Measurement and meaning of markers of reactive species of oxygen, nitrogen and sulfur in healthy human subjects and patients with inflammatory joint disease

Reactive species of oxygen, nitrogen and sulfur play cell signalling roles in human health, e.g. recent studies have shown that increased dietary nitrate, which is a source of RNS (reactive nitrogen species), lowers resting blood pressure and the oxygen cost of exercise. In such studies, plasma nitrite and nitrate are readily determined by chemiluminescence. At sites of inflammation, such as the joints of RA (rheumatoid arthritis) patients, the generation of ROS (reactive oxygen species) and RNS overwhelms antioxidant defences and one consequence is oxidative/nitrative damage to proteins. For example, in the inflamed joint, increased RNS-mediated protein damage has been detected in the form of a biomarker, 3-nitrotyrosine, by immunohistochemistry, Western blotting, ELISAs and MS. In addition to NO?, another cell-signalling gas produced in the inflamed joint is H2S (hydrogen sulfide), an RSS (reactive sulfur species). This gas is generated by inflammatory induction of H2S-synthesizing enzymes. Using zinc-trap spectrophotometry, we detected high (micromolar) concentrations of H2S in RA synovial fluid and levels correlated with clinical scores of inflammation and disease activity. What might be the consequences of the inflammatory generation of reactive species? Effects on inflammatory cell-signalling pathways certainly appear to be crucial, but in the current review we highlight the concept that ROS/RNS-mediated protein damage creates neoepitopes, resulting in autoantibody formation against proteins, e.g. type-II collagen and the complement component, C1q. These autoantibodies have been detected in inflammatory autoimmune diseases.     

Validation of BIA in Obese Children and Adolescents and Re‐evaluation in a Longitudinal Study

Decrease in fat mass (FM) is a one of the aims of pediatric obesity treatment; however, measurement techniques suitable for routine clinical assessment are lacking. The objective of this study was to validate whole‐body bioelectrical impedance analysis (BIA; TANITA BC‐418MA) against the three‐component (3C) model of body composition in obese children and adolescents, and to test the accuracy of our new equations in an independent sample studied longitudinally. A total of 77 white obese subjects (30 males) aged 5–22 years, BMI‐standard deviation score (SDS) 1.6–3.9, had measurements of weight, height (HT), body volume, total body water (TBW), and impedance (Z). FM and fat‐free mass (FFM) were calculated using the 3C model or predicted from TANITA. FFM was predicted from HT²/Z. This equation was then evaluated in 17 other obese children (5 males) aged 9–13 years. Compared to the 3C model, TANITA manufacturer's equations overestimated FFM by 2.7 kg (P < 0.001). We derived a new equation: FFM = ?2.211 + 1.115 (HT²/Z), with r² of 0.96, standard error of the estimate 2.3 kg. Use of this equation in the independent sample showed no significant bias in FM or FFM (mean bias 0.5 ± 2.4 kg; P = 0.4), and no significant bias in change in FM or FFM (mean bias 0.2 ± 1.8 kg; P = 0.7), accounting for 58% (P < 0.001) and 55% (P = 0.001) of the change in FM and FFM, respectively. Our derived BIA equation, shown to be reliable for longitudinal assessment in white obese children, will aid routine clinical monitoring of body composition in this population.     

Activity of vaccinia virus-neutralizing antibody in the sera of smallpox vaccinees

Individuals vaccinated against smallpox maintain substantial antiviral antibody responses for many years after vaccination. In this study, we examined the ability of antiviral antibodies from 104 unique serum samples to neutralize the two infectious forms of vaccinia virus, intracellular mature virus (IMV) and extracellular enveloped virus (EEV). While we found direct correlations between antiviral antibody titers and the ability to neutralize IMV and EEV, correlation with EEV neutralization was weaker. To determine factors that may influence more varied EEV neutralization within a vaccinated population, we asked the following questions. (1) Does vaccinia virus-neutralizing ability remain constant over time? (2) Do multiple vaccinations boost IMV and EEV neutralization activity? We found that serum from vaccinated individuals retained ability to neutralize EEV for a relatively long time, but there was a significant drop in EEV neutralization ability in the third decade after vaccination. While all vaccinees maintained some ability to neutralize IMV, a number of individuals lost the capacity to neutralize EEV. Interestingly, the ability to neutralize either virus form was not altered by the number of vaccinations received. Since it is likely that neutralizing antibodies against both IMV and EEV are required for maximal protective immunity, a loss of anti-EEV-neutralizing ability may warrant the revaccination of individuals who have been vaccinated >20 years ago, should widespread pre-event smallpox vaccination be instituted.     

Cell surface expression of the vaccinia virus complement control protein is mediated by interaction with the viral A56 protein and protects infected cells from complement attack

The vaccinia virus (VACV) complement control protein (VCP) is the major protein secreted from VACV-infected cells. It has been reported that VCP binds to the surfaces of uninfected cells by interacting with heparan sulfate proteoglycans (HSPGs). In this study, we show that VCP is also expressed on the surfaces of infected cells and demonstrate that surface localization occurs independently of HSPGs. Since VCP does not contain a transmembrane domain, we hypothesized that VCP interacts with a membrane protein that localizes to the infected-cell surface. We show that the VACV A56 membrane protein is necessary for the cell surface expression of VCP and demonstrate that VCP and A56 interact in VACV-infected cells. Since the surface expression of VCP was abrogated by reducing agents, we examined the contribution of an unpaired cysteine residue on VCP to VCP surface expression and VCP's interaction with A56. To do this, we mutated the unpaired cysteine in VCP and generated a recombinant virus expressing the altered form of VCP. Following the infection of cells with the mutant virus, VCP was neither expressed on the cell surface nor able to interact with A56. Importantly, the cell surface expression of VCP was found to protect infected cells from complement-mediated lysis. Our findings suggest a new function for VCP that may be important for poxvirus pathogenesis and impact immune responses to VACV-based vaccines.     

Validation of Bioelectrical Impedance Analysis in Adolescents Across Different Ethnic Groups

Adolescent obesity is difficult to assess in multi‐ethnic populations using BMI, due to variability in the BMI–fatness relationship. We aimed to describe body composition (BC), and to validate leg–leg bioelectrical impedance analysis (BIA), in adolescents from different ethnic groups using deuterium (D₂O) as the reference method. Measurements were made of weight, height, total body water (TBW), and BIA (TANITA TBF‐300) in 110 white, 170 Asian, and 102 black adolescents aged 11–15 years. TBW was converted to lean mass (LM) using assumed hydration of lean tissue. General linear models were used to compare BC by D₂O between the ethnic groups. BC values from D₂O were compared with TANITA values, and used to generate ethnic‐specific prediction equations in the whole sample, and also in equation‐generation (group 1) and cross‐validation (group 2) subsamples. Ethnic variability in BMI did not reflect variability in adiposity. Asians had less LM than white and black adolescents, and less fat mass (FM) than white girls. TANITA in‐built equations did not predict BC accurately across ethnic groups, with significant bias in white and Asian males, and Asian and black females. The new equation generated from the entire sample removes ethnic‐specific mean biases. The group 1 equation showed no significant bias in any ethnic group when tested in group 2. We found significant variability in BC between ethnic groups that was not reflected by BMI. Manufacturers' equations are unsuitable for predicting BC in multi‐ethnic populations, and our new equations are recommended.