Strength through diversity : networking for community development.

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Flaviviruses Versus The Cell, and Evolution In The Primate Interferon Response

Long-term interactions between viruses and their hosts often develop into genetic arms races, which result in fast-evolving proteins (i.e. proteins evolving under positive natural selection), especially in immune proteins. A bioinformatic screen of proteins in a component of the primate innate immune response, the interferon system, demonstrated that proteins farther downstream of interferon induction are more likely to be evolving under positive natural selection compared to proteins in interferon induction pathways. One of the proteins under positive selection in this screen, STING, is a known target of proteases from a group of viruses called flaviviruses. The human haplotypes of STING (three of which are studied in this work) demonstrate a range of phenotypes of antagonism and interferon induction that may help explain the evolutionary history of this crucial immune protein. The cleavage of STING demonstrates that the dengue virus protease targets host proteins for cleavage as well as viral proteins. In an attempt to identify novel targets of the dengue virus protease, a machine learning screen was used to predict possible motifs based on known motifs. This resulted in the identification of DGAT2, a newly described target of flavivirus proteases. The ability to cleave DGAT2, a host protein involved in maintaining lipid homeostasis, improves dengue virus replication, and is a conserved property of all flavivirus proteases tested. DGAT2 is not evolving under positive selection, making it a host-virus antagonistic interaction that has not resulted in an evolutionary arms race. However, identifying and describing this host-virus interaction helps us understand how dengue virus and other flaviviruses alter the host lipid environment during replication.</p

Application of therapeutic drug monitoring to the treatment of bacterial central nervous system infection: a scoping review

BackgroundBacterial central nervous system (CNS) infection is challenging to treat and carries high risk of recurrence, morbidity, and mortality. Low CNS penetration of antibiotics may contribute to poor clinical outcomes from bacterial CNS infections. The current application of therapeutic drug monitoring (TDM) to management of bacterial CNS infection was reviewed.MethodsStudies were included if they described adults treated for a suspected/confirmed bacterial CNS infection and had antibiotic drug concentration(s) determined that affected individual treatment.ResultsOne-hundred-and-thirty-six citations were retrieved. Seventeen manuscripts were included describing management of 68 patients. TDM for vancomycin (58/68) and the beta-lactams (29/68) was most common. Timing of clinical sampling varied widely between studies and across different antibiotics. Methods for setting individual PK-PD targets, determining parameters and making treatment changes varied widely and were sometimes unclear.DiscussionDespite increasing observational data showing low CNS penetration of various antibiotics, there are few clinical studies describing practical implementation of TDM in management of CNS infection. Lack of consensus around clinically relevant CSF PK-PD targets and protocols for dose-adjustment may contribute. Standardised investigation of TDM as a tool to improve treatment is required, especially as innovative drug concentration-sensing and PK-PD modelling technologies are emerging. Data generated at different centres offering TDM should be open access and aggregated to enrich understanding and optimize application

What does antimicrobial stewardship look like where you are? Global narratives from participants in a massive open online course

BACKGROUND Whilst antimicrobial stewardship (AMS) is being implemented globally, contextual differences exist. We describe how the use of a massive open online course (MOOC) platform provided an opportunity to gather diverse narratives on AMS from around the world. METHODS A free 3 week MOOC titled 'Tackling antimicrobial resistance: a social science approach' was launched in November 2019. Learners were asked specific questions about their experiences of AMS via 38 optional free-text prompts dispersed throughout the modules. Content analysis was used to identify key emerging themes from the learners' responses in the first three runs of the MOOC. RESULTS Between November 2019 and July 2020, 1464 learners enrolled from 114 countries. Overall, 199 individual learners provided a total of 1097 responses to the prompts. The diverse perspectives describe unique challenges present in different contexts including ill-defined roles for pharmacists and nurses in AMS; inadequate governance and policy inconsistencies in surveillance for antibiotic consumption and antimicrobial resistance (AMR) in some countries; lack of ownership of antibiotic decision-making and buy-in from different clinical specialties; and human resource and technological constraints. Patients' knowledge, experiences and perspectives were recognized as a valuable source of information that should be incorporated in AMS initiatives to overcome cultural barriers to the judicious use of antibiotics. CONCLUSIONS Analysis of learner comments and reflections identified a range of enablers and barriers to AMS implementation across different healthcare economies. Common challenges to AMS implementation included the role of non-physician healthcare workers, resource limitations, gaps in knowledge of AMR, and patient engagement and involvement in AMS

Validating a prediction tool to determine the risk of nosocomial multidrug-resistant Gram-negative bacilli infection in critically ill patients: A retrospective case–control study

BACKGROUND:The Singapore GSDCS score was developed to enable clinicians predict the risk of nosocomial multidrug-resistant Gram-negative bacilli (RGNB) infection in critically ill patients. We aimed to validate this score in a UK setting. METHOD:A retrospective case-control study was conducted including patients who stayed for more than 24h in intensive care units (ICUs) across two tertiary National Health Service hospitals in London, UK (April 2011-April 2016). Cases with RGNB and controls with sensitive Gram-negative bacilli (SGNB) infection were identified. RESULTS:The derived GSDCS score was calculated from when there was a step change in antimicrobial therapy in response to clinical suspicion of infection as follows: prior Gram-negative organism, Surgery, Dialysis with end-stage renal disease, prior Carbapenem use and intensive care Stay of more than 5 days. A total of 110 patients with RGNB infection (cases) were matched 1:1 to 110 geotemporally chosen patients with SGNB infection (controls). The discriminatory ability of the prediction tool by receiver operating characteristic curve analysis in our validation cohort was 0.75 (95% confidence interval 0.65-0.81), which is comparable with the area under the curve of the derivation cohort (0.77). The GSDCS score differentiated between low- (0-1.3), medium- (1.4-2.3) and high-risk (2.4-4.3) patients for RGNB infection (P<0.001) in a UK setting. CONCLUSION:A simple bedside clinical prediction tool may be used to identify and differentiate patients at low, medium and high risk of RGNB infection prior to initiation of prompt empirical antimicrobial therapy in the intensive care setting

Homogeneity of antimicrobial policy, yet heterogeneity of antimicrobial resistance: antimicrobial non-susceptibility among 108,717 clinical isolates from primary, secondary and tertiary care patients in London

Objectives: We examined the four-year trend in antimicrobial susceptibilities and prescribing across levels-of-care at two London teaching hospitals and their multisite renal unit, and for the surrounding community. Methods: Laboratory and pharmacy information management systems were interrogated, with antimicrobial use and susceptibilities analysed between hospitals, within hospitals, and over time. Results: 108,717 isolates from 71,687 patients were identified, with significant differences (at p<0.05) in antimicrobial susceptibility between and within hospitals. Across the four years, rates of extended-spectrum β-lactamase (ESBL)-/AmpC-producing Enterobacteriaceae ranged from 6.4 to 10.7% among community isolates, 17.8 to 26.9% at ward level and 25.2 to 52.5% in critical-care. Significant variations were also demonstrated in glycopeptide-resistant enterococci (ward level 6.2 to 17.4%; critical-care 21.9 to 56.3%), methicillin-resistant Staphylococcus aureus (ward level 18.5 to 38.2%; critical-care 12.5 to 47.9%) and carbapenem-resistant Pseudomonas spp. (ward level 8.3 to 16.9%; critical-care 19.9 to 53.7%). Few instances of persistently higher resistance were seen between the hospitals in equivalent cohorts, despite persistently higher antimicrobial use in hospital 1 than hospital 2. We found significant fluctuations in non-susceptibility year-on-year across the cohorts, but with few persistent trends. Conclusions: The marked heterogeneity of antimicrobial susceptibilities between hospitals, within hospitals, and over time demands detailed, standardised surveillance and appropriate benchmarking to identify possible drivers and effective interventions. Homogenous antimicrobial policies are unlikely to continue to be suitable as individual hospitals join hospital networks, and policies should be tailored to local resistance rates, at least at the hospital level, and possibly with finer resolution, particularly for critical-care