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To account for potential spatial autocorrelation in brain maps, we conducted Spin Test analyses 64 using the BrainSMASH Python library ( 65

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Such a framework would need to compare different types of harm (e.g., disease, dependence, and bystander risk) arising over different periods (immediate, intermediate, and long-term), affecting different subpopulations (e.g., youth smokers, nonsmokers, adults, and deprived groups), caused by diverse products spanning a risk continuum of several orders of magnitude (e.g., cigarettes, vapes, and pouches), and used over varying periods (e.g., decades of heavy use vs

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Clinical and radiografic periodontal status and whole salivary cotinine, IL-1b and IL-6 levels in cigarette-and waterpipe-smokers and E-cig users