f 1e5, maximum injection time of 50 ms, a TopN of 8 in constructive mode, and an isolation window of 2.0 m/z. The normalized collision power (NCE) was scaled at 17.five, 35, and 52.5, and also the dynamic exclusion time was set at three s. 4.9. Molecular Networking Generation As already reported [27], the spectral information permitted us to generate molecular networking employing the semi-quantitative bioinformatics approach. Data acquisition, processing (i.e., MS information conversion, preprocessing, MS1 annotation, and generation of molecular networks), visualization, and network evaluation have already been described in detail elsewhere [26]. Briefly, raw data have been converted to open MS format (.mzXML) having a ProteoWizard’s MSConvert module. The mzXML files have been then preprocessed (deconvolution, de-isotoping, alignment, and gap-filling) with MZmine 2 application [50]. The single .mgf output file was then loaded on the International All-natural Merchandise Social networking (GNPS) web-based platform as a way to create the multimatrix molecular network [25]. For the usage of high-resolution information, the fundamental parameters have been modified to m/z 0.02 for the mass tolerance of precursor and fragment ions used for MS/MS spectral library looking, and m/z 0.02 for the mass tolerance of fragment ions utilised for molecular networking. The minimum cluster size was set to 1. Moreover, hyperlinks involving nodes had been produced when the cosine score was higher than 0.70, plus the minimum quantity of prevalent fragment ions shared by two MS/MS spectra was 6. Links PARP2 web between two nodes had been only kept within the network if each and every node was within the prime 10 most comparable nodes. The molecular network was visualized employing Cytoscape three.8.0 software program [51]. As Cytoscape computer software permits for the visualization of all of the data in the analysis of the samples, like the peak region in the unique compounds identified, the peak region applied within this study was collected at this step. The nodes had been annotated by spectral matching in comparison with all the on the internet libraries of GNPS, mzCloud, and by details propagation.Int. J. Mol. Sci. 2022, 23,14 of4.ten. Patients Plasma sample analyses were performed on a cohort of 17 COVID-19 sufferers admitted in ICU at Rennes University Hospital. Blood samples were obtained from a study authorized by the Rennes Hospital Ethic Committee (CHU Rennes, n 35RC20_9795_HARMONICOV, ClinicalTrials.gov Identifier: NCT04373200), and informed consent was obtained from patients in accordance with all the Declaration of Helsinki. All sufferers received HCQ (Plaquenil) therapy of 400 mg/day till day 4 (D4) post-admission. At D4, the peripheral blood was collected in tubes containing lithium heparin along with the plasma samples have been prepared and stored at -80 C before the HPLC MS/MS analysis. 4.11. Statistics All of the experiments were repeated at the least 3 times. One-way analysis of variance (ANOVA) followed by Dunnett’s post hoc tests were performed working with Prism 8 (GraphPad Application, Inc., La Jolla, CA, USA). All of the error bars denote typical error of your mean (SEM). Statistical significance was depicted as follows: p 0.05, p 0.01, p 0.001. Pearson correlation coefficients among patients’ characteristics and relative quantification of HCQ and its metabolites have been calculated applying α adrenergic receptor Formulation Microsoft Excel.Supplementary Components: Supplementary information are out there on the web at mdpi/ article/10.3390/ijms23010082/s1. Author Contributions: Conceptualization, P.-J.F., T.G., B.L.D. and B.F.; methodology, P.-J.F., T.G., B.L.D. and B.F.; investigation, P