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The recent years has witnessed an exponential growth in the field of natural killer (NK) cell-based immunotherapy for cancer treatment. As a prerequisite to precise evaluations and on-demand interventions, the noninvasive tracking of adoptive NK cells plays a crucial role not only in post-treatment monitoring, but also in offering opportunities for preclinical studies on therapy optimizations. Here, we describe an NK cell tracking strategy for cancer immunotherapy based on ultrasound imaging modality. Nanosized ultrasound contrast agents, gas vesicles (GVs), were surface-functionalized to label NK cells. Unlike traditional microbubble contrast agents, nanosized GVs with their unique thermodynamical stability enable the detection of labeled NK cells under nonlinear contrast-enhanced ultrasound (nCEUS), without a noticeable impact on cellular viability or migration. By such labeling, we were able to monitor the trafficking of systematically infused NK cells to a subcutaneous tumor model. Upon co-treatment with interleukin (IL)-2, we observed a rapid enhancement in NK cell trafficking at the tumor site as early as 3 h post-infusion. Altogether, we show that the proposed ultrasound-based tracking strategy is able to capture the dynamical changes of cell trafficking in NK cell-based immunotherapy, providing referencing information for early-phase monotherapy evaluation, as well as understanding the effects of modulatory co-treatment. In cellular immunotherapies, the post-infusion monitoring of the living therapeutics has been challenging. Several popular imaging modalities have been explored the monitoring of the adoptive immune cells, evaluating their trafficking and accumulation in the tumor. Here we demonstrated, for the first time, the ultrasound imaging-based immune cell tracking strategy. We showed that the acoustic labeling of adoptive immune cells was feasible with nanosized ultrasound contrast agents, overcoming the size and stability limitations of traditional microbubbles, enabling dynamical tracking of adoptive natural killer cells in both monotherapy and synergic treatment with cytokines. This article introduced the cost-effective and ubiquitous ultrasound imaging modality into the field of cellular immunotherapies, with broad prospectives in early assessment and on-demand image-guided interventions. [Display omitted] [ABSTRACT FROM AUTHOR]

• UPLC-Q-TOF-MS and R software were used to identify YSH absorbable chemicals and predict its treatment mechanism. • The efficacy of YSH in alleviating chronic liver injury was studied for the first time. • YSH absorbable chemicals treat chronic liver injury by regulating AKT phosphorylation. Chronic liver injury (CLI) is a complex condition that requires effective therapeutic interventions. The Yi-Shan-Hong (YSH) formula is an empirically derived remedy that has shown effectiveness and safety in the management of chronic liver damage. However, the bioactive components and multifaceted mechanisms of YSH remain inadequately understood. To examine the bioactive compounds and functional processes that contribute to the therapeutic benefits of YSH against CLI. Serum pharmacochemistry and network pharmacology were employed to identify active compounds and possible targets of YSH in CLI. In addition, YSH was also given in three doses to d -(+)-galactosamine hydrochloride (D -GalN) -induced CLI rats to test its therapeutic efficacy. The analysis of serum samples successfully detected 25 compounds from YSH. Searches on the databases resulted in 277 genes as being correlated with chemicals in YSH, and 397 genes associated with CLI. In vivo experiments revealed that YSH displayed a notable therapeutic impact on liver injury caused by d -GalN. This was evidenced by enhanced liver function and histopathological improvements, reduced oxidative stress response, proinflammatory factors, and fibrosis levels. Importantly, no discernible adverse effects were observed. Furthermore, the administration of YSH treatment reversed the activation of AKT phosphorylation caused by d -GalN, aligning with the findings of the network pharmacology study. These findings provide preclinical evidence of YSH's therapeutic value in CLI and highlight its hepatoprotective action via the PI3K/AKT signaling pathway. [Display omitted] [ABSTRACT FROM AUTHOR]

Gamma-aminobutyric acid (GABA), a non-protein-producing amino acid synthesized from the excitatory amino acid glutamate via the enzyme glutamic acid decarboxylase, is extensively found in microorganisms, plants and vertebrates, and is abundantly expressed in the spinal cord and brain. It is the major inhibitory neurotransmitter in the mammalian nervous system. GABA plays crucial roles in the regulation of synaptic transmission, the promotion of neuronal development and relaxation, and the prevention of insomnia and depression. As the major inhibitory neurotransmitter, GABA plays pivotal roles in the regulation of pain sensation, which is initiated by the activation of peripheral nociceptors and transmitted to the spinal cord and brain along nerves. GABA exerts these roles by directly acting on three types of receptors: ionotropic GABA A and GABA C receptors and G protein-coupled GABA B receptor. The chloride-permeable ion channel receptors GABA A and GABA C mediate fast neurotransmission, while the metabotropic GABA B receptor mediates slow effect. Different GABA receptors regulate pain sensation via different signaling pathways. Here we highlight recent updates on the involvement of specific GABA receptors and their subtypes in the process of pain sensation. Further understanding of different GABA receptors and signaling pathways in pain sensation will benefit the development of novel analgesics for pain management by targeting specific GABA receptor subtypes and signaling pathways. [Display omitted] • GABA regulates synaptic transmission contributing to pain sensation. • GABA A receptor regulates membrane potential depending on transmembrane chloride gradient. • GABA A receptor-mediated analgesic effects rely on subunits compositions. • GABA B receptor modulates pain transmission. [ABSTRACT FROM AUTHOR]

A task allocation problem for heterogeneous unmanned aerial vehicles (UAVs) in the presence of environment uncertainty is studied in this paper. Generally, the process of finding efficient allocation scheme can be computationally prohibitive. This work presents a Q-learning based fast task allocation (FTA) algorithm through neural network approximation and prioritized experience replay, which effectively offloads the online computation to an offline learning procedure. Specifically, the proposed approach develops a Q network that encodes the allocation rules. The Q network not only considers the effect of environment uncertainty, but also is capable of handling total different tasks. Comparison simulations are provided to show the efficiency of the proposed algorithm. [ABSTRACT FROM AUTHOR]

The distributed finite-time formation tracking control problem for multiple unmanned helicopters is investigated in this paper. The control object is to maintain the positions of follower helicopters in formation with external interferences. The helicopter model is divided into a second order outer-loop subsystem and a second order inner-loop subsystem based on multiple-time scale features. Using radial basis function neural network (RBFNN) technique, we first propose a novel finite-time multivariable neural network disturbance observer (FMNNDO) to estimate the external disturbance and model uncertainty, where the neural network (NN) approximation errors can be dynamically compensated by adaptive law. Next, based on FMNNDO, a distributed finite-time formation tracking controller and a finite-time attitude tracking controller are designed using the nonsingular fast terminal sliding mode (NFTSM) method. In order to estimate the second derivative of the virtual desired attitude signal, a novel finite-time sliding mode integral filter is designed. Finally, Lyapunov analysis and multiple-time scale principle ensure the realization of control goal in finite-time. The effectiveness of the proposed FMNNDO and controllers are then verified by numerical simulations. [ABSTRACT FROM AUTHOR]

The traditional structural analysis of the containment building subjected to aircraft impact forces is often performed using the uncoupled calculation method, which directly applies the reaction force versus time curve to the containment building. The difference between the displacement of containment building calculated with the uncoupled method and that calculated using the coupled method is of significant. In order to explain the cause of this problem, the theoretical analysis of the simplified model are presented. The aircraft is simplified as a single-degree-of-freedom (SDOF) model. Three containment building models with different degree of simplification are analyzed, including the elastic free model, elastic clamped model and elastoplastic model with fixed support. The surfaces of these models are perpendicular to the direction of impact. The results indicate that due to Riera assumes the target to be rigid with fixed support, the impact force equation will lead to the calculation time difference between uncoupled method and coupled method. And the difference of time will cause the different displacement of the containment building by order of magnitude. Riera’s impact force equation is widely used in the uncoupled method, so its rationality has great significance. This work points out the shortcoming of this equation, and provides a theoretical support for the improvement of the containment structural performance analysis method due to aircraft strike, also for the subsequent improvement of the impact force equations. [ABSTRACT FROM AUTHOR]

The applications of dielectric capacitors are essential for modern pulsed-power and high-power electronic devices. Antiferroelectric ceramics have garnered much attention as promising materials for capacitive energy storage on account of their ultrahigh recoverable energy density (W rec). However, the relatively high energy loss originating from electric field induced antiferroelectric-ferroelectric (AFE-FE) phase transition results in low energy storage efficiency (η). Herein, the La3+ ions incorporated (Pb 0.98 Sr 0.02)(Zr 0.85 Sn 0.15)O 3 antiferroelectric ceramics were explored to obtain stable antiferroelectric phase and trigger a unique multistage AFE-FE(Ⅰ)-FE(Ⅱ) phase transition simultaneously. Consequently, this strategy led to the achievement of an ultrahigh W rec of 13.9 J/cm3 and an enhanced η of 80.4% in the optimal composition. Notably, these ceramics have also demonstrated exceptional thermal reliability of W rec and η in a wide temperature range, outperforming other previously reported PbZrO 3 -based ceramics. These results offer an efficient approach to promote the capacitive energy storage behavior in antiferroelectric ceramics. [ABSTRACT FROM AUTHOR]

A novel poly(aspartic acid) based PASP-l-PAHy hydrogel possesses the comprehensive merits of injectability, self-biodegradability, shape-adaptability, transparence, biocompatibility, and adhesion is reported. The hydrogel could seamlessly fill and stably adhere to skin incisions, and accelerate wound healing process. [Display omitted] • Designing and developing a novel versatile poly(aspartic acid) hydrogel. • The multiple crosslinks of chemical bonds (amide bond) and physical bonds (ionic bond and hydrogen bond) endows the hydrogel with comprehensive merits. • Desired autolytic biodegradation ensures removal trauma of wound dressing after 10 days. • The poly(aspartic acid) based hydrogel accelerates rat skin full-thickness wound healing. Severely chronic dermal wounds with irregular rupture shapes or even cavities are calling for injectable and self-biodegradable wound dressings for skin lesion with complex contours remain a great challenge. Here, we report an injectable, self-biodegradable poly(aspartic acid)-l-poly(aspartyl hydrazide) (PASP-l-PAHy) hydrogel to address these issues. The starting materials were cheap, and the new strategy for fabrication of self-biodegradable poly(aspartic acid) based hydrogel was facile, efficient, mild and environmentally friendly, which is consistent with the concept of green chemistry. The hydrogel possesses the comprehensive merits of injectability, self-biodegradability, shape-adaptability, transparence, biocompatibility, and adhesion, and shows specific autolytic biodegradation. The hydrogel was generated by in-situ gelation of poly(aspartic acid) (PASP) and poly(aspartyl hydrazide) (PAHy) polymers based on dual chemical (amide bond) and physical (hydrogen bond and ionic bond) crosslinks. The acceleration of wound healing could be observed in a rat skin full-thickness wound model for repairing skin tissue defects via hydrogel injection and autolytic biodegradation, highlighting great potential applications in wound dressing for the irregular dermal lesions without secondary skin damage. The injectable and self-biodegradable hydrogel augments formation of blood vessels and mature granulation tissue, thus enabling faster skin tissue restoration outcomes. [ABSTRACT FROM AUTHOR]

A major challenge in motor imagery (MI) of electroencephalogram (EEG) based brain–computer interfaces (BCIs) is the individual differences for different people. That the classification model should be retrained from scratch for a new subject often leads to unnecessary time consumption. In this paper, a "brain-ID" framework based on the hybrid deep neural network with transfer learning (HDNN-TL) is proposed to deal with individual differences of 4-class MI task. An end-to-end HDNN is developed to learn the common features of MI signal. HDNN consists of convolutional neural network (CNN) and Long Short-Term Memory (LSTM) which are utilized to decode the spatial and temporal features of the MI signal simultaneously. To deal with the EEG individual differences problem, transfer learning technique is implemented to fine-tune the followed fully connected (FC) layer to accommodate new subject with fewer training data. The classification performance on BCI competition IV dataset 2a by the proposed HDNN-TL in terms of kappa value is 0.8. We compared HDNN-TL, HDNN and other state-of-art methods and the experimental results demonstrate that the proposed method can get a satisfying result for new subjects with less time and fewer training data in MI task. [ABSTRACT FROM AUTHOR]

• A stochastic distribution system planning with energy storage degradation is solved. • Energy arbitrage and regulation services are co-optimized for siting and sizing. • A Gaussian mixture model is adopted to generate stochastic scenarios. • A modified progressive hedging algorithm which outperforms Gurobi is introduced. With the trend of energy storage participating in ancillary service markets, it is still computationally burdensome to incorporate the rapidly changing real-time signals in the long-run distribution system planning. In this paper, a two-stage stochastic programming is proposed for the distribution system with energy storage, where the storage degradation and ancillary service revenue for frequency regulation are both considered. For this purpose, the problem is formulated as a mixed-integer linear programming optimizing the overall planning cost, including investment and maintenance cost, power transaction cost and revenue from regulation services. A degradation penalty is added in the objective to avoid excessive charge/discharge when providing regulation services, thus further benefiting the economy of the distribution system. The model also considers uncertainties of load demand and electricity prices. A Gaussian mixture model is adopted to characterize these uncertainties and a set of representative scenarios are sampled. To accelerate the optimization, a modified progressive hedging with parallel computing is proposed. It is demonstrated through a 33-bus distribution system that the proposed algorithm has a speed approximately 15 times as fast as the state-of-art commercial software Gurobi when solving the model in 100 scenarios. For this case study, considering degradation penalty has been shown to extend energy storage lifespan by one year. [ABSTRACT FROM AUTHOR]

Exposure to long-term ambient air pollution is believed to have adverse effects on human health. However, the mechanisms underlying these impacts are poorly understood. DNA methylation, a crucial epigenetic modification, is susceptible to environmental factors and likely involved in these processes. We conducted a whole-genome bisulfite sequencing study on 120 participants from a highly polluted region (HPR) and a less polluted region (LPR) in China, where the HPR had much higher concentrations of five air pollutants (PM 2.5 , PM 10 , SO 2 , NO 2 , and CO) (fold difference 1.6 to 6.6 times; P value 1.80E-07 to 3.19E-23). Genome-wide methylation analysis revealed 371 DMRs in subjects from the two areas and these DMRs were located primarily in gene regulatory elements such as promoters and enhancers. Gene enrichment analysis showed that DMR-related genes were significantly enriched in diseases related to pulmonary disorders and cancers and in biological processes related to mitochondrial assembly and cytokine production. Further, HPR participants showed a higher mtDNA copy number. Of those identified DMRs, 15 were significantly correlated with mtDNA copy number. Finally, cytokine assay indicated that an increased plasma interleukin-5 level was associated with greater air pollution. Taken together, our findings suggest that exposure to long-term ambient air pollution can lead to alterations in DNA methylation whose functions relate to mitochondria and immune responses. Image 1 • We used whole-genome bisulfite sequencing to study the influence of air pollution on DNA methylation in blood leukocyte. • DNA methylation levels were compared between residents from two areas with distinct air quality in China. • Differentially methylated regions were enriched in gene regulatory elements. • Genes involved in mitochondrial function and immune response are preferentially impacted by air pollution. Summary: By comparing DNA methylation of subjects from two areas with distinct air quality in China, we identified differential methylation regions whose functions are mostly related to mitochondria and immune responses. [ABSTRACT FROM AUTHOR]

Highlights • Multi-physical CFD model is developed by considering Seebeck effect. • Thermoelectric currents and thermoelectric-magnetic effects during MSLBW are calculated. • The influence of TECs on weld pool dynamics is characterized. • Simulation data is validated by experimentally determined seam morphologies. Abstract Thermoelectric currents (TECs) caused by Seebeck effect were usually neglected in welding simulation. This paper characterizes the TECs and thermoelectric-magnetic phenomena during the magnetically supported laser beam welding (MSLBW) of thick aluminum (Al) alloy. The simulation is based on a computational fluid dynamic (CFD) model developed in three dimensions. The model considers multi-physical mechanisms including thermal transfer, solid–liquid (S/L) transition, molten metal convection, magnetohydrodynamics (MHD) and Seebeck effect. The computed TEC distribution in laser welding pool highly depends on welding time and temperature gradient. The large current densities occur near the weld pool edge and the vectors are opposite at both side of S/L interface. The maximum TEC density obtained in the stabilized weld pool is 2.14 × 106 A/m2, leading to a self-induced magnetic field of 2.27 × 10−3 T and a Lorentz force of 2.62 × 103 N/m3. The influences of TECs on weld pool dynamics are quite limited in LBW but notable in MSLBW. The inversion of MF direction leads to different Lorentz force distributions, weld pool dimensions and seam profiles. The simulation data agrees well with the experimental results. [ABSTRACT FROM AUTHOR]