N-acylethanolamine regulation of TLR3-induced hyperthermia and neuroinflammatory gene expression: A role for PPARα.

Increasing evidence suggests that SARS-CoV-2, the virus responsible for the COVID-19 pandemic, is associated with increased risk of developing neurological or psychiatric conditions such as depression, anxiety or dementia. While the precise mechanism underlying this association is unknown, aberrant activation of toll-like receptor (TLR)3, a viral recognizing pattern recognition receptor, may play a key role. Synthetic cannabinoids and enhancing cannabinoid tone via inhibition of fatty acid amide hydrolase (FAAH) has been demonstrated to modulate TLR3-induced neuroimmune responses and associated sickness behaviour. However, the role of individual FAAH substrates, and the receptor mechanisms mediating these effects, are unknown. The present study examined the effects of intracerebral or systemic administration of the FAAH substrates N-oleoylethanolamide (OEA), N-palmitoylethanolamide (PEA) or the anandamide (AEA) analogue meth-AEA on hyperthermia and hypothalamic inflammatory gene expression following administration of the TLR3 agonist, and viral mimetic, poly I:C. The data demonstrate that meth-AEA does not alter TLR3-induced hyperthermia or hypothalamic inflammatory gene expression. In comparison, OEA and PEA attenuated the TLR3-induced hyperthermia, although only OEA attenuated the expression of hyperthermia-related genes (IL-1ß, iNOS, COX2 and m-PGES) in the hypothalamus. OEA, but not PEA, attenuated TLR3-induced increases in the expression of all IRF- and NFκB-related genes examined in the hypothalamus, but not in the spleen. Antagonism of PPARα prevented the OEA-induced attenuation of IRF- and NFκB-related genes in the hypothalamus following TLR3 activation but did not significantly alter temperature. PPARα agonism did not alter TLR3-induced hyperthermia or hypothalamic inflammatory gene expression. These data indicate that OEA may be the primary FAAH substrate that modulates TLR3-induced neuroinflammation and hyperthermia, effects partially mediated by PPARα.

FPGA-Based Soft-Core Processors for Image Processing Applications.

With security and surveillance, there is an increasing need to process image data efficiently and effectively either at source or in a large data network. Whilst a Field-Programmable Gate Array has been seen as a key technology for enabling this, the design process has been viewed as problematic in terms of the time and effort needed for implementation and verification. The work here proposes a different approach of using optimized FPGA-based soft-core processors which allows the user to exploit the task and data level parallelism to achieve the quality of dedicated FPGA implementations whilst reducing design time. The paper also reports some preliminary progress on the design flow to program the structure. An implementation for a Histogram of Gradients algorithm is also reported which shows that a performance of 328 fps can be achieved with this design approach, whilst avoiding the long design time, verification and debugging steps associated with conventional FPGA implementations.