dataesr/scientific-paragraphs-categorization huggingface dataset:
On the first sheet is attached a small label, handwritten by Raddi, indicating "Piper marginatum ex H: Cors:", while the second sheet does not have any label. On the second specimen at PI, accession number 043360, there is a label handwritten by Raddi "Piper caudatum Vahl?", which is a synonym of P. marginatum Jacq. (Yuncker, 1972: 61). On the lower portion of the sheet is mounted a leaf and two stem portions of Peperomia arifolia Miq. , a species quite frequent in the mountains surrounding Rio de Janeiro. It is worth noting the differences between the two species mounted on this sheet. On the upper portion of the sheet are the specimens of Piper marginatum, which is a species characterized by shrubby habit, leaf blades with palmate venation with all veins reaching the apex, densely ciliate margins, and leaf base not peltate.
mm] long). Notes. -Original specimens of Piper pumilum Raddi are present at PI and FI. At PI there is a specimen, with accession number 043374, consisting of a decumbent plant with running stems with numerous thin roots, obovate leaves shallowly notched, and one inflorescence. It also has the label "Piper (Peperomia) pumilum, nob. " handwritten by Raddi. This specimen is here designated as the lectotype of P. pumilum. At FI there is a sheet, barcode FI055273, on which several small branches belonging to two different species are mounted. Most branches on the sheet are Piper serpens Sw. (≡ Peperomia serpens (Sw. ) Loudon, see below under this name), and are easily recognizable by the broadly ovate leaves obtuse at apex. The branch with one leaf overlapping the specimen label is easily distinguished from the other branches on the same sheet by the obovate leaves, round and shallowly notched at apex.
Piper bracteatum We found only one specimen annotated by Raddi with these names, which is deposited at PI. The specimen, with accession number 043358, only has two loose, small leaves, and has two labels handwritten by Raddi. The label written in pencil has the annotation "solitariis Roem. 326. Folia 4-6 lin; petioli lineam longi; spadices pollicares erecti rubri. " The label in ink has the annotation "Piper molle Roem. et Sch: I. 326. Peperomia mollis Humb. et B: N. Gen: I. p. 65. "  Raddi (1828: 10)  described this plant as having filiform, repent, muchbranched stems, ovate, sub-fleshy, softly pubescent leaves, and leaf-opposed spikes. The name to be used for this species is Peperomia mollis. Collection locality and habit. -The collection locality of this species was described by Raddi under Piper callitrichoides Raddi as "among the moss on the trunk of the trees growing in the very shaded forests of Serra da Estrela".
Piper gracillimum Notes. -Original specimens of Piper gracillimum Raddi are at PI and FI. The specimen at PI, accession number 043378, bears Raddi's handwritten annotation "Piper (Peperomia) gracillimum nob. " and is here designated as the lectotype. The specimen at FI, barcode FI055252, has the annotation "In Brasilia legit Cl. Raddi" handwritten by Parlatore, and is the isolectotype of this name. Raddi's specimens represent a species fairly common in the mountains surrounding Rio de Janeiro traditionally known as Peperomia pseudoestrellensis C. DC. , which is here treated as a synonym of Piper gracillimum. As this species belongs to Peperomia, the new combination Peperomia gracillima (Raddi) E. F. Guim. , G. A. Queiroz & Delprete is here provided. Casimir de  Candolle (1898: 277) , along with the original description of Peperomia pseudoestrellensis C.
"Piper nigrum ex H. Mus. Fl. 1826. " Piper marginatum Jacq. Notes. -The specimen at PI with accession number 043365 (with "2" written in pencil) has three branches with several leaves and spikes, and a label with the annotation "Piper nigrum, ex H. Mus. Fl. 1826" handwritten by Raddi. This specimen has been incorrectly identified by Raddi, as the leaf blades of this specimen are cordate at base and thus characteristic of Piper marginatum (vs. blades round or obtuse at base in P. nigrum L. ). Notes. -In PI there is a specimen, accession number 043357, with three labels. One label has the annotation "Piper polystachyon, 203" written in ink by an unknown author. A second label, handwritten by Raddi, has the annotations "Piper trifolium? ex H. Mus. Flor. " in pencil, and "Piper polystachyon" in ink.
5. "Piper siriboa L. ,Sp. Pl. 1: 29. 1753" [incorrectly identified with this name by Raddi]. Manekia obtusa (Miq. ) T. Arias, Callejas & Bornst. in Novon 16(2): 206. 2006. Notes. -One specimen in PI, with accession number 043366, was identified by Raddi as Piper siriboa L. , a species 12 Version of Record.
Epidermal layer staining and dermal suspension flow cytometry Three hours after ID injection, skin pieces were digested to separate the epidermal layer from the dermal layer. Epidermal sheets were first saturated with 3% BSA for 1 h and stained with anti-CD1a (clone O10; Dako) for 1 h, then washed in PBS 1X and incubated with anti-mouse IgG1-Alexa-594 antibody (2 lg/ml; Molecular Probes Inc) for 1 h 30 in PBS 1X containing 1% BSA. Epidermal sheets were mounted for microscopy with Vectashield mounting medium (Molecular Probes Inc) and were analyzed using the Axio Z1 microscope equipped for acquisition using Zen software. Alexa-594 signals were acquired using a combination of LED Colibri 7 and emission filters: LED 590 nm, EmBP 605/70. Dendrites' length, number of dendrites per LC, and number of LCs per square millimetre were measured using ImageJ software.
Dermal layers were digested to obtain a dermis cell suspension. A total of 500,000 dermis cells were incubated for 10 min at 4 °C with Fc block (Miltenyi Biotec) and Live/Dead TM Fixable Aqua dead cell stain kit (Molecular Probes Inc), according to the manufacturer's recommendations. Cells were stained for 20 min at 4 °C for the following surface markers: CD1a (LFA-1-APC), CD14 (MuP9-V450), CD163 (GHI/61-BV605), CD11c (ITGAX-PE-CF594), CD80 (L307. 4-APCH7), CD86 (B7. 2-Percp-Cy5. 5) (BD Biosciences), CD1c (BDCA-1-Pecy7), HLA-DR (L243-BV786), and CD45 (H130-A700) (BioLegend). Intracellular CD207 (Langerin-PE; BD Biosciences) staining was performed using the Cytofix/Cytoperm TM fixation/permeabilisation solution kit (BD Biosciences) following the supplier's protocol. Samples were analysed with a flow cytometer (LSRFortessa TM , BD Biosciences) and FACS Diva v6 and FlowJo TM software (BD Biosciences).
Funding This project has received funding from the  European Union 's  Seventh Programme for research, technological development and demonstration  under grant agreement No  241904 , the  European Union 's  Horizon 2020 Research, Innovation Programme  under grant agreement No. 681137  and  EUROSTARS E! 11941 -IDMA-VAC. The group of BC has received an award from the  'Fondation pour la Recherche Medicale' (FRM ''Equipe").
Total flavonoid content (TFC) The total flavonoid content (TFC) of A. strigosa was determined by the aluminum chloride colorimetric assay, as reported by  Quettier-Deleu et al. (2000)  with slight modification. Each extract was prepared at a concentration of 1 mg/mL of sterile ultrapure water and an aliquot (1 mL) was mixed with 1 mL of 2% methanolic aluminum chloride. The mixture was incubated for 30 min in the dark and at room temperature. The absorbance was measured at 415 nm, using rutin as standard. The TFC was expressed as mg rutin equivalents (RE) per Gram of extract (mg RE/g). Analysis of TFC was repeated three times and data are presented as mean values ±SEM.
Total phenolic content (TPC) With slight modification, the total phenolic content (TPC) of A. strigosa extracts was evaluated using the Folin-Ciocalteu method  (Phuyal et al. , 2020). A stock of each A. strigosa extract was prepared at a concentration of 1 mg/mL. An aliquot (500 μL) of the extract was oxidized with 2. 5 mL of 0. 2 N Folin-Ciocalteu reagent for 5 min. Then the reaction was neutralized with 2 mL of 75 g/L sodium carbonate and incubated in the dark at 37 °C for 1 h. The absorbance was measured at 760 nm, where gallic acid was used as a standard. The TPC was expressed as a percentage of total gallic acid equivalents per Gram of extract (mg GAE/g). Analysis of TPC was repeated three times and data are presented as mean values ±SEM.
Liquid chromatography-mass spectrophotometry For HPLC-PDA-MS/MS analysis, the mass spectrometer (LC-MS 8050; Shimadzu, Japan) was coupled to a triple quadruple spectrometer with an ESI source. The samples underwent chromatographic separation using a Zorbax Eclipse XDB-C18 column (4. 6 mm i. d. × 150 mm long, 3. 5 µm particle size; Agilent, Santa Clara, CA, United States). Two mobile phases, water and acetonitrile (ACN), were used and the gradient applied from 5% to 60% ACN over 40 min at a flow rate of 1 mL/min. The extracts were injected via an autosampler (SIL-40C xs) controlled by LC solution software (Shimadzu, Japan). The ions were collected in the negative mode.
Assay of cell viability Capan-2 cells (5 × 10 3 ) were seeded in 96-well plates and allowed to grow until they reached 30%-40% confluency. The cells were then treated with increasing concentrations of extract and incubated for a total period of 72 h. Cell viability was assessed by the reduction of 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT; Sigma-Aldrich, St. Louis, MO, United States). Cell growth was determined as the proportional viability of the treated cells in comparison with the vehicle (sterile ultrapure water)-treated cells, the viability of which was assumed to be 100%. The assay was performed in triplicate and repeated three times. Data are presented as mean values ±SEM.
Modelling of PC chemical degradation kinetics and formation of impurities, as well as time-to-failure prediction The datasets related to the degradation of PC and its degradation products were fitted to kinetic degradation models using the PREDISTAB software that automates the semi-predictive methods (KC  Waterman and Adami, 2005). Two approaches were tested: isoconversional and model screening. The fit of the model was evaluated using the Bayesian Information Criterion (BIC), the Akaike Information Criterion (AIC), the Relative Mean Square Error (RMSE), and the determination coefficient R 2. The best-fitted model was then used to predict the long-term degradation rate of PC over 24 months and the appearance of its degradations products, allowing the attribution of shelf life to the preparation.
004 to 0. 489 Å -1. Neutrons of wavelengths λ of 1. 75-16. 5 Å were used simultaneously by time-of-flight. Data reduction for D11 data was done using GRASP software  [36]. For the ZOOM data, MANTID software [37] was used. The raw intensity data were corrected for the background scattering and weighted by the transmission of the sample  [38]. In addition, a Cadmium sample was used to subtract the electronic background noise. For normalization and absolute scaling, a 1 mm reference sample containing distilled water was used as an isotropic scatterer. The 2D data were finally radially averaged to give the 1D scattering intensity.
Acknowledgements We gratefully acknowledge the  Institut Laue-Langevin (ILL, Grenoble, France , experiment 9-10-1704 [48]) and ISIS Pulsed Neutron and Muon Source ( STFC Rutherford Appleton Laboratory, Didcot , U. K. , experiment RB2210341 [49]) for allowing to measure some neutron scattering spectra. Funding Open Access funding enabled and organized by  Projekt DEAL. We thank the  Fonds der chemischen Industrie (FCI)  and the  Technische Universität Berlin  for the financial support.
Fractionation of Hop Leaf DSE by Preparative HPLC Hop leaf DSE was fractionated by preparative HPLC using a Shimadzu ® HPLC system equipped with a LC-20AP binary high-pressure pump, a CBM-20A controller and an SPD-M20A diode array detector. The software used was LabSolution version 5. 3. Five hundred µL of a filtered solution of leaf DSE at 100 mg•mL -1 , solubilized in methanol, were injected into an Uptisphere Strategy C18-HQ (250 × 21. 2 mm, 5 µm,) prep-LC column (Interchim, France). The mobile phases consisted of two solvents with the addition of 0. 1% (v/v) formic acid: ultra-pure water (A) and acetonitrile (B). Acetonitrile (LC-MS grade) was purchased from Carlo Erba Reagents ® (Val-de-Reuil, France) and formic acid from Merck™ (Darmstadt, Germany). The following gradient was applied: 10-100% B (0-45 min), then 100% B (45-65 min).
Data Analyses Optical density (OD) was read at 630 nm after 6 days of incubation with a spectrophotometer (Biotek EL 808, BioTek Instruments, Santa Clara, CA, USA). Once the net optical density was calculated, half inhibitory concentration (IC 50 ), the concentration that inhibits the spore germination by 50%, was determined using a non-linear regression with four parameters (dose-response curve). Each experiment was repeated at least twice to obtain one IC 50 per modality taking into account inter-and intra-experiments variability. A Fisher test with a p-value (α = 5%) was first performed to compare all the modalities. Afterwards, a pairwise comparison of IC 50 , based on 95% confidence intervals with Bonferroni adjustments, was used for each strain separately, and then for each modality, comparing the two strains.
Statistical Analysis Statistical comparisons between the groups were performed with a one-way analysis of variance (ANOVA) followed by the Tukey test, and the comparison between rat groups was made by t-test using GraphPad Prism ®software (version 5. 0; GraphPad Software, Inc. , San Diego, CA, USA). Data were represented as mean ± SD (* p < 0. 05, ** p < 0. 01, and *** p < 0. 001).
Statistical Analysis Efficacy and safety data were summarized by oral corticosteroid use at induction baseline (Yes/No) and oral corticosteroid dose, using < 20 mg/day or ≥ 20 mg/day to represent lower and higher doses of oral corticosteroids, respectively. These post hoc analyses are based on pooled data from OCTAVE Induction 1 and 2, with a focus on systemic corticosteroid exposure; therefore, patients receiving budesonide or beclomethasone were excluded. Efficacy endpoints are reported for the full analysis set (all patients who underwent randomization) and patients with missing binary efficacy data were treated as non-responders. Differences (95% confidence intervals [CIs]) from placebo were based on the normal approximation for the difference in binomial proportions. For a comparison of differences between tofacitinib and placebo, the p values were based on the Cochran-Mantel-Haenszel χ 2 test.
Acknowledgments These studies were sponsored by  Pfizer. The authors would like to thank the patients, investigators, and study teams involved in OCTAVE Induction 1 and 2. Medical writing support, under the guidance of the authors, was provided by  Helen Findlow, PhD ,  McCann Health Medical Communications , and was funded by  Pfizer Inc, New York, NY, USA  in accordance with Good Publication Practice (GPP3) guidelines (Ann Intern Med. 2015;163: 461-464 ).
Funding This work has been partially supported by  University of Rouen Normandy ,  INSA Rouen Normandy , the  Centre National de la Recherche Scientifique (CNRS) ,  European Regional Development Fund (ERDF) ,  Labex SynOrg  ( ANR-11-LABX-0029 ),  Carnot Institute I2C , the graduate school for research  XL-Chem  ( ANR-18-EURE-0020 XL CHEM ), and  Region Normandie. L. M. and T. B. thank the  European Research Council (ERC)  under the European Union's  Horizon 2020 research and innovation program  (grant agreement no. 758710 ). F. D. thanks  Labex SynOrg  ( ANR-11-LABX-0029 ) and the  Region Normandy  ( RIN 50% program ) for a doctoral fellowship.
Following three washes for 10 min in PBST, the membranes were immersed for 1 h at room temperature with an appropriate secondary antibody (dilution 1/5000 in 1% milk TBST) conjugated to horseradish peroxidase. Membranes were washed three times in TPBS for 10 min, and the Supersignal West Femto Maximum Sensitivity Substrate (ThermoFisher Scientific, Illkirch-Graffenstaden, France) was used to reveal the immunoreactivity through enhanced chemiluminescence and a Chemidoc XRS+ device (Bio-Rad, Marnes-la-Coquette, France). Image processing and quantification were performed using Image Lab software (Bio-Rad, Marnes-la-Coquette, France).
The primer sequences are described in Table  1. PCR reactions were carried out in triplicate at a final volume of 15 µL, containing 7. 5 µL MESA Green qPCR Mastermix (Eurogentec, Uppsala, Sweden) and 3. 5 µL of cDNA and forward and reverse primers at 300 nM. Thermal cycling conditions were achieved by the activation of DNA polymerase at 95 • C for 10 min, followed by 40 cycles of amplification at 95 • C for 15 s, 60 • C for 30 s, and 72 • C for 30 s. Melting curve analysis was performed to control the absence of non-specific products. For each transcript, the amplification efficiency was determined by the slope of the standard curve generated from twofold serial dilutions of cDNA. The 2 -∆∆Ct method was used to determine the relative gene expression. The results are depicted as graphs of relative expression data (fold induction)  [41].
Gene Name Accession Number Primer Sequences Abcd1-F Abcd1-R NM_007435. 2 5 GCCAAGTTGTGGATGTGGAG3 5 TTCCGCAGAGTCGGGATAGA3 Abcd2-F Abcd2-R NM_011994. 4 5 TAGAACGCATCCTGCACAGC3 5 CTCCTTCGCCATCGAATTGT3 Acox1-F Acox1-R NM_001377522. 1 5 TCGAAGCCAGCGTTACGAG3 5 GGTCTGCGATGCCAAATTCC3 Cat-F Cat-R NM_009804. 2 5 AGCGACCAGATGAAGCAGTG3 5 TCCGCTCTCTGTCAAAGTGTG3 Table  1. Cont.
Gene Name Accession Number Primer Sequences Il-1β-F Il-1β-R NM_008361. 4 5 GAGATTGAGCTGTCTGCTCA 3 5 AAGGAGAACCAAGCAACGAC 3 Il-4-F IL-4-R NM_021283. 2 5 CCATATCCACGGATGCGACAA3 5 CCTCGTTCAAAATGCCGATGAT3 iNos-F iNos-R NM_010927. 4 5 CCTAGTCAACTGCAAGAGAA3 5 TTTCAGGTCACTTTGGTAGG3 Tnf-α-F Tnf-α-R NM_013693. 3 5 CCCTCACACTCAGATCATCTTCT3 5 GCTACGACGTGGGCTACAG3 36b4-F 36b4-R NM_007475. 5 5 CGACCTGGAAGTCCAACTAC3 5 ATCTGCTGCATCTGCTTG3.
These LPS-dependent increases were significantly attenuated by cotreatment with Schot or Spina at both concentrations (Figure  10A, B ). In contrast, treatment with Schot or Spina alone, at both concentrations, had no effect on Il-1β expression in the Wt and Acox1 -/-cell lines when compared to the control cells (Figure  10A, B ). On the other hand, we also evaluated the gene expression of the anti-inflammatory cytokine Il-4. The obtained data revealed that Schot and Spina treatment increased the Il-4 mRNA expression in the Wt cells but not in the Acox1 -/-cells (Figure  10C, D ). However, the LPS-reduced levels of Il-4 mRNA in both cell lines were partially but significantly rescued by Schot and Spina treatment at concentrations of 1 and 2. 5 µM (Figure  10C, D ). Total RNA was isolated from BV-2 cells, and then the expression level of genes of interest was quantified by real-time RT-qPCR.
The objective of this study is to examine the potential association between drug use and adverse event reporting in France. A number of drug users and cases reported were extracted from the French Health Care Insurance database (Open Medic) and the French pharmacovigilance database. We performed two separate mixed-effect models (with a drug used or reporting rate as dependent variables) with a random intercept for drug classes. We selected 62 drugs from 10 drug classes, for which 177 364 cases were reported in the French pharmacovigilance database in 2020. The results showed a strong association between drug users and the number of reported cases in France among each drug class (P < 0. 01). Within a drug class, the number of reported cases is, therefore, a proxy for the exposure to a given drug in the population.
| INTRODUCTION Spontaneous reporting of adverse events, aggregated in national and international pharmacovigilance databases, and quantitative detection of disproportionality signals are cornerstones of pharmacovigilance activity  [1]. While disproportionality analyses allow the detection of higher than expected associations between adverse events and drugs, the lack of patient exposure data and the selective reporting of adverse events do not allow the calculation of adverse event incidence rates  [2]. Yet, despite this selective reporting, a recent study suggested that the total number of adverse events reported for a given drug is correlated to drug exposure without evidence of the Weber effect or other time-varying reporting bias  [3]. This total number of reported adverse events cannot be used as a proxy for drug exposure per se, given drugs display heterogeneous safety profiles, different indications, and exposed populations, but we hypothesized that it could be the case among a drug class.
| Data sources We first extracted all sell data of drugs dispensed by French pharmacies from January 1, 2020 to December 31, 2020 from the Open Medic database  [4, 5]. Open Medic is a spreadsheet of all drug reimbursements by the health care insurance system. It provides for each drug the number of boxes sold and the number of patients taking it overall and categorized by age and sex. These data are collected by the Caisse Nationale de l'Assurance Maladie (French National Health Insurance System), in charge of medication reimbursement in France. We arbitrarily selected 10 drugs classes at the ATC 4th level with various characteristics, exposure, and safety profile: J01A tetracyclines, L01EA BCR-ABL tyrosine kinase inhibitors, M05BA bisphosphonates, N06AB selective serotonin reuptake inhibitors, B01AA vitamin K antagonists, C08CA dihydropyridine derivatives, L04AB tumor necrosis factor alpha inhibitors, M01AH Coxibs, N05BA benzodiazepine derivatives, and R06A antihistamines for systemic use.
| RESULT Among the 62 selected drugs, the number of exposed patients in 2020 in France ranged from 571 for ponatinib to 6 086 943 for desloratadine, with a median of 176 409 patients (Q1-Q3 31 104-628 988) per drug. The median number of boxes dispensed per patient in 2020 was 6. 42 ranging from 1. 25 for zoledronic acid to 21. 1 for warfarine. Overall, 177 364 cases were reported of these drugs in France in 2020. The median number of adverse event cases reported in the French pharmacovigilance database for 100 000 exposed patients was 29. 2 cases (Q1-Q3 8. 7-115. 0). The median number of cases reported by sex according to drug exposure was 25. 8 for women (Q1-Q3 8. 1-124. 0) vs. 21. 6 for men (Q1-Q3 5. 3-110. 0). The number of cases reported by drug class is presented in Table  1 , and individual data for all drugs are available in Table  S1.
In the mixed effect model with the number of drug users as the dependent variable, we found that the number of adverse event cases reported and the proportion of female cases were independently associated with the number of exposed patients (R 2 = 0. 78) (Table  2 ). Intra-class slopes are presented in Figure  1 , and separate regression models for each drug class are presented in Figure  S1. Overall, the coefficients of determination (R 2 ) ranged from 0. 61 for benzodiazepines to 0. 98 for selective serotonin reuptake inhibitors. Moreover, adding a random factor for drug class significantly improved the goodness-of-the-fit of the model compared to linear regression without accounting for dug class (Figure  S2 ). In the mixed effect model with the reporting rate as the dependent variable, the date of the first case recorded in the dataset (as a proxy of labeling date) and the proportion of females exposed were not significantly associated with reporting rate (Table  2 ).
| DISCUSSION Adverse event reporting is known to be influenced by several factors, such as the safety profile of drugs (i. e. , the severity of adverse drug reactions), the gender, the characteristics of the exposed population, media attention, and the date and content of labeling  [6]. Nevertheless, in a sample of 10 drug classes and 62 drugs with various indications and safety profiles, we found that the number of spontaneously reported cases of adverse events in France is correlated with the number of exposed patients among drug classes. Within a drug class, the number of reported cases is, therefore, a proxy for the exposure to a given drug in the population. This finding could be useful to approximate and compare drug exposure within pharmacovigilance databases. Indeed, exposure data are most of the time kept confidential by manufacturers.