Identification Of Lipolysis-Derived Lipid Mediators And The Activation Of A Pro-Inflammatory Cyclooxygenase Pathway, Via Cyclooxygenase-2, In Adipose Tissue

Adipose lipolysis triggers pro-inflammatory responses that play critical roles in insulin resistance and associated metabolic syndrome. However, pro-inflammatory mediators generated by adipose lipolysis, particularly in the context of lipid mediators, are poorly defined. In this study, the activation of the beta-3 adrenergic receptor (ADRB3)/hormone sensitive lipase (HSL) pathway, a well-employed model system, was utilized to characterize the pro-inflammatory lipid mediators generated by adipose lipolysis. Cultured adipocytes were treated with an ADRB3 agonist and the media was analyzed for eicosanoids using the LC-MS/MS lipidomic method. Among the characterized eicosanoids, I found that approximately 43 metabolites generated by cyclooxygenase (COX), lipoxygenase, and cytochrome P450 enzymes were significantly produced in response to ADRB3/HSL-stimulated lipolysis in adipocytes. Mechanistically, I observed that lipolysis induced cyclooxygenase 2 (COX-2), not COX-1, expression in an HSL-dependent manner in adipocytes and in the epididymal white adipose tissue (EWAT) of C57BL/6 mice that were injected with a specific ADRB3 agonist, CL-316243 (CL). Additionally, JNK and NFκB are activated by ADRB3-mediated lipolysis and regulate the increased COX-2 expression. Moreover, treatment with a pharmacological COX-2 inhibitor, celecoxib, decreased the COX metabolites in the media of ADRB3-stimulated adipocytes. Inflamed adipose tissue involves the increased presence and activation of macrophages that are recruited to the tissue by the pro-inflammatory cytokine, MCP-1/CCL2. Interestingly, not only was MCP-1/CCL2 expression significantly increased in ADRB3/HSL-mediated lipolysis, but its expression was also dependent on JNK/NFκB/COX-2 activation. Furthermore, I observed that celecoxib pretreatment significantly blocked macrophage infiltration in the EWAT of mice treated with CL. In summary, I have shown for the first time that ADRB3/HSL signaling activates a pro-inflammatory cyclooxygenase pathway via COX-2, in adipose tissue

Generalizing mkFit and its Application to HL-LHC

mkFit is an implementation of the Kalman filter-based track reconstruction algorithm that exploits both thread- and data-level parallelism. In the past few years the project transitioned from the R&D phase to deployment in the Run-3 offline workflow of the CMS experiment. The CMS tracking performs a series of iterations, targeting reconstruction of tracks of increasing difficulty after removing hits associated to tracks found in previous iterations. mkFit has been adopted for several of the tracking iterations, which contribute to the majority of reconstructed tracks. When tested in the standard conditions for production jobs, speedups in track pattern recognition are on average of the order of 3.5x for the iterations where it is used (3-7x depending on the iteration). Multiple factors contribute to the observed speedups, including vectorization and a lightweight geometry description, as well as improved memory management and single precision. Efficient vectorization is achieved with both the icc and the gcc (default in CMSSW) compilers and relies on a dedicated library for small matrix operations, Matriplex, which has recently been released in a public repository. While the mkFit geometry description already featured levels of abstraction from the actual Phase-1 CMS tracker, several components of the implementations were still tied to that specific geometry. We have further generalized the geometry description and the configuration of the run-time parameters, in order to enable support for the Phase-2 upgraded tracker geometry for the HL-LHC and potentially other detector configurations. The implementation strategy and high-level code changes required for the HL-LHC geometry are presented. Speedups in track building from mkFit imply that track fitting becomes a comparably time consuming step of the tracking chain

Generalizing mkFit and its Application to HL-LHC

mkFit is an implementation of the Kalman filter-based track reconstruction algorithm that exploits both threadand data-level parallelism. In the past few years the project transitioned from the R&D phase to deployment in the Run-3 offline workflow of the CMS experiment. The CMS tracking performs a series of iterations, targeting reconstruction of tracks of increasing difficulty after removing hits associated to tracks found in previous iterations. mkFit has been adopted for several of the tracking iterations, which contribute to the majority of reconstructed tracks. When tested in the standard conditions for production jobs, speedups in track pattern recognition are on average of the order of 3.5x for the iterations where it is used (3-7x depending on the iteration). Multiple factors contribute to the observed speedups, including vectorization and a lightweight geometry description, as well as improved memory management and single precision. Efficient vectorization is achieved with both the icc and the gcc (default in CMSSW) compilers and relies on a dedicated library for small matrix operations, Matriplex, which has recently been released in a public repository. While the mkFit geometry description already featured levels of abstraction from the actual Phase-1 CMS tracker, several components of the implementations were still tied to that specific geometry. We have further generalized the geometry description and the configuration of the run-time parameters, in order to enable support for the Phase-2 upgraded tracker geometry for the HL-LHC and potentially other detector configurations. The implementation strategy and high-level code changes required for the HL-LHC geometry are presented. Speedups in track building from mkFit imply that track fitting becomes a comparably time consuming step of the tracking chain. Prospects for an mkFit implementation of the track fit are also discussed

Resolvins suppress tumor growth and enhance cancer therapy

National Cancer Institute grants RO1 01CA170549-02 (to D. Panigrahy and C.N. Serhan), ROCA148633-01A4 (to D. Panigrahy), and GM095467 (to C.N. Serhan); the Stop and Shop Pediatric Brain Tumor Fund (to M.W. Kieran); the CJ Buckley Pediatric Brain Tumor Fund (to M.W. Kieran); Alex Lemonade Stand (to M.W. Kieran); Molly’s Magic Wand for Pediatric Brain Tumors (to M.W. Kieran); the Markoff Foundation Art-In-Giving Foundation (to M.W. Kieran); the Kamen Foundation (to M.W. Kieran); Jared Branfman Sunflowers for Life (to M.W.K.); and The Wellcome Trust program 086867/Z/08 (to M. Perretti)

Inflammation resolution: a dual-pronged approach to averting cytokine storms in COVID-19?

Severe coronavirus disease (COVID-19) is characterized by pulmonary hyper-inflammation and potentially life-threatening cytokine storms . Controlling the local and systemic inflammatory response in COVID-19 may be as important as anti-viral therapies. Endogenous lipid autacoid mediators, referred to as eicosanoids, play a critical role in the induction of inflammation and pro-inflammatory cytokine production. SARS-CoV-2 may trigger a cell death ( debris )-induced eicosanoid storm , including prostaglandins and leukotrienes, which in turn initiates a robust inflammatory response. A paradigm shift is emerging in our understanding of the resolution of inflammation as an active biochemical process with the discovery of novel endogenous specialized pro-resolving lipid autacoid mediators (SPMs), such as resolvins. Resolvins and other SPMs stimulate macrophage-mediated clearance of debris and counter pro-inflammatory cytokine production, a process called inflammation resolution. SPMs and their lipid precursors exhibit anti-viral activity at nanogram doses in the setting of influenza without being immunosuppressive. SPMs also promote anti-viral B cell antibodies and lymphocyte activity, highlighting their potential use in the treatment of COVID-19. Soluble epoxide hydrolase (sEH) inhibitors stabilize arachidonic acid-derived epoxyeicosatrienoic acids (EETs), which also stimulate inflammation resolution by promoting the production of pro-resolution mediators, activating anti-inflammatory processes, and preventing the cytokine storm. Both resolvins and EETs also attenuate pathological thrombosis and promote clot removal, which is emerging as a key pathology of COVID-19 infection. Thus, both SPMs and sEH inhibitors may promote the resolution of inflammation in COVID-19, thereby reducing acute respiratory distress syndrome (ARDS) and other life-threatening complications associated with robust viral-induced inflammation. While most COVID-19 clinical trials focus on anti-viral and anti-inflammatory strategies, stimulating inflammation resolution is a novel host-centric therapeutic avenue. Importantly, SPMs and sEH inhibitors are currently in clinical trials for other inflammatory diseases and could be rapidly translated for the management of COVID-19 via debris clearance and inflammatory cytokine suppression. Here, we discuss using pro-resolution mediators as a potential complement to current anti-viral strategies for COVID-19

Aspirin-triggered proresolving mediators stimulate resolution in cancer.

Inflammation in the tumor microenvironment is a strong promoter of tumor growth. Substantial epidemiologic evidence suggests that aspirin, which suppresses inflammation, reduces the risk of cancer. The mechanism by which aspirin inhibits cancer has remained unclear, and toxicity has limited its clinical use. Aspirin not only blocks the biosynthesis of prostaglandins, but also stimulates the endogenous production of anti-inflammatory and proresolving mediators termed aspirin-triggered specialized proresolving mediators (AT-SPMs), such as aspirin-triggered resolvins (AT-RvDs) and lipoxins (AT-LXs). Using genetic and pharmacologic manipulation of a proresolving receptor, we demonstrate that AT-RvDs mediate the antitumor activity of aspirin. Moreover, treatment of mice with AT-RvDs (e.g., AT-RvD1 and AT-RvD3) or AT-LX

Generalizing mkFit and its Application to HL-LHC

mkFit is an implementation of the Kalman filter-based track reconstruction algorithm that exploits both thread- and data-level parallelism. In the past few years the project transitioned from the R&D phase to deployment in the Run-3 offline workflow of the CMS experiment. The CMS tracking performs a series of iterations, targeting reconstruction of tracks of increasing difficulty after removing hits associated to tracks found in previous iterations. mkFit has been adopted for several of the tracking iterations, which contribute to the majority of reconstructed tracks. When tested in the standard conditions for production jobs, speedups in track pattern recognition are on average of the order of 3.5x for the iterations where it is used (3-7x depending on the iteration). Multiple factors contribute to the observed speedups, including vectorization and a lightweight geometry description, as well as improved memory management and single precision. Efficient vectorization is achieved with both the icc and the gcc (default in CMSSW) compilers and relies on a dedicated library for small matrix operations, Matriplex, which has recently been released in a public repository. While the mkFit geometry description already featured levels of abstraction from the actual Phase-1 CMS tracker, several components of the implementations were still tied to that specific geometry. We have further generalized the geometry description and the configuration of the run-time parameters, in order to enable support for the Phase-2 upgraded tracker geometry for the HL-LHC and potentially other detector configurations. The implementation strategy and high-level code changes required for the HL-LHC geometry are presented. Speedups in track building from mkFit imply that track fitting becomes a comparably time consuming step of the tracking chain