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The gasdermin (GSDM) family, a novel group of structure-related proteins, consists of GSDMA, GSDMB, GSDMC, GSDMD, GSDME/DNFA5, and PVJK/GSDMF. GSDMs possess a C-terminal repressor domain, cytotoxic N-terminal domain, and flexible linker domain (except for GSDMF). The GSDM-NT domain can be cleaved and released to form large oligomeric pores in the membrane that facilitate pyroptosis. The emerging roles of GSDMs include the regulation of various physiological and pathological processes, such as cell differentiation, coagulation, inflammation, and tumorigenesis. Here, we introduce the basic structure, activation, and expression patterns of GSDMs, summarize their biological and pathological functions, and explore their regulatory mechanisms in health and disease. This review provides a reference for the development of GSDM-targeted drugs to treat various inflammatory and tissue damage-related conditions.

Regulated cell death (RCD) is a signal-controlled process that not only eliminates infected, damaged, or aged cells but is also implicated in a variety of pathological conditions. The process of RCD is regulated by intracellular proteins that undergo varying levels of post-translational modifications, including mono- or polyubiquitination. Functionally, ubiquitination can affect protein abundance, localization, and activity. Like other post-translational modifications, ubiquitination is a dynamic and reversible process mediated by deubiquitinases, a large class of proteases that cleave ubiquitin from proteins and other substrates. The balance between ubiquitination and deubiquitination machinery determines cell fate under stressful conditions. Here, we review the latest advances in our understanding of the role of deubiquitinases in regulating the main types of RCD, including apoptosis, necroptosis, pyroptosis, and ferroptosis. This knowledge may contribute to identifying new protein degradation-related prognostic markers and therapeutic targets for human disease.

The brain network is one specific type of critical infrastructure networks, which supports the cognitive function of biological systems. With the importance of network reliability in system design, evaluation, operation, and maintenance, we use the percolation methods of network reliability on brain networks and study the network resistance to disturbances and relevant failure modes. In this paper, we compare the brain networks of different species, including cat, fly, human, mouse, and macaque. The differences in structural features reflect the requirements for varying levels of functional specialization and integration, which determine the reliability of brain networks. In the percolation process, we apply different forms of disturbances to the brain networks based on metrics that characterize the network structure. Our findings suggest that the brain networks are mostly reliable against random or k-core-based percolation with their structure design, yet becomes vulnerable under betweenness or degree-based percolation. Our results might be useful to identify and distinguish brain connectivity failures that have been shown to be related to brain disorders, as well as the reliability design of other technological networks.

As an important Ca2+ sensor, calmodulin (CaM) and calmodulin-like protein (CML) play core roles in plant growth, development, and response to environmental stimuli. The CaM/CML gene family has been well characterized in various plant species, such as Arabidopsis thaliana, rice, and tomato; however, in the tea plant, the CaM/CML gene family has not been systematically and comprehensively characterized. In the present study, a total of 5 CsCaM and 60 CsCML proteins were identified from the tea plant genome, which were unevenly distributed on the 14 chromosomes of the tea plant. All the proteins contained two to four EF-hand domains. Meanwhile, an integrated analysis of physicochemical properties, sequence structure, motif identification, phylogeny, gene duplication, promoter cis-elements, and RNA-seq expression profiles in the CsCaM/CML gene family was performed. Transcriptome analysis revealed that CsCaM/CMLs were differentially expressed in different tissues of the tea plant, suggesting their potential roles in plant growth and development. The expression profiles associated with various stress treatments revealed that CsCaM/CML genes were involved in a wide range of abiotic factors, including cold and drought stress. Quantitative real-time PCR (qRT-PCR) was also used to validate the differences in expression under abiotic stress. Overall, these findings enhanced our understanding of CsCaM/CML genes and provided useful information for further research into their molecular functions in abiotic stress response, and in multiple physiological processes in the tea plant.

This paper investigates the stabilization for stochastic coupled Kuramoto oscillators (SCKOs) via nonlinear distributed feedback control. An original nonlinear distributed feedback control with the advantages of fast response, no steady-state deviation, and easy implementation is designed to stabilize SCKOs. With the help of the Lyapunov method and stochastic analysis skills, some novel sufficient conditions guaranteeing the stochastic stability for SCKOs are provided by constructing a new and suitable Lyapunov function for SCKOs. Finally, a numerical example is given to illustrate the effectiveness and applicability of the theoretical result.

A general sampling problem can be described by an Ellsberg urn, which is a mathematical model that assumes that balls are randomly drawn from an urn with an uncertain numbers of colored balls. This means that the Ellsberg urn is essentially an intricate model with simultaneous randomness and epistemic uncertainty, and this is the core problem discussed in this paper. Since practical sampling is usually processed in an intricate environment, the solution for an equivalent mathematical problem is necessary. Suppose an Ellsberg urn contains three unknown numbers of colored balls (i.e., a two-degrees-of-freedom Ellsberg urn), and three balls are randomly drawn from the urn. Compared to the published papers, this paper first constructs a chance space with two-dimensional uncertainty space and three-dimensional probability space to rigorously calculate the color distributions for those drawn balls by uncertainty theory, probability theory, and chance theory. Moreover, it is interesting to find that all cases of the drawn balls are symmetric in such a specific situation of a sample problem with epistemic uncertainty.

This paper proposes a novel method for construction component classification by designing a feature-based deep learning network to tackle the automation problem in construction digitization. Although scholars have proposed a variety of ways to achieve the use of deep learning to classify point clouds, there are few practical engineering applications in the construction industry. However, in the process of building digitization, the level of manual participation has significantly reduced the efficiency of digitization and increased the application restrictions. To address this problem, we propose a robust classification method using deep learning networks, which is combined with traditional shape features for the point cloud of construction components. The proposed method starts with local and global feature extraction, where global features processed by the neural network and the traditional shape features are processed separately. Then, we generate a feature map and perform deep convolution to achieve feature fusion. Finally, experiments are designed to prove the efficiency of the proposed method based on the construction dataset we establish. This paper fills in the lack of deep learning applications of point clouds in construction component classification. Additionally, this paper provides a feasible solution to improve the construction digitization efficiency and provides an available dataset for future work.

Resilience, the ability of a system to withstand disruptions and quickly return to a normal state, is essential for a low-Earth-orbit satellite communication system (LEO-SCS), as its large number of satellites, may encounter various disturbances. As a developing system with asymmetrical and insufficient data, it is with both aleatory and epistemic uncertainties, which renders existing resilience measures inapplicable. This paper utilizes uncertainty theory to define belief instantaneous availability, based on which a new resilience measure for the LEO-SCS is proposed. As the resilience is mainly determined by the dynamic and uncertain characteristics of an LEO-SCS, an uncertain satellite network evolution model is developed to describe its operating patterns, and an evaluation method is proposed to estimate its resilience. To illustrate our proposed uncertain theory-based resilience evaluation method, an LEO-SCS case with 48 satellites is studied, and its resilience values under different backup strategies are compared to assist in system design decisions.

Ferroptosis is a type of iron-dependent regulated cell death caused by the disruption that occurs when oxidative stress and antioxidant defenses interact, and then driven by lipid peroxidation and subsequent plasma membrane ruptures. The regulation of ferroptosis involves many factors, including the crosstalk between subcellular organelles, such as mitochondria, endoplasmic reticulum (ER), lysosomes, lipid droplets, and peroxisomes. Here, we show that the ER protein STING1 (also known as STING or TMEM173) promotes ferroptosis in human pancreatic cancer cell lines by increasing MFN1/2-dependent mitochondrial fusion, but not mitophagy-mediated mitochondrial removal. The classic ferroptosis inducer erastin, but not sulfasalazine, induces the accumulation of STING1 in the mitochondria, where it binds to MFN1/2 to trigger mitochondrial fusion, leading to subsequent reactive oxygen species production and lipid peroxidation. Consequently, in vitro or xenograft mouse models show that the genetic depletion of STING1 or MFN1/2 (but not the mitophagy regulator PINK1 or PRKN) reduces the sensitivity of pancreatic cancer cells to ferroptosis. These findings not only establish a new mitochondrial fusion-dependent cell death mechanism, but also indicate a potential strategy for enhancing ferroptosis-based therapy.

The metabolic checkpoint of ferroptosis remains obscure. We find that glucose favors system xc− inhibitor-induced ferroptosis by activating pyruvate oxidation, thereby promoting fatty acid synthesis and subsequent lipid peroxidation. In contrast, the upregulation of pyruvate dehydrogenase kinase 4 (PDK4) switches into a ferroptosis-resistant state in pancreatic cancer cells.

Tablet-mediated interventions have shown promise in improving the mathematical skills of individuals with autism spectrum disorder (ASD) and/or intellectual disability (ID). This meta-analysis aims to provide a quantitative synthesis of single-case experimental studies of using tablet-mediated interventions to teach mathematics to individuals with ASD and/or ID. Twenty-seven published studies between 2012 and 2022 were included. The Tau-U effect size index was used to gauge the overall effect size of tablet-mediated interventions. The obtained effect size (Tau-U = 0.98, 95% CI 0.92-1.00) indicated large improvements in mathematics performance after using tablet-mediated interventions. The analysis of potential moderating variables, including participant characteristics, intervention components, and target mathematical skills found no statistically significant moderators. Implications for researchers and practitioners who use tablet-mediated interventions to teach mathematics to individuals with ASD and/or ID are also discussed.

This paper is aimed to study the fluctuation of the instantaneous availability (IA) for the parallel repairable system. First, the Markov model of IA for the two-unit parallel system with two states (up and down) under exponential distribution is established. Next, by Laplace transformation, the analytical solution of IA is obtained. The fluctuation of IA is analyzed according to the fluctuation theories. Then, in the same way, the fluctuation of IA for the n-unit parallel system with two states is analyzed, where the n units of the system are all same. Finally, some numerical examples are provided to show the effectiveness of the results in this paper.

Belief reliability is a new proposed reliability metric considering both aleatory and epistemic uncertainty. In belief reliability theory, system reliability analysis is a key component. Traditional system belief reliability theory for systems with random and uncertain components is based on a complex belief reliability formula, which is not understandable and efficient enough in engineering practise. In this paper, we put forward a novel system belief reliability analysis method, called decomposition method to cope with the problem. An algorithm of this method is proposed according to the properties of the cut sets of systems and the complexity of the algorithm is analyzed and compared with that of the reliability formula method. Finally, the effectiveness and efficiency of this method is further illustrated with a comparative case study.

Epistemic uncertainties, caused by data asymmetry and deficiencies, exist in resilience evaluation. Especially in the system design process, it is difficult to obtain enough data for system resilience evaluation and improvement. Mathematics methods, such as evidence theory and Bayesian theory, have been used in the resilience evaluation for systems with epistemic uncertainty. However, these methods are based on subjective information and may lead to an interval expansion problem in the calculation. Therefore, the problem of how to quantify epistemic uncertainty in the resilience evaluation is not well solved. In this paper, we propose a new resilience measure based on uncertainty theory, a new branch of mathematics that is viewed as appropriate for modeling epistemic uncertainty. In our method, resilience is defined as an uncertainty measure that is the belief degree of a system’s behavior after disruptions that can achieve the predetermined goal. Then, a resilience evaluation method is provided based on the operation law in uncertainty theory. To design a resilient system, an uncertain programming model is given, and a genetic algorithm is applied to find an optimal design to develop a resilient system with the minimal cost. Finally, road networks are used as a case study. The results show that our method can effectively reduce cost and ensure network resilience.

The pilot is the main person in charge of taxiing safety while moving on the airport surface. The visual separation and speed adjustment are directly related to safety and efficiency of airport surface operation. According to the actual taxiing procedures and airport control rules in China, this paper proposes a novel microscopic simulation model based on the pilots’ visual separation. This model is also built by refining the aircraft taxiing procedures at intersections. The observation range, the separation judgment, pilots’ visual distance, rate of proximity and the intention for speed governing are discussed as parameters in the model. The rules for aircraft separation judgment, pilots’ autonomous speed governing, and position updates are also set up and discussed. The proposed simulation can accurately simulate the acceleration and deceleration intentions under different motion trends while reproducing the motion process including the following acceleration, following deceleration and delayed deceleration caused by separation changes. The results demonstrate that the number of conflicts can be reduced to 50% based on visual separation adjustment of 50 s when the convergence angle is 30°. The pilot’s visual distance is inversely proportional to the fluctuation range of the speed of the rear aircraft, the proximity rate of the front and rear aircraft and the probability of conflict. The simulation results of this model conform to the actual taxiing routes and control rules, which provides technical support for improving the safety level of airport surface operation and presents certain reference value and practicability.

Listeria monocytogenes is a major foodborne pathogen that can cause listeriosis in humans and animals. Andrographolide is known as a natural antibiotic and exhibits good antibacterial activity. We aimed to investigate the effect of andrographolide on two quorum-sensing (QS) systems, LuxS/AI-2 and Agr/AIP of L. monocytogenes, as well as QS-controlled phenotypes in this study. Our results showed that neither luxS expression nor AI-2 production was affected by andrographolide. Nevertheless, andrographolide significantly reduced the expression levels of the agr genes and the activity of the agr promoter P2. Results from the crystal violet staining method, confocal laser scanning microscopy (CLSM), and field emission scanning electron microscopy (FE-SEM) demonstrated that andrographolide remarkably inhibited the biofilm-forming ability of L. monocytogenes 10403S. The preformed biofilms were eradicated when exposed to andrographolide, and reduced surviving cells were also observed in treated biofilms. L. monocytogenes treated with andrographolide exhibited decreased ability to secrete LLO and adhere to and invade Caco-2 cells. Therefore, andrographolide is a potential QS inhibitor by targeting the Agr QS system to reduce biofilm formation and virulence of L. monocytogenes.

Abstract. Pancreatic ductal adenocarcinoma (PDAC) is the most common type of exocrine pancreatic cancer with a 9% 5-year survival rate. High mobility group box 1 (HMGB1) is a nuclear protein that can act as a DNA chaperone in the sustainment of chromosome structure and function. When released into the extracellular space, HMGB1 becomes the most well characterized damage-associated molecular pattern (DAMP) to trigger immune responses. Recent evidence indicates that intracellular HMGB1 is a novel tumor suppressor in PDAC, which is connected to its role in the prevention of oxidative stress, genomic instability, and histone release. However, since extracellular HMGB1 is a DAMP and proinflammatory cytokine, cancer cells can also exploit it to survive through the receptor for advanced glycation endproducts (RAGE) in the pancreatic tumor microenvironment. Interestingly, targeting the HMGB1-RAGE pathway has become a new anti-cancer therapy strategy for PDAC.

The Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis 3.0) recommended defining sepsis as a life-threatening organ dysfunction caused by the host's uncontrolled response to infection. The bromodomain and extra-terminal (BET) protein family (such as BRD2, BRD3, and BRD4), an epigenetic regulator of gene transcription, has recently been recognized as a significant septic regulator of inflammation and immune response, including cytokine and chemokine production. Mechanistically, the two N-terminal conserved tandem bromodomains (namely the first bromodomain [BD1] and the second bromodomain [BD2]) favor the binding of BETs to acetylated histones or transcription factors, thereby initiating gene transcription machinery after CycT1 and CDK9 (also known as P-TEFb) are recruited to gene promoters to phosphorylate RNA pol II. Notably, BD1 and BD2 are not functionally redundant because they have different target genes in innate immune cells. Small-molecule BET inhibitors (BETis) for different BDs, such as I-BET, JQ1, I-BET151, apabetalone, RVX-297, and dBET1 have shown promising therapeutic effects in experimental sepsis models. This mini-review summarizes the emerging roles of BETs and the applications of BETis in sepsis, discusses the existing shortcomings of BETis, and introduces possible future research directions in this area.

Sepsis is a potentially life-threatening, pathological condition caused by a dysregulated host response to infection. Pathologically, systemic inflammation can initiate coagulation activation, leading to organ dysfunction, and ultimately to multiple organ failure and septic death. The inflammasomes are cytosolic multiprotein signaling complexes that control the host response to diverse pathogen-associated molecular patterns (PAMPs) from microorganisms as well as damage-associated molecular patterns (DAMPs) from dead or dying host cells. Recent studies highlight that the activation of canonical and non-canonical inflammasomes not only mediate the maturation and secretion of interleukin-1 (IL1) family cytokines, but also trigger the release of coagulation factor III, tissue factor (F3, best known as TF) in activated macrophages and monocytes. These emerging functions of inflammasomes in immunocoagulation are further positively regulated by stimulator of interferon response cGAMP interactor 1 (STING1, also known as STING or TMEM173, a hub of the innate immune signaling network) and high mobility group box 1 (HMGB1, a nuclear DAMP). This mini-review will discuss the regulation and function of inflammasome-dependent coagulation activation in sepsis.

Summary: Although induction of ferroptosis, an iron-dependent form of non-apoptotic cell death, has emerged as an anticancer strategy, the metabolic basis of ferroptotic death remains poorly elucidated. Here, we show that glucose determines the sensitivity of human pancreatic ductal carcinoma cells to ferroptosis induced by pharmacologically inhibiting system xc−. Mechanistically, SLC2A1-mediated glucose uptake promotes glycolysis and, thus, facilitates pyruvate oxidation, fuels the tricyclic acid cycle, and stimulates fatty acid synthesis, which finally facilitates lipid peroxidation-dependent ferroptotic death. Screening of a small interfering RNA (siRNA) library targeting metabolic enzymes leads to identification of pyruvate dehydrogenase kinase 4 (PDK4) as the top gene responsible for ferroptosis resistance. PDK4 inhibits ferroptosis by blocking pyruvate dehydrogenase-dependent pyruvate oxidation. Inhibiting PDK4 enhances the anticancer activity of system xc− inhibitors in vitro and in suitable preclinical mouse models (e.g., a high-fat diet diabetes model). These findings reveal metabolic reprogramming as a potential target for overcoming ferroptosis resistance.

Pancreatic ductal adenocarcinoma (PDAC), one of the most aggressive solid malignancies, is characterized by the presence of oncogenic KRAS mutations, poor response to current therapies, prone to metastasis, and a low 5-year overall survival rate. Macroautophagy (herein referred to as autophagy) is a lysosome-dependent degradation system that forms a series of dynamic membrane structures to engulf, degrade, and recycle various cargoes, such as unused proteins, damaged organelles, and invading pathogens. Autophagy is usually upregulated in established cancers, but it plays a dual role in the regulation of the initiation and progression of PDAC. As a type of selective autophagy, mitophagy is a mitochondrial quality control mechanism that uses ubiquitin-dependent (e.g., the PINK1-PRKN pathway) and -independent (e.g., BNIP3L/NIX, FUNDC1, and BNIP3) pathways to regulate mitochondrial turnover and participate in the modulation of metabolism and cell death. Genetically engineered mouse models indicate that the loss of PINK1 or PRKN promotes, whereas the depletion of BNIP3L inhibits oncogenic KRAS-driven pancreatic tumorigenesis. Mitophagy also play a dual role in the regulation of the anticancer activity of certain cytotoxic agents (e.g., rocaglamide A, dichloroacetate, fisetin, and P. suffruticosa extracts) in PDAC cells or xenograft models. In this min-review, we summarize the latest advances in understanding the complex role of mitophagy in the occurrence and treatment of PDAC.

The induction and consequences of regulated cell death (RCD) are accompanied by changes in gene and protein expression, biochemical pathways, as well as cell morphology and size. Such RCDs have a significant impact on development, tissue homeostasis, and the occurrence and progression of disease. Among different forms of RCD, ferroptosis appears to be the main cause of tissue damage driven by iron overload and lipid peroxidation. In fact, the dysfunctional ferroptotic response is implicated in a variety of pathological conditions and diseases, such as neurodegenerative diseases, tissue ischemia-reperfusion injury, tumorigenesis, infections, and immune diseases. Ferroptotic response can be fine-tuned through various oxidative stress and antioxidant defense pathways, coupling with metabolism, gene transcription, and protein degradation machinery. Accordingly, a series of ferroptosis inducers or inhibitors targeting redox- or iron metabolism-related proteins or signal transduction have been developed. Although this kind of RCD has recently attracted great interest in basic and clinical research, detecting and monitoring a ferroptotic response still faces challenges. In this mini-review, we not only summarize the latest knowledge about the characteristics of ferroptosis in vitro and in vivo, but also discuss the specificity and limitations of current biomarkers of ferroptosis.

Drug-induced ferroptosis, an iron-dependent regulatory necrosis, has been proposed for the therapy of pancreatic ductal adenocarcinoma. However, genetically engineered mouse models have revealed that high-iron diets or deletion of pancreatic GPX4 (a key repressor of ferroptosis) accelerate the development of mutant Kras-driven PDAC by activating the STING1/TMEM173-dependent DNA sensor pathway. Abbreviations ADM: acinar-to-ductal metaplasia; CGAS: cyclic GMP-AMP synthase; DAMP: damage-associated molecular pattern; GPX4: glutathione peroxidase 4; GEMM: genetically engineered mouse models; PDAC: pancreatic ductal adenocarcinoma; PanIN: pancreatic intraepithelial neoplasia, SLC7A11: solute carrier family 7 member 11; STING1: cGAMP-stimulator of interferon response cGAMP interactor 1; TME: tumor microenvironment; 8-OHG: 8-hydroxy-2ʹ-deoxyguanosine

Pancreatic ductal adenocarcinoma (PDAC) is an immune resistant tumor. We recently demonstrated that inhibiting CDK1/2/5 by dinaciclib not only blocks immune checkpoint expression, but also triggers histone-dependent immunogenic cell death. This dual mechanism turns immunologically “cold” tumor microenvironment into a “hot” one, improves overall survival rates in mouse PDAC models.

COVID-19 has attracted global attention due to its rapid spread around the world with substantial morbidity and associated mortality. Severe COVID-19 can be complicated by the acute respiratory distress syndrome, sepsis and septic shock leading to death. These complications are thought to result from an overactivation of the immune system, leading to a cytokine storm syndrome associated with multiple organ failure. Here, we report that high mobility group box 1 (HMGB1), a prototypical damage-associated molecular pattern (DAMP) and a central mediator of lethal inflammation, could be a potential target for innovative therapeutic strategies for COVID-19. Serum HMGB1 in severe COVID-19 patients is elevated (189.40 ± 140.88 ng/ml). Exogenous HMGB1 induces the expression of SARS-CoV-2 entry receptor ACE2 in alveolar epithelial cells in an AGER-dependent manner. Importantly, genetic (using AGER siRNA) or pharmacological (using glycyrrhizin, chloroquine, hydroxychloroquine, and FPS-ZM1) inhibition of the HMGB1-AGER pathway blocks ACE2 expression. Thus, HMGB1 inhibitors are likewise promising drug candidates for the treatment of patients suffering from COVID-19.

Mitochondria are multifunctional organelles that regulate cancer biology by synthesizing macromolecules, producing energy, and regulating cell death. The understanding of mitochondrial morphology, function, biogenesis, fission and fusion kinetics, and degradation is important for the development of new anticancer strategies. Mitophagy is a type of selective autophagy that can degrade damaged mitochondria under various environmental stresses, especially oxidative damage and hypoxia. The key regulator of mitophagy is the autophagy receptor, which recognizes damaged mitochondria and allows them to enter autophagosomes by binding to MAP1LC3 or GABARAP, and then undergo lysosomal-dependent degradation. Many components of mitochondria, including mitochondrial membrane proteins (e.g., PINK1, BNIP3L, BNIP3, FUNDC1, NIPSNAP1, NIPSNAP2, BCL2L13, PHB2, and FKBP8) and lipids (e.g., cardiolipin and ceramides), act as mitophagy receptors in a context-dependent manner. Dysfunctional mitophagy not only inhibits, but also promotes, tumorigenesis. Similarly, mitophagy plays a dual role in chemotherapy, radiotherapy, and immunotherapy. In this review, we summarize the latest advances in the mechanisms of mitophagy and highlight the pathological role of mitophagy receptors in tumorigenesis and treatment.

Ferroptosis is a form of regulated cell death that is characterized by iron-dependent oxidative damage and subsequent plasma membrane ruptures and the release of damage-associated molecular patterns. Due to the role of iron in mediating the production of reactive oxygen species and enzyme activity in lipid peroxidation, ferroptosis is strictly controlled by regulators involved in many aspects of iron metabolism, such as iron uptake, storage, utilization, and efflux. Translational and transcriptional regulation of iron homeostasis provide an integrated network to determine the sensitivity of ferroptosis. Impaired ferroptosis is implicated in various iron-related pathological conditions or diseases, such as cancer, neurodegenerative diseases, and ischemia-reperfusion injury. Understanding the molecular mechanisms underlying the regulation of iron metabolism during ferroptosis may provide effective strategies for the treatment of ferroptosis-associated diseases. Indeed, iron chelators effectively prevent the occurrence of ferroptosis, which may provide new approaches for the treatment of iron-related disorders. In this review, we summarize recent advances in the theoretical modeling of iron-dependent ferroptosis, and highlight the therapeutic implications of iron chelators in diseases.

REBCO (Rare-earth-based barium copper oxide) conductors are appropriate materials for high-field magnet applications. Vacuum impregnation using epoxy resin is a technique widely used for stable operation of superconducting coils. However, epoxy-impregnated REBCO coils often experience critical current degradation problems. Finding a suitable impregnating material for REBCO coils is important for their application in high-field superconducting magnets. A new toughness epoxy, IR-3, was developed recently. An in-depth understanding of IR-3 on the performance of REBCO coils is critically necessary for its application. Thus, this paper explores the effects of IR-3 impregnation on the performance of REBCO coils at 77 K and 4.2 K. The test results are compared to similar coils impregnated with CTD-101 K and MY750. Meanwhile, the radial stresses at 77 K in self-field and 4.2 K under 10 T were simulated. All epoxy impregnated REBCO coils showed no decay in critical current after thermal cycles at 77 K. When charged at 4.2 K in external fields of 5 T and 10 T, the IR-3 impregnated REBCO coils avoided performance degradation problems and had superior electrical stabilities. Combing the excellent performance at low temperatures, IR-3 is a promising candidate material for impregnating high-field REBCO coils.

Decision time, also known as choice reaction time, has been frequently discussed in the field of psychology. The Hick–Hyman Law (HHL) has been a fundamental model that has revealed the quantitative relationship between the mean choice reaction time of human and the information entropy of stimuli. However, the HHL is only focused on rule-based behavior in which rules for selecting response according to stimulus are certain and neglects to model the knowledge-based behavior in which choices are uncertain and influenced by human belief. In this article, we explored the decision time related to one basic knowledge-based behavior—uncertain binary choice, where selections of response are determined by human belief degrees but not by stimuli uncertainties. Two experiments were conducted: one for verifying the HHL and the other for uncertain binary choice. The former (experiment) demonstrated the effectiveness of the HHL, and the latter one indicated that there is an exponential relationship existing between decision time and entropy of belief degree in uncertain binary choice. Moreover, data obtained from both experiments showed that the disturbance term of decision time should not be seen as probabilistic as existing studies have assumed, which highlighted the necessity and advantage of uncertain regression analysis.

Many new types of regulated cell death have been recently implicated in human health and disease. These regulated cell deaths have different morphological, genetic, biochemical, and functional hallmarks. Ferroptosis was originally described as a carcinogenic RAS-dependent non-apoptotic cell death, and is now defined as a type of regulated necrosis characterized by iron accumulation, lipid peroxidation, and the release of damage-associated molecular patterns (DAMPs). Multiple oxidative and antioxidant systems, acting together autophagy machinery, shape the process of lipid peroxidation during ferroptosis. In particular, the production of reactive oxygen species (ROS) that depends on the activity of nicotinamide adenine dinucleotide phosphate (NADPH) oxidases (NOXs) and the mitochondrial respiratory chain promotes lipid peroxidation by lipoxygenase (ALOX) or cytochrome P450 reductase (POR). In contrast, the glutathione (GSH), coenzyme Q10 (CoQ10), and tetrahydrobiopterin (BH4) system limits oxidative damage during ferroptosis. These antioxidant processes are further transcriptionally regulated by nuclear factor, erythroid 2-like 2 (NFE2L2/NRF2), whereas membrane repair during ferroptotic damage requires the activation of endosomal sorting complexes required for transport (ESCRT)-III. A further understanding of the process and function of ferroptosis may provide precise treatment strategies for disease.

Autophagy is a self-eating process of using lysosomes to degrade macromolecular substances (e.g., proteins and organelles) that are damaged, degenerated, or aging. Lipid metabolism is the synthesis and degradation of lipids (e.g., triglycerides, steroids, and phospholipids) to generate energy or produce the structural components of cell membranes. There is a complex interplay between lipid metabolism (e.g., digestion, absorption, catabolism, biosynthesis, and peroxidation) and autophagy machinery, leading to the modulation of cell homeostasis, including cell survival and death. In particular, lipid metabolism is involved in the formation of autophagic membrane structures (e.g., phagophores and autophagosomes) during stress. Moreover, autophagy, especially selective autophagy (e.g., lipophagy, ferritinophagy, clockophagy, and mitophagy), promotes lipid catabolism or lipid peroxidation-induced ferroptosis through the degradation of various substances within the cell. A better understanding of the mechanisms of autophagy and possible links to lipid metabolism will undoubtedly promote potential treatments for a variety of diseases.

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) is a novel coronavirus that has caused a worldwide pandemic of the human respiratory illness COVID-19, resulting in a severe threat to public health and safety. Analysis of the genetic tree suggests that SARS-CoV-2 belongs to the same Betacoronavirus group as severe acute respiratory syndrome coronavirus (SARS-CoV) and Middle East respiratory syndrome coronavirus (MERS-CoV). Although the route for viral transmission remains a mystery, SARS-CoV-2 may have originated in an animal reservoir, likely that of bat. The clinical features of COVID-19, such as fever, cough, shortness of breath, and fatigue, are similar to those of many acute respiratory infections. There is currently no specific treatment for COVID-19, but antiviral therapy combined with supportive care is the main strategy. Here, we summarize recent progress in understanding the epidemiological, virological, and clinical characteristics of COVID-19 and discuss potential targets with existing drugs for the treatment of this emerging zoonotic disease.

Prefabricated construction promotes providing better productivity and project results. Building models, including their elements’ fabrication details, are complex structures that need accurate information delivery among the project participants and their partial designs. This paper extends the IFC data model to support prefabricated construction. Also, it discusses the advantages of systematically managing exchange requirements in a database to facilitate generating IDM (Information Delivery Manual). The paper first introduces a BIM-based collaborative work mode by sharing and extracting the model views. The core of the sharing is the establishment of view exchange standard about the linked model and the definition of exchange requirements based on the design process, leading to the formulation of the IDM standard again from the perspective of the actual design. Process maps covering architecture, structure, plumbing, mechanical engineering, and electrical engineering are made to show how to realize BIM-based collaborative work. Then the exchange requirements referred to the object and attribute of the BIM model which should be delivered in a special phase are defined in particular tables. To facilitate the automation of managing and exchanging requirements, a database management system is designed with its corresponding user-interface, which enhances the collaboration and delivery throughout the project life cycle. The proposed approach supports better information reuse and delivery among the project participants.

Summary: Sepsis and septic shock are associated with life-threatening organ dysfunction caused by an impaired host response to infections. Although circadian clock disturbance impairs the early inflammatory response, its impact on post-septic immunosuppression remains poorly elucidated. Here, we show that Bmal1, a core circadian clock gene, plays a role in the regulation of host immune responses in experimental sepsis. Mechanistically, Bmal1 deficiency in macrophages increases PKM2 expression and lactate production, which is required for expression of the immune checkpoint protein PD-L1 in a STAT1-dependent manner. Consequently, targeted ablation of Pkm2 in myeloid cells or administration of anti-PD-L1-neutralizing antibody or supplementation with recombinant interleukin-7 (IL-7) facilitates microbial clearance, inhibits T cell apoptosis, reduces multiple organ dysfunction, and reduces septic death in Bmal1-deficient mice. Collectively, these findings suggest that the circadian clock controls the immune checkpoint pathway in macrophages and therefore represents a potential therapeutic target for lethal infection. : Deng et al. demonstrate that BMAL1 plays a role in preventing the development of a sepsis phenotype during severe infection through counter-regulating PD-L1 expression and T cell exhaustion. These findings indicate that targeting the circadian clock and immunometabolism pathway has potential for treating infectious diseases that lead to lethal sepsis. Keywords: Bmal1, Pkm2, Pd-l1, Stat1, IL-7, sepsis, checkpoint, circadian clock, metabolism, macrophages

Hepatitis B virus (HBV) X (HBx) protein is a pivotal regulator of HBV‐triggered autophagy. However, the role of HBx‐induced epigenetic changes in autophagy remains largely unknown. The cytoplasmic (Cyt) high‐mobility group box 1 (HMGB1) has been identified as a positive regulator of autophagy, and its Cyt translocation is closely associated with its acetylation status. Here, we evaluated the function of HMGB1 in HBx‐mediated autophagy and its association with histone deacetylase (HDAC). Using cell lines with enforced expression of HBx, we demonstrated that HBx upregulated the expression of HMGB1 and promoted its Cyt translocation by acetylation to facilitate autophagy. We further identified the underlying mechanism by which decreased nuclear HDAC activity and expression levels contribute to the HBx‐promoted hyperacetylation and subsequent translocation of HMGB1. We also identified the HDAC1 isoform as a critical factor in regulating this phenomenon. In addition, HBx bound to HMGB1 in the cytoplasm, which triggered autophagy in hepatocytes. Pharmacological inhibition of HMGB1 Cyt translocation with ethyl pyruvate prevented HBx‐induced autophagy. These results demonstrate a novel function of acetylated HMGB1 in HBx‐mediated autophagy in hepatocytes.

To provide high quality of network service, the response time reliability (RTR), the probability that the response time of a service is within the maximum allowable time determined by users, attracts researchers from both academic and industry. For those networked systems that can adjust their configuration adaptively, such as cloud computing systems, ad hoc networks, and network function virtualization systems, it is essential to predict the RTR of the system, and use the prediction result as a constraint to optimize the system configuration, e.g., tradeoff between reliability and energy efficiency. In general, the RTR changes along with the workload of the system. Due to the complex communication process, it is not easy to derive the analytical model between workload and RTR, and the maximum response time that users can tolerate also changes with the system workload according to users' experience. This paper proposes a variable thresholdbased RTR real-time prediction framework based on data-driven approaches to forecast the RTR for networked systems. In this framework, the response time threshold varies with the workload, reflecting both users' acceptable and perceived response time, and a real-time updating model between workload and RTR is built for RTR prediction based on the latest monitored dada. Finally, a communication network is taken as the example to validate the effectiveness of the proposed method from different perspectives. The experimental results illustrate that this continually updating model can obtain more accurate RTR prediction.

Belief reliability is a new reliability metric based on the uncertainty theory, which aims to measure system performance incorporating the influences from design margin, aleatory uncertainty, and epistemic uncertainty. A key point in belief reliability is to determine the belief reliability distribution based on the actual conditions, which, however, could be difficult when available information is limited. This paper proposes an optimal model to determine the belief reliability distribution based on the maximum entropy principle when kth moments of what can be obtained. An estimation method using linear interpolation and a genetic algorithm is subsequently applied to the optimal model. When only the expected value and the variance are available, the optimal results are in accordance with the maximum entropy principle. It could be observed in the sensitivity analysis that the accuracy of the optimal results is a decreasing function of the width of variances and an increasing function of the number of interpolation points. Therefore, researchers could adapt to different widths of variances and requirements of accuracy by adjusting the number of interpolation points. It could be concluded that this new method to acquire belief reliability distribution is important in the application of belief reliability.

Accurate inventory management starts with the scientific and rational classification of numerous varieties of spare parts. This paper presents a stochastic data envelopment analysis (DEA) model to address the problem of optimization of spares varieties under uncertainty. An index system is proposed in terms of product life-cycle process, which contains five design indexes, four operation indexes and five support indexes. Then, the quantification method of the index system is briefly discussed in preparation for mathematical calculation. A stochastic spares optimization model (SSOM) is proposed based on stochastic DEA with the constraints of 14 factors of the index system. The SSOM could be converted into equivalent deterministic models by probability theory, which overcomes the difficulty in solving non-linear programming. A numerical example is given to illustrate the proposed method in terms of ability to provide reasonable inventory management policies.

Complicated systems are always required to perform different missions each of which may include several phases. Meanwhile, these systems and their components can get exhausted and deteriorated during the operating processes, which drives systems and components into different states. These systems, which is in possession of the characteristics of multiple states and phased missions simultaneously, are called multi-state and phased-mission systems (MS-PMSs). During the last decade, some scholars have made considerable efforts to study the analyzing methods to the reliability of MS-PMSs. However, compared with the independent researches into multi-state systems or phased-mission systems, the achievement of MS-PMSs is still insufficient. Besides, these studies focused on the modeling methods to the MS-PMSs from the system level and the failure behavior was seldom mentioned. In this paper, by extending our previous studies, two accumulating rules of failure mechanism are provided and a revised hierarchical BDD-based method is proposed to model and analyze the reliability of MS-PMSs. Finally, a simplified realistic example is given to illustrate the using of the proposed method.

The optimization of spare parts inventory is very important in the modern aerospace engineering system, especially in the environment with low management effectiveness and a wide variety of spare parts. At present, there are many optimization models for spare parts inventory, and the single-objective optimization inventory is mostly used. But the single-objective optimization model has some limitations. First, in the applications of practical engineering, a single-goal decision problem is generally rare, and most of the decisions we have experienced involve many complicated goals. Second, it is difficult to truly present the actual situation when the mathematical programming model is used to discuss the optimization problem in practical engineering application. The solution to solve the model is a hybrid intelligent algorithm by combining the genetic algorithm with the inverse uncertainty distribution function. Finally, an example is given to illustrate the feasibility of the optimization model.

Abstract Background To investigate the potential mechanism of splenic enlargement in Ang II/APOE model and the associations between the spleen volume and the indices of abdominal aortic aneurysm (AAA) in human. Methods To investigate the changes of spleen volume on AAA formation, apolipoprotein E knockout (Apo E−/−) mice were treated with Ang II (1000 ng/kg/min) up to 28 days to generate AAA. We used Magnetic Resonance Imaging (MRI), liquid measurement, H&E and immunohistochemistry to analyze the morphological or pathological changes of spleen. To investigate the changes of spleen volume in human, a retrospective case-control study involving 30 male AAA patients and 25 male controls were performed. Spleen volume was measured on computed tomography images. Univariate analysis and multivariable sequential logistic regression analyses were used to analyze the association between spleen volume and maximal diameter (Dmax). Results In Ang II/APOE model, we found splenic enlargement in mice with AAA compared with the sham group. Histopathological investigations revealed hypertrophies of splenic follicles and increased populations of CD3+ T cells. In clinic cohort study, univariate analysis revealed higher values in large AAA (Dmax > 5.5 cm,n = 15) compared with the small (Dmax

Ferroptosis is a form of regulated cell death that may facilitate the selective elimination of tumor cells. The tumor suppressor p53 (TP53) has been demonstrated to promote ferroptosis via a transcription-dependent mechanism. Here, we show that TP53 limits erastin-induced ferroptosis by blocking dipeptidyl-peptidase-4 (DPP4) activity in a transcription-independent manner. Loss of TP53 prevents nuclear accumulation of DPP4 and thus facilitates plasma-membrane-associated DPP4-dependent lipid peroxidation, which finally results in ferroptosis. These findings reveal a direct molecular link between TP53 and DPP4 in the control of lipid metabolism and may provide a precision medicine strategy for the treatment of colorectal cancer by induction of ferroptosis.

Abstract Background P73 antisense RNA 1 T (non-protein coding), also known as TP73-AS1, is a long non-coding RNA (lncRNA) which is involved in cell proliferation and the development of tumors. However, the exact effects and molecular mechanisms of TP73-AS1 in hepatocellular carcinoma (HCC) progression are still unknown. The present study is aimed to investigate the detailed functions and the mechanism of TP73-AS1 in regulation of HCC cell proliferation. Methods TP73-AS1 expression in HCC tissues and cell lines was determined using real-time PCR assays; the correlation of TP73-AS1 expression with clinicopathological features of HCC was analyzed. The functions of TP73-AS1 in regulation of HCC cell proliferation was evaluated using MTT and BrdU assays. The candidate upstream miRNAs of HMGB1 were screened using miRcode, miRWalk, miRanda and Target scan, verified using real-time PCR assays. The interaction between TP73-AS1 and miR-200a was confirmed using Luciferase report gene assays. The proten levels of HMGB1 signaling-related factors in response to co-processing TP73-AS1 knockdown and miR-200a inhibition were determined using Western blot assays and ELISA. Further, miR-200a, HMGB1 mRNA and RAGE mRNA and their correlations in HCC tissues were determined. Results TP73-AS1 was upregulated in HCC tissues and cell lines. High TP73-AS1 expression was correlated with worse clinicopathological features, poorer prognosis and shorter survival. Knockdown of TP73-AS1 inhibited the HCC proliferation and the expression levels of HMGB1, RAGE and NF-κB in HCC cells. By using online tools, we screened out several candidate upstream miRNAs of HMGB1, among which miR-200a overexpression inhibited HMGB1 mRNA expression the most significantly. By using luciferase assays, we confirmed that miR-200a could directly bind to TP73-AS1 and the 3’UTR of HMGB1; TP73-AS1 competed with HMGB1 for miR-200a binding. MiR-200a inhibition could up-regulate HMGB1, RAGE, NF-κB expression as well as NF-κB regulated cytokines levels, which could be partially restored by si-TP73-AS1. In HCC tissues, miR-200a was down-regulated while HMGB1 and RAGE were up-regulated; TP73-AS1 was inversely correlated with miR-200a, while positively correlated with HMGB1 and RAGE, respectively. Conclusion Our data indicated that TP73-AS1 might be an oncogenic lncRNA that promoted proliferation of HCC and could be regarded as a therapeutic target in human HCC.

Accelerated degradation testing (ADT) is commonly used to obtain degradation data of products by exerting loads over usage conditions. Such data can be used for estimating component lifetime and reliability under usage conditions. The design of ADT entails to establish a model of the degradation process and define the test plan to satisfy given criteria under the constraint of limited test resources. Bayesian optimal design is a method of decision theory under uncertainty, which uses historical data and expert information to find the optimal test plan. Different expected utility functions can be selected as objectives. This paper presents a method for Bayesian optimal design of ADT, based on the inverse Gaussian process and considering three objectives for the optimization: relative entropy, quadratic loss function, and Bayesian D-optimality. The Markov chain Monte Carlo and the surface fitting methods are used to obtain the optimal plan. By sensitivity analysis and a proposed efficiency factor, the Bayesian D-optimality is identified as the most robust and appropriate objective for Bayesian optimization of ADT.

Model-based reliability analysis and assessment methods rely on models, which are assumed to be precise, to predict reliability. In practice, however, the precision of the model cannot be guaranteed due to the presence of epistemic uncertainty. In this paper, a new reliability metric, called belief reliability, is defined to explicitly account for epistemic uncertainty in model-based reliability analysis and assessment. A new method is developed to explicitly quantify epistemic uncertainty by measuring the effectiveness of the engineering analysis and assessment activities related to reliability. To evaluate belief reliability, an integrated framework is presented where the contributions of design margin, aleatory uncertainty, and epistemic uncertainty are integrated to yield a comprehensive and systematic description of reliability. The developed methods are demonstrated by two case studies.

Inflammation involves a Warburg effect that switches cellular metabolism to glycolysis. Here the authors show this switch drives IL-1β, IL-18 and HMGB1 release from macrophages by activating the NLRP3 and AIM2 inflammasomes via protein kinase R phosphorylation, a pathway that can be inhibited to prevent sepsis in mice.

Neutrophil extracellular trap (NET) formation results in the expulsion of granulocyte proteins and DNA into the extracellular space. This process is mediated by the enzyme peptidyl arginine deiminase 4 (PADI4) and translocation of elastase to the nucleus. NET formation, marked by increased levels of extracellular DNA, promotes pancreatic cancer proliferation and metastasis. Mice deficient in Padi4 demonstrate decreased pancreatic tumor growth, associated with a reduction in circulating extracellular DNA levels, diminished pancreatic stromal activation and improved survival in murine orthotopic pancreatic adenocarcinoma. Transplantation of Padi4−/− bone marrow into genetically engineered mice with Kras driven pancreatic adenocarcinoma (Pdx1-Cre:KrasG12D/+, KC mice) limits the frequency of invasive cancers when compared with syngeneic controls. DNA from neutrophils activates pancreatic stellate cells that form dense, fibrous stroma which can promote and enable tumor proliferation. DNase treatment diminishes murine tumor growth and stromal activation to reverse the effect of NETs within the tumor microenvironment. Furthermore, deletion of the receptor for advanced glycation end products (RAGE) in pancreatic stellate cells abrogates the effects of DNA in promoting stellate cell proliferation and decreases tumor growth. Circulating neutrophil-derived DNA correlates with the stage in patients with pancreatic ductal adenocarcinoma, confirming the role of NETs in human pancreatic cancer. These findings support further investigation into targeting of NETs, PADI4 and extracellular DNA as a potential treatment strategy in patients with pancreatic cancer. Trial Registration: This study reports correlative data from a clinical trial registered with clinicaltrials.gov, NCT01978184 (November 7, 2013).

Inflammasome activation can trigger an inflammatory and innate immune response through the release of cytokines and induction of pyroptosis. A dysfunctional inflammasome has been implicated in the development of human pathologies, including sepsis and septic shock. Here, we show that advanced glycosylation end-product specific receptor (AGER/RAGE) is required for caspase-11 inflammasome activation in macrophages. A nuclear damage-associated molecular pattern (nDAMP) complex, including high-mobility group box 1, histone, and DNA, can promote caspase-11-mediated gasdermin D cleavage, interleukin 1β proteolytic maturation, and lactate dehydrogenase release. The inhibition of AGER-mediated lipid peroxidation via arachidonate 5-lipoxygenase (ALOX5) limits caspase-11 inflammasome activation and pyroptosis in macrophages in response to nDAMPs or cytosolic lipopolysaccharide. Importantly, the pharmacologic inhibition of the AGER-ALOX5 pathway or global depletion (Ager−/−) or conditional depletion of AGER in myeloid cells (AgerMye−/−) protects against lipopolysaccharide-induced septic death in poly(I:C)-primed mice. These data identify a molecular basis for caspase-11 inflammasome activation and provide a potential strategy to treat sepsis.

Abstract Sepsis is characterized by dysregulated systemic inflammation with release of early (for example, Interleukin (IL)-1β) and late (for example, HMGB1) proinflammatory mediators from macrophages. Plumbagin, a medicinal plant-derived naphthoquinone, has been reported to exhibit antiinflammatory activity, but the underling mechanisms remain unclear. Here, we have demonstrated that plumbagin inhibits the inflammatory response through interfering with the immunometabolism pathway in activated macrophages. Remarkably, plumbagin inhibited lipopolysaccharide (LPS)-induced aerobic glycolysis by downregulating the expression of pyruvate kinase M2 (PKM2), a protein kinase responsible for the final and rate-limiting reaction step of the glycolytic pathway. Moreover, the NADPH oxidase 4 (NOX4)-mediated oxidative stress was required for LPS-induced PKM2 expression, because pharmacologic or genetic inhibition of NOX4 by plumbagin or RNA interference limited LPS-induced PKM2 expression, lactate production and subsequent proinflammatory cytokine (IL-1β and HMGB1) release in macrophages. Finally, plumbagin protected mice from lethal endotoxemia and polymicrobial sepsis induced by cecal ligation and puncture. These findings identify a new approach for inhibiting the NOX4/PKM2-dependent immunometabolism pathway in the treatment of sepsis and inflammatory diseases.