from the segmentation by neuron simulator  (Hines and Carnevale, 1997). The field was calculated using the LSA implementation of Neu-ronEAP Python library  (Telenczuk and Telenczuk, 2016). In all calculations, we used an extracellular conductivity of 0. 3 Sm  (Nunez and Srinivasan, 2006). In Figure  8 , we removed the baseline from the extracellular potential by calculating an average potential in a window from 2 to 1 ms before the peak of the action potential.
Code accessibility The code for the figures of the full morphology model is deposited and available at Zenodo (DOI: 10. 5281/zenodo. 1222159). We used the full morphology model published by  Hallermann et al. (2012)  and the simplified model published by  Yu et al. (2008)  in their original form and with altered parameters, as stated where appropriate. To calculate the local field potential, we used the NeuronEAP Python library  (Telenczuk and Telenczuk, 2016).
This research was supported by the  CNRS , the  European Union  ( Human Brain  Project  H2020-720270 ), and the ( ANR-14-CE13-0003 ). M. T. was supported by  Ecole des Neurosciences de Paris  (ENP, http://www. parisneuroscience. fr/)and  DIM Cerveau et Pensée  (http://dimcerveaupensee. fr/).
First-principles calculations were performed using density functional theory as implemented in the Vienna ab initio simulation package  53. We chose the PBE functional within the generalized gradient approximation to treat the exchange-correlation interaction of electrons 54. To consider the long-range van der Waals interaction between atomic layers, we adopted the semi-empirical dispersion-corrected D3 scheme proposed by Grimme  55. O 2 molecules were adsorbed onto an eight layers surface slab of tetragonal CsPbBr 3 containing 80 atoms with a vacuum gap of 20 Å. The energy cutoff for the plane wave basis was chosen to be 500 eV and Brillouin zone integration using the Monkhorst-Pack scheme with 7 ×.
Acknowledgements This research is supported by the  Singapore Ministry of Education  through the  Academic Research Fund  under Projects  MOE2016-T2-1-054 , Tier  1-RG105/16 , Tier  1-RG92/15 , and Tier 1-RG189/17 (S). H. Z. thanks the  National Science Fund for Distinguished Young Scholars of China  ( 61604074 ). J. W. and C. H. S. thank the  National Research Foundation (NRF) Competitive Research Programme (CRP)  award #  NRFCRP13-2014-04.
Purpose Metastatic neuroendocrine tumors (mNETs) are rare, heterogeneous tumors that present diagnostic and treatment challenges, with limited data on the management of mNETs in clinical practice. The present study was designed to identify current diagnostic and treatment patterns in mNET patients treated in the US community oncology setting. Methods Patient-level data was collected from medical records of adults with mNETs from the Vector Oncology Data Warehouse, a comprehensive US community oncology network database. Results Of the 263 patients included (median follow-up, 22 months; range, 0. 1-193. 9), 30. 4% (80/263) had intestinal tumors, 11. 0% (29/263) had pancreatic, and 58. 6% (154/263) had tumors of other or unknown location. Progression-free survival (PFS) from the start of first-line therapy differed significantly by tumor grade (log rank P = 0.
Patients and Methods In this retrospective study, we examine information from The Vector Oncology Data Warehouse (VODW), a comprehensive cancer patient database that includes electronic medical record and billing system data for patients who were treated in a US community oncology setting. Patients from the VODW who were ≥ 18 years of age at the time of diagnosis of mNET were eligible for inclusion. Following institutional review board approval of the study protocol, demographic, medical, treatment, and select patient symptom data were collected from the VODW. Clinical Research Nurses (CRNs) verified eligibility and extracted information onto case report forms that were entered into a secured data management system for analysis. Dates of death were recorded from the clinical record or the linked Social Security death index data.
6%) from this analysis are notable, as both are important factors in the treatment and management of mNETs  [12]. Similar rates of undocumented tumor differentiation have been reported in community oncology networks (41. 5%)  [35] ; however, single-center institutional studies have reported lower rates ranging from 3. 4 to 11%  [31, 34]. Other/unknown primary tumor locations have been reported at variable rates ranging from 11 to 39%  [29, 31, 36, 37]. Of note, 48% of patients in the Vector database did not have a documented primary tumor site reported at diagnosis; rather, these patients had a metastatic tumor site recorded at diagnosis. However, for the survival analysis, the Bother/ unknown^tumor category included both primary and metastatic tumor sites, which may have impacted the outcomes.
Acknowledgements The authors thank  MedVal Scientific Information Services, LLC  (Princeton, NJ) and  Susan Martin, PhD  and  Philip Sjostedt , BPharm of The Medicine Group,  LLC (New Hope, PA)  for medical writing and editorial assistance, which was funded by  Ipsen Biopharmaceuticals, Inc. We also thank  Susan Pitman Lowenthal, MD, MPH ,  David Cox, PhD , and  David Ray, PharmD ,  MBA, MPH  for their contributions to the study analysis and interpretation of the data. This manuscript was prepared according to the  International Society for Medical Publication Professionals' BGood Publication Practice  for Communicating Company-Sponsored Medical Research: The  GPP3 Guidelines^and the International Committee of Medical Journal Editors' BUniform Requirements for Manuscripts Submitted to Biomedical Journals.
Search-oriented conversational systems rely on information needs expressed in natural language (NL). We focus here on the understanding of NL expressions for building keywordbased queries. We propose a reinforcementlearning-driven translation model framework able to 1) learn the translation from NL expressions to queries in a supervised way, and, 2) to overcome the lack of large-scale dataset by framing the translation model as a word selection approach and injecting relevance feedback in the learning process. Experiments are carried out on two TREC datasets and outline the effectiveness of our approach.