Qiang Ma

Metasurfaces, composed of planar arrays of intricately designed meta-atom structures, possess remarkable capabilities in controlling electromagnetic waves in various ways. A critical aspect of metasurface design involves selecting suitable meta-atoms to achieve target functionalities such as phase retardation, amplitude modulation, and polarization conversion. Conventional design processes often involve extensive parameter sweeping, a laborious and computationally intensive task heavily reliant on designer expertise and judgement. Here, we present an efficient genetic algorithm assisted meta-atom optimization method for high-performance metasurface optics, which is compatible to both single- and multi-objective device design tasks. We first employ the method for a single-objective design task and implement a high-efficiency Pancharatnam-Berry phase based metalens with an average focusing efficiency exceeding 80% in the visible spectrum. We then employ the method for a dual-objective metasurface design task and construct an efficient spin-multiplexed structural beam generator. The device is capable of generating zeroth-order and first-order Bessel beams respectively under right-handed and left-handed circular polarized illumination, with associated generation efficiencies surpassing 88%. Finally, we implement a wavelength and spin co-multiplexed four-channel metahologram capable of projecting two spin-multiplexed holographic images under each operational wavelength, with efficiencies over 50%. Our work offers a streamlined and easy-to-implement approach to meta-atom design and optimization, empowering designers to create diverse high-performance and multifunctional metasurface optics.

Tuberculosis, a fatal infectious disease caused by Mycobacterium tuberculosis (M.tb), is difficult to treat with antibiotics due to drug resistance and short drug half-life. Phototherapy represents a promising alternative to antibiotics in combating M.tb. Exploring an intelligent material allowing effective tuberculosis treatment is definitely appealing, yet a significantly challenging task. Herein, an all-in-one biomimetic therapeutic nanoparticle featured by aggregation-induced second near-infrared emission, granuloma-targeting, and self-oxygenation is constructed, which can serve for prominent fluorescence imaging-navigated combined phototherapy toward tuberculosis. After camouflaging the biomimetic erythrocyte membrane, the nanoparticles show significantly prolonged blood circulation and increased selective accumulation in tuberculosis granuloma. Upon laser irradiation, the loading photosensitizer of aggregation-induced emission photosensitizer elevates the production of reactive oxygen species (ROS), causing M.tb damage and death. The delivery of oxygen to relieve the hypoxic granuloma microenvironment supports ROS generation during photodynamic therapy. Meanwhile, the photothermal agent, Prussian blue nanoparticles, plays the role of good photothermal killing effect on M.tb. Moreover, the growth and proliferation of granuloma and M.tb colonies are effectively inhibited in the nanoparticle-treated tuberculous granuloma model mice, suggesting the combined therapeutic effects of enhancing photodynamic therapy and photothermal therapy.

Nuclear factor-kappaB (NF-ĸB) plays a crucial role in both innate and adaptive immune systems, significantly influencing various physiological processes such as cell proliferation, migration, differentiation, survival, and stemness. The function of NF-ĸB in cancer progression and response to chemotherapy has gained increasing attention. This review highlights the role of NF-ĸB in inflammation control, biological mechanisms, and therapeutic implications in cancer treatment. NF-ĸB is instrumental in altering the release of inflammatory factors such as TNF-α, IL-6, and IL-1β, which are key in the regulation of carcinogenesis. Specifically, in conditions including colitis, NF-ĸB upregulation can intensify inflammation, potentially leading to the development of colorectal cancer. Its pivotal role extends to regulating the tumor microenvironment, impacting components such as macrophages, fibroblasts, T cells, and natural killer cells. This regulation influences tumorigenesis and can dampen anti-tumor immune responses. Additionally, NF-ĸB modulates cell death mechanisms, notably by inhibiting apoptosis and ferroptosis. It also has a dual role in stimulating or suppressing autophagy in various cancers. Beyond these functions, NF-ĸB plays a role in controlling cancer stem cells, fostering angiogenesis, increasing metastatic potential through EMT induction, and reducing tumor cell sensitivity to chemotherapy and radiotherapy. Given its oncogenic capabilities, research has focused on natural products and small molecule compounds that can suppress NF-ĸB, offering promising avenues for cancer therapy.

The emergence of monkeypox has become a global health threat after the COVID-19 pandemic. Due to the lack of available specifically treatment against MPV, developing an available vaccine is thus the most prospective and urgent strategy. Herein, a programmable macrophage vesicle based bionic self-adjuvanting vaccine (AM@AEvs-PB) is first developed for defending against monkeypox virus (MPV). Based on MPV-related antigen-stimulated macrophage-derived vesicles, the nanovaccine is constructed by loading the mature virion (MV)-related intracellular protein (A29L/M1R) and simultaneously modifying with the enveloped virion (EV) antigen (B6R), enabling them to effectively promote antigen presentation and enhance adaptive immune through self-adjuvant strategy. Owing to the synergistic properties of bionic vaccine coloaded MV and EV protein in defensing MPV, the activation ratio of antigen-presenting cells is nearly four times than that of single antigen in the same dose, resulting in stronger immunity in host. Notably, intramuscular injection uptake of AM@AEvs-PB demonstrated vigorous immune-protective effects in the mouse challenge attempt, offering a promising strategy for pre-clinical monkeypox vaccine development.

Hydrological models and drought indices based on simulation of soil moisture have been widely used in large-scale agricultural drought assessments. However, hydrological models often oversimplify crop modules and does not consider irrigation, crop growth, and water demand impacts. Therefore, in the present study, a coupled hydrological-crop growth model Variable Infiltration Capacity - Environmental Policy Integrated Climate (VIC-EPIC) was used to consider the impact of the irrigation process on drought and propose a crop water anomaly percentage index (CWAPI) based on the crop water demand and consumption processes. Identification and assessment methods of drought events were also evaluated. The validation results of the VIC-EPIC model showed that the correlation coefficients between the MODIS evapotranspiration and the simulated evapotranspiration at 37% merged grids were above 0.74. The correlation coefficient (0.79) of the CWAPI-simulated values and statistical values of drought area rates was greater than that (0.72) of soil moisture anomaly percentage index (SMAPI), indicating that the simulation of drought area rate based on CWAPI was more reasonable. After identifying regional drought events and comparing the identified characteristic values of these events with the average drought data of each city, it was found that SMAPI misjudged some regions with high hydraulic conductivity as severe drought regions. This limitation was overcome by CWAPI, which directly reflects the degree of crop water shortage and considers the impact of irrigation on drought. Agricultural drought occurs due to low soil water content, which is caused by rapid percolation of soil water and insufficient storage of local and irrigation water. This study of drought indices will help develop a more timely and comprehensive adaptive strategy to deal with droughts by considering the impacts of irrigation, crop growth, and water demand on drought.