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Despite intensive investigations numerous diseases remain etiologically puzzling and recalcitrant to treatments. A hypothesis is proposed here assuming that these difficulties are due to an unsuitable approach to the mechanisms of life, which is subjugated by an apparent complexity and fails to grasp the uniformity that lays behind. The stability of metabolism, despite the enormous complex of chemical reactions, suggests that reciprocal control is a prerequisite of life. Negative feedback loops have been known for a long time to maintain homeostasis, while more recently, different life processes involved in transitions or changes have been modeled by positive loops giving rise to bistable switches, also including various diseases. The present hypothesis makes a generalization, by assuming that any functional element of a biological system is involved in a positive or a negative feedback loop. Consequently, the hypothesis holds that the starting mechanism of any disease that affects a healthy human can be conceptually reduced to a bistable or multistationary loop system, thus providing a unifying model leading to the discovery of critical therapeutic targets.

Despite intensive investigations numerous diseases remain etiologically puzzling and recalcitrant to treatments. A theory is proposed here assuming that these difficulties are due to an unsuitable approach to the mechanisms of life, which is subjugated by an apparent complexity and fails to grasp the uniformity that lays behind. The stability of metabolism, despite the enormous complex of chemical reactions, suggests that reciprocal control is a prerequisite of life. Negative feedback loops have been known for a long time to maintain homeostasis, while more recently, different life processes involved in transitions or changes have been modeled by positive loops giving rise to bistable switches, also including various diseases. The present theory makes a generalization, by assuming that any functional element of a biological system is involved in a positive or a negative feedback loop. Consequently, the theory holds that the starting mechanism of any disease that affects a healthy human can be conceptually reduced to a bistable or multistationary loop system, thus providing a unifying model leading to the discovery of critical therapeutic targets.

Pleiotropy, which refers to the ability of different mutations on the same gene to cause different pathological effects in human genetic diseases, is important in understanding system-level biological diseases. Although some biological experiments have been proposed, still little is known about pleiotropy on gene–gene dynamics, since most previous studies have been based on correlation analysis. Therefore, a new perspective is needed to investigate pleiotropy in terms of gene–gene dynamical characteristics. To quantify pleiotropy in terms of network dynamics, we propose a measure called in silico Pleiotropic Scores ( s P S ), which represents how much a gene is affected against a pair of different types of mutations on a Boolean network model. We found that our model can identify more candidate pleiotropic genes that are not known to be pleiotropic than the experimental database. In addition, we found that many types of functionally important genes tend to have higher s P S values than other genes; in other words, they are more pleiotropic. We investigated the relations of s P S with the structural properties in the signaling network and found that there are highly positive relations to degree, feedback loops, and centrality measures. This implies that the structural characteristics are principles to identify new pleiotropic genes. Finally, we found some biological evidence showing that s P S analysis is relevant to the real pleiotropic data and can be considered a novel candidate for pleiotropic gene research. Taken together, our results can be used to understand the dynamics pleiotropic characteristics in complex biological systems in terms of gene–phenotype relations. [ABSTRACT FROM AUTHOR]

Energy transitions (ETs) can solve some societal problems but must transform societies. Accordingly, socio-technical transitions and other systemic frameworks have been used to assess ETs. However, based on these frameworks, assessments miss a value co-creation orientation, the focus on actors' researched benefits and enabled service exchange, and the consideration of needed de/re-institutionalization practices. Analyzing those elements could prevent socioeconomic shocks and loss of opportunities and unfold possible ET challenges against ET viability and sustainability. Intending to develop a theory synthesis work for enriching previous frameworks, we propose service-dominant logic (S-D logic) as an integrative framework to assess ETs. We offer a literature review on ET systems' frameworks to compare them with the proposal. We also identify the implications of adopting S-D logic for rethinking energy systems' dynamics and ETs. Thus, we contribute to the literature by providing an integrative framework for assessing ETs and we illustrate its potentialities by deriving some challenges of the current Italian ET. This study paves the way for deeper analyses on the contribution of S-D logic to ETs and the operationalization of other systems' frameworks in our integrative one. Merging with quantitative models could also follow. [ABSTRACT FROM AUTHOR]

Drug target discovery is an essential step to reveal the mechanism of action (MoA) underlying drug therapeutic effects and/or side effects. Most of the approaches are usually labor-intensive while unable to identify the tissue-specific interacting targets, especially the targets with weaker drug binding affinity. In this work, we proposed an integrated pipeline, FL-DTD, to predict the drug interacting targets of novel compounds in a tissue-specific manner. This method was built based on a hypothesis that cells under a status of homeostasis would take responses to drug perturbation by activating feedback loops. Therefore, the drug interacting targets can be predicted by analyzing the network responses after drug perturbation. We evaluated this method using the expression data of estrogen stimulation, gene manipulation and drug perturbation and validated its good performance to identify the annotated drug targets. Using STAT3 as a target protein, we applied this method to drug perturbation data of 500 natural compounds and predicted five compounds with STAT3 interacting activities. Experimental assay validated the STAT3-interacting activities of four compounds. Overall, our evaluation suggests that FL-DTD predicts the drug interacting targets with good accuracy and can be used for drug target discovery. [ABSTRACT FROM AUTHOR]

The Drosophila brain has only a fraction of the number of neurons of higher organisms such as mice and humans. Yet the sheer complexity of its neural circuits recently revealed by large connectomics datasets suggests that computationally modeling the function of fruit fly brain circuits at this scale poses significant challenges. To address these challenges, we present here a programmable ontology that expands the scope of the current Drosophila brain anatomy ontologies to encompass the functional logic of the fly brain. The programmable ontology provides a language not only for modeling circuit motifs but also for programmatically exploring their functional logic. To achieve this goal, we tightly integrated the programmable ontology with the workflow of the interactive FlyBrainLab computing platform. As part of the programmable ontology, we developed NeuroNLP++, a web application that supports free-form English queries for constructing functional brain circuits fully anchored on the available connectome/synaptome datasets, and the published worldwide literature. In addition, we present a methodology for including a model of the space of odorants into the programmable ontology, and for modeling olfactory sensory circuits of the antenna of the fruit fly brain that detect odorant sources. Furthermore, we describe a methodology for modeling the functional logic of the antennal lobe circuit consisting of a massive number of local feedback loops, a characteristic feature observed across Drosophila brain regions. Finally, using a circuit library, we demonstrate the power of our methodology for interactively exploring the functional logic of the massive number of feedback loops in the antennal lobe. [ABSTRACT FROM AUTHOR]

Abstract Background The World Health Organisation framed responsiveness, fair financing and equity as intrinsic goals of health systems. However, of the three, responsiveness received significantly less attention. Responsiveness is essential to strengthen systems’ functioning; provide equitable and accountable services; and to protect the rights of citizens. There is an urgency to make systems more responsive, but our understanding of responsiveness is limited. We therefore sought to map existing evidence on health system responsiveness. Methods A mixed method systemized evidence mapping review was conducted. We searched PubMed, EbscoHost, and Google Scholar. Published and grey literature; conceptual and empirical publications; published between 2000 and 2020 and English language texts were included. We screened titles and abstracts of 1119 publications and 870 full texts. Results Six hundred twenty-one publications were included in the review. Evidence mapping shows substantially more publications between 2011 and 2020 (n = 462/621) than earlier periods. Most of the publications were from Europe (n = 139), with more publications relating to High Income Countries (n = 241) than Low-to-Middle Income Countries (n = 217). Most were empirical studies (n = 424/621) utilized quantitative methodologies (n = 232), while qualitative (n = 127) and mixed methods (n = 63) were more rare. Thematic analysis revealed eight primary conceptualizations of ‘health system responsiveness’, which can be fitted into three dominant categorizations: 1) unidirectional user-service interface; 2) responsiveness as feedback loops between users and the health system; and 3) responsiveness as accountability between public and the system. Conclusions This evidence map shows a substantial body of available literature on health system responsiveness, but also reveals evidential gaps requiring further development, including: a clear definition and body of theory of responsiveness; the implementation and effectiveness of feedback loops; the systems responses to this feedback; context-specific mechanism-implementation experiences, particularly, of LMIC and fragile-and conflict affected states; and responsiveness as it relates to health equity, minority and vulnerable populations. Theoretical development is required, we suggest separating ideas of services and systems responsiveness, applying a stronger systems lens in future work. Further agenda-setting and resourcing of bridging work on health system responsiveness is suggested.

The Drosophila brain has only a fraction of the number of neurons of higher organisms such as mice and humans. Yet the sheer complexity of its neural circuits recently revealed by large connectomics datasets suggests that computationally modeling the function of fruit fly brain circuits at this scale poses significant challenges. To address these challenges, we present here a programmable ontology that expands the scope of the current Drosophila brain anatomy ontologies to encompass the functional logic of the fly brain. The programmable ontology provides a language not only for modeling circuit motifs but also for programmatically exploring their functional logic. To achieve this goal, we tightly integrated the programmable ontology with the workflow of the interactive FlyBrainLab computing platform. As part of the programmable ontology, we developed NeuroNLP++, a web application that supports free-form English queries for constructing functional brain circuits fully anchored on the available connectome/synaptome datasets, and the published worldwide literature. In addition, we present a methodology for including a model of the space of odorants into the programmable ontology, and for modeling olfactory sensory circuits of the antenna of the fruit fly brain that detect odorant sources. Furthermore, we describe a methodology for modeling the functional logic of the antennal lobe circuit consisting of a massive number of local feedback loops, a characteristic feature observed across Drosophila brain regions. Finally, using a circuit library, we demonstrate the power of our methodology for interactively exploring the functional logic of the massive number of feedback loops in the antennal lobe.

Pancreatic cancer is the leading cause of cancer-related deaths worldwide, with limited treatment options and low long-term survival rates. The complex and variable signal regulation networks are one of the important reasons why it is difficult for pancreatic cancer to develop precise targeted therapy drugs. Numerous studies have associated feedback loop regulation with the development and therapeutic response of cancers including pancreatic cancer. Therefore, we review researches on the role of feedback loops in the progression of pancreatic cancer, and summarize the connection between feedback loops and several signaling pathways in pancreatic cancer, as well as recent advances in the intervention of feedback loops in pancreatic cancer treatment, highlighting the potential of capitalizing on feedback loops modulation in targeted therapy for pancreatic cancer. [ABSTRACT FROM AUTHOR]

Simple Summary: The lncRNA XIST has been verified as an oncogenic gene in non-small cell lung cancer (NSCLC), whereas the tumor suppressors miR-34a, miR-449a, and miR-16 were downregulated in NSCLC. The lncRNA XIST is known to bind to the miR-449a and miR-34a sponges, however, the biological functions linking all these non-coding RNAs (ncRNAs) are still unknown in NSCLC. This study aims to perform dynamic analysis of the gene regulation between these two ncRNAs in NSCLC. Thus, we presented a Boolean model of the plausible network connecting the lncRNA XIST/miR-34a/miR-449a and miR-16 in NSCLC. We observed that miR-449a/miR-34a regulates miR-16 and p21 expression by targeting HDAC1, c-Myc, and the lncRNA XIST. Our results demonstrate that the lncRNA XIST is an attractive target of drug development in NSCLC and that favorable outcomes can be achieved through tumor suppressor miRNAs. The long non-coding RNA X inactivate-specific transcript (lncRNA XIST) has been verified as an oncogenic gene in non-small cell lung cancer (NSCLC) whose regulatory role is largely unknown. The important tumor suppressors, microRNAs: miR-449a and miR-16 are regulated by lncRNA XIST in NSCLC, these miRNAs share numerous common targets and experimental evidence suggests that they synergistically regulate the cell-fate regulation of NSCLC. LncRNA XIST is known to sponge miR-449a and miR-34a, however, the regulatory network connecting all these non-coding RNAs is still unknown. Here we propose a Boolean regulatory network for the G1/S cell cycle checkpoint in NSCLC contemplating the involvement of these non-coding RNAs. Model verification was conducted by comparison with experimental knowledge from NSCLC showing good agreement. The results suggest that miR-449a regulates miR-16 and p21 activity by targeting HDAC1, c-Myc, and the lncRNA XIST. Furthermore, our circuit perturbation simulations show that five circuits are involved in cell fate determination between senescence and apoptosis. The model thus allows pinpointing the direct cell fate mechanisms of NSCLC. Therefore, our results support that lncRNA XIST is an attractive target of drug development in tumor growth and aggressive proliferation of NSCLC, and promising results can be achieved through tumor suppressor miRNAs. [ABSTRACT FROM AUTHOR]

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Long non-coding RNA (lncRNA) such as ANRIL and UFC1 have been verified as oncogenic genes in non-small cell lung cancer (NSCLC). It is well known that the tumor suppressor microRNA-34a (miR-34a) is downregulated in NSCLC. Furthermore, miR-34a induces senescence and apoptosis in breast, glioma, cervical cancer including NSCLC by targeting Myc. Recent evidence suggests that these two lncRNAs act as a miR-34a sponge in corresponding cancers. However, the biological functions between these two non-coding RNAs (ncRNAs) have not yet been studied in NSCLC. Therefore, we present a Boolean model to analyze the gene regulation between these two ncRNAs in NSCLC. We compared our model to several experimental studies involving gain- or loss-of-function genes in NSCLC cells and achieved an excellent agreement. Additionally, we predict three positive circuits involving miR-34a/E2F1/ANRIL, miR-34a/E2F1/UFC1, and miR-34a/Myc/ANRIL. Our circuit- perturbation analysis shows that these circuits are important for regulating cell-fate decisions such as senescence and apoptosis. Thus, our Boolean network permits an explicit cell-fate mechanism associated with NSCLC. Therefore, our results support that ANRIL and/or UFC1 is an attractive target for drug development in tumor growth and aggressive proliferation of NSCLC, and that a valuable outcome can be achieved through the miRNA-34a/Myc pathway. [ABSTRACT FROM AUTHOR]

Pancreatic cancer is the leading cause of cancer-related deaths worldwide, with limited treatment options and low long-term survival rates. The complex and variable signal regulation networks are one of the important reasons why it is difficult for pancreatic cancer to develop precise targeted therapy drugs. Numerous studies have associated feedback loop regulation with the development and therapeutic response of cancers including pancreatic cancer. Therefore, we review researches on the role of feedback loops in the progression of pancreatic cancer, and summarize the connection between feedback loops and several signaling pathways in pancreatic cancer, as well as recent advances in the intervention of feedback loops in pancreatic cancer treatment, highlighting the potential of capitalizing on feedback loops modulation in targeted therapy for pancreatic cancer.

Community management is a common approach to securing access to clean water for rural residents. Its failure to sustain water services over acceptable lifetimes has been well-documented, adversely impacting human health when users return to unimproved sources during system downtimes. The objective of this study is to identify effective strategies for improving the performance of community-managed systems. The quantitative system dynamics models were developed using monitoring data for Bolivia and Colombia to simulate typical performance as infrastructure ages and to test strategies to improve performance. The two models captured the performance behavior revealed from monitoring data and were driven by the same structure: two reinforcing loops and two balancing loops. Although a strategy to professionalize the service provider enabled them to meet or exceed the target performance threshold, external financial support alone was ineffective. The paradigm shift from fix-on-failure corrective maintenance to preventive maintenance enables systems to sustain high performance levels over time. The models are useful for understanding the underlying system structure driving performance of community-managed systems and designing high-impact interventions using model simulations. [ABSTRACT FROM AUTHOR]

Systemic change is universally desirable and poorly defined. This article seeks to refine a practitioner-developed framework - Adopt-Adapt-Expand-Respond (AAER) - for conceptualising systemic change, and offers case studies to demonstrate its utility in planning for and measuring such change. To do so, the article firstly seeks to define the nature of a system and the components of change within that system. It also discusses the relevance of behaviour change among both actors and institutions in conceptualising systemic change. Finally, in exploring the utility of AAER throughout the implementation of development interventions, it examines the role of the framework in adaptive management: utilising data on observed changes to alter programme intervention tactics. [ABSTRACT FROM AUTHOR]

Theory in ecology and evolution often relies on the analysis of invasion processes, and general approaches exist to understand the early stages of an invasion. However, predicting the long‐term transformations of communities following an invasion remains a challenging endeavour.We propose a general analytical method that uses both resident community and invader dynamical features to predict whether an invasion causes large long‐term impacts on the invaded community.This approach reveals a direction in which classic invasion analysis, based on initial invasion growth rate, can be extended. Indeed, we explain how the density dependence of invasion growth, if properly defined, synthetically encodes the long‐term biotic transformations caused by an invasion, and therefore predicts its ultimate outcome. This approach further clarifies how the density dependence of the invasion growth rate is as much a property of the invading population as it is one of the invaded community.Our theory applies to any stable community model, and directs us towards new questions that may enrich the toolset of invasion analysis, and suggests that indirect interactions and dynamical stability are key determinants of invasion outcomes. [ABSTRACT FROM AUTHOR]

The complex dynamics of the homogeneous H2O2–NaSCN–CuSO4–NaOH oscillator is influenced by the addition of EDTA, which manifests itself in the modification or complete suppression of the oscillations. However, depending on EDTA concentration, this effect can be reversible or not. Potentiometric and spectroscopic studies of these phenomena, together with recent discoveries about possible chemical interactions and compound formation in the Cu(II)–H2O2–EDTA system, resulted in the development of a new kinetic mechanism of the complex interaction of EDTA with this oscillatory system. The model involves 13 intermediates and is an extension of our former, 10‐variable mechanism of the H2O2–NaSCN–CuSO4–NaOH oscillator. Reliability of the proposed reaction scheme has been confirmed by numerical calculations, enabling also the estimation of appropriate reaction rate constants. The work is an example of the application of the chemical oscillatory reaction to study qualitatively and quantitatively the interactions of foreign species with the components of positive and negative feedback loops of a chemical dynamical system. [ABSTRACT FROM AUTHOR]

The initiation, progression, and metastatic spread of cancer elicits diverse changes in systemic physiology. In this way, cancer represents a novel homeostatic challenge to the host system. Here, we discuss how the hypothalamus, a critical brain region involved in homeostasis senses, integrates and responds to cancer-induced changes in physiology. Through this lens, cancer-associated changes in behavior (e.g., sleep disruption) and physiology (e.g., glucocorticoid dysregulation) can be viewed as the result of an inability to re-establish homeostasis. We provide examples at each level (receptor sensing, integration of systemic signals, and efferent regulatory pathways) of how homeostatic organization becomes disrupted across different cancers. Finally, we lay out predictions of this hypothesis and highlight outstanding questions that aim to guide further work in this area. Cancer represents a homeostatic challenge to the host system. The brain detects cancer-induced changes in physiology via multiple receptor modalities present on afferent nerves, as well as centrally within the hypothalamus and other brain structures. Integration of peripheral signals elicits downstream changes in neuronal output. The hypothalamus attempts to restore homeostasis via the HPA axis and autonomic nervous system. Failure to restore homeostasis can result in deleterious phenotypes associated with cancer, such as blunted glucocorticoid responses and sleep/wake disruption. [ABSTRACT FROM AUTHOR]

Background: Chronic stress increases chronic disease risk and may underlie the association between exposure to adverse socioeconomic conditions and adverse health outcomes. The relationship between exposure to such conditions and chronic stress is complex due to feedback loops between stressor exposure and psychological processes, encompassing different temporal (acute stress response to repeated exposure over the life course) and spatial (biological/psychological/social) scales. We examined the mechanisms underlying the relationship between exposure to adverse socioeconomic conditions and chronic stress from a complexity science perspective, focusing on amplifying feedback loops across different scales.Methods: We developed a causal loop diagram (CLD) to interpret available evidence from this perspective. The CLD was drafted by an interdisciplinary group of researchers. Evidence from literature was used to confirm/contest the variables and causal links included in the conceptual framework and refine their conceptualisation. Our findings were evaluated by eight independent researchers.Results: Adverse socioeconomic conditions imply an accumulation of stressors and increase the likelihood of exposure to uncontrollable childhood and life course stressors. Repetition of such stressors may activate mechanisms that can affect coping resources and coping strategies and stimulate appraisal of subsequent stressors as uncontrollable. We identified five feedback loops describing these mechanisms: (1) progressive deterioration of access to coping resources because of repeated insolvability of stressors; (2) perception of stressors as uncontrollable due to learned helplessness; (3) tax on cognitive bandwidth caused by stress; (4) stimulation of problem avoidance to provide relief from the stress response and free up cognitive bandwidth; and (5) susceptibility to appraising stimuli as stressors against a background of stress.Conclusions: Taking a complexity science perspective reveals that exposure to adverse socioeconomic conditions implies recurrent stressor exposure which impacts chronic stress via amplifying feedback loops that together could be conceptualised as one vicious cycle. This means that in order for individual-level psychological interventions to be effective, the context of exposure to adverse socioeconomic conditions also needs to be addressed. [ABSTRACT FROM AUTHOR]

An exciting area in behavioural ecology focuses on understanding why animals exhibit consistent among-individual differences in behaviour (animal personalities). Animal personality has been proposed to emerge as an adaptation to individual differences in state variables, leading to the question of why individuals differ consistently in state. Recent theory emphasizes the role that positive feedbacks between state and behaviour can play in producing consistent among-individual covariance between state and behaviour, hence state-dependent personality. We review the role of feedbacks in recent models of adaptive personalities, and provide guidelines for empirical testing of model assumptions and predictions. We discuss the importance of the mediating effects of ecology on these feedbacks, and provide a roadmap for including state-behaviour feedbacks in behavioural ecology research.

The formation of the shadow wage in Ukraine is a major problem and a threat to economic growth. According to different valuation methods, the shadow economy in Ukraine ranges from 35% to 54% of GDP, and the shadow wage is estimated at 18% of GDP. The general scheme for tax evasion by businesses is to informally pay cash to workers in “envelopes”, which results in a large amount of cash in the economy and, as a consequence, further opportunities for tax evasion. Despite the urgency of the current issue for Ukraine and a large number of works by Ukrainian and foreign scientists dedicated to finding positive and negative features of the existence of shadow wages, there is still a lack of research that determines the formation of shadow wages through the use of economic and mathematical tools. Based on that, a model of shadow wage formation using the system dynamics method was constructed, which takes into account such factors as the amount of cash in the economy and the size of the minimum wage. Based on the modeling results it was found that raising the minimum wage would reduce the share of the shadow component in GDP. Taking that into consideration, conclusions were drawn regarding the first objectives of government policy, which should aim at creating opportunities for economic growth and reducing the amount of cash in the economy in order to lower the size of the shadow sector in Ukrainian economy as a whole.

The corticothalamic (CT) pathways emanate from either Layer 5 (L5) or 6 (L6) of the neocortex and largely outnumber the ascending, thalamocortical pathways. The CT pathways provide the anatomical foundations for an intricate, bidirectional communication between thalamus and cortex. They act as dynamic circuits of information transfer with the ability to modulate or even drive the response properties of target neurons at each synaptic node of the circuit. L6 CT feedback pathways enable the cortex to shape the nature of its driving inputs, by directly modulating the sensory message arriving at the thalamus. L5 CT pathways can drive the postsynaptic neurons and initiate a transthalamic corticocortical circuit by which cortical areas communicate with each other. For this reason, L5 CT pathways place the thalamus at the heart of information transfer through the cortical hierarchy. Recent evidence goes even further to suggest that the thalamus via CT pathways regulates functional connectivity within and across cortical regions, and might be engaged in cognition, behavior, and perceptual inference. As descending pathways that enable reciprocal and context-dependent communication between thalamus and cortex, we venture that CT projections are particularly interesting in the context of hierarchical perceptual inference formulations such as those contemplated in predictive processing schemes, which so far heavily rely on cortical implementations. We discuss recent proposals suggesting that the thalamus, and particularly higher order thalamus via transthalamic pathways, could coordinate and contextualize hierarchical inference in cortical hierarchies. We will explore these ideas with a focus on the auditory system.

The corticothalamic (CT) pathways emanate from either Layer 5 (L5) or 6 (L6) of the neocortex and largely outnumber the ascending, thalamocortical pathways. The CT pathways provide the anatomical foundations for an intricate, bidirectional communication between thalamus and cortex. They act as dynamic circuits of information transfer with the ability to modulate or even drive the response properties of target neurons at each synaptic node of the circuit. L6 CT feedback pathways enable the cortex to shape the nature of its driving inputs, by directly modulating the sensory message arriving at the thalamus. L5 CT pathways can drive the postsynaptic neurons and initiate a transthalamic corticocortical circuit by which cortical areas communicate with each other. For this reason, L5 CT pathways place the thalamus at the heart of information transfer through the cortical hierarchy. Recent evidence goes even further to suggest that the thalamus via CT pathways regulates functional connectivity within and across cortical regions, and might be engaged in cognition, behavior, and perceptual inference. As descending pathways that enable reciprocal and context-dependent communication between thalamus and cortex, we venture that CT projections are particularly interesting in the context of hierarchical perceptual inference formulations such as those contemplated in predictive processing schemes, which so far heavily rely on cortical implementations. We discuss recent proposals suggesting that the thalamus, and particularly higher order thalamus via transthalamic pathways, could coordinate and contextualize hierarchical inference in cortical hierarchies. We will explore these ideas with a focus on the auditory system. [ABSTRACT FROM AUTHOR]

Hyper-positive real, matrix-valued, rational functions are associated with absolute stability (the Lurie problem). Here, quantitative subsets of Hyper-positive functions, related through nested inclusions, are introduced. Structurally, this family of functions turns out to be matrix-convex and closed under inversion. A state-space characterization of these functions through a corresponding Kalman-Yakubovich-Popov Lemma, is given. Technically, the classical Linear Matrix Inclusions, associated with passive systems, are here substituted by Quadratic Matrix Inclusions. [ABSTRACT FROM AUTHOR]

Background: The World Health Organisation framed responsiveness, fair financing and equity as intrinsic goals of health systems. However, of the three, responsiveness received significantly less attention. Responsiveness is essential to strengthen systems' functioning; provide equitable and accountable services; and to protect the rights of citizens. There is an urgency to make systems more responsive, but our understanding of responsiveness is limited. We therefore sought to map existing evidence on health system responsiveness. Methods: A mixed method systemized evidence mapping review was conducted. We searched PubMed, EbscoHost, and Google Scholar. Published and grey literature; conceptual and empirical publications; published between 2000 and 2020 and English language texts were included. We screened titles and abstracts of 1119 publications and 870 full texts. Results: Six hundred twenty-one publications were included in the review. Evidence mapping shows substantially more publications between 2011 and 2020 (n = 462/621) than earlier periods. Most of the publications were from Europe (n = 139), with more publications relating to High Income Countries (n = 241) than Low-to-Middle Income Countries (n = 217). Most were empirical studies (n = 424/621) utilized quantitative methodologies (n = 232), while qualitative (n = 127) and mixed methods (n = 63) were more rare. Thematic analysis revealed eight primary conceptualizations of 'health system responsiveness', which can be fitted into three dominant categorizations: 1) unidirectional user-service interface; 2) responsiveness as feedback loops between users and the health system; and 3) responsiveness as accountability between public and the system. Conclusions: This evidence map shows a substantial body of available literature on health system responsiveness, but also reveals evidential gaps requiring further development, including: a clear definition and body of theory of responsiveness; the implementation and effectiveness of feedback loops; the systems responses to this feedback; context-specific mechanism-implementation experiences, particularly, of LMIC and fragile-and conflict affected states; and responsiveness as it relates to health equity, minority and vulnerable populations. Theoretical development is required, we suggest separating ideas of services and systems responsiveness, applying a stronger systems lens in future work. Further agenda-setting and resourcing of bridging work on health system responsiveness is suggested. [ABSTRACT FROM AUTHOR]

Since 2009, the Indian River Lagoon (IRL) has lost over half its seagrass due to phytoplankton blooms. The loss was especially high in the north-central IRL and Banana River lagoon--nearly 100% in some segments. Over 190 km2 of seagrass was lost. One question is what might natural recovery look like? Can we emulate that process to jump-start restoration? Planting that much area is not feasible. The goal is to develop restoration procedures with positive feedback loops--both ecological and cultural. Ecologically, feedback means getting many patches established that subsequently provide a source for new recruits. This initial jump-start is especially important in segments that lost virtually all their seagrass. Culturally, feedback entails involving and training volunteers to plant small patches of seagrass in many places. A few successes promote more participation and thus more success. Recovery will take time, persistence, and some luck. Reducing risk is the key factor. Proposals are made about how to reduce the risk of failure in planting seagrass--over both space and time. [ABSTRACT FROM AUTHOR]

Fundamental biological processes of cell identity and cell fate determination are controlled by complex regulatory networks. These processes require molecular mechanisms that confer cellular phenotypic memory and state persistence. In this minireview, we will summarize mechanisms of cell memory based on regulatory hysteretic feedback loops and explore epigenetic mechanisms widely represented in nature, with special focus on epithelial-to-mesenchymal plasticity. We will also discuss the functional consequences of cell memory and epithelial-to-mesenchymal plasticity dynamics during development and cancer metastasis. [ABSTRACT FROM AUTHOR]

The complex relationship that exists between water resources and agricultural production has been increasing constantly globally. Several factors are interacting to influence the management of water resources making the system complex and dynamic. To increase the understanding of these complex and dynamic systems, relevant tools are needed to identify the causal relationships that exist between the drivers and their influences on the system. Participatory modelling based on the system dynamics approach provides a simplistic and visualisation tool that can improve the understanding of the functioning of a complex and dynamic system. A multi-stage participatory approach was used in this study involving relevant stakeholders in the development of an integrated conceptual system dynamic model using causal loop diagrams. This approach was used because it captures the thought process and mental model of relevant stakeholders in the development of the model, making it a valuable tool for policy and decision making at government and individual levels. The integrated model built in this study used causal loop diagrams to address problems of water management and agricultural sustainability in the Breede River Catchment. The model shows major causal-relationships and feedback loops that determine the functioning of the overall system. The model demonstrates the usefulness of the participatory approach in solving problems related to water management and agricultural development in the catchment. [ABSTRACT FROM AUTHOR]

Macromarketing is definitionally concerned with systems — marketing, markets and society — and their interactions. This paper lays out a case for systems research in macromarketing, the use of methods designed to study systems. In doing so, it highlights the limitations of much micromarketing research. Macromarketing and the Journal of Macromarketing is the home of systems research in marketing. Macromarketing scholars need to increase our use of systems research methodologies. We also need to connect macromarketing to wider, particularly business, systems research. Following the calls by this Journal's first editor George Fisk, systems research must not live in our discipline and journal alone, all social sciences need the insights of systems research and systems research needs the insights of macromarketing. [ABSTRACT FROM AUTHOR]

The purpose of this qualitative study was to understand how feedback loops function within the Ministry of Education (MoE) Provincial Education Directorate (PED) in Herat province of Afghanistan, how the MoE/PED collects, analyzes, and uses feedback for improving its policies and programs, and responds to the issues and barriers identified at the school levels. To narrow down the research, it investigated the feedback loops around teacher professional development (TPD). We used semi-structured interviews and document analysis to collect data. The participants were 34 individuals selected purposefully from six schools, one CBE, and Herat educational offices. We used thematic analysis methods for analyzing the data. The findings indicate that the MoE/PED did not collect regular or quality feedback about TPD activities, usually offered as teacher training workshops, from this study participants. Besides, we did not find any evidence that the MoE/PED has used the rarely collected feedback for improving TPD programs, so the feedback loops were not closed. The mechanisms for collecting, analyzing, and using feedback are not well defined and established at the MoE/PED. The existing structures for communicating information between schools and the higher authorities in the MoE/PED are manual and paper-based, and the process is very time-consuming.

Abstract Circadian oscillators are networks of biochemical feedback loops that generate 24-hour rhythms in organisms from bacteria to animals. These periodic rhythms result from a complex interplay among clock components that are specific to the organism, but share molecular mechanisms across kingdoms. A full understanding of these processes requires detailed knowledge, not only of the biochemical properties of clock proteins and their interactions, but also of the three-dimensional structure of clockwork components. Posttranslational modifications and protein–protein interactions have become a recent focus, in particular the complex interactions mediated by the phosphorylation of clock proteins and the formation of multimeric protein complexes that regulate clock genes at transcriptional and translational levels. This review covers the structural aspects of circadian oscillators, and serves as a primer for this exciting realm of structural biology.