A visible light-activated azo-fluorescent switch for imaging-guided and light-controlled release of antimycotics.

Azo switches are widely employed as essential components in light-responsive systems. Here, we develop an azo-fluorescent switch that is visible light-responsive and its light-responsive processes can be monitored using fluorescence imaging. Visible light irradiation promotes isomerization, accompanied by changes in fluorescence that enable the process to be monitored through fluorescence imaging. Furthermore, we document that the nanocavity size of liposome encapsulated nanoparticles containing azo changes in the isomerization process and show that this change enables construction of a light-responsive nanoplatform for optically controlled release of antimycotics. Also, natural light activation of nanoparticles of the switch loaded with an antimycotic agent causes death of Rhizoctonia solani. The results show that these nanoparticles can double the holding period in comparison to small molecule antimycotics. The strategy used to design the imaging-guided light-controlled nano-antimycotic release system can be applicable to protocols for controlled delivery of a wide variety of drugs.

[Analysis of Clinical Characteristics and Prognosis of AML Patients with Co-Mutation of CEBPA Gene and GATA2 Gene].

OBJECTIVE: To analyze the clinical characteristics and prognosis of patients with co-mutation of CEBPA gene and GATA2 gene, so as to facilitate clinicians to formulate more accurate individualized treatment plans for patients. METHODS: A total of 43 acute myeloid leukemia (AML) patients with CEBPA double mutations and CEBPA-bZIP domain mutation admitted to the First Affiliated Hospital of Harbin Medical University from January 2017 to April 2022 were included, and the clinical characteristics and prognosis of patients with GATA2 gene mutation among them were compared and analyzed. RESULTS: The median age of patients with GATA2 gene mutation was 48.0 years, which was significantly lower than 57.0 years of patients without GATA2 gene mutation (P < 0.05). However, there were no significant differences in sex, white blood cell count, hemoglobin concentration, platelet count, immunophenotype, bone marrow and peripheral blood blast cell ratio and complete remission rate between the two groups (P >0.05). The median overall survival and event-free survival time of patients with GATA2 gene mutation were not reached, while those of patients without GATA2 gene mutation were 14.8 and 8.1 months, respectively (both P < 0.05). CONCLUSION: The median age of patients with GATA2 gene mutation is lower than that of patients without GATA2 gene mutation. GATA2 gene mutation further prolongs the survival time of AML patients with CEBPA double mutations and CEBPA-bZIP domain mutation.

Adaptive Distributed Control of Nonlinear Multiagent Systems With Event-Triggered for Communication Faults and Dead-Zone Inputs.

This article studies the containment control problem of nonlinear multiagent systems (MASs) subjected to communication link faults and dead-zone inputs. In case of an unknown fault in the communication link, there is no constant Laplacian matrix anymore and each follower agent cannot be informed of the global information simultaneously. To deal with this problem, an adaptive compensating estimator is constructed to estimate the signal spanned by the leaders. Instead of using the linear filter, a nonlinear filter is employed, which both solves the classical complexity explosion in the traditional backstepping method and flushes out the usefulness of the boundary layer error. Considering the dead zone input, we propose two event-triggered schemes, that is, the update-triggered scheme and the transmit-triggered scheme. In the former, the threshold function involves the tracking errors and additional dynamic variable, which can provide the desirable tradeoff between the containment control performance of the considered MASs and saving communication resources. In the latter, the triggered condition is designed according to the characteristic of dead zone, which makes the communication burden be reduced further. Following the backstepping design framework, an adaptive containment control is constructed, it is shown that the containment error can converge to an adjustable residual set even if MASs are subjected to the unknown and bounded communication link faults and dead-zone inputs. Finally, an example is given to show the effectiveness of the proposed results.

Optimized Backstepping-Based Containment Control for Multiagent Systems With Deferred Constraints Using a Universal Nonlinear Transformation.

This article investigates an optimized containment control problem for multiagent systems (MASs), where all followers are subject to deferred full-state constraints. A universal nonlinear transformation is proposed for simultaneously handling the cases with and without constraints. Particularly, for the constrained case, initial values of states are flexibly managed to the midpoint between upper and lower boundaries by utilizing a state-shifting function, thus eliminating the initial restriction conditions. By deferred constraints, the state is forced to fall back into the restrictive boundaries within a preassigned time. A neural network (NN)-based reinforcement learning (RL) algorithm is executed under the identifier-critic-actor architecture, where the Hamilton-Jacobi-Bellman (HJB) equation is built in every subsystem to optimize control performance. For actor and critic NNs, updating laws are simplified, since the gradient descent method is performed based on a simple positive function rather than square of Bellman residual error. In view of the Lyapunov stability theorem and graph theory, it is proved that all signals are bounded and the outputs of followers can eventually enter into the convex hull constituted by leaders. Finally, simulations confirm the validity of the proposed approach.

N-palmitoylethanolamide attenuates negative emotions induced by morphine withdrawal in mice.

Depression and anxiety are prominent symptoms of withdrawal syndrome, often caused by the abuse of addictive drugs like morphine. N-palmitoylethanolamide (PEA), a biologically active lipid, is utilized as an anti-inflammatory and analgesic medication. Recent studies have highlighted PEA's role in mitigating cognitive decline and easing depression resulting from chronic pain. However, it remains unknown whether PEA can influence negative emotions triggered by morphine withdrawal. This study seeks to explore the impact of PEA on such emotions and investigate the underlying mechanisms. Mice subjected to morphine treatment underwent a 10-day withdrawal period, followed by assessments of the effect of PEA on anxiety- and depression-like behaviors using various tests. Enzyme-linked immunosorbent assay was conducted to measure levels of monoamine neurotransmitters in specific brain regions. The findings indicate that PEA mitigated anxiety and depression symptoms and reduced 5-hydroxytryptamine, noradrenaline, and dopamine levels in the hippocampus and prefrontal cortex. In summary, PEA demonstrates a significant positive effect on negative emotions associated with morphine withdrawal, accompanied with the reduction in levels of monoamine neurotransmitters in key brain regions. These insights could be valuable for managing negative emotions arising from morphine withdrawal.

Imaging Dissolution Dynamics of Individual NaCl Nanoparticles during Deliquescence with In Situ Transmission Electron Microscopy.

Water vapor condensation on hygroscopic aerosol particles plays an important role in cloud formation, climate change, secondary aerosol formation, and aerosol aging. Conventional understanding considers deliquescence of nanosized hygroscopic aerosol particles a nearly instantaneous solid to liquid phase transition. However, the nanoscale dynamics of water condensation and aerosol particle dissolution prior to and during deliquescence remain obscure due to a lack of high spatial and temporal resolution single particle measurements. Here we use real time in situ transmission electron microscopy (TEM) imaging of individual sodium chloride (NaCl) nanoparticles to demonstrate that water adsorption and aerosol particle dissolution prior to and during deliquescence is a multistep dynamic process. Water condensation and aerosol particle dissolution was investigated for lab generated NaCl aerosols and found to occur in three distinct stages as a function of increasing relative humidity (RH). First, a < 100 nm water layer adsorbed on the NaCl cubes and caused sharp corners to dissolve and truncate. The water layer grew to several hundred nanometers with increasing RH and was rapidly saturated with solute, as evidenced by halting of particle dissolution. Adjacent cube corners displayed second-scale curvature fluctuations with no net particle dissolution or water layer thickness change. We propose that droplet solute concentration fluctuations drove NaCl transport from regions of high local curvature to regions of low curvature. Finally, we observed coexistence of a liquid water droplet and aerosol particle immediately prior to deliquescence. Particles dissolved discretely along single crystallographic directions, separated by few second lag times with no dissolution. This work demonstrates that deliquescence of simple pure salt particles with sizes in the range of 100 nm to several microns is not an instantaneous phase transition and instead involves a range of complex dissolution and water condensation dynamics.

Dual Channels Event-Triggered Asymptotic Consensus Control for Fractional-Order Nonlinear Multiagent Systems.

This article investigates the event-triggered leaderless consensus control problem for fractional-order multiagent systems (FOMASs), where both the agent-to-agent communication channel and the controller-to-actuator communication channel are based on the events. A filter is introduced to transform the original high-order system into a first-order one, greatly simplifying the complexity of controller design compared to the traditional backstepping. Further, the convergence of filtered output signals is proved to be consistent with that of the outputs of agents themselves. Superior to the traditional event-triggered scheme, two dynamic variables are designed for the triggering conditions of the communication among agents and the controller update, respectively. Via elaborately constructing the dynamic variables, zero-error leaderless consensus can be achieved instead of only ultimately uniformly bounded result. It is proved that the proposed control strategy can guarantee better control performance of leaderless consensus under limited communication resources, and Zeno behavior is excluded. Finally, two examples are provided to verify the effectiveness of our proposed control approach.

Nussbaum-Based Adaptive Neural Networks Tracking Control for Nonlinear PDE-ODE Systems Subject to Deception Attacks.

In this article, the novel adaptive neural networks (NNs) tracking control scheme is presented for nonlinear partial differential equation (PDE)-ordinary differential equation (ODE) coupled systems subject to deception attacks. Because of the special infinite-dimensional characteristics of PDE subsystem and the strong coupling of PDE-ODE systems, it is more difficult to achieve the tracking control for coupled systems than single ODE system under the circumstance of deception attacks, which result in the states and outputs of both PDE and ODE subsystems unavailable by injecting false information into sensors and actuators. For efficient design of the controllers to realize the tracking performance, a new coordinate transformation is developed under the backstepping method, and the PDE subsystem is transformed into a new form. In addition, the effect of the unknown control gains and the uncertain nonlinearities caused by attacks are alleviated by introducing the Nussbaum technology and NNs. The proposed tracking control scheme can guarantee that all signals in the coupled systems are bounded and the good tracking performance can be achieved, despite both sensors and actuators of the studied systems suffering from attacks. Finally, a simulation example is given to verify the effectiveness of the proposed control method.

ADP-Based Fault-Tolerant Control for Multiagent Systems With Semi-Markovian Jump Parameters.

This article analyzes and validates an approach of integration of adaptive dynamic programming (ADP) and adaptive fault-tolerant control (FTC) technique to address the consensus control problem for semi-Markovian jump multiagent systems having actuator bias faults. A semi-Markovian process, a more versatile stochastic process, is employed to characterize the parameter variations that arise from the intricacies of the environment. The reliance on accurate knowledge of system dynamics is overcome through the utilization of an actor-critic neural network structure within the ADP algorithm. A data-driven FTC scheme is introduced, which enables online adjustment and automatic compensation of actuator bias faults. It has been demonstrated that the signals generated by the controlled system exhibit uniform boundedness. Additionally, the followers' states can achieve and maintain consensus with that of the leader. Ultimately, the simulation results are given to demonstrate the efficacy of the designed theoretical findings.

Characterization of different-sized human αA-crystallin homomers and implications to Asp151 isomerization.

Site-specific modifications of aspartate residues spontaneously occur in crystallin, the major protein in the lens. One of the primary modification sites is Asp151 in αA-crystallin. Isomerization and racemization alter the crystallin backbone structure, reducing its stability by inducing abnormal crystallin-crystallin interactions and ultimately leading to the insolubilization of crystallin complexes. These changes are considered significant factors in the formation of senile cataracts. However, the mechanisms driving spontaneous isomerization and racemization have not been experimentally demonstrated. In this study, we generated αA-crystallins with different homo-oligomeric sizes and/or containing an asparagine residue at position 151, which is more prone to isomerization and racemization. We characterized their structure, hydrophobicity, chaperone-like function, and heat stability, and examined their propensity for isomerization and racemization. The results show that the two differently sized αA-crystallin variants possessed similar secondary structures but exhibited different chaperone-like functions depending on their oligomeric sizes. The rate of isomerization and racemization of Asp151, as assessed by the deamidation of Asn151, was also found to depend on the oligomeric sizes of αA-crystallin. The predominant isomerization product via deamidation of Asn151 in the different-sized αA-crystallin variants was L-ß-Asp in vitro, while various modifications occurred around Asp151 in vivo. The disparity between the findings of this in vitro study and in vivo studies suggests that the isomerization of Asp151 in vivo may be more complex than what occurs in vitro.

Case report: Ultrasound misdiagnoses atypical parathyroid adenoma as malignant thyroid tumor.

Atypical Parathyroid Adenoma (APA) is a type of tumor that lies somewhere between parathyroid adenoma and parathyroid carcinoma. It often affects adults over the age of 60, and the clinical symptoms are consistent with those of hyperparathyroidism. This condition has a low occurrence, and its ultrasonographic signs are strikingly similar to thyroid malignant tumors, making it easily misdiagnosed. As a result, a case of APA ultrasonography misdiagnosis admitted to our hospital was recorded in order to serve as a reference point for APA diagnosis.

Characterization of ßB2-crystallin tryptophan mutants reveals two different folding states in solution.

Conserved tryptophan residues are critical for the structure and the stability of ß/γ-crystallin in the lenses of vertebrates. During aging, in which the lenses are continuously exposed to ultraviolet irradiation and other environmental stresses, oxidation of tryptophan residues in ß/γ-crystallin is triggered and impacts the lens proteins to varying degrees. Kynurenine derivatives, formed by oxidation of tryptophan, accumulate, resulting in destabilization and insolubilization of ß/γ-crystallin, which correlates with age-related cataract formation. To understand the contribution of tryptophan modification on the structure and stability of human ßB2-crystallin, five tryptophan residues were mutated to phenylalanine considering its similarity in structure and hydrophilicity to kynurenine. Among all mutants, W59F and W151F altered the stability and homo-oligomerization of ßB2-crystallin-W59F promoted tetramerization whereas W151F blocked oligomerization. Most W59F dimers transformed into tetramer in a month, and the separated dimer and tetramer of W59F demonstrated different structures and hydrophobicity, implying that the biochemical properties of ßB2-crystallin vary over time. By using SAXS, we found that the dimer of ßB2-crystallin in solution resembled the lattice ßB1-crystallin dimer (face-en-face), whereas the tetramer of ßB2-crystallin in solution resembled its lattice tetramer (domain-swapped). Our results suggest that homo-oligomerization of ßB2-crystallin includes potential inter-subunit reactions, such as dissociation, unfolding, and re-formation of the dimers into a tetramer in solution. The W>F mutants are useful in studying different folding states of ßB2-crystallin in lens.

Integral BLF-Based Adaptive Dynamic Event-Triggered Boundary Control for a Flexible Riser System.

For the flexible riser systems modeled with partial differential equations (PDEs), this article explores the boundary control problem in depth for the first time using a dynamic event-triggered mechanism (DETM). Given the intrinsic time-space coupling characteristic inherent in PDE computations, implementing a state-dependent DETM for PDE-based flexible risers presents a significant challenge. To overcome this difficulty, a novel dynamic event-triggered control method is introduced for flexible riser systems, focusing on optimizing available control inputs. In order to save computational costs from the controller to the actuator, a dynamic event-triggered adaptive boundary controller is designed to effectively reduce boundary position vibrations. Additionally, considering external disturbances, an adaptive bounded compensation term is incorporated to counteract the influence of external disturbances on the system. Addressing boundary position constraints, a new integral barrier Lyapunov function (iBLF) tailored specifically for flexible riser systems is introduced, thereby alleviating conservatism in the controller design of flexible risers modeled by PDEs. At last, the validity of the proposed method is demonstrated through a simulation example.

Integrated molybdenum single atom array sensors with multichannels for nitrite detection in foods.

Nitrite (NO2-) is present in a variety of foods, but the excessive intake of NO2- can indirectly lead to carcinogenic, teratogenic, mutagenicity and other risks to the human body. Therefore, the detection of NO2- is crucial for maintaining human health. In this study, an integrated array sensor for NO2- detection is developed based on molybdenum single atom material (IMSMo-SAC) using high-resolution electrohydrodynamic (EHD) printing technology. The sensor comprises three components: a printed electrode array, multichannels designed on polydimethylsiloxane (PDMS) and an electronic signal process device with bluetooth. By utilizing Mo-SAC to facilitate electron transfer during the redox reaction, rapid and efficient detection of NO2- can be achieved. The sensor has a wide linear range of 0.1 µM-107.8 mM, a low detection limit of 33 nM and a high sensitivity of 0.637 mA-1mM-1 cm-2. Furthermore, employing this portable array sensor allows simultaneously measurements of NO2- concentrations in six different foods samples with acceptable recovery rates. This array sensor holds great potential for detecting of small molecules in various fields.

Electrochemical aptasensors based on porous carbon derived from graphene oxide/ZIF-8 composites for the detection of Erwinia cypripedii.

In this research, self-screening aptamer and MOFs-derived nanomaterial have been combined to construct electrochemical aptasensor for environmental detection. By utilizing the large specific surface area of reduced graphene oxide (rGO), ZIF-8 was grown in situ on surface of rGO, and the composites was pyrolyzed to obtain MOFs-derived porous carbon materials (rGO-NCZIF). Thanks to the synergistic effect between rGO and NCZIF, the complex exhibits remarkable characteristics, including a high electron transfer rate and electrocatalytic activity. In addition, the orderly arrangement of imidazole ligands within ZIF-8 facilitated the uniform doping of nitrogen elements into the porous carbon, thereby significantly enhancing its electrochemical performance. After carboxylation, rGO-NCZIF was functionalized with self-screening aptamer for fabricating electrochemical aptasensor, which can be used to detect Erwinia cypripedii, a kind of quarantine plant bacteria, with detection limit of 4.92 × 103 cfu/mL. Due to the simplicity and speed, the aptasensor is suitable for rapid customs inspection and quarantine. Additionally, the universality of this sensing strategy was verified through exosomes detection by changing the aptamer. The results indicated that the rGO-NCZIF-based electrochemical aptasensor had practical value in the environmental and medical fields.

Evolutionary Dynamics-Driven Learning of Optimal Decisions for Nonlinear System: Extend-Policy Iterative Algorithm.

An extend-policy iterative algorithm is proposed for solving the ecological evolving-lung cancer cells growth inhibition optimal drug delivery scheme. With the analysis of the cell proliferation-apoptosis process of lung cancer cells with primitive immune system and external drug interventions, such as chemotherapeutic drugs and immunological agents, a model of ecological containment of lung cancer cells mimicking injection labeling is constructed. The HJB equation for biological tissue damage has also been established by considering the concentration of lung cancer cells in the blood and the amount of drug administered. The final simulation experiment proved the effectiveness of the drug delivery scheme.

Machine intelligence-accelerated discovery of all-natural plastic substitutes.

One possible solution against the accumulation of petrochemical plastics in natural environments is to develop biodegradable plastic substitutes using natural components. However, discovering all-natural alternatives that meet specific properties, such as optical transparency, fire retardancy and mechanical resilience, which have made petrochemical plastics successful, remains challenging. Current approaches still rely on iterative optimization experiments. Here we show an integrated workflow that combines robotics and machine learning to accelerate the discovery of all-natural plastic substitutes with programmable optical, thermal and mechanical properties. First, an automated pipetting robot is commanded to prepare 286 nanocomposite films with various properties to train a support-vector machine classifier. Next, through 14 active learning loops with data augmentation, 135 all-natural nanocomposites are fabricated stagewise, establishing an artificial neural network prediction model. We demonstrate that the prediction model can conduct a two-way design task: (1) predicting the physicochemical properties of an all-natural nanocomposite from its composition and (2) automating the inverse design of biodegradable plastic substitutes that fulfils various user-specific requirements. By harnessing the model's prediction capabilities, we prepare several all-natural substitutes, that could replace non-biodegradable counterparts as exhibiting analogous properties. Our methodology integrates robot-assisted experiments, machine intelligence and simulation tools to accelerate the discovery and design of eco-friendly plastic substitutes starting from building blocks taken from the generally-recognized-as-safe database.

Adaptive Virotherapy Strategy for Organism With Constrained Input Using Medicine Dosage Regulation Mechanism.

In this article, the constrained adaptive control strategy based on virotherapy is investigated for organism using the medicine dosage regulation mechanism (MDRM). First, the tumor-virus-immune interaction dynamics is established to model the relations among the tumor cells (TCs), virus particles, and the immune response. The adaptive dynamic programming (ADP) method is extended to approximately obtain the optimal strategy for the interaction system to reduce the populations of TCs. Due to the consideration of asymmetric control constraints, the nonquadratic functions are proposed to formulate the value function such that the corresponding Hamilton-Jacobi-Bellman equation (HJBE) is derived which can be deemed as the cornerstone of ADP algorithms. Then, the ADP method of a single-critic network architecture which integrates MDRM is proposed to obtain the approximate solutions of HJBE and eventually derive the optimal strategy. The design of MDRM makes it possible for the dosage of the agentia containing oncolytic virus particles to be regulated timely and necessarily. Furthermore, the uniform ultimate boundedness of the system states and critic weight estimation errors is validated by Lyapunov stability analysis. Finally, simulation results are given to show the effectiveness of the derived therapeutic strategy.

Cooperative Control for Stochastic Multiagent Systems With Deferred Dynamic Constraints via a Novel Universal Barrier Function Approach.

This article investigates the cooperative control problem for stochastic multiagent systems (MASs) with dynamic constraints. A new universal barrier function is proposed, which is applicable to many systems with different types of constraint functions, even unconstrained systems. Several mapping functions are constructed to constrain the state variables directly without feasibility conditions, and the tracking control is achieved for stochastic MASs with deferred full-state constraints under the backstepping framework. In order to regulate the tracking error more precisely, the funnel error transformation is improved and the deferred funnel controller is developed by introducing a preassigned finite-time function. Based on the deferred funnel controller, the tracking error can be maintained within the predetermined funnel in the preassigned time. The convergence time can be defined according to the actual requirements, and it is independent of the design controller parameters and initial conditions. Finally, some simulation results are given to demonstrate the effectiveness of the proposed control algorithm.

Dynamic Threshold Finite-Time Prescribed Performance Control for Nonlinear Systems With Dead-Zone Output.

This article investigates the tracking control problem for nonlinear systems. An adaptive model is proposed to represent the dead-zone phenomenon and solve its control challenge with a Nussbaum function in conjunction. Drawing inspiration from the existing prescribed performance control schemes, a novel dynamic threshold scheme is developed that fuses a proposed continuous function with a finite-time performance function. A dynamic event-triggered strategy is applied to reduce the redundant transmission. The proposed time-varying threshold control strategy has fewer updates than the traditional fixed threshold and improves the efficiency of resource utilization. A command filter backstepping approach is employed to prevent the complexity explosion faced by the computation. The suggested control strategy ensures that all system signals are bounded. The validity of the simulation results has been verified.