Menstrual Irregularity: A Physiological Adaptation to Cope Perceived Stress.

INTRODUCTION: Menstrual cycle characteristics are regulated hormonally and are integrated at the level of the hypothalamus. Stress can affect the hypothalamic-pituitary gonadal axis. The objective of the study was to analyse the stress levels of women and compare their autonomic tone and menstrual characteristics. METHODOLOGY: A group of 100 apparently healthy, young, female volunteers were included in this pilot cohort study. Subjects were assessed for perceived stress using the Perceived Stress Scale 14 Item (PSS-14) questionnaire, underwent a heart rate variability (HRV) test on the second, 10th, and 21st days of their menstrual cycle, and their menstrual history was recorded. The statistical analysis was done using Statistical Product and Service Solutions (SPSS, version 21.0; IBM SPSS Statistics for Windows, Armonk, NY) software. Metric data were expressed in terms of numerical value and analysed as mean ± SD. Paired Student's T-test was used to compare the HRV data of all three days of the menstrual cycle separately, and p value<0.05 was considered significant. Menstrual irregularity was complained of by 13 subjects (Group A), and the rest (87 subjects) reported regular menses (Group B). RESULT: The perceived stress scores of Group A were significantly higher than Group B (32.53±5.062 vs 28.057±7.618; p=0.044). On second day, Group A had higher median R-R interval (714.38±106 vs 656.84±73.50 ms; p=0.015) and lower average heart rate (85.85±12.07 vs 92.39±9.98 bpm; p=0.034) than Group B, suggesting parasympathetic dominance. On the 10th day, Group A had a higher standard deviation of heart rate (7.09±1.88 vs 5.97±1.71 bpm; p=0.032) and a very low-frequency band (1105.94±984.12 vs 730.49±557.41 µs2; p=0.046) than Group B, indicating parasympathetic dominance in Group A. On the 21st day, Group A had a higher standard deviation of R-R interval (58.19±20.46 vs 44.85±14.55 ms; p=0.004), root mean square standard deviation (55.71±29.84 vs 31.89±15.99 ms; p<0.001), percentage of R-R differing by 50 ms (19.20±19.58 vs 10.87±10.31%; p=0.020), total power (3,440.23±2722.29 vs 2,068.28±1,322.49 µs2; p=0.004), high-frequency band (1,247.57±1173.54 vs 539.06±HPO438.92 µs2; p<0.001), standard deviation ratio of the Poincaré plot (0.53±0.19 vs 0.39±0.16; p=0.003), normalised HF (44.0±12.9 vs 35.4±10.6; p=0.009), and a lower LF/HF ratio (1.43±0.80 vs 2.11±1.16; p=0.043) and normalised LF (53.9±14.4 vs 64.1±11.9; p=0.006) than Group B, suggesting higher parasympathetic tone of Group A than Group B. CONCLUSION: Analysing these results, it can be concluded that, in apparently healthy young women, menstrual irregularity is a physiological adaptation to combat perceived stress and maintain parasympathetic dominance.

Mutual Information between EDA and EEG in Multiple Cognitive Tasks and Sleep Deprivation Conditions.

Sleep deprivation, a widespread phenomenon that affects one-third of normal American adults, induces adverse changes in physical and cognitive performance, which in turn increases the occurrence of accidents. Sleep deprivation is known to increase resting blood pressure and decrease muscle sympathetic nerve activity. Monitoring changes in the interplay between the central and autonomic sympathetic nervous system can be a potential indicator of human's readiness to perform tasks that involve a certain level of cognitive load (e.g., driving). The electroencephalogram (EEG) is the standard to assess the brain's activity. The electrodermal activity (EDA) is a reflection of the general state of arousal regulated by the activation of the sympathetic nervous system through sweat gland stimulation. In this work, we calculated the mutual information between EDA and EEG recordings in order to consider linear and non-linear interactions and provide an insight of the relationship between brain activity and peripheral autonomic sympathetic activity. We analyzed EEG and EDA data from ten participants performing four cognitive tasks every two hours during 24 h (12 trials). We decomposed EEG data into delta, theta, alpha, beta, and gamma spectral components, and EDA into tonic and phasic components. The results demonstrate high values of mutual information between the EDA and delta component of EEG, mainly in working memory tasks. Additionally, we found an increase in the theta component of EEG in the presence of fatigue caused by sleep deprivation, the alpha component in tasks demanding inhibition and attention, and the delta component in working memory tasks. In terms of the location of brain activity, most of the tasks report high mutual information in frontal regions in the initial trials, with a trend to decrease and become uniform for all the nine analyzed EEG channels as a consequence of the sleep deprivation effect. Our results evidence the interplay between central and sympathetic nervous activity and can be used to mitigate the consequences of sleep deprivation.

A framework based on the information domain to measure coupling changes in electrophysiological signals.

Objectives.In this paper, the features of physiological signals of healthy dataset are extracted using the linear and non-linear techniques, and a comparison has been made on healthy young and old subjects to study the aging and gender-related changes in the contribution of Heart Rate (HR), Blood Pressure (BP), and Respiration (RESP).Methods. To quantify the coupling changes in cardiovascular, cardiorespiratory, and vasculorespiratory complexity, an information domain approach based on compensated transfer entropy (cTE) is proposed.Result. The results show that there is a substantial decrease in the flow of information from BP tro the time interval between successive R-peaks (RR) and from RR to BP. There is also a significant decrease in the flow of information from RESP to BP and RESP to RR but there is no significant change in the information flow from BP to RESP and RR to RESP.Conclusion. We have done linear and non-linear analysis on the healthy datasets of young and old subjects. As already existed techniques lacks in studying complex behaviours of electrophysiological signals so to overcome these limitations, we have proposed compensated transfer entropy (cTE). We conducted an investigation to determine the degree to which recordings of RESP, BP, and HR can be utilized to predict changes in the other parameters. Specifically, the proposed analysis examined the relationship between these variables and assessed their consistency across different age groups and genders. By analyzing the data, we aimed to gain insights into the interdependencies and predictive potential of these physiological measures in relation to each other.

Dataset used to refine a treatment protocol of a biofeedback-based virtual reality intervention for pain and anxiety in children and adolescents undergoing surgery.

There is a great need for nonpharmacologic pain management strategies, given the catastrophic effects of the opioid epidemic and the role of opioid prescription in precipitating addiction [1], particularly in children and adolescents at risk of chronic pain and opioid use after surgery [2], [3], [4]. Biofeedback-based virtual reality (VR-BF) is an innovative approach to managing pain that compliments and may even increase accessibility [5] and acceptability [6] of existing mind-body therapies for pain management, like biofeedback (BF). BF teaches patients behavioral modification techniques that impact involuntary processes [7,8]. For example, slow breathing increases heart rate variability (HRV) [9] to reduce pain through the downregulation of the sympathetic nervous system [10,11]. However, barriers to widespread use, such as the need for trained personnel and high costs of direct intervention, have hindered its widespread clinical use and access to this therapy [5,12]. VR-BF has not yet been integrated into perioperative care, and as such, no defined treatment protocols for preoperative training and postoperative application of VR-BF exist, particularly in children. The dataset presented in this article may help fill the unmet, critical need for accessible, effective, alternative therapeutic options for reducing postoperative pain and opioid exposure in children. This investigation aimed to establish measurable outcomes impacting a perioperative treatment protocol of VR-BF, a novel VR-based therapy that teaches patients relaxation techniques and monitors the sensitivity of heart rate variability (HRV) to different frequencies and durations of VR-BF sessions. Achievement of target physiological parameters, including HRV, was measured in children and adolescents undergoing surgery anticipated to cause moderate to severe pain (e.g., orthopedic, chest) requiring postoperative pain management by the Acute Pain Services at Nationwide Children's Hospital (NCH). This dataset included 23 surgical patients evaluated quantitatively and qualitatively to refine a treatment protocol for the feasibility and acceptability of (a) preoperative education and training in relaxation, and (b) postoperative application of a VR-BF intervention for pain management [13]. Qualitative data was collected using an investigator-derived questionnaire to obtain feedback and understand the patient and family experience using VR-BF. Descriptive statistics (mean±SD or median with interquartile range [IQR] for continuous variables; frequencies and percentages for categorical variables) and exploratory spline regression analyses were generated to define measurable outcomes for a future pilot, randomized clinical trial protocol.

OperatorEYEVP: Operator Dataset for Fatigue Detection Based on Eye Movements, Heart Rate Data, and Video Information.

Detection of fatigue is extremely important in the development of different kinds of preventive systems (such as driver monitoring or operator monitoring for accident prevention). The presence of fatigue for this task should be determined with physiological and objective behavioral indicators. To develop an effective model of fatigue detection, it is important to record a dataset with people in a state of fatigue as well as in a normal state. We carried out data collection using an eye tracker, a video camera, a stage camera, and a heart rate monitor to record a different kind of signal to analyze them. In our proposed dataset, 10 participants took part in the experiment and recorded data 3 times a day for 8 days. They performed different types of activity (choice reaction time, reading, correction test Landolt rings, playing Tetris), imitating everyday tasks. Our dataset is useful for studying fatigue and finding indicators of its manifestation. We have analyzed datasets that have public access to find the best for this task. Each of them contains data of eye movements and other types of data. We evaluated each of them to determine their suitability for fatigue studies, but none of them fully fit the fatigue detection task. We evaluated the recorded dataset by calculating the correspondences between eye-tracking data and CRT (choice reaction time) that show the presence of fatigue.

The constrained disorder principle defines living organisms and provides a method for correcting disturbed biological systems.

The constrained disorder principle defines the existence and function of living organisms. The principle specifies that biological systems comprise a disorder within constrained random boundaries. Per this principle, living organisms are machines with a degree of error that do not strive to optimize. Their differentiator from non-living organisms is their intrinsic disorder within personalized dynamic random boundaries. The constrained disorder is mandatory for the systems' existence and proper operation. It provides living organisms the flexibility and adaptability required for operating under continuously changing internal and external milieus. The constrained disorder principle defines health and disease states by specifying the degree of the disorder and the arbitrary boundaries of biological systems. Disturbed systems lose their disorder or operate out of the disorder boundaries leading to diseases. The principle provides a platform for applying the constrained disorder to correct systems disturbances and improve disease outcomes.

Real-time analysis of heart rate variability during aerobic exercise in patients with cardiovascular disease.

Background: Exercise therapy for cardiovascular disease (CVD) is mainly evaluated based on the heart rate (HR) or Borg scale. However, these indices can be unreliable depending on the patient's medication or their subjective decisions; thus, alternative methods are required for easier and safer implementation of aerobic exercise. Here, we examined whether real-time analysis of HR variability (HRV) can help maintain exercise intensity at the ventilatory threshold (VT) during exercise. Methods: Twenty-eight patients with CVD treated at Keio University Hospital between August 2018 and March 2020 were enrolled. Initially, oxygen uptake (VO2) and HR at the VT were determined using the cardiopulmonary exercise test. Patients then performed aerobic exercise on a stationary bicycle for 30 min while a parameter of HRV, the high-frequency (HF) component, was monitored in real time using an electrocardiograph. The work rate during exercise was adjusted every 2 min to maintain the HF range between 5 and 10. The VO2 and HR values, recorded every 2 min during exercise, were compared with those at VT. The Bland-Altman method was used to confirm similarity. Results: VO2 and HR during exercise were closely correlated with those at VT (e.g., 19 min after exercise initiation; VO2: r = 0.647, HR: r = 0.534). The Bland-Altman plot revealed no bias between the mean values (e.g., 19 min; VO2: -0.22 mL/kg/min; HR: -0.07/min). Conclusion: Real-time HRV analysis with electrocardiograph alone during exercise can provide continuous and non-invasive exercise intensity measurements at VT, promoting safer and effective exercise strategies.

Non-contact neuromodulation of the human autonomic nervous system function via different odors: Sex, menstrual cycle, and odor dose- and duration-specific effects.

In recent decades, it has been uncovered that the autonomic nervous system (ANS) can be influenced using non-contact neuromodulation via odor stimulation. Increasing parasympathetic-vagal activation of the ANS is integral to improving the sympathovagal balance between the sympathetic- and parasympathetic nervous systems, which is often imbalanced in several chronic inflammatory disorders, such as rheumatoid arthritis and inflammatory bowel diseases. Although research into olfactory stimulation has been observed on the ANS, it is still lacking in the exploration of odor concentration and odor-specific effects. This is particularly the case as research has not utilized specified tools, such as the olfactometer to provide precise odor delivery. Furthermore, no research has compared the results in separate sex cohorts to investigate the role of sex or the menstrual stage on the subsequent interactions. In this study, we investigated the olfactory stimulation effects of four natural odors (mushroom, lavender, jasmine, and rose) in three concentrations (low, moderate, and high) on the ANS. To observe activity from the ANS, we used an electrocardiogram (ECG) based heart rate variability (HRV) and eye-tracker technology (pupil diameter). We found for the first time in literature that there were acute dose- and duration-specific odor effects of odors on the ANS. We also found sex and menstrual cycle effects in this interaction. Furthermore, there were stark distinctions in sympathovagal activity dependent ANS activation (HRV) in comparison to the oculomotor nerve-parasympathetic/cervical sympathetic nerves dependent ANS responses (pupil diameter). Sympathovagal activity dependent HRV showed odor, sex, and menstrual-stage interactions in both divisions of the ANS while the pupil responses only indicated increased sympathetic activation. These results shed light on the use of odor-specific stimulation to modulate the ANS activity in the context of sex and the menstrual stage. Future studies should be performed using a chronic odor delivery design to investigate the long-term effects of odors on the ANS. Clinical trial registration: Australian New Zealand Clinical Trials Registry, identifier [ACTRN12622000415707].

Impact of autonomic regulation on burnout and performance in thoracic surgery residents.

Objective: This study sought to determine the feasibility of collecting physiologic data in thoracic surgery residents and whether it would correlate with burnout and burnout with performance. Methods: This was a prospective study of thoracic surgery residents over a 5-month period. Participants were evaluated with a wearable biometric device (heart rate variability and sleep) and the Maslach Burnout Inventory. Resident performance was quantified using Accreditation Council for Graduate Medical Education Milestones (scale, 1-5) normalized to program-designated targets (3 for postgraduate year 6 or lower residents and 4 for postgraduate year 7 residents). Results: The cohort consisted of 71% female participants (5/7) with 86% of residents having 1 or more children. High levels of emotional exhaustion (median, 30 [interquartile range, 20-36], where >26 is high) and high levels of depersonalization (median, 16 [interquartile range, 14-22], where >12 is high) were common, but personal accomplishment was also uniformly high (median, 43 [interquartile range, 41-46], where >38 is high). There was a significant correlation between heart rate variability and emotional exhaustion (r(12) = 0.65, P = .01) but not depersonalization (P = .28) or personal accomplishment (P = .24). Depersonalization and personal accomplishment did not correlate with resident performance (P = .12 and P = .75, respectively); however, increased emotional exhaustion showed a significant correlation with higher resident performance during periods when burnout was reported (r(6) = 0.76, P = .047). Conclusions: Dynamic measurement of resting heart rate variability may offer an objective measure of burnout in thoracic surgery residents. Thoracic surgery residents who report high levels of burnout in this cohort maintained the ability to meet program-designated milestones at or above the level expected of their postgraduate year.

Effect of intensive weekend mindfulness-based intervention on BDNF, mitochondria function, and anxiety. A randomized, crossover clinical trial.

Background: The previous metanalysis found that Mind-body intervention (MBI) improves neuropsychologic well-being and may increase brain-derived growth factor (BDNF). BDNF is a neurotrophic factor related to neuroplasticity. Objective: To evaluate the effect of the short intensive MBI compared to control-relaxation on Site on BDNF and examine if this change is related to mitochondria function or stress-related neurohormonal activity. Methods: Randomized, controlled, two-period cross-over trial conducted in a medical center in Thailand. Healthy-meditation naive Nurse and Occupational Therapy Students, 23 assigned randomly to MBI, and 24 relaxations at the site for 8 h during the weekend. The wash-out period was three months between the two periods. All volunteers took the blood test for BDNF, mitochondrial oxidative phosphorylation (OXPHOS), Cortisol, and Heart rate variability (HRV) measurement before and Visual Analogue Scale for Anxiety (VAS-A), forward and backward digit span after each period. Results: A total of 40 participants finished the trials. The cross over trial analysis showed a significant treatment effect between MBI and Relaxation on-site for the mean VAS-A as 9.89 (95% CI 4.81 to 19.47; P = 0.001), serum BDNF as 1.24 (95% CI 0.16 to 2.32; P = 0.04), and OXPHOS complex-1 was decreased 0.41 (95% CI 0.03-0.29 p = 0.03). There were no significant differences for digit span, cortisol, and HRV. Conclusion: In healthy meditation naïve females, even a short period of MBI may increase serum BDNF and reduce anxiety more than relaxation on-site. The more reduction of OXPHOS complex-1 in the mindfulness group suggests oxidative stress may be a more sensitive indicator than stress-related neurohormonal activity.

Validity of Elite-HRV Smartphone Application for Measuring Heart Rate Variability Compared to Polar V800 Heart Rate Monitor.

BACKGROUND: With technological advancement, it has become very easy to obtain heart rate variability data with handy heart rate monitors as well as smartphone applications. This study was conducted to assess the validity of Elite HRV smartphone application to measure time domain heart rate variability indices at rest, in comparison to Polar V-800 heart rate monitor. METHODS: Heart rate variability data were acquired from twenty apparently healthy male medical students in supine position after simultaneously connecting Polar V800 and Elite HRV to chest-worn Polar H7 sensor. Time domain indices viz. Mean RR intervals, mean heart rate, standard deviation of normal to normal intervals and root mean square of successive differences of interval were taken for comparison. Difference, validity and agreement were assessed using students t-test, intraclass correlation coefficient and Bland Altman plot and limits of agreement. RESULTS: Students t-test showed that there was no significant difference between the data obtained from Elite HRV and Polar V-800 in all the parameters viz. mean RR intervals, mean heart rate, standard deviation of normal to normal intervals and root mean square of successive differences of interval (p>0.05). Correlation was excellent as shown by Intra-class correlation coefficient of >0.999 in all the parameters. Bland Altman analysis revealed small bias and narrow limits of agreement with all the parameters: mean heart rate [-0.003 (0.05 - 0.04)], mean RR [0.01 (-0.58 - 0.60)], standard deviation of normal to normal intervals [-0.01 (-0.32 - 0.30)] and root mean square of successive differences of interval [-0.05 (-0.89 - 0.79)]. CONCLUSIONS: Elite HRV smartphone application provided reliable time-domain heart rate variability data consistent with the data obtained from validity tested Polar V800 heart rate monitor.

Relationship Between Cognitive Appraisal of Control and Cardiac Vagal Regulation During an Unsupported Ski Crossing of Greenland.

Purpose: The aim of the present study was to investigate the relationships between Perceived Control (PC) and Heart rate variability (HRV) during a 27-day expedition, during which an unsupported crossing was made from the west coast to the east coast of Greenland (across the Ice Sheet); and that therefore a high PC represents a favourable factor for recovery and stress management. Methods: Four subjects participated in the study. PC was measured on alternated days in the evening at the end of the day, using the Pearlin Mastery Scale; and the next day, upon waking, heart rate using a wrist heart rate monitor and a chest strap. Together with the PC, the perceived effort was measured through the CR-100 Borg scale and each subject was asked to indicate the most emotionally significant event of the day.Time and frequency domain indices for heart rate variability were calculated. Results: Several correlations were observed between PC and HRV indices. In particular two indices in the time domain, standard deviation of all NN intervals (SDNN) (rrm = 0.51) and root mean square of successive (RMSSD) (rrm = 0.46), showed a significant and strong positive correlation. Conclusion: The existence of a positive correlation between PC and cardiac vagal regulation is of great interest to individuals immerged into extreme situations, because it can affect performance or prevents maladaptive states or injuries. To improve stress management, it could be convenient for members of extreme expeditions to adopt forms of cognitive training that modify their cognitive appraisal in order to raise their perception of control.

Research Opportunities in Autonomic Neural Mechanisms of Cardiopulmonary Regulation: A Report From the National Heart, Lung, and Blood Institute and the National Institutes of Health Office of the Director Workshop.

This virtual workshop was convened by the National Heart, Lung, and Blood Institute, in partnership with the Office of Strategic Coordination of the Office of the National Institutes of Health Director, and held September 2 to 3, 2020. The intent was to assemble a multidisciplinary group of experts in basic, translational, and clinical research in neuroscience and cardiopulmonary disorders to identify knowledge gaps, guide future research efforts, and foster multidisciplinary collaborations pertaining to autonomic neural mechanisms of cardiopulmonary regulation. The group critically evaluated the current state of knowledge of the roles that the autonomic nervous system plays in regulation of cardiopulmonary function in health and in pathophysiology of arrhythmias, heart failure, sleep and circadian dysfunction, and breathing disorders. Opportunities to leverage the Common Fund's SPARC (Stimulating Peripheral Activity to Relieve Conditions) program were characterized as related to nonpharmacologic neuromodulation and device-based therapies. Common themes discussed include knowledge gaps, research priorities, and approaches to develop novel predictive markers of autonomic dysfunction. Approaches to precisely target neural pathophysiological mechanisms to herald new therapies for arrhythmias, heart failure, sleep and circadian rhythm physiology, and breathing disorders were also detailed.

Acute Cardiovascular Effects of Hydrotreated Vegetable Oil Exhaust.

Ambient air pollution is recognized as a key risk factor for cardiovascular morbidity and mortality contributing to the global disease burden. The use of renewable diesel fuels, such as hydrotreated vegetable oil (HVO), have increased in recent years and its impact on human health are not completely known. The present study investigated changes in cardiovascular tone in response to exposure to diluted HVO exhaust. The study participants, 19 healthy volunteers, were exposed in a chamber on four separate occasions for 3 h and in a randomized order to: (1) HVO exhaust from a wheel loader without exhaust aftertreatment, (2) HVO exhaust from a wheel loader with an aftertreatment system, (3) clean air enriched with dry NaCl salt particles, and (4) clean air. Synchronized electrocardiogram (ECG) and photoplethysmogram (PPG) signals were recorded throughout the exposure sessions. Pulse decomposition analysis (PDA) was applied to characterize PPG pulse morphology, and heart rate variability (HRV) indexes as well as pulse transit time (PTT) indexes were computed. Relative changes of PDA features, HRV features and PTT features at 1, 2, and 3 h after onset of the exposure was obtained for each participant and exposure session. The PDA index A13, reflecting vascular compliance, increased significantly in both HVO exposure sessions but not in the clean air or NaCl exposure sessions. However, the individual variation was large and the differences between exposure sessions were not statistically significant.

Protocol: A randomized controlled trial to assess effectiveness of a 12-month lifestyle intervention to reduce cardiovascular disease risk in families ten years after pre-eclampsia (FINNCARE).

Pre-eclampsia (PE) is a multisystem progressive disorder affecting 3-5% of pregnancies. PE independently increases the risk for premature cardiovascular disease (CVD) in mothers and their children long-term. The effectiveness of a family-centered lifestyle intervention to lower CVD risk in PE families has not previously been evaluated. In the current FINNCARE study, we prospectively compare CVD risk and CVD progression in PE families (mother, father and child) in a cross-sectional study setting 8-12 years from delivery with non-PE control families of comparable age. Furthermore, we evaluate the effectiveness and feasibility of an interactive web-based behavioral 12-month lifestyle intervention to reduce blood pressure and the CVD risk profile overall in a randomized controlled trial. In total, 300 PE families will be randomized 1:1 to a PE-intervention or a PE-control group, and the 100 non-PE control families similarly followed-up at 12 months. Primary outcome is 24-hour mean systolic BP change from baseline in mother and child. Study aims to provide information on CVD progression and CVD risk management in the family following PE.

Cardiac and Autonomic Dysfunctions Assessed Through Recurrence Quantitative Analysis of Electrocardiogram Signals and an Application to the 6-Hydroxydopamine Parkinson's Disease Animal Model.

A classic method to evaluate autonomic dysfunction is through the evaluation of heart rate variability (HRV). HRV provides a series of coefficients, such as Standard Deviation of n-n intervals (SDNN) and Root Mean Square of Successive Differences (RMSSD), which have well-established physiological associations. However, using only electrocardiogram (ECG) signals, it is difficult to identify proper autonomic activity, and the standard techniques are not sensitive and robust enough to distinguish pure autonomic modulation in heart dynamics from cardiac dysfunctions. In this proof-of-concept study we propose the use of Poincaré mapping and Recurrence Quantification Analysis (RQA) to identify and characterize stochasticity and chaoticity dynamics in ECG recordings. By applying these non-linear techniques in the ECG signals recorded from a set of Parkinson's disease (PD) animal model 6-hydroxydopamine (6-OHDA), we showed that they present less variability in long time epochs and more stochasticity in short-time epochs, in their autonomic dynamics, when compared with those of the sham group. These results suggest that PD animal models present more "rigid heart rate" associated with "trembling ECG" and bradycardia, which are direct expressions of Parkinsonian symptoms. We also compared the RQA factors calculated from the ECG of animal models using four computational ECG signals under different noise and autonomic modulatory conditions, emulating the main ECG features of atrial fibrillation and QT-long syndrome.

Is there an association between socioeconomic status and the degree of diurnal variation in heart rate?

BACKGROUND: Disruption in circadian rhythms is associated with cardiovascular disease and may play a role in socioeconomic differences in cardiovascular disease prevalence. However, it is unclear whether low SES is associated with a lower diurnal rhythm in autonomic activity markers. We investigated the association between SES and the amplitude of the daily fluctuation of heart rate. METHODS: We included data of 450 participants of a HELIUS sub-study in Amsterdam, the Netherlands. Participants wore an Actiheart monitor (CamNtech), a chest-worn monitor which measures heart rate every 15 s for several days. Cosinor analysis was performed on the time series of heart rate within each participant. We analyzed the association between the cosinor parameters (amplitude, midline and peak time of the diurnal HR rhythm) and SES indicators (education, occupational class and a proxy of income) in multivariate linear regression models, adjusting for age, sex and ethnicity. RESULTS: There was a clear diurnal rhythm in the average heart rates, with a peak between noon and 18:00 and a trough between 04:00 and 06:00. This rhythm was present for all categories of education, occupation and income proxy. The estimates for the cosinor parameters did not differ consistently and significantly between categories of education, occupation or income proxy. CONCLUSIONS: We did not find any consistent evidence to support our hypothesis of a diminished amplitude in the diurnal variation of heart rate in individuals with lower SES. Future studies should explore SES differences in the diurnal variation in markers of autonomic activity other than heart rate.

Personal Resources and Organizational Outcomes: Sex as a Moderator of the Complex Relationships Between Self-Esteem, Heart Rate Variability, and Work-Related Exhaustion.

Global self-esteem represents a protective personal resource lowering the risk of psychological distress. Research conducted in the work setting has confirmed the psychosocial benefits of high self-esteem. However, research linking self-esteem to neurobiological adaptability appears quite scarce. In this study, we propose a theoretical model in which self-esteem predicts work-related exhaustion indirectly, through the mediation of heart rate variability (HRV) and negative affect at work. Moreover, we explore the relationship between self-esteem and HRV. From one side, one would expect a positive link between self-esteem and HRV, signaling higher autonomic adaptability. However, recent studies have shown that in women, such associations become more complex, with even reversed patterns as compared with that in men. Thus, we included sex as a moderator of the relationship between HRV and self-esteem. The model was tested on a sample of 110 individuals working in the relational professions (54% males; M age = 42.6, SD = 13.73), observed for an entire workday. Results confirmed the protective role of self-esteem against the experience of negative affect and (indirectly) work-related exhaustion. Symptoms of exhaustion at work were also negatively predicted by HRV, and both HRV and negative affect acted as mediators of the relationship between self-esteem and work-related exhaustion. Notably, sex differences emerged in the association between global self-esteem and cardiac vagal tone at work: in women, self-esteem was negatively related to HRV, which in turn led to higher work-related exhaustion, whereas in men, no evidence of this indirect effect appeared. Burnout prevention programs should not ignore important sex differences in how individuals respond to work-related stress.

Heterogeneity in patterns of pain development after nerve injury in rats and the influence of sex.

The genesis of neuropathic pain is complex, as sensory abnormalities may differ between patients with different or similar etiologies, suggesting mechanistic heterogeneity, a concept that is largely unexplored. Yet, data are usually grouped for analysis based on the assumption that they share the same underlying pathogenesis. Sex is a factor that may contribute to differences in pain responses. Neuropathic pain is more prevalent in female patients, but pre-clinical studies that can examine pain development in a controlled environment have typically failed to include female subjects. This study explored patterns of development of hyperalgesia-like behavior (HLB) induced by noxious mechanical stimulation in a neuropathic pain model (spared nerve injury, SNI) in both male and female rats, and autonomic dysfunction that is associated with chronic pain. HLB was analyzed across time, using both discrete mixture modeling and rules-based longitudinal clustering. Both methods identified similar groupings of hyperalgesia trajectories after SNI that were not evident when data were combined into groups by sex only. Within the same hyperalgesia development group, mixed models showed that development of HLB in females was delayed relative to males and reached a magnitude similar to or higher than males. The data also indicate that sympathetic tone (as indicated by heart rate variability) drops below pre-SNI level before or at the onset of development of HLB. This study classifies heterogeneity in individual development of HLB and identifies sexual dimorphism in the time course of development of neuropathic pain after nerve injury. Future studies addressing mechanisms underlying these differences could facilitate appropriate pain treatments.

Identification of Latent Risk Clinical Attributes for Children Born Under IUGR Condition Using Machine Learning Techniques.

BACKGROUND AND OBJECTIVE: Intrauterine Growth Restriction (IUGR) is a condition in which a fetus does not grow to the expected weight during pregnancy. There are several well documented causes in the literature for this issue, such as maternal disorder, and genetic influences. Nevertheless, besides the risk during pregnancy and labour periods, in a long term perspective, the impact of IUGR condition during the child development is an area of research itself. The main objective of this work is to propose a machine learning solution to identify the most significant features of importance based on physiological, clinical or socioeconomic factors correlated with previous IUGR condition after 10 years of birth. METHODS: In this work, 41 IUGR (18 male) and 34 Non-IUGR (22 male) children were followed up 9 years after the birth, in average (9.1786 ± 0.6784 years old). A group of machine learning algorithms is proposed to classify children previously identified as born under IUGR condition based on 24-hours monitoring of ECG (Holter) and blood pressure (ABPM), and other clinical and socioeconomic attributes. In additional, an algorithm of relevance determination based on the classifier is also proposed, to determine the level of importance of the considered features. RESULTS: The proposed classification solution achieved accuracy up to 94.73%, and better performance than seven state-of-the-art machine learning algorithms. Also, relevant latent factors related to HRV and BP monitoring are proposed, such as: day-time heart rate (day-time HR), day-night systolic blood pressure (day-night SBP), 24-hour standard deviation (SD) of SBP, dropped, morning cortisol creatinine, 24-hour mean of SDs of all NN intervals for each 5 minutes segment (24-hour SDNNi), among others. CONCLUSION: With outstanding accuracy of our proposed solutions, the classification system and the indication of relevant attributes may support medical teams on the clinical monitoring of IUGR children during their childhood development.