text:
Research ArticleInflammation Open Access | 10.1172/jci.insight.138385
Antineutrophil properties of natural gingerols in models of lupus
Ramadan A. Ali,1 Alex A. Gandhi,1 Lipeng Dai,2 Julia Weiner,1 Shanea K. Estes,1 Srilakshmi Yalavarthi,1 Kelsey Gockman,1 Duxin Sun,2 and Jason S. Knight1
1Division of Rheumatology, Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan, USA.
2Department of Pharmaceutical Sciences, College of Pharmacy, University of Michigan, Ann Arbor, Michigan, USA.
Address correspondence to: Jason S. Knight, 1150 W. Medical Center Drive, Ann Arbor, Michigan 48109, USA. Phone: 734.936.3257; Email: jsknight@umich.edu.
Find articles by Ali, R. in: JCI | PubMed | Google Scholar
Find articles by Gandhi, A. in: JCI | PubMed | Google Scholar
Find articles by Dai, L. in: JCI | PubMed | Google Scholar
Find articles by Weiner, J. in: JCI | PubMed | Google Scholar
Find articles by Estes, S. in: JCI | PubMed | Google Scholar
Find articles by Yalavarthi, S. in: JCI | PubMed | Google Scholar
Find articles by Gockman, K. in: JCI | PubMed | Google Scholar
Find articles by Sun, D. in: JCI | PubMed | Google Scholar
Find articles by Knight, J. in: JCI | PubMed | Google Scholar |
Published December 29, 2020 - More info
Published in Volume 6, Issue 3 on February 8, 2021
© 2021 Ali et al. This work is licensed under the Creative Commons Attribution 4.0 International License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
Published December 29, 2020 - Version history
Received: March 23, 2020; Accepted: December 16, 2020
Ginger is known to have antiinflammatory and antioxidative effects and has traditionally been used as an herbal supplement in the treatment of various chronic diseases. Here, we report antineutrophil properties of 6-gingerol, the most abundant bioactive compound of ginger root, in models of lupus and antiphospholipid syndrome (APS). Specifically, we demonstrate that 6-gingerol attenuates neutrophil extracellular trap (NET) release in response to lupus- and APS-relevant stimuli through a mechanism that is at least partially dependent on inhibition of phosphodiesterases. At the same time, administration of 6-gingerol to mice reduces NET release in various models of lupus and APS, while also improving other disease-relevant endpoints, such as autoantibody formation and large-vein thrombosis. In summary, this study is the first to our knowledge to demonstrate a protective role for ginger-derived compounds in the context of lupus. Importantly, it provides a potential mechanism for these effects via phosphodiesterase inhibition and attenuation of neutrophil hyperactivity.
Systemic lupus erythematosus (lupus) is the prototypical systemic autoimmune disease, characterized by antinuclear autoantibodies and circulating immune complexes. Lupus has the potential to impact essentially any organ in the body. Antiphospholipid syndrome (APS) is a closely related thromboinflammatory disease defined by the presence of circulating antiphospholipid antibodies (aPL), as detected by anticardiolipin or anti–β-2-glycoprotein I (anti-β2GPI) immunoassays or the functional lupus anticoagulant screen (1, 2). APS is a leading acquired cause of thrombosis and pregnancy loss (3) and can occur as a standalone syndrome (primary APS) or in association with lupus (4). In fact, aPL are present in one-third of patients with lupus, amplifying the risk of the thromboembolic events that are among the leading causes of morbidity and mortality in lupus.
Neutrophils release neutrophil extracellular traps (NETs) — tangles of chromatin and microbicidal proteins expelled from neutrophils in response to both infectious and sterile stimuli (5, 6) — which have garnered much recent attention as amplifiers of inflammation and thrombosis in autoimmune diseases such as lupus and APS (7–10). For example, rising levels of blood neutrophils predict glomerulonephritis in lupus (11), while recent studies by our group and others have revealed a key role for neutrophils and NETs in the thrombotic manifestation inherent to lupus and APS. We have shown that patients with APS have higher levels of cell-free DNA and NETs in plasma and that their neutrophils are prone to spontaneous NETosis as compared with healthy controls (12). Furthermore, aPL isolated from patients with APS can trigger healthy control neutrophils to release NETs (12), while also potentiating thrombosis in vivo in neutrophil- and NET-dependent fashion (13). In lupus and APS, NETs promote type I IFN production (14, 15) and autoantibody formation (16, 17). At the same time, lupus-associated autoantibodies, including anti-ribonucleoprotein (anti-RNP) (14), aPL (12), and anti–double-stranded DNA (anti–dsDNA) (18), accelerate NETosis, thereby setting up a vicious cycle.
Ginger has long been perceived to have antiinflammatory and antioxidative properties (19, 20) and has been used traditionally as herbal medicine for the treatment of many ailments, including chronic conditions such as asthma and arthritis. The health-promoting properties of ginger have been attributed to its richness in phenolic phytochemicals (21), such as gingerols and shogaols (22, 23). Of these bioactive compounds, 6-gingerol is the most abundant in fresh ginger, with concentrations of up to 2100 μg/g (24). It has been suggested that ginger may mediate its antiinflammatory effects by reducing levels of proinflammatory cytokines as well as tempering synthesis and secretion of chemokines at sites of inflammation. For example, whole ginger extract can inhibit IL-12, TNF-α, IL-1β, RANTES, and MCP-1 production by LPS-stimulated macrophages (25). Similar effects can be achieved using 6-gingerol alone (26), which also extend to human synoviocytes and chondrocytes (27, 28). In vivo, 6-gingerol blocks activation of NF-κB in phorbol ester–stimulated mouse skin (29) and suppresses the inflammatory response to carrageenan-induced paw edema in rats (30). However, none of these studies have provided a detailed explanation of mechanism.
We were intrigued by recent studies that reported a role for ginger extract and specifically 6-gingerol as inhibitors of cAMP-specific phosphodiesterase (PDE) activity. For example, both ginger extract and 6-gingerol appear to inhibit PDE4 activity in vitro, as tested in human cell lines expressing predominantly the PDE4 isoform (31). In addition, an in silico study identified 3 candidates (including 6-gingerol) from ginger as potential PDE4 inhibitors capable of inhibiting cAMP binding and hydrolysis by PDE4 (32). PDEs (and especially PDE4, the predominant isotype expressed by leukocytes) are attractive therapeutic targets for chronic inflammatory diseases. Theophylline, a nonspecific PDE inhibitor, is leveraged for its antiinflammatory and vasodilatory properties in the treatment of asthma and chronic obstructive pulmonary disease (33). There has also been targeted drug development, including the PDE4 inhibitor apremilast, which is currently used in the clinic in the context of psoriasis, psoriatic arthritis, and Behçet's disease (34).
The antiinflammatory effects of ginger have yet to be investigated in the context of lupus and APS. Of particular note, no attention has been given to the effects of gingerols on activation and function of neutrophils as thromboinflammatory mediators in lupus and APS. Given evidence that gingerols may similarly exploit cAMP-regulated pathways that we recently characterized in lupus and APS neutrophils (35), here we sought to determine the extent to which ginger-derived compounds might function as natural suppressors of aberrant neutrophil hyperactivity.
Gingerols inhibit NETosis elicited by E. coli LPS. We first tested the efficacy of 3 related compounds, 6-gingerol, 8-gingerol, and 10-gingerol (differing only in length of aliphatic side chain), for their ability to suppress NETosis by control neutrophils. We found that both 6- and 8-gingerol at concentrations as low as 10 μM completely neutralized LPS-triggered NETosis (Figure 1, A–C). We then asked whether inhibition would extend to NETosis activated by phorbol 12-myristate 13-acetate (PMA). Indeed, PMA-mediated NETosis was also suppressed by all gingerols (Figure 1D).
Gingerol suppresses NETosis in response to various stimuli. Human neutrophils were isolated from healthy volunteers and then treated with various stimuli for 3 hours in the presence of different gingerol analogues. NETosis was quantified by measuring the enzymatic activity of nuclease-liberated myeloperoxidase (MPO). Dose response to LPS-mediated NETosis upon treatment with 6-gingerol (A), 8-gingerol (B), and 10-gingerol (C). NETosis in response to PMA (D), RNP ICs (E), and APS IgG (F) was quantified in the presence of 10 μM gingerol. NETosis was assessed by immunofluorescence microscopy (G). Neutrophils were treated with LPS, PMA, RNP ICs, or APS IgG in the presence or absence of 6-gingerol (10 μM). Blue, DNA; green, extracellular neutrophil elastase. Scale bar: 100 microns. For A–F, mean and SEM are presented for n = 3 independent experiments; *P < 0.05, **P < 0.01, ****P < 0.0001 as compared with the 0 μM gingerol group by 1-way ANOVA corrected with Dunnett's test.
Gingerols inhibit NETosis elicited by lupus and APS autoantibodies. Neutrophils are activated by various lupus-relevant stimuli, including RNP-containing immune complexes (ICs) and aPL to release NETs. We tested the efficacy of 6-gingerol, 8-gingerol, and 10-gingerol for their ability to suppress NETosis when control neutrophils were activated by either RNP ICs or aPL. All 3 gingerols suppressed RNP IC–induced NETosis at the 10 μM concentration, while 6- and 8-gingerol neutralized aPL-mediated NETosis at the same dose (Figure 1, E and F). The impact of 6-gingerol on NETosis was also assessed by immunofluorescence microscopy with similar results (Figure 1G). The 10 μM concentration was the lowest dose that prevented NETosis in response to LPS (Figure 1A), PMA, and APS IgG (Supplemental Figure 1, A–B; supplemental material available online with this article; https://doi.org/10.1172/jci.insight.138385DS1). At the same time, we found that neutrophils appear healthy over 3 hours, even at concentrations as high as 1 mM 6-gingerol (Supplemental Figure 1C). In summary, these data demonstrate that gingerols have broad anti-NETosis properties that extend to lupus-relevant stimuli, such as RNP ICs and aPL.
Gingerols inhibit ROS formation by neutrophils. Ginger has been reported to have antioxidative properties. Thus, we reasoned that gingerols might suppress NETosis by preventing the neutrophil oxidative burst, as ROS are required for most forms of NETosis. All gingerols suppressed formation of H2O2 in neutrophils, whether stimulated by LPS, PMA, RNP ICs, or aPL (Figure 2). Taken together, these data suggest a potential mechanism by which gingerols mitigate NETosis, namely by suppressing ROS formation.
Gingerols suppress ROS. Human neutrophils were treated with various stimuli in the presence of different gingerol analogs for 1 hour. Hydrogen peroxide formation was measured by a colorimetric assay. Mean and SEM are presented for n = 3 independent experiments; *P < 0.05, ****P < 0.0001 as compared with the LPS-alone group (A), PMA-alone group (B), RNP ICs–alone group (C), or APS IgG–alone group (D) by 1-way ANOVA corrected with Dunnett's test.
6-Gingerol inhibits cAMP-specific PDE activity. Ginger extracts and specifically 6-gingerol have been suggested to function as PDE inhibitors. Here, we reasoned that 6-gingerol might suppress NETosis through modulation of cAMP levels and downstream pathways. We first tested the effect of 6-gingerol on PDE activity in neutrophils. We found that 6-gingerol reduced PDE activity by 40%, as compared with a 50% reduction by the synthetic PDE4 inhibitor rolipram (Figure 3A). We also measured intracellular concentrations of cAMP upon stimulation of neutrophils with the adenylate cyclase activator forskolin. Interestingly, both 6-gingerol and 3-isobutyl-1-methylxanthine (IBMX) (another synthetic PDE inhibitor) significantly potentiated intracellular cAMP concentrations, as compared with untreated samples (Figure 3B). Having documented a gingerol-mediated increase in intracellular concentrations of cAMP, we considered that activity of the key downstream cAMP-dependent kinase, PKA, might also increase in neutrophils. Indeed, 6-gingerol significantly enhanced neutrophil PKA activity (Figure 3, C and D). Furthermore, the suppressive effects of 6-gingerol on NETosis could be mitigated by blocking PKA activity (Figure 3E). In summary, these data demonstrate that 6-gingerol attenuates NETosis in vitro through a mechanism that at least partially depends on inhibition of PDE activity, potentiation of cAMP levels, and resultant activation of PKA.
6-Gingerol blocks PDE activity and raises cAMP levels. Human neutrophils were treated with 6-gingerol. Some samples were additionally treated with forskolin, cAMP, and synthetic PDE4 inhibitors (rolipram and IBMX) as indicated. PDE activity (A), cAMP levels (B), and PKA activity (C and D) were measured with kits as described in Methods. In E, neutrophils were treated with APS IgG in the presence or absence of 6-gingerol and/or PKA inhibitor. NETosis was quantified by measuring the enzymatic activity of nuclease-liberated myeloperoxidase (MPO). Mean and SEM are presented for n = 3–4 independent experiments; *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001 by 1-way ANOVA corrected with Dunnett's test.
6-Gingerol attenuates lupus-relevant disease activity in mice. We next tested the efficacy of 6-gingerol on disease activity in a lupus mouse model. Administration of 6-gingerol to TLR7 agonist–treated mice (Figure 4A) resulted in a marked reduction in plasma NET levels, as evident by reductions in both cell-free DNA and myeloperoxidase-DNA (MPO-DNA) complexes (Figure 4, B and C). Key antibodies, including anti-dsDNA, anti-β2GPI, and total IgG, were also reduced (Figure 4, D–F). Spleen size, total leukocytes, lymphocytes, neutrophils, and platelets were not significantly altered by 6-gingerol (Supplemental Figure 2, A–E). Given that 6-gingerol inhibited cAMP-specific PDE activity in vitro, we reasoned that it would also increase cAMP concentration in vivo and thereby inhibit proinflammatory cytokines — similar to synthetic PDE inhibitors (36). As expected, 6-gingerol–treated mice showed significantly lower levels of both IFN-γ and TNF-α (Supplemental Figure 3, A–B). We next investigated the efficacy of 6-gingerol treatment after disease onset in the same lupus model. To do this, 6-gingerol treatment was delayed for 4 weeks relative to the initiation of the TLR7 agonist; both TLR7 agonist and 6-gingerol were then administered together for the final 2 weeks of the experiment (Figure 5A). While vehicle-treated mice accrued higher levels of NETs and autoantibodies between weeks 4 and 6, these increases were markedly blunted in the mice receiving 6-gingerol (Figure 5, B–E, and Supplemental Figure 4, A–D). Taken together, these data suggest that 6-gingerol reduces lupus-relevant NET release and autoantibody formation in vivo.
6-Gingerol attenuates NET release and autoantibody formation in a lupus mouse model. BALB/c mice were treated topically with TLR7 agonist (R848) or vehicle DMSO for 6 weeks (3 times per week). Some mice were additionally injected (i.p.) with 20 mg/kg 6-gingerol (3 times per week). Schematic of the TLR7 agonist–induced (R848) lupus model (A). NET levels in serum were assessed by measuring cell-free DNA (B) and MPO-DNA complexes (C). Anti–double-stranded DNA (anti-dsDNA) (D), anti–β-2 glycoprotein I (β2GPI) IgG (E), and total IgG (F) levels in serum were assessed by ELISA. Mean is presented as a horizontal line; *P < 0.05, **P < 0.01, ***P < 0.001 as compared with the R848-alone group by 1-way ANOVA corrected with Dunnett's test.
Efficacy of 6-gingerol treatment after development of lupus phenotype in a lupus mouse model. BALB/c mice were treated topically with TLR7 agonist (R848) or vehicle DMSO for 6 weeks (3 times per week). Starting at week 4 of treatment, some mice were additionally injected (i.p.) with 20 mg/kg 6-gingerol (3 times per week). Schematic of the TLR7 agonist–induced (R848) lupus model by week 4 followed by 6-gingerol treatment (A). NET levels in serum were assessed before and after 6-gingerol treatment by measuring MPO-DNA complexes (B). Anti–double-stranded DNA (anti-dsDNA) (C), anti–β-2 glycoprotein I (β2GPI) IgG (D), and total IgG (E) levels in serum were assessed by ELISA before and after 6-gingerol treatment. Mean is presented as a horizontal line; *P < 0.05, **P < 0.01, ***P < 0.001 by paired t test.
6-Gingerol attenuates aPL-mediated venous thrombosis. The pathologic role of neutrophils and NETs in thrombosis has been observed in both human (37–39) and mouse studies (13, 40, 41). Since 6-gingerol suppressed aPL-mediated NETosis in vitro, we reasoned that it might also mitigate aPL-accelerated NETosis and thrombosis in vivo. We induced large-vein thrombosis utilizing an electrolytic inferior vena cava (IVC) model that we have described previously (35, 42) (Figure 6A). Administration of aPL increased serum NET levels, which returned to baseline when mice were treated with 6-gingerol (Figure 6B). As expected, administration of aPL, but not control IgG, increased thrombus length and weight, which again returned to control levels upon administration of 6-gingerol (Figure 6, C–E). We also examined the effect of the synthetic PDE4 inhibitor rolipram on NETosis and venous thrombosis. Similar to 6-gingerol, rolipram suppressed aPL-mediated NETosis in vitro in dose-dependent fashion (Figure 7A). In the aforementioned model of aPL-accelerated large-vein thrombosis, administration of rolipram to the APS mice returned circulating MPO-DNA complexes (Figure 7B) and thrombus size (Figure 7, C and D) to levels seen in control mice. In summary, these data demonstrate that 6-gingerol suppresses NETosis and venous thrombosis in vivo and provide further support of the idea that 6-gingerol functions as a PDE4 inhibitor, given that its effects are phenocopied by a synthetic PDE4 inhibitor.
6-Gingerol prevents aPL-mediated acceleration of venous thrombosis. Schematic of the electrolytic model of venous thrombosis (A). Direct current results in the release of free radicals within the inferior vena cava, which activate endothelial cells and initiate a thrombogenic environment in the presence of constant blood flow. MPO-DNA complexes were measured in serum of mice treated with control IgG or APS IgG in the presence or absence of 6-gingerol (B). Thrombus formation was assessed at 24 hours. Thrombus length (C) and thrombus weight (D) were measured. Representative thrombi (E). **P < 0.01, ***P < 0.001, ****P < 0.0001 by 1-way ANOVA corrected with Dunnett's test.
The synthetic PDE4 inhibitor rolipram suppresses APS-mediated NETosis and venous thrombosis. Human neutrophils were stimulated with APS IgG for 3 hours. Some samples were additionally treated with the PDE4 inhibitor rolipram. NETosis was quantified by measuring the enzymatic activity of nuclease-liberated myeloperoxidase (MPO) (A). MPO-DNA complexes were assessed for control IgG- or APS IgG-treated mice in the presence or absence of rolipram (B). Thrombus formation was assessed at 24 hours. Thrombus length (C) and thrombus weight (D) were measured; **P < 0.01, ***P < 0.001, ****P < 0.0001 by 1-way ANOVA corrected with Dunnett's test.
Kinetics of 6-gingerol in plasma and neutrophils. Finally, we preformed pharmacokinetic studies of 6-gingerol. In particular, we focused on the distribution of 6-gingerol in neutrophils, the major theme of the above experiments. Interestingly, we observed accumulation of 6-gingerol in neutrophils at the same time levels were dropping in plasma (Figure 8). These results are in line with previous work suggesting that ginger biophenolics are rapidly cleared from plasma by conversion into glucuronide conjugates but then reconverted into their free forms in tissues by enzymes such as β-glucuronidases (43).
Kinetics of 6-gingerol in plasma and neutrophils following injection (i.p.) with 20 mg/kg 6-gingerol. Male C57BL/6 mice were injected (i.p.) with 20 mg/kg 6-gingerol, and peripheral blood was collected after 0.5, 2, 4, and 24 hours. 6-Gingerol concentrations in plasma (A) and in neutrophils (B) were then quantitated. Values and error bars represent mean ± SEM, respectively.
Here, we have revealed antineutrophil properties of 6-gingerol that may have protective effects in disease states, such as lupus and APS. In vivo, we characterized 2 lupus-relevant inflammatory models and found that 6-gingerol reduced NETosis in both. Beyond inhibition of NETosis, we also saw positive effects of disease phenotypes, such as autoantibody formation and thrombosis, and observed that 6-gingerol behaved very similarly to a synthetic PDE4 inhibitor.
Mechanistically, we found that the effects of 6-gingerol on neutrophils are at least partially attributable to its ability to inhibit PDE activity (Supplemental Figure 5). In vitro data demonstrate that 6-gingerol increases intracellular concentrations of cAMP and enhances PKA activity in neutrophils. Furthermore, 6-gingerol suppressed the production of proinflammatory cytokines, such as TNF-α and IFN-γ, similar to PDE4 inhibitors (36), therefore exerting an overall antiinflammatory effect in TLR7 agonist–induced lupus. The activation of cAMP/PKA by 6-gingerol would seem to support this pathway as a potential therapeutic target in lupus and APS with drugs such as PDE4 inhibitors (44). This is in agreement with our previous work demonstrating the potential role of adenosine receptors, cAMP, and PKA in suppressing APS-mediated NETosis and thrombosis (35).
Ginger has previously been reported to have antiinflammatory (45), antioxidant (46), and antithrombotic (47) effects. Regarding the latter, gingerol-related compounds, including 6-gingerol, have been shown to prevent platelet aggregation (48), although this finding has not been reproduced by all groups (49). Here, it is certainly possible that both antiplatelet and antineutrophil properties are contributing to protection against venous thrombosis. Beyond thrombosis, ginger has also been considered as a treatment for rheumatic diseases. Several clinical studies have suggested beneficial effects of ginger for the treatment of arthritis. For example, ginger extract was found to alleviate pain and decrease joint swelling (50, 51); to our knowledge, neutrophil phenotypes have not been considered in any of these clinical studies. In mice, there is evidence that ginger may modulate inflammatory cell trafficking, with decreased recruitment of neutrophils, eosinophils, and monocytes into inflamed airways (52). Here, there was a trend toward reduced neutrophil numbers in circulation (Supplemental Figure 2A), and future studies should endeavor to look specifically at the effect of 6-gingerol on neutrophil trafficking in models of autoimmunity.
We found that 6-gingerol concentrations as low as 10 μM were effective in mitigating NETosis. This is a concentration that provides no cellular toxicity over 24 hours (53). In fact, for the duration of our assay (3 hours), we did not detect toxic effects, even at molar concentration of 6-gingerol. Ginger extracts are generally regarded as safe (54), with 2 grams daily (approximately 25 mg/kg) demonstrating low levels of toxicity and high levels of tolerability in humans (55). Given the faster metabolic rate of mice as compared with humans (and the allometric scaling factor of 10), 250 mg/kg ginger extract has been a common dose for murine in vivo studies. As ginger extracts typically consist of 5% active phenolic compounds (mostly 6-gingerol), the dose chosen here (10 mg/kg 6-gingerol) lines up well with previous work.
Free forms of ginger biophenolics, including 6-gingerol, can be detected in human plasma upon oral administration of ginger extracts (56, 57). These compounds are rapidly cleared from plasma and converted into glucuronide conjugates. A recent study proposed a model whereby these conjugated forms are reconverted into their free forms in tissues by enzymes, such as β-glucuronides (43), which are known to be abundantly expressed by neutrophils (58). Consistent with this model, we appreciated accumulation of 6-gingerol in neutrophils at the same time levels were dropping in plasma.
While it is unlikely that ginger extract or 6-gingerol would find a role as a primary therapeutic in individuals with active disease, one wonders if future studies might administer ginger supplements to individuals at high risk for autoimmune conditions and/or cardiovascular disease (for example, individuals with autoantibodies who have yet to have clinical events or patients with cardiovascular risk factors). In such scenarios, its antineutrophil properties might prove protective against disease emergence. Based on the data presented here, we would argue that such studies should have not only clinical endpoints, but also mechanistic endpoints focusing on neutrophil activity.
Purification of patient IgG. IgG was purified from APS or control sera with a Protein G Agarose Kit following the manufacturer's instructions (Pierce) as previously described (35). Briefly, serum was diluted in IgG binding buffer and passed through a Protein G Agarose column at least 5 times. IgG was then eluted with 0.1 M glycine and neutralized with 1 M Tris. This was followed by overnight dialysis against PBS at 4°C. IgG purity was verified with Coomassie staining, and concentrations were determined by BCA protein assay (Pierce) according to the manufacturer's instructions. All IgG samples were determined to be free of detectable endotoxin by the Pierce LAL Chromogenic Endotoxin Quantitation Kit (88282) according to the manufacturer's instructions.
Human neutrophil purification and NETosis assays. Blood from healthy volunteers was collected into heparin tubes by standard phlebotomy techniques. The anticoagulated blood was then fractionated by density-gradient centrifugation using Ficoll-Paque Plus (GE Healthcare). Neutrophils were further purified by dextran sedimentation of the red blood cell layer, before lysing residual red blood cells with 0.2% sodium chloride. Neutrophil preparations were at least 95% pure, as confirmed by both flow cytometry and nuclear morphology.
To assess NETosis, neutrophils were resuspended in RPMI media (Gibco) supplemented with 0.5% BSA (MilliporeSigma) and 0.5% fetal bovine serum (Gibco), which had been heat-inactivated at 56°C. Neutrophils (1 × 105/well) were then cultured in 96-well plates at 37°C with 100 nM PMA (MilliporeSigma), 2 μg/mL LPS (Escherichia coli O26:B6, L2654, MilliporeSigma), 10 μg/mL APS IgG, or 10 μg/mL RNP ICs. RNP ICs were formed by mixing IgG purified from 3 individuals with lupus and anti-RNP positivity with SmRNP (Arotec). In some cases, cultures were also supplemented with 6-gingerol, 8-gingerol, and 10-gingerol (Cayman Chemical). After 3 hours in culture, NET-associated MPO activity was measured as follows. The culture media was discarded (to remove any soluble MPO) and replaced with 100 μL RPMI supplemented with 10 U/mL Micrococcal nuclease (Thermo Fischer Scientific). After 10 minutes at 37°C, digestion of NETs was stopped with 10 mM EDTA. Supernatants were transferred to a V-shaped 96-well plate and centrifuged at 350g for 5 minutes to remove debris. Supernatants were then transferred into a new plate. To measure for MPO activity, an equal volume of 3,3′,5,5′-tetramethylbenzidine (3,3′,5,5′-TMB) substrate (1 mg/mL, Thermo Fischer Scientific) was added to each well. After 10 minutes of incubation in the dark, the reaction was stopped by the addition of 50 μL of 1 mM sulfuric acid. Absorbance was measured at 450 nm using a Cytation 5 Cell Imaging Multi-Mode Reader.
Immunofluorescence microscopy. For immunofluorescence microscopy, 1.5 × 105 neutrophils were seeded onto coverslips coated with 0.001% poly-l-lysine (MilliporeSigma) and fixed with 4% paraformaldehyde for 15 minutes at room temperature. Blocking was with 1% BSA overnight at 4°C. The primary antibody was against neutrophil elastase (Abcam, 21595, diluted 1:100), and the FITC-conjugated secondary antibody was from Southern Biotech (4052-02, diluted 1:250). DNA was stained with Hoechst 33342 (Invitrogen). Images were collected with a Cytation 5 Cell Imaging Multi-Mode Reader.
H2O2 assay. The generation of H2O2 was quantified as described previously (17). Briefly, H2O2 production was detected by a colorimetric assay, with 50 μM Amplex Red reagent (Invitrogen), and 10 U/ml horseradish peroxidase (MilliporeSigma) was added to the culture medium. Absorbance was measured at 560 nm and linearity was assured with an H2O2 standard curve.
Measurement of PDE activity. Human neutrophils (1 × 107) were washed twice with cold PBS and pelleted by centrifugation at 2500g for 5 minutes. The cell pellet was resuspended in 100 μL RIPA buffer (MilliporeSigma, R0278) supplemented with protease inhibitors (Roche Diagnostics GmbH, 35440400) for 15 minutes on ice. The mixture was centrifuged at 14,000g for 5 minutes to clear cell debris. The activity of PDE was measured using the Bridge-It cAMP-PDE assay kit (Mediomics, catalog PD-1016). The supernatant was mixed with the reaction mixture according to the manufacturer's instructions in the presence or absence of 10 μM 6-gingerol or 0.1 μM of the PDE4 inhibitor rolipram and allowed to proceed for 1 hour at 37°C. The reaction was stopped and assay solution was added. After 30 minutes at 37°C, fluorescence was measured with a Synergy HT Multi-Mode Microplate Reader (BioTek) at excitation 480 nm and emission. Relative activity was calculated and normalized to mean control values.
Measurement of intracellular cAMP. cAMP levels in human neutrophils were measured using the Bridge-It cAMP Designer fluorescence assay kit (Mediomics, catalog 122934). Briefly, neutrophils (1 × 105) were washed twice with PBS and resuspended in 100 μL Krebs-Ringer Bicarbonate Buffer (without IBMX). To investigate the effect of 6-gingerol on the cAMP level, neutrophils were incubated at room temperature for 30 minutes in the presence or absence of 10 μM 6-gingerol. Neutrophils were then stimulated with 100 μM forskolin for 10 minutes. Samples were centrifuged at 12,000g for 2 minutes and supernatants were discarded. The cAMP designer assay solution was then added to the cell pellet and carefully transferred to 96-well black-side clear-bottom plates. The plate was incubated at room temperature for 30 minutes before measuring fluorescence with a Synergy HT Multi-Mode Microplate Reader (BioTek) at excitation 480 nm with a band pass filter of 20 nm and emission 540 nm with a band pass filter of 40 nm.
Measurement of PKA activity. Neutrophils (1 × 107) were preincubated with 10 μM 6-gingerol or 0.1 μM of the PDE4 inhibitor rolipram and then treated with 100 μM forskolin or 1 μM cAMP. The activity of PKA was then measured using the PKA activity assay kit (Arbor Assays, catalog K027-H1). Briefly, neutrophils were washed twice with cold PBS and pelleted by centrifugation at 2500g for 5 minutes. The cell pellet was resuspended in 1 mL activated cell lysis buffer for 30 minutes on ice. The mixture was centrifuged at 10,600g at 4°C for 10 minutes to pellet the cell debris. In a 96-well plate, the supernatant was mixed with the kinase assay buffer, followed by addition of ATP, and the plate was incubated at 30°C for 90 minutes. The plate was washed 4 times, followed by the addition of donkey anti-rabbit IgG HRP conjugate and the rabbit phosphor PKA substrate antibody, and then incubated at room temperature for 60 minutes. The plate was washed 4 times, followed by the addition of TMB substrate and incubation at room temperature for 30 minutes. Stop solution was added and the optical density was read at 450 nm using a Cytation 5 Cell Imaging Multi-Mode Reader.
Animal housing and treatments. Mice were purchased from The Jackson Laboratory, housed in a specific pathogen–free barrier facility, and fed standard chow. Male C57BL/6 mice were used for venous thrombosis experiments, and 6-gingerol (AdooQ Bioscience) was administered by intraperitoneal injection, 10 mg/kg, daily. Therapy was always started 1 day before IVC surgery and continued through the duration of the experiment. Female BALB/c mice were used for resiquimod-induced (R848-induced) lupus, and 6-gingerol was administered by intraperitoneal injection at 20 mg/kg 3 times per week.
In vivo venous thrombosis. To model large-vein thrombosis, we employed an electrolytic model that has been used previously by our group and others (35, 42). Briefly, after exposure of the IVC, any lateral branches were ligated using 7-0 Prolene suture (back branches remained patent). A 30-gauge silver-coated copper wire (KY-30-1-GRN, Electrospec) with exposed copper wire at the end was placed inside a 25-gauge needle and inserted into the IVC, where it was positioned against the anterior wall and functioned as the anode. Another needle was implanted subcutaneously, completing the circuit (cathode). A constant current of 250 μA was applied for 15 minutes. The current was supplied by a voltage-to-current converter as described in detail previously (42). After removal of the needle, the abdomen was closed. Before recovery from anesthesia, mice received a single intravenous injection of either control or APS IgG (500 μg). Twenty-four hours later, mice were humanely euthanized, blood was collected, and thrombus size was measured.
Quantification of MPO-DNA complexes. MPO-DNA complexes were quantified similarly as previously described (59). This protocol used several reagents from the Cell Death Detection ELISA kit (Roche). First, a high-binding EIA/RIA 96-well plate (Costar) was coated overnight at 4°C with anti-human MPO antibody (Bio-Rad0400-0002) and diluted to a concentration of 0.5 μg/mL in coating buffer (Cell Death Detection ELISA kit). The plate was washed 3 times with wash buffer (0.05% Tween 20 in PBS) and then blocked with 1% BSA in PBS for 1 hour at room temperature. The plate was again washed 3 times, before incubating for 1 hour at room temperature with 1:500 mouse serum in the aforementioned blocking buffer. The plate was washed 5 times and then incubated for 1 hour at room temperature with 1× anti-DNA antibody (HRP-conjugated; Cell Death Detection ELISA kit) diluted 1:100 in blocking buffer. After 5 more washes, the plate was developed with 3,3′,5,5′-TMB substrate (Invitrogen), followed by a 2 N sulfuric acid stop solution. Absorbance was measured at a wavelength of 450 nm with a Synergy HT Multi-Mode Microplate Reader (BioTek). Data were normalized to an in vitro–prepared NET standard included on every plate.
R848 treatment. Female BALB/c mice were treated with the TLR7 agonist R848 (Enzo Life Science) as previously described (60) with slight modifications. Epicutaneous application was to the ear 3 times per week, with 100 μg R848 dissolved in 8 μL DMSO. For 6-gingerol treatment, some mice were injected intraperitoneally with 20 μg/kg 6-gingerol on the same days as R848 treatment. Serum and tissues were collected after 6 weeks of treatment.
Quantification of anti-dsDNA and total IgG. Kits for mouse anti-dsDNA and mouse total IgG were purchased from Alpha Diagnostic International (catalog 5120 and 6320, respectively) and performed according to the manufacturer's instructions.
Quantification of anti-β2GPI. High-binding EIA/RIA plates were coated overnight at 4°C with 1 μg/mL mouse β2GPI (R&D 6575-AH) diluted in coating buffer from a Cell Death Detection ELISA kit. Plates were then washed with 0.05% Tween 20 in PBS and blocked with 1% BSA in PBS for 1 hour at room temperature. The plate was again washed, before incubation for 1 hour at room temperature with 1:500 mouse serum in the aforementioned blocking buffer. The plate was washed and then incubated for 1 hour at room temperature with anti-mouse IgG HRP (Jackson ImmunoResearch, 115-035-068) diluted 1:20,000 in blocking buffer. The plate was washed and developed with 3,3′,5,5′-TMB substrate (Invitrogen) followed by a 2 N sulfuric acid stop solution. Absorbance was measured at a wavelength of 450 nm with a Synergy HT Multi-Mode Microplate Reader (BioTek).
Quantification of cell-free DNA. Cell-free DNA was quantified in mouse serum using a Quant-iT PicoGreen dsDNA assay kit (Invitrogen) according to the manufacturer's instructions.
Complete blood counts. Peripheral leukocyte and platelet counts were determined with an automated Hemavet 950 counter (Drew Scientific).
Quantification of IFN-γ and TNF-α. Kits for quantitative detection of mouse IFN-γ (88-7314) and TNF-α (88-7324) were purchased from Invitrogen and performed according to the manufacturer's instructions.
Pharmacokinetic studies of 6-gingerol in neutrophils. Male C57BL/6 mice were treated with 20 mg/kg 6-gingerol by intraperitoneal injection. Peripheral blood was collected 0.5, 2, 4, and 24 hours after 6-gingerol treatment. Plasma was collected and neutrophils were isolated from peripheral blood using the EasySep negative selection kit (STEMCELL Technologies, catalog 19762) according to the manufacturer's instructions.
Bioanalysis. Neutrophil samples were suspended with 100 μL of 20% acetonitrile and then subjected to 3 freeze-thaw cycles. Samples were sonicated twice (3 seconds each) to breakdown neutrophil pellets, with cooling on ice for 15 seconds between sonications. A stock solution of 6-gingerol was diluted to 0.25, 0.5, 1, 2.5, 5, 10, 25, 50, and 100 ng/mL methanol to prepare working solutions. To prepare calibration curves, 30 μL blank cell suspension was spiked with 30 μL of the various working solutions above respectively; whereas 30 μL of tested samples was spiked with 30 μL methanol. All samples, were spiked with 30 μL internal standard solution. All the samples were vortexed for extraction and centrifuged at 10,000g at 4°C for 15 minutes. Finally, isolated supernatants from each tube were submitted for subsequent LC-MS analysis. Plasma samples were prepared in a similar way.
LC-MS analysis. The mass spectrometer AB Sciex QTRAP 5500, coupled with the Shimazu LC20A liquid chromatography system, was operated in multiple-reaction monitoring–positive mode for determination of 6-gingerol in neutrophil pellets and plasma samples. Chromatographic separation was accomplished with the application of a Waters XBridge C18, 2.1 × 50 mm, 5 μm column. The mobile phase A consisted of 0.1% formic acid in deionized water, and mobile phase B consisted of 100% acetonitrile supplemented with 0.1% formic acid. The HPLC was subjected to gradient elution, at 0.4 mL/minute, and positive ion mode was adopted in the mass spectrometer. The mobile phase B was maintained at 1% during the initial 0.5 minutes and then increased to 99% from 0.5 minutes to 2.5 minutes. The composition of mobile phase B was decreased to 1% at 4.5 minutes and maintained there until the end of the run time at 6.6 minutes. Mass/charge (m/z) transitions 295.1→137.2 and 295.1→177.0 were monitored for 6-gingerol quantification in biological samples, while m/z transition 455.2→425.2 was monitored for internal standard.
Statistics. Data were analyzed with GraphPad Prism software (version 8). For continuous variables, group means were compared by either 2-tailed t test (2 groups) or 1-way ANOVA (more than 2 groups); correction for multiple comparisons was by Dunnett's test. Statistical significance was defined as P < 0.05.
Study approval. This study complied with all relevant ethical regulations and was approved by the University of Michigan Institutional Review Board. All participants provided informed consent for blood donation. Mouse experimental protocols were approved by the University of Michigan Institutional Animal Care and Use Committee, and all relevant ethical regulations were followed.
RAA, AAG, LD, JW, SKE, SY, KG, and DS conducted experiments and analyzed data. RAA and JSK designed the study and analyzed data. All authors drafted the manuscript and gave approval before submission.
RAA was supported by NIH grant T32AR007080. JSK was supported by grants from the NIH (R01HL134846), the Lupus Research Alliance, and the Burroughs Wellcome Fund. The work was supported by an administrative supplement to R01HL134846 from the NIH Office of Dietary Supplements.
Conflict of interest: The authors have declared that no conflict of interest exists.
Copyright: © 2021, Ali et al. This is an open access article published under the terms of the Creative Commons Attribution 4.0 International License.
Reference information: JCI Insight. 2021;6(3):e138385.https://doi.org/10.1172/jci.insight.138385.
Miyakis S, et al. International consensus statement on an update of the classification criteria for definite antiphospholipid syndrome (APS). J Thromb Haemost. 2006;4(2):295–306.
Bertolaccini ML, et al. 14th International congress on antiphospholipid antibodies task force. Report on antiphospholipid syndrome laboratory diagnostics and trends. Autoimmun Rev. 2014;13(9):917–930.
Gómez-Puerta JA, Cervera R. Diagnosis and classification of the antiphospholipid syndrome. J Autoimmun. 2014;48–49:20–25:.:S0896–8411(14)00008–0.
Cervera R, et al. Antiphospholipid syndrome: clinical and immunologic manifestations and patterns of disease expression in a cohort of 1,000 patients. Arthritis Rheum. 2002;46(4):1019–1027.
Brinkmann V, et al. Neutrophil extracellular traps kill bacteria. Science. 2004;303(5663):1532–1535.
Kenny EF, et al. Diverse stimuli engage different neutrophil extracellular trap pathways. Elife. 2017;6:24437.
Grayson PC, Kaplan MJ. At the bench: neutrophil extracellular traps (NETs) highlight novel aspects of innate immune system involvement in autoimmune diseases. J Leukoc Biol. 2016;99(2):253–264.
Fuchs TA, et al. Neutrophil extracellular trap (NET) impact on deep vein thrombosis. Arterioscler Thromb Vasc Biol. 2012;32(8):1777–1783.
Rao AN, et al. Do neutrophil extracellular traps contribute to the heightened risk of thrombosis in inflammatory diseases? World J Cardiol. 2015;7(12):829–842.
Knight JS, Kaplan MJ. Lupus neutrophils: 'NET' gain in understanding lupus pathogenesis. Curr Opin Rheumatol. 2012;24(5):441–450.
Banchereau R, et al. Personalized immunomonitoring uncovers molecular networks that stratify lupus patients. Cell. 2016;165(3):551–565.
Yalavarthi S, et al. Release of neutrophil extracellular traps by neutrophils stimulated with antiphospholipid antibodies: a newly identified mechanism of thrombosis in the antiphospholipid syndrome. Arthritis Rheumatol. 2015;67(11):2990–3003.
Meng H, et al. In vivo role of neutrophil extracellular traps in antiphospholipid antibody-mediated venous thrombosis. Arthritis Rheumatol. 2017;69(3):655–667.
Garcia-Romo GS, et al. Netting neutrophils are major inducers of type I IFN production in pediatric systemic lupus erythematosus. Sci Transl Med. 2011;3(73):73ra20–73ra20.
Lood C, et al. Neutrophil extracellular traps enriched in oxidized mitochondrial DNA are interferogenic and contribute to lupus-like disease. Nat Med. 2016;22(2):146–153.
Lande R, et al. Neutrophils activate plasmacytoid dendritic cells by releasing self-DNA-peptide complexes in systemic lupus erythematosus. Sci Transl Med. 2011;3(73):73ra19–73ra19.
Knight JS, et al. Peptidylarginine deiminase inhibition is immunomodulatory and vasculoprotective in murine lupus. J Clin Invest. 2013;123(7):2981–2993.
van der Linden M, et al. Neutrophil extracellular trap release is associated with antinuclear antibodies in systemic lupus erythematosus and anti-phospholipid syndrome. Rheumatology (Oxford). 2018;57(7):1228–1234.
Grzanna R, et al. Ginger—an herbal medicinal product with broad anti-inflammatory actions. J Med Food. 2005;8(2):125–32.
Mashhadi NS, et al. Anti-oxidative and anti-inflammatory effects of ginger in health and physical activity: review of current evidence. Int J Prev Med. 2013;4(suppl 1):S36–S42.
Shukla Y, Singh M. Cancer preventive properties of ginger: a brief review. Food Chem Toxicol. 2007;45(5):683–690.
Jolad SD, et al. Fresh organically grown ginger (Zingiber officinale): composition and effects on LPS-induced PGE2 production. Phytochemistry. 2004;65(13):1937–1954.
Jolad SD, et al. Commercially processed dry ginger (Zingiber officinale): composition and effects on LPS-stimulated PGE2 production. Phytochemistry. 2005;66(13):1614–1635.
Wohlmuth H, et al. Gingerol content of diploid and tetraploid clones of ginger (Zingiber officinale Roscoe). J Agric Food Chem. 2005;53(14):5772–5778.
Tripathi S, et al. Ginger extract inhibits LPS induced macrophage activation and function. BMC Complement Altern Med. 2008;8(1):1.
Tripathi S, et al. Effect of 6-gingerol on pro-inflammatory cytokine production and costimulatory molecule expression in murine peritoneal macrophages. J Surg Res. 2007;138(2):209–213.
Frondoza CG, et al. TNF-α expression of synoviocyte cultures is inhibited by hydroxy-alkoxy-phenyl compounds (HAPC) from ginger. Trans Orthop Res Soc. 2000;46:1038.
Carmelita GF, et al. An in vitro screening assay for inhibitors of proinflammatory mediators in herbal extracts using human synoviocyte cultures. In Vitro Cell Dev Biol Anim. 2004;40(3–4):95–101.
Kim SO, et al. [6]-Gingerol inhibits COX-2 expression by blocking the activation of p38 MAP kinase and NF-kappaB in phorbol ester-stimulated mouse skin. Oncogene. 2005;24(15):2558–2567.
Young H-Y, et al. Analgesic and anti-inflammatory activities of [6]-gingerol. J Ethnopharmacol. 2005;96(1):207–210.
Röhrig T, et al. Inhibition of cyclic adenosine monophosphate-specific phosphodiesterase by various food plant-derived phytotherapeutic agents. Medicines (Basel). 2017;4(4):80.
Chang T-T, et al. In silico pharmacology suggests ginger extracts may reduce stroke risks. Mol Biosyst. 2011;7(9):2702–2710.
Barnes PJ. Theophylline: new perspectives for an old drug. Am J Respir Crit Care Med. 2003;167(6):813–818.
Hatemi G, et al. Apremilast for Behçet's syndrome--a phase 2, placebo-controlled study. N Engl J Med. 2015;372(16):1510–1518.
Ali RA, et al. Adenosine receptor agonism protects against NETosis and thrombosis in antiphospholipid syndrome. Nat Commun. 2019;10(1):1916.
Perez-Aso M, et al. Apremilast, a novel phosphodiesterase 4 (PDE4) inhibitor, regulates inflammation through multiple cAMP downstream effectors. Arthritis Res Ther. 2015;17(1):249.
Döring Y, et al. Neutrophil extracellular traps in atherosclerosis and atherothrombosis. Circ Research. 2017;120(4):736–743.
Martinod K, Wagner DD. Thrombosis: tangled up in NETs. Blood. 2014;123(18):2768–2776.
Matevosyan K, Sarode R. Thrombosis, microangiopathies, and inflammation. Semin Thromb Hemost. 2015;41(06):556–562.
von Brühl M-L, et al. Monocytes, neutrophils, and platelets cooperate to initiate and propagate venous thrombosis in mice in vivo. J Exp Med. 2012;209(4):819–835.
Martinod K, et al. Neutrophil histone modification by peptidylarginine deiminase 4 is critical for deep vein thrombosis in mice. Proc Natl Acad Sci U S A. 2013;110(21):8674–8679.
Palmer OR, et al. Update on the electrolytic IVC model for pre-clinical studies of venous thrombosis. Res Pract Thromb Haemost. 2018;2(2):266–273.
Mukkavilli R, et al. Pharmacokinetic-pharmacodynamic correlations in the development of ginger extract as an anticancer agent. Sci Rep. 2018;8(1):3056.
Baillie GS, et al. Compartmentalisation of phosphodiesterases and protein kinase A: opposites attract. FEBS Lett. 2005;579(15):3264–3270.
Chang C-P, et al. The effect of Chinese medicinal herb Zingiberis rhizoma extract on cytokine secretion by human peripheral blood mononuclear cells. J Ethnopharmacol. 1995;48(1):13–19.
Danwilai K, et al. Antioxidant activity of ginger extract as a daily supplement in cancer patients receiving adjuvant chemotherapy: a pilot study. Cancer Manag Res. 2017;9:11–18.
Thomson M, et al. The use of ginger (Zingiber officinale Rosc.) as a potential anti-inflammatory and antithrombotic agent. Prostaglandins Leukot Essent Fatty Acids. 2002;67(6):475–478.
Nurtjahja-Tjendraputra E, et al. Effective anti-platelet and COX-1 enzyme inhibitors from pungent constituents of ginger. Thromb Res. 2003;111(4-5):259–265.
Marx W, et al. The effect of ginger (Zingiber officinale) on platelet aggregation: a systematic literature review. PLoS One. 2015;10(10):0141119.
Srivastava KC, Mustafa T. Ginger (Zingiber officinale) and rheumatic disorders. Med Hypotheses. 1989;29(1):25–28.
Srivastava KC, Mustafa T. Ginger (Zingiber officinale) in rheumatism and musculoskeletal disorders. Med Hypotheses. 1992;39(4):342–348.
Ahui ML, et al. Ginger prevents Th2-mediated immune responses in a mouse model of airway inflammation. Int Immunopharmacol. 2008;8(12):1626–1632.
de Lima RMT, et al. Toxic, cytogenetic and antitumor evaluations of [6]-gingerol in non-clinical in vitro studies. Biomed Pharmacother. 2019;115:108873.
Schwertner HA, et al. Variation in concentration and labeling of ginger root dietary supplements. Obstet Gynecol. 2006;107(6):1337–1343.
Chrubasik S, et al. Zingiberis rhizoma: a comprehensive review on the ginger effect and efficacy profiles. Phytomedicine. 2005;12(9):684–701.
Zick SM, et al. Pharmacokinetics of 6-gingerol, 8-gingerol, 10-gingerol, and 6-shogaol and conjugate metabolites in healthy human subjects. Cancer Epidemiol Biomarkers Prev. 2008;17(8):1930–1936.
Zick SM, et al. Quantitation of 6-, 8- and 10-gingerols and 6-shogaol in human plasma by high-performance liquid chromatography with electrochemical detection. Int J Biomed Sci. 2010;6(3):233–240.
Bartholomé R, et al. Deconjugation kinetics of glucuronidated phase II flavonoid metabolites by beta-glucuronidase from neutrophils. Drug Metab Pharmacokinet. 2010;25(4):379–387.
Kessenbrock K, et al. Netting neutrophils in autoimmune small-vessel vasculitis. Nat Med. 2009;15(6):623–625.
Yokogawa M, et al. Epicutaneous application of toll-like receptor 7 agonists leads to systemic autoimmunity in wild-type mice: a new model of systemic lupus erythematosus. Arthritis Rheumatol. 2014;66(3):694–706.
Version 1 (December 29, 2020): In-Press Preview
Version 2 (February 8, 2021): Electronic publication


text:
Complex Business Fraud Litigation
Corporate, M&A and Venture Capital
Digital & Mobile Media
Food Beverage & Hospitality
Intellectual Property / Technology
International Business Practice
Litigation / Alternative Dispute Resolution
Non-Compete & Trade Secrets
Reorganization & Creditors' Rights
Golenbock Eiseman Assor Bell & Peskoe LLP
Home / Case Studies / Non-Compete Claims
Non-Compete Claims
September 14, 2021 | Non-Compete & Trade Secrets
As part of its strategy to enter a new geographical market, our client, one of the world's largest insurance brokers, hired a group of employees in that market from another of the world's largest insurance brokers. One of the new hires became the President of our client's affiliate in that market. Shortly thereafter, the former employer initiated an action in Michigan state court against our brokerage client and its affiliate's President, whom we also represented. Plaintiff alleged that the new President misappropriated confidential information and was soliciting plaintiff's clients and employees in breach of her employment agreement's restrictive covenants, allegedly with her new employer's encouragement and assistance.
Months later, during the course of discovery, two of plaintiff's corporate clients transferred their health and benefits insurance business from plaintiff to our brokerage client. Plaintiff filed an emergency motion for a Temporary Restraining Order and Preliminary Injunction. In its motion, plaintiff sought to enjoin our clients not only from soliciting, accepting, and servicing business from plaintiff's current or prospective clients, but also from servicing the two clients that had already moved their business.
In the span of a little more than a week, the GEABP team drafted a 20-page opposition brief and secured three supporting affidavits, two of which were provided by the non-parties who had transferred their business from plaintiff to our brokerage client. When plaintiff submitted an untimely and improper reply brief less than 48 hours before the hearing, we – less than 24 hours later – submitted opposition in response to that brief as well.
The preliminary injunction hearing was held remotely via Zoom. After hearing oral argument, the judge gave his ruling from the bench, adopting all of our key arguments and denying plaintiff's motion for injunctive relief in its entirety. The case settled shortly thereafter.
Case Studies by Practice Area
Litigation/Alternative Dispute Resolution
In 1982, the Golenbock law firm was founded based upon a pragmatic business model-to provide the highest quality legal services by top-notch attorneys, free of the layers of professional and administrative bureaucracy that drive up legal costs at the largest law firms. Together with a collegial work environment, this ethos has fueled the growth of Golenbock Eiseman Assor Bell & Peskoe.
Together, as One. Golenbock Eiseman Assor Bell & Peskoe LLP is a Member of the Alliott Global Alliance of independent professional firms.
© Copyright, 2023 Golenbock Eiseman Assor Bell & Peskoe LLP. All Rights Reserved.
This website contains attorney advertising. Prior results do not guarantee a similar outcome. | Disclaimer

redpajama_set_name: RedPajamaCommonCrawl


text:
Q: Serialising a ray future and returning the results later I've wrapped Ray in a web API (using ray start --head and uvicorn with ray.init). Now I'm trying to:

*

*Submit a job to Ray (via the API) and serialise the future and return to the user

*Later, let the user hit an API to see if the task is finished and return the results

The kicker is that being a multi-thread I can't guarantee that the next call will be from the same thread. Here is what I naively though would work:
id = my_function.remote()
id_hex = id.hex()

Then in another request/invocation:
id = ray._raylet.ObjectID(binascii.unhexlify(id_hex))
ray.get(id)

Now this never gets finished (it times out) even though I know the future is finished and that the code works if I run it in the same thread as the original request.
I'm guessing this has to do with using another initialisation of Ray.
Is there anyway to force Ray to "refresh" a futures result from Redis?

A: Getting objectID directly in your way can cause unexpected behaviors because of Ray's ref counting / optimization mechanism. One recommendation is to use "detached actor". You can create a detached actor and delegate the call in there. Detached actors will survive in the lifetime of Ray (unless you kill it), so you don't need to worry about problems you mentioned. Yes. It can make the program a bit slower as it requires 2 hops, but I guess this overhead wouldn't matter for your workload (client submission model).
https://docs.ray.io/en/latest/advanced.html?highlight=detached#detached-actors
ray.remote
class TaskInvocator:
    def __init__(self):
        self.futures = {}
    def your_function(self):
        object_id = real_function.remote()
        self.futures[object_id.hex()] = object_id
    def get_result(self, hex_object_id):
        return ray.get(self.futures[hex_object_id])

TaskInvocator.remote(detached=True, name='invocator-1')
task_invocator = ray.util.get_actor('invocator-1')
object_id = task_invocator.your_function.remote()
blah blah...
result = ray.get(task_invocator.get_result.remote(object_id.hex()))

A: Serializing a ray future to a string out-of-band and then deserializing it is not supported. The reason for this is because these futures are more than just IDs, they have a lot of state associated with them in various system components.
One thing you could do to support this type of API is have an actor that manages the lifetime of these tasks. When you start the task, you pass its ObjectID to the actor. Then, when a user hits the endpoint to check if it's finished, it pings the actor which looks up the corresponding ObjectID and calls ray.wait() on it.

redpajama_set_name: RedPajamaStackExchange


text:
Readers ask: What Is Cattle Farming In India?
1 Is cattle farming profitable in India?
2 Are there cattle farms in India?
3 How do you do cow farming in India?
4 Why is cattle farming important?
5 Which livestock is most profitable?
6 What type of livestock is most profitable?
7 Which livestock farming is most profitable in India?
8 Is Indian cow milk A1 or A2?
9 Which is the biggest cattle farm in Asia?
10 How do I start a cow farm?
11 Which is more profitable cow or buffalo?
12 Which is the biggest dairy farm in India?
13 What are the disadvantages of raising beef cattle?
14 How do cows help farmers?
15 What are the types of livestock farming?
Is cattle farming profitable in India?
Dairy farming is very profitable business in india. In many parts of india be it a rural or urban dairy farming business has gain its importance and became very popular in terms of its profit margin.
Are there cattle farms in India?
It is estimated that there are about 10,000 cattle farms in India at various stages of construction.
How do you do cow farming in India?
Dairy farming set up needs some requirements well before establishing it.
Space/Shelter Requirements of Dairy Farming Animals:
Dairy Breeds of India:
Fodder Management of the Dairy Farm:
Daily Dairy Farm Management:
Disease Control and Management:
Dairy Farming Reproduction/Breeding Management:
Why is cattle farming important?
Livestock production constitutes a very important component of the agricultural economy of developing countries, a contribution that goes beyond direct food production to include multipurpose uses, such as skins, fibre, fertilizer and fuel, as well as capital accumulation.
You might be interested: Readers ask: How Did Annual Flooding Affect Farming?
Which livestock is most profitable?
What type of livestock is most profitable?
Beef cattle are considered the most profitable and easiest to raise for profit, but homesteaders with small acreage won't be able to raise cattle. Cattle, whether you want beef or dairy cattle, require plenty of good-quality pasture, supplemental hay, fresh water, room to roam, and veterinarian care.
Which livestock farming is most profitable in India?
Commercial pig farming in India is one of the most profitable livestock farming business. Pigs grow faster than any other animals. They have higher feed conversion efficiency. That means they have a great feed to meat converting ratio.
Is Indian cow milk A1 or A2?
Status of cattle in India Indian native breeds of cows and buffaloes are of A2 milk type and hence are a source for safe milk. The A1 / A2 status of cattle is determined by the two alleles for beta-casein gene i.e. A1 and A2 and cattle may be homozygous for one type of protein (A1A1 or A2A2), or heterozygous (A1A2).
Which is the biggest cattle farm in Asia?
A cattle farm in Tamil Nadu's Krishnagiri District, which began its journey as a horse-rearing center during the British rule in 19th century, has become one of the largest in Asia.
You might be interested: Readers ask: What Does Slash And Burn Farming Mean?
How do I start a cow farm?
How to Start a Cattle Farm: Commercial Cattle Farming Business
Make a Business Plan.
Select Farm Location.
Purchase Equipment & Machinery.
Build Shelter.
Determine the Purpose of Your Cattle Farm.
Choose Breed.
Purchase Cattle.
Feeding Your Animals.
Which is more profitable cow or buffalo?
The study conducted in Karnal district of Haryana revealed that milk production by rearing buffalo was more profitable as compared to that of cow. The gross income (Rs. 22249.52) and net income (Rs. 3720.28) per buffalo per annum was significantly higher as compared to (Rs.
Which is the biggest dairy farm in India?
Dudhsagar Dairy is the largest dairy in Asia, processing on an average 1.41 million kilograms of milk each day. Dudhsagar Dairy.
Industry Milk Production
Headquarters Mehsana, Gujarat, India
What are the disadvantages of raising beef cattle?
The disadvantages of raising beef cattle are:
A producer can take on several risks by raising beef cattle.
The efficiency of a beef animal is not as stable as that of other livestock.
A beef cow has a 283-day gestation period.
The cost of starting a beef operation is expensive.
How do cows help farmers?
The different compartments help digest the lignin & cellulose that make up the plants they eat. Cattle are able to convert the energy in a way that we as humans could not do. Cattle also provide us with many other by-products – parts of the cow that are used to make products for home, health, food and industry.
What are the types of livestock farming?
Intensive Livestock Farming.
Semi-intensive Livestock Farming.
Extensive Livestock Farming.
Nomadic Livestock Farming.
Transhumant Livestock Farming.
Organic Livestock Farming.


text:
Devices Interventional Cardiology Personnel
News Release - April 20, 2006
Steven Goldberg, M.D. Joins Cardiac Dimensions as Chief Clinical Officer
KIRKLAND, Wash.--(HSMN NewsFeed)--April 20, 2006--Cardiac Dimensions® Inc. today announced that Steven Goldberg, M.D., Director of the Cardiac Catheterization Lab at University of Washington Medical Center, has joined the company as Chief Clinical Officer. Dr. Goldberg will work closely with Cardiac Dimensions Chief Medical Officer, David Reuter, M.D., PhD., in supporting the company's ongoing worldwide clinical trials of the CARILLON(TM) Mitral Contour System(TM).
Dr. Goldberg is a board certified interventional cardiologist. After completing his fellowship at U.C. Irvine working with Dr. Jonathan Tobis, he served as Associate Director of the Catheterization Lab and Assistant Professor of Medicine at Harbor-UCLA. Prior to joining University of Washington Medical Center, he was Director of the Catheterization Lab at West LA, VA Medical Center. In addition to his new responsibilities at Cardiac Dimensions, he will maintain his current clinical, educational, administrative, and research duties at the University of Washington Medical Center.
"We are very excited to have him on board and I know Steve looks forward to working with our clinical investigators to help bring our important therapy through successful clinical trials," commented Rick Stewart, President and CEO of Cardiac Dimensions.
Approximately 5 million people in the U.S. and over 20 million people worldwide suffer from Heart Failure. The majority of those suffer from dilated cardiomyopathy and functional mitral regurgitation (FMR). While surgical options exist and can be effective in reducing FMR, they are infrequently used due to the burden of the surgery itself, which is associated with high operative morbidity and mortality rates.
The CARILLON Mitral Contour System is an investigational device that combines a proprietary implantable device and delivery system. The implant consists of a shaping ribbon between distal and proximal anchors, and is delivered percutaneously (through the skin) via jugular access under fluoroscopic guidance. The implant is designed to be positioned, adjusted, and gently anchored in the coronary sinus/great cardiac vein (GCV) to reshape the annulus around the mitral valve to reduce mitral regurgitation (MR). Preclinical data has demonstrated both a reduction in MR and an improvement in Cardiac Output. Clinical studies are ongoing in both the U.S. and Europe.
Cardiac Dimensions Inc. is based in Kirkland, WA, and develops and manufactures devices designed for treating heart failure and related conditions. It is a privately held company whose investors include MPM Capital, Interwest Partners, Polaris, and Frazier Health Care.
For further information contact Tom Douthitt at 425 605-5900 or visit our Web site at www.cardiacdimensions.com.


text:
Teleology and Conspiracy Thinking
Published by Steven Novella under Conspiracy Theories,Neuroscience
I hate the headline of the Independent article about this new study – "Scientists discover the reason people believe in conspiracy theories." No, they didn't. What they potentially found was an additional factor that predicts conspiracy thinking, meaning that it correlates with it. A much better headline would be – "Scientists find that believing in final causes correlates with conspiratorial thinking," or something like that.
I understand the need to make headlines eye-catching, but you can do that without misrepresenting the science. The body of the article itself, while it does a decent job of explaining teleology, also misrepresents the implications of the study in a typical way – it fails to put it into the context of existing research.
Mainstream science reporting often follows a typical narrative – we essentially knew nothing, then scientists made this breakthrough discovery, and now we fully understand "the" cause of whatever.
The real scientific narrative is often quite different – we know something about this complex phenomenon, but there is still much that is not known, and now scientists have added one more piece to the puzzle. This is actually, in my opinion, a far more compelling narrative, but you have to tell the whole story of the scientific question, not just the one study.
The researchers in the current study had a working hypothesis that teleology is part of conspiratorial thinking. Teleology is the belief that things happen for a reason, that the final result is, in fact, the cause. Things happen because they were meant to. Things exist because of the purpose they serve.
Teleology is generally considered to be philosophically and scientifically invalid, primarily because you cannot reverse the arrow of causation. Science generally follows the "shit happens" philosophy. Things happens for reasons unrelated to whatever effects they ultimately have. If an asteroid hits the Earth it was not because it was meant to, or because human civilization deserved to be wiped out. It is because of orbital mechanics, gravity, Newton's laws of motion, and Keplers laws of planetary motion. The fact that human civilization got wiped out was just bad luck.
But despite the fact that teleological thinking is not valid, it is still psychologically compelling and infests our thinking. It is properly understood as a cognitive bias.
The researchers wanted to know if teleological thinking correlates with conspiratorial thinking. A connection makes sense – conspiracy theorists generally believe that apparently random or disconnected events happened for a reason. In the case of conspiracy theorists the reason was not fate or God, but the conspiracy – dark and powerful agents operating in the world with their own nefarious purposes.
They did a small pilot study on a convenience sample of college students (of course) but then followed up with a larger sample of the general population. They found that conspiratorial thinking moderately correlated with teleological thinking. It also correlated with belief in creationism, which is explained by the fact that creationism strongly correlates with teleological thinking (species exist because they were made with a purpose, not because of unguided evolution).
The researchers, however, then delved a little deeper, and this relates to what we already know about conspiracy thinking (a context completely ignored in the Independent article). It has already been established that conspiracy thinking correlates with the need for certainty (cognitive closure), for example. Conspiracy thinking also strongly correlates with pattern recognition and something called hyperactive agency detection. Conspiracy theorists tend to see patterns in random noise, and tend to see a hidden agency behind those patterns.
Approach to knowledge also correlates – belief in intuition, lack of need for evidence, and belief that facts are political all correlate with increased belief in conspiracy theories. Researchers have also found that conspiracy theorists generally lack control over their lives, want to feel special, and yet generally are frustrated over lack of success in their life. Finally, conspiracy thinking correlates with lack of trust in authorities, lack of acceptance of science, and lack of analytical thinking. (So again, the idea that scientists have found "the" cause of conspiracy thinking ignores a large body of research.)
Back to the current study – they found that teleological thinking is now an additional factor that correlates with conspiracy thinking, but they wanted to further explore it's relationship to other factors, specifically agency detection. They found:
We called the first factor 'animism', as it clusters measures involving attribution of consciousness and agency to nonliving entities. The second factor, 'finalism', tapped instead into the attribution of purpose and final causes to the universe and human life. We then conducted a series of multiple regressions with creationism and conspiracism as dependent variables, and animism and finalism, as well as science rejection, analytical thinking and randomness perception, as predictors. Finalism was the main predictor for creationism, β = 0.55, t = 17.19, p < 0.05, followed at a smaller degree by animism, β = 0.23, t = 6.93, p < 0.05, whereas rejection of science and animism were the main predictors for conspiracism (respectively β = 0.30, t = 8.80, p < 0.05; β = 0.32, t = 9.65, p < 0.05), jointly with finalism to a slightly lesser extent, β = 0.23, t = 7.26, p < 0.05.
So, contrary to the mainstream reporting, the study found that conspiracy thinking most strongly correlated with agency detection along with rejection of science, and only to a lesser extent with teleological thinking. Creationism, however, was primarily correlated with teleological thinking. The authors conclude:
Collectively, these results identify teleological thinking as a new predictor of conspiracism, independent of agency perception, anthropomorphism, science rejection, analytical thinking and randomness perception. As a finalist and purpose-driven view of the natural world, teleological thinking has long been associated with creationism and identified as an obstacle to the acceptance of evolutionary theory. We suggest that this powerful cognitive bias extends to social and historical events, and nowadays to conspiracy narratives. As such, creationism could be seen as a conspiracist belief system (indeed, involving the ultimate conspiracy theory: the purposeful creation of all things, and conspiracism as a type of creationist belief targeting socio-historic events (e.g. specific events have been purposefully created by an all-powerful agency).
I agree that creationism often includes conspiratorial thinking – you have to think there is a conspiracy among the world's scientists to reject creationism and promote evolution, if you disagree with the science.
While I agree that this study adds another piece to the conspiracy puzzle – teleological thinking – it is not the major piece. Agency detection is still a larger predictor. But the study does highlight how complex sociopsychological phenomena such as conspiracy thinking are. Teasing apart the complex cause and effects of why a particular individual, or groups of people, believe certain conspiracies is likewise complex. There is no "the" cause.
But it does help to understand specific cognitive biases, and how those biases contribute to arriving at certain narratives or conclusions that are at odds with reality. This study also adds to the large body of research which collectively shows that there is a general predisposition in people toward conspiracy thinking, although in some people far more than others.
There is a host of cognitive biases which collectively push toward a stable (if invalid) narrative that gives the powerful illusion of explanatory power – the conspiracy theory.


text:
jimmi campkin
jimmicampkin@gmail.com
© 2023 By Henry Cooper. Proudly created with Wix.com
I was born and grew up in a fading post-industrial town, where nature took over the abandoned crumbling remains of so many concrete beehives and gave me my playground and my aesthetic. This sense of nostalgic adventure - of exploration, environment, hazy evenings in open fields or studying the graffiti that lined the walls of the old railway - these elements have made both my writing and my photography.
I have had no formal training in photography besides having a pair of eyes and a curious mind. My work is often light, heavy, optimistic, suffocating, surreal and sentimental. But ultimately these are just words; your eyes will see what you want to see.
Thank you very much for visiting and viewing.


Frame Design, Old Window Frames was posted April 11, 2016 at 4:37 am by getyourjob.info . More over Old Window Frames has viewed by 6022 visitor.
Frame Ideas, Old Window Picture Frame was posted December 4, 2015 at 2:49 pm by getyourjob.info . More over Old Window Picture Frame has viewed by 7515 visitor.
Frame Ideas, Old Window Frames For Sale was posted April 13, 2016 at 9:08 am by getyourjob.info . More over Old Window Frames For Sale has viewed by 5964 visitor.


"We Built This Place – We Run This Place".
Home/Media, Uncategorized/"We Built This Place – We Run This Place".
This music video from Saleh Haddad / Abdulkhaliq speaks to that.
There's some incoherence at work here in the cultural signs: the kafil / sponsor-employer is dressed as Saudi, while the main worker is dressed as Pathan – but is reading a Malayalam newspaper and watching Hindi TV. Perhaps this is deliberate, to produce a sense of generic 'South Asian' migrant (which is in fact how many Arabs do think of anyone hailing from anywhere in South Asia, even naming all such migrants 'Indian'. Because I'm working among Malayalis I have no idea how Pakistanis or Nepalis feel about being labelled 'Indian'). The Driver character is dressed as Bangladeshi.
The video plays with various tropes of Gulf migrant life: construction, driving, house-servant work, a shouting boss, Ray-Ban sunglasses, the labourer's resistance tactic of the 'go-slow' – and even the risk of jail (2.53).
I recently published (along with Jane Bristol-Rhys) an article about the endurance of colonial stereotypes of masculinity in the Gulf, and the ways in which Arab men and South Asian men are drawing on different gender regimes and norms of what is considered masculine when they assess each other. This video speaks right into a discourse I've found to be widespread among migrants: that a proper man would not depend on others to get the important things done.


text:
package utils;

import java.util.ArrayList;
import java.util.List;
import java.util.Random;

public class NodoMateria implements java.io.Serializable{
	private int id;
	private ArrayList<NodoPredicado> estados;
	private ArrayList<NodoMateria> adyacentes;
	private ArrayList<Integer> colores;
	private ArrayList<Integer> coloresPosibles;

	public NodoMateria(List<Integer> nuevosColores) {
		colores    = new ArrayList<Integer>();
		adyacentes = new ArrayList<NodoMateria>();
		coloresPosibles = new ArrayList<Integer>();

		for (Integer i : nuevosColores) {
			this.coloresPosibles.add(i);
		}
	}
	public NodoMateria(int c1, int c2, int c3, int c4, int c5) {
		colores    = new ArrayList<Integer>();
		adyacentes = new ArrayList<NodoMateria>();
		coloresPosibles = new ArrayList<Integer>();

		this.colores.add(c1);
		this.colores.add(c2);
		this.colores.add(c3);
		this.colores.add(c4);
		this.colores.add(c5);
	}

	public NodoMateria(int i) {
		colores    = new ArrayList<Integer>();
		adyacentes = new ArrayList<NodoMateria>();
		coloresPosibles = new ArrayList<Integer>();
		Random randomGenerator = new Random();

		for(int j = 0; j < randomGenerator.nextInt(4) + 1 ; j++){
			this.colores.add(j);
		}
		this.colores.add(i);

		coloresPosibles.add(i);
	}

	public NodoMateria(int i, int k, int n) {
		colores    = new ArrayList<Integer>();
		adyacentes = new ArrayList<NodoMateria>();
		coloresPosibles = new ArrayList<Integer>();
		Random randomGenerator = new Random();
//		randomGenerator.nextInt(3) + 1

		for(int j = 0; j < i + 1 ; j++){
//			this.coloresPosibles.add(randomGenerator.nextInt(1000000));
			this.coloresPosibles.add(j);
		}
		this.coloresPosibles.add(i);

	}

	public NodoMateria(int i, boolean k) {
		Random randomGenerator = new Random();
		colores    = new ArrayList<Integer>();
		adyacentes = new ArrayList<NodoMateria>();
		coloresPosibles = new ArrayList<Integer>();

		int l = 0;
		int p = i;
		for(int j = Math.min(l, p) ; j < Math.max(l, p); j++){
//			this.colores.add(randomGenerator.nextInt(i));
			this.colores.add(j);
			this.coloresPosibles.add(j);
		}

	}

	public NodoMateria(int i, int j) {
		colores    = new ArrayList<Integer>();
		adyacentes = new ArrayList<NodoMateria>();
		coloresPosibles = new ArrayList<Integer>();
		this.colores.add(i);
		this.colores.add(j);
	}

	public void addAdyacente(NodoMateria m) {
		this.adyacentes.add(m);
	}

	public void addEstados(ArrayList<NodoPredicado> estados) {
		this.estados = estados;
	}

	public void setColor(Integer i) {
		this.colores.add(i);
	}

	public void clearColors(){
		this.colores = new ArrayList<Integer>();
	}

	public ArrayList<Integer> getColoresPosibles() {
		return this.coloresPosibles;
	}

	public void setId(int id) {
		this.id = id;
	}

	public int getId() {
		return this.id;
	}

	public int getColor(int i) {
		return colores.get(i);
	}

	public ArrayList<Integer> getColores() {
		return this.colores;
	}

	public List<NodoMateria> getAdyacentes() {
		return this.adyacentes;
	}

	public NodoPredicado getEstado(int i) {
		return estados.get(i);
	}
}

redpajama_set_name: RedPajamaGithub


text:
Example 6: Manual evaluation of non-Poissonian Likelihood
=========================================================

In this example we show to manually evaluate the non-Poissonian
likelihood. This can be used, for example, to interface ``nptfit`` with
parameter estimation packages other than MultiNest. We also show how to
extract the prior cube.

We will take the exact same analysis as considered in the previous
example, and show the likelihood peaks at exactly the same location for
the normalisation of the non-Poissonian template.

**NB:** This example makes use of the Fermi Data, which needs to already
be installed. See Example 1 for details.

.. code:: python

    # Import relevant modules

    %matplotlib inline
    %load_ext autoreload
    %autoreload 2

    import numpy as np
    import healpy as hp
    import matplotlib.pyplot as plt

    from NPTFit import nptfit # module for performing scan
    from NPTFit import create_mask as cm # module for creating the mask
    from NPTFit import psf_correction as pc # module for determining the PSF correction
    from NPTFit import dnds_analysis # module for analysing the output

    from __future__ import print_function

Setup an identical instance of NPTFit to Example 5
--------------------------------------------------

Firstly we initialize an instance of ``nptfit`` identical to that used
in the previous example.

.. code:: python

    n = nptfit.NPTF(tag='non-Poissonian_Example')

.. code:: python

    fermi_data = np.load('fermi_data/fermidata_counts.npy')
    fermi_exposure = np.load('fermi_data/fermidata_exposure.npy')
    n.load_data(fermi_data, fermi_exposure)

.. code:: python

    analysis_mask = cm.make_mask_total(mask_ring = True, inner = 0, outer = 5, ring_b = 90, ring_l = 0)
    n.load_mask(analysis_mask)

.. code:: python

    iso = np.load('fermi_data/template_iso.npy')
    n.add_template(iso, 'iso')

.. code:: python

    n.add_poiss_model('iso','$A_\mathrm{iso}$', False, fixed=True, fixed_norm=1.47)
    n.add_non_poiss_model('iso',
                          ['$A^\mathrm{ps}_\mathrm{iso}$','$n_1$','$n_2$','$S_b$'],
                          [[-6,1],[2.05,30],[-2,1.95]],
                          [True,False,False],
                          fixed_params = [[3,22.]])

.. code:: python

    pc_inst = pc.PSFCorrection(psf_sigma_deg=0.1812)
    f_ary = pc_inst.f_ary
    df_rho_div_f_ary = pc_inst.df_rho_div_f_ary

.. parsed-literal::

    Loading the psf correction from: /group/hepheno/smsharma/NPTFit/examples/psf_dir/gauss_128_0.181_10_50000_1000_0.01.npy

.. code:: python

    n.configure_for_scan(f_ary=f_ary, df_rho_div_f_ary=df_rho_div_f_ary, nexp=1)

.. parsed-literal::

    The number of parameters to be fit is 3

Evaluate the Likelihood Manually
--------------------------------

After configuring for the scan, the instance of ``nptfit.NPTF`` now has
an associated function ``ll``. This function was passed to MultiNest in
the previous example, but we can also manually evaluate it.

The log likelihood function is called as: ``ll(theta)``, where ``theta``
is a flattened array of parameters. In the case above:

.. math::  \theta = \left[ \log_{10} \left( A^\mathrm{ps}_\mathrm{iso} \right), n_1, n_2 \right]

As an example we can evaluate it at a few points around the best fit
parameters:

.. code:: python

    print('Vary A: ', n.ll([-3.52+0.22,2.56,-0.48]), n.ll([-3.52,2.56,-0.48]), n.ll([-3.52-0.24,2.56,-0.48]))
    print('Vary n1:', n.ll([-3.52,2.56+0.67,-0.48]), n.ll([-3.52,2.56,-0.48]), n.ll([-3.52,2.56-0.37,-0.48]))
    print('Vary n2:', n.ll([-3.52,2.56,-0.48+1.18]), n.ll([-3.52,2.56,-0.48]), n.ll([-3.52,2.56,-0.48-1.02]))

.. parsed-literal::

    Vary A:  -587.546407526 -587.02757201 -588.170002713
    Vary n1: -588.440076554 -587.02757201 -586.815912499

.. parsed-literal::

    /group/hepheno/heptools/anaconda3/envs/venv_py27/lib/python2.7/site-packages/NPTFit-0.1rc0-py2.7-linux-x86_64.egg/NPTFit/nptf_scan.py:416: VisibleDeprecationWarning: using a non-integer number instead of an integer will result in an error in the future

.. parsed-literal::

    Vary n2: -587.141423107 -587.02757201 -587.081816027

To make the point clearer we can fix :math:`n_1` and :math:`n_2` to
their best fit values, and calculate a Test Statistics (TS) array as we
vary :math:`\log_{10} \left( A^\mathrm{ps}_\mathrm{iso} \right)`. As
shown the likelihood is maximised at approximated where MultiNest told
us was the best fit point for this parameter.

.. code:: python

    Avals = np.arange(-5.5,0.5,0.01)
    TSvals_A = np.array([2*(n.ll([-3.52,2.56,-0.48])-n.ll([Avals[i],2.56,-0.48])) for i in range(len(Avals))])

.. code:: python

    plt.plot(Avals,TSvals_A,color='black', lw=1.5)
    plt.axvline(-3.52+0.22,ls='dashed',color='black')
    plt.axvline(-3.52,ls='dashed',color='black')
    plt.axvline(-3.52-0.24,ls='dashed',color='black')
    plt.axhline(0,ls='dashed',color='black')
    plt.xlim([-4.0,-3.0])
    plt.ylim([-5.0,15.0])
    plt.xlabel('$A^\mathrm{ps}_\mathrm{iso}$')
    plt.ylabel('$\mathrm{TS}$')
    plt.show()

.. image:: Example6_Manual_nonPoissonian_Likelihood_files/Example6_Manual_nonPoissonian_Likelihood_17_0.png

Next we do the same thing for :math:`n_2`. This time we see that this
parameter is much more poorly constrained than the value of the
normalisation, as the TS is very flat.

**NB:** it is important not to evaluate breaks exactly at a value of
:math:`n=1`. The reason for this is the analytic form of the likelihood
involves :math:`(n-1)^{-1}`.

.. code:: python

    n2vals = np.arange(-1.995,1.945,0.01)
    TSvals_n2 = np.array([2*(n.ll([-3.52,2.56,-0.48])-n.ll([-3.52,2.56,n2vals[i]])) for i in range(len(n2vals))])

.. code:: python

    plt.plot(n2vals,TSvals_n2,color='black', lw=1.5)
    plt.axvline(-0.48+1.18,ls='dashed',color='black')
    plt.axvline(-0.48,ls='dashed',color='black')
    plt.axvline(-0.48-1.02,ls='dashed',color='black')
    plt.axhline(0,ls='dashed',color='black')
    plt.xlim([-2.0,1.5])
    plt.ylim([-5.0,15.0])
    plt.xlabel('$n_2$')
    plt.ylabel('$\mathrm{TS}$')
    plt.show()

.. image:: Example6_Manual_nonPoissonian_Likelihood_files/Example6_Manual_nonPoissonian_Likelihood_20_0.png

In general :math:`\theta` will always be a flattened array of the
floated parameters. Poisson parameters always occur first, in the order
in which they were added (via ``add_poiss_model``), following by
non-Poissonian parameters in the order they were added (via
``add_non_poiss_model``). To be explicit if we have :math:`m` Poissonian
templates and :math:`n` non-Poissonian templates with breaks
:math:`\ell_n`, then:

.. math::

    \theta = \left[ A_\mathrm{P}^1, \ldots, A_\mathrm{P}^m, A_\mathrm{NP}^1, n_1^1, \ldots, n_{\ell_1+1}^1, S_b^{(1)~1}, \ldots, S_b^{(\ell_1)~1}, \ldots, A_\mathrm{NP}^n, n_1^n, \ldots, n_{\ell_n+1}^n, S_b^{(1)~n}, \ldots, S_b^{(\ell_n)~n} \right]

Fixed parameters are deleted from the list, and any parameter entered
with a log flat prior is replaced by :math:`\log_{10}` of itself.

Extract the Prior Cube Manually
-------------------------------

To extract the prior cube, we use the internal function
``log_prior_cube``. This requires two arguments: 1. ``cube``, the unit
cube of dimension equal to the number of floated parameters; and 2.
``ndim``, the number of floated parameters.

.. code:: python

    print(n.prior_cube(cube=[1,1,1],ndim=3))

.. parsed-literal::

    [1.0, 30.0, 1.9500000000000002]


text:
/ Xeni Jardin / 6:53 pm Mon Dec 17, 2018
Court orders deer poacher to watch 'Bambi' repeatedly as part of sentence
In the Ozarks, a Missouri court ordered a poacher to watch the movie "Bambi" over and over again as part of his sentence for a criminal scheme to illegally kill hundreds of deer.
From KansasCity.com
David Berry Jr. was ordered to watch the Disney classic at least once a month during his year-long jail sentence in what conservation agents have called one of the largest deer poaching cases in state history, the Springfield News-Leader reports.
"The deer were trophy bucks taken illegally, mostly at night, for their heads, leaving the bodies of the deer to waste," said Don Trotter, the prosecuting attorney in Lawrence County.
Berry, his father, two brothers and another man who helped them had their hunting, fishing and trapping privileges revoked temporarily or permanently. The men have paid a combined $51,000 in fines and court costs — but the judge ordered a special addition to Berry's sentence for illegally taking wildlife.
Court records show he was ordered by Lawrence County Judge Robert George to "view the Walt Disney movie Bambi, with the first viewing being on or before December 23, 2018, and at least one such viewing each month thereafter" while at the county jail.
Berry was also sentenced to 120 days in jail in nearby Barton County for a firearms probation violation.
IMAGE: This undated photo provided by in Lawerence County Sheriff in Mt. Vernon, Mo., shows David Berry Jr. Berry was ordered to watch the Walt Disney movie at least once each month during his one-year jail sentence in what conservation agents are calling one of the largest deer poaching cases in state history. Lawrence County Prosecuting Attorney Don Trotter says the deer were killed for their heads and their bodies were left to rot. (Lawerence County Sheriff)
(via Josh Stearns)
missouri / murder / News / picks / weird justice
A new AI tool from Adobe can detect Photoshopped faces
We presume it can tell by the pixels.
Microsoft takes down MS Celeb facial recognition database, 10 million+ pics of ~100,000 faces, maybe yours, scraped under Creative Commons
Military research and Chinese firms had access to the data Microsoft scraped under Creative Commons licenses.
Survey: 50% of Americans believe 'made-up news' is a very big problem for the country today. 46% say the same about climate change.
More Americans view made-up news as a 'very big problem' for the country, over terrorism, illegal immigration, racism, and sexism.


In medieval Sweden a knight returns from war only to find a ravaged homeland. He meets up with a group of travelling players and eventually confronts the embodiment of death with whom he engages in a game of chess for his life. The knight and Death play as the cultural turmoil envelopes the people around them as they try, in different ways, to deal with the upheaval the plague has caused.
a Janus Films release ; Svensk Filmindustri presents a film by Ingmar Bergman ; producer, Allan Ekelund ; screenplay writer, Ingmar Bergman ; director, Ingmar Bergman.
[Irvington, N.Y.] : Criterion Collection : Home Vision Cinema, c1998.
Swedish dialogue, with optional English subtitles or English dubbed version, with no subtitles.
Gunnar Björnstrand, Bengt Ekerot, Nils Poppe, Max Von Sydow, Bibi Andersson, Inga Gill, Maud Hansson, Inga Landgré, Gunnel Lindblom.
Photography, Gunnar Fischer; editor, Lennart Wallén; music, Erik Nordgren.
Originally released as motion picture in 1957.
Based on the play Painting on wood, by Ingmar Bergman.
"The Classic Collection, a joint venture between Janus Films and Home Vision Cinema"--Container.
Special features: audio commentary by film historian Peter Cowie; Ingmar Bergman: an illustrated filmography; theatrical trailer; restoration demonstration.
Knights and knighthood Sweden Drama.


text:
Басова, Евгения Владимировна () — российский писатель. Член СП России.

Биография
Родилась в 1963 году в Красноярске, жила в посёлке Понорница Черниговской области, на Украине, в Магадане. Окончила факультет журналистики МГУ имени М. В. Ломоносова. Живёт в Чебоксарах, трое детей. Работала лаборанткой в литейном цехе, санитаркой в отделении для новорожденных, художником-оформителем в детском центре, руководителем литературной студии для подростков, редактором заводской газеты, корреспондентом в областных газетах, дизайнером в полиграфии.

В рассказах и повестях для детей и подростков затрагивает недетские темы одиночества и бесприютности, непонятности, инаковости, предательства и внутренней жестокости, поиск искренней привязанности.

Библиография
 «Эй, рыбка» (псевд. Илга Понорницкая, 2011, «Самокат»)
 «Булка, Беляш и другие с Лесной улицы» (псевд. Илга Понорницкая, 2013, «Речь»)
 «Уезжающие и остающиеся» (2014, «КомпасГид»)
 «Следы» (2017, «Речь»)
 «Деньги, дворняги, слова» (2017, «Детская литература»)
 «Подросток Ашим» (2018, «Детское время»)
 «Внутри что-то есть» (рассказ в сб., 2019, «Волчок»)
 «Изо» (2019, «Самокат»)
 «Наша Земля — дышит» (2020, «Детское время»)

Публикации
 Произведения Евгений Басовой выходили в журналах «Октябрь» и «Звезда», «Кукумбер», «Московский литератор», «День и ночь», «Новый енисейский литератор» (Красноярск), «Чиж и еж» (Санкт-Петербург), «Урал» (Екатеринбург), «Лик Чувашии», «Лик», «Чувашия литературная» (Чебоксары).
 Евгения Басова. Библиогид
 Российские деятели культуры номинированы на премию памяти Астрид Линдгрен
 Враг Мышаня и Бычок с диареей против детской литературы. Что происходит с рынком книг для детей, и почему взрослые и уполномоченный по правам ребёнка замечают только худшие образцы
 Авторы книг для детей и их родителей: как начать читать

Награды
 Финалист и лауреат Национальной премии «Заветная мечта» (2008, 2009).
 Лауреат Международного конкурса детской и юношеской литературы имени А. Н. Толстого  (2009).
 Финалист Всероссийского конкурса на лучшее произведение для детей и юношества Книгуру (2017).
 Финалист премии Владислава Крапивина 2014 года.
 Лауреат Всероссийского конкурса на лучшее произведение для детей и юношества Книгуру (2018).
Лауреат литературного конкурса на соискание премий правительства Москвы имени Корнея Чуковского (2020).

Примечания

redpajama_set_name: RedPajamaWikipedia


The auditions for the 2018 eeemerging programme will take place on the 4th, 5th and 6th of September in Utrecht (Netherlands), Lyon (France) and Vienna (Austria). The 8 eeemerging co-organizers will select 4 ensembles among 12 that will join the 2018 eeemerging programme for their first year of support. Two have already been selected to join the 2018 eeemerging program: L'Apothéose who won the Göttingen Händel Competition and Rumorum who won the eeemerging prize during the York Early Music Competition.
In the framework of this programme, these 6 ensembles will benefit from trainings on promotion, communication and administration and will be offered concerts and residencies.
The selected ensembles have to play two extracts from their repertoire and answer the questions of the jury composed of 8 partners coming from the United Kingdom, Latvia, Germany, Slovenia, Romania, Spain, Italy and France.


Marking its first home meet of the season, the University of Utah track and field team hosted the first part of the Utah/Weber State Spring Classic at the McCarthey Family Track and Field on Friday, April 7. Taking advantage of the friendly crowd and familiar terrain, the Utes ended up with four event titles, including setting a new track record.
Junior Dakota Grossman thinks that this classic was special for the team because it happens only once a year, and it gives her team a home field advantage.
"It's our home field, we practice here, and it's really exciting because we finally get to have some fans and family come out and support us," Grossman said.
In the long jump event, freshman Ann Wingeleth broke the track record by hitting a mark of 20 feet, 1.5 inches (6.13m), breaking the previous record set by Montana State's Carley McCutchen (5.95m) in 2015.
Freshman Holly Stallman competed in the long jump as well, finishing sixth overall with a mark of 17 feet, 11.5 inches (5.47m). Junior Madison Lanford followed in 17th place with a mark of 15 feet, 11 inches (4.85m), while sophomore Lauren McCluskey earned 21st place overall with a mark of 14 feet, 2.5 inches (4.33m).
Sophomore Christine Glasmann won the javelin competition for the second year in a row, after throwing for 148 feet, 5 inches (45.23m), and against a strong headwind that continued throughout the meet.
The Utes also won the 3000-meter steeplechase as senior Dana Snell, who was the only Ute to compete in the race, took the title after finishing with a final time of 11:24.04. Snell was also recognized later in the meet as the team's lone participating senior.
Utah's 4×100-meter relay team finished third with a time of 48.78 seconds. Utah also competed in the 100-meter hurdles, with Lanford finishing 16th overall with a time of 15.60 seconds. Freshman Piper Wehrli placed 19th overall with a personal best time of 15.92 seconds, while McCluskey came in just behind Wehrli to take 20th overall, posting a time of 15.93 seconds.
Up next, the Utes will head to Walnut, Calif. to compete in the Mt. Sac relays.


text:
Home /Mike Pompeo said Iran-backed militias moved rockets near American bases in Iraq
EntertainmentMay 15, 2019
Mike Pompeo said Iran-backed militias moved rockets near American bases in Iraq
Secretary of State Mike Pompeo told Iraqi officials that U.S. intelligence showed Iran-backed militias moved missiles near bases housing American forces.
Pompeo made the disclosure to Iraq's top brass during his surprise visit earlier this month, Reuters reported. The revelation comes just hours after all non-emergency personnel at the U.S. Embassy in Iraq was ordered to leave the country.
US NON-ESSENTIAL PERSONNEL ORDERED TO LEAVE IRAQ EMBASSY, CONSULATE
He asked the military officials to keep the Shi'ite militias in control as they are expanding their presence in the country and now are part of the country's security apparatus. The top diplomat warned that otherwise, the U.S. would have to use force to tackle the security threats.
"The message from the Americans was clear. They wanted guarantees that Iraq would stop those groups threatening U.S. interests," a senior Iraqi military source with knowledge of Pompeo's trip told Reuters.
"They said if the U.S. were attacked on Iraqi soil, it would take action to defend itself without coordinating with Baghdad."
A State Department spokesperson told Fox News: "Given the increased threat stream we are seeing in Iraq, which we shared with the Iraqi government during the Secretary's visit on May 7 and in subsequent engagements, the Secretary has decided to place Mission Iraq on ordered departure.
"Ensuring the safety of U.S. government personnel and U.S. citizens and security of our facilities are our highest priorities. We remain committed to partnering with Iraqis to advance our mutual interests."
"For safety reasons, I am not able to detail specific security concerns."
— Senior Iraqi military source
In this Sunday, May 12, 2019 photo released by the U.S. Air Force, a U.S. Air Force B-52H Stratofortress aircraft assigned to the 20th Expeditionary Bomb Squadron takes off from Al Udeid Air Base, Qatar.
(Staff Sgt. Ashley Gardner, U.S. Air Force via AP)
U.S. officials said last week that urgent "credible threats" from Iran against Americans were detected in Iraq, prompting the embassy to advise against all travel to the region, citing "heightened tensions."
On Wednesday morning, all non-emergency personnel at the U.S. Embassy and consulate in Iraq was ordered to leave the country. Normal visa services were also temporarily halted.
But the claim at hostile militia forces are positioning the rockets near bases housing American troops, provides more insight into the threats the U.S. faces in the Middle East in the wake of rising tensions between the Trump administration and the Iranian regime.
COTTON SAYS AMERICA WOULD WIN WAR AGAINST IRAN IN 'TWO STRIKES'
President Trump denied Tuesday the reports that the administration was planning to send more than 100,000 troops to the region in the wake of heightened tensions in the region, but instead noted that "If we did that, we'd send a hell of a lot more troops than that."
Iraqi Prime Minister Adel Abdul Mahdi told the media on Tuesday that his side didn't have information showing "movements that constitute a threat to any side," though added that his government "is doing its duty to protect all parties."
Secretary of State Mike Pompeo said Tuesday that "We fundamentally do not seek war with Iran, we're looking for the regime to simply stop conducting assassination campaigns throughout Europe."
His comments followed numerous threatening comments by Iranian officials who effectively threatened the U.S. with war.
Iran's Supreme leader Ayatollah Ali Khamenei also downplayed the escalation. Iran's state TV quoted Khamenei on Tuesday as calling negotiations with the U.S. "poison" and saying: "This is not a military confrontation, because no war is going to happen."
Khamenei, who has final say on all state matters, said: "Neither we, nor they are seeking war, they know that it is not to their benefit."
Iranian state media reported Wednesday however that Khamenei followed up these remarks by saying it wouldn't be difficult for the Islamic Republic to enrich uranium to weapons-grade levels amid rising tensions with the U.S., state media reported Wednesday.