dataesr/scientific-paragraphs-categorization huggingface dataset:
, 2016). We are concerned that researchers may not be aware of the potential deterioration of NCC estimation in the presence of numerous tied events and that this problem may be insufficiently taken into account in practice. In particular, researchers should be aware of the possible limitations of the default options used in the available statistical software for implementing conditional logistic regression. In R, while the clogit function uses the exact method by default, it calls the coxph function which uses Efron's approximation by default. In SAS, conditional logistic regression can be performed using either the PHREG procedure with a STRATA statement, which employs Breslow's approximation as the default, or the LOGISTIC procedure with a STRATA statement. The latter procedure relies upon the exact method for discrete data assuming that events really occurred at exactly the same time  (Allison, 2010).
A C K N O W L E D G M E N T S This research was supported by the French Medicines Agency (Agence Nationale de Sécurité du Médicament et des produits de santé, ANSM) and the French Institute for Research in Public Health (Institut pour la Recherche en Santé Publique, GIS-IReSP). MA is a James McGill Professor of Biostatistics at McGill University. The authors wish to thank Agnès Fournier and Gianluca Severi for kindly sharing the E3N data and Mohammed Sedki for his support with codes. The authors are also grateful to all participants, practitioners, and study staff of the E3N study. The E3N cohort is conducted with the financial support of Mutuelle Générale de l'Éducation Nationale (MGEN), the European Community, Ligue nationale contre le Cancer, Institut Gustave Roussy, Institut National de la Santé et de la Recherche Médicale (Inserm), and Fondation de France.
LAL is an aqueous extract of blood cells (amebocytes) from the horseshoe crab limulus polyphemus. In the presence of endotoxin, LAL becomes turbid and, under appropriate conditions, forms a solid gel-clot. The turbidimetric LAL test is performed by adding a given volume of Pyrotell ® T to a given volume of specimen and incubating the reaction mixture at 37 • C. As a consequence, the turbidity in samples will increase in a doseand time-dependent manner. The kinetic-turbidimetric assay quantifies the endotoxin activity based on the gel formation time to reach a designated turbidity (or a designated visible light absorption) by spectrophotometry. The higher the endotoxin concentration in the specimen, the faster turbidity will develop. The detection limit is 0. 005 EU•mL -1. Data were analyzed with a Microsoft Excel spreadsheet (Microsoft 365 MSO, Version 2210 Build 16.
Discovery of AePGT homologs in Arnebia euchroma From the cDNA library sequence data of A. euchroma suspensioncultured cells, six putative PGT genes were identified with local BLAST using previously described AePGT (GenBank: DQ397513. 2), LePGT1 (GenBank: AB055078. 1) and LePGT2 (GenBank: AB055079. 1) as queries. The candidate gene shared 97. 4% identity with the query sequence of AePGT (GenBank: DQ397513. 2). Previously described AePGT was still designated to AePGT in this study. The six putative candidate genes were designated as AePGT1-6, each encoding polypeptides of different lengths. AePGT4-6 have 306 or 307 amino acids (aa) like AePGT, while AePGT1 has 389 aa. AePGT2 and AePGT3 have only 246 aa and 256 aa, respectively (Table  S2 , Fig. S1 ). Sequence alignment revealed an extra N-terminal region of AePGT1 and an absence of 61 and 50 amino acids at the N-terminal of AePGT2 and 3.
Chimeric enzymes revealed the N-terminal of the AePGTs is required for catalytic activity We next used SWISS-MODEL tools to generate 3D structural models for some of the AePGTs to better understand the specific influences of structural diversity on the observed differences in catalytic activity. Specifically, with the crystal structure of ApUbiA (PDB ID:4TQ5) as a basis  (Huang et al. , 2014) , we used the fully automated protein structure homology-modeling server to model 3D structures for AePGT, AePGT2, AePGT3, and AePGT6 (Fig. 5 ). A comparison of the 3D models of AePGT2 and AePGT3 with AePGT and AePGT6 highlights the absence of the first transmembrane helix (TM1) in the N-termini of AePGT2 and AePGT3; TM1 which surrounds the central cavity, with TM2 and TM9 in the front and TM5 and TM6 in the back.
However, there were only a few studies on efficient heterologous shikonin-producing via the technology of synthetic biology. We have established an optimized high-efficiency yeast system to produce GBA and confirmed that yeast could be engineered systematically to enable an efficient production of monoterpene-quinone or naphthoquinone  (Wang et al. , 2017). Our highly efficient catalytic AePGTs will perhaps increase GBA and other shikonin pathway products in cell cultures and yeast production systems. Together with the several P450s genes cloned from the transcriptome database of A. euchroma in our laboratory  (Wang et al. , 2019) , all these progresses hold promise for functional identification of the latter steps involved in the shikonin biosynthesis pathway.
Cloning and phylogenetic analysis of candidate genes Complementary DNA and RNA were obtained as previously described  (Wang et al. , 2014). Using the cDNA of A. euchroma suspension-cultured cells, seven pairs of oligonucleotide primers were designed according to cDNA library sequence data of A. euchroma recorded in our lab (Table  S1 ). Complete fragments of AePGTs DNA were recovered, and the DNA was sequenced completely to confirm the correct sequence. The chimeric AePGTs were synthesized by Synbio Technologies gene company (Suzhou, China). Multiple sequence alignments were performed using the ClustalW software  (Larkin et al. , 2007). From this alignment, a consensus phylogenetic tree was generated by the neighbor-joining method using MEGA 6. 0  (Tamura et al. , 2013). Bootstrap values in percentages (only those greater than 70% are presented) are indicated on the nodes.
3D structural modeling of AePGTs 3D structural models of AePGT, AePGT2, AePGT3, and AePGT6 sequences were generated using the Swiss-model workspace server (http://swissmodel. expasy. org) (Schwede et al. , 2003)  and the PyMOL for molecular visualization. The crystal structure of ApUbiA (PDB ID:4TQ5) was used for molecular modeling  (Huang et al. , 2014).
Already incubation for only 3h led to an increase in PI-positive hepatocytes compared to controls for all tested APAP concentrations (SFig 1C). PI positive nuclei were visualized using a combined fluorescence/phase contrast microscope (Nicon, Dusseldorf, Germany). Five representative images were quantified per well. The results are from three independent experiments (with different mice), and each experiment was performed in triplicate. A second set of experiments was performed for the 4mM APAP-concentration at 5 different time points: 1, 4, 8, 18, 24 hours. This data set was rescaled to match the 24h data set (see SFig. 1). The scaling was necessary as the 24h-toxicity and the dead-cell kinetics were measured using hepatocytes from two different mice, each mouse having different levels of GSH prior to starvation that were not known.
Pharmacokinetic (PK) model The PK model considers two compartments: the peritoneal cavity into which APAP is injected, and the blood compartment, into which APAP diffuses from the peritoneal cavity. Clearance of APAP in the blood is modeled by a first-order decay term. Only a fraction of the dose injected intraperitoneally is assumed to reach the blood compartment according to a limited bio-availability. Parameters were fitted for the experimentally measured blood kinetics observed for the dose of 300 mg/kg of body weight and one data point measured at 24h each for 56 mg/kg, 167mg/kg, and 500mg/kg through minimization of the log-likelihood function using the CMA-ES algorithm  (Hansen and Ostermeier, 1996; Hansen, 2006). In a next step, prediction of the concentration-time curve for the doses 89, 158, 281, 375 and 500 mg/kg was done in MATLAB using the estimated parameters.
Thus, all mean values of reaction rates for sulfation, glucuronidation and glutathione-s-transferase are the same from one cell to another. It was verified that the results do not depend critically on the number of cells chosen. Using 160 cells instead of 3251 cells gave for the same seed an only very slightly different parameter distribution such that the fraction of death cells differs by only ~ ±5% from those where 3251 cells have been used. The equations are presented in the supplementary material. They were implemented in MATLAB. Physiologically relevant parameter ranges were determined from literature for each parameter and parameters having an influence on the simulation were estimated using the in vitro fraction of dead cells after a 24h exposure to 0. 25mM, 0. 5mM, 1mM, 2mM, 4mM or 8mM APAP.
Establishment of in vitro and in vivo data of APAP hepatotoxicity In a first step we determined in vitro and in vivo APAP hepatotoxicity (corresponding to Fig. 1 (I), (V)). In vitro: Primary hepatocytes were isolated from male C57BL6/N mice and cultivated in a 3D configuration between two soft gel collagen layers (SFig. 1). Six different concentrations ranging between 0. 25 mM and 32 mM APAP were tested and cytotoxicity was analyzed by propidium iodide (PI) staining and cell morphology after a 24 h exposure period (Fig. 2A-C , SFig. 1C, D). For the 4mM dose, cytotoxicity was analyzed at 5 different time points (Fig. 2C ). The cytotoxicity was measured in terms of the number of dead cells, that was manually quantified based on PI positive nuclei and cell morphology (SFig. 1B). The representative result of PI-stained hepatocytes demonstrates that the technique allows a clear differentiation between PI positive and negative hepatocytes (Fig  2B ).
The fraction of dead cells increases to almost its saturation value after 10 hours. Analysis of hepatocytes of three different mice resulted in a concentration-dependent increase of cytotoxicity, where approximately 40% of all hepatocytes lost their ability to exclude PI at concentrations of 4 mM and 8 mM APAP (Fig 2C ). At even higher, concentrations (16 and 32 mM, not shown in Fig. 2C ) a sharp increase of the concentration response curve was obtained, leading to cell death of all (i. e. not only CYP-positive) hepatocytes. In vivo: To determine the APAP-induced hepatotoxicity in vivo (Fig. 2D -F; SFig. 2), the same mouse strain (C57BL6/N, male) was studied that has been used to generate the in vitro data with cultivated hepatocytes. APAP was intraperitoneally administered at five doses ranging between 89 and 500 mg/kg body weight and livers were analyzed 24 h after administration (SFig 2A).
The result demonstrates a dose-dependent increase of the pericentral dead cell area (SFig 2B). For doses up to 375 mg/kg the dead cell area corresponds approximately to the pericentral fraction of hepatocytes that express CYP2E1 (SFig 2C). Next, the pericentral dead cell area was quantified in relation to the total area of the liver tissue to calculate the fraction of dead cells in vivo. Mean values and standard deviations of three mice per dose showed a dose-dependent increase in the fraction of dead hepatocytes, with 89 mg APAP/kg b. w. representing the NOAEL and 158 mg APAP/kg b. w. the LOAEL (Fig  2F ). These in vivo-hepatotoxicity data serve as reference for comparison to all in vitroin vivo extrapolation strategies. The here presented in vivo data of APAP are in agreement with previous reports on APAP-induced liver injury in mice  (McGill et al.
, 2012; Ghallab et al. , 2022). The in vitro experiments showed slightly higher APAP-induced cytotoxicity compared to previous reports  (Jemnitz et al. , 2008; Jaruchotikamol et al. , 2009). A possible explanation of this discrepancy is that we started incubation with APAP already at two hours after hepatocyte isolation, the time when Cyp2e1 expression is still preserved. In the next step, the classical extrapolation strategy based on AUC and Cmax has been studied. For determination of the dose-dependent drug concentration at the site of action, four doses (56, 167, 300 and 450 mg APAP/kg b. w. ) were administered to male C57BL6/N mice and blood was taken from the portal vein to determine APAP plasma concentrations. The data was collected 30 minutes after injection for all doses, and over additional time points to determine the temporal kinetics for the 300 mg/kg dose.
Funding DD acknowledges support by the  BMBF -grants LiSyM, MSDILI and  LiSyM-Cancer  as well as by the  ANR -project iLITE and  EU -project  PASSPORT. JD acknowledges support by ANR-project iLite and BMBF -project LiSyM. GC acknowledges support by  EU -project  PASSPORT. AG is funded by the  German Research Foundation  (DFG;  GH 276/1-1 ; project no. 457840828 ).
Essential oil analysis A Hewlett-Packard Agilent gas chromatograph (6890 Plus), associated with a Hewlett-Packard Agilent Mass Spectrometer (5973), and an A polar column: 5% Phenyl 95% dimethylpolysiloxane HP-5MS (30 m x 0. 25 mm; 0. 25 µm) was used to analyze the essential oil. The gas chromatograph was programmed at an initial temperature of 60°C for 8 min, then increased to 250°C at a rate of 2°C/min, isotherm for 10 min. Helium was used as the carrier gas (0. 5 mL/min); 0. 2 L was injected in split mode (1 hr 13) with a fraction of 1/20; injector and detector temperatures were 250 and 280°C, respectively. The mass spectrometer was operated in EI mode at 70 eV; ion source temperature, 230°C; MS data was acquired in scan mode at a range of 30 to 500 m/z. The identification of each compound was based on a comparison of its mass spectra with those of the NIST mass spectral library 02 and Wiley 7.
5 min using Harris Haematoxylin (Sigma), followed by a rinsing for 10 min with running water. Finally, the slides were assembled using Aquatex and dried for one week. The slides were scanned using a Nanozoomer digital pathology scanner (Hamamatsu, Shizuoka, Japan) and visualized using a Hamamatsu NDP viewer. ImageJ public domain software (ImageJ Website, https://imagej. net/ij/, accessed on 5 January 2023) was used to assess the area covered by lipid droplets. Lipid vesicle coverage equal to or greater than 5% was considered to represent steatosis. Histological scoring was performed for steatosis using a previously established scoring system  [34].
Determination of Combined Effects and Statistical Analysis First, all the results were transformed into the fold change of the DMSO-treated group. Graphpad Prism 9 was used to carry out statistical analyses. Each dataset was analyzed using a one-way ANOVA test accompanied by a Tukey's multiple comparisons test, with p < 0. 05 considered significant. To identify the combined effects, we considered the "Combination Subthresholding approach" and the "highest single agent approach/cooperative effect", as previously described in  [35]. Briefly, the "Combination Subthresholding approach" consists in showing that a combination of noneffective doses of drugs yields a significant effect, and the "highest single agent approach/cooperative effect" reflects that the resulting effect of a drug combination is greater than the effects produced by its individual components  [35].
Mechanical and microscopical characterization Scanning electron microscopy (SEM) analysis was carried out with Hitachi 3000 microscope. All images were taken at an accelerating voltage of 15 kV. For measuring single fiber properties, Favimat (Textechno Herbert Stein GmbH and Co. KG, Möchengladbach, Germany) was used. The fiber ends are clamped between two sets of jaws. The displacement is insured by a constant speed motor with interchangeable equipment to vary the rate of elongation. The data of the load and elongation are transferred to a computer to be plotted and analyzed.
Acknowledgements This work is supported by  ANR   DEFIS  project (grant  ANR-PRC-17-CE07-0008 ) and  ANR   SULFIVE  project (grant  ANR-PRC-21-CE07-0042 ) of the  French National Research Agency (ANR). The authors thank  Dr. Didier Le Scheme 7. Downstream  functionalizations. Nouen responsible for the analytical platforms and facilities of  LIMA  ( UMR7042   CNRS-Unistra-UHA ). The " Direction du Numérique " of the  Université de Pau et des Pays de l'Adour and Mésocentre de Calcul Intensif Aquitain (MCIA)  are acknowledged for computational facilities. This work was also performed using HPC resources from  GENCI-IDRIS  (Grant  2023-[project AD010800045R1 ]). We also would like to thank referees for their valuable suggestion and comments.
NMR Spectroscopy Analysis of Pigments In order to identify the pigments and confirm their purity, data on the indolic amine group and the two amides were evaluated using NMR spectroscopy. For the sake of simplicity, numbers were assigned to each of the amide protons (2 and 3) and to the indolic N-H proton (1) contained in the molecule, and the chemical shifts detected by 1 H-NMR associated with each of them were compared with the values reported in the literature. Figure  4A  shows the common molecular structure of violacein and deoxyviolacein. In the case of violacein, R would be a hydroxyl group whereas in the case of deoxyviolacein, R would be hydrogen. group and the two amides were evaluated using NMR spectroscopy. For the sake of simplicity, numbers were assigned to each of the amide protons (2 and 3) and to the indolic N-H proton (1) contained in the molecule, and the chemical shifts detected by 1 H-NMR associated with each of them were compared with the values reported in the literature.
A CAMAG ATS 4 applicator tool (CAMAG, Muttenz, Switzerland) automatically drew 2 to 10 µL of the sample and applied it to an F254 silica-covered glass plate (Merck, Saint-Quentin Fallavier, France). The plate was then transferred to a CAMAG ATC2 automatic developing chamber which was first saturated with 15 mL 65:35 ethyl acetate/cyclohexane vapor and wherein 15 mL of the same solvent was automatically poured into the bottom of the integrated glass chamber. Upon completion of the solvent migration, pigment separation was observed on the silica plate. The plate was then placed in a CAMAG TLC scanner 4 (CAMAG, Muttenz, Switzerland), which scanned the solvent fronts at a wavelength of 570 nm and processed the data to obtain the proportions of each compound in the anolyte.
Patient Recruitment, Follow-Up and Study Instrument PLHIV taking HAART were assessed for eligibility by the HIV care clinic prescriber, a medical doctor. Those eligible, as described above, and who consented to participate were subjected to baseline laboratory investigations. Patients with normal liver function tests (LFTs) and free of hepatitis B and C were consecutively enrolled to IPT. While those willing to participate but without liver diseases or deranged liver enzymes were consecutively enrolled as the comparator group (unexposed) (Fig. 1 ). Eligible patients were forwarded to data collectors (two registered nurse practitioners and a pharmacist working at the HIV care clinic) for enrollment. The data collectors were responsible for enrollment and follow-up of patients under the terms of the study protocol.
Study participants were informed on the signs and symptoms of hepatic injury such as nausea, vomiting, abdominal pain, unexplained fatigue, jaundice and dark urine, and advised to visit the health facility or call the research team in case they experienced similar events. All follow-ups were made through hospital visits. Both exposed and unexposed groups, once enrolled, were expected to be followed-up for a period of 6 months because IPT was prescribed for 6 months. Due to a shortage of laboratory supplies impacted by the COVID-19 pandemic, the majority of the study participants completed their follow-up in 4 months. During follow-up, liver function tests (LFTs) were taken on a monthly basis for both groups. All study participants, regardless of their exposure status, were actively and equally monitored by the treating physician and data collectors for the risk of hepatic injury until the onset of hepatic injury or death, discontinuation of IPT or completion of the study, whichever came first.
Patients who developed liver damage during the study period were managed according to the national treatment protocol. In all cases who developed hepatotoxicity, possible alternative explanations such as hepatitis B and C infections, alcohol consumption and intake of other drugs were assessed and ruled out. A structured questionnaire adopted from a similar study conducted previously  [17]  was used to collect data. The questionnaire had four main sections: patient demographic characteristics, drug details, baseline and followup test results, and reaction (liver injury) details. Data were collected by the data collectors working in the HIV care clinic and supervised by one of the authors (M. R. ).
Data Analysis Data were entered using a program census and survey processing system (CSPro) version 7. 4 and analysed using R 4. 0. 4 [24]  and SPSS 20. 0. Descriptive statistics including percentages, frequencies, number needed to harm, mean (standard deviation, SD) and median (interquartile range, IQR) were computed as appropriate. As a measure of frequency, incidence rate of DILI was computed using descriptive statistics. Chi-square tests of independence and bivariate logistic regression were used to identify factors associated with DILI. A Cox proportional hazard model was used to explore whether there was increased risk of drug-induced liver injury (DILI) associated with IPT and compare the time-to-event onset of DILI in both groups (time-to-event analysis). To compare the incidence rate of DILI in the exposed versus the unexposed, the rate ratio (RR) or the hazard ratio with 95% confidence interval (CI) was computed, as appropriate.
Discussion In this real-world observational cohort study, a higher risk of DILI was observed in the exposed group but its statistical significance at a multivariate level could not be explored for reasons reported in the data analysis of the methods section. Nevertheless, considering the life-threatening nature of the outcome, observing 12 cases (4. 2%) only in the exposed group is clinically important and of concern. All possible causes that could be potentially hepatotoxic were assessed and no alternative explanation was found for all cases. However, we acknowledge that other unmeasured confounders may still exist, which is an inherent limitation of such studies. Comparing this finding with studies reported elsewhere is a challenge due to variability of the results. A recent metaanalysis and systematic review of individual participant data from randomised controlled trials reported a 2.
Acknowledgements The authors sincerely thank  Dr Kahsay Michael ,  Pharmacist Yohana Teklu ,  Sr. Bisrat Gebrelul  and  Sr. Alganesh Hadgu  for their outstanding contribution in enrolment and monitoring of patients and data collection. The study participants are grateful for their time and willingness to participate. The authors would also like to acknowledge the staff of the National Medicines and Food Administration of Eritrea namely:  Merhawi Bahta ,  Merhawi Debesai ,  Sirak Tesfamariam ,  Marta Amanuel ,  Kisanet Dawit  and  Feven Ghebreberhan  for their assistance in the data management. Finally, the authors sincerely thank the staff of the  HIV control programme (Sr Nigisty Tesfamicael and Tadesse Kidane)  for their collaboration and review comments.