Dynamic Pathway Model Research Articles

The reciprocity of social media engagement and collective actions: A longitudinal study on Ukrainian refugees

This study examined the effect of social media engagement on collective action intention to help Ukrainian refugees. This study proposes a dynamic, transactional model that draws upon computer-mediated communication research and the dynamic dual pathway model of collective action (DPPM) to investigate the impact of two types of social media engagement, namely actions and cues, on intergroup helping. The model aims to achieve two objectives: First, it examines the mediating role of anger and collective efficacy, the two parallel psychological mechanisms proposed by DPPM, in the effects of action and cues on collective action intention. Second, it tests the dynamic and reciprocal relationship between collection action intention and social media actions and cues over time. A three-wave longitudinal survey of U.S. adults was conducted after the Russian-Ukrainian War started. Longitudinal mediation analyses showed that social media action predicted greater collective action intentions indirectly through collective efficacy but not anger. Social media cues did not predict collective action intentions through collective efficacy or anger. Collective action intentions, in turn, increased subsequent social media actions and cues, forming a positive feedback loop. The effect of social media actions on collective action intention was stronger than that of social media cues.

Executable models of immune signaling pathways in HIV-associated atherosclerosis

Atherosclerosis (AS)-associated cardiovascular disease is an important cause of mortality in an aging population of people living with HIV (PLWH). This elevated risk has been attributed to viral infection, anti-retroviral therapy, chronic inflammation, and lifestyle factors. However, the rates at which PLWH develop AS vary even after controlling for length of infection, treatment duration, and for lifestyle factors. To investigate the molecular signaling underlying this variation, we sequenced 9368 peripheral blood mononuclear cells (PBMCs) from eight PLWH, four of whom have atherosclerosis (AS+). Additionally, a publicly available dataset of PBMCs from persons before and after HIV infection was used to investigate the effect of acute HIV infection. To characterize dysregulation of pathways rather than just measuring enrichment, we developed the single-cell Boolean Omics Network Invariant Time Analysis (scBONITA) algorithm. scBONITA infers executable dynamic pathway models and performs a perturbation analysis to identify high impact genes. These dynamic models are used for pathway analysis and to map sequenced cells to characteristic signaling states (attractor analysis). scBONITA revealed that lipid signaling regulates cell migration into the vascular endothelium in AS+ PLWH. Pathways implicated included AGE-RAGE and PI3K-AKT signaling in CD8+ T cells, and glucagon and cAMP signaling pathways in monocytes. Attractor analysis with scBONITA facilitated the pathway-based characterization of cellular states in CD8+ T cells and monocytes. In this manner, we identify critical cell-type specific molecular mechanisms underlying HIV-associated atherosclerosis using a novel computational method.

Applying the Dynamic Dual Pathway Model of Approach Coping to Collective Action Among Advantaged Group Allies and Disadvantaged Group Members.

We apply the dynamic dual pathway model of approach coping to understanding the predictors of future collective action among a sample of advantaged group allies and disadvantaged group members who were attending a protest. We propose that problem-focused approach coping (i.e., group efficacy beliefs) would be a stronger predictor of future collective action among disadvantaged compared to advantaged group members, and emotion-focused approach coping (i.e., group-based anger) would be a stronger predictor of future collective action among advantaged compared to disadvantaged group members. Data was collected from LGBTIQ+ and heterosexual people (N = 189) protesting as part of the 2019 Christopher Street Day Parade in Cologne, Germany. We found that increased group efficacy predicted intentions to engage in future collective action for the rights of sexual minorities among LGBTIQ+ but not heterosexual participants. Increased group-based anger was a predictor of future collective action intentions regardless of which group the participants belonged to. Our findings extend the dynamic dual pathway model by applying it to a sample of advantaged group allies and disadvantaged group members attending a protest using a multiple perspectives approach.

Explaining different orientations to the 2013 Gezi Park demonstrations in Istanbul, Turkey.

Although a notable minority orient to real-world demonstrations by actively participating, other less involved, safer, orientations are more frequent. Thus, in the context of anti-government demonstrations in Gezi Park/Taksim Square in Istanbul, Turkey, in 2013, we distinguished between the orientations of participating, visiting, and watching. Study 1 (N=359) and Study 2 (N=327) confirmed that participating was characterized by greater experience of police violence and feelings of collective empowerment (Drury & Reicher, European Journal of Social Psychology, 35, 2005, 35) than visiting and watching the demonstrations. Expanding upon and replicating the findings from Study 1, Study 2 examined identification with protestors and left-wing ideology, along with constructs (social support, anger at the government, protestor's efficacy, endorsement of protestors) from the dynamic dual pathway model (van Zomeren etal., Personality and Social Psychology Review, 16, 2012, 180) as predictors of the three different orientations to the demonstrations. As expected, the dynamic dual pathway model predicted reported participation via endorsement of protestors, independent of identification with protestors and left-wing ideology.

Model-based identification of TNF\u03b1-induced IKK\u03b2-mediated and I\u03baB\u03b1-mediated regulation of NF\u03baB signal transduction as a tool to quantify the impact of drug-induced liver injury compounds

Drug-induced liver injury (DILI) has become a major problem for patients and for clinicians, academics and the pharmaceutical industry. To date, existing hepatotoxicity test systems are only poorly predictive and the underlying mechanisms are still unclear. One of the factors known to amplify hepatotoxicity is the tumor necrosis factor alpha (TNFα), especially due to its synergy with commonly used drugs such as diclofenac. However, the exact mechanism of how diclofenac in combination with TNFα induces liver injury remains elusive. Here, we combined time-resolved immunoblotting and live-cell imaging data of HepG2 cells and primary human hepatocytes (PHH) with dynamic pathway modeling using ordinary differential equations (ODEs) to describe the complex structure of TNFα-induced NFκB signal transduction and integrated the perturbations of the pathway caused by diclofenac. The resulting mathematical model was used to systematically identify parameters affected by diclofenac. These analyses showed that more than one regulatory module of TNFα-induced NFκB signal transduction is affected by diclofenac, suggesting that hepatotoxicity is the integrated consequence of multiple changes in hepatocytes and that multiple factors define toxicity thresholds. Applying our mathematical modeling approach to other DILI-causing compounds representing different putative DILI mechanism classes enabled us to quantify their impact on pathway activation, highlighting the potential of the dynamic pathway model as a quantitative tool for the analysis of DILI compounds.

A Study to Determine the Impact of Management on Public Service Motivation in Public Sector Employees

Milwaukee Area Technical College (MATC) was tasked with the development of career path information for our students. The IT faculty team, under the direction and leadership of the Associate Dean, created the Information Technology Pathways model. The Associate Dean invested significantly in infrastructure and planning to ensure cross-team knowledge exchange. We also wanted to enhance awareness and increase student engagement via social media platforms like Facebook, Twitter, LinkedIn, YouTube, and MeetUp. This study was designed to create pathways and curriculum that other programs could replicate; other departments can now benefit from the template and design strategies developed to enhance the IT curriculum and pathways. These pathways and the dialogues have led to increased training requests and pooled training. Our MATC case study is a good example that identifies and shares pathways, curriculum development, and partnering with advisory committees to gain input for incorporating instructional technology in the classroom based on student needs. Purpose: This article describes a dynamic and innovative pathway model for instructors to service student, parents, counselor, and employer needs around digital and social technologies that support student enrollment, retention and provide collaborative learning opportunities for improved job placement. The goal is to produce graduates that bring relevant and reliable skill sets that match current business and industry needs. The two primary reasons for enrolling are preparing for a job and career change. In addition, it provides training for a career ladder for training employees who need to advance, many employers are moving incumbent workers along this career path as well. Methodology/Approach: A case study Findings: The integration of pathways including certificates, embedded technical diplomas, associate degrees, online community through digital, mobile and social technologies, MeetUp, LinkedIn, Google Apps, groups, Netlab, Blackboard Learn & Internships.com, have a positive influence on student advising, enrollment, retention and job placement. Many of the social media tools are free so they did not involve increased funding but mostly involved legwork, making them effective tools for reaching new students. Research Limitations: The research was limited to the IT faculty population at MATC, and did not include data collected from students outside the USA to find out what role cultural mores, attitudes and gender play in the learning process. Practical Implications: Workplace employers are increasingly experiencing a skills mismatch and the growing retirement gap. Thus, institutions of higher education are under increased scrutiny regarding the preparedness of their graduates for the workforce. This study provides curriculum design strategies that foster community, utilize mobile, social media and support student learning and retention through effective course design. The sharing of best practices will help the next generation of students with pathways that are connective and progressive and empower them with marketable, stackable credentials. The study provides an entry point for all learners and a bridge to further opportunities on a pathway at any point to gain support and structure for job entry, advancement and higher wages. This is important since there is an increased demand for a credentialed workforce. The end result will be a larger pool of qualified workers and a better pipeline to fill skilled jobs, which subsequently will result in higher employee retention and loyalty. Pathways enable students, faculty and leadership a familiar path of program offerings and job prospects. In addition, this model can be used to inform policy and practice related to performance funding, college affordability, and alignment of higher education and workforce needs, as well as for new research on topics including: state-level labor market outcomes for certificates and degrees; returns to for-profit college credentials; the impact of the federal grants and loans on earnings and employment; challenges in using labor market outcomes data in performance funding systems; and how post-college earnings data can be used to help students make better program and career choices. It is necessary to rethink the academic work environments based on social media tools and applications like Google Groups, MeetUp, Blackboard Building Blocks or LinkedIn, in accordance with the learning needs, skills, and competencies of students.

Transition Pathway and Its Free-Energy Profile: A Protocol for Protein Folding Simulations

We propose a protocol that provides a systematic definition of reaction coordinate and related free-energy profile as the function of temperature for the protein-folding simulation. First, using action-derived molecular dynamics (ADMD), we investigate the dynamic folding pathway model of a protein between a fixed extended conformation and a compact conformation. We choose the pathway model to be the reaction coordinate, and the folding and unfolding processes are characterized by the ADMD step index, in contrast to the common a priori reaction coordinate as used in conventional studies. Second, we calculate free-energy profile as the function of temperature, by employing the replica-exchange molecular dynamics (REMD) method. The current method provides efficient exploration of conformational space and proper characterization of protein folding/unfolding dynamics from/to an arbitrary extended conformation. We demonstrate that combination of the two simulation methods, ADMD and REMD, provides understanding on molecular conformational changes in proteins. The protocol is tested on a small protein, penta-peptide of met-enkephalin. For the neuropeptide met-enkephalin system, folded, extended, and intermediate sates are well-defined through the free-energy profile over the reaction coordinate. Results are consistent with those in the literature.

Free-energy profile along an isomerization pathway: Conformational isomerization in alanine dipeptide

The free-energy profile for the conformational isomerization process in alanine dipeptide is presented in atomistic detail by using an action-derived molecular dynamics (ADMD) method and replica-exchange molecular dynamics (REMD) method. First, by employing ADMD, a dynamic isomerization pathway model of the alanine dipeptide with two available low-energy conformations, C7 ax and C7 eq , is determined. The pathway model is chosen to be the reaction coordinate, so the isomerization process is characterized by the ADMD step index, which is not an a-priori reaction coordinate as found in conventional studies of molecular conformational changes. Second, by employing the REMD method, the free-energy profile is calculated as a function of temperature. This couple of procedures is a quite natural protocol for conformational isomerization process simulations, irrespective of the arbitrary selection of the reaction coordinate. The alliance between the two simulation methods, ADMD and REMD, is demonstrated to have a great synergy effect on understanding the conformational changes in molecules.

Dynamic Folding Pathway Models of the Trp-Cage Protein

Using action-derived molecular dynamics (ADMD), we study the dynamic folding pathway models of the Trp-cage protein by providing its sequential conformational changes from its initial disordered structure to the final native structure at atomic details. We find that the numbers of native contacts and native hydrogen bonds are highly correlated, implying that the native structure of Trp-cage is achieved through the concurrent formations of native contacts and native hydrogen bonds. In early stage, an unfolded state appears with partially formed native contacts (~40%) and native hydrogen bonds (~30%). Afterward, the folding is initiated by the contact of the side chain of Tyr3 with that of Trp6, together with the formation of the N-terminal α-helix. Then, the C-terminal polyproline structure docks onto the Trp6 and Tyr3 rings, resulting in the formations of the hydrophobic core of Trp-cage and its near-native state. Finally, the slow adjustment processes of the near-native states into the native structure are dominant in later stage. The ADMD results are in agreement with those of the experimental folding studies on Trp-cage and consistent with most of other computational studies.

Protesters as “Passionate Economists”

To explain the psychology behind individuals’ motivation to participate in collective action against collective disadvantage (e.g., protest marches), the authors introduce a dynamic dual pathway model of approach coping that integrates many common explanations of collective action (i.e., group identity, unfairness, anger, social support, and efficacy). It conceptualizes collective action as the outcome of two distinct processes: emotion-focused and problem-focused approach coping. The former revolves around the experience of group-based anger (based in appraised external blame for unfair collective disadvantage). The latter revolves around beliefs in the group’s efficacy (based in appraised instrumental coping potential for social change). The model is the first to make explicit the dynamic nature of collective action by explaining how undertaking collective action leads to the reappraisal of collective disadvantage, thus inspiring future collective action. The authors review empirical support for the model, discuss its theoretical and practical implications, and identify directions for future research and application.

Systems biology model repository for macrophage pathway simulation

The Macrophage Pathway Knowledgebase (MACPAK) is a computational system that allows biomedical researchers to query and study the dynamic behaviors of macrophage molecular pathways. It integrates the knowledge of 230 reviews that were carefully checked by specialists for their accuracy and then converted to 230 dynamic mathematical pathway models. MACPAK comprises a total of 24 009 entities and 12 774 processes and is described in the Cell System Markup Language (CSML), an XML format that runs on the Cell Illustrator platform and can be visualized with a customized Cytoscape for further analysis. MACPAK can be accessed via an interactive web site at http://macpak.csml.org. The CSML pathway models are available under the Creative Commons license.

Dynamic Mathematical Modeling of IL13-Induced Signaling in Hodgkin and Primary Mediastinal B-Cell Lymphoma Allows Prediction of Therapeutic Targets

Primary mediastinal B-cell lymphoma (PMBL) and classical Hodgkin lymphoma (cHL) share a frequent constitutive activation of JAK (Janus kinase)/STAT signaling pathway. Because of complex, nonlinear relations within the pathway, key dynamic properties remained to be identified to predict possible strategies for intervention. We report the development of dynamic pathway models based on quantitative data collected on signaling components of JAK/STAT pathway in two lymphoma-derived cell lines, MedB-1 and L1236, representative of PMBL and cHL, respectively. We show that the amounts of STAT5 and STAT6 are higher whereas those of SHP1 are lower in the two lymphoma cell lines than in normal B cells. Distinctively, L1236 cells harbor more JAK2 and less SHP1 molecules per cell than MedB-1 or control cells. In both lymphoma cell lines, we observe interleukin-13 (IL13)-induced activation of IL4 receptor α, JAK2, and STAT5, but not of STAT6. Genome-wide, 11 early and 16 sustained genes are upregulated by IL13 in both lymphoma cell lines. Specifically, the known STAT-inducible negative regulators CISH and SOCS3 are upregulated within 2 hours in MedB-1 but not in L1236 cells. On the basis of this detailed quantitative information, we established two mathematical models, MedB-1 and L1236 model, able to describe the respective experimental data. Most of the model parameters are identifiable and therefore the models are predictive. Sensitivity analysis of the model identifies six possible therapeutic targets able to reduce gene expression levels in L1236 cells and three in MedB-1. We experimentally confirm reduction in target gene expression in response to inhibition of STAT5 phosphorylation, thereby validating one of the predicted targets.

Division of labor by dual feedback regulators controls JAK2/STAT5 signaling over broad ligand range

Cellular signal transduction is governed by multiple feedback mechanisms to elicit robust cellular decisions. The specific contributions of individual feedback regulators, however, remain unclear. Based on extensive time-resolved data sets in primary erythroid progenitor cells, we established a dynamic pathway model to dissect the roles of the two transcriptional negative feedback regulators of the suppressor of cytokine signaling (SOCS) family, CIS and SOCS3, in JAK2/STAT5 signaling. Facilitated by the model, we calculated the STAT5 response for experimentally unobservable Epo concentrations and provide a quantitative link between cell survival and the integrated response of STAT5 in the nucleus. Model predictions show that the two feedbacks CIS and SOCS3 are most effective at different ligand concentration ranges due to their distinct inhibitory mechanisms. This divided function of dual feedback regulation enables control of STAT5 responses for Epo concentrations that can vary 1000-fold in vivo. Our modeling approach reveals dose-dependent feedback control as key property to regulate STAT5-mediated survival decisions over a broad range of ligand concentrations.

Reverse Engineering of Bacterial Chemotaxis Pathway via Frequency Domain Analysis

Chemotaxis is defined as a behavior involving organisms sensing attractants or repellents and leading towards or away from them. Therefore, it is possible to reengineer chemotaxis network to control the movement of bacteria to our advantage. Understanding the design principles of chemotaxis pathway is a prerequisite and an important topic in synthetic biology. Here, we provide guidelines for chemotaxis pathway design by employing control theory and reverse engineering concept on pathway dynamic design. We first analyzed the mathematical models for two most important kinds of E. coli chemotaxis pathway—adaptive and non-adaptive pathways, and concluded that the control units of the pathway de facto function as a band-pass filter and a low-pass filter, respectively, by abstracting the frequency response properties of the pathways. The advantage of the band-pass filter is established, and we demonstrate how to tune the three key parameters of it—A (max amplification), ω1 (down cut-off frequency) and ω2 (up cut-off frequency) to optimize the chemotactic effect. Finally, we hypothesized a similar but simpler version of the dynamic pathway model based on the principles discovered and show that it leads to similar properties with native E. coli chemotactic behaviors. Our study provides an example of simulating and designing biological dynamics in silico and indicates how to make use of the native pathway's features in this process. Furthermore, the characteristics we discovered and tested through reverse engineering may help to understand the design principles of the pathway and promote the design of artificial chemotaxis pathways.

Dynamic folding pathway models of the villin headpiece subdomain (HP‐36) structure

We have investigated the folding pathway of the 36-residue villin headpiece subdomain (HP-36) by action-derived molecular dynamics simulations. The folding is initiated by hydrophobic collapse, after which the concurrent formation of full tertiary structure and alpha-helical secondary structure is observed. The collapse is observed to be associated with a couple of specific native contacts contrary to the conventional nonspecific hydrophobic collapse model. Stable secondary structure formation after the collapse suggests that the folding of HP-36 follows neither the framework model nor the diffusion-collision model. The C-terminal helix forms first, followed by the N-terminal helix positioned in its native orientation. The short middle helix is shown to form last. Signs for multiple folding pathways are also observed.

Dynamic Pathway Models for Ion Transport in Nanostructured Heterolayers

AbstractThe influence of local structure variations on the charge transport properties are still not well understood at an atomic level. In this work the experimentally observed drastic conductivity enhancement in epitactic stacks of BaF2:CaF2 heterolayers compared to any of the two fluoride ion conducting phases is reproduced by molecular dynamics simulations and analyzed in detail with particular emphasis on the variation of properties with the distance to the two-phase boundary. Ion mobility varies with the distance to the interface but remains significantly enhanced throughout the modeled layers when compared to bulk materials.The bond valence method is utilized to study correlations between the conductivity enhancement and the microstructure. A time-averaged violation of local electroneutrality postulated in the mesoscopic multiphase model is verified by the bond valence analysis of the molecular dynamics simulation trajectories. The variation of the ion mobility can be related to the extension of clusters of unoccupied accessible pathway regions.

Dynamic folding pathway models of α-helix and β-hairpin structures

We present dynamic folding pathway models of α-helix and β-hairpin structures at atomistic details by using the action-derived molecular dynamics method. The present formulation is free from common assumptions widely used in molecular dynamics such as high temperature simulations, a choice of order parameter set, an arbitrary identification of the folded configuration, or an exponential kinetics. The present dynamic folding pathway models for both helix and hairpin formations are consistent with experimental data.

Dynamic pathway model for the formation of C(60).

We present a dynamic pathway model for the formation of C(60) using the action-derived molecular dynamics simulations. We propose candidate precursors for dynamic pathway models in which carbons spontaneously aggregate due to favorable energetics and kinetics. Various planar polycyclic models are in a disadvantageous state where they cannot be trapped in the forward reaction due to their high excess internal energies. Our simulation results show that precursors either in the shape of tangled polycyclics or in the shape of open cages are kinetically favored over precursors in the shape of planar hexagonal graphite fragments. Calculated activation energies for the probable precursor models are in good agreement with experiment. Existence of chains in the models of tangled polycyclics and open cages is beneficially for the formation of C(60) molecule. Chains attached to the precursor model are energetically favorable and display lithe movements along the dynamic pathway.

Lateralization of auditory language functions: A dynamic dual pathway model

Spoken language comprehension requires the coordination of different subprocesses in time. After the initial acoustic analysis the system has to extract segmental information such as phonemes, syntactic elements and lexical-semantic elements as well as suprasegmental information such as accentuation and intonational phrases, i.e., prosody. According to the dynamic dual pathway model of auditory language comprehension syntactic and semantic information are primarily processed in a left hemispheric temporo-frontal pathway including separate circuits for syntactic and semantic information whereas sentence level prosody is processed in a right hemispheric temporo-frontal pathway. The relative lateralization of these functions occurs as a result of stimulus properties and processing demands. The observed interaction between syntactic and prosodic information during auditory sentence comprehension is attributed to dynamic interactions between the two hemispheres.