Search Results (93)

Stress is a major factor that threatens the body’s homeostasis or well-being. Excessive stress causes psychological anxiety and tension, which disrupts the balance of the autonomic nervous system that maintains the body’s balance, resulting in hormonal imbalance and brain changes. In this study, we investigated the effects of Withania somnifera (Ashwagandha) extract on depression, neurobehavior, and hippocampal changes in model mice exposed to stress. Using an excessive restraint stress-induced depression model, we measured the behavioral changes and the levels of brain-derived neurotrophic factor (BDNF) and antioxidant genes in five groups: control, stress, low-dose W. somniferous extract (20 mg/kg/day), high-dose W. somniferous extract (40 mg/kg/day), and L-theanine (50 mg/kg/day, positive control). Stressed mice showed poorer performance in the open field and elevated plus maze tests compared with the control group. The impaired performance was restored following W. somniferous extract administration. In addition, W. somniferous extract restored the decreased expression of BDNF in the hippocampus caused by restraint stress, improved the balance of stress hormones (i.e., cortisol, dopamine, and norepinephrine), and also regulated BDNF, inflammatory genes, and antioxidant genes in brain tissue. Therefore, W. somniferous extract can induce antidepressant and anti-stress effects by maintaining brain BDNF expression and preventing hippocampal tissue alterations caused by restraint stress. Full article

Non-pharmacological interventions, such as physical activity and exercise, are essential in managing type 1 diabetes mellitus by improving glycemic control, cardiovascular health and autonomic function. Given the chronic nature and long-term complications associated with type 1 diabetes, strategies beyond pharmacotherapy are essential. This review examines the effects of exercise on heart rate variability, a key indicator of autonomic nervous system activity. A systematic search was conducted in March 2024 across PubMed, Embase, Cochrane and CINAHL databases. Studies evaluating the retrospective or prospective impact of exercise or physical activity on heart rate variability parameters were included. Utilizing best evidence synthesis, the methodological quality of the included studies was evaluated. Seven studies met the inclusion criteria, all of which were rated as methodologically weak. Moderate evidence suggests that exercise may enhance heart rate variability, particularly by increasing parasympathetic activity and improving sympathovagal balance. However, evidence remains limited regarding the optimal type, frequency and intensity of exercise. Exercise appears to support autonomic function in individuals with type 1 diabetes mellitus. Nonetheless, further high-quality research is needed to determine the most effective exercise modalities and to inform evidence-based clinical guidelines. Full article

Background: Reliable and non-invasive methods for assessing welfare in poultry are essential for improving evidence-based welfare monitoring and advancing management practices in commercial production systems. The iris-to-pupil (IP) ratio, previously validated by our group in primates and cattle, reflects autonomic nervous system balance and may serve as a physiological indicator of stress in laying hens. This study evaluated the utility of the IP ratio under field conditions across diverse commercial layer housing systems. Materials and Methods: In total, 296 laying hens (Lohmann Brown, n = 269; White Leghorn, n = 27) were studied across four locations in Canada housed under different systems: Guelph (indoor; pen), Spring Island (outdoor and scratch; organic), Ottawa (outdoor, indoor and scratch; free-range), and Toronto (outdoor and hobby; free-range). High-resolution photographs of the eye were taken under ambient lighting. Light intensity was measured using the light meter app. The IP ratio was calculated using NIH ImageJ software (Version 1.54p). Statistical analysis included one-way ANOVA and linear regression using GraphPad Prism (Version 5). Results: Birds housed outdoors had the highest IP ratios, followed by those in scratch systems, while indoor and pen-housed birds had the lowest IP ratios (p < 0.001). Subgroup analyses of birds in Ottawa and Spring Island farms confirmed significantly higher IP ratios in outdoor environments compared to indoor and scratch systems (p < 0.001). The IP ratio correlated weakly with ambient light intensity (r² = 0.25) and age (r² = 0.05), indicating minimal influence of these variables. Although White Leghorn hens showed lower IP ratios than Lohmann Browns, this difference was confounded by housing type; all White Leghorns were housed in pens. Thus, housing system but not breed was the primary driver of IP variation. Conclusions: The IP ratio is a robust, non-invasive physiological marker of welfare assessment in laying hens, sensitive to housing environment but minimally influenced by light or age. Its potential for integration with digital imaging technologies supports its use in scalable welfare assessment protocols. Full article

The review compares the principles of organization of the brain and immune system, two important organs developed over 500 million years in multicellular organisms, including humans. It summarizes the latest results from research in neurosciences and immunology concerning intercellular communication. While in the brain, intercellular communication is primarily based on exchange of electrical signals, this is not the case in the immune system. The question, therefore, arises as to whether nature developed two entirely different systems of organization. It will be demonstrated that a few basic principles of brain and immune responses are organized in a different way. A majority of intercellular communications, however, such as the formation of synapses, are shown to have many similarities. Both systems are intimately interconnected to protect the body from the1 dangers of the outside and the inside world. During homeostasis, all systems are in regulatory balance. A new hypothesis states that the central systems surrounded by bone, namely the central nervous system (CNS) and the central immune system (CIS), are based on three types of stem cells and function in an open but autonomous way. T cell immune responses to antigens from blood and cerebrospinal fluid protect the system and maintain neuroimmune homeostasis. The newly discovered tunneling nanotubes and extracellular vesicles are postulated to play an important role in crosstalk with already known homeostasis regulators and help in cellular repair and the recycling of biologic material. Three examples are selected to illustrate dysfunctions of homeostasis, namely migraine, multiple sclerosis, and brain cancer. The focus on these different conditions provides deep insights into such neurological and/or immunological malfunctions. Technological advances in neurosciences and immunology can enable neuroimmunomodulation and the development of new treatment possibilities. Full article

The imbalance in the interaction between the autonomic nervous system and the immune system serves as a central mechanism in the onset and progression of cardiovascular diseases. The excessive activation of the sympathetic nervous system and suppression of vagal function contribute to chronic inflammation and cardiac remodeling. Precision medicine, by integrating multidimensional data such as genomics and metabolomics, offers a novel perspective for the personalized design of exercise interventions. This systematic review explores the bidirectional regulatory mechanisms of exercise interventions on the autonomic nervous system–immune axis and examines the potential applications of precision medicine in optimizing exercise prescriptions and clinical translation. Exercise significantly improves cardiovascular function through immunometabolic reprogramming, which includes suppressing sympathetic overactivity, enhancing vagal tone, and modulating the IL-6/IL-10 balance, as well as activating the short-chain fatty acid (SCFA)–Treg axis. Moreover, precision-medicine-driven ACE I/D gene typing provides a basis for selecting tailored exercise prescriptions, thereby significantly enhancing the efficacy of exercise interventions. By leveraging a multi-tiered “neuro–immune–metabolic” regulatory framework, exercise interventions contribute to improved cardiovascular health. The application of precision medicine technology overcomes individual variability constraints, advancing exercise prescription design from generalized recommendations toward personalized and dynamically adaptive strategies. Full article

The gut–brain axis (GBA) refers to the biochemical bidirectional communication between the central nervous system (CNS) and the gastrointestinal tract, linking brain and gut functions. It comprises a complex network of interactions involving the endocrine, immune, autonomic, and enteric nervous systems. The balance of this bidirectional pathway depends on the composition of the gut microbiome and its metabolites. While the causes of neurodegenerative diseases (NDDs) vary, the gut microbiome plays a crucial role in their development and prognosis. NDDs are often associated with an inflammation-related gut microbiome. However, restoring balance to the gut microbiome and reducing inflammation may have therapeutic benefits. In particular, introducing short-chain fatty acid-producing bacteria, key metabolites that support gut homeostasis, can help counteract the inflammatory microbiome. This strong pathological link between the gut and NDDs underscores the gut–brain axis (GBA) as a promising target for therapeutic intervention. This review, by scrutinizing the more recent original research articles published in PubMed (MEDLINE) database, emphasizes the emerging notion that GBA is an equally important pathological marker for neurological movement disorders, particularly in Alzheimer’s disease, Parkinson’s disease, multiple sclerosis, amyotrophic lateral sclerosis, Huntington’s disease and neurotraumatic disorders such as traumatic brain injury and spinal cord injury. Additionally, the GBA presents a promising therapeutic target for managing these diseases. Full article

The intricate brain–heart interaction, essential for physiological balance, is largely governed by the autonomic nervous system (ANS). This bidirectional communication, involving both the sympathetic and parasympathetic branches of the ANS, is critical for maintaining cardiac homeostasis. Dysregulation of the ANS is a significant factor in cardiovascular diseases. Beyond the ANS, higher brain functions, particularly through interoceptive prediction, contribute to this dynamic interplay. The Cav1.3 L-type calcium channel, expressed in both the central nervous system (CNS) and the heart, is crucial for this interaction. Cav1.3, a key regulator of cellular excitability, exhibits genetic variations that are linked to both neurological and cardiac disorders, highlighting its pivotal role in the brain–heart axis. This review aims to delve into the under-explored role of Cav1.3 in brain–heart interaction, specifically examining how it modulates ANS activity and, consequently, the cardiac function. This will illuminate its significant role in the broader context of brain–heart interactions. Full article

The influence of gameplay on autonomic nervous system activity was investigated by comparing electrocardiogram (ECG) data during seated rest and gameplay. A total of 13 participants (6 in the gameplay group and 7 in the control group) were analyzed. RR interval time series (2 Hz) and heart-rate variability (HRV) indices, including mean RR, SDRR, VLF, LF, HF, LF/HF, and HF peak frequency, were extracted from ECG signals over 5 min and 10 min segments. HRV indices were calculated using fast Fourier transform (FFT). The classification was performed using Logistic Regression (LGR), Random Forest (RF), XGBoost (XGB, v2.9.2), One-Class SVM (OCS), Isolation Forest (ILF), and Local Outlier Factor (LOF). A balanced dataset of 5 min and 10 min segments was evaluated using k-fold cross-validation (k = 3, 4, 5). Performance metrics, including recall, F-score, and PR-AUC, were computed for each classifier. Grid search was applied to optimize parameters for LGR, RF, and XGB, while default settings were used for the other classifiers. Among all models, OCS with k = 3 achieved the highest classification accuracy for both 5 min and 10 min data. These findings suggest that machine learning-based classification can effectively distinguish ECG patterns between gameplay and rest. Full article

Chronic kidney disease (CKD) is a progressive pathology characterized by gradual function loss. It is accompanied by complications including cardiovascular disorders. This study involves 4-h electrocardiographic records from the Telemetric and Holter ECG Warehouse (THEW) project database to analyze the dynamics in heart rate variability (HRV) indices of 51 patients with CKD. It proposes three algorithms to process long-term electrocardiography records: QRS complex and R-wave detection, premature ventricular contraction (PVC) identification, and tachograms. PVCs were analyzed with the consideration of the changes occurring before, during, and after hemodialysis, especially during the interdialytic period. The hour with the highest PVCs occurrence was identified and used to assess HRV fluctuations and segmented into 5 min blocks with a 0.77 min overlap, yielding a dynamic HRV vector, one for each of seven HRV indices selected to evaluate autonomic nervous system balance. R-wave and PVC identification resulted in 97.53% and 85.83% positive predictive values, respectively. PVCs’ prevalence and HRV changes’ relationship in 48 h records could relate to cardiovascular risk. The stratification of hemodialysis patients into three distinct PVC patterns (p < 0.001) identified two clinically significant high-risk subgroups: Class 1, indicative of electrical instability, and Class 3, of advanced autonomic dysfunction, demonstrating divergent arrhythmogenic mechanisms with direct implications for risk stratification. Full article

Studies have shown that wearable commercial off-the-shelf sensors, such as accelerometers, inertial measurement units, and heart monitors, can distinguish between individuals with a mild traumatic brain injury (mTBI) and uninjured controls. However, there is no consensus on which metrics derived from wearable sensors are best to use for objective identification of mTBI symptoms. The primary aim of this scoping review was to map the state of knowledge of wearable sensor-based assessments for mTBI, based on previously published research. Data sources included Web of Science and PubMed. Original peer-reviewed articles were selected if mTBI was clinically diagnosed, an uninjured control cohort was included, and data collection used at least one digital sensor worn on the body. After screening 507 articles, 21 studies were included in the analysis. Overall, the studies identified multiple wearables-derived physiological metrics that differ between individuals with mTBI and uninjured controls. Some metrics associated with static balance, walking tasks, and postural changes to initiate an autonomic nervous system response were shown to support diagnosis of mTBI in retrospective studies with acceptable to outstanding accuracy. Further studies are needed to formulate standard protocols, reproduce results in large heterogeneous cohorts in prospective studies, and develop improved models that can diagnose mTBI with sufficient sensitivity and specificity in targeted populations. Full article

Coronary artery spasm (CAS) is a reversible vasoconstriction of normal or atherosclerotic epicardial coronary arteries with a subsequent reduction in myocardial blood flow, leading to myocardial ischemia, myocardial infarction, severe arrhythmias, or even sudden death. It is an entity that should be recognized based on a particular clinical presentation. Numerous differences exist between CAS and obstructive coronary disease in terms of mechanisms, risk factors, and therapeutic solutions. The gold standard for CAS diagnosis is represented by transitory and reversible occlusion of the coronary arteries at spasm provocation test, which consists of an intracoronary administration of Ach, ergonovine, or methylergonovine during angiography. The pathophysiology of CAS is not fully understood. However, the core of CAS is represented by vascular smooth muscle cell contraction, with a circadian pattern. The initiating event of this contraction may be represented by endothelial dysfunction, inflammation, or autonomic nervous system unbalance. Our study explores the intricate balance of these factors and their clinical relevance in the management of CAS. Full article

Canine monocytic ehrlichiosis (CME) is a globally prevalent disease transmitted by the tick Rhipicephalus sanguineus and caused by the Gram-negative bacterium Ehrlichia spp. Following an incubation period, the infection is categorized based on the progression of the disease into acute, subclinical, and chronic stages. Besides hematological alterations, the cardiovascular system is significantly impacted by the hemodynamic effects of the disease, as persistent anemia can lead to myocardial hypoxia and the activation of inflammatory processes, potentially causing myocarditis. It is known that in dogs infected with Ehrlichia canis, there is a higher occurrence of arrhythmias and a predominance of sympathetic activity. This study assessed arrhythmogenic parameters, including P wave dispersion (Pd), QT dispersion (QTd), and QT instability, along with heart rate variability (HRV) analysis from 24 h Holter monitoring in naturally infected dogs during the acute phase (n = 10) and chronic phase (n = 10) compared to a control group (n = 10). The Pd and QTd values were higher in the infect group, confirming the arrhythmogenic character. Instability parameters (TI, LTI, and STI) were higher in sick animals, but no worsening was observed in the chronic phase. All HRV metrics in the time domain were higher in the control group, indicating a balanced sympathovagal activity throughout the day in healthy dogs. Additionally, parameters linked to parasympathetic activity (rMSSD and pNN50) were reduced in the sick groups, confirming the dominance of sympathetic activity. These findings indicate a decrease in HRV in sick individuals and reinforce this useful marker for assessing the influence of the autonomic nervous system on the cardiovascular system. In conclusion, CME exhibits arrhythmogenic activity characterized by the deterioration of predictive parameters for ventricular arrhythmias and increased activity of the sympathetic autonomic nervous system in the heart. This is likely secondary to myocarditis, myocardial hypoxia, and structural damage to cardiomyocytes. Full article

Background: Heart rate variability (HRV) is a key biomarker reflecting autonomic nervous system (ANS) function and neurocardiac regulation. Reduced HRV has been associated with cardiovascular risk, neurodegenerative disorders, and autonomic dysfunction. In Parkinson’s disease (PD), HRV impairments indicate altered autonomic balance, which may be modifiable through structured exercise interventions. This study investigates the effects of aerobic exercise on HRV in patients with PD and evaluates autonomic adaptations to rehabilitation. Methods: A total of 110 patients with PD (55 male, 55 female) participated in a supervised three-month aerobic exercise program. HRV was assessed pre- and post-intervention using electrocardiogram (ECG) recordings. Time-domain and frequency-domain HRV metrics, including standard deviation of RR intervals (SDRR), very-low-frequency (VLF), low-frequency (LF), high-frequency (HF) power, and LF/HF ratio, were analyzed. Principal Component Analysis (PCA) and clustering techniques were applied to identify subgroups of HRV responders based on autonomic adaptation. Results: Significant improvements in HRV were observed post-intervention, with a reduction in LF/HF ratio (p < 0.05), indicating improved autonomic balance. Cluster analysis identified four distinct HRV response subgroups: Strong Responders, Moderate Responders, Mixed/Irregular Responders, and Low Responders. These findings highlight individual variability in autonomic adaptations to exercise. PCA revealed that key HRV parameters contribute differently to autonomic regulation, emphasizing the complexity of HRV changes in PD rehabilitation. Conclusions: This study demonstrates that aerobic exercise induces beneficial autonomic adaptations in PD patients, as reflected by HRV changes. The identification of response subgroups suggests the need for personalized rehabilitation strategies to optimize autonomic function. Further research is warranted to explore the long-term impact of HRV-guided rehabilitation interventions in PD management. Full article

Background: Periodic limb movements in sleep (PLMS) are characterised by repetitive, involuntary limb movements that occur during sleep and are often associated with autonomic nervous system dysregulation. While it is known that PLMS influence cardiovascular parameters, the exact role of heart rate variability (HRV) and the balance between sympathetic and parasympathetic activity remains unclear. Previous studies have suggested that longer PLMS events may trigger more pronounced autonomic responses, but the relationship between the duration of PLMS and autonomic dynamics has yet to be fully explored. This study aims to investigate the influence of PLMS duration on autonomic co-activation and its potential cardiovascular implications. Methods: A retrospective analysis was conducted on polysomnographic, demographic, and medical data from five patients, encompassing a total of 1348 PLMS events. We measured heart rate (HR), high-frequency HRV (HF-HRV), systolic blood pressure (SBP), and diastolic blood pressure (DBP) for 10 heartbeats before and 10 heartbeats after each PLMS series. A time–frequency approach was used, employing 10 RR interval segments to analyse HF-HRV dynamics. Statistical analysis was performed using IBM SPSS Statistics (v. 28.0.0.0), and the Kruskal–Wallis test was used to assess statistically significant deviations from baseline. Results: HF-HRV increased during PLMS, indicating enhanced parasympathetic activation. No significant changes in mean DBP or SBP were observed with leg movements of <2.1 s. However, with movements of >2.1 s, significant increases in DBP and SBP were noted, suggesting sympathetic activation. Longer PLMS events were associated with greater parasympathetic activity, while the absence of HR changes indicates concurrent sympathetic activation, supporting autonomic co-activation. Conclusions: Our study indicates that PLMS events lasting >2.1 s are linked to increased parasympathetic activity, likely accompanied by sympathetic activation. This simultaneous activation of both branches of the autonomic nervous system, referred to as autonomic co-activation, could lead to autonomic dysregulation and an increased risk of cardiovascular instability, including potentially life-threatening events. Full article

Fetal heart rate variability (FHRV) is a critical indicator of fetal well-being and autonomic nervous system development during labor. Traditional monitoring methods often provide limited insights, potentially leading to delayed interventions and suboptimal outcomes. This study proposes an advanced predictive analytics approach by integrating approximate entropy analysis with a hidden Markov model (HMM) within a digital twin framework to enhance real-time fetal monitoring. We utilized a dataset of 469 fetal electrocardiogram (ECG) recordings, each exceeding one hour in duration, to ensure sufficient temporal information for reliable modeling. The FHRV data were preprocessed and partitioned into parasympathetic and sympathetic components based on downward and non-downward beat detection. Approximate entropy was calculated to quantify the complexity of FHRV patterns, revealing significant correlations with umbilical cord blood gas parameters, particularly pH levels. The HMM was developed with four hidden states representing discrete pH levels and eight observed states derived from FHRV data. By employing the Baum–Welch and Viterbi algorithms for training and decoding, respectively, the model effectively captured temporal dependencies and provided early predictions of the fetal acid–base status. Experimental results demonstrated that the model achieved 85% training and 79% testing accuracy on the balanced dataset distribution, improving from 78% and 71% on the imbalanced dataset. The integration of this predictive model into a digital twin framework offers significant benefits for timely clinical interventions, potentially improving prenatal outcomes. Full article