Modeling the hypothalamus-pituitary-adrenal axis: A review and extension

A mathematical representation of the reactive scope model

Researchers have long sought to understand and predict an animal's response to stressful stimuli. Since the introduction of the concept of homeostasis, a variety of model frameworks have been proposed to describe what is necessary for an animal to remain within this stable physiological state and the ramifications of leaving it. Romero et al. (Horm Behav 55(3):375-389, 2009) introduced the reactive scope model to provide a novel conceptual framework for the stress response that assumes an animal's ability to tolerate a stressful stimulus may degrade over time in response to the stimulus. We provide a mathematical formulation for the reactive scope model using a system of ordinary differential equations and show that this model is capable of recreating existing experimental data. We also provide an experimental method that may be used to verify the model as well as several potential additions to the model. If future experimentation provides the necessary data to estimate the model's parameters, the model presented here may be used to make quantitative predictions about physiological mediator levels during a stress response and predict the onset of homeostatic overload.

VeVaPy, a Python Platform for Efficient Verification and Validation of Systems Biology Models with Demonstrations Using Hypothalamic-Pituitary-Adrenal Axis Models

In order for mathematical models to make credible contributions, it is essential for them to be verified and validated. Currently, verification and validation (V&V) of these models does not meet the expectations of the system biology and systems pharmacology communities. Partially as a result of this shortfall, systemic V&V of existing models currently requires a lot of time and effort. In order to facilitate systemic V&V of chosen hypothalamic-pituitary-adrenal (HPA) axis models, we have developed a computational framework named VeVaPy-taking care to follow the recommended best practices regarding the development of mathematical models. VeVaPy includes four functional modules coded in Python, and the source code is publicly available. We demonstrate that VeVaPy can help us efficiently verify and validate the five HPA axis models we have chosen. Supplied with new and independent data, VeVaPy outputs objective V&V benchmarks for each model. We believe that VeVaPy will help future researchers with basic modeling and programming experience to efficiently verify and validate mathematical models from the fields of systems biology and systems pharmacology.

Children and Adolescents Dietary Habits and Lifestyle Changes during COVID-19 Lockdown in Italy

Background: We evaluated the changes in lifestyle during the COVID-19 pandemic lockdown in a sample of children and adolescents in order to assess any increase in risk factors for the onset of cardiovascular diseases in later ages. Methods: We conducted a cross-sectional study involving 965 parents who completed an online survey about dietary habits and lifestyle during the first lockdown in Italy (from 9 March 2020 to 18 May 2020) and compared their findings with the period before the pandemic. The inclusion criteria were parents (or caregivers) with Italian residency and with children aged between 5 and 18 years. Results: We identified 563 adolescents and 402 children. The mean age was 12.28 years (SD 3.754). The pandemic was associated with an increase in the consumption of high-calorie snack foods. The total amount of food in homes during lockdown compared with before the pandemic increased 50%. Relating to the parent-perceived child weight status, more parents reported obesity in their children after lockdown (+0.6% in the 5–11 age group and +0.2% in the 12–18 age group). We reported a reduction of physical activity, an increase of sedentary lifestyle and sleep habits changes. Conclusion: The COVID-19 pandemic was associated with changes in the lifestyles of children and adolescents; this could cause an increase in the incidence of obesity and of cardiovascular and metabolic diseases in adulthood.

How exposure to chronic stress contributes to the development of type 2 diabetes: A complexity science approach

Chronic stress contributes to the onset of type 2 diabetes (T2D), yet the underlying etiological mechanisms are not fully understood. Responses to stress are influenced by earlier experiences, sex, emotions and cognition, and involve a complex network of neurotransmitters and hormones, that affect multiple biological systems. In addition, the systems activated by stress can be altered by behavioral, metabolic and environmental factors. The impact of stress on metabolic health can thus be considered an emergent process, involving different types of interactions between multiple variables, that are driven by non-linear dynamics at different spatiotemporal scales. To obtain a more comprehensive picture of the links between chronic stress and T2D, we followed a complexity science approach to build a causal loop diagram (CLD) connecting the various mediators and processes involved in stress responses relevant for T2D pathogenesis. This CLD could help develop novel computational models and formulate new hypotheses regarding disease etiology.

Perspective: Drawing on Findings From Critical Illness to Explain Myalgic Encephalomyelitis/Chronic Fatigue Syndrome

We propose an initial explanation for how myalgic encephalomyelitis / chronic fatigue syndrome (ME/CFS) could originate and perpetuate by drawing on findings from critical illness research. Specifically, we combine emerging findings regarding (a) hypoperfusion and endotheliopathy, and (b) intestinal injury in these illnesses with our previously published hypothesis about the role of (c) pituitary suppression, and (d) low thyroid hormone function associated with redox imbalance in ME/CFS. Moreover, we describe interlinkages between these pathophysiological mechanisms as well as “vicious cycles” involving cytokines and inflammation that may contribute to explain the chronic nature of these illnesses. This paper summarizes and expands on our previous publications about the relevance of findings from critical illness for ME/CFS. New knowledge on diagnostics, prognostics and treatment strategies could be gained through active collaboration between critical illness and ME/CFS researchers, which could lead to improved outcomes for both conditions.

From work stress to disease: A computational model

In modern society, work stress is highly prevalent. Problematically, work stress can cause disease. To help understand the causal relationship between work stress and disease, we present a computational model of this relationship. That is, drawing from allostatic load theory, we captured the link between work stress and disease in a set of mathematical formulas. With simulation studies, we then examined our model’s ability to reproduce key findings from previous empirical research. Specifically, results from Study 1 suggested that our model could accurately reproduce established findings on daily fluctuations in cortisol levels (both on the group level and the individual level). Results from Study 2 suggested that our model could accurately reproduce established findings on the relationship between work stress and cardiovascular disease. Finally, results from Study 3 yielded new predictions about the relationship between workweek configurations (i.e., how working hours are distributed over days) and the subsequent development of disease. Together, our studies suggest a new, computational approach to studying the causal link between work stress and disease. We suggest that this approach is fruitful, as it aids the development of falsifiable theory, and as it opens up new ways of generating predictions about why and when work stress is (un)healthy.

Personal ozone exposure and stress hormones in the hypothalamus-pituitary-adrenal and sympathetic-adrenal-medullary axes

BACKGROUND

The effect of ozone exposure on neuroendocrine responses in humans has not been fully studied.

METHODS

We conducted a longitudinal panel study with four rounds of visits among 43 college students in Shanghai, China, from May to October 2016. For each visit, we monitored personal real-time ozone exposure for consecutive 3 days (from 8:00 a.m. to 6:00p.m. each day), followed by blood sample collection. We measured serum levels of three hormones in the hypothalamus-pituitaryadrenal (HPA) axis, including corticotropin releasing hormone (CRH), adrenocorticotropic hormone (ACTH), and cortisol, and three catacholamines indicating sympathetic-adrenal-medullary (SAM) axis activation, including adrenaline, noradrenaline, and dopamine. We applied linear mixed-effect models to evaluate the associations between ozone exposure and these neurohormones and further compared models using personal and fixed-site ozone measurements.

MAIN RESULTS

At lag 0-8 h, personal ozone exposure ranged from 4.5 ppb to 104.3 ppb with an average of 21.0 ± 14.7 ppb, which was approximately half of the ambient ozone concentration. Per 10-ppb increase in personal ozone exposure (lag 0-8 h) was associated with increases of 5.60% [95% confidence interval (CI): 2.30%, 9.01%] in CRH, 5.91% (95% CI: 0.55%, 11.56%) in cortisol, and 10.13% (95% CI: 2.75%, 18.05%) in noradrenaline, whereas associated with a 12.15% (95% CI: 1.23%, 21.87%) decrease in dopamine. Overall, models using personal ozone measurements yielded larger effect estimates and better model fits than models using fixed-site measurements.

CONCLUSIONS

Short-term exposure to low levels of ozone may lead to activation of the HPA and SAM axes.

Neuro-consequences of the spaceflight environment

As human space exploration advances to establish a permanent presence beyond the Low Earth Orbit (LEO) with NASA's Artemis mission, researchers are striving to understand and address the health challenges of living and working in the spaceflight environment. Exposure to ionizing radiation, microgravity, isolation and other spaceflight hazards pose significant risks to astronauts. Determining neurobiological and neurobehavioral responses, understanding physiological responses under Central Nervous System (CNS) control, and identifying putative mechanisms to inform countermeasure development are critically important to ensuring brain and behavioral health of crew on long duration missions. Here we provide a detailed and comprehensive review of the effects of spaceflight and of ground-based spaceflight analogs, including simulated weightlessness, social isolation, and ionizing radiation on humans and animals. Further, we discuss dietary and non-dietary countermeasures including artificial gravity and antioxidants, among others. Significant future work is needed to ensure that neural, sensorimotor, cognitive and other physiological functions are maintained during extended deep space missions to avoid potentially catastrophic health and safety outcomes.

Theory: Treatments for Prolonged ICU Patients May Provide New Therapeutic Avenues for Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS)

We here provide an overview of treatment trials for prolonged intensive care unit (ICU) patients and theorize about their relevance for potential treatment of myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS). Specifically, these treatment trials generally target: (a) the correction of suppressed endocrine axes, notably through a "reactivation" of the pituitary gland's pulsatile secretion of tropic hormones, or (b) the interruption of the "vicious circle" between inflammation, oxidative and nitrosative stress (O&NS), and low thyroid hormone function. There are significant parallels in the treatment trials for prolonged critical illness and ME/CFS; this is consistent with the hypothesis of an overlap in the mechanisms that prevent recovery in both conditions. Early successes in the simultaneous reactivation of pulsatile pituitary secretions in ICU patients-and the resulting positive metabolic effects-could indicate an avenue for treating ME/CFS. The therapeutic effects of thyroid hormones-including in mitigating O&NS and inflammation and in stimulating the adreno-cortical axis-also merit further studies. Collaborative research projects should further investigate the lessons from treatment trials for prolonged critical illness for solving ME/CFS.

Hypothesis: Mechanisms That Prevent Recovery in Prolonged ICU Patients Also Underlie Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS)

Here the hypothesis is advanced that maladaptive mechanisms that prevent recovery in some intensive care unit (ICU) patients may also underlie Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS). Specifically, these mechanisms are: (a) suppression of the pituitary gland's pulsatile secretion of tropic hormones, and (b) a "vicious circle" between inflammation, oxidative and nitrosative stress (O&NS), and low thyroid hormone function. This hypothesis should be investigated through collaborative research projects.

Circadian rhythms and the HPA axis: A systems view

The circadian timing system comprises a network of time-keeping clocks distributed across a living host whose responsibility is to allocate resources and distribute functions temporally to optimize fitness. The molecular structures generating these rhythms have evolved to accommodate the rotation of the earth in an attempt to primarily match the light/dark periods during the 24-hr day. To maintain synchrony of timing across and within tissues, information from the central clock, located in the suprachiasmatic nucleus, is conveyed using systemic signals. Leading among those signals are endocrine hormones, and while the hypothalamic-pituitary-adrenal axis through the release of glucocorticoids is a major pacesetter. Interestingly, the fundamental units at the molecular and physiological scales that generate local and systemic signals share critical structural properties. These properties enable time-keeping systems to generate rhythmic signals and allow them to adopt specific properties as they interact with each other and the external environment. The purpose of this review is to provide a broad overview of these structures, discuss their functional characteristics, and describe some of their fundamental properties as these related to health and disease. This article is categorized under: Immune System Diseases > Computational Models Immune System Diseases > Biomedical Engineering.

A new model for the HPA axis explains dysregulation of stress hormones on the timescale of weeks

Stress activates a complex network of hormones known as the hypothalamic-pituitary-adrenal (HPA) axis. The HPA axis is dysregulated in chronic stress and psychiatric disorders, but the origin of this dysregulation is unclear and cannot be explained by current HPA models. To address this, we developed a mathematical model for the HPA axis that incorporates changes in the total functional mass of the HPA hormone-secreting glands. The mass changes are caused by HPA hormones which act as growth factors for the glands in the axis. We find that the HPA axis shows the property of dynamical compensation, where gland masses adjust over weeks to buffer variation in physiological parameters. These mass changes explain the experimental findings on dysregulation of cortisol and ACTH dynamics in alcoholism, anorexia, and postpartum. Dysregulation occurs for a wide range of parameters and is exacerbated by impaired glucocorticoid receptor (GR) feedback, providing an explanation for the implication of GR in mood disorders. These findings suggest that gland-mass dynamics may play an important role in the pathophysiology of stress-related disorders.

Organ-On-A-Chip in vitro Models of the Brain and the Blood-Brain Barrier and Their Value to Study the Microbiota-Gut-Brain Axis in Neurodegeneration

We are accumulating evidence that intestinal microflora, collectively named gut microbiota, can alter brain pathophysiology, but researchers have just begun to discover the mechanisms of this bidirectional connection (often referred to as microbiota-gut-brain axis, MGBA). The most noticeable hypothesis for a pathological action of gut microbiota on the brain is based on microbial release of soluble neurotransmitters, hormones, immune molecules and neuroactive metabolites, but this complex scenario requires reliable and controllable tools for its causal demonstration. Thanks to three-dimensional (3D) cultures and microfluidics, engineered in vitro models could improve the scientific knowledge in this field, also from a therapeutic perspective. This review briefly retraces the main discoveries linking the activity of gut microbiota to prevalent brain neurodegenerative disorders, and then provides a deep insight into the state-of-the-art for in vitro modeling of the brain and the blood-brain barrier (BBB), two key players of the MGBA. Several brain and BBB microfluidic devices have already been developed to implement organ-on-a-chip solutions, but some limitations still exist. Future developments of organ-on-a-chip tools to model the MGBA will require an interdisciplinary approach and the synergy with cutting-edge technologies (for instance, bioprinting) to achieve multi-organ platforms and support basic research, also for the development of new therapies against neurodegenerative diseases.

Allostatic adaptation and personalized physiological trade-offs in the circadian regulation of the HPA axis: A mathematical modeling approach

The hypothalamic-pituitary-adrenal (HPA) axis orchestrates the physiological response to unpredictable acute stressors. Moreover, the HPA axis exhibits prominent circadian activity and synchronizes peripheral circadian clocks to daily environmental cycles, thereby promoting homeostasis. Persistent disruption of homeostatic glucocorticoid circadian rhythmicity due to chronic stress exposure is correlated with the incidence of various pathological conditions including depression, diabetes and cancer. Allostatic habituation of the HPA axis, such that glucocorticoid levels retain homeostatic levels upon chronic exposure to stress, can therefore confer fitness advantages by preventing the sustained dysregulation of glucocorticoid-responsive signaling pathways. However, such allostatic adaptation results in a physiological cost (allostatic load) that might impair the homeostatic stress-responsive and synchronizing functions of the HPA axis. We use mathematical modeling to characterize specific chronic stress-induced allostatic adaptations in the HPA network. We predict the existence of multiple individualized regulatory strategies enabling the maintenance of homeostatic glucocorticoid rhythms, while allowing for flexible HPA response characteristics. We show that this regulatory variability produces a trade-off between the stress-responsive and time-keeping properties of the HPA axis. Finally, allostatic regulatory adaptations are predicted to cause a time-of-day dependent sensitization of the acute stress response and impair the entrainability of the HPA axis.

Adoption of New Medical Technologies: The Case of Customized Individually Made Knee Implants

OBJECTIVES

To investigate the impact of insurance coverage on the adoption of customized individually made (CIM) knee implants and to compare patient outcomes and cost effectiveness of off-the-shelf and CIM implants.

METHODS

A system dynamics simulation model was developed to study adoption dynamics of CIM and meet the research objectives. The model reproduced the historical data on primary and revision knee replacement implants obtained from the literature and the Nationwide Inpatient Sample. Then the dynamics of adoption of CIM implants were simulated from 2018 to 2026. The rate of 90-day readmission, 3-year revision surgery, recovery period, time savings in operating rooms, and the associated cost within 3 years of primary knee replacement implants were used as performance metrics.

RESULTS

The simulation results indicate that by 2026, an adoption rate of 90% for CIM implants can reduce the number of readmissions and revision surgeries by 62% and 39%, respectively, and can save hospitals and surgeons 6% on procedure time and cut down cumulative healthcare costs by approximately $38 billion.

CONCLUSIONS

CIM implants have the potential to deliver high-quality care while decreasing overall healthcare costs, but their adoption requires the expansion of current insurance coverage. This work presents the first systematic study to understand the dynamics of adoption of CIM knee implants and instrumentation. More broadly, the current modeling approach and systems thinking perspective could be used to consider the adoption of any emerging customized therapies for personalized medicine.

Fine particulate matter constituents and stress hormones in the hypothalamus-pituitary-adrenal axis

Fine particulate matter (PM_2.5) has recently been associated with the activation of the hypothalamus-pituitary-adrenal (HPA) axis, increasing cardiometabolic risks. However, it is unknown which constituents of PM_2.5 were mainly responsible for these associations. In a longitudinal panel study with 4 repeated measurements among 43 college students in Shanghai, China, we measured serum levels of corticotropin releasing hormone (CRH), adrenocorticotropic hormone (ACTH) and cortisol, as indicators of HPA axis activation. Then, we evaluated the associations of 22 constituents of PM_2.5 with these stress hormones using linear mixed-effect models. During the study period, the average daily concentration of PM_2.5 was 41.1 μg/m³. We found that short-term exposure to PM_2.5 was associated with elevated levels of the 3 stress hormones. We observed that water-soluble inorganic ions, especially nitrate (NO₃^-) and ammonium, had stronger influences on 3 hormones. Six metallic elements, including Zn, Mn, Cu, Fe, Br, and Cr, had positive but generally instable associations with 3 hormones. The effects of organic carbon and elemental carbon on hormones were generally weak. When correcting for multiple comparisons using false discovery rate, NO₃^- was still significantly associated with CRH, but other important associations turned to be insignificant. An interquartile range increase in NO₃^- on the previous day were associated with 12.13% increase (95% confidence interval: 4.45%, 20.37%) in CRH. Our findings suggested that water-soluble inorganic constituents of PM_2.5 (especially, NO₃^-) might have stronger influences on the activation of HPA axis than carbonaceous and elemental components.

Modeling and estimating the feedback mechanisms among depression, rumination, and stressors in adolescents

The systemic interactions among depressive symptoms, rumination, and stress are important to understanding depression but have not yet been quantified. In this article, we present a system dynamics simulation model of depression that captures the reciprocal relationships among stressors, rumination, and depression. Building on the response styles theory, this model formalizes three interdependent mechanisms: 1) Rumination contributes to 'keeping stressors alive'; 2) Rumination has a direct impact on depressive symptoms; and 3) Both 'stressors kept alive' and current depressive symptoms contribute to rumination. The strength of these mechanisms is estimated using data from 661 adolescents (353 girls and 308 boys) from two middle schools (grades 6-8). These estimates indicate that rumination contributes to depression by keeping stressors 'alive'-and the individual activated-even after the stressor has ended. This mechanism is stronger among girls than boys, increasing their vulnerability to a rumination reinforcing loop. Different profiles of depression emerge over time depending on initial levels of depressive symptoms, rumination, and stressors as well as the occurrence rate for stressors; levels of rumination and occurrence of stressors are stronger contributors to long-term depression. Our systems model is a steppingstone towards a more comprehensive understanding of depression in which reinforcing feedback mechanisms play a significant role. Future research is needed to expand this simulation model to incorporate other drivers of depression and provide a more holistic tool for studying depression.

Anxiolytic-like effects of paeoniflorin in an animal model of post traumatic stress disorder

Post-traumatic stress disorder (PTSD) is the serious psychiatric disorder. Paeoniflorin (PF) produces the antidepressant-like properties. However, few studies are concerned about its anti-PTSD-like effects and mechanisms. To investigate these, the single prolonged stress (SPS) model was utilized. PTSD-like behavioral deficits in rats after exposure to SPS were improved by PF (10 and 20 mg/kg, i.p.), evidenced by blocking increased freezing time in contextual fear paradigm (CFP) and increased time and entries in open arms in elevated plus maze (EPM) test without affecting the locomotor activity in open field (OF) test. We also found that increased levels of corticosterone (Cort), corticotropin releasing hormone (CRH) and adrenocorticotropic hormone (ACTH) after exposure to SPS were reversed by PF (10 and 20 mg/kg, i.p.) in serum, respectively. Moreover, the decreased levels of serotonin (5-HT) and 5-Hydroxyindoleacetic acid (5-HIAA) in prefrontal cortex and hippocampus were reversed by PF (10 and 20 mg/kg, i.p.), respectively. In summary, the anti-PTSD-like activities of PF were associated with the modulation of HPA axis and 5-HT system activation.

Perturbing the Hypothalamic-Pituitary-Adrenal Axis: A Mathematical Model for Interpreting PTSD Assessment Tests

We use a dynamical systems model of the hypothalamic-pituitary-adrenal (HPA) axis to understand the mechanisms underlying clinical protocols used to probe patient stress response. Specifically, we address dexamethasone (DEX) and ACTH challenge tests, which probe pituitary and adrenal gland responses, respectively. We show that some previously observed features and experimental responses can arise from a bistable mathematical model containing two steady-states, rather than relying on specific and permanent parameter changes due to physiological disruption. Moreover, we show that the timing of a perturbation relative to the intrinsic oscillation of the HPA axis can affect challenge test responses. Conventional mechanistic hypotheses supported and refuted by the challenge tests are reexamined by varying parameters in our mathematical model associated with these hypotheses. We show that (a) adrenal hyposensitivity can give rise to the responses seen in ACTH challenge tests and (b) enhanced cortisol-mediated suppression of the pituitary in subjects with PTSD is not necessary to explain the responses observed in DEX stress tests. We propose a new two-stage DEX/external stressor protocol to more clearly distinguish between the conventional hypothesis of enhanced suppression of the pituitary and bistable dynamics hypothesized in our model.

SD Meets OR: A New Synergy to Address Policy Problems

We reflect on our past seven years of collaboration to develop systems models of U.S. higher education and scientific workforce development. Based on three recent modeling examples, we offer a methodological proposition that many traditional Operations Research (OR) models can be improved by including feedback processes as is commonly done in system dynamics (SD) modeling. Such models, even if simple and approximate, can be powerful, insightful, easy to communicate, and effective. While these modeling examples may not follow conventional SD or OR modeling, they benefit from and contribute to both schools of modeling. We argue that to build such synergy, modeling teams should be willing to create models building on the strengths of each school of modeling.

The HPA axis and ethanol: a synthesis of mathematical modelling and experimental observations

Stress and alcohol use are interrelated-stress contributes to the initiation and upholding of alcohol use and alcohol use alters the way we perceive and respond to stress. Intricate mechanisms through which ethanol alters the organism's response to stress remain elusive. We have developed a stoichiometric network model to succinctly describe neurochemical transformations underlying the stress response axis and use numerical simulations to model ethanol effects on complex daily changes of blood levels of cholesterol, 6 peptide and 8 steroid hormones. Modelling suggests that ethanol alters the dynamical regulation of hypothalamic-pituitary-adrenal (HPA) axis activity by affecting the amplitude of ultradian oscillations of HPA axis hormones, which defines the threshold with respect to which the response to stress is being set. These effects are complex-low/moderate acute ethanol challenge (<8 mM) may reduce, leave unaltered or increase the amplitude of ultradian cortisol (CORT) oscillations, giving rise to an intricate response at the organism level, offering also a potential explanation as to why apparently discordant results were observed in experimental studies. In contrast, high-dose acute ethanol challenge (>8 mM) increases instantaneous CORT levels and the amplitude of ultradian CORT oscillations in a dose-dependent manner, affecting the HPA axis activity also during the following day(s). Chronic exposure to ethanol qualitatively changes the HPA axis dynamics, whereas ethanol at intoxicating levels shuts down this dynamic regulation mechanism. Mathematical modelling gives a quantitative biology-based framework that can be used for predicting how the integral HPA axis response is perturbed by alcohol.

Potential Glucocorticoid and Mineralocorticoid Effects of Nine Organophosphate Flame Retardants

Organophosphate flame retardants (OPFRs), as alternatives of polybrominated diphenyl ethers (PBDEs), have been frequently detected in the environment and biota, and could pose adverse effects on organisms. However, information on the potential endocrine disruption of OPFRs, especially their effects on steroid hormone receptors, such as glucocorticoid and mineralocorticoid receptors (GR/MR), is limited. In this study, the dual-luciferase reporter gene assay via GR/MR and a H295R steroidogenesis assay were employed to evaluate the endocrine disruption of nine OPFRs. We found TMPP, TPHP, and TDBPP exhibited both GR and MR antagonistic activities, while TNBP and TDCIPP only showed MR antagonistic property within a concentration range of 10^-8 to 10^-5 mol/L(M). In the H295R steroidogenesis assay, the fold changes of eight steroidogenic genes in response to OPFRs were further studied. We found CYP17,CYP21, and CYP11B1 expression were significantly down-regulated following TMPP, TPHP, or TDBPP exposure at a concentration of 2 × 10^-6 M. Meanwhile TMPP decreased the production of cortisol and TDBPP down-regulated the secretion of aldosterone. Our results indicate that some OPFRs can interact with GR and MR, and have the potential to disturb steroidogenesis. Data provided here will be helpful to comprehensively understand the potential endocrine disruption of OPFRs.

A Dynamic Model of Post-Traumatic Stress Disorder for Military Personnel and Veterans

Post-traumatic stress disorder (PTSD) stands out as a major mental illness; however, little is known about effective policies for mitigating the problem. The importance and complexity of PTSD raise critical questions: What are the trends in the population of PTSD patients among military personnel and veterans in the postwar era? What policies can help mitigate PTSD? To address these questions, we developed a system dynamics simulation model of the population of military personnel and veterans affected by PTSD. The model includes both military personnel and veterans in a “system of systems.” This is a novel aspect of our model, since many policies implemented at the military level will potentially influence (and may have side effects on) veterans and the Department of Veterans Affairs. The model is first validated by replicating the historical data on PTSD prevalence among military personnel and veterans from 2000 to 2014 (datasets from the Department of Defense, the Institute of Medicine, the Department of Veterans Affairs, and other sources). The model is then used for health policy analysis. Our results show that, in an optimistic scenario based on the status quo of deployment to intense/combat zones, estimated PTSD prevalence among veterans will be at least 10% during the next decade. The model postulates that during wars, resiliency-related policies are the most effective for decreasing PTSD. In a postwar period, current health policy interventions (e.g., screening and treatment) have marginal effects on mitigating the problem of PTSD, that is, the current screening and treatment policies must be revolutionized to have any noticeable effect. Furthermore, the simulation results show that it takes a long time, on the order of 40 years, to mitigate the psychiatric consequences of a war. Policy and financial implications of the findings are discussed.

Dynamic transitions in a model of the hypothalamic-pituitary-adrenal axis

Dynamic properties of a nonlinear five-dimensional stoichiometric model of the hypothalamic-pituitary-adrenal (HPA) axis were systematically investigated. Conditions under which qualitative transitions between dynamic states occur are determined by independently varying the rate constants of all reactions that constitute the model. Bifurcation types were further characterized using continuation algorithms and scale factor methods. Regions of bistability and transitions through supercritical Andronov-Hopf and saddle loop bifurcations were identified. Dynamic state analysis predicts that the HPA axis operates under basal (healthy) physiological conditions close to an Andronov-Hopf bifurcation. Dynamic properties of the stress-control axis have not been characterized experimentally, but modelling suggests that the proximity to a supercritical Andronov-Hopf bifurcation can give the HPA axis both, flexibility to respond to external stimuli and adjust to new conditions and stability, i.e., the capacity to return to the original dynamic state afterwards, which is essential for maintaining homeostasis. The analysis presented here reflects the properties of a low-dimensional model that succinctly describes neurochemical transformations underlying the HPA axis. However, the model accounts correctly for a number of experimentally observed properties of the stress-response axis. We therefore regard that the presented analysis is meaningful, showing how in silico investigations can be used to guide the experimentalists in understanding how the HPA axis activity changes under chronic disease and/or specific pharmacological manipulations.

Depression as a systemic syndrome: mapping the feedback loops of major depressive disorder

BACKGROUND

Depression is a complex public health problem with considerable variation in treatment response. The systemic complexity of depression, or the feedback processes among diverse drivers of the disorder, contribute to the persistence of depression. This paper extends prior attempts to understand the complex causal feedback mechanisms that underlie depression by presenting the first broad boundary causal loop diagram of depression dynamics.

METHOD

We applied qualitative system dynamics methods to map the broad feedback mechanisms of depression. We used a structured approach to identify candidate causal mechanisms of depression in the literature. We assessed the strength of empirical support for each mechanism and prioritized those with support from validation studies. Through an iterative process, we synthesized the empirical literature and created a conceptual model of major depressive disorder.

RESULTS

The literature review and synthesis resulted in the development of the first causal loop diagram of reinforcing feedback processes of depression. It proposes candidate drivers of illness, or inertial factors, and their temporal functioning, as well as the interactions among drivers of depression. The final causal loop diagram defines 13 key reinforcing feedback loops that involve nine candidate drivers of depression.

CONCLUSIONS

Future research is needed to expand upon this initial model of depression dynamics. Quantitative extensions may result in a better understanding of the systemic syndrome of depression and contribute to personalized methods of evaluation, prevention and intervention.