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Type I interferons (IFN) induce powerful antiviral and innate immune responses via the transcription factor, IFN‐stimulated gene factor (ISGF3). However, in some pathological contexts, type I IFNs are responsible for exacerbating inflammation. Here, we show that a high dose of IFN‐β also activates an inflammatory gene expression program in contrast to IFN‐λ3, a type III IFN, which elicits only the common antiviral gene program. We show that the inflammatory gene program depends on a second, potentiated phase in ISGF3 activation. Iterating between mathematical modeling and experimental analysis, we show that the ISGF3 activation network may engage a positive feedback loop with its subunits IRF9 and STAT2. This network motif mediates stimulus‐specific ISGF3 dynamics that are dependent on ligand, dose, and duration of exposure, and when engaged activates the inflammatory gene expression program. Our results reveal a previously underappreciated dynamical control of the JAK–STAT/IRF signaling network that may produce distinct biological responses and suggest that studies of type I IFN dysregulation, and in turn therapeutic remedies, may focus on feedback regulators within it. Synopsis The dose and duration of type I interferon exposure is interpreted by a signaling module that contains a stimulus‐contingent positive feedback loop to specify ISGF3 activation dynamics. A secondary, potentiated phase of ISGF3 activates a pro‐inflammatory gene expression program. High‐dose IFN‐β activates a pro‐inflammatory gene program in epithelial cells. IFN‐β, but not IFN‐λ3, induces a second, potentiated phase in ISGF3 activity. ISGF3 induces its subunits to form a stimulus‐contingent positive feedback loop. The positive feedback motif is required for the pro‐inflammatory gene program. Graphical Abstract The dose and duration of type I interferon exposure is interpreted by a signaling module that contains a stimulus‐contingent positive feedback loop to specify ISGF3 activation dynamics. A secondary, potentiated phase of ISGF3 activates a pro‐inflammatory gene expression program.

In this paper, we propose a logic-in-memory (LIM) inverter comprising a silicon nanowire (SiNW) n-channel feedback field-effect transistor (n-FBFET) and a SiNW p-channel metal oxide semiconductor field-effect transistor (p-MOSFET). The hybrid logic and memory operations of the LIM inverter were investigated by mixed-mode technology computer-aided design simulations. Our LIM inverter exhibited a high voltage gain of 296.8 (V/V) when transitioning from logic ‘1’ to ‘0’ and 7.9 (V/V) when transitioning from logic ‘0’ to ‘1’, while holding calculated logic at zero input voltage. The energy band diagrams of the n-FBFET structure demonstrated that the holding operation of the inverter was implemented by controlling the positive feedback loop. Moreover, the output logic can remain constant without any supply voltage, resulting in zero static power consumption.

Signal transduction and cytoskeleton networks in a wide variety of cells display excitability, but the mechanisms are poorly understood. Here, we show that during random migration and in response to chemoattractants, cells maintain complementary spatial and temporal distributions of Ras activity and phosphatidylinositol (3,4)-bisphosphate [PI(3,4)P₂]. In addition, depletion of PI(3,4)P₂ by disruption of the 5-phosphatase, Dd5P4, or by recruitment of 4-phosphatase INPP4B to the plasma membrane, leads to elevated Ras activity, cell spreading, and altered migratory behavior. Furthermore, RasGAP2 and RapGAP3 bind to PI(3,4)P₂, and the phenotypes of cells lacking these genes mimic those with low PI(3,4)P₂ levels, providing a molecular mechanism. These findings suggest that Ras activity drives PI(3,4)P₂ down, causing the PI(3,4)P₂-binding GAPs to dissociate from the membrane, further activating Ras, completing a positive-feedback loop essential for excitability. Consistently, a computational model incorporating such a feedback loop in an excitable network model accurately simulates the dynamic distributions of active Ras and PI(3,4)P₂ as well as cell migratory behavior. The mutually inhibitory Ras-PI(3,4)P₂ mechanisms we uncovered here provide a framework for Ras regulation that may play a key role in many physiological processes.

Summary After a period of heavy emphasis on negative interactions, such as predation and competition, the past two decades have seen an explosion of literature on the role of positive interactions in ecological communities. Such positive interactions can take many forms. One possibility is that amelioration of environmental stress by plants or sessile animals enhances growth, reproduction and survival of others, but many more intricate patterns exist. Importantly such positive interactions may contribute to creating a positive feedback. For instance, biomass can lead to improved environmental conditions causing better growth and therefore leading to more biomass. A positive feedback is a necessary (but not sufficient) condition for the emergence of alternative stable states at the community scale. However, the literature on positive interactions in plant and animal communities rarely addresses this connection. Here, we address this gap, asking the question of when positive interactions may lead to alternative stable states, and hence set the stage for catastrophic transitions at tipping points in ecosystems. We argue that, although there are a number of now classical examples in the literature for which positive interactions are clearly the main actors of positive feedback loops, more empirical and theoretical research scaling up from the individual‐level interactions to the community and the ecosystem scale processes is needed to further understand under which conditions positive interactions can trigger positive feedback loops, and thereby alternative stable states. Lay Summary

Background Recent data indicated that macrophages may mutually interact with cancer cells to promote tumor progression and chemoresistance, but the interaction in cholangiocarcinoma (CCA) is obscure. Methods 10x Genomics single-cell sequencing technology was used to identified the role of macrophages in CCA. Then, we measured the expression and prognostic role of macrophage markers and aPKC ɩ in 70 human CCA tissues. Moreover, we constructed monocyte-derived macrophages (MDMs) generated from peripheral blood monocytes (PBMCs) and polarized them into M1/M2 macrophages. A co-culture assay of the human CCA cell lines (TFK-1, EGI-1) and differentiated PBMCs-macrophages was established, and functional studies in vitro and in vivo was performed to explore the interaction between cancer cells and M2 macrophages. Furthermore, we established the cationic liposome-mediated co-delivery of gemcitabine and aPKC ɩ -siRNA and detect the antitumor effects in CCA. Results M2 macrophage showed tumor-promoting properties in CCA. High levels of aPKC ɩ expression and M2 macrophage infiltration were associated with metastasis and poor prognosis in CCA patients. Moreover, CCA patients with low M2 macrophages infiltration or low aPKC ɩ expression benefited from postoperative gemcitabine-based chemotherapy. Further studies showed that M2 macrophages-derived TGFβ1 induced epithelial-mesenchymal transition (EMT) and gemcitabine resistance in CCA cells through aPKC ɩ -mediated NF-κB signaling pathway. Reciprocally, CCL5 was secreted more by CCA cells undergoing aPKC ɩ -induced EMT and consequently modulated macrophage recruitment and polarization. Furthermore, the cationic liposome-mediated co-delivery of GEM and aPKC ɩ -siRNA significantly inhibited macrophages infiltration and CCA progression. Conclusion our study demonstrates the role of Macrophages-aPKC ɩ -CCL5 Feedback Loop in CCA, and proposes a novel therapeutic strategy of aPKC ɩ -siRNA and GEM co-delivered by liposomes for CCA.

The Alzheimer’s disease (AD) is a neurodegenerative disease, which is caused by the aggregation of beta-amyloid peptide ( A β ) in the patient’s brain and the disorder of Ca 2 + homeostasis in neurons. Caluwé and Dupont (Theor Biol 331:12–18, 2013) proposed a deterministic AD model to explore the effect of Ca 2 + on AD. They demonstrated the positive feedback loop between A β and Ca 2 + : and the occurrence of bistability. Based on their results, we further discuss the bistable behaviors. We present two periodically feasible drug strategies to alleviate the AD and screen out more effective one. In this paper, we also formulate a stochastic AD model, analyze the existence and uniqueness of global positive solutions and establish sufficient conditions for the existence of ergodic stationary distribution. Furthermore, the confidence ellipses describing the configurational arrangement of stochastic coexistence equilibria are constructed by stochastic sensitivity function technique, and tipping threshold is estimated as well. Noise-induced stochastic switching between two coexistence equilibria is observed in bistability region. Our results provide a new idea to control noise to alleviate AD through physical therapy.

Positive feedback driven by transcriptional regulation has long been considered a key mechanism underlying cell lineage segregation during embryogenesis. Using the developing spinal cord as a paradigm, we found that canonical, transcription‐driven feedback cannot explain robust lineage segregation of motor neuron subtypes marked by two cardinal factors, Hoxa5 and Hoxc8. We propose a feedback mechanism involving elementary microRNA–mRNA reaction circuits that differ from known feedback loop‐like structures. Strikingly, we show that a wide range of biologically plausible post‐transcriptional regulatory parameters are sufficient to generate bistable switches, a hallmark of positive feedback. Through mathematical analysis, we explain intuitively the hidden source of this feedback. Using embryonic stem cell differentiation and mouse genetics, we corroborate that microRNA–mRNA circuits govern tissue boundaries and hysteresis upon motor neuron differentiation with respect to transient morphogen signals. Our findings reveal a previously underappreciated feedback mechanism that may have widespread functions in cell fate decisions and tissue patterning. SYNOPSIS Robust cell fate decision and precise tissue boundary formation are critical for development. This study reports a feedback mechanism involving mRNA‐microRNA interactions during cell lineage segregation in mouse spinal cord development. Robust lineage segregation of mouse Hoxa5 + and Hoxc8 + motor neurons does not require canonical transcriptional feedback loops. Mathematical modeling derives a wide range of biologically plausible parameters that allow bistability to arise from post‐transcriptional networks. An intuitive interpretation of the mathematical analysis reveals a hidden feedback mechanism involving mRNA‐microRNA interactions. In vitro and in vivo experiments validate the critical roles of two microRNAs in lineage segregation and tissue boundary formation. Graphical Abstract Robust cell fate decision and precise tissue boundary formation are critical for development. This study reports a feedback mechanism involving mRNA‐microRNA interactions during cell lineage segregation in mouse spinal cord development.

Many types of multiple positive feedbacks with each having potentials to generate bistability exist extensively in natural, raising the question of why a particular architecture is present in a cell. In this study, the authors investigate multiple positive feedback loops across three classes: one-loop class, two-loop class and three-loop class, where each class is composed of double positive feedback loop (DPFL) or double negative feedback loop (DNFL) or both. Through large-scale sampling and robustness analysis, the authors find that for a given class, the homogeneous DPFL circuit (i.e. the coupled circuit that is composed of only DPFLs) is more robust than all the other circuits in generating bistable behaviour. In addition, stochastic simulation shows that the low stable state is more robust than the high stable state in homogeneous DPFL whereas the high-stable state is more robust than the low-stable state in homogeneous DNFL circuits. It was argued that this investigation provides insight into the relationship between robustness and network architecture.

Many governments and organisations are currently aligning many aspects of their policies and practices to the sustainable development goals (SDGs). Achieving the SDGs should increase social-ecological resilience to shocks like climate change and its impacts. Here, we consider the relationship amongst the three elements—the SDGs, social-ecological resilience and climate change—as a positive feedback loop. We argue that long-term memory encoded in historical, archaeological and related ‘palaeo-data’ is central to understanding each of these elements of the feedback loop, especially when long-term fluctuations are inherent in social-ecological systems and their responses to abrupt change. Yet, there is scant reference to the valuable contribution that can be made by these data from the past in the SDGs or their targets and indicators. The historical and archaeological records emphasise the importance of some key themes running through the SDGs including how diversity, inclusion, learning and innovation can reduce vulnerability to abrupt change, and the role of connectivity. Using paleo-data, we demonstrate how changes in the extent of water-related ecosystems as measured by indicator 6.6.1 may simply be related to natural hydroclimate variability, rather than reflecting actual progress towards Target 6.6. This highlights issues associated with using SDG indicator baselines predicated on short-term and very recent data only. Within the context of the contributions from long-term data to inform the positive feedback loop, we ask whether our current inability to substantively combat anthropogenic climate change threatens achieving both the SDGS and enhanced resilience to climate change itself. We argue that long-term records are central to understanding how and what will improve resilience and enhance our ability to both mitigate and adapt to climate change. However, for uptake of these data to occur, improved understanding of their quality and potential by policymakers and managers is required.

Abstract Myofibroblasts are central mediators of fibrosis. Typically derived from resident fibroblasts, myofibroblasts represent a heterogeneous population of cells that are principally defined by acquired contractile function and high synthetic ability to produce extracellular matrix (ECM). Current literature sheds new light on the critical role of ECM signaling coupled with mechanotransduction in driving myofibroblastic activation. In particular, transforming growth factor β1 (TGF-β1) and extra domain A containing fibronectin (EDA-FN) are thought to be the primary ECM signaling mediators that form and also induce positive feedback loops. The outside-in and inside-out signaling circuits are transmitted and integrated by TGF-β receptors and integrins at the cell membrane, ultimately perpetuating the abundance and activities of TGF-β1 and EDA-FN in the ECM. In this review, we highlight these conceptual advances in understanding myofibroblastic activation, in hope of revealing its therapeutic anti-fibrotic implications.