As a global-optimized and naturally inspired algorithm, particle swarm optimization (PSO) is characterized by its high quality and easy application in practical optimization problems. However, PSO has some obvious drawbacks, such as early convergence and slow convergence speed. Therefore, we introduced some appropriate improvements to PSO and proposed a novel chaotic PSO variant with arctangent acceleration coefficient (CPSO-AT). A total of 10 numerical optimization functions were employed to test the performance of the proposed CPSO-AT algorithm. Extensive contrast experiments were conducted to verify the effectiveness of the proposed methodology. The experimental results showed that the proposed CPSO-AT algorithm converges quickly and has better stability in numerical optimization problems compared with other PSO variants and other kinds of well-known optimal algorithms.

The study of molecular mechanisms at the single-cell level holds immense potential for enhancing immunotherapy and understanding neuroinflammation and neurodegenerative diseases by identifying previously concealed pathways within a diverse range of paired cells. However, existing single-cell pairing platforms have limitations in low pairing efficiency, complex manual operation procedures, and single-use functionality. Here, we report a multiparametric cellular immunity analysis by a modular acoustofluidic platform: CIAMAP. This platform enables users to efficiently sort and collect effector-target (i.e., NK92-K562) cell pairs and monitor the real-time dynamics of immunological response formation. Furthermore, we conducted transcriptional and protein expression analyses to evaluate the pathways that mediate effector cytotoxicity toward target cells, as well as the synergistic effect of doxorubicin on the cellular immune response. Our CIAMAP can provide promising building blocks for high-throughput quantitative single-cell level coculture to understand intercellular communication while also empowering immunotherapy by precision analysis of immunological synapses.

Therapeutic apheresis aims to selectively remove pathogenic substances, such as antibodies that trigger various symptoms and diseases. Unfortunately, current apheresis devices cannot handle small blood volumes in infants or small animals, hindering the testing of animal model advancements. This limitation restricts our ability to provide treatment options for particularly susceptible infants and children with limited therapeutic alternatives. Here, we report our solution to these challenges through an acoustofluidic-based therapeutic apheresis system designed for processing small blood volumes. Our design integrates an acoustofluidic device with a fluidic stabilizer array on a chip, separating blood components from minimal extracorporeal volumes. We carried out plasma apheresis in mouse models, each with a blood volume of just 280 μL. Additionally, we achieved successful plasmapheresis in a sensitized mouse, significantly lowering preformed donor-specific antibodies and enabling desensitization in a transplantation model. Our system offers a new solution for small-sized subjects, filling a critical gap in existing technologies and providing potential benefits for a wide range of patients.

Particle swarm optimization (PSO) is a common metaheuristic algorithm. However, when dealing with practical engineering structure optimization problems, it is prone to premature convergence during the search process and falls into a local optimum. To strengthen its performance, combining several ideas of the differential evolution algorithm (DE), a dynamic probability mutation particle swarm optimization with chaotic inertia weight (CWDEPSO) is proposed. The main improvements are achieved by improving the parameters and algorithm mechanism in this paper. The former proposes a novel inverse tangent chaotic inertia weight and sine learning factors. Besides, the scaling factor and crossover probability are improved by random distributions, respectively. The latter introduces a monitoring mechanism. By monitoring the convergence of PSO, a developed mutation operator with a more reliable local search capability is adopted and increases population diversity to help PSO escape from the local optimum effectively. To evaluate the effectiveness of the CWDEPSO algorithm, 24 benchmark functions and two groups of engineering optimization experiments are used for numerical and engineering optimization, respectively. The results indicate CWDEPSO offers better convergence accuracy and speed compared with some well-known metaheuristic algorithms.

Gradient biomaterials that exhibit spatially varying physical, chemical, or biological properties can be used in various applications such as tissue engineering, organoid development, mechanobiology, and spatially controlled drug delivery. However, current fabrication methods often suffer from limited gradient precision, restricted material compatibility, and poor reproducibility. Here, we introduced gradient regulation via acoustofluidic dynamic engineering (GRADE), a programmable system to generate high-fidelity gradient biomaterials across different material systems. By incorporating focused interdigital transducers with the pulsed surface acoustic wave actuation, GRADE can achieve tunable and directional acoustic streaming (0 to 22 millimeters per second), which allows accurate regulation of the gradient magnitude and length. Its open microchannel design enables nondestructive extraction of centimeter-scale gradients and supports device reuse, enhancing practicality and scalability. In contrast to magnetic or electrospinning techniques that are limited to specific material types, the GRADE approach supports composition-independent fluid manipulation of a diverse group of biomaterials and cross-linking methods, thus providing greater versatility and translational potential. Furthermore, we demonstrate stiffness-dependent mechanosensation in stem cells cultured on customized gradient substrates, which validates the platform’s usability. The experimental results show that GRADE has the ability to uncover mechanobiological responses in physiologically relevant contexts. All these results establish GRADE as a powerful and versatile platform for gradient biomaterial fabrication. It shows broad potential to advance both fundamental research and translational biomedical applications.

Mechanomodulation, the process of altering cellular behavior through applied mechanical forces, plays a critical role in physiological processes and has substantial implications for cancer therapy, immunology, and drug development. However, precise and efficient stimulation of nonadherent cells remains a major challenge, limiting the investigation of mechanotransduction pathways and the development of targeted therapeutics. Here, we developed an acoustofluidic platform named Suspension-cell Targeted Response to Excitation via Acoustofluidic Mechanomodulation (STREAM) to enable precise, high-throughput stimulation of suspension cells. STREAM accomplishes this using 101.14-megahertz high-frequency surface acoustic waves to deliver controlled mechanical stimulation at a throughput of 500,000 cells per minute. STREAM modulates intracellular calcium ion (Ca ²⁺ ) signaling by activating mechanosensitive ion channels, triggering mitochondrial membrane disruption and tunable K562 leukemia cell apoptosis rates from 5.15 to 47.1%. STREAM provides a scalable, precise tool for studying mechanotransduction in suspension cells, with broad applications in cancer research, immunotherapy, and high-throughput drug screening.