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BBX genes play an important role in plant growth, development, and stress response. However, systematic analysis of BBX gene family regarding resistance to fungal infections has not been previously conducted in Chrysanthemum. In this study, a systematic analysis of the BBX gene family was performed, and its function in defense of necrotrophic fungus Alternaria sp. has been probed into through publicly available genome and RNA-seq data of Chrysanthemum after Alternaria sp. infection. The systematic analyses included identifying the BBX gene family in Chrysanthemum, their evolutionary relationships, conserved domains, motifs, gene structure, cis -acting elements, and collinearity. Based on the RNA-seq data analyses and expressional pattern, CmBBX32 was selected as a candidate gene for further investigation because it responded continuously to the infection and up-regulated expression when Chrysanthemum was inoculated with Alternaria sp. Gene expression analysis showed the expression of CmBBX32 increased sharply during the infection process, and was highest in flowers. Besides, virus-induced gene silencing (VIGS) of CmBBX32 in Chrysanthemum reduced the resistance to Alternaria sp. infection, as evidenced by phenotypic analysis of infection symptoms, microscopic examination of spore germination and hyphal growth, as well as quantitative analysis of the marker gene associated with the SA and JA defense pathways. Overall, the data generated in this study should form the basis for future functional characterizations of BBX genes in Chrysanthemum, especially regarding the resistance to biological stress in Chrysanthemum.

The development of efficient and low-cost electrocatalysts for the oxygen evolution reaction (OER) is critical for improving the efficiency of water electrolysis. Here, we report a strategy using Fe substitution to enable the inactive spinel CoAl 2 O 4 to become highly active and superior to the benchmark IrO 2 . The Fe substitution is revealed to facilitate surface reconstruction into active Co oxyhydroxides under OER conditions. It also activates deprotonation on the reconstructed oxyhydroxide to induce negatively charged oxygen as an active site, thus significantly enhancing the OER activity of CoAl 2 O 4 . Furthermore, it promotes the pre-oxidation of Co and introduces great structural flexibility due to the uplift of the oxygen 2 p levels. This results in the accumulation of surface oxygen vacancies along with lattice oxygen oxidation that terminates as Al 3+ leaches, preventing further reconstruction. We showcase a promising way to achieve tunable electrochemical reconstruction by optimizing the electronic structure for low-cost and robust spinel oxide OER catalysts. The development of efficient and low-cost electrocatalysts for the oxygen evolution reaction is critical for improving the efficiency of water electrolysis. Here, the inactive spinel CoAl 2 O 4 is activated via iron substitution to achieve high activity and stability for water oxidation.

HighlightsThis review highlights pathogenesis and clinical challenges of sepsis.Advantages of different types of nanoplatforms are presented, and the rationality of nanoplatforms in sepsis management is analyzed.Advances of nanoplatforms in diagnosis and therapy of sepsis are systematically summarized, and ongoing challenges and future perspectives are discussed.Sepsis, a highly life-threatening organ dysfunction caused by uncontrollable immune responses to infection, is a leading contributor to mortality in intensive care units. Sepsis-related deaths have been reported to account for 19.7% of all global deaths. However, no effective and specific therapeutic for clinical sepsis management is available due to the complex pathogenesis. Concurrently eliminating infections and restoring immune homeostasis are regarded as the core strategies to manage sepsis. Sophisticated nanoplatforms guided by supramolecular and medicinal chemistry, targeting infection and/or imbalanced immune responses, have emerged as potent tools to combat sepsis by supporting more accurate diagnosis and precision treatment. Nanoplatforms can overcome the barriers faced by clinical strategies, including delayed diagnosis, drug resistance and incapacity to manage immune disorders. Here, we present a comprehensive review highlighting the pathogenetic characteristics of sepsis and future therapeutic concepts, summarizing the progress of these well-designed nanoplatforms in sepsis management and discussing the ongoing challenges and perspectives regarding future potential therapies. Based on these state-of-the-art studies, this review will advance multidisciplinary collaboration and drive clinical translation to remedy sepsis.

High-rate battery-type cathode materials have attracted wide attention for advanced battery-supercapacitor hybrid (BSH) devices. Herein, a core-shell structure of the hollow mesoporous carbon spheres (HMCS) supported NiSe 2 nanosheets (HMCS/NiSe 2 ) is constructed through two-step reactions. The HMCS/NiSe 2 shows a max specific capacity of 1,153.5 C·g −1 at the current density of 1 A·g −1 , and can remain at 774.5 C·g −1 even at 40 A·g −1 (the retention rate as high as 67.1%) and then the HMCS/NiSe 2 electrode can keep 80.5% specific capacity after 5,000 cycles at a current density of 10 A·g −1 . Moreover, the density functional theory (DFT) calculation confirmed that the introduction HMCS into NiSe 2 made adsorption/desorption of OH − easier, which can achieve higher rate capability. The HMCS/NiSe 2 //6 M KOH//HMCS hybrid device has energy density of 47.15 Wh·kg −1 and power density of 801.8 W·kg −1 . This work provides a feasible electrode material with a high rate and its preparation method for high energy density and power density energy storage devices.

Antibiotics with multiple mechanisms of action and broad-spectrum are urgently required to combat the growing health threat posed by resistant pathogenic microorganisms. Combining computational and medicinal chemistry tools, we used the structure of human α-defensin 5 (HD5) to design a class of peptidomimetic antibiotics with improved activity against both gram-negative and gram-positive bacteria. The most promising lead, compound 10, showed potent killing of multiple drug-resistant gram-negative bacteria isolated from patients. Compound 10 exhibited a multiplex mechanism of action through targeting membrane components—outer membrane protein A and lipopolysaccharide, as well as a potential intracellular target—70S ribosome, thus causing membrane perturbation and inhibition of protein synthesis. In vivo efficacy, stability, and safety of compound 10 were also validated. This human defensin-inspired synthetic peptidomimetic could help solve the serious problem of drug resistance to conventional antibiotics.

Host defense peptides (HDPs) have emerged as a novel therapeutic paradigm for wound management; however, their clinical applications remain a challenge owing to their poor pharmacological properties and lack of suitable pharmaceutical formulations. Nanodefensin (ND), a nanoengineered human α-defensin 5 (HD5), has shown improved pharmacological properties relative to the parent compound. In this study, we engineered a nanodefensin-encased hydrogel (NDEFgel), investigated the effects of NDEFgel on wound healing, and elucidated underlying mechanisms. ND was chemically synthesized and tested functions by antimicrobial and scratch assays and western blotting. Different NDEFgels were evaluated by characterizations including degradation, drug release and antimicrobial activity. In full-thickness excisional murine models, the optimal NDEFgel was directly applied onto wound sites, and the efficacy was assessed. Moreover, the underlying mechanisms of pro-regenerative effect developed by NDEFgel were also explored. Apart from bactericidal effects, ND modulated fibroblast behaviors by promoting migration and differentiation. Among the tested hydrogels, the Pluronic F127 (Plu) hydrogel represented the most desirable carrier for ND delivery owing to its favorable controlled release and compatibility with ND. Local treatment of NDEFgel on the wound bed resulted in accelerated wound regeneration and attenuated bacterial burden. We further demonstrated that NDEFgel therapy significantly upregulated genes related to collagen deposition and fibroblasts, and increased the expression of myofibroblasts and Rac1. We therefore found that Rac1 is a critical factor in the ND-induced modulation of fibroblast behaviors through a Rac1-dependent cytoskeletal rearrangement. Our results indicate that NDEFgel may be a promising dual-action therapeutic option for advanced wound management in the future.

Aqueous rechargeable Zn//MnO 2 batteries have attracted extensive research interest owing to their low cost and high energy density. However, the slow reaction kinetics, the disproportionation of the MnO 2 cathode, and the irreversible phase transition mechanism considerably restrict their development. Here, we chose Mo-doped α-MnO 2 (Mo–MnO 2 ) as the cathode material and proposed a stable N–H⋯O bond-reinforced interaction formed via NH 4 + intercalation to stabilize the 2 × 2 tunnel structure of Mo–MnO 2 . Theoretical and experimental studies were conducted to demonstrate the performance of the cathode. Mn 3+ dissolution was effectively inhibited, and lattice distortion did not occur during the proton insertion/removal process, which further improved the cyclic stability of the cathode. Specifically, at a current density of 100 mA g −1 , the Mo–MnO 2 cathode exhibited a specific capacity of 265.2 mA h g −1 , the energy density was 364.3 W h kg −1 , and the cathode exhibited excellent cyclic stability. At a current density of 2.0 A g −1 , the specific capacity was 95.2% after 1000 cycles. This work provides further insight into the bond interaction between nonmetallic cations in the main materials of electrodes and contributes to the construction of aqueous-based zinc-ion batteries with high energy density and long-term cycling capability.

The development of efficient and low-cost electrocatalysts for the oxygen evolution reaction (OER) is critical for improving the efficiency of water electrolysis. Here, we report a strategy using Fe substitution to enable the inactive spinel CoAl2O4 to become highly active and superior to the benchmark IrO2. The Fe substitution is revealed to facilitate surface reconstruction into active Co oxyhydroxides under OER conditions. It also activates deprotonation on the reconstructed oxyhydroxide to induce negatively charged oxygen as an active site, thus significantly enhancing the OER activity of CoAl2O4. Furthermore, it promotes the pre-oxidation of Co and introduces great structural flexibility due to the uplift of the oxygen 2p levels. This results in the accumulation of surface oxygen vacancies along with lattice oxygen oxidation that terminates as Al3+ leaches, preventing further reconstruction. We showcase a promising way to achieve tunable electrochemical reconstruction by optimizing the electronic structure for low-cost and robust spinel oxide OER catalysts.

Class-Incremental Learning (CIL) requires models to continually acquire knowledge of new classes without forgetting old ones. Despite Pre-trained Models (PTMs) have shown excellent performance in CIL, catastrophic forgetting still occurs as the model learns new concepts. Existing work seeks to utilize lightweight components to adjust the PTM, while the forgetting phenomenon still comes from {\\em parameter and retrieval} levels. Specifically, iterative updates of the model result in parameter drift, while mistakenly retrieving irrelevant modules leads to the mismatch during inference. To this end, we propose MOdel Surgery (MOS) to rescue the model from forgetting previous knowledge. By training task-specific adapters, we continually adjust the PTM to downstream tasks. To mitigate parameter-level forgetting, we present an adapter merging approach to learn task-specific adapters, which aims to bridge the gap between different components while reserve task-specific information. Besides, to address retrieval-level forgetting, we introduce a training-free self-refined adapter retrieval mechanism during inference, which leverages the model's inherent ability for better adapter retrieval. By jointly rectifying the model with those steps, MOS can robustly resist catastrophic forgetting in the learning process. Extensive experiments on seven benchmark datasets validate MOS's state-of-the-art performance. Code is available at: https://github.com/sun-hailong/AAAI25-MOS

Class-Incremental Learning (CIL) requires models to continually acquire knowledge of new classes without forgetting old ones. Despite Pre-trained Models (PTMs) have shown excellent performance in CIL, catastrophic forgetting still occurs as the model learns new concepts. Existing work seeks to utilize lightweight components to adjust the PTM, while the forgetting phenomenon still comes from {\\em parameter and retrieval} levels. Specifically, iterative updates of the model result in parameter drift, while mistakenly retrieving irrelevant modules leads to the mismatch during inference. To this end, we propose MOdel Surgery (MOS) to rescue the model from forgetting previous knowledge. By training task-specific adapters, we continually adjust the PTM to downstream tasks. To mitigate parameter-level forgetting, we present an adapter merging approach to learn task-specific adapters, which aims to bridge the gap between different components while reserve task-specific information. Besides, to address retrieval-level forgetting, we introduce a training-free self-refined adapter retrieval mechanism during inference, which leverages the model's inherent ability for better adapter retrieval. By jointly rectifying the model with those steps, MOS can robustly resist catastrophic forgetting in the learning process. Extensive experiments on seven benchmark datasets validate MOS's state-of-the-art performance. Code is available at: https://github.com/sun-hailong/AAAI25-MOS