Assessing Fear of Thyroid Cancer in the General U.S. Population: A Cross-Sectional Study.

Background: This study aimed to measure fear of thyroid cancer in the general U.S. population and identify factors associated with a high level of thyroid cancer-specific fear that may contribute to overtreatment. Methods: We conducted a cross-sectional survey using Prolific Academic Ltd.®, an online survey platform. The survey was administered in August 2020 to English speaking adults (>17 years) in the United States who were registered with Prolific. The target sample was stratified to represent the demographics of the U.S. population. A validated, eight-item breast cancer fear scale was adapted to measure thyroid cancer-specific fear. Multivariate logistic regression identified factors significantly associated with high levels of thyroid cancer-specific fear. Results: Of the 1136 respondents (94.3% eligibility), 50.4% were female, 74.1% White, and the mean age was 45 years (SD = 16 years). Overall, 47.5% of respondents had high levels of thyroid cancer-specific fear. Multivariate regression demonstrated that age <40 years (OR = 2.46 vs. 65+ [95% confidence interval {CI} = 1.60-3.80]) and female gender (OR = 1.48 vs. male [CI = 1.13-1.93]) were associated with high levels of thyroid cancer fear. Believing thyroid cancer (OR = 2.71 [CI = 1.99-3.69]) and cancer in general are serious (OR = 1.53 [CI = 1.13-2.08]) were also associated with high levels of thyroid cancer fear. Respondents who overestimated thyroid cancer incidence (OR = 1.64 [CI = 1.25-2.13]) and believed they had a high chance of developing cancer (OR = 1.70 [CI = 1.19-2.42]) were also more likely to have high fear of thyroid cancer. Conclusion: Thyroid cancer-specific fear is prevalent in U.S. adults particularly in females and those younger than 40 years. Because disease-specific fear is associated with overtreatment, targeted education about the seriousness, incidence, and risk factors for developing thyroid cancer may decrease public fear and possibly overtreatment related to "scared decision-making."

Macrophage circadian rhythms are differentially affected based on stimuli.

Macrophages are white blood cells that play disparate roles in homeostasis and immune responses. They can reprogram their phenotypes to pro-inflammatory (M1) or anti-inflammatory (M2) states in response to their environment. About 8-15% of the macrophage transcriptome has circadian oscillations, including genes closely related to their functioning. As circadian rhythms are associated with cellular phenotypes, we hypothesized that polarization of macrophages to opposing subtypes might differently affect their circadian rhythms. We tracked circadian rhythms in RAW 264.7 macrophages using luminescent reporters. Cells were stably transfected with Bmal1:luc and Per2:luc reporters, representing positive and negative components of the molecular clock. Strength of rhythmicity, periods and amplitudes of time series were assessed using multiple approaches. M1 polarization decreased amplitudes and rhythmicities of Bmal1:luc and Per2:luc, but did not significantly affect periods, while M2 polarization increased periods but caused no substantial alterations to amplitudes or rhythmicity. As macrophage phenotypes are also altered in the presence of cancer cells, we tested circadian effects of conditioned media from mouse breast cancer cells. Media from highly aggressive 4T1 cells caused loss of rhythmicity, while media from less aggressive EMT6 cells yielded no changes. As macrophages play roles in tumors, and oncogenic features are associated with circadian rhythms, we tested whether conditioned media from macrophages could alter circadian rhythms of cancer cells. Conditioned media from RAW 264.7 cells resulted in lower rhythmicities and periods, but higher amplitudes in human osteosarcoma, U2OS-Per2:luc cells. We show that phenotypic changes in macrophages result in altered circadian characteristics and suggest that there is an association between circadian rhythms and macrophage polarization state. Additionally, our data demonstrate that macrophages treated with breast cancer-conditioned media have circadian phenotypes similar to those of the M1 subtype, and cancer cells treated with macrophage-conditioned media have circadian alterations, providing insight to another level of cross-talk between macrophages and cancer.

Circadian Alterations Increase with Progression in a Patient-Derived Cell Culture Model of Breast Cancer.

Circadian rhythm disruption can elicit the development of various diseases, including breast cancer. While studies have used cell lines to study correlations between altered circadian rhythms and cancer, these models have different genetic backgrounds and do not mirror the changes that occur with disease development. Isogenic cell models can recapitulate changes across cancer progression. Hence, in this study, a patient-derived breast cancer model, the 21T series, was used to evaluate changes to circadian oscillations of core clock protein transcription as cells progress from normal to malignant states. Three cell lines were used: H16N2 (normal breast epithelium), 21PT (atypical ductal hyperplasia), and 21MT-1 (invasive metastatic carcinoma). The cancerous cells are both HER2+. We assessed the transcriptional profiles of two core clock proteins, BMAL1 and PER2, which represent a positive and negative component of the molecular oscillator. In the normal H16N2 cells, both genes possessed rhythmic mRNA oscillations with close to standard periods and phases. However, in the cancerous cells, consistent changes were observed: both genes had periods that deviated farther from normal and did not have an anti-phase relationship. In the future, mechanistic studies should be undertaken to determine the oncogenic changes responsible for the circadian alterations found.

Delays are Self-enhancing: An Explanation of the East-West Asymmetry in Recovery from Jetlag.

There is evidence in mammals that recovering from jetlag after westward travel is faster than after eastward travel. To understand why, mathematical models have been used, along with theories of entrainment rooted in experimental evidence. The most complete understanding relies on detailed mathematical modeling, so it is helpful to develop an intuition about why there is an east-west asymmetry. One such intuition is that humans have long periods and therefore recover better when they can delay. Although this is part of the reason, it does not explain why short-period mice also recover from westward travel faster. Our goal is to provide a simple intuition consistent with detailed mathematical theories, but which does not require mathematical expertise to follow. Here, we present the intuition that westward travel is easier to recover from because of a simple principle: delays are self-enhancing.

Nobiletin affects circadian rhythms and oncogenic characteristics in a cell-dependent manner.

The natural product nobiletin is a small molecule, widely studied with regard to its therapeutic effects, including in cancer cell lines and tumors. Recently, nobiletin has also been shown to affect circadian rhythms via their enhancement, resulting in protection against metabolic syndrome. We hypothesized that nobiletin's anti-oncogenic effects, such as prevention of cell migration and formation of anchorage independent colonies, are correspondingly accompanied by modulation of circadian rhythms. Concurrently, we wished to determine whether the circadian and anti-oncogenic effects of nobiletin differed across cancer cell lines. In this study, we assessed nobiletin's circadian and therapeutic characteristics to ascertain whether these effects depend on cell line, which here also varied in terms of baseline circadian rhythmicity. Three cell culture models where nobiletin's effects on cell proliferation and migration have been studied previously were evaluated: U2OS (bone osteosarcoma), which possesses robust circadian rhythms; MCF7 (breast adenocarcinoma), which has weak circadian rhythms; and MDA-MB-231 (breast adenocarcinoma), which is arrhythmic. We found that circadian, migration, and proliferative effects following nobiletin treatment were subtle in the U2OS and MCF7 cells. On the other hand, changes were clear in MDA-MB-231s, where nobiletin rescued rhythmicity and substantially reduced oncogenic features, specifically two-dimensional cell motility and anchorage-independent growth. Based on these results and those previously described, we posit that the effects of nobiletin are indeed cell-type dependent, and that a positive correlation may exist between nobiletin's circadian and therapeutic effects.

Chemical modulation of circadian rhythms and assessment of cellular behavior via indirubin and derivatives.

Circadian rhythms are critical regulators of many physiological and behavioral functions. The use and abilities of small molecules to affect oscillations have recently received significant attention. These manipulations can be reversible and tunable, and have been used to study various biological mechanisms and molecular properties. Here, we outline procedures for assessment of cellular circadian changes following treatment with small molecules, using luminescent reporters. We describe reporter generation, luminometry experiments, and data analysis. Protocols for studies of accompanying effects on cells, including motility, viability, and anchorage-independent proliferation assays are also presented. As examples, we use indirubin-3'-oxime and two derivatives, 5-iodo-indirubin-3'-oxime and 5-sulfonic acid-indirubin-3'-oxime. In this case study, we analyze effects of these compounds on Bmal1 and Per2 (positive and negative core circadian elements) oscillations and provide step-by-step protocols for data analysis, including removal of trends from raw data, period estimations, and statistical analysis. The reader is provided with detailed protocols, and guidance regarding selection of and alternative approaches.

Circadian oscillations persist in low malignancy breast cancer cells.

Epidemiological studies have shown that humans with altered circadian rhythms have higher cancer incidence, with breast cancer being one of the most cited examples. To uncover how circadian disruptions may be correlated with breast cancer and its development, prior studies have assessed the expression of BMAL1 and PER2 core clock genes via RT-qPCR and western blot analyses. These and our own low-resolution data show that BMAL1 and PER2 expression are suppressed and arrhythmic. We hypothesized that oscillations persist in breast cancer cells, but due to limitations of protocols utilized, cannot be observed. This is especially true where dynamic changes may be subtle. In the present work, we generated luciferase reporter cell lines representing high- and low-grade breast cancers to assess circadian rhythms. We tracked signals for BMAL1 and PER2 to determine whether and to what extent oscillations exist and provide initial correlations of circadian rhythm alterations with breast cancer aggression. In contrast to previous studies, where no oscillations were apparent in any breast cancer cell line, our luminometry data reveal that circadian oscillations of BMAL1 and PER2 in fact exist in the low-grade, luminal A MCF7 cells but are not present in high-grade, basal MDA-MB-231 cells. To our knowledge, this is the first evidence of core circadian clock oscillations in breast cancer cells. This work also suggests that circadian rhythms are further disrupted in more aggressive/high tumor grades of breast cancer, and that use of real time luminometry to study additional representatives of breast and other cancer subtypes is merited.

Analyses of BMAL1 and PER2 Oscillations in a Model of Breast Cancer Progression Reveal Changes With Malignancy.

From an epidemiological standpoint, disruptions to circadian rhythms have been shown to contribute to the development of various disease pathologies, including breast cancer. However, it is unclear how altered circadian rhythms are related to malignant transformations at the molecular level. In this article, a series of isogenic breast cancer cells representing disease progression was used to investigate the expression patterns of core circadian clock proteins BMAL1 and PER2. Our model is indicative of 4 stages of breast cancer and includes the following cells: MCF10A (non-malignant), MCF10AT.Cl2 (pre-malignant), MCF10Ca1h (well-differentiated, malignant), and MCF10Ca1a (poorly differentiated, malignant). While studies of circadian rhythms in cancer typically use low-resolution reverse transcription polymerase chain reaction assays, we also employed luciferase reporters BMAL1:Luc and PER2:Luc in real-time luminometry experiments. We found that across all 4 cancer stages, PER2 showed relatively stable oscillations compared with BMAL1. Period estimation using both wavelet-based and damped-sine-fitting methods showed that the periods are distributed over a wide circadian range and there is no clear progression in mean period as cancer severity progresses. Additionally, we used the K-nearest neighbors algorithm to classify the recordings according to cancer line, and found that cancer stages were largely differentiated from one another. Taken together, our data support that there are circadian discrepancies between normal and malignant cells, but it is difficult and insufficient to singularly use period evaluations to differentiate them. Future studies should employ other progressive disease models to determine whether these findings are representative across cancer types or are specific to this series.

Resynchronization Dynamics Reveal that the Ventral Entrains the Dorsal Suprachiasmatic Nucleus.

Although the suprachiasmatic nucleus (SCN) has long been considered the master circadian clock in mammals, the topology of the connections that synchronize daily rhythms among SCN cells is not well understood. We combined experimental and computational methods to infer the directed interactions that mediate circadian synchrony between regions of the SCN. We analyzed PERIOD2 (PER2) expression from SCN slices during and after treatment with tetrodotoxin, allowing us to map connections as cells resynchronized their daily cycling following blockade and restoration of cell-cell communication. Using automated analyses, we found that cells in the dorsal SCN stabilized their periods slower than those in the ventral SCN. A phase-amplitude computational model of the SCN revealed that, to reproduce the experimental results: (1) the ventral SCN had to be more densely connected than the dorsal SCN and (2) the ventral SCN needed strong connections to the dorsal SCN. Taken together, these results provide direct evidence that the ventral SCN entrains the dorsal SCN in constant conditions.

Inhibitory and excitatory networks balance cell coupling in the suprachiasmatic nucleus: A modeling approach.

Neuronal coupling contributes to circadian rhythms formation in the suprachiasmatic nucleus (SCN). While the neurotransmitter vasoactive intestinal polypeptide (VIP) is considered essential for synchronizing the oscillations of individual neurons, γ-aminobutyric acid (GABA) does not have a clear functional role despite being highly concentrated in the SCN. While most studies have examined the role of either GABA or VIP, our mathematical modeling approach explored their interplay on networks of SCN neurons. Tuning the parameters that control the release of GABA and VIP enabled us to optimize network synchrony, which was achieved at a peak firing rate during the subjective day of about 7Hz. Furthermore, VIP and GABA modulation could adjust network rhythm amplitude and period without sacrificing synchrony. We also performed simulations of SCN networks to phase shifts during 12h:12h light-dark cycles and showed that GABA networks reduced the average time for the SCN model to re-synchronize. We hypothesized that VIP and GABA balance cell coupling in the SCN to promote synchronization of heterogeneous oscillators while allowing flexibility for adjustment to environmental changes.

Amplitude metrics for cellular circadian bioluminescence reporters.

Bioluminescence rhythms from cellular reporters have become the most common method used to quantify oscillations in circadian gene expression. These experimental systems can reveal phase and amplitude change resulting from circadian disturbances, and can be used in conjunction with mathematical models to lend further insight into the mechanistic basis of clock amplitude regulation. However, bioluminescence experiments track the mean output from thousands of noisy, uncoupled oscillators, obscuring the direct effect of a given stimulus on the genetic regulatory network. In many cases, it is unclear whether changes in amplitude are due to individual changes in gene expression level or to a change in coherence of the population. Although such systems can be modeled using explicit stochastic simulations, these models are computationally cumbersome and limit analytical insight into the mechanisms of amplitude change. We therefore develop theoretical and computational tools to approximate the mean expression level in large populations of noninteracting oscillators, and further define computationally efficient amplitude response calculations to describe phase-dependent amplitude change. At the single-cell level, a mechanistic nonlinear ordinary differential equation model is used to calculate the transient response of each cell to a perturbation, whereas population-level dynamics are captured by coupling this detailed model to a phase density function. Our analysis reveals that amplitude changes mediated at either the individual-cell or the population level can be distinguished in tissue-level bioluminescence data without the need for single-cell measurements. We demonstrate the effectiveness of the method by modeling experimental bioluminescence profiles of light-sensitive fibroblasts, reconciling the conclusions of two seemingly contradictory studies. This modeling framework allows a direct comparison between in vitro bioluminescence experiments and in silico ordinary differential equation models, and will lead to a better quantitative understanding of the factors that affect clock amplitude.

Velocity response curves demonstrate the complexity of modeling entrainable clocks.

Circadian clocks are biological oscillators that regulate daily behaviors in organisms across the kingdoms of life. Their rhythms are generated by complex systems, generally involving interlocked regulatory feedback loops. These rhythms are entrained by the daily light/dark cycle, ensuring that the internal clock time is coordinated with the environment. Mathematical models play an important role in understanding how the components work together to function as a clock which can be entrained by light. For a clock to entrain, it must be possible for it to be sped up or slowed down at appropriate times. To understand how biophysical processes affect the speed of the clock, one can compute velocity response curves (VRCs). Here, in a case study involving the fruit fly clock, we demonstrate that VRC analysis provides insight into a clock׳s response to light. We also show that biochemical mechanisms and parameters together determine a model׳s ability to respond realistically to light. The implication is that, if one is developing a model and its current form has an unrealistic response to light, then one must reexamine one׳s model structure, because searching for better parameter values is unlikely to lead to a realistic response to light.

Weakly circadian cells improve resynchrony.

The mammalian suprachiasmatic nuclei (SCN) contain thousands of neurons capable of generating near 24-h rhythms. When isolated from their network, SCN neurons exhibit a range of oscillatory phenotypes: sustained or damping oscillations, or arrhythmic patterns. The implications of this variability are unknown. Experimentally, we found that cells within SCN explants recover from pharmacologically-induced desynchrony by re-establishing rhythmicity and synchrony in waves, independent of their intrinsic circadian period We therefore hypothesized that a cell's location within the network may also critically determine its resynchronization. To test this, we employed a deterministic, mechanistic model of circadian oscillators where we could independently control cell-intrinsic and network-connectivity parameters. We found that small changes in key parameters produced the full range of oscillatory phenotypes seen in biological cells, including similar distributions of period, amplitude and ability to cycle. The model also predicted that weaker oscillators could adjust their phase more readily than stronger oscillators. Using these model cells we explored potential biological consequences of their number and placement within the network. We found that the population synchronized to a higher degree when weak oscillators were at highly connected nodes within the network. A mathematically independent phase-amplitude model reproduced these findings. Thus, small differences in cell-intrinsic parameters contribute to large changes in the oscillatory ability of a cell, but the location of weak oscillators within the network also critically shapes the degree of synchronization for the population.

Velocity response curves support the role of continuous entrainment in circadian clocks.

Circadian clocks drive endogenous oscillations in organisms across the tree of life. The Earth's daily light/dark cycle entrains these clocks to the environment. Two major theories of light entrainment have been presented in the literature. The discrete theory emphasizes the instantaneous phase-shifting behavior of short pulses of light, and the continuous theory emphasizes changes to the period of oscillations in constant-light conditions. Historically, the primary tool for predicting and understanding discrete entrainment has been the PRC, which measures discrete adjustments to the clock's phase. The authors present a unified theory, which relies on a velocity response curve (VRC), similar in shape to a PRC, but that describes continuous adjustments to the clock's speed. The VRC explains data from both discrete and continuous light experiments and is therefore an invaluable tool to understand entrainment. The authors relate VRC features to specific entrainment behaviors, such as seasonal adjustments to the phase of entrainment. Furthermore, they estimate a VRC from PRC data and successfully reproduce additional PRC data. Finally, they entrain a VRC-based model to natural light/dark cycles, demonstrating the unified theory's ability to predict clock behavior in the face of a fluctuating signal. The results indicate that a VRC-based model not only provides a comprehensive understanding of entrainment but also has excellent predictive capabilities.

Oscillator model reduction preserving the phase response: application to the circadian clock.

Mathematical model reduction is a long-standing technique used both to gain insight into model subprocesses and to reduce the computational costs of simulation and analysis. A reduced model must retain essential features of the full model, which, traditionally, have been the trajectories of certain state variables. For biological clocks, timing, or phase, characteristics must be preserved. A key performance criterion for a clock is the ability to adjust its phase correctly in response to external signals. We present a novel model reduction technique that removes components from a single-oscillator clock model and discover that four feedback loops are redundant with respect to its phase response behavior. Using a coupled multioscillator model of a circadian clock, we demonstrate that by preserving the phase response behavior of a single oscillator, we preserve timing behavior at the multioscillator level.

Synchrony and entrainment properties of robust circadian oscillators.

Systems theoretic tools (i.e. mathematical modelling, control, and feedback design) advance the understanding of robust performance in complex biological networks. We highlight phase entrainment as a key performance measure used to investigate dynamics of a single deterministic circadian oscillator for the purpose of generating insight into the behaviour of a population of (synchronized) oscillators. More specifically, the analysis of phase characteristics may facilitate the identification of appropriate coupling mechanisms for the ensemble of noisy (stochastic) circadian clocks. Phase also serves as a critical control objective to correct mismatch between the biological clock and its environment. Thus, we introduce methods of investigating synchrony and entrainment in both stochastic and deterministic frameworks, and as a property of a single oscillator or population of coupled oscillators.

Sensitivity Measures for Oscillating Systems: Application to Mammalian Circadian Gene Network.

Vital physiological behaviors exhibited daily by bacteria, plants, and animals are governed by endogenous oscillators called circadian clocks. The most salient feature of the circadian clock is its ability to change its internal time (phase) to match that of the external environment. The circadian clock, like many oscillators in nature, is regulated at the cellular level by a complex network of interacting components. As a complementary approach to traditional biological investigation, we utilize mathematical models and systems theoretic tools to elucidate these mechanisms. The models are systems of ordinary differential equations exhibiting stable limit cycle behavior. To study the robustness of circadian phase behavior, we use sensitivity analysis. As the standard set of sensitivity tools are not suitable for the study of phase behavior, we introduce a novel tool, the parametric impulse phase response curve (pIPRC).

A novel computational model of the circadian clock in Arabidopsis that incorporates PRR7 and PRR9.

In plants, as in animals, the core mechanism to retain rhythmic gene expression relies on the interaction of multiple feedback loops. In recent years, molecular genetic techniques have revealed a complex network of clock components in Arabidopsis. To gain insight into the dynamics of these interactions, new components need to be integrated into the mathematical model of the plant clock. Our approach accelerates the iterative process of model identification, to incorporate new components, and to systematically test different proposed structural hypotheses. Recent studies indicate that the pseudo-response regulators PRR7 and PRR9 play a key role in the core clock of Arabidopsis. We incorporate PRR7 and PRR9 into an existing model involving the transcription factors TIMING OF CAB (TOC1), LATE ELONGATED HYPOCOTYL (LHY) and CIRCADIAN CLOCK ASSOCIATED (CCA1). We propose candidate models based on experimental hypotheses and identify the computational models with the application of an optimization routine. Validation is accomplished through systematic analysis of various mutant phenotypes. We introduce and apply sensitivity analysis as a novel tool for analyzing and distinguishing the characteristics of proposed architectures, which also allows for further validation of the hypothesized structures.