荆楚理工学院

Abstract Selenium (Se) biofortification in forage tree species offers a sustainable strategy to improve nutritional quality. This study investigated the physiological and molecular responses of Broussonetia papyrifera, a high-biomass woody species, to exogenous selenite (Na2SeO3) and selenate (Na2SeO4). Low Se concentrations (≤ 0.4 mM) significantly enhanced plant growth, while higher concentrations (0.8 mM), especially Na2SeO4, inhibited biomass accumulation in a dose-dependent manner. Both forms of Se substantially increased foliar Se content, with Na2SeO4 showing higher uptake efficiency. Genome-wide screening identified four sulfate/Na2SeO4 assimilation-related genes including ATP sulfurylase 1 (BpAPS1), BpAPS2, adenosine 5′-phosphosulfate reductase (BpAPR1), and BpAPR2. Phylogenetic analyses confirmed the evolutionary conservation of these proteins, which were localized to the chloroplasts. Tissue-specific expression patterns revealed a positive correlation between transcript levels of BpAPS1, BpAPR1, and BpAPR2 and Se content, while BpAPS2 expression was inversely correlated, indicating functional divergence. Compared to wild-type (WT) plants, transgenic Arabidopsis thaliana lines overexpressing these genes accumulated 1.27- to 1.60-fold more Se under Na2SeO4 stress, accompanied by coordinated upregulation of key endogenous Se metabolism genes like AtAPS, AtAPR, S-adenosylmethionine carriers 3 (AtSAM), homocysteine S-methyltransferase (AtHMT), methylselenol methyltransferase (AtMMT), suggesting enhanced Se assimilation and detoxification capacity. Collectively, these findings clarify the functional roles of the APS and APR gene families in Se uptake, assimilation, and detoxification in a woody crop, highlighting potential genetic targets for Se biofortification.

Based on density functional theory, the structure, mechanical, optoelectronic, kinetic, thermodynamic and hydrogen storage properties of cubic A2CuH6 (A=Li, Na, K) double perovskites are studied. The lattice constants of Li2CuH6, Na2CuH6, and K2CuH6 are 6.32, 7.07, and 7.98 & Aring;, respectively. The B/G values indicate that Li2CuH6 and K2CuH6 exhibit ductility, while Na2CuH6 exhibits brittleness. Electronic properties reveal that A2CuH6 (A=Li, Na, K) compounds have metallic nature. The optical properties of A2CuH6 show that Li2CuH6 and K2CuH6 crystals have high dielectric constants, which is beneficial for their applications as hydrogen storage. Importantly, A2CuH6 (A=Li, Na, K) materials were confirmed for their structural, dynamic, thermodynamic, and mechanical stability. Gravimetric hydrogen densities (GHD) of Li2CuH6, Na2CuH6, and K2CuH6 are 7.25, 5.23, and 4.09 wt%, respectively. The volumetric hydrogen storage capacities of Li2CuH6, Na2CuH6, and K2CuH6 are 159.06, 113.77, and 79.11 g & sdot;H2/L, respectively. Therefore, Li2CuH6 owns the highest gravimetric and volumetric hydrogen storage capacities among these compounds. This study provides a new option for designing novel copper-based hydrogen storage materials.

Electrocatalytic nitrate reduction reaction (NO3RR) is a promising strategy for converting nitrate (NO3- ) pollutants into valuable ammonia (NH3), and catalyst is widely recognized as the most crucial factor influencing this process. In this work, metal-organic frameworks (MOFs) are synthesized using Cu and 1,3,5-benzenetricarboxylic acid (BTC) for NO3RR, in which intentional coordination defects are fabricated to improve their electrocatalytic activity. Compared to conventional MOF (Cu-BTC), MOF with coordination defects (Cu-BTC-D) shows lower crystallinity and higher catalytic performance. Cu-BTC-D efficiently overcomes the kinetic barriers of NO3RR, achieving a NH3 Faradaic efficiency of 92% and a NH3 yield of 13.06 mg h-1 cm-2 at -0.7 V (vs. RHE), superior to Cu-BTC. Mechanism research proves that the increased electrochemically active surface area, reduced charge transfer resistance and enhanced reaction kinetics are responsible for the enhanced performance of Cu-BTC-D. Meanwhile, Cu-BTC-D also retains satisfactory stability. Experimental results and density functional theory (DFT) conclusions reveal that the defect engineering strategy of Cu-BTC improves the conversion efficiency of NO3-and NH3 yield for NO3RR, which provides a sustainable approach for nitrogen-containing wastewater treatment and nitrogen resource recovery.

In evolutionary algorithms, premature convergence often arises from overexploitation of locally crowded regions. To address this, we propose IKUN (A Mean-FIeld Game Theoretic KD-Tree Density GUided Swarm OptimizatioN Mechanism), a general-purpose enhancement that integrates mean-field game theory with KD-tree-based density estimation to guide population dynamics through distribution-aware potential feedback. Each individual is modeled as an agent in a discrete-time mean-field game, optimizing an augmented objective combining fitness with a historical crowding penalty. The density-aware potential is computed by querying a KD-tree recording recent solution points within a sliding window, enabling efficient local occupancy estimation without additional function evaluations. By penalizing densely populated, low-quality regions while encouraging exploration of sparse areas, IKUN delays premature convergence. The mechanism is embedded into four representative algorithms—PSO, DE, JADE, and GA—demonstrating strong generalizability. Experiments on the CEC-2022 benchmark suite confirm consistent improvements in optimization quality, robustness, and global search capability; the KD-tree overhead is negligible whenever objective evaluations dominate the total cost, as is typical in real-world applications. Additionally, when applied as an evolutionary feature selection component for extreme learning machine classifiers on six public datasets, IKUN yields more compact feature subsets with equal or higher accuracy. The mechanism is lightweight, theoretically grounded, and broadly applicable as a plug-in enhancement to existing population-based optimizers. Code is available at https://github.com/junbolian/IKUN-Mechanism.

Photosensitizers are susceptible to interference from the biological internal environment, which largely restricts the clinical application of photodynamic therapy. For instance, most existing photosensitizers tend to aggregate in the biological environment, resulting in a decrease in reactive oxygen species yield; their therapeutic efficacy is unsatisfactory in hypoxic tumor environments; they are difficult to accumulate effectively in tumor sites and cannot accurately distinguish between tumors and healthy tissues. To address these issues, this review systematically elaborates on a series of optimization strategies, including improving the intersystem crossing efficiency of photosensitizers through molecular engineering, endowing them with aggregation-induced emission properties, developing type I photosensitizers, and functionalizing photosensitizers by modifying biological proteins, targeting groups, or combining with nanoengineering, aiming to enhance the efficiency of photodynamic therapy. By summarizing the latest research breakthroughs, innovative methods, and emerging applications in this field, the review provides practical solutions and broad application prospects for photodynamic therapy, which is expected to promote the clinical translation and application of photosensitizers.