Electrochemical Knocking-Down of Zn Metal Clusters into Single Atoms.

Single Atoms Catalysts (SACs) have emerged as a class of highly promising heterogeneous catalysts, where the traditional bottom-up synthesis approaches often encounter considerable challenges in relation to aggregation issues and poor stability. Consequently, achieving densely dispersed atomic species in a reliable and efficient manner remains a key focus in the field. Herein, we report a new facile electrochemical knock-down strategy for the formation of SACs, whereby the metal Zn clusters are transformed into single atoms. While a defect-rich substrate plays a pivotal role in capturing and stabilizing isolated Zn atoms, the feasibility of this novel strategy is demonstrated through a comprehensive investigation, combining experimental and theoretical studies. Furthermore, when studied in exploring for potential applications, the material prepared shows a remarkable improvement of 58.21% for the Li+ storage and delivers a capacity over 300 Wh kg-1 after 500 cycles upon the transformation of Zn clusters into single atoms.

Portable Mass Spectrometry for On-site Detection of Hazardous Volatile Organic Compounds via Robotic Extractive Sampling.

Various hazardous volatile organic compounds (VOCs) are frequently released into environments during accidental events that cause many hazards to ecosystems and humans. Therefore, rapid, sensitive, and on-site detection of hazardous VOCs is crucial to understand their compositions, characteristics, and distributions in complex environments. However, manual handling of hazardous VOCs remains a challenging task, because of the inaccessible environments and health risk. In this work, we designed a quadruped robotic sampler to reach different complex environments for capturing trace hazardous VOCs using a needle trap device (NTD) by remote manipulation. The captured samples were rapidly identified by portable mass spectrometry (MS) within minutes. Rapid detection of various hazardous VOCs including toxicants, chemical warfare agents, and burning materials from different environments was successfully achieved using this robot-MS system. On-site detection of 83 typical hazardous VOCs was examined. Acceptable analytical performances including low detection limits (at subng/mL level), good reproducibility (relative standard deviation (RSD) < 20%, n = 6), excellent quantitative ability (R2 > 0.99), and detection speed (within minutes) were also obtained. Our results show that the robot-MS system has excellent performance including safety, controllability, applicability, and robustness under dangerous chemical conditions.

Switch Volmer-Heyrovsky to Volmer-Tafel Pathway for Efficient Acidic Electrocatalytic Hydrogen Evolution by Correlating Pt Single Atoms with Clusters.

As cost-effective catalysts, platinum (Pt) single-atom catalysts (SACs) have attracted substantial attention. However, most studies indicate that Pt SACs in acidic hydrogen evolution reaction (HER) follow the slow Volmer-Heyrovsky (VH) mechanism instead of the fast kinetic Volmer-Tafel (VT) pathway. Here, this work propose that the VH mechanism in Pt SACs can be switched to the faster VT pathway for efficient HER by correlating Pt single atoms (SAs) with Pt clusters (Cs). Our calculations reveal that the correlation between Pt SAs and Cs significantly impacts the electronic structure of exposed Pt atoms, lowering the adsorption barrier for atomic hydrogen and enabling a faster VT mechanism. To validate these findings, this work purposely synthesize three catalysts: l-Pt@MoS2, m-Pt@MoS2 and h-Pt@MoS2 with low, moderate, and high Pt-loading, having different distributions of Pt SAs and Cs. The m-Pt@MoS2 catalyst with properly correlating Pt SAs and Cs exhibits outstanding performance with an overpotential of 47 mV and Tafel slope of 32 mV dec-1. Further analysis of the Tafel values confirms that the m-Pt@MoS2 sample indeed follows the VT reaction mechanism, aligning with the theoretical findings. This study offers a deep understanding of the synergistic mechanism, paving a way for designing novel-advanced catalysts.

Two-Phase Fermentation Systems for Microbial Production of Plant-Derived Terpenes.

Microbial cell factories, renowned for their economic and environmental benefits, have emerged as a key trend in academic and industrial areas, particularly in the fermentation of natural compounds. Among these, plant-derived terpenes stand out as a significant class of bioactive natural products. The large-scale production of such terpenes, exemplified by artemisinic acid-a crucial precursor to artemisinin-is now feasible through microbial cell factories. In the fermentation of terpenes, two-phase fermentation technology has been widely applied due to its unique advantages. It facilitates in situ product extraction or adsorption, effectively mitigating the detrimental impact of product accumulation on microbial cells, thereby significantly bolstering the efficiency of microbial production of plant-derived terpenes. This paper reviews the latest developments in two-phase fermentation system applications, focusing on microbial fermentation of plant-derived terpenes. It also discusses the mechanisms influencing microbial biosynthesis of terpenes. Moreover, we introduce some new two-phase fermentation techniques, currently unexplored in terpene fermentation, with the aim of providing more thoughts and explorations on the future applications of two-phase fermentation technology. Lastly, we discuss several challenges in the industrial application of two-phase fermentation systems, especially in downstream processing.

Dual-gradient Concentration Distribution in Sb-Cu Alloy Nanoarrays for Robust Sodium-ionStorage.

Alloy-type materials are attractive for anodes in sodium-ion batteries (SIBs) owing to their high theoretical capacities and overall performance. However, the accumulation of stress/strain during repeated cycling results in electrode pulverization, leading to rapid capacity decay and eventual disintegration, thus hindering their practical applications. Herein, we report a 3D coral-like Sb-Cu alloy nanoarray with gradient distribution of both elements. The array features a Sb-rich bottom and a Cu-rich top with increasing Sb and decreasing Cu concentrations from top to bottom. The former is the active component that provides the high capacity, whereas the latter serves as an inert additive that acts against volume variation. The gradual transition in composition within the electrode introduces a ladder-type volume expansion effect, facilitating a smooth distribution and effective release of stress, thereby ensuring the wanted mechanical stability and structural integrity. The as-developed nanoarray affords a high reversible capacity (460 mAh g-1 at 0.5 C), stable cycling (89% retention over 120 cycles at 1.0 C), and superior rate capability (354 mAh g-1 at 10 C). The concentration dual-gradient strategy paves a new pathway of designing alloy-type materials for SIBs.

Challenges and Opportunities in Preserving Key Structural Features of 3D-Printed Metal/Covalent Organic Framework.

Metal-organic framework (MOF) and covalent organic framework (COF) are a huge group of advanced porous materials exhibiting attractive and tunable microstructural features, such as large surface area, tunable pore size, and functional surfaces, which have significant values in various application areas. The emerging 3D printing technology further provides MOF and COFs (M/COFs) with higher designability of their macrostructure and demonstrates large achievements in their performance by shaping them into advanced 3D monoliths. However, the currently available 3D printing M/COFs strategy faces a major challenge of severe destruction of M/COFs' microstructural features, both during and after 3D printing. It is envisioned that preserving the microstructure of M/COFs in the 3D-printed monolith will bring a great improvement to the related applications. In this overview, the 3D-printed M/COFs are categorized into M/COF-mixed monoliths and M/COF-covered monoliths. Their differences in the properties, applications, and current research states are discussed. The up-to-date advancements in paste/scaffold composition and printing/covering methods to preserve the superior M/COF microstructure during 3D printing are further discussed for the two types of 3D-printed M/COF. Throughout the analysis of the current states of 3D-printed M/COFs, the expected future research direction to achieve a highly preserved microstructure in the 3D monolith is proposed.

Functions, accumulation, and biosynthesis of important secondary metabolites in the fig tree (Ficus carica).

Ficus carica is an economically important horticultural plant. Due to its abundant secondary metabolites, F. carica has gained interest for its applications in medicine and as a nutritional supplement. Both external and internal factors affect the accumulation of secondary metabolites in F. carica. The assembly of the F. carica genome has facilitated functional analysis of key genes and transcription factors associated with the biosynthesis of secondary metabolites, particularly anthocyanin. In this review, we summarize the various types and functions of secondary metabolites, with a particular focus on flavonoids, coumarins, and terpenes. We also explore the factors influencing their biosynthesis and accumulation, including varieties, tissue, environmental factors (e.g., light), stresses (e.g., high temperature, low temperature, drought, nutrient deficiencies, salinity), hormonal treatments, and developmental factors. Furthermore, we discuss the involvement of structural genes and transcription factors in the biosynthesis of secondary metabolites, specifically anthocyanin and furanocoumarins, knowledge of which will promote the breeding and genetic engineering of novel F. carica varieties.

Coordination-Driven Templated Synthesis of Hierarchically Porous Zeolitic Imidazolate Frameworks for Cascade Enzyme Cycle Amplification Coupled Immunoassay.

Although hierarchically porous zeolitic imidazolate frameworks (HPZIFs) not only inherit the intrinsic architectural and chemical stabilities of their microporous counterparts but also afford open space for the efficient mass diffusion of the macromolecules involved, their rational design and construction are still challenging. Herein, HPZIFs with tailorable pore sizes ranging from 18 to 54 nm were successfully fabricated by using a newly developed soft-template-directed strategy. Our success rooted in the fact that the screened PS81-PVP44-PEO113 triblock copolymer could effectively coordinate with the metal precursor for the directed crystallization of ZIFs along surfactant assemblies. The advantages of continuous large pores and open structures in such HPZIFs were fully taken into account to serve as a bioreactor for the efficient immunoassay. The expanded large pores provided not only a significantly vast surface area to enhance the density of capture antibodies but also enough space for accommodating multiple conjugated biomolecules in one pore channel. In combination with a cascade enzyme cycle amplification strategy, a model biomarker of prostate-specific antigen (PSA) at the femtomolar level was checked with a limit of detection of 92 fM using the developed immunosensor. Specific screening on patients with prostate cancer or even benign prostatic hyperplasia was exemplified through accurately quantifying small changes of PSA concentration in clinical serum samples, prefiguring the great potential of the developed HPZIF-8 immunosensor platform for the early monitoring and diagnostics of diseases.

Traditional and non-traditional lipid parameters as risk factors for sudden sensorineural hearing loss.

OBJECTIVE: The purpose was to explore the effects of traditional and non-traditional lipid parameters on Sudden Sensorineural Hearing Loss (SSNHL). METHODS: The study included 452 patients diagnosed with SSNHL, among whom 206 patients had a level of hearing improvement ≥10 dB after one month of follow-up. A propensity score-matched (2:1) control group was used. Conditional and unconditional logistic regression were used to analyze the risk factors for SSNHL. RESULTS: Patients with SSNHL had a higher risk of concomitant hypertension and elevated atherosclerogenic lipid levels, with apolipoprotein B and apolipoprotein E identified as independent risk factors for the onset of SSNHL. Additionally, the Lipid Comprehensive Index (LCI) was an independent risk factor for the degree of hearing loss. A positive linear correlation was revealed between triglyceride, non-high-density lipoprotein cholesterol, atherogenic index, Castelli risk index, atherogenic index of plasma, LCI and hearing loss. However, no linear relationship was observed between hearing gain and any lipid parameters. When Total Cholesterol (TC) was in the range of borderline high, the treatment effect was the best. However, the statistical significance disappeared upon adjusting for confounding factors. CONCLUSION: Patients with SSNHL exhibited markedly dysregulated lipid metabolism. Elevated serum lipid levels may be a causative factor in auditory impairment and can influence the extent of hearing loss. Promptly improving cochlear microcirculation may benefit patients with borderline elevated TC.

PEGA: A Privacy-Preserving Genetic Algorithm for Combinatorial Optimization.

Evolutionary algorithms (EAs), such as the genetic algorithm (GA), offer an elegant way to handle combinatorial optimization problems (COPs). However, limited by expertise and resources, most users lack the capability to implement EAs for solving COPs. An intuitive and promising solution is to outsource evolutionary operations to a cloud server, however, it poses privacy concerns. To this end, this article proposes a novel computing paradigm called evolutionary computation as a service (ECaaS), where a cloud server renders evolutionary computation services for users while ensuring their privacy. Following the concept of ECaaS, this article presents privacy-preserving genetic algorithm (PEGA), a privacy-preserving GA designed specifically for COPs. PEGA enables users, regardless of their domain expertise or resource availability, to outsource COPs to the cloud server that holds a competitive GA and approximates the optimal solution while safeguarding privacy. Notably, PEGA features the following characteristics. First, PEGA empowers users without domain expertise or sufficient resources to solve COPs effectively. Second, PEGA protects the privacy of users by preventing the leakage of optimization problem details. Third, PEGA performs comparably to the conventional GA when approximating the optimal solution. To realize its functionality, we implement PEGA falling in a twin-server architecture and evaluate it on two widely known COPs: 1) the traveling Salesman problem (TSP) and 2) the 0/1 knapsack problem (KP). Particularly, we utilize encryption cryptography to protect users' privacy and carefully design a suite of secure computing protocols to support evolutionary operators of GA on encrypted chromosomes. Privacy analysis demonstrates that PEGA successfully preserves the confidentiality of COP contents. Experimental evaluation results on several TSP datasets and KP datasets reveal that PEGA performs equivalently to the conventional GA in approximating the optimal solution.

Analysis of Ginkgo biloba Root Exudates and Inhibition of Soil Fungi by Flavonoids and Terpene Lactones.

Ginkgo biloba is abundant in secondary metabolites, including flavonoids and terpenoids. While the majority of research has focused on the role of these compounds in disease resistance, their specific contribution to pathogen defense has been rarely explored. In this study, we collected root exudates from hydroponically cultivated ginkgo seedlings and conducted a metabolomic analysis. We identified several primary metabolites mainly comprising amino acids and nucleotides, while secondary metabolites consisted of various compounds, including bioactive compounds such as flavonoids and terpenoids. Focusing on the secondary metabolites with relatively higher abundance in the exudates, we selected a mixture of flavonoids and terpenoids for in vitro inhibition experiments against two soil-borne fungal pathogens, Fusarium oxysporum f. sp. cucumerinum that causes cucumber wilt and Rhizoctonia solani AG-8 that causes wheat root rot. The results indicated that the growth rate of both fungus cells was significantly reduced with the increasing concentration of the flavonoid and terpenoid mixture extracted from ginkgo and was completely inhibited at a concentration of 5 mg/mL. Further experiments revealed that this mixture of flavonoids and terpenoids had a destructive effect on the cellular structure of both fungi, thereby reducing cell viability and achieving an antifungal effect. These findings provide a foundation for further research into the use of ginkgo extracts in biological control.

DefendFL: A Privacy-Preserving Federated Learning Scheme Against Poisoning Attacks.

Federated learning (FL) has become a popular mode of learning, allowing model training without the need to share data. Unfortunately, it remains vulnerable to privacy leakage and poisoning attacks, which compromise user data security and degrade model quality. Therefore, numerous privacy-preserving frameworks have been proposed, among which mask-based framework has certain advantages in terms of efficiency and functionality. However, it is more susceptible to poisoning attacks from malicious users, and current works lack practical means to detect such attacks within this framework. To overcome this challenge, we present DefendFL, an efficient, privacy-preserving, and poisoning-detectable mask-based FL scheme. We first leverage collinearity mask to protect users' gradient privacy. Then, cosine similarity is utilized to detect masked gradients to identify poisonous gradients. Meanwhile, a verification mechanism is designed to detect the mask, ensuring the mask's validity in aggregation and preventing poisoning attacks by intentionally changing the mask. Finally, we resist poisoning attacks by removing malicious gradients or lowering their weights in aggregation. Through security analysis and experimental evaluation, DefendFL can effectively detect and mitigate poisoning attacks while outperforming existing privacy-preserving detection works in efficiency.

The visual stimulation in disorders of consciousness.

Severe brain damage usually leads to disorders of consciousness (DOC), which include coma, unresponsive wakefulness syndrome (UWS) and a minimally conscious state (MCS). Visual stimulation is widely used, especially in the diagnosis and treatment and treatment of DOC. Researchers have indicated that tests based on visual stimulation including visual pursuit, when used in conjunction with the Coma Recovery Scale-Revised, are able to differentiate between UWS from an MCS. Recently, targeting patients' circadian rhythms has been proposed to be a possible treatment target for DOC. Indeed, light therapy has been applied in some other fields, including treating seasonal affective disorder, sleep problems, and Parkinson's disease. However, at present, although visual stimulation and light therapy are frequently used in DOC, there is still no international unified standard. Therefore, we recommend the development of an international consensus in regard to the definitions, operational criteria and assessment procedures of visual stimulation and light therapy. This review combines visual stimulation, circadian rhythm recovery, and light therapy in DOC patients and presents the mechanisms and current advances in applications related to light therapy and visual stimulation in an attempt to provide additional ideas for future research and treatment of DOC.