dataesr/scientific-paragraphs-categorization huggingface dataset:
Acknowledgments This study is co-supported by the  National Key Research and Development Program of China  ( 2017YFA0604804  and  2017YFA0604302 ) and  National Natural Science Foundation of China  ( 41475099  and  41630530 ). We thank  Sam Levis  for revising language errors in the manuscript, and  Joe Melton ,  Ruxu Lian , and  Zhongda Lin  for helpful discussions. We are also grateful to two anonymous reviewers for their valuable comments and suggestions and ERL editors for handing this paper. SPH acknowledges the support from the  ERC -funded project  GC2. 0 (694481 ) and from the  High-end Foreign Expert Programme of China  ( GDW20191100161 ). And acknowledge support from the  Helmholtz Foundation  and its  ATMO programme and Impulse and Networking fund. GL is funded by the  Deutsche Forschungsgemeinschaft (DFG, German Research Foundation ) (338130981).
Run performance was assessed and for data analyzed with the Torrent Suite Software v. 5. 10. 0 (ThermoFisher Scientific). Single-nucleotide variants and small indels were detected using the Variant Caller plug-in version 5. 10. 0. 18 with low stringency settings (threshold: 2%). The Integrative Genomics Viewer (IGV v 5. 01; Broad Institute, Cambridge, MA, U. S. A. ) was used for visual inspection of the aligned reads.
We also demonstrated that LOD ranged from 3% to 6% for the T790M mutation using a commercial DNA sample. We also assessed the LOD for the EGFR-activating mutation L858R and Del19, and found them to be, respectively, between 3% and 6% and 1% and 3% (data not shown). In our series, Idylla failed to detect 3 T790M mutations because of very low VAFs (1. 3-4%) that were well below the manufacturer's recommended assay LOD. That failure was also reported recently by Evrard et al. , who described Idylla's inability to detect T790M mutations in samples with VAFs < 5%  [9]. Finally, we found the internal Ct value to be a very good marker to check the reliability of the result. Indeed, in our opinion, because of the risk of a false-negative finding, the analysis must be considered non-interpretable for a negative result obtained with a sample having a Ct > 25.
Questionnaire Online survey was assessed from March to May 2019 through the association Santé Respiratoire France (https ://sante -respi ratoi re. com). Four pulmonologists, one sexologist, one expert patient and one psychiatrist developed the questionnaire. The following data were collected at inclusion: demographic characteristics (age, gender, marital or relationship status, occupation, living area: urban, suburban, rural), smoking history, breathlessness and exacerbations etc. ). A detailed description of the questionnaires is available in Additional file 1.
Fatigue severity scale (FSS) The FSS is a questionnaire with nine questions estimating the fatigue severity in different situations during the past week. Grading ranges from 1 (strong disagreement) to 7 (strong agreement) where the final score is the mean value of the nine items, and a score ≥ 4 is interpreted as fatigue  [16]. FSS scale has been validated in COPD  [17, 18]. Once the questionnaire was completed and tested, it was then emailed to every member of BPCO association. Followed by completion of the survey data by anonymous volunteers, to respect the clause: "strengthening the reporting of observational studies in epidemiology" (STROBE) statement  [19]. COPD was validated by a spirometry and by a physician-diagnosis.
79. We should have at least 369 subjects and we included more than 700. Qualitative variables were described in numbers and percentages. Quantitative variables were described by mean and standard deviation or median and interquartile range. Missing data are reported in the tables. Differences in clinical characteristics were assessed using chi-square tests or Fisher's exact tests, as appropriate, for discrete variables, and Wilcoxon or Kruskal-Wallis tests for quantitative variables. Relationships between different variables were examined with the Pearson correlation test. A value of p ≤ 0. 05 was considered statistically significant. The analysis of the results was carried out with Graph Pad Prism ® statistical software.
Nevertheless, respiratory or physical symptoms, such as dyspnea, cough, weakness, and reduced physical activity or fear of breathing difficulty, were reported to affect sexual activity, lowering the QoL of responders and COPD patients in general. For many patients, the libido loss triggers a sense of shame, which can reduce their self-esteem and cause depression. This study also confirms that individuals with COPD are at higher risk for developing depression  [32]  and subsequent worsening of sexual dysfunction. Although doctors are reluctant to address the topic of sexuality in practice, our data suggest that patients want their doctors to address these concerns and provide resources to them. Despite the high incidence of sexual dissatisfaction among COPD patients, only 6% had talked about sexuality with a specialist.
Dynamic light scattering (DLS) DLS measurements were acquired on a Zetasizer Nano ZS (Malvern Instruments) operating at a laser wavelength of 633 nm equipped with a Peltier temperature controller set to 25 °C. Data were collected on 50 lM protein samples in NMR buffer in 3 Â 3 mm cuvettes. Using the Malvern DTS software, mean hydrodynamic diameters were calculated from three replicates in the volume-weighted mode.
Nuclear magnetic resonance (NMR) spectroscopy NMR experiments were performed on Bruker Avance 600 or 750 MHz spectrometers, equipped with cryogenically-cooled triple resonance 1 H{ 13 C/  15  N} TCI probes and z axis selfshielded gradient coils. Data acquisition, processing, and spectral analyses were carried out in TOPSPIN 2. 1, iNMR 3. 6. 3 and CCPNmr 2. 1. 5. 2D 1 H-15 N correlation spectra of monomeric uniform  15  N nitrogen labeled aSyn and HMWAs were acquired using the SOFAST-HMQC pulse sequence on 50 lM samples dissolved in NMR buffer at 10 °C, with 1 K and 256 complex points for sweep-widths (SW) of 16 ppm and 28 ppm in 1 H and  15  N dimensions, respectively. Spectra were recorded with 32 scans and interscan delays of 60 ms. Processing was done by zero-filling to 4 times the number of complex points, followed by a sine modulated window function multiplication, Fourier transformation (FT) and baseline correction in both dimensions.
Diffusion ordered spectroscopy (DOSY) was performed on 50 lM monomeric aSyn and homogeneous HMWA samples in NMR buffer. Diffusion coefficients were obtained by fitting intensity curves from bipolar pulse-pair longitudinal-eddy-current delay (BPPLED) experiments with an array of linearly shifted gradient power. A series of 28 1D NMR spectra were collected as a function of gradient amplitude. Intensities were measured by integrating signals from 1D proton ( 1 H) NMR spectra between 0. 75 ppm and 3. 2 ppm. Monomeric aSyn and its hydrodynamic radius/diameter (Rh) obtained by DLS was used as the internal reference to determine Rh for HMWAs. 15 N amidebackbone relaxation data were acquired using standard pulse sequences provided in the Bruker Topspin library. Spectra used for longitudinal relaxation T 1 (1/R 1 ) analysis were collected using the following delay times (in ms): 12, 52, 102,  152, 202, 302, 402, 602, 902, 2002, 5002.
T 2 data (1/R 2 ) were measured using a pulse sequence employing a CPMG pulse train with the following delays (in ms): 6, 10, 18, 26, 34, 42, 82, 122, 162, 202, 242, 322 and 462. Duplicate spectra were collected for several time points to estimate uncertainty. To determine R 1 and R 2 relaxation rates resonance signal intensities were extracted and fit as a function of the relaxation delay time in CCPNmr. To obtain steady-state hetero-nuclear (het) NOE values, we calculated ratios of peak intensities in paired spectra collected with and without an initial 4 s period of proton saturation during the 5 s recycling delay. For relaxation experiments, the concentrations of aSyn and HMWA aggregates were 50 lM. Resolution settings and processing were the same as for 2D SOFAST-HMQC experiments. 8, 16 and 32 transients were used for T1, T2 and hetNOE experiments, respectively.
Acknowledgments We thank  Dr. Rudi Lurz  ( MPI fuer Molekulare Genetik, Berlin ) for help with TEM experiments and  Dr. Peter Schmieder  and  Monika Beerbaum  for excellent maintenance of NMR infrastructure. A. B. and J. R. acknowledge support by the  Wellcome Trust  ( 103139  and  108504 ) and the  Deutsche Forschungsgemeinschaft.
Rheological properties. Flow rheological measurements were carried out on juices and concentrates with a Physica imposed stress rheometer (model MCR301, Anton Paar Gmbh, Graz, Austria), equipped with a duvet geometry measurement module (double concentric cylinder, ref. DG27 / T2000 / SS) and accompanied by Rheoplus software for data acquisition. The temperature was regulated at 25 • C using a Peltier effect system connected to a refrigerant (Viscotherm VT2, Anton Paar Gmbh, Graz, Austria). The limit apparent viscosity for a shear rate of 1000 s -1 was chosen to compare concentrates. Indeed, this value is close to that evaluated on the membrane surface in the CMF system  (Dahdouh et al. , 2015). 2. 3. 1. 4. Particle size and distribution. Measurements of juice particle size were made with a Laser diffraction granulometer (Mastersizer 3000, Malvern Instruments Limited, Worcestershire, UK).
2. 3. 2. 1. 2. HPLC analysis. HPLC carotenoid analyses were performed according to a previous study  (Poulaert et al. , 2012)  with an Agilent 1100 system equipped with a diode array detector and autosampler. The column used was a C30 YMC column (250 × 4. 6 mm, 5 μm, YMC Europe GMBH, Germany). The flow rate was 1 mL. min -1 , the analysis temperature 25 • C and the injection volume 20 μL. The mobile phases were water (eluent A), methanol (eluent B) and MTBE (eluent C) that follow the gradient described by  Gleize, Steib, André, and Reboul (2012). The absorbance was measured at 450 nm to identify β-carotene (BC), β-cryptoxanthin (BCX) and 470 nm for lycopene (LYC). Chromatographic data and UV-Visible spectra (Agilent ChemStation Plus software) allowed the different carotenoids to be identified.
The process combined i) an enzymatic liquefaction with the preselected enzyme mixture at 300 μL kg -1 ii) a crossflow microfiltration operation using the preselected membrane/TmP combination with or without diafiltration, iii) a possible additional step of pasteurization. Seven operating parameters were modulated: enzymatic liquefaction conditions (dose of enzyme, temperature, implementation mode), CMF conditions (crossflow velocity, temperature), and with or without diafiltration and pasteurization alone or in combination (Table  2 ). Statistical analyses were performed from means and standard deviations using XLSTAT software 2016. Statistical significance was tested using one-way analysis of variance with a post-hoc Fisher's test. A P value <0. 05 was considered statically significant. From a Plackett-Burman experimental design, the effects of each factor were calculated by multiple linear regression using MS-Excel between the lowest and the highest level [-1,1].
Data source A bibliometric analysis using Boolean searches on the Web of Science (WoS, Clarivate Analytics, Philadelphia, PA, USA) , SCOPUS (Elsevier, Amsterdam, Netherlands) and PubMed (National Center for Biotechnology Information, NIH, Bethesda, MD, USA) was carried out to evaluate the main trends of publications about One Health and infectious disease research in the country of Panama, between 1990 and 2019. We used two independent search tactics in several languages (e. g. , English, Spanish, German, Portuguese, Italian). Firstly, broad-spectrum search engines such as WoS and SCOPUS were used to look for publications related to the One Health model. Secondly, a more public health-oriented search engine like PubMed was used to quest for publications speci cally regarding infectious diseases (Supplementary Figure  S1 ).
Additional criteria for exclusion were incorrect time frame (e. g. , only articles between 1990 and 2019 were considered in the analysis), and review articles (Supplementary Figure  S1 ). For the second search strategy, we conducted analogous queries in PubMed for all the scienti c documents (e. g. , controlled clinical trials, books, datasets, journal articles, letters, and reviews), and re ned the exploration by searching for the neglected and emerging infectious diseases listed in Mackey et al. [2] , Maxwell et al. [15]  and Klohe et al. [3]  (Supplementary Table  S2 ) (e. g. , "Panama"[A liation] AND "Dengue virus"[Title/Abstract]). The latter references are key articles regarding pathogens and diseases with spillover potential in LAC and more broadly as well.
Results 4,547 publications about One Health related subjects were identi ed using combined Boolean searches in WoS and SCOPUS from the country of Panama since 1990, representing 59. 5% (4,547 / 7,632) of the total publication output of the country in these databases during the same time frame. Of these 4,547 publications, 78. 3% (3,564 / 4,547) were reliable peer-reviewed articles from international journals after eliminating duplicates (Table  1 ; Supplementary Figure  S1 ). Four institutions in Panama, the Smithsonian Tropical Research Institute (STRI), the Gorgas Memorial Institute for Health Studies (ICGES), the University of Panama (UP), and the Institute for Scienti c Research and High Technology Services (INDICASAT), encompassed 96% (3,425 / 3,564) of the total scienti c records related to the One Health concept between 1990 and 2019 (Table  1 ).
We also gathered 256 scienti c documents through re ned searches in PubMed, with 82. 0% (211 / 256) focusing speci cally on neglected and/or emerging infectious diseases (Supplementary Figure  S1 ). We identi ed a statistically signi cant correlation between the number of cumulative peer-reviewed articles associated with the One Health model in Panama and the year of publication (rho = 0. 99, two-tailed P < 0. 05), depicting a strong monotonic positive relationship between scienti c productivity and time. The results could not be explained by the increase in the number of scientists alone, as the data tted an exponential growth pattern [Y= 2. 0e-044*exp(0. 052*X); R 2 = 0. 98] better than a classic tendency of linear population growth [Y= 11. 04 *X -22018; R 2 = 0. 80] (Fig. 1 A ). The growth in scienti c productivity about One Health related subjects appears to be in uenced heavily by STRI, taking off around the year 2000 (Fig.
While these are valid possibilities, we acknowledge that zoonotic infectious diseases were central to the One Health movement initially and continue to be a core element of it to date. Also, to avoid bias in our search strategy by picking One Health related terms subjectively, we used information and terminology from 19 scienti c publications, which were recently identi ed through a system dynamics approach, to delineate the central dogma of the One Health concept  [23]. In addition, we could have missed articles from scienti c journals that were not indexed in the WoS, SCOPUS or PubMed during the study period, but these are the largest abstract and citation databases of peer-reviewed literature, including medical, technical and social sciences. These search engines have been used before to assess the publication trend of important infectious diseases, including those studied under the One Health framework [18,  19, 24, 25, 71].
The purpose of developing this instrument was to assess the distress or di culty experienced from impaired cognition and to detect treatment responsiveness in a clinical trial setting. The initial development and concept elicitation data for the PRECIS instrument have previously been reported  [15] , and development was conducted in accordance with guidance from the US Food and Drug Administration  [8, 16]  and the American Educational Research Association's Standards for Educational and Psychological Testing  [17]. During this development, a conceptual model was proposed based on published data, clinical experience, and advice from leading clinicianscientists in schizophrenia research and neuropsychology  [15]. The model included seven domains reported to contribute to the subjective experience of CIAS: attention, communication/social cognition, executive functioning, intermittent impaired perception, memory, metacognitive abilities, and sharpness of thought.
Study Design This psychometric validation study included patients with schizophrenia who were participating in a Phase II, randomized, double-blinded, placebo-controlled, parallel group study to evaluate the e cacy (cognition and everyday living skills), safety, and tolerability of four orally administered doses of BI 409306 during a 12-week treatment period (clinicaltrials. gov: NCT02281773)  [18]. Healthy individuals (control group) were recruited separately from subgroups at the same study sites, but using a separate, parallel-study protocol (Clinicaltrial. gov: NCT01505894). The study was conducted in accordance with the ethical principles of the Declaration of Helsinki  [19] , International Council for Good Clinical Practice  [20] , and applicable country-speci c regulatory requirements.
Statistical Analyses Analyses were conducted using SAS version 9. 4 software (SAS Institute, Cary, CA, USA). Descriptive statistics were calculated for demographic variables (age, gender, race, and ethnicity). For individual items in the PRECIS instrument, the mean, standard deviation (SD), range, and ceiling and oor effects were calculated. Effects of gender (female vs male), age (≤45 years vs >45 years) and race-ethnicity (white vs black vs other) on PRECIS item scores (35-item instrument) were examined using standard statistical tests. Responses to the PRECIS instrument were converted into a total score (unweighted), calculated using the sum of the 35-item scores divided by 35 (average item score). Individual domain scores (scores for each category of items) were computed as the average score across all items within each domain.
Reliability Reliability was assessed using assessments of internal reliability and test-retest replicability. Internal reliability, or inter-item consistency, of the original 35-item PRECIS instrument was evaluated by means of Cronbach's alpha  [21, 22]  based on data obtained at baseline from patients with schizophrenia. Cronbach's alpha ranges from 0 to 1, with higher values indicating increased reliability. Inter-item correlations were analyzed using Spearman's (non-parametric) rank order correlation coe cients. Unfortunately, repeated administrations of the PRECIS items during the pre-treatment or run-in phase of the study, as would ideally be used for test-retest purposes, were not included during the main clinical trial (NCT02281773). These analyses were therefore performed during the last phase of the clinical trial (Weeks 9-12).
Acknowledgments We acknowledge the statistical support of  Brian and Bernet Kato at New England Research Institutes (NERI) ,  Ashley Magnavita  for comprehensive project management, and the support of the clinical trial sites that contributed data. We acknowledge the editorial support (in the form of initial preparation of the outline based on input from all authors, collation and incorporation of author feedback to develop subsequent drafts, assembling tables and gures, copyediting, and referencing) provided by  Rachael Baylie, PhD , of  Fishawack Communications Ltd , which was funded by  Boehringer Ingelheim International GmbH.
The panel members were then trained in the evaluation of samples of P. palmata, using a 15-cm unstructured scale for each attribute, ranging from lowest to highest intensity. The GDA results were transformed to numbers from 0 to 100 (lowest to highest intensity) for the data analysis. Both the training and sensory evaluation phases were conducted in a sensory test facility equipped with individual booths. Red lights were used during The MC of both D-and SD-samples was determined gravimetrically by drying ca. 5 g of sample at 105 °C until constant weight (typically 24 h). Three replicate measurements were made on each sample. The subsequent results from chemical analyses were expressed as part of the dry weight (DW) of the samples. The a w was measured with a LabMaster-aw (Novasina AG, Lachen, Switzerland).
Sensory analysis The effects of two different levels of moisture during 126 days of storage on the quality of P. palmata as food was investigated in this study with emphasis on the sensory characteristics of the product. Both dry (D-126) and semi-dry (SD-12, SD-61, SD-126) samples of P. palmata were evaluated by nine trained panel members in a GDA based on 12 sensory attributes (Table  1 ). Significant differences were detected between samples regarding most of the sensory attributes, except for bitterness, associated with low scores, and saltiness, perceived as intense in all samples (Table  2 ). The PCA of the mean scores (averaged over panelists) for each attribute explains 81. 6% of the variance in the dataset (72. 0 and 9. 6% by PC-1 and -2 respectively, Fig. 1 ). Strong marine flavor and odor ("seaweed" and fishy) were identified from the evaluation of the control stored during the entire period (D-126) and SD-samples stored for 12 days (SD-12) as well as a tough and crunchy texture, supporting previous reports from the sensory evaluation of dried P.
Conclusions Three of the 18 food poisoning cases reported in France from January 2011 to March 2018 following the consumption of sea figs (Microcosmus) were investigated. The HILIC-LCMS analyses in low-and high-resolution unequivocally revealed the presence of ATX-a in concentrations ranging from 193. 7 to 1240. 2 µg/kg. This is the first time that this freshwater toxin has been reported in sea figs as the possible toxicant responsible for human food poisoning. The range of the ATX-a concentrations found in the sea fig samples was lower than the animal toxicological data reported in the literature. This raises questions about the toxin level necessary to make consumers sick but could also indicate the presence of unknown ATX analogues or the concomitant action of another toxicant.
The third is the WAK domain containing Pro25 (WAK1) and WAK4  (52). The fourth is the L-LEC domain containing LecRK1  (55). The accumulation of Arabidopsis sequences available in databases by Mya: million years ago 2000  (101) , and the recent release of the complete sequence of the Arabidopsis genome, revealed that the Arabidopsis genome contains nearly 1,000 genes encoding Ser/Thr protein kinases, several hundred of which are RLKs  (2). Comparative genome analysis between Arabidopsis and other sequenced genomes again highlighted that RLKs were highly similar to the Drosophila Pelle protein kinase and the mammalian INTERLEUKIN1 RECEPTOR-ASSOCIATED KINASE (IRAK). Overall, these results provided a first indication that (a) RLKs have a monophyletic origin and are close relatives to animal Pelle kinases and IRAKs, (b) RLK kinase domains evolve more rapidly than kinase domains of other protein kinases, (c) some ECDs found in plants are unfamiliar in animals, and (d) although the ECDs are similar, kinase domains of some of these RLK receptors do not cluster together in the phylogenetic trees, suggesting that several associations between these ECDs (e.