dataesr/scientific-paragraphs-categorization huggingface dataset:
Acknowledgments The authors thank the patients and their family members for their participation in our study. This study was supported by the  European Research Council (ERC)   Consolidator Grant iDysChart (ERC grant  agreement  820074 ) (to K. B. ); a  doctoral fellowship program  ("Cell Communication in Health and Disease"; co-financed by the  Austrian Science Fund  and the  Medical University of Vienna ) (K. B. ); an  Austrian Science Fund Hertha Firnberg fellowship  ( T934-B30 ) (B. H. ); the  Intramural Research Program ,  Clinical Center, US National Institutes of Health  (S. D. R. ); and the  Academy of Finland  ( 288475  and  294173 ), the  Sigrid Juselius Foundation , the  Finnish Cancer Institute , and  Biocenter Finland  (M. V. ). F. R. -L. was supported by  INSERM  and by government grants from the  Agence National de la Recherche  as part of the  Investment for the Future program  ( ANR-10-IAHU-01  and  ANR-18-RHUS-0010 ), the  Centre de R ef erence D eficits Immunitaires  H er editaires, the  Agence National de la Recherche  ( ANR-14-CE14-0026-01  and  ANR-18-CE17-0001 ), and the  Fondation pour la Recherche M edicale (Equipe FRM   EQU202103012670 ).
Data variables and analysis Data on demographic and clinical characteristics, and drug prescriptions of patients were retrieved from the EMR system of the OPD. Data from the EMR was retrieved in a MS Excel CSV format, cleaned and processed using Python in Jupyter Notebook, a webbased interactive computing platform  [18] , and analyzed using STATA® (version 16. 0 Copyright 1985-2019 StataCorp LLC). Based on the available data variables  [12]  we calculated the following indicators and summarized in table  1  (1) Average number of medicines per encounter (2) Number and proportion of medicines prescribed by generic names (3) Number and proportion of encounters with an injection prescribed (4) Number and proportion of medicines prescribed from the essential medicines list Indicator 1 is summarized as an average with its range.
The EMR of the hospital facilitated the audit of prescribing patterns in the hospital to identify targets for quality improvement. This allowed relatively easy access to data allowing inclusion of all data for analyses unlike other studies which only sampled prescriptions from patient encounters. Other hospitals in Ghana will likely benefit from such use of technology to ensure rapid audit and feedback to prescribers and hospitals to improve RUM. The study has the following strengths. First, is the large dataset from the EMR which was available and used for analyses. Second, the completeness of study variables used for this study was high at approximately to 98%. Third, the study was conducted and reported in accordance with the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines statement  [39].
TDR is able to conduct its work thanks to the commitment and support from a variety of funders. A full list of TDR donors is available at: https://tdr. who. int/about-us/ourdonors Institutional Review Board Statement: The study was conducted in accordance with the Declaration of Helsinki, and permission to use data from the EMR was sought from the Director of the University Hospital, KNUST. Ethical approval was sought and obtained from the Committee on Human Research, Publication and Ethics (CHRPE) of KNUST (CHRPE/AP/066/22 of 18/02/2022). Data confidentiality: The electronic databases are kept in a password protected computer of the principal investigator. No patient identifiers were used in this study. Informed Consent Statement: As this was a record review study with no patient identifiers, the issue of informed patient consent did not apply.
Acknowledgments: This research was conducted through the  Structured Operational Research and Training Initiative (SORT IT ), a global partnership coordinated by  TDR , the  Special Programme for Research and Training in Tropical Diseases at the World Health Organization. The specific SORT IT program that led to these publication included a partnership of TDR with the WHO Country office in Ghana and was implemented along with The Tuberculosis Research and  Prevention Center Non-Governmental Organization , Armenia; The  International Union Against Tuberculosis and Lung Diseases , Paris and South East Asia offices;  Medecins Sans Frontières -Luxembourg , Luxembourg;  ICMR-National Institute of Epidemiology, Chennai, India; Institute of Tropical Medicine, Antwerp, Belgium ; the  University of Washington, USA ;  Jawaharlal Institute of Postgraduate Medical Education & Research (JIPMER ); CSIR water institute, Accra, Ghana;  Kintampo Health Research Center, Accra, Ghana ;  Environmental Protection Agency ,  Accra Ghana , Medwise solutions consultancy, Nairobi, Kenya;  Institute of Statistics, Social and Economics Research, Accra, Ghana ; Members of the Antimicrobial Stewardship Committee at the University Hospital, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana.
Patient Selection To be included in the study, patients had to be receiving health care for a single pregnancy, with follow-up before 22 weeks 0 days of gestation, and had to have delivered in any of the maternity units. The exclusion criteria were patients with a multiple pregnancy, an HIV-positive status, a referral from another hospital for maternal-fetal complications, and an opposition to the use of their medical data for research purposes. Neonates delivered at or after 22 weeks' gestation were also included. The exposed group (endometriosis group) comprised pregnant women with a history of endometriosis, which was documented retrospectively from an imaging workup using specific criteria to ascertain the diagnosis and the staging of the disease  22, 23  or from an available operative report describing endometriotic lesions with histological confirmation.
Data Collection Patients were enrolled prospectively before 22 weeks' gestation during prenatal consultations. After obtaining signed written consent, the practitioners used the patients' medical records to complete a detailed, paper-based questionnaire about maternal medical history, painful symptoms before the pregnancy, and the mode of conception. After delivery, clinical research assistants used the medical records to complete a detailed, web-based questionnaire regarding maternal characteristics, medical In France, collecting data on race and ethnicity is strictly forbidden. Only information on the geographical origin of patients was collected.
We also conducted an analysis according to disease phenotype (SUP, OMA, and DE) to ascertain the association between endometriosis phenotype and the primary and/or secondary outcomes by comparing these 3 subgroups to the entire control group. All of the statistical tests were 2-sided, and P <. 05 was considered to be significant. All analyses were performed with SAS, version 9. 4 (SAS Institute Inc) from October 7, 2020, to February 7, 2021.
However, with 339 women included, the study ensured adequate power for the DE phenotype but not for the SUP and OMA phenotypes. In addition, we assumed that we did not reach the exact expected power to fully assess the implication of the disease phenotype, although the available data did not reveal any pattern except for SGA, which was increased in the OMA and DE phenotypes, thus calling for further analysis. Third, imaging diagnoses of endometriosis raise the question of diagnostic confirmation of endometriosis. It is now well documented that specific imaging criteria are sufficiently accurate for a nonsurgical diagnosis of OMA and DE. 1, 48 However, the endometriosis group included women with a diagnosis based on imaging as well as women who were surgically treated for endometriosis. This heterogeneity could be a bias given the presupposed benefit of removing ectopic lesions for a viable intrauterine pregnancy,  49  which is different from an adverse pregnancy outcome.
INTRODUCTION Psoriatic arthritis (PsA) is a chronic, immune-mediated inflammatory disease with varied musculoskeletal and dermatological manifestations, including joint inflammation, enthesitis, dactylitis, and skin disease  (1). Due to the substantial and enduring impact of psoriatic disease on patients  (2, 3) , it is critical to evaluate the long-term safety and efficacy of treatments. In recent years, the interleukin (IL)-17 cytokine superfamily has emerged as a target of new monoclonal antibody therapies for a range of A video abstract of this article can be found at: https://players. brightcove. net/3806881048001/default_default/index. html?videoId=6309214290112 Clinicaltrials. gov identifiers: NCT02969525 and NCT03347110. The views expressed herein are those of the authors and not necessarily those of the NHS, the NIHR, or the Department of Health.
PATIENTS AND METHODS Study design and participants. The BE ACTIVE trial (ClinicalTrials. gov identifier: NCT02969525) was a 48-week randomized phase IIb dose-ranging study, double-blind and placebo-controlled from the beginning of the study to week 12, then dose-blind to week 48. It was conducted at 41 sites across 5 countries in Europe and the US  (6). Patients who completed 48 weeks of treatment in the double-and dose-blind periods and gave separate informed consent were eligible to enter the OLE study (ClinicalTrials. gov identifier: NCT03347110) for a further 104 weeks of treatment, up to a total of 152 weeks. A safety follow-up visit took place at week 168, 20 weeks after the last dose of bimekizumab (see Supplementary Figure  1 , available on the Arthritis & Rheumatology website at http://onlinelibrary.
All TEAEs were classified using the Medical Dictionary for Regulatory Activities (MedDRA) version 19. 0. Prespecified safety topics of interest included serious, fungal, and opportunistic infections, including tuberculosis (TB). Prespecified safety topics of interest also included liver enzyme elevation, major adverse cardiac events (MACE), malignancies, inflammatory bowel disease (IBD), neutropenia, hypersensitivity, suicidal ideation and behavior (SIB), and depression. MACE, IBD, and SIB events were adjudicated by independent committees. TEAEs leading to withdrawal from the study were a secondary safety endpoint. Efficacy endpoints were prespecified via protocol as secondary and included the following: the proportion of patients achieving ≥20%, ≥50%, or ≥70% improvement in disease activity based on the American College of Rheumatology criteria (ACR20, ACR50, ACR70) at week 96  (11) ; the proportion of patients (among those anonymized IPD and redacted study documents which may include raw datasets, analysis-ready datasets, study protocol, blank case report form, annotated case report form, statistical analysis plan, dataset specifications, and clinical study report.
Missing binary efficacy variables were imputed in the most conservative manner, using nonresponder imputation (NRI), with patients who did not enter the OLE study considered nonresponders from week 48 onwards. Missing continuous efficacy variables were imputed using multiple imputation based on the assumption that data were missing at random. Nonmonotone missing data were imputed with the Markov chain Monte Carlo (MCMC) method; monotone missing data were imputed with a monotone regression model. All computations and generation of outputs were done in SAS version 9. 3 or later. Ethics approval. The BE ACTIVE trial and its OLE study were conducted in accordance with the Declaration of Helsinki and the International Conference for Harmonisation Guidelines for Good Clinical Practice. Ethical approval was obtained from the relevant institutional review boards at all participating sites.
There are currently 2 phase III studies underway, the BE OPTIMAL trial (ClinicalTrials. gov identifier: NCT03895203) and the BE COMPLETE trial (ClinicalTrials. gov identifier: NCT03896581), as well as their combined OLE study, BE VITAL (ClinicalTrials. gov identifier: NCT04009499), after which more robust conclusions will likely be possible. In conclusion, the safety of bimekizumab in patients with PsA over 3 years of treatment was consistent with the previous 48-week results, as well as other recently published studies of IL-17 inhibitors in PsA patients. High thresholds of disease control were achieved within the first year of treatment and sustained through 3 years. Despite the limited sample size, the present study supports the further development of bimekizumab to address an unmet need for improved and sustained efficacy on skin and joint disease in patients with PsA.
ACKNOWLEDGMENTS The authors thank the patients and the investigators and their teams who took part in this study. The authors also acknowledge  Heather Edens, PhD  ( UCB Pharma, Smyrna, GA ) for publication coordination and  Aaron Keeling ,  BA  ( Costello Medical, Boston, MA ) and  Hannah Brechka, PhD  ( Costello Medical, Cambridge, UK ), for medical writing and editorial assistance based on the authors' input and direction. Support for third-party writing assistance for this article, provided by  Aaron Keeling , BA, and  Hannah Brechka, PhD , was funded by  UCB Pharma  in accordance with Good Publication Practice (GPP3) guidelines (http://www. ismpp. org/gpp3).
0001) was with IL-8 (Figure  2C ), a cytokine which also had significantly higher levels in TB patients (Figure  2D ). Expression levels of both IL-8 receptors (CXCR1 and CXCR2) were also higher in TB patients (Figure  2E ), however stimulation of blood from healthy controls with IL-8 did not induce IL-1ra (Figure  2F ). We next explored gene expression signatures commonly associated with these two cytokines and found genes related to the peroxisome proliferator-activated receptor (PPAR)g pathway (Figure  2G ). We validated our findings using a published dataset of transcriptional analysis of human monocyte-derived macrophages (hMDMs) infected with different bacterial strains  (19). This showed a weak, yet significant positive correlation (r=0. 34, q=0. 03) between IL1RN (the transcript for IL-1ra) and PPARG transcripts in hMDMs infected with mycobacteria, but not with non-mycobacterial species (r= -0.
In summary, our study of immune-metabolic responses revealed perturbed responses in TB disease at transcriptomic, proteomic and metabolomic levels. Integration of these datasets has improved our knowledge on how TB disease impacts immune-metabolic pathways resulting in perturbed IL-1 responses, which are essential for M. tb control. This better understanding of how M. tb alters immune responses may facilitate the improved design of preventive and therapeutic tools, including host-directed strategies.
Samples were processed in 7 batches (4 for Visit 1, 3 for Visit 2), within which the samples were randomized, and the same lot of reagents was used for all samples. All samples were normalized together following background subtraction of the negative control probes, using positive control probes and housekeeping genes (SDHA, HPRT1, POLR2A, RPL19, G6PD, TBP) selected by the GNorm method as previously described  (68). This was done using the nSolver ™ analysis software (NanoString technologies). Quality control for our data involved checking the following metrics: fields of view counted (flag if < 0. 75), binding density (flag if not in the 0. 05-2. 75 range), linearity of positive controls (flag if R2 < 0. 9) and limit of detection for positive controls (flag if 0. 5 fM positive control < 2 SDs above the mean of the negative controls).
Metabolomic analysis Supernatants from TruCulture Null tubes were thawed and tested by Ultrahigh Performance Liquid Chromatography-Tandem Mass Spectroscopy (UPLC-MS/MS) for a total of 696 metabolites. Samples were measured on the Metabolon Inc platform (Morrisville, North Carolina, US). For metabolite quantification, peaks were quantified using area-under-thecurve. A data normalization step was performed to correct variation resulting from instrument inter-day tuning differences, and values were rescaled to set the medial equal to 1. Missing values were imputed with the minimum.
Data acquisition was performed on a FACS LSR flow cytometer using FACSDiva software (BD Biosciences, San Jose, CA). FlowJo software (Treestar, Ashland, OR) was used to analyze data. Statistical analysis, data visualization, and software ANOVA (Kruskal-Wallis) testing was performed for multigroup comparisons and paired t-tests for intra-patient analysis with Qlucore Omics Explorer, v. 3. 2 (Qlucore) or GraphPAD Prism. To correct for multiple testing we report false discovery rate (FDR)-adjusted ANOVA p values; q values. Dot plot graphs were compiled with GraphPad Prism v. 6. 0, heatmaps and Principal Component Analysis (PCA) plots with Qlucore. ROC curves were calculated with R (v. 3. 4. 4) and results drawn with graphical package ggplot2 (v. 3. 1. 0). UpSet plots were drawn with UpSetR (v1.
42) with the options "scale" set to TRUE, and the option "ncp" set to 1. Position of each sample on the first component was then extracted and used for further analysis (R v. 3. 6. 1). Pearson correlations were performed in R (v3. 6. 0) between IL-1Ra protein concentrations quantified by Luminex and the metabolites quantified through mass spectrometry for either TB or LTBI cases. To down-size the number of metabolites analyzed, only metabolites that belong to metabolic groups composed of at least 7 metabolites and that are not labelled as 'Drug' or 'Chemical' were considered. The metabolite and protein correlation heatmap was plotted with the ggplot2 R package (v. 3. 3. 1).
Funding This study was funded by the  Bill and Melinda Gates Foundation  ( OPP1114368  and  OPP1204624 ), with additional support from the  French Government 's  Investissement d'Avenir Program, Laboratoire d'Excellence  " Milieu Inteŕieur " Grant  ANR-10-LABX-69-01. AL was supported by the  Fondation Recherche Medicale  ( SPF20170938617 ) and the  European Commision  ( H2020-MSCA-IF-2018 ,  841729 ). NS was supported by an  Institut Pasteur Roux Cantarini  fellowship.
32 To avoid extensive studies and timelines that authorization of a new vaccine candidate would require, the alreadyapproved Wuhan-based mRNA vaccines have been recommended as boosters as they indeed induce potent cross-reactive responses. While many second-generation vaccines are under development, their path to approval is complicated in light of the increasing safety database on the approved vaccines. However, given the limitations of current vaccines, particularly on the durability of mRNA, the emergence of VOCs, and the need for continued booster doses, further vaccine solutions are sought in this protracted epidemic. We previously reported the preclinical efficacy of an adenoassociated virus (AAV)-based COVID-19 vaccine (AAVCOVID). 33 AAVCO VID candidates demonstrated durability of high neutralizing responses in non-human primate (NHP) models for at least 11 months following a single-dose immunization.
Therefore, we designed a construct with a minimal CMV promoter to achieve higher expression within the packaging limitation of AAV to drive the prefusion stable fulllength SARS-CoV-2 Spike antigen. Additionally, the polyadenylation sequence was modified, although its impact on dose and potency was not fully established. ACM vaccine candidates were produced and tested in murine models for the ancestral Wuhan SARS-CoV-2 strain, as well as the Beta, Delta, and Omicron VOCs. To assess any improvement of NHP efficacy at a lower dose, ACM-Beta was tested in a SARS-CoV-2 Beta viral challenge in cynomolgus macaques, illustrating strong protection at the reduced dose. Compared with prior protection data from AC1, however, some breakthrough viral replication was observed in nasal and tracheal swabs.
Cynomolgus macaques (Macaca For the first study testing AC1 and AC3, the different vaccinated groups (n = 6 for each) received a 10 12 gc or 10 11 gc of AC1 vaccine candidate or 10 11 gc of AC3 vaccine candidate, while control animals (n = 6) received only the diluent. Blood was sampled from vaccinated animals at weeks 0, 1, 2, 4, 5, 6, 7, 8, and 9. Sixty-seven days after immunization, all animals were exposed to a total dose of 10 5 PFU of SARS-CoV-2 virus (human coronavirus 2019 [hCoV-19]/France/ lDF0372/2020 strain; GISAID EpiCoV platform under accession number EPI_ISL_406596) via the combination of intranasal and intratracheal routes (0. 25 mL in each nostril and 4. 5 mL in the trachea; i. e. , a total of 5 mL; day 0), using atropine (0. 04 mg/kg) for pre-medication and ketamine (5 mg/kg) with medetomidine (0.
ACKNOWLEDGMENTS We thank the  Bill and Melinda Gates Foundation  for funding the NHP challenge studies. These studies would not have been possible without the responsiveness and help of dozens of individuals within  Mass Eye and Ear, Mass General, Mass General Brigham Innovation , the  Gene Therapy Program  at the  University of Pennsylvania ,  Novartis Gene Therapies ,  Novartis Institutes for Biomedical Research , the  Penn Center for Innovation ,  5AM   Ventures ,  Aldevron , and Catalent. We thank  A. Sheridan  from the  Grousbeck Center Gene Transfer Vector Core at Mass Eye and Ear  for AAV production;  C. Leborgne  from  Genethon  for anti-AAV Nab prescreen in NHP; and  N. Hacohen  and  M. Gentili  from the  Broad Institute  for providing pseudovirus reagents. We thank  B. Delache ,  R.
Ducancel ,  A. Pouget , and  Y. Gorin  for their help with the logistics and safety management; and  I. Mangeot  and  C. Morice  for help with resources management. B. Targat contributed to data management. We thank  S. Van der Werf ,  S. Bellil , and  V. Enouf  for contributions to viral stock challenge production; and  A. Nougairede  for sharing the plasmid used for the sgRNA assays standardization. The IDMIT research infrastructure is supported by the  Programme Investissements d'Avenir , managed by the  ANR  under reference  ANR-11-INBS-0008. The  Fondation Bettencourt Schueller  and the  Region Ilede-France  contributed to the implementation of IDMIT's facilities and imaging technologies. The NHP model of SARS-CoV-2 infection has been developed thanks to the support from  REACTing , the  Fondation pour la Recherche Medicale  (FRM; AM-CoV-Path), and the  European Infrastructure   TRANSVAC2  ( 730964 ).
The virus stock used in NHPs was obtained through the  EVAg  platform (https:// www. european-virus-archive. com/), funded by  H2020  ( 653316 ) or from the  Biodefense, Research Resources , and Translational Research of  NIH/NIAID/DMID/OBRRTR/RRS  ( Program Officer ,  Clint Florence, PhD ). Funding for this project was provided by donations from  Giving/Grousbeck  ( Emilia Fazzalari  and  Wyc Grousbeck ) and multiple other donors (Nathalie, Alexandre, and  Charles de Gunzburg ;  David Vargo; Julia  and  Mark Casady  and the  One Step Forward Education Foundation ;  Katrine S. Bosley ;  Tamra Gould  and  Howard Amster II Donor Advised Fund of the Jewish Federation of Cleveland ; The  Tej Kohli Foundation ;  Michel Plantevin ;  Susan Stoddart  and  Chris Snook ;  Delori Family ; Annette and  Dan Nova; Jennifer  and  Jonathan Uhrig ;  Lyle Howland  and  Jack Manning; Michelle  and  Bob Atchinson ; Elizabeth and Phill Gross; William and  Carolyn Aliski)  through the  Mass Eye and Ear donor network  (L.
The region concerning the lipid peroxidation-related signal (1740-1755 cm -1 ) is highlighted in grey. The data and the images were processed using Orange and Mountain map software respectively. Scale bars 10 µm for large topographies, 2. 5 µm for zoomed regions. was detected (Figure  6E ), whereas in others a strong signal at 1740 cm -1 associated with the new bands in the fingerprint region was observed (Figure  6E' ). The negative control, COS-7 cells transfected with high amount of Citrine-Trimera showed very similar IR fingerprint with almost non-detectable peak at 1740 cm -1 as non-transfected COSNOX cells (Figure  6D ). The IR maps recorded at 1740 cm -1 revealed the location of the peroxided species (Figure  6 , middle right). In non-transfected COSNOX cells and COS-7 cells transfected with Citrine-Trimera, a homogeneous low signal on the 1740 cm -1 IR map was consistent with the spectra (Figure  6A , Figure  6D ).