dataesr/scientific-paragraphs-categorization huggingface dataset:
05-3 min, and retention time wavelet range = 0. 0-0. 15. Deisotope chromatograms were grouped using the isotopic peaks grouper algorithm set at m/z and tR tolerances of 10 ppm and 0. 1 min, respectively. Peak alignment of samples was then achieved using the join aligner method with parameters set at m/z and tR tolerances of 10 ppm and 0. 15 min, respectively. MS/MS scans were associated to the corresponding MS scans using a m/z and tR tolerance of 10 ppm and 0. 15 min, respectively. The gap-filling process was performed on the peak list using the same RT and m/z range gap filler module with a m/z tolerance of 10 ppm. Molecular Network generation. The MNs were generated using the feature-based molecular networking workflow of the Global Natural Products Social platform and MetGem software  [9, 10].
MNs were built using LC-MS/MS data obtained from both the urine and plasma samples analyses. The following settings were used to build the network: minimum pairs Cos > 0. 60, parent ion mass tolerance = 0. 02 Da, fragment ion mass tolerance = 0. 02, network topK < 150, minimum matched peaks = 3, and minimum cluster size = 2. The library spectra inquiries were performed using the same parameter values as those defined for the network building. The MNs were finally visualized and annotated using Cytoscape 3. 4. 0™ software (San Diego, CA, USA)  [31]. Identification of tramadol metabolites. The structure assignment of tramadol and its metabolites was based on MS and MS/MS data, using a tolerance window of 5 and 15 ppm, respectively. Identification was supported by experimental chromatographic retention time (tR) values.
Acknowledgments: The authors thank the  Assistance Publique-Hôpitaux de Paris ,  Région Ile de France  and the  Ville de Paris. We also gratefully thank  Arezki Khaled Boukerma  ( Laboratoire de Toxicologie Biologique, Hôpital Lariboisière, APHP ) for quantitative determination of tramadol, Odesmethyl tramadol, and N-desmethyl tramadol in plasma samples.
2D NMR experiments were achieved using standard Bruker microprograms (Xwin-NMR version 2. 1 software). All chemical shifts (δ) are given in parts per million (ppm) with the solvent signal as reference relative to TMS as internal standard, while the coupling constants (J) are given in hertz (Hz). Deuterated solvents such as methanol (methanol-d 4 ), dimethyl sulfoxide (DMSO-d6), and chloroform (CDCl 3 ) were used as solvents. 2. 5. Antimicrobial Assay 2. 5. 1. Microorganisms. The extracts and some isolated compounds were tested for their antibacterial activities against four bacterial strains, namely, Staphylococcus aureus ATCC 25923 (Gram-positive bacterium), Pseudomonas aeruginosa ATCC 76110, Escherichia coli ATCC 25922, and Klebsiella pneumonia 22 (Gram-negative bacteria). These microorganisms were taken from the Research Unit of Microbiology and Antimicrobial Substances.
Chemical Analysis. The EtOAc and n-BuOH extracts from the EtOH crude extract of P. succulenta were subjected to repeated column chromatography on silica gel and Sephadex LH-20 to yield thirteen metabolites  (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13). Their structures were elucidated by spectroscopic and spectrometric analysis as well as by comparison with literature data (Supplementary materials/figures (available here)). The isolated compounds were identified as veprisine (1)  [12] , naucleofficine III (2)  [13] , vepridimerine B (3)  [14] , vepridimerine C (4)  [14] , barbinervic acid (5)  [15] , quinovic acid 3β-O-α-Lrhamnoside (6)  [16] , scopoletin (9)  [17] , gallic acid (10)  [18] , quercetin 3-O-β-D-glucopyranoside  (11)   [19] , kaempferol 3-O-α-L-rhamnopyranoside-7-O-α-L-rhamnopyranoside  (12)   [20] , and borreriagenin (13)  [21].
TIN is typically characterized by a (sub)acute rise in creatininemia, which is seldom specific. 6 Besides, there is often no abnormality in the urinalysis. Therefore, anamnesis is pivotal to the early diagnosis. Etiologic investigations should rely on a thorough knowledge of the most suspect drugs, to promptly discontinue the possible culprit. Furthermore, early treatment with steroids may speed renal recovery. 5 et, quantitative and qualitative data about the association of TIN with various drugs are scarce. Therefore, we aimed to rank the drugs having the strongest association with TIN, based on the international pharmacovigilance database and a disproportionality analysis.
DISCUSSION Although virtually any drug can be associated with a risk of TIN, this analysis of the World Health Organization safety database highlights the most frequently involved. These drugs should alert the clinician facing suspicion of TIN or acute renal failure of undetermined cause. PPIs, antibiotics, and nonsteroidal antiinflammatory drugs are the most reported drugs for TIN. This ranking is confirmed by the disproportionality analysis, which is a more reliable indicator of the comparative risk for a drug to be associated with TIN. Previous studies  S1-S3  suggested that TIN was more frequent in the elderly. Indeed, their reduced renal function makes them prone to the accumulation of drugs and metabolites. They are also exposed to a wider range of drugs. In VigiBase, half of the reports concerned patients > 60 years of age.
g. , nivolumab), their association with TIN is confirmed, even though the exact underlying mechanism is still debated. S16-S20  Sodium phosphate can elicit acute or chronic phosphate nephropathy, S21 which pathophysiology is totally different from common drug-induced TIN (of immunoallergic mechanism). To our knowledge, this study about TIN is the first to rely on a comprehensive analysis of >15,000 reports from the World Health Organization safety database, with drugs used in a real-life setting. Though, pharmacovigilance studies are hindered by underreporting. S22 Conversely, we cannot exclude that some diagnoses of TIN might have been wrongly attributed to the notified drug. A confirmation of the diagnosis by renal biopsy may have lacked in some cases, as these data are not provided in VigiBase.
In this comprehensive analysis of the World Health Organization safety database, a ranking of drugs associated with TIN has been established. The strongest associations with TIN involve PPIs, antibiotics (b-lactams, fluoroquinolones, glycopeptides), and nonsteroidal anti-inflammatory drugs. Early identification of a potential causative drug is pivotal to increase chances of recovery. Hence, pharmacovigilance data can foster the efficient management of (sub)acute renal failure of undetermined origin. research. AOG, DM, and FR performed the research. AOG and DM analyzed the data.
ACKNOWLEDGMENTS The authors acknowledge the UMC who manages and provided the data used in the present study. Access to VigiBase is available without fees to Dr. Fanny Rocher. The views expressed in this article are the authors' personal views and may not be understood or quoted as being made on behalf of or reflect the position of the Agence nationale de sécurité du médicament et des produits de santé, the European Medicines Agency, the World Health Organization, or one of their committees or working parties. The authors thank Dr. Elise Van Obberghen (MD), a native speaker of American English, for proofreading this manuscript. She received no compensation for this work.
Optical macroscopy and implant dimensions Pictures of implants before exposure to the release medium were taken using a SZN-6 trinocular stereo zoom macroscope (Optika, Ponteranica, Italy), equipped with an optical camera (Optika Vision Lite 2. 1 software). The lengths and diameters of the implants were determined using the software ImageJ (US National Institutes of Health, Bethesda, Maryland, USA).
Implant swelling Implants were treated as for the in vitro drug release studies described above. At pre-determined time points: (i) Pictures of the implants were taken with a SZN-6 trinocular stereo zoom macroscope (Optika), equipped with an optical camera (Optika Vision Lite 2. 1 software). The lengths and diameters of the implants were determined using the software ImageJ (US National Institutes of Health). Dynamic changes in the systems' volume were calculated considering cylindrical geometry. (ii) Implant samples were withdrawn and excess water was carefully removed using Kimtech precision wipes (Kimberly-Clark, Rouen, France) and weighed [wet mass  (t) ]. The change in wet mass (%) (t) was calculated as follows: change in wet mass (%)(t) = wet mass (t)mass (t = 0) mass (t = 0) × 100% (1) where mass (t = 0) denotes the implant mass before exposure to the release medium.
Acknowledgments This project has received funding from the  Interreg 2 Seas  programme 2014-2020 co-funded by the  European Regional Development Fund  under subsidy contract No  2S04-014  3DMed. The authors are very grateful for this support. They would also like to thank  Mr. A. Fadel  from the  "Centre Commun de Microscopie" of the University of Lille  (" Plateau techique de la Federation Chevreul CNRS FR 2638 ") for his valuable technical help with the SEM pictures.
For each sample, videos were acquired for 8 s at the frame rate of 3. 75 s -1 , as recommended by the manufacturer with regard to the size range of the particles. Detected tracks were analyzed using the Zetaview® software and translated into particle size distribution profile from which the mean diameter of the particles was expressed. Zeta potential (ζ potential) of the lipoplexes was determined at 25 • C on samples diluted to the tenth in a 5% glucose solution, using the Zetasizer® nano-ZS instrument. Measurements were performed on independent preparations and analyzed with the Zetasizer® software, using the electrophoretic mobility based on the Smoluchowski approximation. Data were expressed as mean value ± standard deviation (SD).
To avoid excitation intensity decrease with deepness, laser power was configured to progressively increase while scanning deeper into the samples. The same increase scale and observation parameters were used for all samples. For each section, two images were acquired and averaged. 3D representations were reconstructed from image stacks using the Fiji image processing software and its 3D Viewer plug-in. 2. 2. 5. 4. Mucus rheology. Rheological properties of mucus samples collected from Calu-3 3D-cultures were analyzed on a Haake Mars Rheometer (Thermo Electron, Karlsruhe, Germany) equipped with a 25-mm plate-plate geometry. The temperature-controlled Peltier plate was allowed to equilibrate at 37 • C for 2 min before sample deposition (180 µL). After another equilibration period, oscillatory measurements were performed at 37 • C, using a gap width of 0.
Five thousand frame videos were acquired in the chosen observation areas. At least 100 lipoplexes were tracked for at least 200 frames in each experimental condition. Thereafter, acquired videos were analyzed using the Fiji software after application of a gaussian blur to facilitate the subsequent tracking. Lipoplexes were tracked and their trajectories were extracted by the particle tracker plug-in  (Sbalzarini and Koumoutsakos, 2005)  using the following set of parameters: radius 6-18, cut-off 0. 001, Per/ Abs 0. 1-0. 5, link range 2 and displacement 10. Positions of the lipoplexes at each time interval were then exported to the Igor Pro 8 software to calculate their mean squared displacements (MSDs) using the following equation: MSD = 1/(N -n) ∑ N-n i=1 |x i+n -x i | 2 , n = 1, ⋯, N -1 where N is the number of consecutive two-dimensional positions of a particle x i = (x i , y i ) recorded with a constant time interval Δt over a period of time T = (N -1)Δt.
Luciferase activity was normalized to the basal luminescence measured in untransfected cells (1. 9 × 10 5 , 1. 9 × 10 5 , and 2. 0 × 10 5 RLU/well in untreated and EGF-and allergen-treated cells, resp. ). (B) Luciferase activity in the Calu-3 2D-model (plate) and 3D-models (3-d ALI and 14-d ALI) exposed to the 1-to 6-based lipoplexes (N/P 4) or L2k/pDNA formulations. The luminescence of the untransfected cells was 2. 2 × 10 5 , 0. 7 × 10 5 , and 0. 4 × 10 5 RLU/well, in the 2D-model and the 3-d ALI and 14-d ALI models, resp. Data presented are mean values ± SEM from 3 independent experiments performed in triplicate. physical characteristics. To characterize the micro-rheology of the Calu-3 cell mucus, we analyzed by MPT the diffusive properties of 3/pDNA lipoplexes in mucus samples collected from the Calu-3 2D-and 3D-models.
On the contrary, confinement radiuses of transfection particles in the mucus from Calu-3 cells cultured on inserts at the ALI for Luciferase activity was normalized to the basal luminescence measured in untransfected cells (2. 5 × 10 4 , 2. 4 × 10 4 , 2. 8 × 10 4 , and 1. 2 × 10 6 RLU/insert for Calu-3, A549, NCI-H292, and 16HBE cultures, resp. ). Data are mean values ± SEM of 3 to 5 independent experiments performed in triplicate. Statistical differences between transfected and control cells was determined by the Student's test (**p < 0. 01 and ***p < 0. 001). (C) Orthogonal projection of (x,z) sections of Calu-3, A549, NCI-H292 and 16HBE cultures, as acquired by CLSM. Images were acquired from the top of the mucus layer (defined as z = 0 µm) to 40 µm depth. Mucins (red) are stained by Alexa-647®-labelled WGA and cover the apical membrane of the unstained cells located below the red fluorescent layer.
Percentages indicated on the graphs represent the amount of lipoplexes showing lower diffusion coefficients than the modal value observed in the mucus from Calu-3 cells grown in plates (dotted line). (D) Mean diffusion coefficients (bold line) of lipoplexes were calculated in each condition cited above. Data presented are mean values from 2 to 4 independent experiments (Calu-3 2D-model (○), 7-d ALI model (Δ), and 14-d ALI model (◇)). Statistical significance between the indicated groups was determined by one-way ANOVA followed by the Tukey's multiple comparison test with *p < 0. 05 and **p < 0. 001. (E) Mean diffusion coefficients of the lipoplexes in mucus from Calu-3 cells grown in plates or on inserts as a function of MUC5AC content in mucus samples (as determined by ELISA). 2002). As well, HDM allergen extract has previously been reported to activate the EGF-R in epithelial cells, supporting the 16-fold increase in MUC5AC production observed in our model  (Heijink et al.
, 2015). Those irregularities may lead to a lack of reproducibility in studies, which has to be considered  (Nafee et al. , 2018). Mucus is a complex material made of many components, and is characterized by a viscoelastic behavior. This behavior obtained with a model of mucus is of crucial importance when attempting to accurately mimic physical properties implicated in clearance and lubrication in the airways. In order to characterize the viscoelastic properties of mucus produced in the Calu-3 3D-models, rheological measurements were performed on the bulk undiluted material collected from the cultures. Viscoelastic data on human mucus secretions obtained from in vitro human tissue cultures grown at the ALI are very scarce. Protocols for sample preparation previously mentioned by  Hill et al.
5 ± 0. 6 • ). Interestingly, these properties are in line with previously reported rheological behavior of ex-vivo samples of human airway mucus  (Murgia et al. , 2017; Schuster et al. , 2013). Consistently, no transfection activity was detected in Calu-3 cells cultured for 7 d (data not shown) or 14 d at the ALI, whatever the gene carrier used. As macro-rheological properties of the mucus produced by the 14d Calu-3 3D-model translated into a viscoelastic behavior of the bulk material, this latter was used to investigate transfection particle diffusion. Experiments were performed with lipid 3-based lipoplexes by MPT. MSDs determined from acquisition of particle trajectories were fitted with a model of confined diffusion. Comparison of the diffusion coefficient distributions confirmed that the mucus produced by the Calu-3 2Dmodel lacks a mesh-like structure, and revealed an increased hindrance to the diffusion of the lipoplexes in the mucus produced by the Calu-3 3D-models.
Funding sources This work was supported by the  Agence Nationale de la Recherche ,  France  ( ANR-17-CE18-0034 ,  2017 ), the  Foundation for Frontier Research in Chemistry, Strasbourg, France  ( ANR-10-LBX-026-CSC, 2019 ), the  ITI InnoVec  ( ANR-10-IDEX-0002 ,  2020 ;  ANR-20-SFRI-0012 ,  2020 ), and  Vaincre la Mucoviscidose ,  Paris, France  ( RF20200502702/ 1/1/161 ,  2020 ).
ACKNOWLEDGMENTS The authors would like to thank  Dr. Lijun Zhong  from the  Centre of Medical and Health Analysis (PUHSC ) for MALDI-TOF experiments. The authors would also like to thank  Dr. Fen Liu  and  Dr Jing Wang  from the  State Key Laboratory of Natural and Biomimetic Drugs (PUHSC)  for their help in conducting the NMR and SPR experiments, respectively.
Fluorescence was measured by ow cytometry with a suitable bandpass lter. Statistical Analysis. Individual experiments were performed at least in triplicate. Data were expressed as mean ± SEM. Signi cant differences were determined using 2-tailed Student's test; level of signi cance set at * P < 0. 05, ** P < 0. 01, and *** P < 0. 01, with P < 0. 05 considered statistically signi cant.
Results Selective inhibition of the viability of HT-1080 by TQ. We rst evaluated the concentration and timedependent effect of TQ on the viability of HT-1080 cell. HT-1080 cells were treated with increasing TQ concentrations for 24 and 48 hours, followed by determination of their viability (UptiBlue assay). Data from Fig. 1A  indicated that TQ induced a signi cant dose-dependent cytotoxic effect on HT1080 viability. Recorded IC 50 values for 24-and 48-hours treatment periods were 39 µM and 36 µM, respectively. Induction of apoptosis by TQ in HT-1080 cells. We examined if TQ-induced cytotoxic effect involved induction of apoptosis. HT-1080 cells were treated with TQ at 5 µM and 10 µM, and apoptosis was assessed by annexin-V/PI assay and ow cytometry. Data presented in Fig. 1B  demonstrated that TQ induced apoptosis in HT1080 cells, at rates of 24% and 41% for 5 µM and 10 µM TQ concentrations, respectively.
To con rm that TQ-induced apoptosis involved caspase activation, we assessed the proteolytic activity of caspase-3 and analysed the cleavage of pro-caspase-3 into caspase-3 by Western blotting. Data from Fig. 1C  showed that TQ-induced pro-caspase 3 cleavage correlated with increased caspase-3 activity. Collectively, these data con rmed that TQ-induced apoptosis involved the caspase-3 pathway. Arresting cell-cycle progression of HT-1080 by TQ. Since drug-induced apoptosis was associated with altered cell-cycle progression, we examined the effect of TQ on cell distribution in the different cell-cycle phases by ow cytometry on PI-stained cells. Data of Fig. 1D  demonstrated concentration-dependent increases in G2/M cell percentage in 5 µM (47. 00 ± 2. 17%) and 10 µM (50. 00 ± 2. 33%) TQ-treated cells, as compared to control cells (18.
Case study: Role of AA substitutions in SULT1A1 variants on drug metabolism The first crystal structure of SULT1A1 was reported for SULT1A1*2 [Protein Data Bank (PDB) ID: 1LS6]. 30 Later, the structures of SULT1A1*1 (PDB ID: GRA) and SULT1A1*3 (PDB ID: 4Z28) were also resolved. Their comparison allows the analysis of structural bases involved in the altered metabolism of SULT1A1*2 and SULT1A1*3. The flexibility of SULT is a well- Relative comparative sulfation activity of SULT2 allozymes toward endogenous steroids and tibolone steroid drugs. -Cholesterol 21. 9 a Comparative in vitro activity was compiled from reported specific activities V max (and V max /K m in brackets): --, strongly decreased; -, decreased; =, similar; +, increased; n. e. , no detectable activity; empty cell, not reported.
The locations of residues R213 and M223 are shown in Figs. 1a  and 2a. We used molecular dynamics (MD) simulations for the major allozymes of SULT1A1, *1, *2, and *3 to obtain insights into conformational flexibility changes resulting from the two mutations. We note here the alloforms with a bound substrate as 'HOLO', and without bound substrate as 'APO', respectively. The simulations of all structures were performed here in the presence of the bound cofactor PAP. Previous MD simulations  12, 14, 15, 17, 110  showed that PAPS and PAP have similar stabilizing effects on SULT structures. To perform MD simulations, we used the crystal structures of the SULT1A1 co-crystallized with the cofactor PAP [PDB IDs: 4GRA, 111 2D06,  112  and 1Z28  113  corresponding to SULT1A1*1 (WT) in APO state, *2 (R213H) with bound 17bestradiol ('E2') in HOLO state and *3 (M223V) in APO state, respectively].
, 2021 ; Moreno et al. , 2006 ). More recently, work has reported on neuroimaging findings  ( Abdallah et al. , 2017 ; Daws et al. , 2022 ) , and current studies are underway for patients with chronic anorexia nervosa (NCT04052568) and obsessive-compulsive disorder (NCT03356483). This significant growth in the literature requires new approaches to review and analyze trends within the knowledge domain. Scientometrics -i. e. , bibliometrics when applied to science research -allows one to summarize large amount of bibliometric data in order to present the state of knowledge and emerging trends of a research topic over time. Distinct from the systematic review, scientometric analysis mainly uses co-cited articles to extract clusters of highly cited articles, revealing research trends and influence networks.
Search strategy and data collection The Web of Science Core Collection (WOSCC) was explored using different keywords and medical subject headings, such as 'psilocybin', 'ketamine' or 'LSD'. Considering the focus on clinical research, several terms not relevant to psychedelics or human studies were excluded. The full list of search terms is available in the published protocol. There were no limitations on language, time or populations. The database source was limited to Science Citation Index Expanded, publication types to articles, reviews and proceedings papers. Irrelevant categories (e. g. , astronomy) and meeting abstracts were also excluded. Reasons for exclusion are presented in the flow-chart (Supplementary Fig. 1 ). The full records with cited references were retrieved on March 18, 2022, into tag-delimited plain text files.
Data analysis The Bibliometrix R package (3. 1. 4) ( Aria and Cuccurullo, 2017 )  was used to extract information on authors and journals. CiteSpace (version 6. 1. R3)  ( Chen, 2006  ) was used to extract co-citation analyses (for co-cited references, co-authors countries, institutions, co-authorship networks), co-occurrence networks (authors' keywords), and conduct burstness analyses. Citation counts are the number of direct citations to a publication. Co-citation analysis extracts pairs of papers that are cited together in the source articles  ( Small, 1973 ) , and co-occurrence networks count paired data within a collection unit. Co-cited network and co-occurrence networks are both undirected graphs. Different units of measure were therefore used: author, journal, reference, country, institution, and keyword.
References retrieved Our dataset retrieved 41,135 documents. Following the data filtering process detailed in our protocol, 19% of the total documents were excluded (Supplementary Fig. 1 ). The final dataset retained 31,867 documents (28,579 articles; 3,288 reviews) cumulating 591,329 references from 2,809 different sources (e. g. , journals, books). Articles in 22 different languages were found, with 95. 5% being in English. On the 168 highly cited articles and 10% of the randomly selected articles, less than 3% of the articles were non-relevant (Supplementary Table  1 ). The first identified paper is the Carter paper from 1901 on three case of poisoning mushrooms  ( Carter, 1901 ). The analysis of scientific production on psychedelics reveals two essential time periods. The first time period with a mean annual growth rate of 4.