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Cigarette smoking remains a significant health threat for smokers and nonsmokers alike. Secondhand smoke (SHS) is intrinsically more toxic than directly inhaled smoke. Recently, a new threat has been discovered – Thirdhand smoke (THS) – the accumulation of SHS on surfaces that ages with time, becoming progressively more toxic. THS is a potential health threat to children, spouses of smokers and workers in environments where smoking is or has been allowed. The goal of this study is to investigate the effects of THS on liver, lung, skin healing, and behavior, using an animal model exposed to THS under conditions that mimic exposure of humans. THS-exposed mice show alterations in multiple organ systems and excrete levels of NNAL (a tobacco-specific carcinogen biomarker) similar to those found in children exposed to SHS (and consequently to THS). In liver, THS leads to increased lipid levels and non-alcoholic fatty liver disease, a precursor to cirrhosis and cancer and a potential contributor to cardiovascular disease. In lung, THS stimulates excess collagen production and high levels of inflammatory cytokines, suggesting propensity for fibrosis with implications for inflammation-induced diseases such as chronic obstructive pulmonary disease and asthma. In wounded skin, healing in THS-exposed mice has many characteristics of the poor healing of surgical incisions observed in human smokers. Lastly, behavioral tests show that THS-exposed mice become hyperactive. The latter data, combined with emerging associated behavioral problems in children exposed to SHS/THS, suggest that, with prolonged exposure, they may be at significant risk for developing more severe neurological disorders. These results provide a basis for studies on the toxic effects of THS in humans and inform potential regulatory policies to prevent involuntary exposure to THS.  相似文献   
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Unlike plasma and most biological fluids which have solute concentrations that are tightly controlled, urine volume can vary widely based upon water consumption and other physiological factors. As a result, the concentrations of endogenous metabolites in urine vary widely and normalizing for these effects is necessary. Normalization approaches that utilized urine volume, osmolality, creatinine concentration, and components that are common to all samples (“total useful MS signal”) were compared in order to determine which strategies could be successfully used to differentiate between dose groups based upon the complete endogenous metabolite profile. Variability observed in LC/MS results obtained from targeted and non-targeted metabonomic analyses was highly dependent on the strategy used for normalization. We therefore recommend the use of two different normalization techniques in order to facilitate detection of statistically significant changes in the endogenous metabolite profile when working with urine samples.  相似文献   
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