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Human paraoxonase‐1 (PON1) is a high‐density lipoprotein‐associated enzyme with antioxidant, anti‐inflammatory, and antiapoptotic roles. The ability of PON1 to hydrolyze specific organophosphate (OP) compounds and prevent accumulation of oxidized lipids in lipoproteins has prompted a large number of studies investigating PON1's role in modulating toxicity and disease. Most of these studies, however, have only focused onPON1single nucleotide polymorphism analyses and have ignored PON1 activity levels, arguably the most important parameter in determining protection against exposure and disease. We developed a two‐substrate activity assay termed “PON1 status” that reveals both the functionalPON1₁₉₂genotype and plasma PON1 activity levels. While our previous studies with PON1 status demonstrated that bothPON1₁₉₂functional genotype and enzymatic activity levels obtained exclusively by determining PON1 status are required for a proper evaluation of PON1's role in modulating OP exposures and risk of disease, the original PON1 status assay requires the use of highly toxic OP metabolites. As many laboratories are not prepared to handle such toxic compounds and the associated waste generated, determination of PON1 status has been limited to rather few studies. Here, we describe a PON1 status protocol that uses non‐OP substrates with a resolution equivalent to that of the original PON1 status approach. We have also included useful suggestions to ensure the assays can easily be carried out in any laboratory. The protocols described here will enable a proper examination of the risk of exposure or susceptibility to disease in PON1 epidemiological studies without the need to handle highly toxic substrates. © 2021 Wiley Periodicals LLC.

This article was corrected on 18 July 2022. See the end of the full text for details.

Basic Protocol: Determining PON1 status using non‐organophosphate substrates

Support Protocol 1: Experimental pathlength determination

Support Protocol 2:PON1DNA genotyping for the Q192R (rs662) polymorphism

A description is presented of the algorithms used to reconstruct energy deposited in the CMS hadron calorimeter during Run 2 (2015–2018) of the LHC. During Run 2, the characteristic bunch-crossing spacing for proton-proton collisions was 25 ns, which resulted in overlapping signals from adjacent crossings. The energy corresponding to a particular bunch crossing of interest is estimated using the known pulse shapes of energy depositions in the calorimeter, which are measured as functions of both energy and time. A variety of algorithms were developed to mitigate the effects of adjacent bunch crossings on local energy reconstruction in the hadron calorimeter in Run 2, and their performance is compared.

A search for decays to invisible particles of Higgs bosons produced in association with a top-antitop quark pair or a vector boson, which both decay to a fully hadronic final state, has been performed using proton-proton collision data collected at$${\sqrt{s}=13\,\text {Te}\hspace{-.08em}\text {V}}$$$\sqrt{s}=13\text{Te}\text{V}$by the CMS experiment at the LHC, corresponding to an integrated luminosity of 138$$\,\text {fb}^{-1}$$${\text{fb}}^{-1}$. The 95% confidence level upper limit set on the branching fraction of the 125$$\,\text {Ge}\hspace{-.08em}\text {V}$$$\text{Ge}\text{V}$Higgs boson to invisible particles,$${\mathcal {B}({\textrm{H}} \rightarrow \text {inv})}$$$B(\text{H}\to \text{inv})$, is 0.54 (0.39 expected), assuming standard model production cross sections. The results of this analysis are combined with previous$${\mathcal {B}({\textrm{H}} \rightarrow \text {inv})}$$$B(\text{H}\to \text{inv})$searches carried out at$${\sqrt{s}=7}$$$\sqrt{s}=7$, 8, and 13$$\,\text {Te}\hspace{-.08em}\text {V}$$$\text{Te}\text{V}$in complementary production modes. The combined upper limit at 95% confidence level on$${\mathcal {B}({\textrm{H}} \rightarrow \text {inv})}$$$B(\text{H}\to \text{inv})$is 0.15 (0.08 expected).