Resveratrol Targeting of Carcinogen-Induced Brain Endothelial Cell Inflammation Biomarkers MMP-9 and COX-2 is Sirt1-Independent

The occurrence of a functional relationship between the release of metalloproteinases (MMPs) and the expression of cyclooxygenase (COX)-2, two inducible pro-inflammatory biomarkers with important pro-angiogenic effects, has recently been inferred. While brain endothelial cells play an essential role as structural and functional components of the blood-brain barrier (BBB), increased BBB breakdown is thought to be linked to neuroinflammation. Chemopreventive mechanisms targeting both MMPs and COX-2 however remain poorly investigated. In this study, we evaluated the pharmacological targeting of Sirt1 by the diet-derived and antiinflammatory polyphenol resveratrol. Total RNA, cell lysates, and conditioned culture media from human brain microvascular endothelial cells (HBMEC) were analyzed using qRT-PCR, immunoblotting, and zymography respectively. Tissue scan microarray analysis of grade I–IV brain tumours cDNA revealed increased gene expression of Sirt-1 from grade I–III but surprisingly not in grade IV brain tumours. HBMEC were treated with a combination of resveratrol and phorbol 12-myristate 13-acetate (PMA), a carcinogen known to increase MMP-9 and COX-2 through NF-κB. We found that resveratrol efficiently reversed the PMA-induced MMP-9 secretion and COX-2 expression. Gene silencing of Sirt1, a critical modulator of angiogenesis and putative target of resveratrol, did not lead to significant reversal of MMP-9 and COX-2 inhibition. Decreased resveratrol inhibitory potential of carcinogen-induced IκB phosphorylation in siSirt1-transfected HBMEC was however observed. Our results suggest that resveratrol may prevent BBB disruption during neuroinflammation by inhibiting MMP-9 and COX-2 and act as a pharmacological NF-κB signal transduction inhibitor independent of Sirt1

Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries

Phase Resetting and Phase Locking in Hybrid Circuits of One Model and One Biological Neuron

To determine why elements of central pattern generators phase lock in a particular pattern under some conditions but not others, we tested a theoretical pattern prediction method. The method is based on the tabulated open loop pulsatile interactions of bursting neurons on a cycle-by-cycle basis and was tested in closed loop hybrid circuits composed of one bursting biological neuron and one bursting model neuron coupled using the dynamic clamp. A total of 164 hybrid networks were formed by varying the synaptic conductances. The prediction of 1:1 phase locking agreed qualitatively with the experimental observations, except in three hybrid circuits in which 1:1 locking was predicted but not observed. Correct predictions sometimes required consideration of the second order phase resetting, which measures the change in the timing of the second burst after the perturbation. The method was robust to offsets between the initiation of bursting in the presynaptic neuron and the activation of the synaptic coupling with the postsynaptic neuron. The quantitative accuracy of the predictions fell within the variability (10%) in the experimentally observed intrinsic period and phase resetting curve (PRC), despite changes in the burst duration of the neurons between open and closed loop conditions