253 research outputs found
Total Synthesis of Brasoside and Littoralisone
The first total syntheses of littoralisone (1) and brasoside (2) have been achieved in 13 overall steps. Both natural products are forged from a common intermediate which is rapidly assembled using organocatalytic technology, including a proline-catalyzed Îą-aminoxylation and a contra-thermodynamic intramolecular Michael addition. Application of the two-step carbohydrate synthesis technology has enabled to access a selectively substituted glucose derivative for use as an intramolecular cycloaddition tether. This synthesis culminates with an intramolecular [2+2] photocycloaddition that serves to support the proposed biosynthetic origins of 1 from 2
Characterization of uncertainties in atmospheric trace gas inversions using hierarchical Bayesian methods
We present a hierarchical Bayesian method for atmospheric trace gas
inversions. This method is used to estimate emissions of trace gases as well
as "hyper-parameters" that characterize the probability density functions
(PDFs) of the a priori emissions and model-measurement covariances. By
exploring the space of "uncertainties in uncertainties", we show that the
hierarchical method results in a more complete estimation of emissions and
their uncertainties than traditional Bayesian inversions, which rely heavily
on expert judgment. We present an analysis that shows the effect of
including hyper-parameters, which are themselves informed by the data, and
show that this method can serve to reduce the effect of errors in assumptions
made about the a priori emissions and model-measurement uncertainties. We
then apply this method to the estimation of sulfur hexafluoride (SF6)
emissions over 2012 for the regions surrounding four Advanced Global
Atmospheric Gases Experiment (AGAGE) stations. We find that improper
accounting of model representation uncertainties, in particular, can lead to
the derivation of emissions and associated uncertainties that are unrealistic
and show that those derived using the hierarchical method are likely to be
more representative of the true uncertainties in the system. We demonstrate
through this SF6 case study that this method is less sensitive to
outliers in the data and to subjective assumptions about a priori emissions
and model-measurement uncertainties than traditional methods
Clinical significance of coronavirus disease 2019 in hospitalized patients with myocardial injury
Background:
The clinical significance of Coronavirus disease 2019 (COVIDâ19) as an associate of myocardial injury is controversial.
Hypothesis:
Type 2 MI/Myocardial Injury are associated with worse outcomes if complicated by COVIDâ19.
Methods:
This longitudinal cohort study involved consecutive patients admitted to a large urban hospital. Myocardial injury was determined using laboratory records as âĽ1 hsâTnI result >99th percentile (male: >34âng/L; female: >16âng/L). Endotypes were defined according to the Fourth Universal Definition of Myocardial Infarction (MI) and COVIDâ19 determined using PCR. Outcomes of patients with myocardial injury with and without COVIDâ19 were assessed.
Results:
Of 346 hospitalized patients with elevated hsâTnI, 35 (10.1%) had laboratoryâconfirmed COVIDâ19 (median age [IQR]; 65 [59â74]; 64.8% male vs. COVIDâ19 negative: 74 [63â83] years; 43.7% male). Cardiac endotypes by COVIDâ19 status (yes vs. no) were: Type 1 MI (0 [0%] vs. 115 [100%]; p <â.0005), Type 2 MI (13 [16.5%] vs. 66 [83.5%]; p =â.045), and nonâischemic myocardial injury (cardiac: 4 [5.8%] vs. 65 [94.2%]; p =â.191, nonâcardiac:19 [22.9%] vs. 64 [77.%]; p <â.0005). COVIDâ19 patients had less comorbidity (median [IQR] Charlson Comorbidity Index: 3.0 [3.0] vs. 5.0 [4.0]; p =â.001), similar hsâTnI concentrations (median [IQR] initial: 46 [113] vs. 62 [138]; p =â.199, peak: 122 [474] vs. 79 [220] ng/L; p =â.564), longer admission (days) (median [IQR]: 14[19] vs. 6[12]; p =â.001) and higher inâhospital mortality (63.9% vs. 11.3%; OR = 13.2; 95%CI: 5.90, 29.7).
Conclusions:
Cardiac sequelae of COVIDâ19 typically manifest as Nonâcardiac myocardial injury/Type 2MI in younger patients with less coâmorbidity. Paradoxically, the admission duration and inâhospital mortality are increased
Dielectric spectra analysis: reliable parameter estimation using interval analysis
Dielectric spectroscopy is an extremely versatile method for characterizing the molecular dynamics over a large range of time scales. Unfortunately, the extraction of model parameters by data fitting is still a crucial problem which is now solved by our program S.A.D.E. S.A.D.E. is based on the algorithm S.I.V.I.A. which was proposed and implemented by Jaulin in order to solve constraint satisfaction problems. The problem of dielectric data analysis is reduced to a problem of choosing the appropriate physical model. In this article, Debye relaxations were used and validated to fit the relaxations of a DGEBA prepolymer and the polarization of the spectrometer electrodes. The conductivity was evaluated too
Cardiotoxicity and myocardial hypoperfusion associated with antiâvascular endothelial growth factor therapies: prospective cardiac magnetic resonance imaging in patients with cancer
No abstract available
Myocardial changes on 3T cardiovascular magnetic resonance imaging in response to haemodialysis with fluid removal
Background:
Mapping of left ventricular (LV) native T1 is a promising non-invasive, non-contrast imaging biomarker. Native myocardial T1 times are prolonged in patients requiring dialysis, but there are concerns that the dialysis process and fluctuating fluid status may confound results in this population. We aimed to assess the changes in cardiac parameters on 3T cardiovascular magnetic resonance (CMR) before and after haemodialysis, with a specific focus on native T1 mapping.
Methods:
This is a single centre, prospective observational study in which maintenance haemodialysis patients underwent CMR before and after dialysis (both scans within 24 h). Weight measurement, bio-impedance body composition monitoring, haemodialysis details and fluid intake were recorded. CMR protocol included cine imaging and mapping native T1 and T2.
Results:
Twenty-six participants (16 male, 65âÂąâ9 years) were included in the analysis. The median net ultrafiltration volume on dialysis was 2.3 L (IQR 1.8, 2.5), resulting in a median weight reduction at post-dialysis scan of 1.35 kg (IQR 1.0, 1.9), with a median reduction in over-hydration (as measured by bioimpedance) of 0.75 L (IQR 0.5, 1.4). Significant reductions were observed in LV end-diastolic volume (â 25 ml, pâ=â0.002), LV stroke volume (â 13 ml, pâ=â0.007), global T1 (21 ms, pâ=â0.02), global T2 (â 1.2 ms, pâ=â0.02) following dialysis. There was no change in LV mass (pâ=â0.35), LV ejection fraction (pâ=â0.13) or global longitudinal strain (pâ=â0.22). On linear regression there was no association between baseline over-hydration (as defined by bioimpedance) and global native T1 or global T2, nor was there an association between the change in over-hydration and the change in these parameters.
Conclusions:
Acute changes in cardiac volumes and myocardial native T1 are detectable on 3T CMR following haemodialysis with fluid removal. The reduction in global T1 suggests that the abnormal native T1 observed in patients on haemodialysis is not entirely due to myocardial fibrosis
COVIDâ19 and its cardiovascular effects: a systematic review of prevalence studies
BACKGROUND: A small minority of people with coronavirus disease 2019 (COVID-19) develop a severe illness, characterised by inflammation, microvascular damage and coagulopathy, potentially leading to myocardial injury, venous thromboembolism (VTE) and arterial occlusive events. People with risk factors for or pre-existing cardiovascular disease may be at greater risk. OBJECTIVES: To assess the prevalence of pre-existing cardiovascular comorbidities associated with suspected or confirmed cases of COVID-19 in a variety of settings, including the community, care homes and hospitals. We also assessed the nature and rate of subsequent cardiovascular complications and clinical events in people with suspected or confirmed COVID-19. SEARCH METHODS: We conducted an electronic search from December 2019 to 24 July 2020 in the following databases: the Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE, Embase, covid-19.cochrane.org, ClinicalTrials.gov and EU Clinical Trial Register. SELECTION CRITERIA: We included prospective and retrospective cohort studies, controlled before-and-after, case-control and cross-sectional studies, and randomised controlled trials (RCTs). We analysed controlled trials as cohorts, disregarding treatment allocation. We only included peer-reviewed studies with 100 or more participants, and excluded articles not written in English or only published in pre-print servers. DATA COLLECTION AND ANALYSIS: Two review authors independently screened the search results and extracted data. Given substantial variation in study designs, reported outcomes and outcome metrics, we undertook a narrative synthesis of data, without conducting a meta-analysis. We critically appraised all included studies using the Joanna Briggs Institute (JBI) checklist for prevalence studies and the JBI checklist for case series. MAIN RESULTS: We included 220 studies. Most of the studies originated from China (47.7%) or the USA (20.9%); 9.5% were from Italy. A large proportion of the studies were retrospective (89.5%), but three (1.4%) were RCTs and 20 (9.1%) were prospective. Using JBI's critical appraisal checklist tool for prevalence studies, 75 studies attained a full score of 9, 57 studies a score of 8, 31 studies a score of 7, 5 studies a score of 6, three studies a score of 5 and one a score of 3; using JBI's checklist tool for case series, 30 studies received a full score of 10, six studies a score of 9, 11 studies a score of 8, and one study a score of 5 We found that hypertension (189 studies, n = 174,414, weighted mean prevalence (WMP): 36.1%), diabetes (197 studies, n = 569,188, WMP: 22.1%) and ischaemic heart disease (94 studies, n = 100,765, WMP: 10.5%)  are highly prevalent in people hospitalised with COVID-19, and are associated with an increased risk of death. In those admitted to hospital, biomarkers of cardiac stress or injury are often abnormal, and the incidence of a wide range of cardiovascular complications is substantial, particularly arrhythmias (22 studies, n = 13,115, weighted mean incidence (WMI) 9.3%), heart failure (20 studies, n = 29,317, WMI: 6.8%) and thrombotic complications (VTE: 16 studies, n = 7700, WMI: 7.4%). AUTHORS' CONCLUSIONS: This systematic literature review indicates that cardiometabolic comorbidities are common in people who are hospitalised with a COVID-19 infection, and cardiovascular complications are frequent. We plan to update this review and to conduct a formal meta-analysis of outcomes based on a more homogeneous selected subsample of high-certainty studies
Mass Activated Droplet Sorting (MADS) Enables Highâ Throughput Screening of Enzymatic Reactions at Nanoliter Scale
Microfluidic droplet sorting enables the highâ throughput screening and selection of waterâ inâ oil microreactors at speeds and volumes unparalleled by traditional wellâ plate approaches. Most such systems sort using fluorescent reporters on modified substrates or reactions that are rarely industrially relevant. We describe a microfluidic system for highâ throughput sorting of nanoliter droplets based on direct detection using electrospray ionization mass spectrometry (ESIâ MS). Droplets are split, one portion is analyzed by ESIâ MS, and the second portion is sorted based on the MS result. Throughput of 0.7â samplesâ sâ 1 is achieved with 98â % accuracy using a selfâ correcting and adaptive sorting algorithm. We use the system to screen â 15â 000â samples in 6â h and demonstrate its utility by sorting 25â nL droplets containing transaminase expressed in vitro. Labelâ free ESIâ MS droplet screening expands the toolbox for droplet detection and recovery, improving the applicability of droplet sorting to protein engineering, drug discovery, and diagnostic workflows.A microfluidic system for sorting nanoliter droplets based on mass spectrometry is presented. Fully automated, labelâ free sorting at 0.7â samplesâ sâ 1 is achieved with 98â % accuracy. In vitro transcription and translation (ivTT) of a transaminase enzyme in ca.â 25â nL samples is demonstrated and samples are sorted on the basis of enzyme activity.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/154315/1/anie201913203.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/154315/2/anie201913203-sup-0001-misc_information.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/154315/3/anie201913203_am.pd
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