Sleep disorders represent multifaceted pathophysiological conditions beyond simple sleep duration or quality disruptions. They are frequently associated with neuropsychiatric symptoms, cognitive decline, and systemic health deterioration. Among them, insomnia and obstructive sleep apnea (OSA) are highly prevalent and chronic, with established links to reduced quality of life and an increased risk of neurodegenerative diseases. This review summarized recent findings from neuroimaging studies that used quantitative cerebral blood flow (CBF) techniques, including arterial spin labeling (ASL) and single-photon emission computed tomography (SPECT), to examine functional brain changes associated with these disorders. Both insomnia and OSA consistently showed perfusion abnormalities in regions such as the prefrontal cortex, cingulate cortex, and hippocampus—areas that are critical for the sleep-arousal cycle, emotional regulation, and cognitive control. These alterations may reflect underlying mechanisms that include hemodynamic dysregulation, impaired metabolic regulation, and reduced connectivity in large-scale brain networks.Collectively, the evidence suggested that sleep disorders should be understood not merely as disturbances of sleep architecture, but as conditions involving cerebral hemodynamic dysregulation. Brain perfusion metrics thus hold clinical promise as sensitive biomarkers for early diagnosis, risk stratification, and treatment monitoring in sleep disorders and support the development of precision-guided interventions based on quantitative neuroimaging.

Objectives: Obesity is increasingly recognized not merely as excess body weight, but as a chronic condition involving metabolic dysregulation and neurobiological vulnerability. In particular, altered brain responsiveness to sensory food cues has emerged as a key mechanism underlying the development and persistence of obesity. Recent neuropsychiatric perspectives emphasize dysfunctions in reward circuits and addictive-like eating behaviors. This review aims to comprehensively synthesize task-based functional magnetic resonance imaging (fMRI) studies to examine brain responsivity in individuals with obesity or at high risk of weight gain. Methods: We systematically reviewed 30 task-based fMRI studies using olfactory and/or gustatory cues. Studies were categorized by stimulus type, participant group, and experimental condition to compare neural responses. Results: Across studies, key patterns included hyperactivation of reward circuits in response to high-calorie stimuli, impaired modulation of neural activity across hunger and satiety states, and exaggerated or blunted affective and motivational responses to sensory stimuli. These neural differences appeared to interact with metabolic condition, physiological state, emotional traits, and genetic predispositions, suggesting their potential utility as neurobiological markers of obesity-related eating behaviors. Conclusions This review underscores the relevance of sensory-driven paradigms—beyond traditional visually cued tasks—in capturing the neural basis of maladaptive eating. By elucidating the links between sensory processing and neural reward circuits, this review highlights the utility of olfactory and gustatory fMRI paradigms in refining our understanding of obesity. These insights may contribute to early identification of high-risk individuals and inform the development of neurobiologically informed, personalized intervention strategies.

Public health and safety professionals, including firefighters, police officers, and emergency medical personnel, serve as critical pillars of public safety and societal well-being. These professions require navigating environments characterized by ‘brittleness’, ‘anxiety’, ‘nonlinearity’, and ‘incomprehensibility’—conditions that lead to chronic physical and psychological stress. This stress significantly elevates the risk of mental health disorders such as post-traumatic stress disorder, anxiety disorders, mood disorders, and sleep disturbances, while also increasing the likelihood of human errors driven by cognitive lapses. Such challenges extend beyond individual health, undermining organizational efficiency and ultimately jeopardizing public safety and societal welfare. Existing mental health management systems predominantly depend on reactive interventions, which are insufficient to meet the dynamic and unpredictable demands of high-risk occupational environments. As a proactive alternative, this paper introduces the concept of ‘Mind Vital Signs,’ an innovative framework that expands the traditional concept of vital signs into the mental health domain. Mind Vital Signs integrates physiological indicators—including heart rate variability, physical activity, respiratory rates, and sleep patterns—with psychological and behavioral data such as ecological momentary assessments and life logs. By employing real-time monitoring and advanced analytics, this multidimensional system facilitates early detection of mental health risks and supports targeted and timely preventive interventions. The implementation of Mind Vital Signs not only bolsters individual resilience and organizational stability but also enhances operational efficiency and strengthens public safety and societal well-being. Future research should prioritize clinical validation and policy development to ensure the effective integration and scalability of Mind Vital Signs in high-risk occupational settings.

Objectives: Recent advances in brain age prediction models reveal accelerated brain aging in major depressive disorder (MDD) patients. This review investigates the complex relationship between brain aging and biological age gap (BAG) in MDD, emphasizing the influences of clinical characteristics, treatment responses, and various neuroimaging techniques on this dynamic interplay. Methods: A systematic review of the existing literature was conducted, focusing on 18 studies that analyze brain aging patterns in MDD patients. Key factors such as age, clinical features, and lifestyle choices were examined to assess their impact on BAG and the overall neurobiological health of individuals with MDD. Results: The findings indicate that MDD patients frequently experience accelerated brain aging, particularly in elderly populations, with BAG serving as a valuable biomarker for assessing biological aging rates. The review highlights the urgent need for more granular approaches, considering variables such as age, gender, and socioeconomic status. Specific local brain aging patterns were observed in regions related to emotional regulation, suggesting that localized BAG changes may provide critical insights into the pathophysiology of MDD and its neurobiological underpinnings. Conclusions BAG is a significant biomarker for evaluating accelerated brain aging in MDD, informing personalized treatment strategies. Future research should incorporate diverse clinical characteristics and advanced neuroimaging techniques in representative samples to enhance the clinical applicability of BAG and deepen the understanding of its role in depression and biological aging.

Public health and safety professionals, including firefighters, police officers, and emergency medical personnel, serve as critical pillars of public safety and societal well-being. These professions require navigating environments characterized by ‘brittleness’, ‘anxiety’, ‘nonlinearity’, and ‘incomprehensibility’—conditions that lead to chronic physical and psychological stress. This stress significantly elevates the risk of mental health disorders such as post-traumatic stress disorder, anxiety disorders, mood disorders, and sleep disturbances, while also increasing the likelihood of human errors driven by cognitive lapses. Such challenges extend beyond individual health, undermining organizational efficiency and ultimately jeopardizing public safety and societal welfare. Existing mental health management systems predominantly depend on reactive interventions, which are insufficient to meet the dynamic and unpredictable demands of high-risk occupational environments. As a proactive alternative, this paper introduces the concept of ‘Mind Vital Signs,’ an innovative framework that expands the traditional concept of vital signs into the mental health domain. Mind Vital Signs integrates physiological indicators—including heart rate variability, physical activity, respiratory rates, and sleep patterns—with psychological and behavioral data such as ecological momentary assessments and life logs. By employing real-time monitoring and advanced analytics, this multidimensional system facilitates early detection of mental health risks and supports targeted and timely preventive interventions. The implementation of Mind Vital Signs not only bolsters individual resilience and organizational stability but also enhances operational efficiency and strengthens public safety and societal well-being. Future research should prioritize clinical validation and policy development to ensure the effective integration and scalability of Mind Vital Signs in high-risk occupational settings.

Public health and safety professionals, including firefighters, police officers, and emergency medical personnel, serve as critical pillars of public safety and societal well-being. These professions require navigating environments characterized by ‘brittleness’, ‘anxiety’, ‘nonlinearity’, and ‘incomprehensibility’—conditions that lead to chronic physical and psychological stress. This stress significantly elevates the risk of mental health disorders such as post-traumatic stress disorder, anxiety disorders, mood disorders, and sleep disturbances, while also increasing the likelihood of human errors driven by cognitive lapses. Such challenges extend beyond individual health, undermining organizational efficiency and ultimately jeopardizing public safety and societal welfare. Existing mental health management systems predominantly depend on reactive interventions, which are insufficient to meet the dynamic and unpredictable demands of high-risk occupational environments. As a proactive alternative, this paper introduces the concept of ‘Mind Vital Signs,’ an innovative framework that expands the traditional concept of vital signs into the mental health domain. Mind Vital Signs integrates physiological indicators—including heart rate variability, physical activity, respiratory rates, and sleep patterns—with psychological and behavioral data such as ecological momentary assessments and life logs. By employing real-time monitoring and advanced analytics, this multidimensional system facilitates early detection of mental health risks and supports targeted and timely preventive interventions. The implementation of Mind Vital Signs not only bolsters individual resilience and organizational stability but also enhances operational efficiency and strengthens public safety and societal well-being. Future research should prioritize clinical validation and policy development to ensure the effective integration and scalability of Mind Vital Signs in high-risk occupational settings.

Objectives: Recent advances in brain age prediction models reveal accelerated brain aging in major depressive disorder (MDD) patients. This review investigates the complex relationship between brain aging and biological age gap (BAG) in MDD, emphasizing the influences of clinical characteristics, treatment responses, and various neuroimaging techniques on this dynamic interplay. Methods: A systematic review of the existing literature was conducted, focusing on 18 studies that analyze brain aging patterns in MDD patients. Key factors such as age, clinical features, and lifestyle choices were examined to assess their impact on BAG and the overall neurobiological health of individuals with MDD. Results: The findings indicate that MDD patients frequently experience accelerated brain aging, particularly in elderly populations, with BAG serving as a valuable biomarker for assessing biological aging rates. The review highlights the urgent need for more granular approaches, considering variables such as age, gender, and socioeconomic status. Specific local brain aging patterns were observed in regions related to emotional regulation, suggesting that localized BAG changes may provide critical insights into the pathophysiology of MDD and its neurobiological underpinnings. Conclusions BAG is a significant biomarker for evaluating accelerated brain aging in MDD, informing personalized treatment strategies. Future research should incorporate diverse clinical characteristics and advanced neuroimaging techniques in representative samples to enhance the clinical applicability of BAG and deepen the understanding of its role in depression and biological aging.

Public health and safety professionals, including firefighters, police officers, and emergency medical personnel, serve as critical pillars of public safety and societal well-being. These professions require navigating environments characterized by ‘brittleness’, ‘anxiety’, ‘nonlinearity’, and ‘incomprehensibility’—conditions that lead to chronic physical and psychological stress. This stress significantly elevates the risk of mental health disorders such as post-traumatic stress disorder, anxiety disorders, mood disorders, and sleep disturbances, while also increasing the likelihood of human errors driven by cognitive lapses. Such challenges extend beyond individual health, undermining organizational efficiency and ultimately jeopardizing public safety and societal welfare. Existing mental health management systems predominantly depend on reactive interventions, which are insufficient to meet the dynamic and unpredictable demands of high-risk occupational environments. As a proactive alternative, this paper introduces the concept of ‘Mind Vital Signs,’ an innovative framework that expands the traditional concept of vital signs into the mental health domain. Mind Vital Signs integrates physiological indicators—including heart rate variability, physical activity, respiratory rates, and sleep patterns—with psychological and behavioral data such as ecological momentary assessments and life logs. By employing real-time monitoring and advanced analytics, this multidimensional system facilitates early detection of mental health risks and supports targeted and timely preventive interventions. The implementation of Mind Vital Signs not only bolsters individual resilience and organizational stability but also enhances operational efficiency and strengthens public safety and societal well-being. Future research should prioritize clinical validation and policy development to ensure the effective integration and scalability of Mind Vital Signs in high-risk occupational settings.

Public health and safety professionals, including firefighters, police officers, and emergency medical personnel, serve as critical pillars of public safety and societal well-being. These professions require navigating environments characterized by ‘brittleness’, ‘anxiety’, ‘nonlinearity’, and ‘incomprehensibility’—conditions that lead to chronic physical and psychological stress. This stress significantly elevates the risk of mental health disorders such as post-traumatic stress disorder, anxiety disorders, mood disorders, and sleep disturbances, while also increasing the likelihood of human errors driven by cognitive lapses. Such challenges extend beyond individual health, undermining organizational efficiency and ultimately jeopardizing public safety and societal welfare. Existing mental health management systems predominantly depend on reactive interventions, which are insufficient to meet the dynamic and unpredictable demands of high-risk occupational environments. As a proactive alternative, this paper introduces the concept of ‘Mind Vital Signs,’ an innovative framework that expands the traditional concept of vital signs into the mental health domain. Mind Vital Signs integrates physiological indicators—including heart rate variability, physical activity, respiratory rates, and sleep patterns—with psychological and behavioral data such as ecological momentary assessments and life logs. By employing real-time monitoring and advanced analytics, this multidimensional system facilitates early detection of mental health risks and supports targeted and timely preventive interventions. The implementation of Mind Vital Signs not only bolsters individual resilience and organizational stability but also enhances operational efficiency and strengthens public safety and societal well-being. Future research should prioritize clinical validation and policy development to ensure the effective integration and scalability of Mind Vital Signs in high-risk occupational settings.

Objectives: Recent advances in brain age prediction models reveal accelerated brain aging in major depressive disorder (MDD) patients. This review investigates the complex relationship between brain aging and biological age gap (BAG) in MDD, emphasizing the influences of clinical characteristics, treatment responses, and various neuroimaging techniques on this dynamic interplay. Methods: A systematic review of the existing literature was conducted, focusing on 18 studies that analyze brain aging patterns in MDD patients. Key factors such as age, clinical features, and lifestyle choices were examined to assess their impact on BAG and the overall neurobiological health of individuals with MDD. Results: The findings indicate that MDD patients frequently experience accelerated brain aging, particularly in elderly populations, with BAG serving as a valuable biomarker for assessing biological aging rates. The review highlights the urgent need for more granular approaches, considering variables such as age, gender, and socioeconomic status. Specific local brain aging patterns were observed in regions related to emotional regulation, suggesting that localized BAG changes may provide critical insights into the pathophysiology of MDD and its neurobiological underpinnings. Conclusions BAG is a significant biomarker for evaluating accelerated brain aging in MDD, informing personalized treatment strategies. Future research should incorporate diverse clinical characteristics and advanced neuroimaging techniques in representative samples to enhance the clinical applicability of BAG and deepen the understanding of its role in depression and biological aging.