Signaling Model Research Articles

Identifying anti-TNF response biomarkers in ulcerative colitis using a diffusion-based signalling model.

Resistance to anti-TNF therapy in subgroups of ulcerative colitis (UC) patients is a major challenge and incurs significant treatment costs. Identification of patients at risk of nonresponse to anti-TNF is of major clinical importance. To date, no quantitative computational framework exists to develop a complex biomarker for the prognosis of UC treatment. Modelling patient-wise receptor to transcription factor (TF) network connectivity may enable personalized treatment. We present an approach for quantitative diffusion analysis between receptors and TFs using gene expression data. Key TFs were identified using pandaR. Network connectivities between immune-specific receptor-TF pairs were quantified using network diffusion in UC patients and controls. The patient-specific network could be considered a complex biomarker that separates anti-TNF treatment-resistant and responder patients both in the gene expression dataset used for model development and separate independent test datasets. The model was further validated in rheumatoid arthritis where it successfully discriminated resistant and responder patients to tocilizumab treatment. Our model may contribute to prognostic biomarkers that may identify treatment-resistant and responder subpopulations of UC patients. Software is available at https://github.com/Amy3100/receptor2tfDiffusion. Supplementary data are available at Bioinformatics Advances online.

Self-Reported Actions, Signaling, and Auditing

In many real-world settings, an action that affects the value of a product or service is self-reported rather than publicly observable. We investigate self-reporting when the action serves as a signal. In our model, a sender chooses an action, and then sends a message concerning the action to multiple receivers. Receivers then bid for the sender's service after deciding whether to audit the sender. We find that self-reporting can reverse the standard result in signaling models that there is overinvestment in the signal, and that the possibility of misrepresentation may in fact improve welfare given self-reported signaling.

Discovery and Disclosure in a Signaling Model of Final-Offer Arbitration

We develop a signaling model of final-offer arbitration (FOA) in which the informed party makes the final settlement demand to the uninformed party. In FOA, each party submits a proposal to an arbitrator, and if no agreement is reached the arbitrator must select one of the two submitted proposals. In the context of this model, we analyze costly voluntary disclosure and costly discovery. In standard litigation models, costly disclosure may occur in the signaling game, but costly discovery never takes place. By contrast, under FOA if information transmission takes place prior to the submission of proposals to the arbitrator, costly discovery may take place. However, the incentive to engage in a voluntary disclosure is weakened relative to a standard litigation model. If information transmission takes place after the submission of proposals to the arbitrator, then the results are analogous to those found in a standard litigation model.

Modeling Auxin Signaling in Roots: Auxin Computations.

Auxin signaling and patterning is an inherently complex process, involving polarized auxin transport, metabolism, and signaling, its effect on developmental zones, as well as growth rates, and the feedback between all these different aspects. This complexity has led to an important role for computational modeling in unraveling the multifactorial roles of auxin in plant developmental and adaptive processes. Here we discuss the basic ingredients of auxin signaling and patterning models for root development as well as a series of key modeling studies in this area. These modeling studies have helped elucidate how plants use auxin signaling to compute the size of their root meristem, the direction in which to grow, and when and where to form lateral roots. Importantly, these models highlight how auxin, through patterning of and collaborating with other factors, can fulfill all these roles simultaneously.

Boolean dynamic modeling of cancer signaling networks: Prognosis, progression, and therapeutics

AbstractCancer is a multifactorial disease. Aberrant functioning of the underlying complex signaling network that orchestrates cellular response to external or internal cues governs incidence, progression, and recurrence of cancer. Detailed understanding of cancer's etiology can offer useful insights into arriving at novel therapeutic and disease management strategies. Such an understanding for most cancers is currently limited due to unavailability of a predictive large‐scale, integrated signaling model accounting for all tumor orchestrating factors. We suggest that the potential of Boolean dynamic (BD) modeling approaches, though qualitative, can be harnessed for developing holistic models capturing multi‐scale, multi‐cellular signaling processes involved in cancer incidence and progression. We believe that constraining such an integrated BD model with variety of omics data at different scales from laboratory and clinical settings could offer deeper insights into causal mechanisms governing the disease leading to better prognosis. We review the recent literature employing different BD modeling strategies to model variety of cancer signaling programs leading to identification of cancer‐specific prognostic markers such as SMAD proteins, which may also serve as early predictors of tumor cells hijacking the epithelial‐mesenchymal plasticity program.In silicosimulations of BD models of different cancer signaling networks combined with attractor landscape analysis and validated with experimental data predicted the nature of short‐ and long‐term response of standard targeted therapeutic agents such as Nutlin‐3, a small molecule inhibitor for p53‐MDM2 interaction. BD simulations also offered a mechanistic view of emerging resistance to drugs such as Trastuzumab for HER+ breast cancer, analysis of which suggested new combination therapies to circumvent them. We believe future improvements in BD modeling techniques, and tools can lead to development of a comprehensive platform that can drive holistic approaches toward better decision‐making in the clinical settings, and thereby help identify novel therapeutic strategies for improved cancer treatment at personalised levels.

Signal Crosstalk Promoted Proliferative Lesions in Mouse Mammary Glands As a Consequence of ET-1 Overexpression

Objective: As a distinct cellular signaling model, a receptor crosstalk between G protein-coupled receptors (GPCR) and epidermal growth factor receptor (EGFR) has been demonstrated in various in vitro studies. In addition, recent in vitro studies had focused on the signaling pathways of endothelin-1 (ET-1) in the pathophysiology of cancer. Accordingly, a growing interest in the analysis of the receptor crosstalk between ET-1 receptors and EGFR and functional consequences of EGFR activation of proliferative diseases evoked us to the analysis of this phenomenon in vivo. Materials and Methods: We performed a comparative study between ET-1 transgenic mice and control mice during the late pregnancy (n=7), early lactation (n=6) the mid of lactation (n=10) and involution day 14 (n=7) periods. Hematoxylin and eosin (HE)- stained parallel sections from mammary glands were microscopically examined. The key signal proteins (ETAR, ETBR, ERK1/2, pEGFR) in transactivation of EGFR were analyzed employing Western blot techniques. Genes (amphiregulin, TGFa, EGF, HB-EGF, ADAM 17) known to play an important role in these activities were analyzed using real-time PCR (RT-PCR) techniques. Results: ET-1 transgenic mice exhibited hyperproliferative lesions (lactational hyperplasia) during the middle of the lactation period. Our RT-PCR analyses showed a prominent up regulation of amphiregulin and ADAM 17 in ET-1 transgenic mice. Moreover, we found higher EGFR and ERKs activations in the transgenic mammary glands. Conclusion: This study highlights a causative effect of upregulated ET-1 gene expression on the induction of proliferative lesions via EGFR transactivation in mammary glands. Further, ET-1 overexpression induced an upregulation of amphiregulin and ADAM17 expressions in the transgenic mammary glands. These results suggests that the enhanced ET-1 gene expression and its receptors might have a crucial role in proliferative diseases maintaining EGFR activation.

Re-Evaluating the Oxidative Phenotype: Can Endurance Exercise Save the Western World?

Mitochondria are popularly called the “powerhouses” of the cell. They promote energy metabolism through the tricarboxylic acid (TCA) cycle and oxidative phosphorylation, which in contrast to cytosolic glycolysis are oxygen-dependent and significantly more substrate efficient. That is, mitochondrial metabolism provides substantially more cellular energy currency (ATP) per macronutrient metabolised. Enhancement of mitochondrial density and metabolism are associated with endurance training, which allows for the attainment of high relative VO2 max values. However, the sedentary lifestyle and diet currently predominant in the Western world lead to mitochondrial dysfunction. Underdeveloped mitochondrial metabolism leads to nutrient-induced reducing pressure caused by energy surplus, as reduced nicotinamide adenine dinucleotide (NADH)-mediated high electron flow at rest leads to “electron leak” and a chronic generation of superoxide radicals (O2−). Chronic overload of these reactive oxygen species (ROS) damages cell components such as DNA, cell membranes, and proteins. Counterintuitively, transiently generated ROS during exercise contributes to adaptive reduction-oxidation (REDOX) signalling through the process of cellular hormesis or “oxidative eustress” defined by Helmut Sies. However, the unaccustomed, chronic oxidative stress is central to the leading causes of mortality in the 21st century—metabolic syndrome and the associated cardiovascular comorbidities. The endurance exercise training that improves mitochondrial capacity and the protective antioxidant cellular system emerges as a universal intervention for mitochondrial dysfunction and resultant comorbidities. Furthermore, exercise might also be a solution to prevent ageing-related degenerative diseases, which are caused by impaired mitochondrial recycling. This review aims to break down the metabolic components of exercise and how they translate to athletic versus metabolically diseased phenotypes. We outline a reciprocal relationship between oxidative metabolism and inflammation, as well as hypoxia. We highlight the importance of oxidative stress for metabolic and antioxidant adaptation. We discuss the relevance of lactate as an indicator of critical exercise intensity, and inferring from its relationship with hypoxia, we suggest the most appropriate mode of exercise for the case of a lost oxidative identity in metabolically inflexible patients. Finally, we propose a reciprocal signalling model that establishes a healthy balance between the glycolytic/proliferative and oxidative/prolonged-ageing phenotypes. This model is malleable to adaptation with oxidative stress in exercise but is also susceptible to maladaptation associated with chronic oxidative stress in disease. Furthermore, mutations of components involved in the transcriptional regulatory mechanisms of mitochondrial metabolism may lead to the development of a cancerous phenotype, which progressively presents as one of the main causes of death, alongside the metabolic syndrome.

Costly signaling in autocracy

ABSTRACT Those who would revolt against an autocrat often face a dilemma caused by uncertainty: they would like to revolt if the ruler would respond with democratization, but they would prefer to concede if the ruler would choose instead to violently suppress the revolution. Consequently, the autocrat must decide how to best signal his willingness to use violence in hope of deterring revolt. Using a simple signaling model, we find that rulers cannot meaningfully convey their type by transferring wealth to the citizenry. However, they can convey their type through shows of force, as long as the strong type of autocrat – who would use violent repression in the case of revolution – has a competitive advantage in displaying his strength. We additionally demonstrate that rulers favor shows of force when their willingness to suppress revolution is questioned and that citizens at times prefer to pay the direct cost of shows of force to learn about the ruler’s type, rather than to remain uninformed. The results illustrate a more general result in costly signaling models: information transmission is only possible when the cost of the signal is smaller for the type that wants to distinguish himself.

Phospho‐dependent signaling during the general stress response by the atypical response regulator and ClpXP adaptor RssB

In the model organism Escherichia coli and related species, the general stress response relies on tight regulation of the intracellular levels of the promoter specificity subunit RpoS. RpoS turnover is exclusively dependent on RssB, a two-domain response regulator that functions as an adaptor that delivers RpoS to ClpXP for proteolysis. Here, we report crystal structures of the receiver domain of RssB both in its unphosphorylated form and bound to the phosphomimic BeF3 - . Surprisingly, we find only modest differences between these two structures, suggesting that truncating RssB may partially activate the receiver domain to a "meta-active" state. Our structural and sequence analysis points to RssB proteins not conforming to either the Y-T coupling scheme for signaling seen in prototypical response regulators, such as CheY, or to the signaling model of the less understood FATGUY proteins.

Computational modeling approaches to cAMP/PKA signaling in cardiomyocytes

The cAMP/PKA pathway is a fundamental regulator of excitation-contraction coupling in cardiomyocytes. Activation of cAMP has a variety of downstream effects on cardiac function including enhanced contraction, accelerated relaxation, adaptive stress response, mitochondrial regulation, and gene transcription. Experimental advances have shed light on the compartmentation of cAMP and PKA, which allow for control over the varied targets of these second messengers and is disrupted in heart failure conditions. Computational modeling is an important tool for understanding the spatial and temporal complexities of this system. In this review article, we outline the advances in computational modeling that have allowed for deeper understanding of cAMP/PKA dynamics in the cardiomyocyte in health and disease, and explore new modeling frameworks that may bring us closer to a more complete understanding of this system. We outline various compartmental and spatial signaling models that have been used to understand how β-adrenergic signaling pathways function in a variety of simulation conditions. We also discuss newer subcellular models of cardiovascular function that may be used as templates for the next phase of computational study of cAMP and PKA in the heart, and outline open challenges which are important to consider in future models.

Understanding cell-cell communication and signaling in the colorectal cancer microenvironment.

Carcinomas are complex heterocellular systems containing epithelial cancer cells, stromal fibroblasts, and multiple immune cell‐types. Cell‐cell communication between these tumor microenvironments (TME) and cells drives cancer progression and influences response to existing therapies. In order to provide better treatments for patients, we must understand how various cell‐types collaborate within the TME to drive cancer and consider the multiple signals present between and within different cancer types. To investigate how tissues function, we need a model to measure both how signals are transferred between cells and how that information is processed within cells. The interplay of collaboration between different cell‐types requires cell‐cell communication. This article aims to review the current in vitro and in vivo mono‐cellular and multi‐cellular cultures models of colorectal cancer (CRC), and to explore how they can be used for single‐cell multi‐omics approaches for isolating multiple types of molecules from a single‐cell required for cell‐cell communication to distinguish cancer cells from normal cells. Integrating the existing single‐cell signaling measurements and models, and through understanding the cell identity and how different cell types communicate, will help predict drug sensitivities in tumor cells and between‐ and within‐patients responses.

Signaling in the ‘Before’ Model of Final Offer Arbitration

We develop a signaling model of final offer arbitration (FOA) in which the informed party makes the final settlement demand to the uninformed party. In FOA, each party submits a proposal to an arbitrator and if no agreement is reached, the arbitrator must select one of the two submitted proposals. We analyze a “before” model of FOA in which all settlement activity occurs prior to the exchange of proposals. We characterize the pure strategy separating, equilibrium associated with this game. Relative to a model of conventional arbitration (CA), the pure strategy separating equilibrium is associated with a higher dispute rate because weak player types have an enhanced incentive to bluff in this setting. This result continues to hold in semi-pooling equilibria. Thus our model is consistent with a higher dispute rate in FOA compared to CA. Results on the incentive to engage in costly voluntary disclosure are mixed across the two models. In contrast with CA, costly discovery can occur in this model of FOA. The analysis of out of equilibrium beliefs and actions is considerably more complex than in the standard litigation model.

The impact of service category and brand positioning on consumer animosity in the service sector – a social identity signaling perspective

PurposeThe present research responds to researchers’ calls for more research of consumer animosity on potential boundary conditions (e.g. product categories) and marketing strategies that may mitigate such negative impacts on marketers’ product and/or brand performance, with a special focus on the soft service sector. This paper aims to address the unique characteristics of service internationalization, i.e. cultural embeddedness, hybridized country origins and high consumption visibility, by proposing a social identity signaling model to explain consumer animosity effects in the soft service sector.Design/methodology/approachTwo surveys (Pretest with 240 participants and Study 1 with 351 participants) and one experiment (Study 2 with 731 participants) were conducted to empirically test our hypotheses in the Japanese-Chinese relationship context.FindingsThe stronger the national/cultural symbolism and social expressiveness, the stronger the consumer avoidance for the service category. Then the consumer culture positioning strategy that can mitigate an offending country’s cultural symbolism can reduce consumer avoidance.Originality/valueThis research introduces two factors that could affect the negative social identity signaling capacity of service categories in the animosity context: the national/cultural symbolism reflecting an offending country and the social expressiveness communicating social identity. In line with the social identity signaling perspective, the present research specifically uses consumer avoidance as the dependent variable to capture the notion that consumers avoid consuming services because they wish to avoid being associated with an offending country that may threaten their in-group social identities.

Single cell transcriptomic analysis of human pluripotent stem cell chondrogenesis

The therapeutic application of human induced pluripotent stem cells (hiPSCs) for cartilage regeneration is largely hindered by the low yield of chondrocytes accompanied by unpredictable and heterogeneous off-target differentiation of cells during chondrogenesis. Here, we combine bulk RNA sequencing, single cell RNA sequencing, and bioinformatic analyses, including weighted gene co-expression analysis (WGCNA), to investigate the gene regulatory networks regulating hiPSC differentiation under chondrogenic conditions. We identify specific WNTs and MITF as hub genes governing the generation of off-target differentiation into neural cells and melanocytes during hiPSC chondrogenesis. With heterocellular signaling models, we further show that WNT signaling produced by off-target cells is responsible for inducing chondrocyte hypertrophy. By targeting WNTs and MITF, we eliminate these cell lineages, significantly enhancing the yield and homogeneity of hiPSC-derived chondrocytes. Collectively, our findings identify the trajectories and molecular mechanisms governing cell fate decision in hiPSC chondrogenesis, as well as dynamic transcriptome profiles orchestrating chondrocyte proliferation and differentiation.

From Transcript to Tissue: Multiscale Modeling from Cell Signaling to Matrix Remodeling.

Tissue-level biomechanical properties and function derive from underlying cell signaling, which regulates mass deposition, organization, and removal. Here, we couple two existing modeling frameworks to capture associated multiscale interactions-one for vessel-level growth and remodeling and one for cell-level signaling-and illustrate utility by simulating aortic remodeling. At the vessel level, we employ a constrained mixture model describing turnover of individual wall constituents (elastin, intramural cells, and collagen), which has proven useful in predicting diverse adaptations as well as disease progression using phenomenological constitutive relations. Nevertheless, we now seek an improved mechanistic understanding of these processes; we replace phenomenological relations in the mixture model with a logic-based signaling model, which yields a system of ordinary differential equations predicting changes in collagen synthesis, matrix metalloproteinases, and cell proliferation in response to altered intramural stress, wall shear stress, and exogenous angiotensin II. This coupled approach promises improved understanding of the role of cell signaling in achieving tissue homeostasis and allows us to model feedback between vessel mechanics and cell signaling. We verify our model predictions against data from the hypertensive murine infrarenal abdominal aorta as well as results from validated phenomenological models, and consider effects of noisy signaling and heterogeneous cell populations.

Designing a Competitive Monotone Signaling Equilibrium

A decision maker (DM) determines a set of reactions that receivers can choose before senders and receivers move in a generalized competitive signaling model with two-sided matching. The DM's optimal design of the unique stronger monotone signaling equilibrium (unique D1 equilibrium) is equivalent to the choice problem of two threshold sender types, one for market entry and the other for pooling on the top. Our analysis sheds light on the impacts of a trade-off between matching efficiency and signaling costs, the relative heterogeneity of receiver types to sender types, and the productivity of the sender's action on optimal equilibrium designing.

Reserve Price Signaling with Public Information: Evidence from Online Auto Auctions

This paper studies the problem of information provision in auctions. The linkage principle indicates that credibly revealing private information would benefit the seller, which implies that a seller should prefer a public reserve price to a secret one if the reserve price could reveal her private information. However, information revelation may backfire if the seller's information is not verifiable, and the reserve price works as a signaling device. In this paper, we consider an auction model in which a seller's choice of reserve price signals her private information about the object's quality. We show that such a signaling incentive could decrease the seller's profit and probability of sale in equilibrium, with a larger impact when the seller's private information is more precise relative to the public information announced by a third party. We estimate the reserve price signaling model using a novel dataset from a large online auto auction platform. We find that the signaling incentive could cost the seller 4% of her profit, and decrease the probability of sale by 15 percentage points. Counterfactual simulations suggest that a secret reserve price can improve both the seller's profit and probability of sale, especially when the signaling incentive is strong. Our findings support the prevalent use of secret reserve prices in practice, contrary to the predictions of linkage principle.

The Role of Social Signaling in Selective Exposure to Information

Effective judgment and decision making demands exposure to diverse information. Yet, a large interdisciplinary literature makes clear that individuals often avoid information that contradicts their prior beliefs, a tendency referred to as selective exposure. Prior research has focused on intrapersonal drivers of selective exposure, including avoidance of cognitive dissonance. We take a complementary approach by investigating the interpersonal drivers of selective exposure. Drawing on the fact that individuals care deeply about their reputations, we test a social signaling model of selective exposure, hypothesizing that (1) individuals shift their information consumption choices to signal to observers and (2) observers reward such shifts. In the context of partisan politics in the United States, three financially-incentivized, pre-registered experiments (N = 2,325) supported both hypotheses. Our results also identified three moderating factors: the type of interaction the observers expect to have with the actors, congruence of group membership between actors and observers (aligned vs. unaligned), and the magnitude of selective exposure. These results suggest that tailoring one’s information consumption choices has strategic value. Importantly, examining the reputational causes and consequences of selective exposure reveals a novel trade-off: what is typically optimal for decision quality may conflict with accomplishing one’s reputation-management goals. In the era of social media, when information consumption choices are more public than ever before, understanding the ways in which reputational considerations shape decision making illuminates not only why selective exposure remains so pervasive, but also suggests novel mitigation strategies.

Preference Signaling and Worker-Firm Matching: Evidence from Interview Auctions

We study whether there are improvements in worker-firm matching when employers and applicants can credibly signal their interest in a match. Using a detailed resume dataset of more than 400 applicants from one university over five years, we analyze a matching process in which firms fill some of their inter- view slots by invitation and the remainder are filled by an auction. Consistent with the predictions of a signaling model, we find the auction is valuable for less desirable firms trying to hire high desirability applicants. Second, we find evidence that is consistent with the auction benefiting overlooked applicants. Candidates who are less likely to be invited for an interview (e.g., non-U.S. citizens) are hired after having the opportunity to interview through the auction. Among hires, these candidates are more represented among auction winners than invited interviewees, and this difference is more pronounced at more desirable firms. Finally, counterfactual analysis shows the auction increases the number and quality of hires for less desirable firms, and total hires in the market.

Reference Dependent Prices in Bargaining: An Experimental Examination of Precise First Offers

Evidence from psychology and marketing suggests that those who make a first in bargaining get a better deal than those who make a round first offer. We report on a series of experiments designed to test for and improve our understanding of the first offer (PFO) effect in bargaining and whether it likely reflects rational optimizing or equilibrium behavior. Our experiment varies whether decisions are incentivized and whether the PFO effect can emerge as an equilibrium of a cheap-talk signaling game. We find evidence of a PFO effect when subjects read a vignette and make unincentivized individual decisions. When monetary incentives are added to the vignette, we still find the PFO effect, but it is not robust. In a bilateral bargaining situation with a cheap-talk equilibrium, we can not find the PFO effect, which is inconsistent with the equilibrium predictions. Moreover, the PFO effect reemerges in a setting in which initial offers are generated by a random device and thus provides a strong refutation of the signaling model. Our evidence suggests that optimizing and equilibrium accounts of the PFO effect are inadequate. Understanding initial offers as reference points, which subtly change perceptions about the kinds of acceptable counteroffers, provides a plausible account of a new finding on which prior explanations are silent: precise offers induce more precise counteroffers.