Convalescent plasma in patients admitted to hospital with COVID-19 (RECOVERY): a randomised controlled, open-label, platform trial

SummaryBackground Azithromycin has been proposed as a treatment for COVID-19 on the basis of its immunomodulatoryactions. We aimed to evaluate the safety and efficacy of azithromycin in patients admitted to hospital with COVID-19.Methods In this randomised, controlled, open-label, adaptive platform trial (Randomised Evaluation of COVID-19Therapy [RECOVERY]), several possible treatments were compared with usual care in patients admitted to hospitalwith COVID-19 in the UK. The trial is underway at 176 hospitals in the UK. Eligible and consenting patients wererandomly allocated to either usual standard of care alone or usual standard of care plus azithromycin 500 mg once perday by mouth or intravenously for 10 days or until discharge (or allocation to one of the other RECOVERY treatmentgroups). Patients were assigned via web-based simple (unstratified) randomisation with allocation concealment andwere twice as likely to be randomly assigned to usual care than to any of the active treatment groups. Participants andlocal study staff were not masked to the allocated treatment, but all others involved in the trial were masked to theoutcome data during the trial. The primary outcome was 28-day all-cause mortality, assessed in the intention-to-treatpopulation. The trial is registered with ISRCTN, 50189673, and ClinicalTrials.gov, NCT04381936.Findings Between April 7 and Nov 27, 2020, of 16 442 patients enrolled in the RECOVERY trial, 9433 (57%) wereeligible and 7763 were included in the assessment of azithromycin. The mean age of these study participants was65·3 years (SD 15·7) and approximately a third were women (2944 [38%] of 7763). 2582 patients were randomlyallocated to receive azithromycin and 5181 patients were randomly allocated to usual care alone. Overall,561 (22%) patients allocated to azithromycin and 1162 (22%) patients allocated to usual care died within 28 days(rate ratio 0·97, 95% CI 0·87–1·07; p=0·50). No significant difference was seen in duration of hospital stay (median10 days [IQR 5 to >28] vs 11 days [5 to >28]) or the proportion of patients discharged from hospital alive within 28 days(rate ratio 1·04, 95% CI 0·98–1·10; p=0·19). Among those not on invasive mechanical ventilation at baseline, nosignificant difference was seen in the proportion meeting the composite endpoint of invasive mechanical ventilationor death (risk ratio 0·95, 95% CI 0·87–1·03; p=0·24).Interpretation In patients admitted to hospital with COVID-19, azithromycin did not improve survival or otherprespecified clinical outcomes. Azithromycin use in patients admitted to hospital with COVID-19 should be restrictedto patients in whom there is a clear antimicrobial indication

Comparing metabolomic and pathologic biomarkers alone and in combination for discriminating Alzheimer¿s disease from normal cognitive aging

Abstract Background A critical and as-yet unmet need in Alzheimer disease (AD) research is the development of novel markers that can identify individuals at risk for cognitive decline due to AD. This would aid intervention trials designed to slow the progression of AD by increasing diagnostic certainty, and provide new pathophysiologic clues and potential drug targets. Results We used two metabolomics platforms (gas chromatography-time of flight mass spectrometry [GC-TOF] and liquid chromatography LC-ECA array [LC-ECA]) to measure a number of metabolites in cerebrospinal fluid (CSF) from patients with AD dementia and from cognitively normal controls. We used stepwise logistic regression models with cross-validation to assess the ability of metabolite markers to discriminate between clinically diagnosed AD participants and cognitively normal controls and we compared these data with traditional CSF Luminex immunoassay amyloid-β and tau biomarkers. Aβ and tau biomarkers had high accuracy to discriminate cases and controls (testing area under the curve: 0.92). The accuracy of GC-TOF metabolites and LC-ECA metabolites by themselves to discriminate clinical AD participants from controls was high (testing area under the curve: 0.70 and 0.96, respectively). Conclusions Our study identified several CSF small-molecule metabolites that discriminated especially well between clinically diagnosed AD and control groups. They appear to be suitable for further confirmatory and validation studies, and show the potential to provide predictive performance for AD

Comparative survey of the topographical distribution of signature molecular lesions in major neurodegenerative diseases

An understanding of the anatomic distributions of major neurodegenerative disease lesions is important to appreciate the differential clinical profiles of these disorders and to serve as neuropathological standards for emerging molecular neuroimaging methods. To address these issues, here we present a comparative survey of the topographical distribution of the defining molecular neuropathological lesions among 10 neurodegenerative diseases from a large and uniformly assessed brain collection. Ratings of pathological severity in 16 brain regions from 671 cases with diverse neurodegenerative diseases are summarized and analyzed. These include: 1) amyloid-β and tau lesions in Alzheimer's disease; 2) tau lesions in three other tauopathies including Pick's disease, progressive supranuclear palsy and corticobasal degeneration; 3) α-synuclein inclusion ratings in four synucleinopathies including Parkinson's disease, Parkinson's disease with dementia, dementia with Lewy bodies, and multiple system atrophy; and 4) TDP-43 lesions in two TDP-43 proteinopathies, including frontotemporal lobar degeneration associated with TDP-43 and amyotrophic lateral sclerosis. The data presented graphically and topographically confirm and extend previous pathological anatomic descriptions and statistical comparisons highlight the lesion distributions that either overlap or distinguish the diseases in each molecular disease category

Splicefinder : a fast and easy screening method for active protein trans-splicing positions

Split intein enabled protein trans-splicing (PTS) is a powerful method for the ligation of two protein fragments, thereby paving the way for various protein modification or protein function control applications. PTS activity is strongly influenced by the amino acids directly flanking the splice junctions. However, to date no reliable prediction can be made whether or not a split intein is active in a particular foreign extein context. Here we describe SPLICEFINDER, a PCR-based method, allowing fast and easy screening for active split intein insertions in any target protein. Furthermore we demonstrate the applicability of SPLICEFINDER for segmental isotopic labeling as well as for the generation of multi-domain and enzymatically active proteins