Diabetes-induced microvascular complications at the level of the spinal cord: a contributing factor in diabetic neuropathic pain.

KEY POINTS: Diabetes is thought to induce neuropathic pain through activation of dorsal horn sensory neurons in the spinal cord. Here we explore the impact of hyperglycaemia on the blood supply supporting the spinal cord and chronic pain development. In streptozotocin-induced diabetic rats, neuropathic pain is accompanied by a decline in microvascular integrity in the dorsal horn. Hyperglycaemia-induced degeneration of the endothelium in the dorsal horn was associated with a loss in vascular endothelial growth factor (VEGF)-A165 b expression. VEGF-A165 b treatment prevented diabetic neuropathic pain and degeneration of the endothelium in the spinal cord. Using an endothelial-specific VEGFR2 knockout transgenic mouse model, the loss of endothelial VEGFR2 signalling led to a decline in vascular integrity in the dorsal horn and the development of hyperalgesia in VEGFR2 knockout mice. This highlights that vascular degeneration in the spinal cord could be a previously unidentified factor in the development of diabetic neuropathic pain. ABSTRACT: Abnormalities of neurovascular interactions within the CNS of diabetic patients is associated with the onset of many neurological disease states. However, to date, the link between the neurovascular network within the spinal cord and regulation of nociception has not been investigated despite neuropathic pain being common in diabetes. We hypothesised that hyperglycaemia-induced endothelial degeneration in the spinal cord, due to suppression of vascular endothelial growth factor (VEGF)-A/VEGFR2 signalling, induces diabetic neuropathic pain. Nociceptive pain behaviour was investigated in a chemically induced model of type 1 diabetes (streptozotocin induced, insulin supplemented; either vehicle or VEGF-A165 b treated) and an inducible endothelial knockdown of VEGFR2 (tamoxifen induced). Diabetic animals developed mechanical allodynia and heat hyperalgesia. This was associated with a reduction in the number of blood vessels and reduction in Evans blue extravasation in the lumbar spinal cord of diabetic animals versus age-matched controls. Endothelial markers occludin, CD31 and VE-cadherin were downregulated in the spinal cord of the diabetic group versus controls, and there was a concurrent reduction of VEGF-A165 b expression. In diabetic animals, VEGF-A165 b treatment (biweekly i.p., 20 ng g-1 ) restored normal Evans blue extravasation and prevented vascular degeneration, diabetes-induced central neuron activation and neuropathic pain. Inducible knockdown of VEGFR2 (tamoxifen treated Tie2CreERT2 -vegfr2flfl mice) led to a reduction in blood vessel network volume in the lumbar spinal cord and development of heat hyperalgesia. These findings indicate that hyperglycaemia leads to a reduction in the VEGF-A/VEGFR2 signalling cascade, resulting in endothelial dysfunction in the spinal cord, which could be an undiscovered contributing factor to diabetic neuropathic pain.

A novel random forest approach to revealing interactions and controls on chlorophyll concentration and bacterial communities during coastal phytoplankton blooms.

Increasing occurrence of harmful algal blooms across the land-water interface poses significant risks to coastal ecosystem structure and human health. Defining significant drivers and their interactive impacts on blooms allows for more effective analysis and identification of specific conditions supporting phytoplankton growth. A novel iterative Random Forests (iRF) machine-learning model was developed and applied to two example cases along the California coast to identify key stable interactions: (1) phytoplankton abundance in response to various drivers due to coastal conditions and land-sea nutrient fluxes, (2) microbial community structure during algal blooms. In Example 1, watershed derived nutrients were identified as the least significant interacting variable associated with Monterey Bay phytoplankton abundance. In Example 2, through iRF analysis of field-based 16S OTU bacterial community and algae datasets, we independently found stable interactions of prokaryote abundance patterns associated with phytoplankton abundance that have been previously identified in laboratory-based studies. Our study represents the first iRF application to marine algal blooms that helps to identify ocean, microbial, and terrestrial conditions that are considered dominant causal factors on bloom dynamics.