dataesr/scientific-paragraphs-categorization huggingface dataset:
For each database query, the two screening steps and the quality scoring were subject to a dual assessment (D. M. and A. O. G. ), which may have limited sources of bias. While findings in children and youth pharmacogenetics are conflicting regarding olanzapine, clozapine, and loxapine, the benefits of genotyping in clinical use may be limited by lack of sufficient evidence, the barriers to routine use, and overall impact  [95]. However, the dose-effect relationship is significantly influenced by cytochromes, holding sway over exposure to the medication  [96]. Yet, in comparison with CYP2D6, CYP1A2 remains less investigated, while olanzapine and clozapine's ADRs are serious. Furthermore, cases of major clinical improvement were fostered by CYP1A2 genotyping  [11] , although its benefit is not collective yet.
The S1 subunit of S protein attaches to ACE2 receptor, which is found on the surface of target cells. In addition to this, the transmembrane protease, serine 2 (TMPRSS2) processes S protein into its constituent subunits, S1 and S2, thus allowing the virus to fuse into the plasma membrane of the host cell. As HDHODH is a druggable target against SARS-CoV-2, we were interested in probing the inhibitory effect of Teriflunomide and compounds 16 and 17 against SARS-CoV-2. Teriflunomide was the most cytostatic with effects at concentrations above 0. 78 μM. 16 had cytostatic effects at concentrations > 3. 1 μM and DMSO had no measurable effect. An infection inhibition assay showed that none of the compounds had an inhibitory effect against SARS-CoV-2 infection in the infected cells. The normalised data show that Teriflunomide and 16 have no effect on the efficiency of infection (Fig  S2 ).
Acknowledgements The authors acknowledge financial support from the  ERDF  (LabFact: InterReg V project  121 ), HEIF  Covid- 19 Emergency Funds (University of Sussex ), the  Ewart Bequest Fund  ( University of Sussex ),  EPSRC  ( EP/P026990/1 ),  Oxford COVID  development fund, and  Wellcome Trust for Institutional Strategic Support Fund (ISSF)  ( University of Sussex ). This work was partly conducted as part of the  Covid Moonshot Consortium  (https://postera. ai/moonshot/) and we are grateful for their support. The authors also thank the  Diamond Light Source  for beam time (proposal mx19301) and the staff of beamlines I03 for assistance with crystal testing and data collection. The SGC is a registered charity (number  1097737 ) that receives funds from  AbbVie ,  Bayer Pharma AG ,  Boehringer Ingelheim ,  Canada Foundation for Innovation ,  Eshelman Institute for Innovation ,  Genome Canada ,  Innovative Medicines Initiative  ( EU/EFPIA) [ULTRA-DD  grant no.
The recommended methodology is that of the (Franz) diffusion cell. When infinite dose conditions of exposure are used, skin absorption may be expressed using receptor fluid data alone, which permit the calculation of a permeability constant (or co-efficient) (K p ). The Guideline recommends the parallel analysis of relevant reference chemicals, preferably of a lipophilicity close to the test substance. Post publication of the OECD Test 428, Franz et al. performed an evaluation of the kinetics of drug absorption through excised human skin, to demonstrate the suitability of the technique for studies of the bioequivalence of topical products  [55]. Using generic topical drug products, the percutaneous absorption as measured using a Franz diffusion cell was compared to that of their corresponding reference products during preclinical development and to clinical data, post regulatory approval.
Raman microspectroscopy of skin Raman spectroscopy (RS) provides a label free, fingerprint of the chemical composition of a sample. Similar CLSM  [66] , in its confocal microscopic mode, confocal Raman microspectroscopy (CRM) can spatially profile the chemical composition of samples in the lateral or axial directions, in situ, with resolution of the order of microns, or even submicron, depending on the wavelength of the source. In spatial mapping, each pixel contains a Raman spectrum, which is a complex superposition of the spectral features of each of the constituent biochemical. Increasingly, multivariate statistical analysis has been employed to, for example, spatially cluster spectra of similar profiles, reduce the dimensionality according to principle components to cluster and differentiate spectral groups within a dataset, and/or correlate systematic variations of features by regressing against external variables such as time, distance or concentration  [67].
GRI = (G1/1) + (G2/2) + …+ (Gx/x) (2) G1 = germination percent in first day. G2 = germination percent in second day to final experiment, MGT = (fx) / f (3) where f is the number of newly germinated seeds on each day and x is the day of counting, GI = (7 * N 1 ) + (6 * N 2 ) + (5 * N 3 ) + … (4) N1, N2,. = the number of germinated seeds in first day, second day and. , VI = GP × Seedling length (SL) (El- ouaer & Hannachi, 2012), (5) Also, fresh shoot mass, fresh root mass, shoot length, root length, dry shoot mass and dry root mass were measured. Mass of root and shoot were measured from the sample mass before and after drying at 70 °C for 12 h. the data were analyzed using SAS software, and means comparisons were done by the least significant difference test (LSD) at p < 0. 05 level of confidence.
Acknowledgements This work has been conducted within the  International Associated Laboratory LEMIR (CNRS/CONICET ) and was supported in part by  CNRS ,  CONICET, FONCyT, SeCyT-UNC  and by the '' ADI 2019 '' project funded by the  IDEX Paris-Saclay ,  ANR-11-IDEX-0003-02. The computations were performed at the  HPC resources from the ''Mesocentre'' computing center of Centra-leSupelec and Ecole Normale Superieure Paris-Saclay  supported by  CNRS  and  Region Ile-de-France  (https://mesocentre. centrale supelec. fr/)and the HPC resources Meso-LUM from ISMO and MAGI from  University Paris 13.
During the preparation of this work  Bertrand Toën  was partially supported by  ERC -2016-ADG-741501. Tony Pantev  was partially supported by  NSF  research grants  DMS-1601438  and  DMS-1901876 , by  Simons Collaboration  grant #  347070 , and by the  Laboratory of Mirror Symmetry NRU HSE, RF Government  grant, ag. No  14. 641. 31. 0001.
1 M Bis-Tris-HCl, (pH 6. 5), 0. 2 M ammonium acetate and 30% ethylene glycol for cryoprotection. The cryoprotected crystals were flash frozen in liquid nitrogen. Structural determination and refinement. The diffraction data were collected at 100 K at the beamline BL41XU in SPring-8 (Hyogo, Japan) and then processed using the program HKL2000  49  and the CCP4 program suite  50. All complex structures presented in this study were determined by molecular replacement using the program MolRep  51. The crystal structure of the Rabex-5 MIU-Ub complex (PDB 2FID) was used as the search model. The atomic models were built to fit 2F o -F c electron density map by using the program COOT  52. Structure refinement was carried out by using the program Phenix  53. The final models obtained after iterative correction and refinement have excellent stereochemistry with R free values of 24.
0 and pH 4. 5, respectively). Ub 2 species were injected for 60 s at a flow rate of 10 μL per min. Equilibrium dissociation constants (K d ) were computed by fitting steady-state binding level (R eq ) to a 1:1 interaction model (R eq = Concentration × R max /(K d + Concentration) + Offset) using Biacore T200 evaluation software (GE Healthcare). All assays were carried out thrice for each sample. The data are presented as mean ± standard deviation. CD measurements. CD spectra were measured in 10 mM sodium phosphate buffer (pH 7. 5) at 25 °C with a J-750 CD spectrophotometer (JASCO) equipped with a quartz cuvette of a 1. 0-mm light path. The concentrations of the samples were adjusted to 0. 1 g L -1. Four scans from 250 to 190 nm were averaged. The data were processed using the Spectra Manager software (JASCO).
Acknowledgements We thank  Drs. Takatoshi Arakawa  and  Shinya Fushinobu  for technical help during CD measurement. We thank the beamline staff of macromolecular crystallography beamlines of  Photon Factory (Tsukuba, Japan ) and  BL41XU of SPring-8 (Hyogo, Japan ) for technical help during data collection. We also thank  CentMeRE, Graduate School of Medicine ,  Osaka University  for technical assistance. This work was supported by  Grantin-Aid for Scientific Research on Innovative Areas 22121003  (S. F. ),  15H01175  (Y. S. ),  15H01183  (S. N. ),  Grant-in-Aid for Scientific Research  (A) 24247014 (S. F. ) and 26241014 (S. N. ),  Grant-in-Aid for Young Scientists  (A) 24687012 (Y. S. ),  Grant-in-Aid for Scientific Research (B)   16H04750  (Y. S. ),  Grant-in-Aid for Scientific Research  (C) T17K00550 (Y.
Data availability. Coordinates and structure factors of RNF168 UDM1-K63-Ub 2 (form I), RNF168 UDM1-K63-Ub 2 (form II), RNF168 UDM1-K63-Ub 2 (tetrameric form), and RNF168 UDM2ΔC-K63-Ub 2 have been deposited in the Protein Data Bank under accession codes 5XIS, 5XIT, 5YDK, and 5XIU, respectively. Other data are available from the corresponding authors upon reasonable request.
Residual water content Water content contained in the powders was determined by Thermo Gravimetric Analysis (TGA) on NETZSCH TG 209F1 (NETZSCH-Gerätebau, Germany) using NETZSCH Proteus 6. 1 software to analyze the data. About 5 mg of the powder were placed in ceramic crucibles and heated from 20 to 1000°C at a heating rate of 10°C/min, under a nitrogen atmosphere with a nominal gas ow rate of 30 mL/min. In addition, the water content of the particles was quanti ed by Karl-Fischer titration using an 889 KF Coulometer (Metrohm Ltd. , Herisau, Switzerland) equipped with an oven (860 KF Thermoprep). A solution of hydranal (HYDRANAL™ -Coulomat AG) was used as titrant. The air ow rate was set at 100 mL/min and the oven temperature at 120°C. The extraction time was set at 500 s and the drift time was 10 µg/min.
14. 1 Cell culture conditions Immortal keratinocyte (HaCaT) cell line derived from normal adult human skin was purchased from CLS Cell Lines Service GmbH (Eppelheim, Germany-accession number 300493)  [27]. The cells were cultured with Dulbecco's modi ed Eagle's medium (DMEM) containing 10% (v/v) fetal bovine serum (FBS) and 1% (v/v) penicillin-streptomycin, at 37°C in a humidi ed atmosphere of 5% CO 2 / 95% air.
Founding The research leading to these results has received funding from the  National Research Agency (ANR) ,  HyDNano  project ( ANR-18-CE18-0025-01 ). This work was supported by a grant from  Regione Campania (I) -POR  Campania  FESR 2014/2020  " Fighting Cancer resistance: Multidisciplinary integrated Platform for a technological Innovative Approach to Oncotherapies (Campania Oncotherapies )" [Project N. B61G18000470007]. Authors and A liations  Dipartimento Di Farmacia, Università Degli Studi via Giovanni Paolo II ,  132 ,  84084  Fisciano, SA,  Italy Chiara Amante ,  Pasquale Del Gaudio ,  Stefania Marzocco University of Lyon ,  Université Claude Bernard Lyon 1, CNRS ,  LAGEPP UMR 5007 ,  43 Bd 11 Novembre 1918 ,  69622 ,  Villeurbanne ,  France Valentina Andretto ,  Annalisa Rosso ,  Geraldine Augusti ,  Giovanna Lollo.
Acknowledgements The authors are much grateful to the  French Ministry of Higher Education, Research and Innovation  (PhD grant for J. B. ), the  CNRS  (Emergence@INC2019 support to A. P. ) and the  French Agence Nationale pour la Recherche (ANR)  (grant number  ANR-18-CE07-0007-01 , CLABCat) for financial support. The  Université de Strasbourg  is also kindly acknowledged. We thank  L. Karmazin  and  C. Bailly  from the  Service de Radiocristallographie de la Fédération de Chimie Le Bel FR 2010  for SCXRD analyses.
These three actions require the implementation of an efficient pharmacovigilance system. The first WHO collaborating center was created in Uppsala, Sweden (UMC) in 1978  [2]. Morocco and South Africa became the first African collaborating countries in 1992  [4]. The pharmacovigilance system in African countries is essentially characterized by spontaneous reporting, the inadequacy of local databases and the absence of tools for automatic generation of pharmacovigilance signals  [4]. Burkina Faso is no exception to this observation, until 2013 the Sourô SANOU University Hospital (CHUSS) of Bobo-Dioulasso was the only hospital center to dedicate a service to pharmacovigilance  [5]. This service is responsible for the detection, notification, analysis of adverse drug events and the use of this information for prevention purposes.
Materials and Methods The study on the implementation of an automated management system of EIs was carried out at the CHUSS of Bobo Dioulasso which is a hospital of last resort in the health pyramid of Burkina Faso. At the server level, the programming language used is PYTHON 3. 9. The HTML5, Javascripts and CSS3 languages were used to display, style and make dynamic the web elements of our pages. In order to avoid repetition of identical procedures during the creation of the web solution, we opted for the DJANGO Framework which is developed in python and responds to the DRY slogan " Don't Repeat Yourself ". This framework is open source and is dedicated to web development. Moreover, it uses an MVT 2  model which is inspired by the MVC 3  model. For the web server we used Apache 2. 0. However, as almost all web servers do not communicate natively with python, we needed an interface to ensure this communication and DJANGO supports two interfaces which are WSGI  4  and the new standard ASGI  5.
Discussion Our objectives were to make available a database capable of responding in real time to the recording, analysis and restitution of data from the pharmacovigilance service. Our results show that these objectives have been achieved because we have developed an application that takes into account: the modules of recording, management and analysis of adverse drug reactions. The evaluation of our system is in progress through the compilation of the paper files already collected on the years spent in the pharmacovigilance service. The implementation of our system is a great innovation in the field of pharmacovigilance in our country and in the African sub-region, although it needs improvement, which are the next steps of this work. These are the integration of the dictionary of adverse reactions such as MedDRA, the International Classification of Medicines (ATC, EphMRA) etc.
Extracts Characterization by UPLC-UV-MS Ultra-High Performance Liquid Chromatography (UPLC) analyses were performed on an Acquity UPLC H-Class system (Waters, Guyancourt, France) coupled with a Diode Array Detector (DAD) and a QDa ESI-Quadrupole Mass Spectrometer. All data were acquired and processed using Empower 3 software. Separation was achieved using an ACQUITY UPLC ® BEH phenyl 1. 7 µm (2. 1 × 100 mm) column (Waters, Milford MA). Gradient elution was performed with (A) 0. 1% formic acid in water and (B) 0. 1% formic acid in acetonitrile at a flowrate of 0. 3 ml/min. The amount of B was increased from 5% for the initial 1 min to 30% at 9 min, and to 100% at 9. 5 min. The condition was then kept at 100% B until 10. 5 min. Finally, the column was reequilibrated to 5% B in 0. 5 min and maintained for an additional 2 min, resulting in a total run time of 13 min.
Acknowledgment The authors are grateful to the  Princess Nourah bint Abdulrahman University Researchers Supporting  Project number ( PNURSP2022R39 ),  Princess Nourah bint Abdulrahman University, Riyadh ,  Saudi Arabia  and Researchers Supporting Project number ( RSP-2021/97 ),  King Saud University, Riyadh ,  Saudi Arabia. M. D. W. thanks the  French Agence Nationale de la Recherche  and the  Région Pays de la Loire  for financial support on Covid-19 research (ANR Flash COVID 19 call -name: CoV2-E-TARGET -grant number:  2020 07132 ). In addition, our appreciation goes to  Landmark University, Omu-Aran, Nigeria.
The IR spectra from the samples in a neat form were measured with a Thermo Scientific Nicolet iS10 FT-IR spectrophotometer. IR absorption frequencies are given in cm -1. Optical rotations were measured at 20 °C with a Perkin Elmer 341 polarimeter and were given in g -1 ⋅cm 3 ⋅dm -1. Low-resolution mass spectra (MS) were recorded with a Perkin-Elmer Sciex API 300 spectrometer [ionspray (IS) mode] (PerkinElmer Inc. , Waltham, MA, USA). High-resolution mass spectra (HRMS) were recorded with a Bruker MaXis spectrometer [electrospray ionization (ESI) mode] (Bruker DaltonikGmbH, Bremen, Germany). 1 H, 13 C NMR spectra and HRMS data of all new compounds are provided in Supplementary Materials as Figures S1-S38.
The IR spectra from the samples in a neat form were measured with a Thermo Scientific Nicolet iS10 FT-IR spectrophotometer. IR absorption frequencies are given in cm -1. Optical rotations were measured at 20 • C with a Perkin Elmer 341 polarimeter and were given in g -1 •cm 3 •dm -1. Low-resolution mass spectra (MS) were recorded with a Perkin-Elmer Sciex API 300 spectrometer [ionspray (IS) mode] (PerkinElmer Inc. , Waltham, MA, USA). High-resolution mass spectra (HRMS) were recorded with a Bruker MaXis spectrometer [electrospray ionization (ESI) mode] (Bruker DaltonikGmbH, Bremen, Germany). 1 H, 13 C NMR spectra and HRMS data of all new compounds are provided in Supplementary Materials as Figures S1-S38.
Nitric oxide (NO) measurement The NO production in the cell culture medium was estimated by using Griess Reagent kit. The level of nitrite (NO 2-) (a stable end product of NO metabolism) was detected for the accumulation of NO. After incubation, 50 µL cell suspensions were taken from each well to new 96-well plates. Then 50 µL Griess Reagent I and Griess Reagent were added respectively. The absorbance was measured at 540 nm. The data from each concentration was measured using ve technical replicates. Ibuprofen (1 mM) was used as positive control group.
RNA isolation and quantitative polymerase chain reaction (qPCR) Cells were seeded in 75 cm 2 cell culture ask, treated with or without ALOE (3 mg/mL) while stimulating with LPS (10 µg/mL) for 24 h. Total RNA was extracted using Trizol reagent according to the manufacturer's instructions. The RNA samples were treated with DNase I to remove genomic DNA and then reverse transcribed using oligo-dT primers. The rst-strand cDNA served as a template for the realtime PCR reaction. qPCR was performed using SYBR Green qPCR kit reagent following the instructions of the manufacturer. The primers for detecting the expression of iNOS, COX-2 and GAPDH were designed using the Primer Premier 5. 0 software program as follows: iNOS-Forward-5'-AGCAACTACTGCT GGTGGTG-3', iNOS-Reverse-5'-TCTTCAGAGTCTGCCCATTG-3'; COX-2-Forward-5'-CTGGAACATGGACTCACTCAGTTTG - 3', COX-2-Reverse-5'-AGGCCTTTGCCACTGCTTGT-3'; GAPDH-Forward-5'-GGCCTTCCGTGTTCCTACC-3', GAPDH-Reverse-5'-TGCCTGCTTCACCACCTTC-3'.
Furthermore, homology-based monoterpene indole alkaloid gene predictions together with a metabolic analysis across 4 different V. minor tissue types guided the identification of candidate monoterpene indole alkaloid genes. These candidates were finally used to identify monoterpene indole alkaloid gene clusters, which combined with synteny analysis allowed for the discovery of a functionally validated vincadifformine-16-hydroxylase, reinforcing the potential of this dataset for monoterpene indole alkaloids gene discovery. It is expected that access to these resources will facilitate the elucidation of unknown monoterpene indole alkaloid biosynthetic routes with the potential of transferring these pathways to heterologous expression systems for large-scale monoterpene indole alkaloid production.
Gene model prediction and functional annotation RNA-seq based gene model prediction was performed using 8 RNA-seq samples (accession number PRJEB40906) including samples from young leaves, old leaves, and adventitious roots exposed to high light and low light conditions  (Stander et al. 2020). The RNA-seq reads were individually aligned to the V. minor genome using HiSAT2 (v. 2. 2. 1,  Kim et al. 2019 ) and the resulting RNA-seq alignments were assembled into transcripts using  StringTie (v. 2. 1. 7, Pertea et al. 2015). Next, the 8 individual transcriptomes were merged using stringtie -merge into a nonredundant set of representative transcripts (v2. 1. 7, Pertea et al. 2015). The consensus transcriptome was then functionally annotated with the Trinotate pipeline (v3. 0. 1,  Bryant et al. 2017 ) that combines BlastX (v.
2. 6. 0-1, Camacho et al. 2009)  and BlastP (v. 2. 6. 0-1, Camacho et al. 2009 ) results from TransDecoder (v. 5. 5. 0, Haas et al. 2013)  predicted ORFs against the Uniprot database, and hmmscan  (v. 3. 1b2, Finn et al. 2011)  against the PFAM database (https://pfam. xfam. org/).
Assembly completeness assessment Assembly statistics were obtained using the stat bash program of the BBMap tool  (v. 38. 94, Bushnell 2014). Genome assembly quality was also evaluate using the k-mer based method merqury  (v. 1. 3, Rhie et al. 2020). Therefore, 20-mers database was constructed from Illumina short-reads using count function from meryl  (v. 1. 3, Koren et al. 2018). Base level consensus quality score (QV) was estimated from k-mer survival rate. Genome coverage by Illumina short-reads was estimated to gain insight into the level of continuity of the final assembly. Reads were firstly aligned using  bwa-mem2 (v. 2. 2. 1, Vasimuddin et al. 2019). Resulting SAM file was sorted using samtools sort (v. 1. 16. 1,  Li et al. 2009 ) and the contig median coverage was calculated from samtools coverage.
To assess the genome and gene annotation completeness, Benchmarking Universal Single-Copy Orthologs  (BUSCO v. 5. 2. 2, Simão et al. 2015)  was applied with default setting using a plant-specific database of 2,326 single-copy orthologs. Number of annotated genes and associated statistics were obtained using agat_sp_statistics perl script from AGAT package (v. 0. 8. 0,  Dainat et al. 2022). Illumina RNA-seq reads used to perform gene annotation were mapped against the annotated genome using the splice-aware aligner  STAR (v. 2. 7. 10a, Dobin et al. 2013)  to gain more insight into the gene annotation quality.
GO enrichment GO term enrichment analysis based on the GO classification was performed by comparing the relative occurrence of a GO term into increased orthogroups gene list to its relative occurrence in the genome by a Fisher's Exact test (2-sided) with the R function topGO (v. 2. 44. 0, Alexa and Rahnenfuhrer 2022). A Benjamini-Hochberg adjusted P-value of 0. 05 was used as the cut-off criterion. Enriched GO terms were grouped based on semantic similarities using rrvgo package (Rel method, cut-off 0. 7, v. 1. 4. 0, Sayols 2020). Enriched terms graphs were performed using ggplot2  (v. 3. 3. 5, Wickham 2011).
Whole-genome duplication analysis The DupPipe pipeline  (Barker et al. 2010)   (Birney et al. 2004 ) was then used to align each gene DNA sequence against its best hit homologous protein sequence from the database in order to annotate its open reading frame and predict the resulting amino acid sequences for each gene. MUSCLE (v. 3. 6, Edgar 2004 ) then align the amino acids sequences for each gene pair to guide the nucleic acid alignments using  RevTrans (v. 1. 4, Wernersson and Pedersen 2003). Finally, substitutions per synonymous site (Ks) are calculated using codeml's F3x4 model from the PAML package (v. 4. 9, Yang 1997) to determine the divergence times between gene pairs. The resulting age distributions (Ks) were plotted using ggplot2  (v. 3. 3. 3, Wickham 2011 ) in R (v. 3. 6. 3, R Core Team 2013).