Neuromodulation of the immune system has been proposed as a novel therapeutic strategy for the treatment of inflammatory conditions. We recently demonstrated that stimulation of near-organ autonomic nerves to the spleen can be harnessed to modulate the inflammatory response in an anesthetized pig model. The development of neuromodulation therapy for the clinic requires chronic efficacy and safety testing in a large animal model. This manuscript describes the effects of longitudinal conscious splenic nerve neuromodulation in chronically-implanted pigs. Firstly, clinically-relevant stimulation parameters were refined to efficiently activate the splenic nerve while reducing changes in cardiovascular parameters. Subsequently, pigs were implanted with a circumferential cuff electrode around the splenic neurovascular bundle connected to an implantable pulse generator, using a minimally-invasive laparoscopic procedure. Tolerability of stimulation was demonstrated in freely-behaving pigs using the refined stimulation parameters. Longitudinal stimulation significantly reduced circulating tumor necrosis factor alpha levels induced by systemic endotoxemia. This effect was accompanied by reduced peripheral monocytopenia as well as a lower systemic accumulation of CD16+CD14high pro-inflammatory monocytes. Further, lipid mediator profiling analysis demonstrated an increased concentration of specialized pro-resolving mediators in peripheral plasma of stimulated animals, with a concomitant reduction of pro-inflammatory eicosanoids including prostaglandins. Terminal electrophysiological and physiological measurements and histopathological assessment demonstrated integrity of the splenic nerves up to 70 days post implantation. These chronic translational experiments demonstrate that daily splenic nerve neuromodulation, via implanted electronics and clinically-relevant stimulation parameters, is well tolerated and is able to prime the immune system toward a less inflammatory, pro-resolving phenotype.
Neuromodulation is a new therapeutic pathway to treat inflammatory conditions by modulating the electrical signalling pattern of the autonomic connections to the spleen. However, targeting this sub-division of the nervous system presents specific challenges in translating nerve stimulation parameters. Firstly, autonomic nerves are typically embedded non-uniformly among visceral and connective tissues with complex interfacing requirements. Secondly, these nerves contain axons with populations of varying phenotypes leading to complexities for axon engagement and activation. Thirdly, clinical translational of methodologies attained using preclinical animal models are limited due to heterogeneity of the intra- and inter-species comparative anatomy and physiology. Here we demonstrate how this can be accomplished by the use of in silico modelling of target anatomy, and validation of these estimations through ex vivo human tissue electrophysiology studies. Neuroelectrical models are developed to address the challenges in translation of parameters, which provides strong input criteria for device design and dose selection prior to a first-in-human trial.
Cryopreservation offers the potential to increase the availability of pancreatic islets for treatment of diabetic patients. However, current protocols, which use dimethyl sulfoxide (DMSO), lead to poor cryosurvival of islets. We demonstrate that equilibration of mouse islets with small molecules in aqueous solutions can be accelerated from > 24 to 6 h by increasing incubation temperature to 37 °C. We utilize this finding to demonstrate that current viability staining protocols are inaccurate and to develop a novel cryopreservation method combining DMSO with trehalose pre-incubation to achieve improved cryosurvival. This protocol resulted in improved ATP/ADP ratios and peptide secretion from β-cells, preserved cAMP response, and a gene expression profile consistent with improved cryoprotection. Our findings have potential to increase the availability of islets for transplantation and to inform the design of cryopreservation protocols for other multicellular aggregates, including organoids and bioengineered tissues.
Background Cardiovascular diseases (CVDs) are among the leading causes of death worldwide. Predictive scores providing personalised risk of developing CVD are increasingly used in clinical practice. Most scores, however, utilise a homogenous set of features and require the presence of a physician. Objective The aim was to develop a new risk model (DiCAVA) using statistical and machine learning techniques that could be applied in a remote setting. A secondary goal was to identify new patient-centric variables that could be incorporated into CVD risk assessments. Methods Across 466,052 participants, Cox proportional hazards (CPH) and DeepSurv models were trained using 608 variables derived from the UK Biobank to investigate the 10-year risk of developing a CVD. Data-driven feature selection reduced the number of features to 47, after which reduced models were trained. Both models were compared to the Framingham score. Results The reduced CPH model achieved a c-index of 0.7443, whereas DeepSurv achieved a c-index of 0.7446. Both CPH and DeepSurv were superior in determining the CVD risk compared to Framingham score. Minimal difference was observed when cholesterol and blood pressure were excluded from the models (CPH: 0.741, DeepSurv: 0.739). The models show very good calibration and discrimination on the test data. Conclusion We developed a cardiovascular risk model that has very good predictive capacity and encompasses new variables. The score could be incorporated into clinical practice and utilised in a remote setting, without the need of including cholesterol. Future studies will focus on external validation across heterogeneous samples.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.