Plant-Soil Moisture Positive Feedback Maintaining Alternative Stable States in the Alpine Marsh Ecosystem.

A self-reinforcing positive feedback is regarded as a critical process for maintaining alternative stable states (ASS); however, identification of ASS and quantification of positive feedbacks remain elusive in natural ecosystems. Here, we used large-scale field surveys to search for ASS and a positive feedback mechanism under a wide range of habitats on the Tibetan Plateau. Using multiple methods, we proved that three stable states exist that accompany alpine marsh degradation. Positive feedbacks between changing soil moisture and plant community composition forced the ecosystem into another stable state, and the alteration of water use efficiency (WUE) of the component species contributed to this shift. This study provides the first empirical evidence that positive feedback loops maintain ASS in the alpine marsh ecosystem on the Tibetan Plateau. Our research revealed the powerful driving role of plants in transitions between states, which may support the conservation and restoration of global alpine marsh ecosystems.

Fostering TBL Success at Alfaisal University: A Complex Adaptive Systems Approach.

This study explores the implementation of Team-Based Learning (TBL) at Alfaisal University's College of Medicine through the lens of Complex Adaptive Systems (CAS) theory. The research question investigates how the application of CAS principles can enhance the implementation and effectiveness of TBL in medical education. The study employed a convergent parallel mixed methods longitudinal design, integrating quantitative performance metrics and qualitative themes. Quantitative analysis revealed modest improvements in individual and team-based learning scores, with a promising trend of students moving from the lower to the higher quartiles over time. Qualitative insights aligned with CAS principles, highlighting the adaptive implementation, emergent outcomes, self-organization, positive feedback loops, and depth of learning facilitated by TBL. The findings demonstrate the value of a CAS-informed approach in navigating the complexities of educational change and fostering a more resilient and adaptive educational model. The study contributes to the understanding of how CAS theory can guide the successful implementation of innovative pedagogies like TBL in medical education.

LncRNA PTENP1/miR-21/PTEN Axis Modulates EMT and Drug Resistance in Cancer: Dynamic Boolean Modeling for Cell Fates in DNA Damage Response.

It is well established that microRNA-21 (miR-21) targets phosphatase and tensin homolog (PTEN), facilitating epithelial-to-mesenchymal transition (EMT) and drug resistance in cancer. Recent evidence indicates that PTEN activates its pseudogene-derived long non-coding RNA, PTENP1, which in turn inhibits miR-21. However, the dynamics of PTEN, miR-21, and PTENP1 in the DNA damage response (DDR) remain unclear. Thus, we propose a dynamic Boolean network model by integrating the published literature from various cancers. Our model shows good agreement with the experimental findings from breast cancer, hepatocellular carcinoma (HCC), and oral squamous cell carcinoma (OSCC), elucidating how DDR activation transitions from the intra-S phase to the G2 checkpoint, leading to a cascade of cellular responses such as cell cycle arrest, senescence, autophagy, apoptosis, drug resistance, and EMT. Model validation underscores the roles of PTENP1, miR-21, and PTEN in modulating EMT and drug resistance. Furthermore, our analysis reveals nine novel feedback loops, eight positive and one negative, mediated by PTEN and implicated in DDR cell fate determination, including pathways related to drug resistance and EMT. Our work presents a comprehensive framework for investigating cellular responses following DDR, underscoring the therapeutic potential of targeting PTEN, miR-21, and PTENP1 in cancer treatment.

Mapping complex public health problems with causal loop diagrams.

This paper presents causal loop diagrams (CLDs) as tools for studying complex public health problems like health inequality. These problems often involve feedback loops-a characteristic of complex systems not fully integrated into mainstream epidemiology. CLDs are conceptual models that visualize connections between system variables. They are commonly developed through literature reviews or participatory methods with stakeholder groups. These diagrams often uncover feedback loops among variables across scales (e.g. biological, psychological and social), facilitating cross-disciplinary insights. We illustrate their use through a case example involving the feedback loop between sleep problems and depressive symptoms. We outline a typical step-by-step process for developing CLDs in epidemiology. These steps are defining a specific problem, identifying the key system variables involved, mapping these variables and analysing the CLD to find new insights and possible intervention targets. Throughout this process, we suggest triangulating between diverse sources of evidence, including domain knowledge, scientific literature and empirical data. CLDs can also be evaluated to guide policy changes and future research by revealing knowledge gaps. Finally, CLDs may be iteratively refined as new evidence emerges. We advocate for more widespread use of complex systems tools, like CLDs, in epidemiology to better understand and address complex public health problems.

Follow the Arrows: Using a Co-Created Causal Loop Diagram to Explore Leverage Points to Strengthen Population Physical Activity Promotion in British Columbia, Canada.

BACKGROUND: Population physical activity promotion (PPAP) is one of the most effective noncommunicable disease prevention strategies, yet coordination is lacking around the world. Whole-of-system approaches and complex systems methods are called for to advance PPAP. This paper reports on a project which (1) used an Attributes Framework with system mapping (group model building and causal loop diagramming of feedback loops) and (2) identified potential leverage points to address the challenge of effective coordination of multisectoral PPAP in British Columbia. METHODS: Key findings from stakeholder interviews and workshops described the current system for PPAP in terms of attributes and dimensions in the framework. These were translated into variables and used in group model building. Participants prioritized the importance of variables to address the coordination challenge and then created causal loop diagrams in 3 small groups. One collective causal loop diagram was created, and top priority variables and associated feedback loops were highlighted to explore potential leverage points. RESULTS: Leverage points included the relationships and feedback loops among priority variables: political leadership, visible policy support and governance, connectivity for knowledge translation, collaborative multisector grants, multisector collaboration, and integrating co-benefits. Leveraging and altering "vicious" cyclical patterns to increase coordinated multisector PPAP are key. CONCLUSIONS: The Attributes Framework, group model building and causal loop diagrams, and emergent feedback loops were useful to explore potential leverage points to address the challenge of multisectoral coordination of PPAP. Future research could apply the same methods in other jurisdictions and compare and contrast resultant frameworks, variables, feedback loops, and leverage points.

A Note on Modelling Bidirectional Feedback Loops in Mendelian Randomization Studies.

Structural equation models (SEMs) involving feedback loops may offer advantages over standard instrumental variables estimators in terms of modelling causal effects in the presence of bidirectional relationships. In the following note, we show that in the case of a single "exposure" and "outcome" variable, modelling relationships using a SEM with a simple bidirectional linear feedback loop offers no advantage over traditional instrumental variables estimators in terms of consistency (i.e. both approaches yield consistent estimates of the causal effect, provided that causal estimates are obtained in both directions). In the case of finite samples, traditional IV estimators and SEM exhibited similar power across many of the conditions we examined, although which method performed best depended on the residual correlation between variables and the strength of the instruments. In particular, the power of SEM was insensitive to the residual correlation between variables, whereas the power of the Wald estimator/2SLS improved (deteriorated) relative to SEM as the magnitude of the residual correlation increased (decreased) assuming a positive causal effect of the exposure on the outcome. The power of SEM improved relative to the Wald estimator/2SLS as the instruments explained more residual variance in the "outcome" variable.

Network switches and their role in circadian clocks.

Circadian rhythms are generated by complex interactions among genes and proteins. Self-sustained ∼24 h oscillations require negative feedback loops and sufficiently strong nonlinearities that are the product of molecular and network switches. Here, we review common mechanisms to obtain switch-like behavior, including cooperativity, antagonistic enzymes, multisite phosphorylation, positive feedback, and sequestration. We discuss how network switches play a crucial role as essential components in cellular circadian clocks, serving as integral parts of transcription-translation feedback loops that form the basis of circadian rhythm generation. The design principles of network switches and circadian clocks are illustrated by representative mathematical models that include bistable systems and negative feedback loops combined with Hill functions. This work underscores the importance of negative feedback loops and network switches as essential design principles for biological oscillations, emphasizing how an understanding of theoretical concepts can provide insights into the mechanisms generating biological rhythms.

Assessing a potential conflict associated with the production of Moringa oleifera in the Limpopo Province of South Africa: A systems thinking approach.

The increased movement of humans throughout the world allowed the transportation of several species, such as Moringa oleifera Lam. (moringa), into biomes far away from their native habitation. Native to India, moringa is a versatile, drought-tolerant, and fast-growing tree that is easily adaptable to wide-ranging tropical and sub-tropical conditions around the world. It is used in cosmetics, as food and medicine for humans, livestock feed, crop biostimulant, and green manure. Even though moringa is an alien species to South Africa, its production is increasing, and its numerous uses are recognised by communities. Moringa forms part of a highly complex (social, ecological, and economic) system. This is because it is on the Species Under Surveillance for Possible Eradication or Containment Targets (SUSPECT) list under the National Environmental Management Biodiversity Act (NEM:BA) of South Africa. Listing species that are regarded as beneficial to communities on national regulations can cause conflicts and uncertainties among various stakeholders (i.e., environmental policymakers, farmers, rural communities, and government bodies). In this paper, a systems thinking approach was applied to address complex and conflicting issues linked to the production and overall status (economic, ecological, legal, and social) of moringa in South Africa. The Causal Loop Diagram (CLD) was developed to present a broad insight into the complexity of moringa in South Africa and assist in underscoring the feedback mechanisms within the system. Moreover, the CLD indicated that the position of moringa within the country comprised a variety of interdependent variables of government policies, environment, and society, which are interconnected into a multifaceted system. The potential conflict dimensions and types associated with allocating moringa an impact category within the South African context were identified, and this may serve as a useful tool for facilitating engagements and decision-making processes among stakeholders in resolving the status of moringa in South Africa.

Comprehensive Parameter Space Mapping of Cell Cycle Dynamics under Network Perturbations.

Studies of quantitative systems and synthetic biology have extensively utilized models to interpret data, make predictions, and guide experimental designs. However, models often simplify complex biological systems and lack experimentally validated parameters, making their reliability in perturbed systems unclear. Here, we developed a droplet-based synthetic cell system to continuously tune parameters at the single-cell level in multiple dimensions with full dynamic ranges, providing an experimental framework for global parameter space scans. We systematically perturbed a cell-cycle oscillator centered on cyclin-dependent kinase (Cdk1), enabling comprehensive mapping of period landscapes in response to network perturbations. The data allowed us to challenge existing models and refine a new model that matches the observed response. Our analysis demonstrated that Cdk1 positive feedback inhibition restricts the cell cycle frequency range, confirming model predictions; furthermore, it revealed new cellular responses to the inhibition of the Cdk1-counteracting phosphatase PP2A: monomodal or bimodal distributions across varying inhibition levels, underscoring the complex nature of cell cycle regulation that can be explained by our model. This comprehensive perturbation platform may be generalizable to exploring other complex dynamic systems.

Artificial Homeostasis Systems Based on Feedback Reaction Networks: Design Principles and Future Promises.

Feedback-controlled chemical reaction networks (FCRNs) are indispensable for various biological processes, such as cellular mechanisms, patterns, and signaling pathways. Through the intricate interplay of many feedback loops (FLs), FCRNs maintain a stable internal cellular environment. Currently, creating minimalistic synthetic cells is the long-term objective of systems chemistry, which is motivated by such natural integrity. The design, kinetic optimization, and analysis of FCRNs to exhibit functions akin to those of a cell still pose significant challenges. Indeed, reaching synthetic homeostasis is essential for engineering synthetic cell components. However, maintaining homeostasis in artificial systems against various agitations is a difficult task. Several biological events can provide us with guidelines for a conceptual understanding of homeostasis, which can be further applicable in designing artificial synthetic systems. In this regard, we organize our review with artificial homeostasis systems driven by FCRNs at different length scales, including homogeneous, compartmentalized, and soft material systems. First, we stretch a quick overview of FCRNs in different molecular and supramolecular systems, which are the essential toolbox for engineering different nonlinear functions and homeostatic systems. Moreover, the existing history of synthetic homeostasis in chemical and material systems and their advanced functions with self-correcting, and regulating properties are also emphasized.

Feedback loops drive ecological succession: towards a unified conceptual framework.

The core principle shared by most theories and models of succession is that, following a major disturbance, plant-environment feedback dynamics drive a directional change in the plant community. The most commonly studied feedback loops are those in which the regrowth of the plant community causes changes to the abiotic (e.g. soil nutrients) or biotic (e.g. dispersers) environment, which differentially affect species availability or performance. This, in turn, leads to shifts in the species composition of the plant community. However, there are many other PE feedback loops that potentially drive succession, each of which can be considered a model of succession. While plant-environment feedback loops in principle generate predictable successional trajectories, succession is generally observed to be highly variable. Factors contributing to this variability are the stochastic processes involved in feedback dynamics, such as individual mortality and seed dispersal, and extrinsic causes of succession, which are not affected by changes in the plant community but do affect species performance or availability. Both can lead to variation in the identity of dominant species within communities. This, in turn, leads to further contingencies if these species differ in their effect on their environment (priority effects). Predictability and variability are thus intrinsically linked features of ecological succession. We present a new conceptual framework of ecological succession that integrates the propositions discussed above. This framework defines seven general causes: landscape context, disturbance and land-use, biotic factors, abiotic factors, species availability, species performance, and the plant community. When involved in a feedback loop, these general causes drive succession and when not, they are extrinsic causes that create variability in successional trajectories and dynamics. The proposed framework provides a guide for linking these general causes into causal pathways that represent specific models of succession. Our framework represents a systematic approach to identifying the main feedback processes and causes of variation at different successional stages. It can be used for systematic comparisons among study sites and along environmental gradients, to conceptualise studies, and to guide the formulation of research questions and design of field studies. Mapping an extensive field study onto our conceptual framework revealed that the pathways representing the study's empirical outcomes and conceptual model had important differences, underlining the need to move beyond the conceptual models that currently dominate in specific fields and to find ways to examine the importance of and interactions among alternative causal pathways of succession. To further this aim, we argue for integrating long-term studies across environmental and anthropogenic gradients, combined with controlled experiments and dynamic modelling.

The Dual Role of Sulforaphane-Induced Cellular Stress-A Systems Biological Study.

The endoplasmic reticulum (ER) plays a crucial role in cellular homeostasis. When ER stress is generated, an autophagic self-digestive process is activated to promote cell survival; however, cell death is induced in the case of excessive levels of ER stress. The aim of the present study was to investigate the effect of a natural compound called sulforaphane (SFN) upon ER stress. Our goal was to investigate how SFN-dependent autophagy activation affects different stages of ER stress induction. We approached our scientific analysis from a systems biological perspective using both theoretical and molecular biological techniques. We found that SFN induced the various cell-death mechanisms in a concentration- and time-dependent manner. The short SFN treatment at low concentrations promoted autophagy, whereas the longer treatment at higher concentrations activated cell death. We proved that SFN activated autophagy in a mTORC1-dependent manner and that the presence of ULK1 was required for its function. A low concentration of SFN pre- or co-treatment combined with short and long ER stress was able to promote cell survival via autophagy induction in each treatment, suggesting the potential medical importance of SFN in ER stress-related diseases.

A dynamic Boolean network reveals that the BMI1 and MALAT1 axis is associated with drug resistance by limiting miR-145-5p in non-small cell lung cancer.

Patients with non-small cell lung cancer (NSCLC) are often treated with chemotherapy. Poor clinical response and the onset of chemoresistance limit the anti-tumor benefits of drugs such as cisplatin. According to recent research, metastasis-associated lung adenocarcinoma transcript 1 (MALAT1) is a long non-coding RNA related to cisplatin resistance in NSCLC. Furthermore, MALAT1 targets microRNA-145-5p (miR-145), which activates Krüppel-like factor 4 (KLF4) in associated cell lines. B lymphoma Mo-MLV insertion region 1 homolog (BMI1), on the other hand, inhibits miR-145 expression, which stimulates Specificity protein 1 (Sp1) to trigger the epithelial-mesenchymal transition (EMT) process in pemetrexed-resistant NSCLC cells. The interplay between these molecules in drug resistance is still unclear. Therefore, we propose a dynamic Boolean network that can encapsulate the complexity of these drug-resistant molecules. Using published clinical data for gain or loss-of-function perturbations, our network demonstrates reasonable agreement with experimental observations. We identify four new positive circuits: miR-145/Sp1/MALAT1, BMI1/miR-145/Myc, KLF4/p53/miR-145, and miR-145/Wip1/p38MAPK/p53. Notably, miR-145 emerges as a central player in these regulatory circuits, underscoring its pivotal role in NSCLC drug resistance. Our circuit perturbation analysis further emphasizes the critical involvement of these new circuits in drug resistance for NSCLC. In conclusion, targeting MALAT1 and BMI1 holds promise for overcoming drug resistance, while activating miR-145 represents a potential strategy to significantly reduce drug resistance in NSCLC.

Weakened casual feedback loops following intensive restoration efforts and climate changes in a large shallow freshwater lake.

Understanding how phytoplankton interacts with local and regional drivers as well as their feedbacks is a great challenge, and quantitative analyses of the regulating role of human activities and climate changes on these feedback loops are also limited. By using monthly monitoring dataset (2000-2017) from Lake Taihu and empirical dynamic modelling to construct causal networks, we quantified the strengths of causal feedbacks among phytoplankton, local environments, zooplankton, meteorology as well as global climate oscillation. Prevalent bidirectional causal linkages between phytoplankton biomass (chlorophyll a) and the tested drivers were found, providing holistic and quantitative evidence of the ubiquitous feedback loops. Phytoplankton biomass exhibited the highest feedbacks with total inorganic nitrogen and ammonia and the lowest with nitrate. The feedbacks between phytoplankton biomass and environmental factors from 2000 to 2017 could be classified into two groups: the local environments (e.g., nutrients, pH, transparency, zooplankton biomass)-driven enhancement loops promoting the response of the phytoplankton biomass, and the climate (e.g., wind speed)-driven regulatory loops suppressing it. The two counterbalanced groups modified the emergent macroecological patterns. Our findings revealed that the causal feedback networks loosened significantly after 2007 following nutrient loading reduction and unsuccessful biomanipulation restoration attempts by stocking carp. The strength of enhancement loops underwent marked decreases leading to reduced phytoplankton responses to the tested drivers, while the climate (decreasing wind speed, warming winter)-driven regulatory loops increased- like a tug-of-war. To counteract the self-amplifying feedback loops, the present eutrophication mitigation efforts, especially nutrient reduction, should be continued, and introduction of alternative measures to indirectly regulate the critical components (e.g., pH, Secchi depth, zooplankton biomass) of the loops would be beneficial.

A system science perspective on burn-out: development of an expert-based causal loop diagram.

Introduction: Burn-out leads to reduced worker well-being, long-term absenteeism, and high costs for employers and society. Determinants at different levels may affect burn-out in an interrelated and dynamic manner. The aim of the present study was to apply a broader systems perspective by exploring and visualizing the complex system of determinants at different levels (living conditions, working conditions, and societal developments) underlying the prevalence of burn-out in the Netherlands. Methods: During three group model building (GMB) sessions with in total eight experts on workers' mental health, a causal loop diagram (CLD) was developed and relevant feedback loops were identified. For the selection of determinants to be included in the CLD a recently published overview of determinants on burn-out at different levels was used. Experts could also add factors that were not listed in the overview. Results: The final CLD consists of 20 factors and depicts a central position of working conditions. Societal developments (e.g., access to mental health care, size of the working population, rougher social climate, etc.) were mostly located at the outside of the CLD and barely integrated in feedback loops. Several reinforcing feedback loops resulting in an increase of the prevalence of burn-out were identified in which the factors (very) high workload, imbalance between work and private life, and insufficient recovery time play an important role. Also, several balancing loops were found that visualize the crucial role of functional support from supervisors to prevent burn-out among workers. Discussion: Applying a broader systems perspective, including determinants at different levels, offers new insights into dynamic feedback loops that contribute to the prevalence of burn-out. Supervisors, amongst others, have a considerable impact on the system underlying the high prevalence of burn-out and may therefore contribute to its prevention. Even though societal developments were less integrated in feedback loops, they might be considered drivers of existing feedback loops. The results from this study confirm that determinants at various levels underly the prevalence of burn-out. To be able to address the diversity of determinants underlying a high prevalence of burn-out, a complex system approach can be helpful.

Matrix stability and bifurcation analysis by a network-based approach.

In this paper, we develop a network-based methodology to investigate the problems related to matrix stability and bifurcations in nonlinear dynamical systems. By matching a matrix with a network, i.e., interaction graph, we propose a new network-based matrix analysis method by proving a theorem about matrix determinant under which matrix stability can be considered in terms of feedback loops. Especially, the approach can tell us how a node, a path, or a feedback loop in the interaction graph affects matrix stability. In addition, the roles played by a node, a path, or a feedback loop in determining bifurcations in nonlinear dynamical systems can also be revealed. Therefore, the approach can help us to screen optimal node or node combinations. By perturbing them, unstable matrices can be stabilized more efficiently or bifurcations can be induced more easily to realize desired state transitions. To illustrate feasibility and efficiency of the approach, some simple matrices are used to show how single or combinatorial perturbations affect matrix stability and induce bifurcations. In addition, the main idea is also illustrated through a biological problem related to T cell development with three nodes: TCF-1, GATA3, and PU.1, which can be considered to be a three-variable nonlinear dynamical system. The approach is especially helpful in understanding crucial roles of single or molecule combinations in biomolecular networks. The approach presented here can be expected to analyze other biological networks related to cell fate transitions and systematic perturbation strategy selection.

Do Psychedelics Facilitate Emergence of Unconscious Psychological Processes?

Psychedelic substances have a long history of use in traditional healing and religious ceremonies worldwide and are increasingly being investigated for their possible therapeutic usage. However, there is still a lack of consensus regarding how best to characterize the psychological effects of psychedelics and how they bring about the positive therapeutic outcomes observed in clinical studies. The aim of this article is to review available evidence from quantitative and qualitative studies on psychedelic-assisted therapy, as well as neurobiological studies, in relation to the hypothesis that psychedelics facilitate the emergence of emotionally charged unconscious material, originally proposed by pioneering psychedelics researcher Stanislav Grof. The reviewed process studies of therapeutic mechanisms in psychedelic-assisted therapy and qualitative studies of treatment participants clearly indicate that the psychedelic experience is associated with the subjective experience of having increased access to and awareness of emotions, memories, and perceptions that are normally avoided or outside of conscious awareness. Brain-imaging studies point to several different neurobiological effects of psychedelics that might be related to these subjective psychological experiences. Available evidence also indicates that this process might constitute an important therapeutic mechanism in psychedelic-assisted therapy, worthy of further investigation.

Feedback thinking in dairy farm management: system dynamics modelling for herd dynamics.

Systems perspectives and system dynamics have been widely used in decision-making for agricultural problems. However, their use in dairy farm management remains limited. This work demonstrates the use of systems approaches and feedback thinking in modelling for dairy farm management. The application of feedback thinking was illustrated with causal loop and stock-and-flow diagrams to disentangle the complexity of the relationship among farm elements. The study aimed to identify the dynamic processes of an intensive dairy farm by mapping the animal stocks (e.g., heifers, lactating cows, dry cows) with the final objective of anticipating the expected milk deliveries over a long time period. The project was conducted for a reference dairy farm that was intensively managed with a herd size of >2 500 cattle heads, which provided monthly farm records from Jan 2016 to Dec 2019. Model development steps included: (i) problem articulation with farm interviews and data analysis; (ii) the development of a dynamic hypothesis and a causal loop diagram; (iii) the development of a stock-and-flow cattle model describing ageing chains of heifers and cows and subsequent calibration of the model parameters; (iv) the evaluation of the model based on lactating cows and milk deliveries against farm historical records; and (v) the analysis of the model results. The model characterized the farm dynamics using three main feedback loops: one balancing loop of culling and two reinforcing loops of heifers' replacement and cows' pregnancy, pushing milk delivery. The model reproduced the historical oscillation patterns of lactating cows and milk deliveries with high accuracy (root mean square percentage error of 2.8 and 5.2% for the number of lactating cows and milk deliveries, respectively). The model was shown to be valid for its purpose, and applications of this model in dairy farm management can support decision-making practices for herd composition and milk delivery targets.

The ups and downs of biological oscillators: a comparison of time-delayed negative feedback mechanisms.

Many biochemical oscillators are driven by the periodic rise and fall of protein concentrations or activities. A negative feedback loop underlies such oscillations. The feedback can act on different parts of the biochemical network. Here, we mathematically compare time-delay models where the feedback affects production and degradation. We show a mathematical connection between the linear stability of the two models, and derive how both mechanisms impose different constraints on the production and degradation rates that allow oscillations. We show how oscillations are affected by the inclusion of a distributed delay, of double regulation (acting on production and degradation) and of enzymatic degradation.