Search Results (124)

This comparative cross-sectional study simultaneously investigated the dual health burden of body mass index (BMI) and common mental disorders (CMDs) driven by occupational stressors in two stepwise regression models. By classifying stress exposure into three clinically relevant tiers (low, moderate, and severe) in two distinctive populations—a hospital and a manufacturing company—we used the validated SDS-30 and SRQ-20 instruments. The robust multiple regression models uncovered a highly nuanced landscape of employee well-being that highlights the context-dependent nature of psychosocial hazards. The most compelling findings emerged from the interaction analyses, which demonstrated that the physical and mental consequences of severe stress do not impact the workforce uniformly. Regarding mental health, severe occupational stress proved to be a potent catalyst for CMD symptoms, but this psychological toll was significantly magnified within the hospital sector relative to the manufacturing environment. An opposite, yet equally context-dependent, pattern emerged regarding physical health. In the main-effects-adjusted model, the severity of occupational stressors did not demonstrate a statistically significant linear association with an overall increase in BMI. However, the interaction model revealed a hidden vulnerability: employees in operational field roles who report severe stress are highly susceptible to severe BMI increases compared with admin personnel. While administrative staff may face sedentary risks, field workers under severe stress likely endure higher physiological allostatic load, erratic shift patterns that disrupt circadian metabolic rhythms, and potentially poorer dietary coping mechanisms during active labor. This combination of physical exhaustion and severe psychological tension severely disrupts metabolic homeostasis, forcing the redistribution of adipose tissue and driving the observed BMI spike. Full article

Chronic stress is a time-dependent condition characterized by sustained dysregulation across neural, autonomic, and endocrine systems, with important consequences for both health and socioeconomic outcomes. Unlike acute stress, which is typically characterized by short-lived physiological activation, chronic stress reflects an accumulated allostatic load and a longer-term recalibration of stress response systems. Recent advances in physiological sensing and artificial intelligence (AI) have supported the development of computational approaches for chronic stress detection using electroencephalography (EEG), heart rate variability (HRV), photoplethysmography (PPG), electrodermal activity (EDA), and wearable multimodal platforms. This narrative review examines current AI-based studies through three main inferential paradigms: resting baseline dysregulation, longitudinal physiological monitoring, and reactivity-based inference. Across modalities, classical machine learning (ML) methods, particularly support vector machines (SVMs) and tree-based ensembles, remain the most commonly used approaches, largely because available datasets are small and most pipelines still depend on engineered features. Deep learning (DL) methods are beginning to emerge, but their use remains constrained by the lack of large, standardized, longitudinal datasets specifically designed for chronic stress research. Major challenges include ambiguity in stress labeling, limited longitudinal validation, circadian confounding, inter-individual variability, and small cohort sizes. Future progress will depend on standardized datasets, biologically grounded multimodal integration, hybrid baseline-reactivity modeling, adaptive personalization, and more interpretable AI systems. Greater emphasis is also needed on clinical relevance and generalizability if AI-based chronic stress monitoring is to move beyond experimental settings. Full article

Physiological dysregulation arising from chronic stress is a key mechanism linking psychosocial factors to long-term health outcomes, yet early identification typically relies on invasive or resource-intensive measurements. This study evaluates whether high-dimensional psychometric survey data can support scalable, non-invasive screening for latent physiological dysregulation. Using longitudinal data from the Midlife in the United States (MIDUS) Waves 2 and 3, we develop a screening-oriented modeling framework that separates longitudinal risk estimation from deployable screening model construction. Physiological targets are defined across inflammatory, metabolic, and neuroendocrine domains using three canonical allostatic load formulations. A teacher–ranking–pruning–student pipeline combines stable feature ranking, parsimony-driven dimensionality reduction, and knowledge distillation. Predictor dimensionality is reduced by more than an order of magnitude without loss of screening performance. Distilled student models consistently outperform linear, tree-based, and direct neural baselines, achieving area under the receiver operating characteristic curve values up to approximately 0.78 and substantial precision–recall lift over baseline prevalence. Longitudinal information is exploited during model development but not required at inference, enabling deployment using psychometric data alone. These findings demonstrate the feasibility of non-invasive screening for latent physiological dysregulation and provide a generalizable framework for translating longitudinal cohort data into deployable population health tools. Full article

Background and Objectives: Burnout is highly prevalent among emergency and acute care healthcare workers (HCWs), yet biological correlates remain debated because candidate biomarkers are strongly shaped by circadian timing, shift work, sleep loss, and overlapping affective symptoms. We mapped post-2018 evidence of biological biomarkers assessed alongside validated burnout measures in emergency department (ED), emergency medical services (EMS), and related acute care settings. Specifically, we asked whether reproducible biological correlates of burnout can be identified in emergency and acute-care healthcare workers when biomarker endpoint class and sampling context are systematically considered. Materials and Methods: We conducted a systematic scoping review with evidence mapping (PRISMA-ScR). PubMed/MEDLINE and the MDPI platform were searched for English-language studies published from 2018 onward (through January 2026). Eligible quantitative studies enrolled ED/EMS or acute care HCWs, assessed burnout using validated instruments, and reported at least one biological biomarker. Evidence was charted by biomarker domain and endpoint class (basal measures, stress reactivity paradigms, and chronic indices such as hair-based markers). Results: Overall, 19 studies were included in mapping/synthesis. Biomarker selection clustered around the hypothalamic–pituitary–adrenal axis (cortisol; n = 10/19), with fewer studies focused on autonomic function (heart rate variability; n = 2/19) and immune–inflammatory markers (n = 2/19), and single-study coverage for oxidative stress (n = 1/19), cardiometabolic candidates (n = 1/19), cellular aging (n = 1/19), neuroglial/multi-system candidates (n = 1/19), and feasibility-oriented multi-marker designs (n = 1/19). Reported associations with burnout were heterogeneous in direction and magnitude, but were more interpretable when endpoint class, timing anchors, and shift/sleep-related covariates were explicitly reported. Rates of confounder adjustment were low across studies (e.g., only 3/19 reported multivariable adjustment, and none systematically measured sleep or circadian factors), substantially limiting interpretability. Conclusions: The 2018+ literature does not support a single reproducible biomarker for burnout in emergency and acute care workforces. Evidence instead suggests multi-system dysregulation that is highly sensitive to endpoint class, sampling timing, and contextual confounding. Future studies should prioritize timing-anchored repeated-measures protocols across shift and recovery windows, jointly model sleep/circadian factors and depressive symptoms, and evaluate multi-marker panels and intervention responsiveness. Full article

Background: Chronic stress is associated with dysregulation of the body’s allostatic systems, contributing to increased allostatic load (AL) and adverse metabolic outcomes. Regular physical activity (PA) is considered a key protective factor that may attenuate AL by enhancing adaptive stress responses and supporting metabolic health. This study examined the differences between PA, primary mediators of AL, and metabolic risk markers in apparently healthy adults in Germany. Methods: Forty-six adults (18–45 years) were categorized into a moderate intensity (regular PA: ≥150 min a week vs. non-regular PA: ≤150 min a week) group according to current PA recommendations. Primary AL mediators were quantified by cortisol (μg/12 h), epinephrine (μg/12 h), norepinephrine (μg/12 h), and dehydroepiandrosterone sulfate (DHEA-S: μg/mL). Group differences in primary AL mediators and metabolic risk markers were examined using the Mann–Whitney U test. Results: A significant group difference was observed for cortisol levels, with higher values in the regular PA group (p = 0.01), with a moderate negative effect size of r = −0.38. No statistically significant differences (p > 0.05) were found between groups for epinephrine, norepinephrine, DHEA-S, or metabolic risk markers, including triglycerides, blood pressure, body mass index (BMI), and high-density lipoprotein cholesterol (HDL-C). Conclusions: The findings suggest that regular PA may be associated with altered stress-regulatory activity, as reflected by differences in cortisol. While no statistically significant group differences were observed for metabolic risk markers, descriptive patterns indicate more favorable lipid profiles and potential variation in primary AL mediators at higher PA levels. Given the exploratory nature of the analyses and the small and unequal group sizes, these findings should be interpreted with caution and warrant confirmation in future studies with larger and more balanced samples. Full article

Lung cancer is the leading cause of cancer-related mortality worldwide. This editorial accompanies the Special Issue “Lung Cancer: From Mechanisms of Action and Risk Factors in Disease Onset to Management” published in Cancers (MDPI), and introduces the twenty-one research and review articles included in the collection. The contributions span a wide spectrum of topics, from risk factors such as allostatic load and telomere biology, to molecular biomarkers including DNA methylation and serum glycopeptides, to advances in low-dose CT screening and the management of incidental findings, to targeted therapy, immunotherapy, surgical techniques, and health economics. Together, the papers highlight the multifactorial and clinically complex nature of lung cancer, and reinforce the importance of integrated, evidence-based strategies to reduce its global burden. Full article

Background: Chronic pain, opioid use, and mental health disorders frequently co-occur in older adults, forming a complex and mutually reinforcing triad. Neurobiological ageing processes—such as neuroinflammation, dopaminergic decline, and impaired top-down regulation—may increase vulnerability to maladaptive coping strategies, including opioid misuse. This review aims to integrate neurobiological, affective, and clinical evidence to propose a unified neuropsychiatric framework for understanding the intersection between chronic pain, emotional distress, and opioid vulnerability in later life, while highlighting implications for integrated treatment and opioid stewardship. Methods: This structured narrative review synthesised interdisciplinary evidence from neuroscience, geriatric psychiatry, and pain medicine. The literature was thematically organised to examine shared neurobiological and psychosocial mechanisms underlying chronic pain, affective disorders, and opioid use disorder (OUD) in older adults, with attention to treatment strategies and stewardship principles. Results: Converging evidence suggests a neuroprogressive continuum linking chronic pain, emotional distress, opioid misuse, and cognitive decline. Key mechanisms include frontolimbic dysfunction, impaired reward processing, and chronic allostatic load. Therapeutic approaches that integrate analgesia with emotional regulation—such as buprenorphine, serotonin–noradrenaline reuptake inhibitors (SNRIs), and multimodal tapering strategies—may offer neuroprotective benefits. Effective opioid stewardship appears to require integrated functional, cognitive, and affective monitoring. Conclusions: Pain management in older adults may benefit from moving beyond symptom-focused approaches toward a neuropsychiatric model of care aimed at preserving homeostatic balance across sensory, emotional, and motivational domains. Within this framework, opioid therapy can be conceptualised as a potential means of functional and neuroaffective restoration, rather than solely as a strategy for risk reduction. Full article

South Asian immigrants in the United States face disproportionate cardiovascular disease (CVD) risks, rooted in multidimensional trauma stemming from immigration stress, sociocultural stigma, and systemic discrimination. This paper situates these health disparities within a broader public mental health crisis, examining the intricate relationship between chronic psychological stress, intergenerational trauma, and CVD outcomes. Applying theoretical frameworks such as intersectionality and allostatic load, we explore how cumulative biopsychosocial consequences contribute to the co-morbidity of CVD and mental health disorders in South Asian communities. The study highlights SAWC-Boston’s community-based public mental health intervention, which employs culturally grounded, trauma-informed strategies to address these complex health challenges. This intervention serves as a model for addressing health disparities through community-centered approaches. Full article

Background: Host physiological factors may influence immune response, treatment tolerance, and survival during immune checkpoint inhibitor (ICI) therapy. Allostatic load (AL) summarizes cumulative physiological dysregulation across multiple biological systems. We evaluated whether pre-treatment AL is associated with immune-related toxicity and clinical outcomes among patients with advanced melanoma receiving ICIs. Methods: We analyzed 399 patients with melanoma treated with ICIs at the University of Virginia Cancer Center (2013–2025). AL was derived from routinely collected clinical laboratory biomarkers measured prior to treatment initiation. Multinominal logistic and Cox regression models assessed associations between AL and immune-related adverse events (irAEs), treatment response, disease progression, and overall survival (OS), adjusting for demographic, clinical, and treatment factors. Results: The mean AL score was 4.43. Each 1-unit increase in AL was associated with higher odds of grade ≥ 2 toxicity (adjusted odds ratio [OR] = 1.30; 95% confidence interval [CI]: 1.08–1.57). Among patients who developed irAEs, higher AL was associated with poorer treatment response (adjusted OR = 1.24; 95% CI: 1.01–1.54) and increased risk of disease progression (adjusted hazard ratio [HR] = 1.14; 95% CI: 0.98–1.33). Higher AL was also associated with shorter OS, with a 26% higher mortality risk per 1-unit increase in AL (adjusted HR = 1.26; 95% CI: 1.14–1.39). Conclusions: Higher pre-treatment AL was associated with increased immune-related toxicity and poorer survival in melanoma patients treated with ICIs. AL represents a feasible pre-treatment marker of host physiological vulnerability that may complement existing clinical predictors. Prospective studies are needed to validate these findings and assess clinical utility. Full article

The human microbiome is often presented as “the next genetics,” with the expectation that microbial profiles will explain complex diseases and yield new therapies. Yet for most conditions, it remains unclear whether microbiome changes act as causal drivers or primarily mirror underlying host biology and pathology. In this narrative review, we argue that microbiome causality is frequently overstated relative to the roles of host genetics and the environment, and we explore the implications for molecular pathology. We outline a simple framework in which the microbiome can act as (i) a primary driver, (ii) a conditional mediator or effect modifier or (iii) an association biomarker that mainly reflects upstream processes. We then use marital and household studies as natural experiments to test whether chronic diseases track more strongly with a shared microbiome or with a shared lifestyle and host susceptibility. Across metabolic, inflammatory, neurodegenerative and ageing-related outcomes, spouses show only low to modest disease concordance, which is difficult to reconcile with a universally strong, transmissible microbiome causality. Adult microbiomes instead appear mostly host-constrained and context-dependent, acting more as destabilisers of homeostasis and amplifiers of allostatic load than as independent disease-causing factors. For molecular pathology, this suggests that microbiome features are often most informative as biomarkers integrated alongside host genomics, immune context and histopathology, rather than as standalone targets. Study designs and diagnostic workflows should therefore jointly model the host genome, environment, behaviour and microbiome within broader systems medicine frameworks. Full article

Severe emotional stress constitutes a significant public-health concern associated with negative health outcomes. Although the clinical effects are well acknowledged, the specific biological mechanisms that translate emotional suffering into systemic disease remain incompletely understood. Psychological stress activates the sympathetic nervous system and hypothalamic–pituitary–adrenal axis, which directly target mitochondria and alter their bioenergetic and redox capacity. For this reason, this narrative review proposes that mitochondria serve as the primary subcellular link in the mind–body connection, as they play a pivotal role in converting neuroendocrine signals into cellular dysfunction. In particular, we focus on the concept of mitochondrial allostatic load (MALT), a framework explaining how the progressive decline in mitochondrial functions, from their initial adaptive roles in energy production, reactive oxygen species signaling, and calcium regulation, to being sources of inflammation and systemic damage, occurs when stress exceeds regulatory limits. We also, discuss how this transition turns mitochondria from adaptive responders into drivers of multi-organ disease. In subsequent sections, we examine diagnostic potentials related to MALT, including the use of biomarkers, such as growth differentiation factor 15, cell-free mitochondrial desoxyribonucleic acid, and functional respirometry. Furthermore, we evaluate mitochondria-targeted therapeutic strategies, encompassing pharmacological compounds, such as mitoquinone mesylate, Skulachev ions, and elamipretide, alongside lifestyle and psychological interventions. Here, we aim to translate MALT biology into clinical applications, positioning mitochondrial health as a target for preventing and treating stress-related disorders. We propose that MALT may serve as a quantifiable bridge between emotional stress and somatic disease, enabling future precision medicine strategies integrating mitochondrial care. Full article

Allostatic load is a physiological measure of chronic stress, and stress is implicated in disrupting appetite regulation. Individuals with obesity and type 2 diabetes have higher allostatic load compared to lean counterparts. However, whether allostatic load differs across prediabetes phenotypes and relates to appetite is unknown. Purpose: Test whether prediabetes phenotypes differ in allostatic load in relation to altered appetite regulation. Methods: Individuals with obesity were recruited, and prediabetes was determined using American Diabetes Association (ADA) criteria (75 g OGTT) for this cross-sectional study. After an overnight fast, appetite hormones (ghrelin and PYY), insulin, and glucose were measured every 30 min up to 120 min of the OGTT. Perception of hunger and fullness as well as desire for sweet and fatty foods were assessed using a visual analog scale. Allostatic load was calculated from physiologic markers. Aerobic fitness (VO₂max), body composition (DXA), clinical labs, and quality-of-life questionnaires were also collected. Results: Participants with impaired fasting glucose (IFG) + impaired glucose tolerance (IGT) had a higher allostatic load, obesity, and insulin resistance compared with IFG or IGT (all p < 0.05), independent of fitness. IFG + IGT also had lower fasting ghrelin (p < 0.05) and no difference in fasting PYY. Hunger, fullness, and sweet ratings were comparable across groups, but fatty food ratings tended to be higher in IFG + IGT than NGT. Conclusions: Allostatic load was associated with altered fasting ghrelin levels in individuals with IFG + IGT, along with elevated body weight and insulin resistance. These findings suggest stress is a potential mechanism underlying appetite dysregulation in different forms of prediabetes. Full article

Exercise acts as a physiological stimulus, requiring precise coordination among endocrine, microbial, and mitochondrial systems to maintain metabolic stability through allostatic regulation. The goal of the article is to integrate multidisciplinary evidence to characterize the thyroid–microbiome–mitochondrial axis as a key regulator of the allostatic state in athletic physiological response. During acute, chronic, and overload training phases, the thyroid–microbiome–mitochondrial axis operates bidirectionally, coupling microbial signaling with endocrine and mitochondrial networks to mediate metabolic response to exercise. This response shows interindividual variability driven by sex, age, genetics, and nutritional status, shaping the boundaries between adaptive efficiency and allostatic overload. Microbial metabolites, such as short-chain fatty acids (SCFA) and secondary bile acids, modulate deiodinase activity, bile acid recycling, and mitochondrial biogenesis through AMPK–SIRT1–PGC1α signaling, optimizing substrate use and thermogenic capacity. Thyroid hormones reciprocally regulate gut motility, luminal pH, and bile secretion, maintaining microbial diversity and mineral absorption. Under excessive training load, caloric restriction, or inadequate recovery, this network becomes transiently unbalanced: SCFA synthesis decreases, D3 activity increases, and a reversible low-T₃/high-rT₃ pattern emerges, resembling early Hashimoto- or Graves-like responses. Selenium-, zinc-, and iron-dependent enzymes form the redox link between microbial metabolism, thyroid control, and mitochondrial defense. In conclusion, the thyroid–microbiome–mitochondrial axis provides the physiological basis for the allostatic state, a reversible phase of dynamic recalibration that integrates training, nutrition, environmental stress, and circadian cues to sustain thyroid activity, mitochondrial efficiency, and microbial balance. This integrative perspective supports precision interventions to optimize recovery and performance in athletes. Full article

This study examined the effect of competition stress on recovery time in female collegiate soccer players. Thirty NCAA Division I athletes were monitored over 35 consecutive days using Polar Team Pro wearable devices, which captured exercise duration, distance covered, energy expenditure, sprint count, speed, heart rate, training load, and recovery duration. Data were collected across 20 practices and 7 competitions, totaling 845 observations. Linear regression was used to assess whether formal competition independently influenced recovery duration, controlling for time of day and workload variables. Athletes averaged 20.1 ± 1.1 years of age. Across all sessions, the mean exercise duration was 59.5 ± 38.7 min, with an average distance of 2.6 ± 2.1 km, and energy expenditure of 387.2 ± 283.5 kcals. Recovery duration was significantly longer after competition (51.3 ± 59.6 h) compared to practice (13.0 ± 15.8 h, p < 0.001). The regression model indicated that formal competition predicted an additional 51 h of recovery time (β = 50.540; p < 0.001), independent of physical workload. Recovery following formal competition is significantly prolonged, holding multiple components of workload constant. These findings offer novel insights into female athlete recovery and highlight the importance of sex-specific approaches in sports science. Full article

Episodic memory is contextual memory linking temporal, spatial, emotional, and self-referential contexts. In this review, we placed particular emphasis on the emotional context because of its nexus with chronic pain effects. Psychological (e.g., depression, anxiety, stress, & loneliness) and medical (neurological, cardiovascular, chronic pain) conditions can adversely affect episodic memory. Furthermore, individual differences in emotional/affective experience as represented by trait personality variables (e.g., conscientiousness, openness to experience, introversion, extraversion, and neuroticism) can either facilitate or harm episodic memory performance. This paper aims to review episodic memory, its associated attention and executive function co-processes, the modulation of memory function as a result of affective experiences as represented by trait personality, and how coping mechanisms can serve as a buffer to maintain episodic memory function using Chiari malformation Type I (a chronic pain syndrome) as a model. Finally, allostatic load and pharmacological effects of pain medications on episodic memory are discussed. Full article