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Objective: Physical exercise may increase brain volume and cortical thickness in late adulthood. However, few studies have examined the possibility for exercise to influence brain morphology in women treated for breast cancer. We conducted a nested sub-study within a randomized clinical trial to examine whether 6 months of moderate-intensity aerobic exercise in postmenopausal women with early-stage breast cancer influences brain morphology., Methods: We included twenty-eight postmenopausal women newly diagnosed with Stage 0-IIIa breast cancer (M age = 62.96 ± 5.40) who were randomized to either 45-60 min of supervised aerobic exercise 3 days/week ( n = 16) or usual care ( n = 12). Before beginning aromatase inhibitor aromatase inhibitor therapy, and the exercise intervention, and again at 6-month follow-up, volumetric and cortical thickness measures were derived from magnetic resonance imaging scans., Results: There were no significant intervention effects on brain volume and cortical thickness. However, greater average exercise intensity (%) during the intervention was associated with greater post-intervention cortical volume, mean cortical thickness, precentral gyrus thickness, and superior parietal thickness (all p < 0.05). Finally, total supervised exercise time was associated with higher precentral gyrus thickness after the intervention ( p = 0.042, R 2 = 0.263)., Conclusion: The exercise intervention did not significantly affect brain volumes and cortical thickness compared to the control group. However, positive associations were found between exercise intensity and brain morphology changes after the 6-month intervention, indicating that exercise may reduce the vulnerability of the brain to the deleterious effects of breast cancer and its treatment., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Molina-Hidalgo, Wan, Velazquez-Diaz, Huang, Grove, Bender, Gentry, Sereika, Kang, Crisafio and Erickson.)

Introduction: Physical activity (PA) has beneficial effects on brain health and cardiovascular disease (CVD) risk. Yet, we know little about whether PA-induced changes to physiological mediators of CVD risk influence brain health and whether benefits to brain health may also explain PA-induced improvements to CVD risk. This study combines neurobiological and peripheral physiological methods in the context of a randomised clinical trial to better understand the links between exercise, brain health and CVD risk., Methods and Analysis: In this 12-month trial, 130 healthy individuals between the ages of 26 and 58 will be randomly assigned to either: (1) moderate-intensity aerobic PA for 150 min/week or (2) a health information control group. Cardiovascular, neuroimaging and PA measurements will occur for both groups before and after the intervention. Primary outcomes include changes in (1) brain structural areas (ie, hippocampal volume); (2) systolic blood pressure (SBP) responses to functional MRI cognitive stressor tasks and (3) heart rate variability. The main secondary outcomes include changes in (1) brain activity, resting state connectivity, cortical thickness and cortical volume; (2) daily life SBP stress reactivity; (3) negative and positive affect; (4) baroreflex sensitivity; (5) pulse wave velocity; (6) endothelial function and (7) daily life positive and negative affect. Our results are expected to have both mechanistic and public health implications regarding brain-body interactions in the context of cardiovascular health., Ethics and Dissemination: Ethical approval has been obtained from the University of Pittsburgh Institutional Review Board (IRB ID: 19020218). This study will comply with the NIH Data Sharing Policy and Policy on the Dissemination of NIH-Funded Clinical Trial Information and the Clinical Trials Registration and Results Information Submission rule., Trial Registration Number: NCT03841669., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Background: Frailty syndrome (FS) is one of the most common noncommunicable diseases, which is associated with lower physical and mental capacities in older adults. FS diagnosis is mostly focused on biological variables; however, it is likely that this diagnosis could fail owing to the high biological variability in this syndrome. Therefore, artificial intelligence (AI) could be a potential strategy to identify and diagnose this complex and multifactorial geriatric syndrome., Objective: The objective of this scoping review was to analyze the existing scientific evidence on the use of AI for the identification and diagnosis of FS in older adults, as well as to identify which model provides enhanced accuracy, sensitivity, specificity, and area under the curve (AUC)., Methods: A search was conducted using PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) guidelines on various databases: PubMed, Web of Science, Scopus, and Google Scholar. The search strategy followed Population/Problem, Intervention, Comparison, and Outcome (PICO) criteria with the population being older adults; intervention being AI; comparison being compared or not to other diagnostic methods; and outcome being FS with reported sensitivity, specificity, accuracy, or AUC values. The results were synthesized through information extraction and are presented in tables., Results: We identified 26 studies that met the inclusion criteria, 6 of which had a data set over 2000 and 3 with data sets below 100. Machine learning was the most widely used type of AI, employed in 18 studies. Moreover, of the 26 included studies, 9 used clinical data, with clinical histories being the most frequently used data type in this category. The remaining 17 studies used nonclinical data, most frequently involving activity monitoring using an inertial sensor in clinical and nonclinical contexts. Regarding the performance of each AI model, 10 studies achieved a value of precision, sensitivity, specificity, or AUC ≥90., Conclusions: The findings of this scoping review clarify the overall status of recent studies using AI to identify and diagnose FS. Moreover, the findings show that the combined use of AI using clinical data along with nonclinical information such as the kinematics of inertial sensors that monitor activities in a nonclinical context could be an appropriate tool for the identification and diagnosis of FS. Nevertheless, some possible limitations of the evidence included in the review could be small sample sizes, heterogeneity of study designs, and lack of standardization in the AI models and diagnostic criteria used across studies. Future research is needed to validate AI systems with diverse data sources for diagnosing FS. AI should be used as a decision support tool for identifying FS, with data quality and privacy addressed, and the tool should be regularly monitored for performance after being integrated in clinical practice., (©Daniel Velazquez-Diaz, Juan E Arco, Andres Ortiz, Verónica Pérez-Cabezas, David Lucena-Anton, Jose A Moral-Munoz, Alejandro Galán-Mercant. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 20.10.2023.)

Physical activity (PA) in the form of aerobic exercise (AE) preserves and improves neurocognitive function across the lifespan. However, a mechanistic understanding of the pathways by which aerobic exercise impacts brain health is still lacking, particularly with respect to stress-related pathways. One mechanistic hypothesis is that AE improves neurocognitive health in part by modifying circulating levels of stress-related hormones and signaling factors associated with the hypothalamic-pituitary-adrenal (HPA) axis and autonomic nervous system (ANS), as commonly measured by the biomarkers cortisol (CORT) and salivary α-amylase (sAA). Thus, this hypothesis predicts that changes in stress biomarkers, such as CORT and sAA, are possible explanatory pathways mediating the positive effects of AE on neurocognitive health. In the present review article, we provide a summary of available studies examining the possibility that exercise-induced changes to stress biomarkers could partly account for exercise-related improvements in neurocognitive health. Our review indicates that despite the intuitive appeal of this hypothesis, there is insufficient evidence available to conclude that chronic and habitual AE affects neurocognitive health by altering stress biomarker pathways. The cross-sectional nature of the majority of reviewed studies highlights the need for well-controlled studies to adequately test this hypothesis., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Molina-Hidalgo, Stillman, Collins, Velazquez-Diaz, Ripperger, Drake, Gianaros, Marsland and Erickson.)

Public health messaging calls for individuals to be more physically active and less sedentary, yet these lifestyle behaviors have been historically studied independently. Both physical activity (PA) and sedentary behavior (SB) are linked through time-use in a 24-hour day and are related to health outcomes, such as neurocognition. While the benefits of PA on brain health in late adulthood have been well-documented, the influence of SB remains to be understood. The purpose of this paper was to critically review the evolving work on SB and brain health in late adulthood and emphasize key areas of consideration to inform potential research. Overall, the existing literature studying the impact of SB on the components and mechanisms of brain health are mixed and inconclusive, provided largely by cross-sectional and observational work employing a variety of measurement techniques of SB and brain health outcomes. Further, many studies did not conceptually or statistically account for the role of PA in the proposed relationships. Therefore, our understanding of the way in which SB may influence neurocognition in late adulthood is limited. Future efforts should include more prospective longitudinal and randomized clinical trials with intentional methodological approaches to better understand the relationships between SB and the brain in late adulthood, and how these potential links are differentiated from PA., Competing Interests: Declaration of competing interest None., (Copyright © 2023. Published by Elsevier Inc.)