Rational reprogramming of the sesquiterpene synthase BcBOT2 yields new terpenes with presilphiperfolane skeleton

Computer-aided rational design of the substrate binding pocket of sesquiterpene synthases BcBOT2 from Botrytis cinerea yielded FPP cyclization products with presilphiperfolane backbone other than the naturally formed sesquiterpene presilphiperfolan-8β-ol. Particularly, amino acids W118 and F138 were found to strongly control the stability and conformation of key cationic intermediates. The W118Q variant forms only presilphiperfolan-9β-ol, whereas the exchange of amino acids at position 138, such as F138V, has a fundamental effect on the course of the cationic cascade. Here, the 1,3-hydride shift en route to presilphiperfolan-8β-ol is suppressed and substituted by a so far unknown 1,2-hydride shift that leads to presilphiperfol-1-ene and presilphiperfolan-1α-ol along with β-caryophyllene and the so far unknown caryophyllene-8β-ol

1,2‐Benzothiazine Derivatives from Sulfonimidamides by Metal‐Catalyzed Annulation Reactions in Solution and under Solvent‐Free Mechanochemical Conditions

Three‐dimensional aza‐analogues of 1,2‐benzothiazine 1,1‐dioxides have been prepared from sulfonimidamides. Two different protocols are presented. The first is a rhodium‐catalyzed annulation reaction with alpha‐sulfonyloxyketones leading to 4 unsubstituted benzothiazine derivatives. By selective bromination with NBS the heterocyclic ring can further be functionalized. In the second approach, an iridium catalyst is applied under solvent‐free mechanochemical conditions providing products with 3,4‐disubstituted thiazine rings from diazoketo esters and diazoketo sulfones.peerReviewe

the global UNITE-COVID study

Funding Information: AE, FD, GDP, LG, VG, AJ, JK, AL, JM, SNM, MO, MP, MC declare no conflicts of interest. MG reports speaking fees from Baxter and Philips. TDC is supported by Research Foundation Flanders (Grant nr G085920N). MA reports Research Grant from GE, Honoraria from Fisher and Paykel, Pfizer, Orion and Gilead. GC reports grants, personal fees as Speakers’ Bureau Member and Advisory Board Member from Integra and Neuroptics, all outside the submitted work. ACM is supported by a Clinician Scientist Fellowship from the Medical Research Council (MR/V006118/1). SE declares no financial COIs and the following non-financial disclosures: Cochrane editor, American Society of Anesthesiologist data review board member. LF reports research funding from NIHR, Baxter, Ortho-Clinical Diagnostics, Exthera Medical and lecture fees from Baxter, Fresenius, Paion, all outside the submitted work. GG received payment for lectures from Getinge, Draeger Medical, Fisher&Paykel, Biotest, MSD, Gilead and unrestricted research grants from Fisher&Paykel and MSD (all unrelated to the present work). MCMD declares potential conflict of interest with BD. PP declares potential conflicts of interest with Pfizer, MSD and Gilead. SJS reports personal fees from Springer-Verlag, GmbH (Vienna, Austria) for educational commitments grants and non-financial support from ESICM (Bruxelles, Belgium), Fresenius (Germany), Liberate Medical LLC (Crestwood, USA), STIMIT AG (Nidau, Switzerland) Reactive Robotics GmbH (Munich, Germany) as well as from Technical University of Munich, Germany, from national (e.g. DGAI) and international (e.g. ESICM) medical societies (or their congress organizers) in the field of anesthesiology and intensive care, all outside the submitted work; SJS holds stocks in small amounts from Alphabeth Inc., Bayer AG, Rhön-Klinikum AG, and Siemens AG. These did not have any influence on this study. AW reports Honorarium for delivery of educational material for Vygon, GE. JLT declares potential conflict of interest with Getinge. JDW has consulted for Pfizer, MSD (honoraria paid to institution), and is a senior clinical investigator funded by the Research Foundation Flanders (FWO, Ref. 1881020N).Purpose: To accommodate the unprecedented number of critically ill patients with pneumonia caused by coronavirus disease 2019 (COVID-19) expansion of the capacity of intensive care unit (ICU) to clinical areas not previously used for critical care was necessary. We describe the global burden of COVID-19 admissions and the clinical and organizational characteristics associated with outcomes in critically ill COVID-19 patients. Methods: Multicenter, international, point prevalence study, including adult patients with SARS-CoV-2 infection confirmed by polymerase chain reaction (PCR) and a diagnosis of COVID-19 admitted to ICU between February 15th and May 15th, 2020. Results: 4994 patients from 280 ICUs in 46 countries were included. Included ICUs increased their total capacity from 4931 to 7630 beds, deploying personnel from other areas. Overall, 1986 (39.8%) patients were admitted to surge capacity beds. Invasive ventilation at admission was present in 2325 (46.5%) patients and was required during ICU stay in 85.8% of patients. 60-day mortality was 33.9% (IQR across units: 20%–50%) and ICU mortality 32.7%. Older age, invasive mechanical ventilation, and acute kidney injury (AKI) were associated with increased mortality. These associations were also confirmed specifically in mechanically ventilated patients. Admission to surge capacity beds was not associated with mortality, even after controlling for other factors. Conclusions: ICUs responded to the increase in COVID-19 patients by increasing bed availability and staff, admitting up to 40% of patients in surge capacity beds. Although mortality in this population was high, admission to a surge capacity bed was not associated with increased mortality. Older age, invasive mechanical ventilation, and AKI were identified as the strongest predictors of mortality.publishersversionpublishe

Clinical and organizational factors associated with mortality during the peak of first COVID-19 wave: the global UNITE-COVID study (Intensive Care Medicine, (2022), 48, 6, (690-705), 10.1007/s00134-022-06705-1)

Publisher Copyright: © 2022 The Author(s).In the original version of this article, the given and family names of Kristina Fuest, Tobias Lahmer, Johannes Herrmann, Patrick Meybohm, Nikolaos Markou, Georgia Vasileiadou were incorrectly structured. The Publisher apologises for this mistake.publishersversionpublishe

Plasma HDL cholesterol and risk of myocardial infarction: a mendelian randomisation study

Background High plasma HDL cholesterol is associated with reduced risk of myocardial infarction, but whether this association is causal is unclear. Exploiting the fact that genotypes are randomly assigned at meiosis, are independent of non-genetic confounding, and are unmodified by disease processes, mendelian random isation can be used to test the hypothesis that the association of a plasma biomarker with disease is causal. Methods We performed two mendelian randomisation analyses. First, we used as an instrument a single nucleotide polymorphism (SNP) in the endothelial lipase gene (LIPG Asn396Ser) and tested this SNP in 20 studies (20 913 myocardial infarction cases, 95 407 controls). Second, we used as an instrument a genetic score consisting of 14 common SNPs that exclusively associate with HDL cholesterol and tested this score in up to 12 482 cases of myocardial infarction and 41 331 controls. As a positive control, we also tested a genetic score of 13 common SNPs exclusively associated with LDL cholesterol. Findings Carriers of the LIPG 396Ser allele (2·6% frequency) had higher HDL cholesterol (0·14 mmol/L higher p=8×10-13) but similar levels of other lipid and non-lipid risk factors for myocardial infarction compared with noncarriers. This difference in HDL cholesterol is expected to decrease risk of myocardial infarction by 13% (odds ratio [OR] 0·87, 95% CI 0·84-0·91). However, we noted that the 396Ser allele was not associated with risk of myocardial infarction (OR 0·99, 95% CI 0·88-1·11, p=0·85). From observational epidemiology, an increase of 1 SD in HDL cholesterol was associated with reduced risk of myocardial infarction (OR 0·62, 95% CI 0·58-0·66). However, a 1 SD increase in HDL cholesterol due to genetic score was not associated with risk of myocardial infarction (OR 0·93 95% CI 0·68-1·26, p=0·63). For LDL cholesterol, the estimate from observational epidemiology (a 1 SD increase in LDL cholesterol associated with OR 1·54, 95% CI 1·45-1·63) was concordant with that from genetic score (OR 2·13 95% CI 1·69-2·69, p=2×10 -10). Interpretation Some genetic mechanisms that raise plasma HDL cholesterol do not seem to lower risk of myocardial infarction. These data challenge the concept that raising of plasma HDL cholesterol will uniformly translate into reductions in risk of myocardial infarction

Co-infection and ICU-acquired infection in COIVD-19 ICU patients: a secondary analysis of the UNITE-COVID data set

Background: The COVID-19 pandemic presented major challenges for critical care facilities worldwide. Infections which develop alongside or subsequent to viral pneumonitis are a challenge under sporadic and pandemic conditions; however, data have suggested that patterns of these differ between COVID-19 and other viral pneumonitides. This secondary analysis aimed to explore patterns of co-infection and intensive care unit-acquired infections (ICU-AI) and the relationship to use of corticosteroids in a large, international cohort of critically ill COVID-19 patients.Methods: This is a multicenter, international, observational study, including adult patients with PCR-confirmed COVID-19 diagnosis admitted to ICUs at the peak of wave one of COVID-19 (February 15th to May 15th, 2020). Data collected included investigator-assessed co-infection at ICU admission, infection acquired in ICU, infection with multi-drug resistant organisms (MDRO) and antibiotic use. Frequencies were compared by Pearson's Chi-squared and continuous variables by Mann-Whitney U test. Propensity score matching for variables associated with ICU-acquired infection was undertaken using R library MatchIT using the "full" matching method.Results: Data were available from 4994 patients. Bacterial co-infection at admission was detected in 716 patients (14%), whilst 85% of patients received antibiotics at that stage. ICU-AI developed in 2715 (54%). The most common ICU-AI was bacterial pneumonia (44% of infections), whilst 9% of patients developed fungal pneumonia; 25% of infections involved MDRO. Patients developing infections in ICU had greater antimicrobial exposure than those without such infections. Incident density (ICU-AI per 1000 ICU days) was in considerable excess of reports from pre-pandemic surveillance. Corticosteroid use was heterogenous between ICUs. In univariate analysis, 58% of patients receiving corticosteroids and 43% of those not receiving steroids developed ICU-AI. Adjusting for potential confounders in the propensity-matched cohort, 71% of patients receiving corticosteroids developed ICU-AI vs 52% of those not receiving corticosteroids. Duration of corticosteroid therapy was also associated with development of ICU-AI and infection with an MDRO.Conclusions: In patients with severe COVID-19 in the first wave, co-infection at admission to ICU was relatively rare but antibiotic use was in substantial excess to that indication. ICU-AI were common and were significantly associated with use of corticosteroids