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

Automated Construction of Software Behavior Models by

We the undersigned committee hereby recommend that the attached document b

Software Testing, Analysis, and Review Conference (STARWEST 2001), October/November 2001. Enjoying the Perks of Model-Based Testing

Software testing demands the use of some model to guide such test tasks as selecting test inputs, validating the adequacy of tests, and gaining insight into test effectiveness. Most testers gradually build a mental model of the system under test, which would enable them to further understand and better test its many functions. Explicit models, being formal and precise representations of a tester’s perception of a program, are excellent shareable, reusable vehicles of communication between and among testers and other teams and of automation for many tasks that are normally tedious and labor-intensive. Model-based testing offers advantages like automating test generation and providing a basis for statistically estimating product quality. These perks can be enjoyed provided the right models are used, the proper resources acquired, and adequate training undergone. Model-based testing is not without difficulties, and knowing what they are and whether they can be avoided and how is key to reaping the most out of it

ACM SAC'03 Special Track on Software Engineering: Applications, Practices, and Tools

The brief letter gives an overview of the topics of the conference track organised by us. Twelve Papers have been selected about Formal Semantics, Design Patterns, UML, Java, Software Testing, etc. The Conference Proceeding containing those papers is published by the ACM

Utilization of Polymeric Micelles as a Lucrative Platform for Efficient Brain Deposition of Olanzapine as an Antischizophrenic Drug via Intranasal Delivery

Schizophrenia is a mental disorder characterized by alterations in cognition, behavior and emotions. Oral olanzapine (OZ) administration is extensively metabolized (~up to 40% of the administrated dose). In addition, OZ is a P-glycoproteins substrate that impairs the blood–brain barrier (BBB) permeability. To direct OZ to the brain and to minimize its systemic side effects, the nasal pathway is recommended. OZ-loaded polymeric micelles nano-carriers were developed using suitable biodegradable excipients. The developed micelles were physicochemically investigated to assess their appropriateness for intranasal delivery and the potential of these carriers for OZ brain targeting. The selected formula will be examined in vivo for improving the anti-schizophrenic effects on a schizophrenia rat model. The binary mixture of P123/P407 has a low CMC (0.001326% w/v), which helps in maintaining the formed micelles’ stability upon dilution. The combination effect of P123, P407 and TPGS led to a decrease in micelle size, ranging between 37.5–47.55 nm and an increase in the EE% (ranging between 68.22–86.84%). The selected OZ–PM shows great stability expressed by a suitable negative charge zeta potential value (−15.11 ± 1.35 mV) and scattered non-aggregated spherical particles with a particle size range of 30–40 nm. OZ–PM maintains sustained drug release at the application site with no nasal cytotoxicity. In vivo administration of the selected OZ–PM formula reveals improved CNS targeting and anti-schizophrenia-related deficits after OZ nasal administration. Therefore, OZ–PM provided safe direct nose-to-brain transport of OZ after nasal administration with an efficient anti-schizophrenic effect

Molecular Identification of Aminoglycoside-Modifying Enzymes and Plasmid-Mediated Quinolone Resistance Genes among Klebsiella pneumoniae

Inappropriate use of antibiotics in clinical settings is thought to have led to the global emergence and spread of multidrug-resistant pathogens. The goal of this study was to investigate the prevalence of genes encoding aminoglycoside resistance and plasmid-mediated quinolone resistance among clinical isolates of Klebsiella pneumoniae. All K. pneumoniae isolates were phenotypically identified using API 20E and then confirmed genotypically through amplification of the specific K. pneumoniae phoE gene. All isolates were genotyped by the enterobacterial repetitive intergenic consensus polymerase chain reaction technique (ERIC-PCR). Antibiotic susceptibility testing was done by a modified Kirby-Bauer method and broth microdilution. All resistant or intermediate-resistant isolates to either gentamicin or amikacin were screened for 7 different genes encoding aminoglycoside-modifying enzymes (AMEs). In addition, all resistant or intermediate-resistant isolates to either ciprofloxacin or levofloxacin were screened for 5 genes encoding the quinolone resistance protein (Qnr), 1 gene encoding quinolone-modifying enzyme, and 3 genes encoding quinolone efflux pumps. Biotyping using API 20E revealed 13 different biotypes. Genotyping demonstrated that all isolates were related to 2 main phylogenetic groups. Susceptibility testing revealed that carbapenems and tigecycline were the most effective agents. Investigation of genes encoding AMEs revealed that acc(6′)-Ib was the most prevalent, followed by acc(3′)-II, aph(3′)-IV, and ant(3′′)-I. Examination of genes encoding Qnr proteins demonstrated that qnrB was the most prevalent, followed by qnrS, qnrD, and qnrC. It was found that 61%, 26%, and 12% of quinolone-resistant K. pneumoniae isolates harbored acc(6′)-Ib-cr, oqxAB, and qebA, respectively. The current study demonstrated a high prevalence of aminoglycoside and quinolone resistance genes among clinical isolates of K. pneumoniae