Integrative analysis of multimodal mass spectrometry data in MZmine 3

3 Pág.We thank Christopher Jensen and Gauthier Boaglio for their contributions to the MZmine codebase. We thank Jianbo Zhang and Zachary Russ for their donations to MZmine development. The MZmine 3 logo was designed by the Bioinformatics & Research Computing group at the Whitehead Institute for Biomedical Research. T.P. is supported by Czech Science Foundation (GA CR) grant 21-11563M and by the European Union’s Horizon 2020 research and innovation programme under Marie Skłodowska-Curie grant agreement 891397. Support for P.C.D. was from US NIH U19 AG063744, P50HD106463, 1U24DK133658 and BBSRC-NSF award 2152526. T.S. acknowledges funding by Deutsche Forschungsgemeinschaft (441958208). M. Wang acknowledges the US Department of Energy Joint Genome Institute ( https://ror.org/04xm1d337 , a DOE Office of Science User Facility) and is supported by the Office of Science of the US Department of Energy operated under subcontract No. 7601660. E.R. and H.H. thank Wen Jiang (HILICON AB) for providing the iHILIC Fusion(+) column for HILIC measurements. M.F., K.D. and S.B. are supported by Deutsche Forschungsgemeinschaft (BO 1910/20). L.-F.N. is supported by the Swiss National Science Foundation (project 189921). D.P. was supported through the Deutsche Forschungsgemeinschaft (German Research Foundation) through the CMFI Cluster of Excellence (EXC-2124 — 390838134 project-ID 1-03.006_0) and the Collaborative Research Center CellMap (TRR 261 - 398967434). J.-K.W. acknowledges the US National Science Foundation (MCB-1818132), the US Department of Agriculture, and the Chan Zuckerberg Initiative. MZmine developers have received support from the European COST Action CA19105 — Pan-European Network in Lipidomics and EpiLipidomics (EpiLipidNET). We acknowledge the support of the Google Summer of Code (GSoC) program, which has funded the development of several MZmine modules through student projects. We thank Adam Tenderholt for introducing MZmine to the GSoC program.Peer reviewe

Ajoene, a sulfur rich molecule from garlic, inhibits genes controlled by quorum sensing

In relation to emerging multiresistant bacteria, development of antimicrobials and new treatment strategies of infections should be expected to become a high priority research area. Quorum Sensing (QS), a communication system used by pathogenic bacteria like Pseudomonas aeruginosa to synchronise the expression of specific genes involved in pathogenicity, is a possible drug target. Previous in vitro and in vivo studies revealed a significant inhibition of P. aeruginosa QS by crude garlic extract. By bioassay-guided fractionation of garlic extracts we determined the primary QS inhibitor present in garlic as ajoene, a sulfur-containing compound with potential as an antipathogenic drug. By comprehensive in vitro and in vivo studies of the effect of synthetic ajoene towards P. aeruginosa was elucidated. DNA microarray studies of ajoene treated P. aeruginosa cultures revealed a concentration dependent attenuation of a few, but central QS controlled virulence factors including rhamnolipid. Furthermore, ajoene treatment of in vitro biofilms demonstrated a clear synergistic, antimicrobial effect with tobramycin on biofilm killing and a cease in lytic necrosis of polymorphonuclear leukocytes. Furthermore, in a pulmonary infectious mouse model a significant clearing of infecting P. aeruginosa was detected in ajoene-treated mice compared to a non-treated control group. This study adds to the list of examples demonstrating the potential of QS interfering compounds in the treatment of bacterial infections

Risk factors for long-term invasive mechanical ventilation: a longitudinal study using German health claims data

Abstract Background Long-term invasive mechanical ventilation (IMV) is a major burden for those affected and causes high costs for the health care system. Early risk assessment is a prerequisite for the best possible support of high-risk patients during the weaning process. We aimed to identify risk factors for long-term IMV within 96 h (h) after the onset of IMV. Methods The analysis was based on data from one of Germany's largest statutory health insurance funds; patients who received IMV ≥ 96 h and were admitted in January 2015 at the earliest and discharged in December 2017 at the latest were analysed. OPS and ICD codes of IMV patients were considered, including the 365 days before intubation and 30 days after discharge. Long-term IMV was defined as evidence of invasive home mechanical ventilation (HMV), IMV ≥ 500 h, or readmission with (re)prolonged ventilation. Results In the analysis of 7758 hospitalisations, criteria for long-term IMV were met in 38.3% of cases, of which 13.9% had evidence of HMV, 73.1% received IMV ≥ 500 h and/or 40.3% were re-hospitalised with IMV. Several independent risk factors were identified (p < 0.005 each), including pre-diagnoses such as pneumothorax (OR 2.10), acute pancreatitis (OR 2.64), eating disorders (OR 1.99) or rheumatic mitral valve disease (OR 1.89). Among ICU admissions, previous dependence on an aspirator or respirator (OR 5.13), and previous tracheostomy (OR 2.17) were particularly important, while neurosurgery (OR 2.61), early tracheostomy (OR 3.97) and treatment for severe respiratory failure such as positioning treatment (OR 2.31) and extracorporeal lung support (OR 1.80) were relevant procedures in the first 96 h after intubation. Conclusion This comprehensive analysis of health claims has identified several risk factors for the risk of long-term ventilation. In addition to the known clinical risks, the information obtained may help to identify patients at risk at an early stage. Trial registration The PRiVENT study was retrospectively registered at ClinicalTrials.gov (NCT05260853). Registered at March 2, 2022