Action Of System Research Articles

Japanese Public Health Insurance System's new genomic strategic action to shorten the "diagnostic odyssey" for patients with rare and intractable diseases.

In June 2024, the Japanese government introduced a new genomic strategic action to shorten the "diagnostic odyssey" for patients with rare and intractable diseases: Six groups of rare diseases, (i) Muscle weakness group, (ii) Growth retardation, intellectual disability, and characteristic facial features group, (iii) Intellectual disability/epilepsy group, (iv) Cardiomyopathy group (mainly adult onset) (v) Proteinuria group, (vi) Fever, inflammation, skin rash, osteoarthritis group, have been newly recognized as "difficult-to-differentiate disorders" and comprehensive genomic testing can be reimbursed when patients belong to one of the six groups and certain requirements are met. The introduction of comprehensive genomic testing will improve the diagnosis rate of diseases and have significant potential to enhance Japan's rare and intractable disease policy. The new strategy in Japan and its rationale will be a reference for insurance reimbursement of comprehensive genomic testing in other countries that have universal health coverage supported by the public health insurance system.

Reinforcement learning-based energy storage management in smart grids

This study investigates the use of reinforcement learning (RL) techniques as a dynamic control mechanism to enhance the management of energy storage in smart grid systems. The research aims to optimize the efficiency of energy storage operations by analyzing collected data from different time intervals in a simulated smart grid scenario. An evaluation of the energy storage status reveals a consistent upward trend in the quantity of stored energy, with a 30% cumulative growth across time intervals. An examination of the demand and supply of the grid indicates a persistent insufficiency of energy, with an average shortfall of 15% in meeting the requirements of the system. Through the use of reinforcement learning (RL) methodologies, the system exhibits a remarkable 450% improvement in cumulative rewards, providing substantiation of its capacity to acquire knowledge and adjust its behavior over time. The system's actions indicate a purposeful shift in strategy, with 75% of instances involving charging procedures, emphasizing a commitment to energy preservation and the buildup of stored energy. Despite a shift in approach, persistent disparities between grid demand and supply need the implementation of more accurate technologies for effective energy management. The findings highlight the effectiveness of using reinforcement learning (RL) for managing energy storage in smart grids. This approach improves energy reserves and optimizes energy storage by altering actions accordingly. These insights contribute to the advancement of adaptive energy management strategies, resulting in the development of sustainable and resilient smart grid infrastructures.

Development and optimization of simulation models and methods for controlling virtual artillery units in game scenarios

In the realm of modern video game development, special attention is given to the simulation of artillery systems, which play a crucial role in various military-themed games. This research presents a mathematical model for simulating the actions of a virtual artillery system. The model is designed to manage the execution of combat tasks, including targeting destruction with a specified number of shells and incorporating the strategic movement between firing positions to minimize detection and attack by enemy forces in the game. The model presumes that all shots are effective and equates the number of firing positions to the number of shots, with a minimum of one shot per position. The model's dynamics do not allow for returning to previous positions, adding a layer of complexity and realism to the gameplay. Movement simulations between positions are designed along virtual roads of varying quality, enhancing the strategic elements of the game. A method for determining the optimal strategy for the artillery system's actions has been developed, introducing the concept of the current structure of combat task execution. This problem-solving approach falls within the realm of Pareto-oriented tasks or dynamic programming challenges. The computational method of the model is based on a general algorithm, underpinned by specialized additional algorithms. Results from this model demonstrate the feasibility of completing combat tasks effectively, with a maximum of two shots per firing position. The research differentiates between defensive and offensive tactics in gameplay, suggesting that while a strategy involving ten shots per target aligns with defensive gameplay, a strategy with four shots per target aligns with offensive actions. Consequently, the "shot-and-scoot" tactic in an offensive context can be aptly termed as “hid-and-shot”.

Natriuretic Peptide Receptors (NPRs) as a Potential Target for the Treatment of Heart Failure.

Heart failure is defined as a complex clinical syndrome that results from any structural or functional impairment of ventricular filling or ejection of blood. The natriuretic peptide is known to exert its biological action on the kidney, heart, blood vessels, renin-angiotensin system, autonomous nervous system, and central nervous system. The natriuretic peptide-natriuretic receptor system plays an important role in the regulation of blood pressure and body fluid volume through its pleiotropic effects. The clinical and animal studies suggest that natriuretic peptide-natriuretic receptors are important targets for the treatment of heart failure and other cardiovascular diseases. Even though attempts targeting natriuretic peptide receptors are underway for heart failure treatment, they seem insufficient despite the receptor systems' potential. This review summarizes natriuretic peptide-natriuretic receptor system's physiological actions and potential target for the treatment of heart failure. Natriuretic peptides play multiple roles in different parts of the body, almost all of the activities related to this receptor system appear to have the potential to be harnessed to treat heart failure or symptoms associated with heart failure.

“Last orders, please!”: The disappearance of communicative spaces at universities

This paper uses the thick description of one recent experience – the closure of the Common Room Club at University College Dublin – to highlight the gap that exists between rhetoric and reality at institutions of higher education in Ireland and beyond. I argue that common rooms have always been part and parcel of the ‘invisible university’. They provide the infrastructure to support what has been called the ‘lifeworld’, sustaining both the communicative experiences of their members and providing vital venues for visitors who are through them more readily drawn into the communicative life of colleagues. As unique spaces within much larger institutions, common rooms form both a protected shield and also a porous social community against the encroachment of the university system's instrumental action and reasoning. However, recent changes in higher education have accelerated the pace of change and the quest for top-down modernisation. As a reaction, and almost by default, the common room has taken on a new function for faculty, staff and visitors and turned into a place of encounter between people and ideas critical and often opposed to managerialism, bureaucratisation and the mindless emulation of higher education's fads and foibles. At University College Dublin, this new role did not remain unnoticed by the University management and triggered an extreme reaction – enforced closure. My paper closes by dwelling on an important question that points into an uncertain future: is it possible for any institution that purports to be a centre of higher learning to either quell or attempt to ‘manage’ lifeworld experiences and sceptical voices for any length of time? In other words, can a university still fulfil its very function and expect loyalty without allowing ‘voice’ (A. O. Hirschman) to be heard?

A Copper Single‐Atom Cascade Bionanocatalyst for Treating Multidrug‐Resistant Bacterial Diabetic Ulcer

AbstractDiabetic ulcers induced by multidrug‐resistant (MDR) bacteria have severely endangered diabetic populations. These ulcers are very challenging to treat because the local high glucose concentration can both promote bacterial growth and limit the immune system's bactericidal action. Herein, a glucose oxidase‐peroxidase (GOx‐POD) dual‐enzyme mimetic (DEM) bionanocatalyst, Au@CuBCats is synthesized to simultaneously control glucose concentration and bacteria in diabetic ulcers. Specifically, the AuNPs can serve as GOx mimics and catalyze the oxidation of glucose for the formation of H2O2; the H2O2 can then be further catalytically converted into OH via the POD‐mimetic copper single atoms. Notably, the unique copper single atoms coordinated by one oxygen and two nitrogen atoms (CuN2O1) exhibit better POD catalytic performance than natural peroxidase. Further DFT calculations are conducted to study the catalytic mechanism and reveal the advantage of this CuN2O1 structure as compared to other copper single‐atom sites. Both in vitro and in vivo experiments confirm the outstanding antibacterial therapeutic efficacy of the DEM bionanocatalyst. This new bionanocatalyst will provide essential insights for the next generation of antibiotic‐free strategies for combating MDR bacterial diabetic ulcers, and also offer inspiration for designing bionanocatalytic cascading medicines.

DESIGNING A PID CONTROL SCHEME FOR DIRECT CURRENT MOTORS WITHOUT USING ELECTRICAL SENSORS

This paper delves into the development of an innovative PID controller for direct current (DC) motors, designed to function independently from mechanical sensors such as encoders. The study emphasizes the importance of confronting this challenge and the pressing need for a viable solution. The proposed method capitalizes on the armature current to estimate the motor's electrical torque, providing a multitude of benefits in tackling this problem. By harnessing this information, a sophisticated control strategy based on pole placement is implemented, enabling precise motor control without reliance on mechanical sensors. The PID control law works in synergy with state feedback to govern the control system's actions, ensuring optimized motor performance and efficiency. To validate the effectiveness of the proposed scheme, a rigorous evaluation process is conducted, encompassing both simulation and real-world testing on a prototype integrated with an ESP32 microcontroller. The findings reveal that the motor's speed demonstrates asymptotically stable behavior in response to fluctuations in load torque and reference speed values, corroborating the efficacy of the proposed solution. Furthermore, the elimination of mechanical sensors simplifies the system's design and minimizes potential failure points, consequently bolstering overall reliability.

Changes in government procurement: COVID-19 as an opportunity for corruption

PurposeExplore the factors making emergency procurement more prone to corruption by advancing explanations for when rules and transparency are relaxed allowing corrupt practices to emerge. Describe institutional factors, such as corruption syndrome (Johnston, 2005, 2015) and legal system, and their impact on procurement rules changes.Design/methodology/approachA qualitative event study using publicly available data offer a timeline and explanation of government procurement control mechanisms and transparency roles in emergencies by comparing two countries. Argentina and Canada had very similar and advanced food procurement systems prior to COVID-19, but they took different stances when the pandemic broke out.FindingsLegal systems and corruption syndrome are linked, where Civil Law is related to Elite Cartels (Argentina) and Common Law with Influence Markets (Canada). The study contributes to understand the role of transparency to minimize the opportunity for direct purchases (electronic trails of decisions, justifications and approvals). Judicial system's actions favor corrupt practices and are aligned with elites despite the civil society outcry.Research limitations/implicationsResearch on corrupt practices has limited access to primary data due to fear of reprisals. Informal conversations revealing glimpses of corruption were used to identify publicly available documents. Numbers play a role in emergencies and performativity theory literature is enriched by providing an example of different interpretation of information when frameworks differ between civil society and courts.Originality/valueA comparative analysis that evidences the role of pre-existing institutional and social conditions shows when emergency situations will be used as an excuse to relax procurement control and transparency mechanisms which in turn facilitate corrupt practices.

Emerging robust and data‐driven control methods for uncertain learning systems

Emerging robust and data‐driven control methods for uncertain learning systems

Legal dispositionism and artificially-intelligent attributions

AbstractIt is conventionally argued that because an artificially-intelligent (AI) system acts autonomously, its makers cannot easily be held liable should the system's actions harm. Since the system cannot be liable on its own account either, existing laws expose victims to accountability gaps and need to be reformed. Recent legal instruments have nonetheless established obligations against AI developers and providers. Drawing on attribution theory, this paper examines how these seemingly opposing positions are shaped by the ways in which AI systems are conceptualised. Specifically, folk dispositionism underpins conventional legal discourse on AI liability, personality, publications, and inventions and leads us towards problematic legal outcomes. Examining the technology and terminology driving contemporary AI systems, the paper contends that AI systems are better conceptualised instead as situational characters whose actions remain constrained by their programming. Properly viewing AI systems as such illuminates how existing legal doctrines could be sensibly applied to AI and reinforces emerging calls for placing greater scrutiny on the broader AI ecosystem.

Leptin, Adiponectin, and Melatonin Modulate Colostrum Lymphocytes in Mothers with Obesity.

Pregnancy complicated by obesity is associated with adverse triggered gestational and neonatal outcomes, with reductions in the subtypes of CD4+ T-lymphocytes representing the modulators of inflammation. It needs to be better established how maternal nutritional statuses impact the neuroendocrine-immune system's action and affect the immunological mechanisms of the maternal-infant relationship via breastfeeding. This study examined the effects of maternal obesity on human colostrum lymphocytes and the intracellular mechanisms of lymphocyte modulation in the presence of leptin, adiponectin, and melatonin via cell proliferation; the release of intracellular calcium; and apoptosis induction. This cross-sectional study analyzed colostrum samples from 52 puerperal splits and divided them into overweight and eutrophic groups. Colostrum lymphocytes underwent immunophenotyping and cell proliferation by flow cytometry and intracellular calcium release and apoptosis assays by immunofluorescence in the presence or absence of hormones. Significant differences were considered when p < 0.05 by the chi-square or t-test. Maternal obesity reduced the population of T-lymphocytes and TCD4+ in human colostrum and proliferative activities (p < 0.05). These hormones restore lymphocyte proliferation to a level similar to the eutrophic group (p < 0.05). Leptin, adiponectin, melatonin hormones, and biological actions consolidated in the scientific literature also represent maternal and infant protection mechanisms via colostrum and the modulation of human colostrum lymphocytes.

Assessing circularity of multi-sectoral systems under the Water-Energy-Food-Ecosystems (WEFE) nexus

The Multi-Sectoral Water Circularity Assessment (MSWCA) is a methodological framework developed for circularity assessment of the Water-Energy-Food-Ecosystems nexus. It involves five methodological steps and includes an indicators list for the selection of case-specific indicators. This study expands the MSWCA to provide a systematic approach for selecting indicators, considering system's circular actions and multi-functionality, the capture of implemented changes, the three CE principles and the sustainable development goals. Furthermore, this study differentiates between benchmark and dynamic circularity assessment and applies the expanded MSWCA in a water system of the HYDROUSA H2020 project. The benchmark assessment indicates that the HYDROUSA system achieves a 75% increase of water circularity, 76–80% increase of nutrients circularity and 14% reduction of operational `carbon footprint compared to the baseline scenario. The dynamic assessment highlights that additional measures can improve the system's circularity performance (e.g. water circularity can reach 94%) and mitigate risks occurring from uncontrollable changes.

Developing intelligence in food security: An agent-based modelling approach of Qatar's food system interactions under socio-economic and environmental considerations

Maintaining the consistent provision of food is becoming a persistent challenge in the light of increasing demands for resources and the multiple risks governing food systems. These include population growth, market volatilities, changing climate and the lack of coordination amongst involved stakeholders. Dynamic and interactive simulation models have demonstrated their utility for developing possible scenarios related to the food sector's subsystems, allowing stakeholders to understand their outcomes, should they occur, and make efficient and sustainable decisions that potentially alleviate the risks. This study proposes an Agent-based model (ABM) that supports informed decision-making through allowing the simulation of multiple scenarios that can potentially influence the food system's strategies and actions. The framework is illustrated considering the economic actors within Qatar's food sector, with a special focus on delivering products in high demand, such as the tomato crop. The model was implemented using the Python-based Mesa library, and it simulates interactions between domestic farmers, local importers, and international exporters to assess the performance of the food sector considering economic, environmental and social scenarios. Scenario (1) describes the baseline case wherein local farmers and importers are acting independently with the aim to maximise their individual profits. Scenario's (2) and (3) represent enhancement plans that foster collaboration, water security and improved food quality. Findings of this study assert that from an economic standpoint, the food system can supply 75% of the market with imported tomatoes, as for the remaining 25%, it can be provided through national farms, with a 76% contribution of greenhouses and 24% open fields. This option offers the minimum economic cost and the lowest Greenhouse Gas (GHG) emissions. However, this perspective implies massive food losses and relatively high-water consumption. Scenario 2, which advocates a full reliance on imports offers a costly monthly strategy in terms of economic expenses and environmental emissions, however, it results in considerable water savings that relieve the strain on the local water supply system. When implementing a plan driven by quality consideration (scenario 3), the reliance on imports reaches up to 82%, and the remaining local produce is mostly supplied by greenhouses, with approximately 78%, leading to quality improvement and a substantial decrease in food losses yet at the expense of both the economic and environmental performance. These results confirm that aspiring water security and social welfare while provisioning food products requires tremendous investment and might lead to significant GHG emissions. The framework developed in this study provides a generic and interactive decision-making scheme that can assist in undertaking future decisions considering economic and environmental constraints and market-driven specifications.

Comparison of frontostriatal circuits in adolescent nicotine addiction and internet gaming disorder.

BackgroundRecently, there has been significantly increased participation in online gaming and other addictive behaviors particularly in adolescents. Tendencies to avoid social interaction and become more involved in technology-based activities pose the danger of creating unhealthy addictions. Thus, the presence of relatively immature cognitive control and high risk-taking properties makes adolescence a period of major changes leading to an increased rate of emotional disorders and addiction.AimsThe critical roles of frontostriatal circuits in addiction have become the primary focus associated with reward in the striatum and cognitive control in the PFC. Internet gaming disorder (IGD) and nicotine addiction are currently becoming more and more serious.MethodsIn the light of neuroimaging, the similarity between brain mechanisms causing substance use disorder (SUD) and IGD have been described in previous literature.ResultsIn particular, two distinct brain systems affect the way we act accounting for uncharacteristic neural function in addiction: the affective system comprises of the striatum driven by emotional, reward-related, and internal stimuli, and a cognitive system consisting of the prefrontal cortex (PFC) supporting the ventral affective system's actions via inhibitory control.Discussion and ConclusionTherefore, as a novel concept, we focused on the implication of frontostriatal circuits in nicotine addiction and IGD by reviewing the main findings from our studies compared to those of others. We hope that all of these neuroimaging findings can lead to effective intervention and treatment for addiction especially during this critical period.

On the parameterized complexity of the synthesis of Boolean nets with restricted place environments

Though constructing a sequential system model may be technically uncomplicated and rather ‘straightforward’, its result is often cumbersome and difficult to analyze since all possible interleavings of system's actions have to be present. This naturally raises the interest to the possibility of automatic synthesis of models that are able to grasp behavioral parallelism of the system. Boolean Petri nets are a classical formalism that enjoys generic concepts of concurrency, synchronization and conflict, and allows to obtain a concise yet expressive system representation. Let τ be a Boolean type of nets. The problem of τ-synthesis consists in deciding whether a given transition system A is isomorphic to the reachability graph of a Boolean Petri net N of type τ (a τ-net, for short). In case of a positive decision, N should be constructed. Another instance of the synthesis problem takes the dependencies of places into account: A place p of a τ-net depends on a transition t if p can influence t, that is, a marking of p can inhibit the firing of t, or if p can be influenced by t, that is, the firing of t can change a marking of p. The problem τ-synthesis of Boolean nets with restricted dependencies (τ-SOBNWRD) consists in deciding for a given transition system A and natural number d whether there exists a Boolean Petri net N of type τ such that, firstly, the reachability graph of N and A are isomorphic and, secondly, every place p of N depends on at most d transitions. For many Boolean types that allow independence, the (unrestricted) τ-synthesis problem is NP-complete, and for all of them τ-SOBNWRD inherits the NP-completeness. In this paper, we enhance our understanding of τ-SOBNWRD from a parameterized point of view: We show for 27 of the 128 thinkable Boolean types that allow independence that τ-SOBNWRD parameterized by d is W[1]-hard, and for 75 of them that the problem is W[2]-hard.

Real-Frequency Response Functions at Finite Temperature.

Building on previous developments [A. Taheridehkordi, S. H. Curnoe, and J. P. F. LeBlanc, Phys. Rev. B 99, 035120 (2019); PRBMDO2469-995010.1103/PhysRevB.99.035120A. Taheridehkordi, S. H. Curnoe, and J. P. F. LeBlancPhys. Rev. B101, 125109 (2020); PRBMDO2469-995010.1103/PhysRevB.101.125109A. Taheridehkordi, S. H. Curnoe, and J. P. F. LeBlancPhys. Rev. B102, 045115 (2020)PRBMDO2469-995010.1103/PhysRevB.102.045115, B. Holm and U. von Barth, Phys. Rev. B 57, 2108 (1998)PRBMDO0163-182910.1103/PhysRevB.57.2108, J. Vičičević and M. Ferrero, Phys. Rev. B 101, 075113 (2020)PRBMDO2469-995010.1103/PhysRevB.101.075113], we show that the diagrammatic MonteCarlo technique allows us to compute finite-temperature response functions directly on the real-frequency axis within any field-theoretical formulation of the interacting fermion problem. There are no limitations on the type and nature of the system's action or whether partial summation and self-consistent treatment of certain diagram classes are used. In particular, by eliminating the need for numerical analytic continuation from a Matsubara representation, our scheme allows us to study spectral densities of arbitrary complexity with controlled accuracy in models with frequency-dependent effective interactions. For illustrative purposes we consider the problem of the plasmon linewidth in a homogeneous electron gas (jellium).

IMER-FM: Iterative Process of System Feature Model Extraction from the Requirements

Software product line engineering (SPLE) is a paradigm to promote systematic software reuse. A Feature Model (FM) is a common means to illustrate the commonality and variability of software products in a family. In most existing FM extraction approaches, keywords in the requirement document or certain types of system behavior or external events are considered features. The resulting FM is a combination of user activities and system actions (SAs), making it hard to understand. In this paper, we present an automatic approach to generate a product line FM from multiple requirement documents. We consider user activity and SAs separately in our approach and focus on the expected behaviors of the software system, together with the data being processed. The resulting FM clearly illustrates the expected functionalities of the software system and their variability in the product line. We also compared our approach with existing techniques by processing the same textual documents, and noted improvements in our results.

Origin of ultra-light fields during inflation and their suppressed non-Gaussianity

We study the structure of multi-field inflation models where the primordial curvature perturbation is able to vigorously interact with an ultra-light isocurvature field — a massless fluctuation orthogonal to the background inflationary trajectory in field space. We identify a class of inflationary models where ultra-light fields can emerge as a consequence of an underlying “scaling transformation” that rescales the entire system's action and keeps the classical equations of motion invariant. This scaling invariance ensures the existence of an ultra-light fluctuation that freezes after horizon crossing. If the inflationary trajectory is misaligned with respect to the scaling symmetry direction, then the isocurvature field is proportional to this ultra-light field, and becomes massless. In addition, we find that even if the isocurvature field interacts strongly with the curvature perturbation — transferring its own statistics to the curvature perturbation — it is unable to induce large non-Gaussianity. The reason is simply that the same mechanism ensuring a suppressed mass for the isocurvature field is also responsible for suppressing its self-interactions. As a result, in models with light isocurvature fields the bispectrum is generally expected to be slow-roll suppressed, but with a squeezed limit that differs from Maldacena's consistency relation.

Direito à Educação: Gestão Democrática e Políticas Públicas em Tempo de Pandemia/Covid-19 no Estado do Tocantins

O artigo objetiva analisar a gestão democrática enquanto princípio do direito à educação no Estado do Tocantins, em tempo de Pandemia da Covid-19. A discussão vislumbra elucidar as políticas públicas voltadas para o atendimento educacional de qualidade na rede pública – abrangendo a educação urbana e do campo – e atuação do sistema estadual para a garantia do direito à educação no exercício da democracia. A pesquisa assenta-se no materialismo histórico dialético, tendo como referência a pesquisa bibliográfica e documental e acervo normativo emitido, principalmente, pelo Ministério da Educação, Conselho Nacional da Educação, Governo do Estado do Tocantins e Conselho Estadual de Educação e dados do CONVIVA. Com atenção crítica, aponta para a inexistência de políticas educacionais e comprometimento do Sistema Estadual de Educação com a situação de crise educacional e, sobretudo, com o direito à educação quanto à gestão democrática.&#x0D; Palavras-chave: Direito à Educação, Políticas Públicas Educacionais, Gestão Democrática, Sistemas de Educação, Pandemia Covid-19.&#x0D; &#x0D; Right to Education: Democratic Management end Public Policies in Time of Pandemic/Covid-19 in the State of Tocantins&#x0D; ABSTRACT&#x0D; The article aims to analyze democratic management as a principle of the right to education in the State of Tocantins, in times of Pandemic Covid-19. The discussion aims to elucidate public policies aimed at quality educational services in the public network – covering urban and rural education – and the state system's actions to guarantee the right to education in the exercise of democracy. The research is based on dialectical historical materialism, having as reference the bibliographic and documental research and normative collection issued, mainly, by the Ministry of Education, National Council of Education, Tocantins State Government and State Council of Education and data from CONVIVA. With critical attention, it points out the non-existence of educational policies and the State Education System's commitment to the situation of educational crisis and especially to the right to education in terms of democratic management.&#x0D; Keywords: Right to Education, Public Educational Policies, Democratic Management, Education Systems, Covid-19 Pandemic.&#x0D; &#x0D; Derecho a la Educación: Gestión Democrática y Políticas Públicas en Tiempos de la Pandemia/Covid-19 en el Estado de Tocantins&#x0D; RESUMEN&#x0D; El artículo tiene como objetivo analizar la gestión democrática como principio del derecho a la educación en el estado de Tocantins, en el momento de la Pandemia 19 de Covid. La discusión tiene como objetivo dilucidar las políticas públicas orientadas a brindar una atención educativa de calidad en la red pública - cubriendo la educación urbana y rural - y el desempeño del sistema estatal para garantizar el derecho a la educación en el ejercicio de la democracia. La investigación se basa en el materialismo histórico dialéctico, teniendo como referencia la investigación bibliográfica y documental y el acervo normativo emitido, principalmente, por el Ministerio de Educación, el Consejo Nacional de Educación, el Gobierno del Estado de Tocantins y el Consejo Estatal de Educación y datos de CONVIVA. Con atención crítica, señala la falta de políticas educativas y el compromiso del Sistema Educativo Estatal con la situación de crisis educativa y, sobre todo, con el derecho a la Educación en materia de gestión democrática.&#x0D; Palabras clave: Derecho a la Educación, Políticas Públicas Educativas, Gestión Democrática, Sistemas Educativos, Pandemia de Covid-19.

Integrative and perturbation-based analysis of the transcriptional dynamics of TGFβ/BMP system components in transition from embryonic stem cells to neural progenitors.

Cooperative actions of extrinsic signals and cell‐intrinsic transcription factors alter gene regulatory networks enabling cells to respond appropriately to environmental cues. Signaling by transforming growth factor type β (TGFβ) family ligands (eg, bone morphogenetic proteins [BMPs] and Activin/Nodal) exerts cell‐type specific and context‐dependent transcriptional changes, thereby steering cellular transitions throughout embryogenesis. Little is known about coordinated regulation and transcriptional interplay of the TGFβ system. To understand intrafamily transcriptional regulation as part of this system's actions during development, we selected 95 of its components and investigated their mRNA‐expression dynamics, gene‐gene interactions, and single‐cell expression heterogeneity in mouse embryonic stem cells transiting to neural progenitors. Interrogation at 24 hour intervals identified four types of temporal gene transcription profiles that capture all stages, that is, pluripotency, epiblast formation, and neural commitment. Then, between each stage we performed esiRNA‐based perturbation of each individual component and documented the effect on steady‐state mRNA levels of the remaining 94 components. This exposed an intricate system of multilevel regulation whereby the majority of gene‐gene interactions display a marked cell‐stage specific behavior. Furthermore, single‐cell RNA‐profiling at individual stages demonstrated the presence of detailed co‐expression modules and subpopulations showing stable co‐expression modules such as that of the core pluripotency genes at all stages. Our combinatorial experimental approach demonstrates how intrinsically complex transcriptional regulation within a given pathway is during cell fate/state transitions.