ObjectiveCountries around the world have increasingly adopted pictorial health warning labels (HWLs) for tobacco packages to warn consumers about smoking-related risks. Research on how pictorial HWLs work has primarily analysed self-reported responses to HWLs; studies at the neural level comparing the brain's response to different types of HWLs may provide an important complement to prior studies, especially if self-reported responses are systematically biased. In this study we characterise the brain's response to three types of pictorial HWLs for which prior self-report studies indicated different levels of efficacy.MethodsCurrent smokers rated pictorial HWLs and then observed the same HWLs during functional MRI (fMRI) scanning. Fifty 18–50-year-old current adult smokers who were free from neurological disorders were recruited from the general population and participated in the study. Demographics, smoking-related behaviours and self-reported ratings of pictorial HWL stimuli were obtained prior to scanning. Brain responses to HWLs were assessed using fMRI, focusing on a priori regions of interest.ResultsPictorial HWL stimuli elicited activation in a broad network of brain areas associated with visual processing and emotion. Participants who rated the stimuli as more emotionally arousing also showed greater neural responses at these sites.ConclusionsSelf-reported ratings of pictorial HWLs are correlated with neural responses in brain areas associated with visual and emotional processing. Study results cross-validate self-reported ratings of pictorial HWLs and provide insights into how pictorial HWLs are processed.

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Graphic health warning labels (HWLs) depicting bodily injury due to smoking are effective for producing changes in affect, cognition and smoking behavior in adult smokers. However, little is known about the effects of repeated presentation of graphic HWL's on the aforementioned processes. The goal of this study was to examine neural and behavioral responses to graphic HWL's and evaluate whether the repeated presentation of graphic HWL's leads to repetition suppression (RS). Smokers (N = 16) performed an event-related HWL cue task while blood oxygen level dependent (BOLD) signal was collected during a functional magnetic resonance imaging (fMRI) experimental session. Consistent with prior literature, graphic HWL's, as compared to scrambled images, elicited increased BOLD response in brain regions involved in self-referential and emotion processing. Importantly, BOLD response at sites in this network diminished during repeated presentation of the same HWL. These findings suggest that while novel graphic HWL's may have a significant effect on smokers' brain activity, repeated presentation may lead to muted responses and thus limit their potential to induce behavioral change.

Introduction: Markers of poor oral health are associated with impaired cognition and higher risk of Alzheimer disease (AD) and thus may help predict AD. Objectives: The aim of this study was to evaluate the cross-sectional association between empirically derived groups of 19 IgG antibodies against periodontal microorganisms and cognition in middle-aged and older adults. Methods: The study population consisted of participants of the third National Health and Nutrition Examination Survey (NHANES III) (1988 to 1994), who were 60 y and older, among whom cognition and IgG antibodies against 19 periodontal microorganisms were measured (N = 5,162). Results: In multivariable quantile regression analyses, the Orange-Red (Prevotella melaninogenica, Prevotella intermedia, Prevotella nigrescens, Porphyromonas gingivalis) and Yellow-Orange (Staphylococcus intermedius, Streptococcus oralis, Streptococcus mutans, Fusobacterium nucleatum, Peptostreptococcus micros, Capnocytophaga ochracea) cluster scores were negatively associated with cognition. A 1-unit higher cluster score for the Orange-Red cluster was associated on average with a lower cognitive score (β for 30th quantile = −0.2640; 95% confidence interval [CI], −0.3431 to −0.1848). Similarly, a 1-unit higher score for the Yellow-Orange cluster was associated with a lower cognitive score (β for 30th quantile = −0.2445; 95% CI, −0.3517 to −0.1372). Conclusion: Groups of IgG antibodies against periodontal microorganisms were associated with lower cognition among free living adults 60 years and older, who were previously undiagnosed with cognitive impairment. Though poor oral health precedes the development of dementia and AD, oral health information is currently not used, to our knowledge, to predict dementia or AD risk. Combining our findings with current algorithms may improve risk prediction for dementia and AD. Knowledge Translation Statement: IgG antibodies against periodontal microorganisms were associated with lower cognition among adults 60 years and older previously undiagnosed with cognitive impairment. Periodontal disease may predict cognition among older adults.

Background: Perfusion Computerized Axial Tomography (pCT) is a modality gaining popularity for acute stroke management decisions. We investigated the role of automated pCT in prediction of deficits measured by NIH Stroke Scale (NIHSS). Method: Acute stroke patients underwent pCT and NIHSS. Digital Imaging and Communications in Medicine ( DICOM ) images were assessed for maximum intensity (MI) and cerebral blood flow (CBF). MI scans (where there is little acute abnormality) were used to transform each scan into standard space. The CBF images were the continuous measure for abnormality. The regional CBF was estimated for 150 regions of interest. Statistical analyses used 4000 permutations to correct for multiple comparisons. Additionally support vector machines (SVM) were used to assess the ability of machine learning to classify the deficit severity. Results: PCT scans for 83 patients where analyzed (mean age ± SD=64.2 ±14.8, 63% males). Traditional analyses revealed (p < 0.01) that reduced blood flow in the large regions of the right hemisphere were associated with left motor impairment, while regional reductions in the left hemisphere were associated with motor impairment on the right side as well as language impairments. We were accurately able to predict diagnosis based purely on perfusion. Reliable detection (all p < 0.001) of aphasia (74.7% accuracy or ACC, 86.1% specificity or SP, 56.8% sensitivity or SN), left upper motor (69.3% ACC, 87.9% SP, 42% SN), right upper motor (74.6% ACC, 84.4% SP, 57.3% SN), left lower (68.9% ACC, 87.5% SP, 43.7% SN) and right lower (71.2% ACC, 87.5% SP, 51.1% SN) impairments were accomplished. Conclusion: We describe a reliable automated pCT method to predict neurological deficit in acute stroke patients. The methodology may be useful in patients in who neurological assessment is not possible (e.g. unconscious or intubated patients) or assessment may be at risk of observer bias (e.g. in clinical trials).