Computational modeling of the synergistic role of GCN2 and the HPA axis in regulating the integrated stress response in the central circadian timing system.

The circadian timing system and integrated stress response (ISR) systems are fundamental regulatory mechanisms that maintain body homeostasis. The central circadian pacemaker in the suprachiasmatic nucleus (SCN) governs daily rhythms through interactions with peripheral oscillators via the hypothalamus-pituitary-adrenal (HPA) axis. On the other hand, ISR signaling is pivotal for preserving cellular homeostasis in response to physiological changes. Notably, disrupted circadian rhythms are observed in cases of impaired ISR signaling. In this work, we examine the potential interplay between the central circadian system and the ISR, mainly through the SCN and HPA axis. We introduce a semimechanistic mathematical model to delineate SCN's capacity for indirectly perceiving physiological stress through glucocorticoid-mediated feedback from the HPA axis and orchestrating a cellular response via the ISR mechanism. Key components of our investigation include evaluating general control nonderepressible 2 (GCN2) expression in the SCN, the effect of physiological stress stimuli on the HPA axis, and the interconnected feedback between the HPA and SCN. Simulation revealed a critical role for GCN2 in linking ISR with circadian rhythms. Experimental findings have demonstrated that a Gcn2 deletion in mice leads to rapid re-entrainment of the circadian clock following jetlag as well as to an elongation of the circadian period. These phenomena are well replicated by our model, which suggests that both the swift re-entrainment and prolonged period can be ascribed to a reduced robustness in neuronal oscillators. Our model also offers insights into phase shifts induced by acute physiological stress and the alignment/misalignment of physiological stress with external light-dark cues. Such understanding aids in strategizing responses to stressful events, such as nutritional status changes and jetlag.NEW & NOTEWORTHY This study is the first theoretical work to investigate the complex interaction between integrated stress response (ISR) sensing and central circadian rhythm regulation, encompassing the suprachiasmatic nucleus (SCN) and hypothalamus-pituitary-adrenal (HPA) axis. The findings carry implications for the development of dietary or pharmacological interventions aimed at facilitating recovery from stressful events, such as jetlag. Moreover, they provide promising prospects for potential therapeutic interventions that target circadian rhythm disruption and various stress-related disorders.

Design and Validation of Experimental Setup for Cell Spheroid Radiofrequency-Induced Heating.

While hyperthermia has been shown to induce a variety of cytotoxic and sensitizing effects on cancer tissues, the thermal dose-effect relationship is still not well quantified, and it is still unclear how it can be optimally combined with other treatment modalities. Additionally, it is speculated that different methods of applying hyperthermia, such as water bath heating or electromagnetic energy, may have an effect on the resulting biological mechanisms involved in cell death or in sensitizing tumor cells to other oncological treatments. In order to further quantify and characterize hyperthermia treatments on a cellular level, in vitro experiments shifted towards the use of 3D cell spheroids. These are in fact considered a more representative model of the cell environment when compared to 2D cell cultures. In order to perform radiofrequency (RF)-induced heating in vitro, we have recently developed a dedicated electromagnetic field applicator. In this study, using this applicator, we designed and validated an experimental setup which can heat 3D cell spheroids in a conical polypropylene vial, thus providing a reliable instrument for investigating hyperthermia effects at the cellular scale.

Circadian Effects of Drug Responses.

Circadian rhythms describe physiological systems that repeat themselves with a cycle of approximately 24 h. Our understanding of the cellular and molecular origins of these oscillations has improved dramatically, allowing us to appreciate the significant role these oscillations play in maintaining physiological homeostasis. Circadian rhythms allow living organisms to predict and efficiently respond to a dynamically changing environment, set by repetitive day/night cycles. Since circadian rhythms underlie almost every aspect of human physiology, it is unsurprising that they also influence the response of a living organism to disease, stress, and therapeutics. Therefore, not only do the mechanisms that maintain health and disrupt homeostasis depend on our internal circadian clock, but also the way drugs are perceived and function depends on these physiological rhythms. We present a holistic view of the therapeutic process, discussing components such as disease state, pharmacokinetics, and pharmacodynamics, as well as adverse reactions that are critically affected by circadian rhythms. We outline challenges and opportunities in moving toward personalized medicine approaches that explore and capitalize on circadian rhythms for the benefit of the patient.

Does seasonality of the microbiota contribute to the seasonality of acute gout flare?

Gout, the most common inflammatory arthritis worldwide, is an auto-inflammatory metabolic disease that leads to monosodium urate crystal deposition. Hyperuricaemia is a significant risk factor for the development of gout; however, hyperuricaemia alone is not sufficient to induce gout.Gout flares have circadian rhythms. Gout flares vary during the day and have strong seasonality, with flares being more common in the spring. The reasons for the predominance of flares in the spring are unclear since serum urate (SU) levels show seasonal variation; however, SU levels are highest in the summer.Immune function varies significantly throughout the year, with enhanced immune responses increasing during the winter. In addition, chronic disruption of circadian rhythms is associated with metabolic syndrome and diseases driven by metabolism. The most telling example relates to Xanthine oxidase (XOD/XDH). The analysis of XOD/XDH established its circadian regulation and demonstrated that inhibition of the activity of XOD is characterised by distinct, crossregulating diurnal/seasonal patterns of activity.The gastrointestinal microbiota of gout patients is highly distinct from healthy individuals. In a small series of gout patients, Bacteroides caccae and Bacteroides xylanisolvens were found to be enriched. Bacteroidales levels were highest during the spring and summer, and loading values were highest in the spring.Our review discusses gout's circadian rhythm and seasonality, possible influences of the microbiome on gout due to our new knowledge that Bacteroidales levels were highest during spring when gout is most common, and potential opportunities for treatment based on our current understanding of this interaction.

Patient-derived breast model repository, a tool for hyperthermia treatment planning and applicator design.

OBJECTIVE: The addition of hyperthermia in the treatment of intact breast cancer with the aim to improve local response is currently in a research phase. First, optimal hyperthermia devices need to be developed, for which a diverse, anatomically and pathologically accurate set of patient models is necessary. METHODS: To investigate the effects of inter-subject variations on hyperthermia treatment plans, we generated a repository of 22 anatomically and pathologically diverse patient models based on MR images of breast cancer patients. Hyperthermia treatment plans were generated for the 22 models using a generic theoretical phased array hyperthermia applicator. RESULTS: Good temperature coverage was achieved in the vast majority of the models, with median values for T10 = 43.5°C (41.9-43.8°C), T50 = 42.5°C (41.3-43.3°C), and T90 = 41.3°C (39.8-42.6°C) under the condition that the maximum temperature increase in the patient is limited to 44°C. CONCLUSIONS: For future development of hyperthermia devices and treatment methods, a repository with a sufficiently large number of representative patient models, such as the one provided in this study, should be used to ensure applicability to a wide variety of patients. This repository is therefore made publicly available.

Towards a comprehensive assessment of QSP models: what would it take?

Quantitative Systems Pharmacology (QSP) has emerged as a powerful ensemble of approaches aiming at developing integrated mathematical and computational models elucidating the complex interactions between pharmacology, physiology, and disease. As the field grows and matures its applications expand beyond the boundaries of research and development and slowly enter the decision making and regulatory arenas. However, widespread acceptance and eventual adoption of a new modeling approach requires assessment criteria and quantifiable metrics that establish credibility and increase confidence in model predictions. QSP aims to provide an integrated understanding of pathology in the context of therapeutic interventions. Because of its ambitious nature and the fact that QSP emerged in an uncoordinated manner as a result of activities distributed across organizations and academic institutions, high entropy characterizes the tools, methods, and computational methodologies and approaches used. The eventual acceptance of QSP model predictions as supporting material for an application to a regulatory agency will require that two key aspects are considered: (1) increase confidence in the QSP framework, which drives standardization and assessment; and (2) careful articulation of the expectations. Both rely heavily on our ability to rigorously and consistently assess QSP models. In this manuscript, we wish to discuss the meaning and purpose of such an assessment in the context of QSP model development and elaborate on the differentiating features of QSP that render such an endeavor challenging. We argue that QSP establishes a conceptual, integrative framework rather than a specific and well-defined computational methodology. QSP elicits the use of a wide variety of modeling and computational methodologies optimized with respect to specific applications and available data modalities, which exceed the data structures employed by chemometrics and PK/PD models. While the range of options fosters creativity and promises to substantially advance our ability to design pharmaceutical interventions rationally and optimally, our expectations of QSP models need to be clearly articulated and agreed on, with assessment emphasizing the scope of QSP studies rather than the methods used. Nevertheless, QSP should not be considered an independent approach, rather one of many in the broader continuum of computational models.

Two heads are better than one: current landscape of integrating QSP and machine learning : An ISoP QSP SIG white paper by the working group on the integration of quantitative systems pharmacology and machine learning.

Quantitative systems pharmacology (QSP) modeling is applied to address essential questions in drug development, such as the mechanism of action of a therapeutic agent and the progression of disease. Meanwhile, machine learning (ML) approaches also contribute to answering these questions via the analysis of multi-layer 'omics' data such as gene expression, proteomics, metabolomics, and high-throughput imaging. Furthermore, ML approaches can also be applied to aspects of QSP modeling. Both approaches are powerful tools and there is considerable interest in integrating QSP modeling and ML. So far, a few successful implementations have been carried out from which we have learned about how each approach can overcome unique limitations of the other. The QSP + ML working group of the International Society of Pharmacometrics QSP Special Interest Group was convened in September, 2019 to identify and begin realizing new opportunities in QSP and ML integration. The working group, which comprises 21 members representing 18 academic and industry organizations, has identified four categories of current research activity which will be described herein together with case studies of applications to drug development decision making. The working group also concluded that the integration of QSP and ML is still in its early stages of moving from evaluating available technical tools to building case studies. This paper reports on this fast-moving field and serves as a foundation for future codification of best practices.

Design and Characterization of an RF Applicator for In Vitro Tests of Electromagnetic Hyperthermia.

The evaluation of the biological effects of therapeutic hyperthermia in oncology and the precise quantification of thermal dose, when heating is coupled with radiotherapy or chemotherapy, are active fields of research. The reliable measurement of hyperthermia effects on cells and tissues requires a strong control of the delivered power and of the induced temperature rise. To this aim, we have developed a radiofrequency (RF) electromagnetic applicator operating at 434 MHz, specifically engineered for in vitro tests on 3D cell cultures. The applicator has been designed with the aid of an extensive modelling analysis, which combines electromagnetic and thermal simulations. The heating performance of the built prototype has been validated by means of temperature measurements carried out on tissue-mimicking phantoms and aimed at monitoring both spatial and temporal temperature variations. The experimental results demonstrate the capability of the RF applicator to produce a well-focused heating, with the possibility of modulating the duration of the heating transient and controlling the temperature rise in a specific target region, by simply tuning the effectively supplied power.

Simultaneous ThermoBrachytherapy: Electromagnetic Simulation Methods for Fast and Accurate Adaptive Treatment Planning.

The combination of interstitial hyperthermia treatment (IHT) with high dose rate brachytherapy (HDR-BT) can improve clinical outcomes since it highly enhances the efficiency of cell kill, especially when applied simultaneously. Therefore, we have developed the ThermoBrachy applicators. To effectively apply optimal targeted IHT, treatment planning is considered essential. However, treatment planning in IHT is rarely applied as it is regarded as difficult to accurately calculate the deposited energy in the tissue in a short enough time for clinical practice. In this study, we investigated various time-efficient methods for fast computation of the electromagnetic (EM) energy deposition resulting from the ThermoBrachy applicators. Initially, we investigated the use of an electro-quasistatic solver. Next, we extended our investigation to the application of geometric simplifications. Furthermore, we investigated the validity of the superpositioning principle, which can enable adaptive treatment plan optimization without the need for continuous recomputation of the EM field. Finally, we evaluated the accuracy of the methods by comparing them to the golden standard Finite-Difference Time-Domain calculation method using gamma-index analysis. The simplifications considerably reduced the computation time needed, improving from >12 h to a few seconds. All investigated methods showed excellent agreement with the golden standard by showing a >99% passing rate with 1%/0.5 mm Dose Difference and Distance-to-Agreement criteria. These results allow the proposed electromagnetic simulation method to be used for fast and accurate adaptive treatment planning.

Design of the novel ThermoBrachy applicators enabling simultaneous interstitial hyperthermia and high dose rate brachytherapy.

OBJECTIVE: In High Dose Rate Brachytherapy for prostate cancer there is a need for a new way of increasing cancer cell kill in combination with a stable dose to the organs at risk. In this study, we propose a novel ThermoBrachy applicator that offers the unique ability to apply interstitial hyperthermia while simultaneously serving as an afterloading catheter for high dose rate brachytherapy for prostate cancer. This approach achieves a higher thermal enhancement ratio than in sequential application of radiation and hyperthermia and has the potential to decrease the overall treatment time. METHODS: The new applicator uses the principle of capacitively coupled electrodes. We performed a proof of concept experiment to demostrate the feasibility of the proposed applicator. Moreover, we used electromagnetic and thermal simulations to evaluate the power needs and temperature homogeneity in different tissues. Furthermore we investigated whether dynamic phase and amplitude adaptation can be used to improve longitudinal temperature control. RESULTS: Simulations demonstrate that the electrodes achieve good temperature homogeneity in a homogenous phantom when following current applicator spacing guidelines. Furthermore, we demonstrate that by dynamic phase and amplitude adaptation provides a great advancement for further adaptability of the heating pattern. CONCLUSIONS: This newly designed ThermoBrachy applicator has the potential to revise the interest in interstitial thermobrachytherapy, since the simultaneous application of radiation and hyperthermia enables maximum thermal enhancement and at maximum efficiency for patient and organization.

Pathway-level analysis of genome-wide circadian dynamics in diverse tissues in rat and mouse.

A computational framework is developed to enable the characterization of genome-wide, multi-tissue circadian dynamics at the level of "functional groupings of genes" defined in the context of signaling, cellular/genetic processing and metabolic pathways in rat and mouse. Our aim is to identify how individual genes come together to generate orchestrated rhythmic patterns and how these may vary within and across tissues. We focus our analysis on four tissues (adipose, liver, lung, and muscle). A genome-wide pathway-centric analysis enables us to develop a comprehensive picture on how the observed circadian variation at the individual gene level, orchestrates functional responses at the pathway level. Such pathway-based "meta-data" analysis enables the rational integration and comparison across platforms and/or experimental designs evaluating emergent dynamics, as opposed to comparisons of individual elements. One of our key findings is that when considering the dynamics at the pathway level, a complex behavior emerges. Our work proposes that tissues tend to coordinate gene's circadian expression in a way that optimizes tissue-specific pathway activity, depending of each tissue's broader role in homeostasis.

Mathematical modeling informs the impact of changes in circadian rhythms and meal patterns on insulin secretion.

Disruption of circadian rhythms has been associated with metabolic syndromes, including obesity and diabetes. A variety of metabolic activities are under circadian modulation, as local and global clock gene knockouts result in glucose imbalance and increased risk of metabolic diseases. Insulin release from the pancreatic ß cells exhibits daily variation, and recent studies have found that insulin secretion, not production, is under circadian modulation. As consideration of daily variation in insulin secretion is necessary to accurately describe glucose-stimulated insulin secretion, we describe a mathematical model that incorporates the circadian modulation via insulin granule trafficking. We use this model to understand the effect of oscillatory characteristics on insulin secretion at different times of the day. Furthermore, we integrate the dynamics of clock genes under the influence of competing environmental signals (light/dark cycle and feeding/fasting cycle) and demonstrate how circadian disruption and meal size distribution change the insulin secretion pattern over a 24-h day.

The physiological significance of the circadian dynamics of the HPA axis: Interplay between circadian rhythms, allostasis and stress resilience.

Circadian time-keeping mechanisms preserve homeostasis by synchronizing internal physiology with predictable variations in the environment and temporally organize the activation of physiological signaling mechanisms to promote survival and optimize the allocation of energetic resources. In this paper, we highlight the importance of the robust circadian dynamics of allostatic mediators, with a focus on the hypothalamic-pituitary-adrenal (HPA) axis, for the optimal regulation of host physiology and in enabling organisms to adequately respond and adapt to physiological stressors. We review studies showing how the chronic disruption of circadian rhythms can result in the accumulation of allostatic load, which impacts the appropriate functioning of physiological systems and diminishes the resilience of internal systems to adequately respond to subsequent stressors. A careful consideration of circadian rhythm dynamics leads to a more comprehensive characterization of individual variability in allostatic load and stress resilience. Finally, we suggest that the restoration of circadian rhythms after pathological disruption can enable the re-engagement of allostatic mechanisms and re-establish stress resilience.

Mathematical analysis of circadian disruption and metabolic re-entrainment of hepatic gluconeogenesis: the intertwining entraining roles of light and feeding.

The circadian rhythms influence the metabolic activity from molecular level to tissue, organ, and host level. Disruption of the circadian rhythms manifests to the host's health as metabolic syndromes, including obesity, diabetes, and elevated plasma glucose, eventually leading to cardiovascular diseases. Therefore, it is imperative to understand the mechanism behind the relationship between circadian rhythms and metabolism. To start answering this question, we propose a semimechanistic mathematical model to study the effect of circadian disruption on hepatic gluconeogenesis in humans. Our model takes the light-dark cycle and feeding-fasting cycle as two environmental inputs that entrain the metabolic activity in the liver. The model was validated by comparison with data from mice and rat experimental studies. Formal sensitivity and uncertainty analyses were conducted to elaborate on the driving forces for hepatic gluconeogenesis. Furthermore, simulating the impact of Clock gene knockout suggests that modification to the local pathways tied most closely to the feeding-fasting rhythms may be the most efficient way to restore the disrupted glucose metabolism in liver.

A framework for 2-stage global sensitivity analysis of GastroPlus™ compartmental models.

Parameter sensitivity and uncertainty analysis for physiologically based pharmacokinetic (PBPK) models are becoming an important consideration for regulatory submissions, requiring further evaluation to establish the need for global sensitivity analysis. To demonstrate the benefits of an extensive analysis, global sensitivity was implemented for the GastroPlus™ model, a well-known commercially available platform, using four example drugs: acetaminophen, risperidone, atenolol, and furosemide. The capabilities of GastroPlus were expanded by developing an integrated framework to automate the GastroPlus graphical user interface with AutoIt and for execution of the sensitivity analysis in MATLAB®. Global sensitivity analysis was performed in two stages using the Morris method to screen over 50 parameters for significant factors followed by quantitative assessment of variability using Sobol's sensitivity analysis. The 2-staged approach significantly reduced computational cost for the larger model without sacrificing interpretation of model behavior, showing that the sensitivity results were well aligned with the biopharmaceutical classification system. Both methods detected nonlinearities and parameter interactions that would have otherwise been missed by local approaches. Future work includes further exploration of how the input domain influences the calculated global sensitivity measures as well as extending the framework to consider a whole-body PBPK model.

Pharmacokinetics and Pharmacodynamics of Curcumin in regulating anti-inflammatory and epigenetic gene expression.

Chronic inflammation is a key driver of cancer development. Nitrite levels, which are regulated by inducible nitric oxide synthase (iNOS), play a critical role in inflammation. While the anti-oxidant and anti-inflammatory effects of curcumin, a natural product present in the roots of Curcuma longa have been studied widely, the acute pharmacokinetics (PK) and pharmacodynamics (PD) of curcumin in suppressing pro-inflammatory markers and epigenetic modulators remain unclear. This study evaluated the PK and PD of curcumin-induced suppression of lipopolysaccharide (LPS)-mediated inflammation in rat lymphocytes. LPS was administered intravenously either alone or with curcumin to female Sprague-Dawley rats. Plasma samples were analysed for curcumin concentration and mRNA expression was quantified in lymphocytes. The relative gene expression of several inflammatory and epigenetic modulators was analysed. To investigate the relationship between curcumin concentration and iNOS, TNF-α, and IL-6 gene expression, PK/PD modeling using Jusko's indirect response model (IDR) integrating transit compartments (TC) describing the delayed response was conducted. The concentration-time profile of curcumin exhibited a bi-exponential decline, which was well described by a two-compartmental pharmacokinetic model. Importantly the results demonstrate that LPS induced gene expression of pro-inflammatory markers in lymphocytes, with peak expression at approximately 3 h and curcumin suppressed the gene expression in animals administered with LPS. These effects were well captured using the IDR model and an IDR model with the transit compartments. In summary, the PK/PD modeling approach could potentially provide a robust quantitative framework for evaluating the acute anti-inflammatory and epigenetic effects of curcumin in future clinical trials.

Concomitant alterations of metabolic parameters, cardiovascular risk factors and altered cortisol secretion in patients with adrenal incidentalomas during prolonged follow-up.

OBJECTIVE: Adrenal incidentalomas (AI) are associated with metabolic and hormonal abnormalities, most commonly autonomous cortisol secretion (ACS). Data regarding alterations of insulin resistance (IR) and ACS after prolonged follow-up are limited. We investigated the evolution of IR, cortisol secretion and ACS development in patients with AI during prolonged follow-up. DESIGN: Prospective study in a tertiary hospital. PATIENTS AND MEASUREMENTS: Seventy-one patients with AI [51 nonfunctioning (NFAI) and 20 ACS] and 5·54 ± 1·7 years follow-up underwent testing for ACS and oral glucose tolerance test to determine IR indices and adrenal imaging. RESULTS: At follow-up, 16/51 (31%) NFAI patients converted to ACS, while two with previous ACS reverted to NFAI; 21% (7/33) of patients who did not covert to ACS exhibited high urinary-free cortisol (H-UFC) levels. All AI patients developed deterioration of IR irrespective of their cortisol secretory status. Eight patients developed newly diagnosed type 2 diabetes (9·8% NFAI and 15% ACS, respectively) and 14 IR (17·6% NFAI and 25% ACS, respectively). Adenoma size increased from 2·1 ± 0·8 to 2·3 ± 0·8 cm, whereas IR correlated with postdexamethasone cortisol level and adenoma size increase. IR showed an incremental continuum trend from normal UFC (Ν-UFC), to H-UFC, C-ACS and ACS patients. CONCLUSIONS: New-onset ACS developed in 31% patients with NFAI, whereas 21% of NFAI patients had H-UFC levels. All AI patients as a group and the subgroups of N-UFC, H-UFC, C-ACS and ACS patients developed deterioration of metabolic parameters during follow-up that was more prominent in ACS patients.

Pharmacokinetics and Pharmacodynamics of the Triterpenoid Ursolic Acid in Regulating the Antioxidant, Anti-inflammatory, and Epigenetic Gene Responses in Rat Leukocytes.

The triterpenoid ursolic acid (UA) has been proposed as a potential cancer chemopreventive agent in many preclinical and clinical studies. In the present work, we aimed to characterize the pharmacokinetics (PK) of UA and to quantitatively assess the antioxidative and anti-inflammatory effects of UA, which are potentially linked to its chemopreventive efficacy. UA was administered intravenously (i.v., 20 mg/kg) or by oral gavage (100 mg/kg) to male Sprague-Dawley rats, and blood samples were collected at a series of designated time points. The plasma concentration of UA was determined using a validated liquid chromatography-mass spectrometry (LC-MS) approach. A biexponential decline in the UA plasma concentration was observed after i.v. dosing and was fitted to a two-compartmental model. The expression levels of phase II drug metabolism (DM)/antioxidant genes and the inflammatory iNos gene in corresponding treatment arms were measured using qPCR as a pharmacodynamic (PD) marker. The expression of phase II DM/antioxidant genes increased and peaked approximately 3 h after 20 mg/kg UA treatment. In a lipopolysaccharide (LPS)-induced acute inflammation model, UA inhibited LPS-stimulated iNos expression and that of the epigenetic markers the DNA methyltransferases (DNMTs) and histone deacetylases (HDACs) in leukocytes. A PK-PD model using Jusko's indirect response model (IDR) with transition compartments (TC) was established to describe the time delay and magnitude of the gene expression elicited by UA. The PK-PD model provided reasonable fitting linking the plasma concentration of UA simultaneously with the PD response based on leukocyte mRNA expression. Overall, our results indicate that UA is effective at inducing various phase II DM/antioxidant genes and inhibiting pro-inflammatory genes in vivo. This PK-PD modeling approach may provide a conceptual framework for the future clinical evaluation of dietary chemopreventive agents in humans.

On the analysis of complex biological supply chains: From Process Systems Engineering to Quantitative Systems Pharmacology.

The use of models in biology has become particularly relevant as it enables investigators to develop a mechanistic framework for understanding the operating principles of living systems as well as in quantitatively predicting their response to both pathological perturbations and pharmacological interventions. This application has resulted in a synergistic convergence of systems biology and pharmacokinetic-pharmacodynamic modeling techniques that has led to the emergence of quantitative systems pharmacology (QSP). In this review, we discuss how the foundational principles of chemical process systems engineering inform the progressive development of more physiologically-based systems biology models.

The role of the hypothalamic-pituitary-adrenal axis in modulating seasonal changes in immunity.

Seasonal changes in environmental conditions are accompanied by significant adjustment of multiple biological processes. In temperate regions, the day fraction, or photoperiod, is a robust environmental cue that synchronizes seasonal variations in neuroendocrine and metabolic function. In this work, we propose a semimechanistic mathematical model that considers the influence of seasonal photoperiod changes as well as cellular and molecular adaptations to investigate the seasonality of immune function. Our model predicts that the circadian rhythms of cortisol, our proinflammatory mediator, and its receptor exhibit seasonal differences in amplitude and phase, oscillating at higher amplitudes in the winter season with peak times occurring later in the day. Furthermore, the reduced photoperiod of winter coupled with seasonal alterations in physiological activity induces a more exacerbated immune response to acute stress, simulated in our studies as the administration of an acute dose of endotoxin. Our findings are therefore in accordance with experimental data that reflect the predominance of a proinflammatory state during the winter months. These changes in circadian rhythm dynamics may play a significant role in the seasonality of disease incidence and regulate the diurnal and seasonal variation of disease symptom severity.