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Biology subjects

Raby, E.

Publications and source records attributed to Raby, E..

3 recordsLinked to original sources

Clinical prediction of wound re-epithelisation outcomes in non-severe burn injury using the plasma lipidome

Whilst wound repair in severe burns has received substantial research attention, non-severe burns (<20% total body surface area) remain relatively understudied, despite causing considerable physiological impact and constituting most of the hospital admissions for burns. Early prediction of healing outcomes would decrease financial and patient burden, and aid in preventing long-term complications from poor wound healing. Lipids have been implicated in inflammation and tissue repair and may play essential roles in burn wound healing. In this study, plasma samples were collected from 20 non-severe burn patients over 6 weeks from admission, including surgery, and analysed by liquid chromatography-tandem mass spectrometry and nuclear magnetic resonance spectroscopy to detect 850 lipids and 112 lipoproteins. Orthogonal projections to latent structures-discriminant analysis was performed to identify changes associated with re-epithelialisation and delayed re-epithelisation. We demonstrated that the lipid and lipoprotein profiles at admission could predict re-epithelisation outcomes at 2 weeks post-surgery, and that these discriminatory profiles were maintained up to 6 weeks post-burn. Inflammatory markers GlycB and C-reactive protein indicated divergent systemic responses to the burn injury at admission. Triacylglycerols, diacylglycerols and low-density lipoprotein subfractions were associated with delayed wound closure (p-value <0.02, Cliffs delta >0.7), whilst high-density lipoprotein subfractions, phosphatidylinositols, phosphatidylcholines, and phosphatidylserines were associated with re-epithelisation at 2 weeks post-surgery (p-value <0.01, Cliffs delta <-0.7). Further model validation will potentially lead to personalised intervention strategies to reduce the risk of chronic complications post-burn injury.

systems biology↗

Metabolic consequences of non-severe burn injury are associated with increased plasma markers of inflammation and cardiovascular disease risk.

Globally, burns are a significant cause of injury that can cause substantial acute trauma as well as lead to increased incidence of chronic co-morbidity and disease. To date, research has primarily focused on the systemic response to severe injury, with little in the literature reported on impact of non-severe injuries (<15% total burn surface area; TBSA). To elucidate the metabolic consequences of non-severe burn injury, longitudinal plasma was collected from adults (n=35) who presented at hospital with a non-severe burn injury at admission, and at 6 week follow up. A cross-sectional baseline sample was also collected from non-burn control participants (n=14). Samples underwent multiplatform metabolic phenotyping using 1H nuclear magnetic resonance spectroscopy and liquid chromatography-mass spectrometry to quantify 112 lipoprotein and glycoproteins signatures and 852 lipid species from across 20 subclasses. Multivariate data modelling (Orthogonal projection to latent structures-discriminate analysis) revealed alterations in lipoprotein and lipid metabolism when comparing baseline control to hospital admission samples, with the phenotypic signature found to be sustained at follow up. Univariate (Mann-Whitney U) testing and OPLS-DA indicated specific increases in GlycB (p-value <1.0e-4), low density lipoprotein-2 subfractions (Variable importance in projection score; VIP >6.83e-1) and monoacyglyceride (20:4)(p-value <1.0e-4) and decreases in circulating anti-inflammatory high-density lipoprotein-4 subfractions (VIP >7.75e-1), phosphatidylcholines, phosphatidylglycerols, phosphatidylinositols and phosphatidylserines. The results indicate a persistent systemic metabolic phenotype that occurs even in cases of non-severe burn injury. The phenotype is indicative of an acute inflammatory profile which continues to be sustained post-injury, suggesting an impact on systems health beyond the site of injury. The phenotypes contained metabolic signatures consistent with chronic inflammatory states reported to have elevated incidence post-burn injury. Such phenotypic signatures may provide patient stratification opportunities, to identify individual responses to injury, personalise intervention strategies and improve acute care, reducing risk of chronic co-morbidity.

systems biology↗

Hunting Eagles with glass mice: revisiting the inoculum effect for Streptococcus pyogenes with a hollow fibre infection model

BackgroundSevere, invasive Streptococcus pyogenes (Strep A) infections result in greater than 500,000 deaths annually. First line treatment for such infections is combination benzylpenicillin and clindamycin, but treatment failure can occur with this regimen. This failure has been partially attributed to the inoculum effect, which presents as reduced antibiotic susceptibility during high bacterial density and plateau-phase growth. Hollow fibre infection models (HFIM) have been proposed as an alternative to in vivo research to study these effects. ObjectivesTo re-evaluate the inoculum effect for benzylpenicillin, clindamycin, linezolid and trimethoprim-sulfamethoxazole using a Strep A HFIM. MethodsDifferential antibiotic susceptibility of Strep A was measured in a HFIM starting from low- and high-density inocula. Dynamic antibiotic concentrations were delivered over 48 hours to simulate human pharmacokinetics. Differences in antibiotic susceptibility were determined at 24 and 48 hours by plate count of remaining viable colony-forming units. ResultsInoculum effects were seen in benzylpenicillin and linezolid at 24 hours, and benzylpenicillin, linezolid and clindamycin at 48 hours. The effect size was greatest for continuously infused benzylpenicillin. No inoculum effect was seen in trimethoprim-sulfamethoxazole. ConclusionsInoculum effects were seen in the HFIM model using benzylpenicillin, linezolid and clindamycin, which may predict reduced clinical efficacy following treatment delay. The model has proven robust and largely in agreeance with published data, recommending it for further Strep A study.

microbiology↗