dataesr/scientific-paragraphs-categorization huggingface dataset:
Our findings are consistent with results of other studies, showing that spin is frequent in the entire medical literature  [ 9 , 12 ]. A systematic review of 35 spin studies evaluated a median prevalence of spin of 67% (from 10% to 84%) in clinical trials, observational studies, diagnostic accuracy tests and systematic reviews  [13]. It has been shown that the impact of spin in published articles is further enhanced by dissemination through press releases and news items  [ 19 , 20 ]  and leads to misinterpretation of the study findings by readers  [ 21 , 22 ]. In pharmacovigilance studies, such practices may result in unjustified safety warnings that may affect physician or patients behaviors  [23]. Spin in pharmacovigilance studies may arise from ignorance of the limitations of disproportionality analysis and spontaneous reporting system databases, imitation of previous practice, or willful intent to enhance sensationalism and newsworthiness of the results so as to be published in higher ranking journals  [ 8 , 24 , 25 ].
The development of reporting recommendations, endorsed by journal editors, may help to reduce the level of spin in published pharmacovigilance disproportionality studies. We also encourage peer reviewers and journal editors to check for inappropriate use of causal language, especially in the abstract and manuscript conclusions. Although, to date, the only RCT aiming to reduce the prevalence of spin in biomedical literature by sending instructions to the authors during the submission process failed to demonstrate a significant impact. The education of authors and peer reviewers on the limits of disproportionality analyses may also be one of the key avenues for improvement  [26]. Our study has several strengths and limitations. Since we conducted our study using a randomized sample of studies indexed in PubMed, our results should only be representative of disproportionality analyses published in journals indexed on this database.
In Europe, the reinforced surveillance system in place relies on the complementary strengths of pharmacovigilance and pharmacoepidemiology. For the early identification of safety signals, the performance of pharmacovigilance and the analysis of spontaneous reporting databases are unequalled to date  [1]. From a limited number of very unusual cases, pharmacovigilance activity can allow detecting very quickly safety signals relating to adverse effects not previously identified during preclinical or clinical studies including large phase III randomized clinical trials. This ability to rapidly spot such safety signals is due to the extraordinary surveillance capacity of the globalized pharmacovigilance system to which each country or group of countries contributes. In the case of France, as detailed in the article by Micallef et al.
, the cases reported continuously to the system are analyzed daily by the Regional Pharmacovigilance Centers  [2]. The results of this medico-pharmacological analysis, together with the information on the case that is completed whenever necessary by a return to the reporter, are also transmitted daily to the National Pharmacovigilance Database. Shared at the European level, this information and the synthesis of the expertise that is carried out each week allows for the detection of safety signals in real time, the only limits of which are linked to: 1-the analysis and processing capacities (in terms of human resources), 2-the frequency of occurrence and notification of adverse events (also relating to the rhythm of the vaccination campaigns and the number of vaccinated subjects), and 3-the possibility of identifying cases with an atypical presentation.
This will potentially be responsible for pharmacovigilance overload as the solicited reporting is likely to retrieve an important amount of common side effects (e. g. reactogenicity, headache, nausea) of no interest for signal detection, little interest for safety monitoring, and high treatment burden for pharmacovigilance systems which will have to treat these data as any other report. Aside of these, these mostly include study performed through the secondary use of electronic healthcare databases (German, Dutch, Danish, Spanish, Italian, British, Norwegian, and French). In those, detection analyses will be run in first step, which results will be enriched by rapid assessments using ecological or self-control risk interval methods, before ad-hoc studies are performed if needed to confirm/finally quantified risk increase and associations.
Similar activities including rapid cycle analyses and ulterior ad-hoc studies investigating specific safety signals are planned by the US Food and Drug Administration (FDA) in the context of the Sentinel Network activities. Finally, national regulators also have scheduled some pharmacoepidemiological activities, as it is the case in France through the ''Groupement d'Intérêt Spécifique EPI-PHARE'' (GIS EPI-PHARE), a joint structure from the French ANSM and the French Health Insurance (CNAM). Only its general action programme (SARS-Cov-2 vaccine monitoring) is known to date  [12]. These activities are notably facilitated by the collection of specific national data regarding vaccines, COVID hospitalizations and COVID screening tests in addition to the usual health care reimbursement collected data, which will be soon made accessible to all researchers by the French Health Data Hub.
In addition to the regulators actions, the risk management plans accompanying marketing authorization also include some specific pharmacoepidemiological studies to be led by the pharmaceutical companies  [13] [14] [15] [16]. The Comirnaty ® Pfizer-BioNTech risk management plan thus includes four non-interventional studies to be performed from. These comprise three secondary databases analyses aimed at estimating incidence rates of safety events of interest, one in a cohort of US active military and their families, one in a cohort of US veterans, and one in a cohort of COVID-19 vaccinated subjects in the EU, and a field cohort study of vaccinated EU citizens which will monitor the safety of the vaccine in real-world setting. Similar studies are comprised in the Vaxzevria ® Oxford AstraZeneca vaccine risk management plan, which includes a pregnancy subcohort, and which planned secondary health data sources studies both aims at assessing baseline incidences and estimating relative risk of safety concerns including adverse event of specific interest (AESIs) among all populations targeted for vaccination and in specific populations as in patient with immunodeficiency or treated with immunosuppressants.
Vaccine serogroup samples Kinetic models were built for each meningococcal conjugated polysaccharide serogroup (A, C, W and Y) from four good manufacturing practice lots of MenACYW-TT (final fills stored in USP Type I borosilicate glass vials) fully liquid vaccine containing 10 µg of meningococcal A, C, W and Y polysaccharide antigens, individually conjugated to tetanus toxoid protein, and formulated in 0. 67% sodium chloride and 30 mM sodium acetate, pH 5. 5-6. 5  (Sanofi Pasteur Inc, 2020). Longterm stability data from three clinical lots, manufactured at the same scale, were used to verify the accuracy of the model.
Polysaccharide quantitation by HPAEC-PAD was done by acidhydrolyzing the total polysaccharide and free polysaccharide samples using the analyte peaks resulting from hydrolysis as mannosamine-6phosphate for serogroup A, glucose for serogroup Y, galactose for serogroup W and N-acetyl neuraminic acid for serogroup C. The free unconjugated polysaccharide proportion (%) was calculated as the ratio of free to total. Data obtained at 5 • C up to six months could not be used to build the kinetic model because the free polysaccharide levels were generally below the limit of quantification (LOQ). The data at 5 • C obtained after longer time durations (at 9, 12 and 18 months for the four lots used to build the kinetic model, and 36, 42, 48 months for three clinical lots) were used to confirm the accuracy of the model (with 99% prediction bands).
Advanced kinetic modeling and stability predictions We applied a general procedure following 'good modeling practices'  (Roque et al. , 2021; Clenet, 2020) , combining advanced kinetics and statistical analyses of the vaccine stability datasets obtained at 25 • C, 45 • C and 56 • C to identify kinetic models which best describe the increase of free polysaccharide for the individual serogroups. AKTS-Thermokinetics software (version 5. 3, AKTS AG, Advanced Kinetics and Technology Solutions, Siders, Switzerland) (AKTS, 2020) was used to screen and compare kinetic models describing the S-shaped profiles (Eq (1)) for the serogroup-specific free polysaccharide increase as a function of time and temperature in a similar manner previously described  (Clénet, 2018; Clénet et al. , 2019; Clénet et al.
While storage of the vaccine product in a freeze-dried form slows the degradation of the vaccine, it can cause some challenges from a technical point of view as well as in terms of patient safety. Indeed, numerous administration errors involving a lyophilized meningococcal conjugate vaccine have been reported in the Vaccine Adverse Event Reporting System (VAERS) database  (Su et al. , 2016). Furthermore, development of a lyophilized format requires more effort and is more expensive than liquid format (lyophilization recipe, addition of a diluent for reconstitution of the product plus addition of specific excipients [polysaccharides, cryoprotectants], and addition of specific characterization package [residual moisture content, cake appearance, glass transitions, time of reconstitution, appearance after reconstitution])  (Ward et al.
Acknowledgements The authors express their thanks to  George Firmstone  for data analysis and critical review of the manuscript,  Philippe Talaga  for input into the study design and critical review of the manuscript,  Arun Arunachalam  for analytical input and critical review of the manuscript,  Christine Prost  and  Philip Oster  for the critical review of the manuscript. Editorial assistance with the preparation of the manuscript was provided by  Richard Glover , inScience Communications,  Springer Healthcare Ltd , Chester, UK, and was funded by  Sanofi Pasteur. The authors also thank  Jean-Sebastien Persico  for editorial assistance and manuscript coordination on behalf of  Sanofi-Pasteur.
It has also to be considered that main RNAseq and/or transcriptomic databases were constituted by means of the glioma tumor bulk composed of the different populations of GBM cells and other constituents such as endothelial cells, pericytes, reactive astrocytes, macrophages (M1 and/or M2), microglial, neurons, and potentially lymphocytes, depending on the level of heterogeneity GBM subgroup. New potential family targets, expressed at the plasma membrane and involved in survival, GSC differentiation, angiogenesis and invasion, constitute a choice option. TRP channels not systematically ubiquitously expressed, potentially playing pleiotropic mechanisms and being overexpressed in pathologic situations such as hypoxia in glioma cells deserve to be more explored, especially since they could be also expressed by other cell types belonging to the tumor micro-environment.
Toxicogenomics approaches Next generation genomic technologies are now being used as powerful tools in the armament to investigate DILI. Toxicogenomics allows for detailed analysis of altered gene and protein expression profiles and across biological scales (which are also relevant to AOP: molecular-single cellpopulation levels) in response to xenobiotic exposure. 110 Its potential for application is enhanced by the availability of accessible databases that can facilitate and harness generated Omics and imaging data (e. g. Open TG-GATEs  111  ). GWAS have resulted in highly revealing findings, such as HLA polymorphisms related to DILI;  112  whilst transcriptomics-based Big Data-driven analysis has identified adverse outcomes at cellular and organism levels. 101 The relative risk for complex diseases such as coronary artery disease can be predicted by calculating the polygenic risk score (PRS).
Notably, these in vitro models of NAFLD were characterised by enhanced CYP2E1 activity and reduced CY3A4 activity, thus reproducing what has been consistently observed in clinical studies, as previously mentioned. Of note, incubation of HepaRG cells with 100 lM stearic acid for 48 hours did not change CYP2E1 and CYP3A4 activities,  257  thus underscoring the importance of the duration of fatty acid exposure. Interestingly, a comparison by gene set enrichment analysis between the transcriptome GSE102536 dataset obtained in lipid-laden HepaRG cells  247  and the GSE61260 dataset obtained from biopsies of obese patients with fatty liver 258 revealed a highly significant correlation (p <0. 001) concerning the upregulated genes (B. Fromenty and S. Bucher, unpublished data). These models disclosed higher cytotoxicity of APAP, 257 troglitazone 236 and a mixture of benzo[a]pyrene and ethanol  240, 247  in NAFLD cells compared with the non-steatotic cells.
However, as discussed in more detail in Sect. 2. 3, the pressure drifted during the experiments, resulting in significant changes in the absolute sensitivity of the sampled molecules. Around 4. 5 L min -1 of the chamber air was directed into the Vocus through 1 m long PTFE tubing (6 mm o. d. , 4 mm i. d. ) for further analysis. A water flow (HPLC grade or 18 M Milli-Q water) at the rate of 15 sccm (standard cubic centimeters per minute) was utilized to produce reagent ions in a discharged ion source. The mass-resolving power of the long TOF mass analyzer was 12 000-13 000, and data were recorded with a time resolution of 5 s. For measuring HOM and other more oxygenated products from kaurene ozonolysis, a chemical-ionization atmospheric-pressure-interface time-of-flight mass spectrometer was used (CI-APi-TOF, Tofwerk AG/Aerodyne Research, Inc.
) were deployed to measure the particle phase. The L-TOF-AMS is similar to the high-resolution TOF-AMS (HR-TOF-AMS) described in  DeCarlo et al. (2006)  but has a longer TOF chamber for increased mass-resolving power. Data of both the Vocus and the nitrate CI-APi-TOF were analyzed with a MATLAB tofTools package (version 607)  (Junninen, 2014) , while the TOF-AMS analysis software packages SQUIRREL (version 1. 63H) and PIKA (version 1. 23H)  (Sueper et al. , 2011)  within Igor Pro (version 6. 37, WaveMetrics Inc. ) were used for the AMS data. The SMPS data were analyzed with MATLAB and Igor Pro. A system for total O 3 reactivity measurement (TORM) was also deployed during the experiments. The TORM consists of a reactor (three 2 L borosilicate glass bottles) in which sampled air reacts with a set concentration of O 3 (150 ppb in this study) produced by an O 3 generator.
A modified O 3 analyzer (model 49i, Thermo Scientific, Waltham, MA, USA) operating in differential mode recorded directly the difference in O 3 before and after the reactor, which is used to calculate the total O 3 reactivity in the COALA chamber. The kaurene concentration could be estimated based on the calculated O 3 reactivity data at a given rate coefficient of kaurene-O 3 reaction, with the assumption that kaurene was the dominant sink for O 3. A detailed explanation of the instrument and calculation can be found elsewhere  (Helmig et al. , 2021). During the experiments, the total flow through the reactor was 6. 0 L min -1 with 5. 0 L min -1 sampling flow from the COALA chamber and 1. 0 L min -1 coming from the O 3 generator (dilution factor f = 0. 83). The residence time in the reactor was estimated to be 60 s.
( 7 ) All data used to estimate HOM molar yield were selected from the periods when there were no seed particles in the chamber. According to an earlier study in the COALA chamber by  Peräkylä et al. (2020) , the lifetime of HOM in the gas phase under a typical situation without seed particles could be assumed to be 200 s, primarily controlled by losses to chamber walls. Therefore, 0. 005 s -1 was used for k loss here. The flush-out rate is over an order of magnitude slower, and considering the low oxidant concentrations in our chamber, it is unlikely that the chemical loss of HOM would be faster than the wall loss rate. The HOM quantification alone had a large uncertainty, which we can only estimate to be at least +100 %/ -50 %. Also the kaurene quantification required several assumptions, as did k 1.
Optical density was determined by spectrophotometry at a wavelength of 545 nm and a reference filter of 630 nm by a microplate reader (Epock, Biotek, Inc. , Winooski, VT, USA). All results were calculated as an average percentage of the control (cells seeded with culture medium without eluates). Statistical analysis of MTT assay results was performed with SPSS. The level of statistical significance was set at 0. 05.
e annotation of the chemical constituents was performed by comparison of spectral data (UV, MS, and MS/ MS) with published data, as well as by the GNPS platform (https://gnps. ucsd. edu/). To create the molecular network, six fragment ions were considered, and for precursor and fragment ions, the mass tolerances were considered up 0. 02 Da and 0. 1 Da. e molecular network was based on edges with cosine scores of more than 0. 7 and 6 ions  [18]. e molecular network was visualized in software Cytoscape 3. 8.
Direct Measurement of Blood Pressure. e direct surgical method was employed for measuring BP in anesthetized normotensive rats using thiopental (70-90 mg/kg). e trachea was exposed and cannulated to improve respiration during the length of the experiment. Next jugular vein and carotid artery were exposed and cannulated using a polyethylene catheter (PE-50) for extract/drug administration and recording BP, respectively. A catheter inserted into the carotid artery was connected to the pressure transducer fixed with the PowerLab data acquisition system for recording BP (ADI Instruments; Castle Hill, Australia). Following surgery, animals were allowed to stabilize for 30 minutes prior to record BP  [19]. Freshly prepared dilutions of extract were administered to rats at 1 ml/kg, and a dose of the most active fraction was selected which provided a 50% reduction in BP to further understand the blood pressure-lowering mechanism.
Acknowledgments e authors extend their appreciation to the  Deanship of Scientific Research at King Saud University  for funding this work through research group  NO-(RG-1439-002 ). e authors are thankful to the  Higher Education Commission of Pakistan, Ministry of Foreign Affairs and International Development (MAEDI) of France , and the  Ministry of Higher Education and Research (MESR) of France  for funding this project through the  PERIDOT Research Program. e authors are also thankful to the  ORIC department of the University of Sargodha  for funding this research project.
Methods: We searched multiple sources to identify adverse reactions (ARs) to inulin or sinistrin: first, classical pharmacovigilance databases including the French Pharmacovigilance (FPVD) and the WHO Database (VigiBase); second, data from a clinical trial, MultiGFR; third, data regarding current use in an hospital. All potential ARs to inulin or sinistrin were analyzed with a focus on hypersensitivity reactions and relationships to batches of sinistrin. Results: From 1991 to 2018, 134 ARs to inulin or sinistrin were registered in the FPVD or VigiBase. Sixty-three cases (47%) were classified as serious, and 129 cases (96%) were hypersensitivity reactions. We found an association between a batch of sinistrin and the occurrence of hypersensitivity reactions. During the MultiGFR clinical trial, 7 patients (7/163 participants) had an Adverse reaction; of these, 4 were hypersensitivity reactions including one case of grade 4 anaphylactic shock.
Study Design and Data Sources This observational, retrospective, pharmacovigilance study is based on all cases of adverse reactions (ARs) to inulin and sinistrin from 1) classical pharmacovigilance databases with spontaneous reports of ARs, the French Pharmacovigilance database (FPVD) and the World Health Organization (WHO) Database VigiBase, 2) the MultiGFR clinical trial (Validation of New Markers of Glomerular Filtration Rate: Dota Gadolinium (Gd) and Calcium EDTA), a French national clinical trial and 3) patient records from a hospital. Created in 1978, VigiBase is the World Health Organization (WHO) international database of suspected adverse drug reactions. It is the largest drug safety data repository in the world with over 25 million reports of suspected ARs of drugs. In France, since 1985, cases transmitted to the French Pharmacovigilance network are registered in the FPVD, that is administered by the ANSM.
Data Extraction We identified all cases related to inulin%, sinistrin%, and polyfructosan% reported before August 31, 2018. Inulin and sinistrin are coded under different terms in the FPVD including INULINE, POLYFRUCTOSAN, SINISTRINE, PRODUIT NON TRANSCODE, SPECIALITE NON TRANSCODEE; so we searched in the FPVD using each of these terms. To obtain an exhaustive list of cases, we also queried the VigiBase database, which includes French pharmacovigilance case reports transmitted by the French authorities and pharmaceutical companies to the WHO. We used in the VigiBase the keywords inulin, polyfructosan, sinistrin (substance), proinuline, and Inutest (trade name), and French cases submitted before August 31, 2018 were retrieved. We crossed data found in FPVD and VigiBase in order to identify cases reported to both sources and cases only reported to FPDV or only to VigiBase.
We merged these results to build a new database. The FPVD identification number was used to obtain detailed information about the patient (age, gender, past medical history), drug exposure, clinical description¸AR characteristics (onset, seriousness), AR outcome. The causality was assessed through semiological and, chronological presentation. We also collected information on all sinistrin-related ARs from the MultiGFR clinical trial. MultiGFR study is a clinical trial (ClinicalTrials. gov Identifier: NCT02286258) conducted to compare the performances of a reference tracer (sinistrin) and two novel non-radioactive tracers Calcium-EDTA and Gd-DOTA (Dotarem ® ) for GFR measurement in patients with chronic-kidney disease (CKD) and in healthy volunteers subjected to one or two GFR measurements.
Participants ranged in age from 18 to 75 years and had no allergy history. We obtained a list of adverse event cases with detailed clinical information from clinical trial records. Finally, we also had access to clinical data from the Department of Physiology of Necker Hospital, Paris, France, where routine GFR measurement by analysis of sinistrin renal clearance is performed. We collected medical records of patients who underwent a GFR measurement between January 2015 and December 2018 to assess all possible ARs that were not reported to the Pharmacovigilance network. All potential ARs to inulin or sinistrin were analysed with special attention to hypersensitivity reactions and their correlations with specific batches of sinistrin. We took care to identify and eliminate duplicates between our sources before the final analysis, based on patient's characteristics and ARs description.
Pharmacovigilance Databases Within the two pharmacovigilance databases (FPVD and VigiBase) 134 cases related to inulin or sinistrin in France were reported from 1991 to 2018. The number of cases varied from 0 to 15 cases per year. There was an overrepresentation of cases from some centers, namely Lyon (66%), followed by Saint Etienne (10%), Paris (6%), Strasbourg (6%), Toulouse (5%), Lille (3%), and other cities (<1%). The median age of patients who had an AR was 40. 5 years old. Seventy-eight patients (58%) were male. Almost half of the cases were serious (47%). Hypersensitivity reactions were found in 129 patients (96%), the other five cases were digestive symptoms, including abnormal liver function tests. Hypersensitivity reactions to inulin or sinistrin varied from non-serious symptoms (skin or respiratory involvement) to anaphylactic shock, with 1-4 ARs described in the 129 patients (mean 1.