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Exosomes have been perceived as promising biomarkers for noninvasive cancer diagnosis and treatment monitoring. However, the sensitive and accurate quantification and phenotyping of exosomes remains challenging. Herein, a versatile electrochemiluminescence (ECL) aptasensor was proposed for the sensitive analysis of tumorous exosomes. Specifically, a ternary nanohybrid (Ru-HAuTiO2), by covalently linking ECL luminophore Ru(dcbpy)32+with gold nanoparticles (AuNPs)-decorated hollow urchin-like TiO2(HTiO2), was ingeniously designed as a highly luminescent and self-enhanced ECL nanoemitter. Notably, the porous HTiO2played an “all-rounder” role, including the carrier for ECL luminophores and AuNPs, coreaction accelerator, and specific exosome capturing scaffold through Ti–phosphate coordination interaction. On the other hand, a polydopamine modified covalent organic framework (PDA@COF) was employed as a quencher to remarkably attenuate the ECL of Ru-HAuTiO2through a dual-quenching mechanism, and further labeled with a specific aptamer (Apt) of exosomal surface protein. Based on forming a Ru-HAuTiO2/exosome/Apt-PDA@COF sandwich structure on the electrode, a “signal on–off” ECL platform for tumorous exosomes was constructed, realizing sensitive detection within the range of 3.1 × 103particles/mL to 1 × 108particles/mL and a low limit of detection of 1.41 × 103particles/mL, achieving phenotypic profiling of surface proteins on different tumorous exosomes. This work provides a promising alternative method for the detection and analysis of exosomes.

Hybrid supramolecular trimetallic halides with a double-shell clathrate structure belong to a type of functional material with complex compositions and wide tunability. The double-shell structure is generally composed of a crown ether molecule sandwiched between different metal halide units. Here, we synthesize six new hybrid trimetallic halides and their solid solutions with the general formula [(A18C6)3MX4][BX4] (where A= K+, Rb+, Cs+; M = Mn2+or Mn1–xZnx2+; B= In3+; X= Cl–or Br–), abbreviated as A-M-X. Through the structural analysis of the crystal structure and characterizations of the optical properties of these materials, we have found a direct correlation between the photoluminescence quantum yield (PLQY) and the suitability of the coordination between the A-site metal and the crown ether. Specifically, as the radius of the alkali metal increases (from K to Rb), the PLQY decreases due to poorer suitability. The suitability of the coordination has been analyzed in detail by quantifying the structural parameters (i.e., A–O bond distance, O–A–O bond angle, and distance from Ametal to the crown ether center). This trend has been further confirmed via two independent systems using solid solutions through M-site alloying and comparing the chloride and bromide analogs. Surprisingly, a selective coordination mode has surfaced when alloying on the A-site, where the larger alkali metal preferentially coordinates with the connected crown ether instead of the isolated one. This effective approach leads to a wide range of tunability of the PLQY from 21.7 to 95.2% within the total 12 materials. Through further analysis, we have found that the substitution of the A-site metal from K to Cs increases the Mn–Xdistance, which weakens the crystal field strength of Mn and aligns with the observed trend in PLQY. Our work has further expanded the material space of hybrid trimetallic double-shell clathrates and provides determining insights into controlling the structure and PLQY.

Developers usually use third-party libraries (TPLs) to facilitate the development of their projects to avoid reinventing the wheels, however, the vulnerable TPLs indeed cause severe security threats. The majority of existing research only considered whether projects used vulnerable TPLs but neglected whether the vulnerable code of the TPLs was indeed used by the projects, which inevitably results in false positives and further requires additional patching efforts and maintenance costs (e.g., dependency conflict issues after version upgrades). To mitigate such a problem, we propose VAScanner, which can effectively identify vulnerable root methods causing vulnerabilities in TPLs and further identify all vulnerable APIs of TPLs used by Java projects. Specifically, we first collect the initial patch methods from the patch commits and extract accurate patch methods by employing a patch-unrelated sifting mechanism, then we further identify the vulnerable root methods for each vulnerability by employing an augmentation mechanism. Based on them, we leverage backward call graph analysis to identify all vulnerable APIs for each vulnerable TPL version and construct a database consisting of 90,749 (2,410,779 with library versions) vulnerable APIswith 1.45% false positive proportion with a 95% confidence interval (CI) of [1.31%, 1.59%] from 362 TPLs with 14,775 versions. The database serves as a reference database to help developers detect vulnerable APIs of TPLs used by projects. Our experiments show VAScanner eliminates 5.78% false positives and 2.16% false negatives owing to the proposed sifting and augmentation mechanisms. Besides, it outperforms the state-of-the-art method-level vulnerability detection tool in analyzing direct dependencies, Eclipse Steady, achieving more effective detection of vulnerable APIs. Furthermore, to investigate the real impact of vulnerabilities on real open-source projects, we exploit VAScanner to conduct a large-scale analysis on 3,147 projects that depend on vulnerable TPLs, and find only 21.51% of projects (with 1.83% false positive proportion and a 95% CI of [0.71%, 4.61%]) were threatened through vulnerable APIs, demonstrating that VAScanner can potentially reduce false positives significantly.

In heavy oil reservoirs, favorable reservoir properties have a positive impact on the production performance during CO2huff-n-puff. It is significant to study the screening method of applicable conditions for CO2huff-n-puff in actual reservoirs. To solve these problems, this paper introduced the orthogonal design method to analyze the main factors based on numerical simulation. The technical analysis and the economic evaluation were both employed to obtain the applicable conditions of selecting oil layers or injection wells during CO2huff-n-puff. And a new algorithms of machine learning, the random forest algorithm, was introduce to find the weighted factors and the scoring standards that were suitable for CO2huff-n-puff. Finally, a set of method for screening suitable reservoir conditions was established. Based on the introduction of orthogonal analysis method and random forest algorithm, a software was established to achieve the purpose of analyzing the feasibility of CO2huff-n-puff considering different reservoir geological parameters. This method increased the accuracy and efficiency in screening reservoir conditions that was suitable for CO2huff-n-puff.

Efficient and harmless treatment of microplastics in soil is the current focus of microplastic pollution management. In this study, the pyrolysis effect of soil microplastics at different temperatures and holding times was analyzed. The results showed that temperature and holding time significantly affected the morphology and compositional structure of soil. Pure microplastics and product adhesion after pyrolysis at low temperature (400°C) were not easy to remove. Interestingly, compared with pure polyethylene (PE), direct pyrolysis of microplastics in soil could obtain better results, and the content of organic matter and polycyclic aromatic hydrocarbons (PAH) could be significantly reduced. However, the pyrolysis performance was very unsatisfactory even if the action time was prolonged at 400°C. Prolonged high‐temperature treatment accelerated the fragmentation of the alkane main chain of PE, thus generating more PAH, and the temperature was not high enough (400°C) for further effective degradation of PAH into carbon dioxide and water. Therefore, higher temperature and longer holding time need to be selected to ensure the pyrolysis performance. This study revealed the role and mechanism of pyrolysis in soil microplastic mixed systems, aiming to provide a basis for the treatment of microplastics in terrestrial ecosystems. Mixing soil and microplastics can achieve better thermal degradation effects.At 400°C pyrolysis, more polycyclic aromatic hydrocarbons were produced.Pyrolysis at 600°C reduced polycyclic aromatic hydrocarbons.

The potential of macrophage-mediated phagocytosis as a cancer treatment is promising. Blocking the CD47–SIRPα interaction with a CD47-specific antibody significantly enhances macrophage phagocytosis. However, concerns regarding their toxicity to nontumor cells remain substantial. Here, we engineered chimeric antigen receptor macrophages (CAR-Ms) by fusing a humanized single-chain variable fragment with FcγRIIa and integrating short hairpin RNA to silence SIRPα, thereby disrupting the CD47–SIRPα signaling pathway. These modified CAR-shSIRPα-M cells exhibited an M1-like phenotype, superior phagocytic function, substantial cytotoxic effects on HER2-positive tumor cells, and the ability to eliminate patient-derived organoids. In vivo, CAR-M cells significantly inhibited tumor growth and prolonged survival in tumor-bearing mice. Notably, CAR-shSIRPα-M cells enhanced cytotoxic T-cell infiltration into tumors, thereby enhancing the antitumor response in both the humanized immune system mouse model and immunocompetent mice. Mechanistically, SIRPα inhibition activated inflammatory pathways and the cGAS-STING signaling cascade in CAR-M cells, leading to increased production of proinflammatory cytokines, reactive oxygen species, and nitric oxide, thereby enhancing their antitumor effects. These findings underscore the potential of SIRPα inhibition as a novel strategy to increase the antitumor efficacy of CAR-M cells in cancer immunotherapy, particularly against solid tumors.

In this article, a reconfigurable intelligent surface-based multidimensional index modulation multiple access (RIS-MD-IMMA) scheme is proposed to fully utilize the potential of index modulation (IM) for multiple access (MA) in an RIS environment. In the proposed scheme, the information of different users is transmitted using symbols with different index entities, and the receiver detects the respective index information independently. Compared with the traditional RIS-assisted nonorthogonal MA (RIS-NOMA) scheme, the proposed scheme mitigates intracluster interference among users and eliminates superposition coding and successive interference cancellation (SIC) operations needed in NOMA. To reduce the required power consumption and computational complexity of the receiver detection, a low-complexity (LC) detection algorithm for RIS-MD-IMMA is proposed. The simulation analysis results show that RIS-MD-IMMA performs better in terms of both the number of serviceable users and bit error rate (BER) performance compared with RIS-NOMA.

Background: Endoscopic submucosal dissection (ESD) is a safe and effective technique for the treatment of gastrointestinal tumors, including rectal neuroendocrine tumors (r-NETs). However, the relative advantages of traction-assisted ESD for the treatment of small rectal lesions are still debated. Aims: We conducted a study to compare the efficacy and safety of rubber band traction-assisted ESD (RBT-ESD) to conventional ESD (C-ESD). Methods: This study retrospectively analyzed consecutive patients with r-NET treated with ESD between October 2021 and October 2023. Our study assessed differences between the groups in the complete resection rate of lesions, muscular layer injury, surgical complications, operation time, resection speed, time to liquid diet, postoperative hospital stay, hospital cost, and recurrence rate. Results: A total of 119 patients with r-NETs participated in this study (RBT-ESD group, n= 27; C-ESD group, n= 92). The operation time in RBT-ESD group was shorter than in C-ESD group, but the difference was not statistically significant (16.0 min [9.0–22.0 min] vs. 18.0 min [13.3–27.0 min], P= 0.056). However, the resection speed was significantly faster in the RBT-ESD group (6.7 vs. 4.1 mm2/min, P= 0.005). Furthermore, the RBT-ESD group showed significantly less muscular layer injury (P= 0.047) and faster diet recovery (P= 0.035). No significant differences were observed in the complete resection rate, surgical complications, postoperative hospital stay, hospital cost, or recurrence rate between the two groups. Conclusion: For r-NETs of < 2 cm in size, the RBT method did not significantly shorten the operation time but resulted in faster resection speed, less muscular layer injury, and earlier postoperative recovery to a liquid diet. Graphical Abstract:

One of the main challenges for NH3-SCR of NOx at low temperatures is developing a catalyst with exceptional low-temperature catalytic activity. Herein, four kinds of clay minerals including halloysite (Hte), Ca-montmorillonite (Ca-Mte), chlorite (Cte), and Na-montmorillonite (Na-Mte) were used as supports and impregnated with Fe and Cu to synthesize Fe-Cu/Hte, Fe-Cu/Ca-Mte, Fe-Cu/Cte, and Fe-Cu/Na-Mte catalysts, respectively. Within a temperature range of 180–240 °C, the resultant Fe-Cu/Hte catalyst produced more than 98 % NOx conversion and demonstrated the best low-temperature NH3-SCR catalytic performance. The characterization results indicated that the weakened crystallinity of active species, high ratios of Fe3+/Fe and Cu+/Cu, and more surface absorbed oxygen species, as well as excellent low-temperature redox ability and surface acidity all contributed to its outstanding low-temperature catalytic activity. The in situDRIFT study at 240 ℃ showed that two forms of the Eley-Rideal (E-R) mechanism existed on the Fe-Cu/Hte and Fe-Cu/Cte catalysts, while the E-R and Langmuir-Hinshelwood (L-H) processes were both involved over the Fe-Cu/Ca-Mte and Fe-Cu/Na-Mte catalysts.

ABSTRACTHypertension diabetes mellitus is one of the serious complications of hypertension. In this study, ambulatory blood pressure monitoring (ABPM) and ultrasonic cardiogram (UCG) were used to investigate the cardiac changes and its influencing factors in hypertensive patients with type 2 diabetes mellitus. The ABPM, UCG, Hemoglobin A1c (HbA1c) and body mass index (BMI) of patients were examined. The comparison of HbA1c, BMI, gender, age, daytime and nighttime blood pressure, left ventricular mass index (LVMI), left ventricular hypertrophy (LVH), isovolumic relaxation time (IVRT) and E/A ratio were made between the two groups. The cardiac function of control group was better than that of group B, while that of group B was better than group A. The cardiac index level in group B was better than that in group A, but lower than that in control group. The LVMI in group A was clearly higher than group B and control group, and the incidence of LVH increased. In group A, the nocturnal systolic blood pressure was higher than control group and group B. Nocturnal diastolic blood pressure, daytime diastolic blood pressure and systolic blood pressure in groups A and B were higher than those the control group. The findings indicated that hypertension complicated with type 2 diabetes mellitus can cause degeneration of the heart, and complicated with type 2 diabetes mellitus can accelerate ventricular remodeling and functional deterioration. Hypertension with type 2 diabetes mellitus are more prone to left ventricular damage.

ABSTRACTCoronary heart disease (CHD) is one of the most common cardiovascular diseases. This study analyzed the diagnostic value of echocardiography combined with serum homocysteine (Hcy) and proprotein convertase subtilisin 9 (PCSK9) in CHD. Here, 108 CHD patients were selected as the study group. Additionally, 108 patients with suspected CHD excluded by coronary angiography were selected as the control group. Serum Hcy and PCSK9 levels were detected by circulating enzymatic and biochemical analysis assay. The contrast echocardiography showed that the contrast agent filling velocity (β) and the maximum number of microbubbles (A) in the study group were declined compared to the control group. Serum Hcy and PCSK9 levels in the study group were higher than those in the control group. In addition, β, A, Hcy and PCSK9 are important influencing factors of CHD. The coronary artery disease branch numbers and the degree of stenosis in CHD patients were negatively correlated with β and A values, and positively correlated with serum Hcy and PCSK9 levels. β, A combined with serum Hcy and PCSK9 levels have diagnostic value for CHD, and are significantly correlated with the severity of CHD.

Natural gas is increasingly recognized as a clean energy source due to its high quality, low pollution levels, and abundant availability. However, certain gas fields contain complex components that require purification for efficient transportation and utilization. Addressing these issues involves efficient gas–liquid separation technology. Existing gas–liquid separation units face challenges such as efficiency, liquid entrainment, energy consumption, and the need for consumable replacement. This study focuses on a novel cyclone-coalescence separator that combines centrifugal and coalescence principles. Implemented in a high-acid natural gas purification plant in China, the cyclone-coalescence separator demonstrated efficiency primarily influenced by gas velocity and diameter. Optimal performance was observed with a 75 mm diameter reactor at velocities of 8–12 m·s−1, achieving a peak efficiency of 96%. The hydrophilic glass fiber with a monofilament structure can coalesce droplets effectively. In practical industrial use, under operational conditions, the hydrocyclone's liquid discharge rate is 89.6 kg·h−1with an inlet concentration of 382.7 g·m3. Over a 400-h cycle, the cyclone-coalescence separator demonstrated superior separation performance with an average liquid discharge volume of 9.09 mg·kg−1, compared to 4.93 mg·kg−1for the precision filter. This successful industrial implementation presents a promising approach to natural gas purification.

Harmful Microcystis blooms and microcystins have become a major hidden threat to the safety of the water environment. The application of enzymatic degradation of microcystins has been severely limited by the complex environment. In this study, chitosan-graphene (CG), prepared from green biomass, was employed as matrix material, loaded with 100–200 nm Fe3O4nanoparticles (MCG) and immobilized microcystinase A (MlrA@MCG). The preparation of MlrA@MCG was characterized by scanning electron microscopy, Fourier-transform infrared spectroscopy, X-ray diffraction, vibrating sample magnetometer and fluorescence labelling. The results of the activity analysis demonstrated that MlrA@MCG exhibited superior degradation activity for MCs, as well as enhanced heat and alkaline resistance in comparison to free MlrA. Furthermore, MlrA@MCG can be recovered simply by means of a magnetic field, and its activity remains at 48.6 % after 10 repeated uses. More importantly, MlrA@MCG and the degradation products of MC-LR were not found to be cytotoxic to human cells. It is interesting that the immobilization of MlrA resulted in a reduction in the cytotoxicity of MCG. 0.2 U of MlrA@MCG can still degrade MC-LR from 232.64 μg L−1to 94.39 μg L−1in water from simulated severe Microcystis blooms within 24 h, showing excellent catalytic activity and stability. The study proposed a secure and efficacious approach for the elimination of microcystins from harmful Microcystis blooms, offering a promising avenue for the improvement of environmental safety.

Autism Spectrum Disorders (ASD) comprise a range of early age-onset neurodevelopment disorders with genetic heterogeneity. Most ASD related genes are involved in synaptic function, which is regulated by mature brain-derived neurotrophic factor (mBDNF) and its precursor proBDNF in a diametrically opposite manner: proBDNF inhibits while mBDNF potentiates synapses. Here we generated a knock-in mouse line (BDNFmet/leu) in which the conversion of proBDNF to mBDNF is attenuated. Biochemical experiments revealed residual mBDNF but excessive proBDNF in the brain. Similar to other ASD mouse models, the BDNFmet/leumice showed reduced dendritic arborization, altered spines, and impaired synaptic transmission and plasticity in the hippocampus. They also exhibited ASD-like phenotypes, including stereotypical behaviors and deficits in social interaction. Moreover, the plasma proBDNF/mBDNF ratio was significantly increased in ASD patients compared to normal children in a case-control study. Thus, deficits in proBDNF to mBDNF conversion in the brain may contribute to ASD-like behaviors, and plasma proBDNF/mBDNF ratio may be a potential biomarker for ASD.

Microvitellogenin (mVg) belongs to the lepidopteran-specific lipoprotein_11 super family and is thought to be involved in insect reproduction. However, the function of mVg in reproduction has not been established. In this study, we identified and characterized MsmVgin Mythimna separata, a destructive insect pest of grain crops. MsmVgis comprised of a 1,310 bp open reading frame (ORF) encoding 437 amino acids. Structural analysis showed that MsmVg contains three conserved domains in the lipoprotein_11 super family, including the all-α-N-terminal domain (NTD), a Pseudomonas putidahomologous domain (PPD), and an all-β-C-terminal domain (CTD). MsmVgwas highly expressed in mature female adults and enriched in the ovaries of 3-day-old female adults. Disruption of MsmVgby RNA interference did not change the expression of MsmVg, vitellogenin (MsVg) or the vitellogenin receptor (MsVgR) in fat bodies, but it inhibited their transcription in ovaries. Phenotype analysis showed that knockdown of MsmVgdid not affect yolk deposition in ovaries, but impaired eggshell formation and led to a reduction in the reproductive capacity. Furthermore, knockdown of MsmVgsignificantly inhibited the expression of genes associated with eggshell formation (MsChP1-3and MsFcP3C). Taken together, these data suggest that MsmVgplays an important role in female reproduction by affecting eggshell formation in M. separata, which provides a potential target for managing this insect pest.

As an important element of the renewable energy distribution generations, the modeling accuracy and control performance of the interleaved Buck-Boost converter directly affects the stability and efficiency of the renewable power generation. Based on the fact that the inductor and capacitance are fractional-order (FO) elements, the Buck-Boost converter is FO system. At present, most FO control strategy research has focused on the integer-order (IO) converters, which is inconsistent with the fractional order nature of converters. In order to improve the stability and dynamical performance of the FO interleaved Buck-Boost converter control system, a dual-loop control system based on the fractional-order lead-lag compensation control (FOLLCC) strategy is proposed. To begin with, the FO state space average model for interleaved Buck-Boost converter operating in continuous conduction mode (CCM) is established according to the FO calculus theory and state space average method. Then, the FOLLCC of the FO interleaved Buck-Boost is designed by using the peak current closed-loop control with inner current loop outer voltage loop. The impact of different FO controllers on the steady-state performance of the system is analyzed to improve the control effect. Using MATLAB for simulation, the simulation results show that the control system based on FOLLCC has shorter rise times, faster response speed, stronger robustness, and better dynamic performance. Finally, the experiments verify the effectiveness of the proposed approach.

Many countries are raising the pension age to mitigate the challenges of population aging, but such a solution may ignore the disparities in health and working conditions across populations. Using large-scale longitudinal data from China, this study provides estimates of healthy working life expectancy (HWLE), defined as the average number of years expected to be spent healthy and in work from age 50 years, and highlights substantial inequities in HWLE by gender, socioeconomic status and geographical region. The HWLE from age 50 years was, on average, 6.87 (95% confidence interval: 6.70 to 7.04) years in China. Hypertension was the leading chronic condition for people working unhealthily (5.67 years for men and 4.85 years for women), and arthritis contributed the largest differences in unhealthy working years across people by occupation (agricultural laborer versus enterprise employee, 3.28 years). Moreover, adopting healthy lifestyles was associated with gains in HWLE (2.13 years for men and 1.61 years for women). Our findings suggest that increasing the pension age through a ‘one-size-fits-all’ approach may not effectively meet the goal of extending working lives. Inclusive initiatives aimed at targeted populations to promote health or work conditions and to facilitate the pension system will be essential to improve HWLE by reducing inequities.

The abnormal energy metabolism level of a tumor reduces the efficiency of chemotherapy. Metal–organic nanomaterials (MONs) with high drug loading efficiency, easy processes of synthesis, and controlled drug release have shown great potential in metabolic blocking and enhancement of tumor therapy. These metal–organic nanomedicines have been reported to modulate glycolysis or oxidative phosphorylation to provide monotherapy or combined therapies in tumorous treatments. In addition, the encapsulation or coordination of fluorescent dyes into MONs endowed them with the imaging ability of tumor metabolism. Herein, this Perspective summarizes the progress of MONs as therapeutic agents or imaging probes for application during tumor metabolic blocking or imaging, providing solid inspiration for biomedical applications of effective biomaterials. In addition, the current drawbacks of MONs for further biological applications in the future were discussed, giving stimulation of innovation and development in biomedical applications of MONs.

Over the past decade, a marked escalation in the prevalence of hepatic pathologies has been observed, adversely impacting the quality of life for many. The predominant therapeutic strategy for liver diseases has been pharmacological intervention; however, its efficacy is often constrained. Currently, liposomes are tiny structures that can deliver drugs directly to targeted areas, enhancing their effectiveness. Specifically, cell membrane-associated liposomes have gained significant attention. Despite this, there is still much to learn about the binding mechanism of this type of liposome. Thus, this review comprehensively summarizes relevant information on cell membrane-associated liposomes, including their clinical applications and future development directions. First, we will briefly introduce the composition and types of cell membrane-associated liposomes. We will provide an overview of their structure and discuss the various types of liposomes associated with cell membranes. Second, we will thoroughly discuss various strategies of drug delivery using these liposomes. Lastly, we will discuss the application and clinical challenges associated with using cell membrane-associated liposomes in treating liver diseases. We will explore their potential benefits while also addressing the obstacles that need to be overcome. Furthermore, we will provide prospects for future development in this field. In summary, this review underscores the promise of cell membrane-associated liposomes in enhancing liver disease treatment and highlights the need for further research to optimize their utilization. In summary, this review underscores the promise of cell membrane-associated liposomes in enhancing liver disease treatment and highlights the need for further research to optimize their utilization.

Extracellular vesicles (EVs) harbor abundant glycans that mediate various functions, such as intercellular communication and disease advancement, which play significant roles in disease progression. However, the presence of EV heterogeneity in body fluids and the complex nature of the glycan structures have posed challenges for the detection of EV glycans. In this study, we provide a streamlined method integrated, membrane-specific separation with lectin-induced aggregation strategy (MESSAGE), for multiplexed profiling of EV glycans. By leveraging a rationally designed lectin-induced aggregation strategy, the expression of EV glycans is converted to size-based signals. With the assistance learning machine algorithms, the MESSAGE strategy with high sensitivity, specificity, and simplicity can be used for early cancer diagnosis and classification, as well as monitoring cancer metastasis via 20 μL plasma sample within 2 h. Furthermore, our platform holds promise for advancing the field of EV-based liquid biopsy for clinical applications, opening new possibilities for the profiling of EV glycan signatures in various disease states.

Microelectrodes have transformed our understanding of spatiotemporal responses to electrical stimulation. However, biological signals are often molecular, complicating the capture of intricate chemical signals. The microfluidic chip developed in this paper accurately measures droplet volume by using impedance analysis. The utilization of droplet volume as a feedback signal for precise microsampling pressure control ensures that microsampling remains unaffected by droplet volume influence. Once the microsampling is complete, chemiluminescence detection enables high temporal resolution and continuous and sensitive monitoring of chemical information within the droplets. Experimental verification shows that the chip can avoid volume influence through impedance feedback, achieving consistent and stable microampling at the nanoliter level (0–3 nL). In just 0.3 s, it can perform sensitive chemiluminescence detection of H2O2and glucose within droplets. The linear detection ranges for these analytes are 10–50,000 and 20–600 μM, respectively, with the limit of detection being 0.648 and 0.334 μM. The significance of this chip lies in its ability to reveal changes in both electrical and chemical signals during transient biological processes. Its potential applications are numerous, encompassing a wide range of emerging areas such as single-cell analysis, cell communication, and cellular immunity.

Inflammation, oxidative stress, fibrosis, and ferroptosis play important roles in diabetic nephropathy development. Krüppel-like factor 4 (KLF4) is a transcriptional factor, which regulates multiple cell processes and is involved in diabetic nephropathy. Berberine has various biological activities, including anti-inflammation, antioxidative stress, and antiferroptosis. Berberine has been shown to inhibit diabetic nephropathy, but whether it involves KLF4 and ferroptosis remains unknown. We established a diabetic nephropathy mice model and administered berberine to the mice. The kidney function, renal structure and fibrosis, expression of KLF4 and DNA methylation enzymes, DNA methylation of the KLF4 promoter, mitochondria structure, and expression of oxidative stress and ferroptosis markers were analyzed. Berberine rescued kidney function and renal structure and prevented renal fibrosis in diabetic nephropathy mice. Berberine suppressed the expression of DNMT1 and DNMT2 and upregulated KLF4 expression by preventing KLF4 promoter methylation. Berberine inhibited the expression of oxidative stress and ferroptosis markers, maintained mitochondria structure, and prevented ferroptosis. Berberine ameliorates diabetic nephropathy by inhibiting Klf4 promoter methylation and ferroptosis.

To discover new osteoclast-targeting antiosteoporosis agents, we identified forty-six diselenyl maleimides, which were efficiently prepared using a novel, simple, and metal-free method at room temperature in a short reaction time. Among them, 3kshowed the most marked inhibition of osteoclast differentiation with an IC50value of 0.36 ± 0.03 μM. Moreover, 3ksignificantly suppressed RANKL-induced osteoclast formation, bone resorption, and osteoclast-specific genes expression in vitro. Mechanistic studies revealed that 3kremarkably blocked the RANKL-induced mitogen-activated protein kinase (MAPK) and NF-κB signaling pathways. In ovariectomized mice, intragastric administration of 3ksignificantly alleviated bone loss, exhibiting an effect similar to that of alendronate. Surface plasmon resonance assay and microscale thermophoresis assay results suggested that RANKL might be a potential molecular target for 3k. Collectively, the findings presented above provided a novel candidate for further development of bone antiresorptive drugs that target RANKL.

Solving the complex challenges of sophisticated terrain and multi-scale targets in remote sensing (RS) images requires a synergistic combination of Transformer and convolutional neural network (CNN). However, crafting effective CNN architectures remains a major challenge. To address these difficulties, this study introduces the knowledge guided evolutionary Transformer for RS scene classification (Evo RSFormer). It amalgamates adaptive evolutionary CNN (Evo CNN) with Transformers in a hybrid strategy synergistically, which combines fine-grained local feature extraction of CNNs with long-range contextual dependency modeling of Transformers. Furthermore, for the development of Evo CNN blocks, this paper presents a knowledge-guided adaptive efficient multi-objective evolutionary neural architecture search (MOE2-NAS) strategy. This approach markedly diminishes the labor-intensive characteristics associated with traditional CNN design, striking a balance for both accuracy and compactness. Additionally, by leveraging domain knowledge from natural scene analysis into the RS field, MOE2-NAS facilitates the efficiency of classical NAS. It utilizes a priori knowledge to generate promising initial solutions and constructs a surrogate model for efficient search. The effectiveness of the proposed Evo RSFormer has been rigorously tested on various benchmark RS datasets, including UC Merced, NWPU45, and AID. Empirical results strongly support the superiority of Evo RSFormer over existing methods. Furthermore, experiments on MOE2-NAS have been studied to confirm the important role of knowledge guidance in improving the efficiency of NAS.

With the development of multimedia technology, events are usually presented in multimedia forms, thus multimedia event extraction (MEE) has become more and more important. Existing MEE works usually use simple strategies to align two modalities, making it difficult to precisely extract events and arguments in complex multimedia documents. To address this problem, we propose a novel Multi-grained Gradual Inference Model (MGIM) that focuses on inferring and interpreting events in complex multimedia structures in a coarse-to-fine manner. To efficiently integrate textual and visual modalities, we design a Coarse-grained Alignment (CA) module, which represents the two modalities in a graph structure and performs coarse-grained alignment. Based on the CA module, we further propose a Fine-grained Inference module (FI) that fine-grained aligns text and image by performing multiple rounds of gradual inference. MGIM provides a comprehensive interpretation of multimedia events at two information granularities (coarse and fine). Extensive experiments on the M2E2 dataset demonstrate the effectiveness of MGIM.

RGB (visible), near-infrared (NI), and thermal infrared (TI) imaging modalities are commonly combined for round-the-clock surveillance. We introduce a novel unsupervised multi-modality person re-identification (MM-ReID) task, which, based on an individual’s image in any one modality, seeks to identify matches in the other two modalities. Compared to prior MM-ReID problem formulations, unsupervised MM-ReID significantly reduces labeling cost and imaging constraints. To address the unsupervised MM-ReID task, we propose a novel inter-modality similarity learning (IMSL) framework consisting of four synergistic interconnected modules: modality mean clustering (MMC), multi-modality reliability estimation (MMRE), shape-based mutual reinforcement (SMR), and modality-aware invariant learning (MIL). MMC iterates with SMR and MIL in a mutually beneficial manner to provide pseudo-labels that are robust to modality gap. MMRE normalizes sample weights, mitigating the impact of noisy labels in the multi-modality setting. SMR emphasizes shape information to implicitly enhance the model’s robustness to the modality gap and is additionally guided by pseudo-labels provided by MMC to attend to identity-related details. MIL explicitly encourages learning of modality-invariant and identity-related features via contrastive feedback for the MMC module. Extensive experimental results on the multi-modality and cross-modality datasets demonstrate that IMSL provides substantial performance gains over existing methods. Code is made available at https://github.com/zqpang/IMSL.

This article presents a novel single-cell biosensor with pico-liter scale sensitivity. The high-sensitivity microwave biosensor integrates a microchannel and a coplanar waveguide (CPW) to facilitate the capture and release of single cells. This biosensor can identify and differentiate solution concentrations, various particles, and tumor cells by measuring the amplitude and phase of the transmission coefficient. The CPW structure enhances the electric field intensity in the sensing area by increasing capacitance, which reduces the sensing area size and improves sensor sensitivity. By measuring the amplitude and phase of the wide-band transmission coefficients of tumor cells, we achieved identification of subtle changes in the electrical properties of different cell types. The sensor is capable of detecting individual particles and cells. To validate its performance, we measured different concentrations of bovine serum albumin (BSA) solution, achieving a 0.5° phase difference, confirming the sensor’s capability to recognize minor changes in pico-liter samples. The measurement of three types of $10~\mu $ m particles verified the sensor’s ability to capture, release, and distinguish between different particle types. Measurements of three cell types showed that despite their small differences, the sensor could still distinguish them. Statistical results from 20 repeated measurements demonstrate the sensor’s feasibility in distinguishing single cells. This noninvasive, label-free sensor holds significant potential for tumor cell recognition, differentiation, and diagnosis.

Multiview representation learning has recently attracted significant attention in the machine learning and computer vision community. However, during fusing information from multiple views, existing work often neglect to exploit the complementary information in each view and endow with the interpretability of model. To this end, in this article, we propose a multiview attention fusion information bottleneck network, termed by MVAIBNet. Specifically, MVAIBNet deliberately develops dual-path reconstructions to extract latent embeddings of views, where view-peculiar representations are disentangled from the embeddings using $\beta$-VAE, to help reconstruct each view. Then, to align and fuse view-common representations, an attention fusion unit, namely the multiview channel fusion unit (MVCFU), is presented accordingly. Furthermore, relying on the information bottleneck principle, we integrate the consistency information and specificity information of the views to prompt a compact semantic representation of multiple views with balancing the complementarity and consistency among multiple views flexibly. Extensive experimental results on four real-world datasets show that our algorithm achieves encouraging performance on several evaluation metrics compared to the state-of-the-art methods.

Anaprazole is a proton pump inhibitor. This study aims to elucidate absorption, metabolism, and excretion pathways of anaprazole sodium in the human body. A total of 4 healthy Chinese male subjects were administered a single oral dose of 20 mg/100 µCi of [14C]‐anaprazole sodium enteric‐coated capsules. The whole blood, plasma, and excreta were analyzed for a total radioactivity (TRA) and metabolite profile. The cumulative radioactivity excretion rate was 93.2%, with 53.3% and 39.9% of the radioactive dose excreted in urine and feces, respectively, and 91.6% of dose recovered within 96 hours after dosing. The parent drug, anaprazole, showed good absorption and was extensively metabolized majorly to thioether M8‐1 via nonenzymatic metabolism. Overall, 35 metabolites were identified in plasma, urine, and fecal samples. Anaprazole was the most abundant component in plasma followed by the thioether M8‐1, accounting for 28.3% and 16.6%, respectively, of the plasma TRA. Thioether carboxylic acid XZP‐3409 (26.3% of urine TRA) and XZP‐3409 oxidation and dehydrogenation product M417a (15.1% of fecal TRA) were the major metabolites present in urine and feces, respectively. Anaprazole was undetectable in urine, while fecal samples showed traces (0.07% dose). Blood/plasma ratios of the radioactivity (approximately 0.60) remained consistent over time. Anaprazole showed good absorption and was extensively metabolized majorly to thioether M8‐1 via nonenzymatic metabolism, and cytochrome P450 3A4 also contributed to its metabolism in healthy individuals.

In this paper, we demonstrate methods to extract $dq$ admittance for a solar photovoltaic (PV) farm from its black-box model used for electromagnetic transient (EMT) simulation. Each $dq$ admittance corresponds to a certain operating condition. Based on the $dq$ admittance, analysis is carried out to evaluate how grid strength and solar irradiance may influence stability. Two types of stability analysis methods (open-loop system based and closed-loop system based) are examined and both can deal with $dq$ admittance's frequency-domain measurements directly and produce graphics for stability analysis. The findings based on $dq$ admittance-based analysis are shown to corroborate EMT simulation results.

Commercial pH paper is a quick and simple tool for measuring a solution’s acidity/basicity, but it only provides qualitative or semi-quantitative results, and the synthetic indicator dyes within can be toxic or carcinogenic. Although pH meters enable more accurate and quantitative analysis, they are less convenient to operate and are tedious to calibrate. This presents a need for an alternative pH testing method for applications where it is not easy or possible to use a pH meter, yet quantitative results are desired. We report herein the fabrication of a pH test strip made from superhydrophobic paper and agarose-anthocyanin film discs. In the proposed method, test strips are dipped into samples and then imaged with a portable scanner (or a smartphone). The color of the film is extracted with ImageJ software (or a mobile app), using the RGB color system. By generating a calibration curve relating the film color to the sample pH using standard buffer solutions, we are able to quantify the pH of beverages and other liquids with an accuracy and precision comparable to that of a pH meter. The test strips offer the same convenience as conventional pH paper, with the added capabilities of quantitation and multiplexed testing, which presents a practical tool for point-of-need pH analysis.

To provide the mechanism-based pharmacotherapy of the Huatan Qushi formula (HTQS formula), for the health management and treatment of non-alcoholic fatty liver disease (NAFLD).

It is important to limit the dc fault current in voltage source converter-based high-voltage direct-current (VSC-HVDC) grids for fault ride-through and safe operation. At present, the most typical method of fault current limitation in VSC-HVDC grids is to install dc reactors directly in the system. However, this will lead to a drastic increase in the required capacity of the direct current circuit breaker (DCCB) metal oxide varistor (MOV), increasing the manufacturing difficulty of the DCCB and reducing its operation reliability. Meanwhile, the dc fault current clearing time is also markedly prolonged, meaning that the dc fault handling speed is reduced. To solve above problems, several dc fault current limiters (FCLs) based on controlled (full-controlled or half-controlled) power electronic switches have been proposed, which inevitably incur a high cost. In this article, a novel diode–thyristor hybrid dc FCL is proposed. It can effectively reduce the high requirement on DCCB MOV rated capacity imposed by the dc reactor and increase the dc fault current clearing speed. In addition, compared with existing dc FCLs with similar functions, its cost is much lower due to the hybrid design. Furthermore, when applied to multiterminal VSC-HVDC grids, an accurate parameter design method for dc FCLs is innovatively proposed based on the concept of optimization. Finally, simulation case studies and experimental tests are carried out to prove the feasibility and superiority of the proposed method.

Graphical Abstract:

Conversational large language models (LLMs) such as ChatGPT and GPT-4 have recently exhibited remarkable capabilities across various domains, capturing widespread attention from the public. To facilitate this line of research, in this paper, we report the development of MOSS, an open-sourced conversational LLM that contains 16 B parameters and can perform a variety of instructions in multi-turn interactions with humans. The base model of MOSS is pre-trained on large-scale unlabeled English, Chinese, and code data. To optimize the model for dialogue, we generate 1.1 M synthetic conversations based on user prompts collected through our earlier versions of the model API. We then perform preference-aware training on preference data annotated from AI feedback. Evaluation results on real-world use cases and academic benchmarks demonstrate the effectiveness of the proposed approaches. In addition, we present an effective practice to augment MOSS with several external tools. Through the development of MOSS, we have established a complete technical roadmap for large language models from pre-training, supervised fine-tuning to alignment, verifying the feasibility of chatGPT under resource-limited conditions and providing a reference for both the academic and industrial communities. Model weights and code are publicly available at https://github.com/OpenMOSS/MOSS.

Use of nanomaterials (NMs) to improve plant abiotic stress tolerance (AST)is a hot topic in NM-enabled agriculture. Previous studies mainly focused on the physiological and biochemical responses of plants treated with NMs under abiotic stress. To use NMs for improving plant AST, it is necessary to understand how they act on this tolerance at the omics and epigenetics levels. In this review, we summarized the knowledge of NM-improved abiotic stress tolerance in relation to omics (such as metabolic, transcriptomic, proteomic, and microRNA), DNA methylation, and histone modifications. Overall, NMs can improve plant abiotic stress tolerance through the modulation at omics and epigenetics levels.

In nature, basic terpene skeletons are produced and subsequently undergo enzymatic or nonenzymatic oxidative transformations, leading to diverse structural variations. To date, thousands of natural products featuring a variety of oxidation patterns have been isolated solely from the labdane family. This work describes a strategy for the comprehensive introduction of oxidation states into the labdane core by employing a combination of enzyme library screening, directed evolution, and sequential chemical oxidation processes. Furthermore, we showcase the functional viability of our chemoenzymatic approach by accomplishing a formal synthesis of nimbolide, highlighting its potential for streamlining the synthesis of complex natural products.

Due to the easy oxidation of Sn2+, which leads to form tin vacancy defects and poor perovskite film quality, caused by the rapid crystallization rate in tin-based perovskite solar cells (PSCs), their efficiency lags far behind that of lead-based PSCs. To improve the photovoltaic (PV) performance and stability of FA0.9PEA0.1SnI3-based PSCs (T-PSCs), a small amount of Pb(SCN)2is introduced into a perovskite precursor as an antioxidant, and acetaminophen (ACE) with various functional groups is used to modify a poly(3,4-ethylenedioxythiophene):poly(styrenesulfonate) (PEDOT:PSS)/perovskite interface. The results show that the Pb(SCN)2additive and ACE interfacial modification can not only optimize energy level alignment in T-PSCs but also inhibit Sn2+oxidation to reduce the trap-state density, resulting in promoted carrier transport. The synergetic effect of the Pb(SCN)2antioxidant and ACE interfacial modification significantly reduces nonradiative recombination and improves the PV performance and stability of T-PSCs. Consequently, the unsealed T-PSCs with the Pb(SCN)2additive and ACE modification achieve a champion efficiency of 12.04% and maintain 99% of their initial PCE after being stored in N2for more than 2100 h, while reference T-PSCs demonstrate a champion PCE of 6.20% and retain only 72% of its initial PCE. Moreover, the modified T-PSCs without encapsulation demonstrate much better stability in humid air.

Near-infrared (NIR) aggregation-induced emission luminogens (AIEgens) are excellent probes for tumor imaging, but there still is space to improve their imaging specificity and sensitivity. In this work, a strategy of tandem targeting and dual aggregation of an AIEgen is proposed to achieve these two purposes. An AIEgen, β-tBu-Ala-Cys(StBu)-Lys(Biotin)-Pra(QMT)-CBT (Ala-Biotin-QMT), is designed to tandem target the biotin receptor and leucine aminopeptidase of a cancer cell and thereafter undergo CBT-Cys click reaction-mediated dual aggregations in the cell. Experimental results show that Ala-Biotin-QMTrenders 4.8-fold and 7.9-fold higher NIR fluorescence signals over those in the “biotin + LAP inhibitor”-treated control groups in living HepG2 cells and HepG2 tumor-bearing mice, respectively. We anticipate that Ala-Biotin-QMT, which has the tandem targeting and dual aggregation property to simultaneously achieve enhanced tumor enrichment and fluorescence onset, could be applied for accurate cancer diagnosis in the clinic in the future.

Glutamate dehydrogenases (GDH) serve as the key regulated enzyme that links protein and carbohydrate metabolism. Combined with motif reassembly and mutation, novel GDHs were designed. Motif reassembly of thermophilic GDH and malate dehydrogenase aims to overcome stability and activity tradeoff in nonaqueous systems. Structural compatibility and dynamic cooperation of the designed AaDHs were studied by molecular dynamics simulation. Furthermore, multipoint mutations improved its catalytic activity for unnatural substrates. Amino acid interaction network analysis indicated that the high density of hydrogen-bonded salt bridges is beneficial to the stability. Finally, the experimental verification determines the kinetics of AaDHs in a nonaqueous system. The activity of Aa05 was increased by 1.78-fold with ionic liquid [EMIM]BF4. This study presents the strategy of a combination of rigid motif assembly and mutations of active sites for robust dehydrogenases with high activity in the nonaqueous system, which overcomes the activity–stability tradeoff effect.

Designing nonprecious metal anode catalysts for photoassisted direct methanol fuel cells (PDMFCs) remains a challenge. As a semiconductor catalyst with a spinel structure, NiCo2O4has good methanol catalytic oxidation activity and photocatalytic activity, making it a highly promising anode non-noble metal catalyst for PDMFCs. However, compared with the noble metal catalyst, the photoelectrocatalytic activity remained to be improved. In this report, an anion regulation strategy was adopted to improve the photoassisted methanol electrocatalytic activity. Using a CoNi-Aspartic (CoNi-Asp) nanorod as the precursor, the anion-regulated NiCo2X4(X = O, S, Se, Te) was prepared by oxidation, sulfuration, selenization, and telluridation reactions. The regulation of anions and their effects on the electronic structure, intermediate product, and photoelectric catalytic performance of NiCo2X4(X= O, S, Se, Te) was systematically discussed. Photoelectrochemical characterization and adsorption energy of •OH revealing the volcano-like correlation between the anion in NiCo2X4(X = O, S, Se, Te) and their photoelectrocatalytic performance. The narrowest band gap (2.239 eV), the highest •OH adsorption energy (−3.32 eV), and the highest ratio of Co3+/Co2+(2.19) ensure the best photoelectric catalytic performance of NiCo2S4, under the visible light irradiation, the photoresponse current density was 1.9 A g–1, the current density at 0.6 V was up to 21.9 A g–1.After 9 h of stability testing, the current retention rate was 80%. This report sheds an idea for the rational design of non-noble anode catalysts for PDMFCs.

The newly identified type VII CRISPR–Cas candidate system uses a CRISPR RNA-guided ribonucleoprotein complex formed by Cas5 and Cas7 proteins to target RNA1. However, the RNA cleavage is executed by a dedicated Cas14 nuclease, which is distinct from the effector nucleases of the other CRISPR–Cas systems. Here we report seven cryo-electron microscopy structures of the Cas14-bound interference complex at different functional states. Cas14, a tetrameric protein in solution, is recruited to the Cas5–Cas7 complex in a target RNA-dependent manner. The N-terminal catalytic domain of Cas14 binds a stretch of the substrate RNA for cleavage, whereas the C-terminal domain is primarily responsible for tethering Cas14 to the Cas5–Cas7 complex. The biochemical cleavage assays corroborate the captured functional conformations, revealing that Cas14 binds to different sites on the Cas5–Cas7 complex to execute individual cleavage events. Notably, a plugged-in arginine of Cas7 sandwiched by a C-shaped clamp of C-terminal domain precisely modulates Cas14 binding. More interestingly, target RNA cleavage is altered by a complementary protospacer flanking sequence at the 5′ end, but not at the 3′ end. Altogether, our study elucidates critical molecular details underlying the assembly of the interference complex and substrate cleavage in the type VII CRISPR–Cas system, which may help rational engineering of the type VII CRISPR–Cas system for biotechnological applications.

Cyclin-dependent kinases (CDKs), including CDK12 and CDK13, play crucial roles in regulating the cell cycle and RNA polymerase II activity, making them vital targets for cancer therapies. SR4835 is a selective inhibitor of CDK12/13, showing significant potential for treating triple-negative breast cancer. To elucidate the selective mechanism of SR4835 among three CDKs (CDK13/12/9), we developed an innovative enhanced sampling method, integrated well-tempered metadynamics-umbrella sampling (IMUS). IMUS synergistically combines the comprehensive pathway exploration capability of well-tempered metadynamics (WT-MetaD) with the precise free energy calculation capability of umbrella sampling, enabling the efficient and accurate characterization of drug-target interactions. The accurate calculation of binding free energy and the detailed analysis of the kinetic mechanism of the drug-target interaction using IMUS successfully elucidate the drug selectivity mechanism targeting the three CDKs, showing that the selectivity is primarily arising from differences in the stability of H-bonds within the Hinge region of the kinases and the interaction patterns during the protein–ligand recognition process. These findings also underscore the utility of IMUS in efficiently and accurately capturing drug-target interaction processes with clear mechanisms.

The present study aimed to identify and verify new plasma protein markers to predict the female fecundability level. A nested case-control study was conducted involving couples who participated in the Chinese National Free Preconception Check-up Project. Women who successfully conceive within one year were defined as the high fecundability group, and those unable to conceive were defined as the low fecundability group. In the training cohort, potential protein biomarkers were identified using proteomics technology and were further tested in a validation cohort by the Western blotting assay, enzyme-linked immunosorbent assay, and biochemical tests. Meanwhile, receiver operating characteristic curve analysis were used to evaluate the predictive value. Cox proportional hazard regression analyses were conducted to calculate hazard ratios; restricted cubic spline analysis was used to assess the linear relationship between the the protein level and hazard ratios for fecundability. Pyruvate, a key product of glycolysis, was significantly increased in the high fecundability group (P< 0.01) compared to the low fecundability group, and its area under the curve value was 0.68 (P< 0.05). There was a linear positive dose–response association between the pyruvate level and fecundability possibility (hazard ratios = 1.66, 95% CI: 1.07–2.59, pfor trend = 0.025, nonlinearity, p-value = 0.2927).

ABSTRACTAn unknown filamentous cyanobacterium was isolated from the Yuqiao Reservoir, a eutrophic drinking water reservoir in Tianjin city, northern China. The cyanobacterium shares some morphological similarities with most Leptolyngbya-like species, having thin trichomes that can facultatively produce sheaths, with one trichome per sheath, and contain peripheral thylakoids. Based on a combination of morphological, molecular, ultrastructural and ecological evidence, we propose the description of a new cyanobacterial taxon, Cyanoleptonema yuqiaoensis gen. & sp. nov. which expands our understanding of cyanobacterial diversity. Phylogenetic analyses based on 16S rRNA gene sequences placed this freshwater strain into a well-supported clade closely related to the marine or saline genera Sodalinemaand Baaleninema. Genetic identity between Cyanoleptonemaand other cyanobacteria, including Sodalinemaand Baaleninema, was found to be less than 95% in 16S rRNA. The genus was further distinguished by morphological and ecological characteristics, including cell size and the ratio between cell length and width.

Accurate prediction of Drug-Target binding Affinity (DTA) is a daunting yet pivotal task in the sphere of drug discovery. Over the years, a plethora of deep learning-based DTA models have emerged, rendering promising results in predicting the binding affinities between drugs and their target proteins. However, in contrast to the conventional approach of modeling binding affinity in vector spaces, we propose a more nuanced modeling process in a continuous space to account for the diversity of input samples. Initially, the drug is encoded using the Simplified Molecular Input Line Entry System (SMILES), while the target sequences are characterized via a pretrained language model. Subsequently, highly correlative information is extracted utilizing residual gated convolutional neural networks. In a departure from existing deep learning-based models, our model learns the hidden representations of the drugs and targets jointly. Instead of employing two vectors, our hidden representations consist of two Gaussian distributions. To validate the effectiveness of our proposal, we conducted evaluations on commonly utilized benchmark datasets. The experimental outcomes corroborated that our method surpasses the state-of-the-art vectorial representation methods in terms of performance. This approach, therefore, offers potential enhancements in the precision of DTA predictions, potentially contributing to more efficient drug discovery processes.

With the development of vehicle applications such as intelligent transportation and autonomous driving, the application fields based on location services have increasingly higher requirements for vehicle positioning reliability and real-time accuracy. However, the existing single navigation source of vehicles makes it difficult to realize real-time and high-precision positioning in different scenarios. The current multi-source information fusion methods have the problems of low generalization ability, poor expansibility, and high computational complexity, so it is challenging to apply in the field of vehicle positioning. To solve the above problems, this paper proposes a vehicle heterogeneous multi-source information fusion positioning method (MIFP) based on information probability, which converts the multiple heterogeneous navigation sources into information probability models to realize the unification of the time-frequency parameter format and designs an information fusion algorithm to realize the rapid fusion based on the theory of relative entropy. Through simulation tests and experimental verification by comparing with mainstream information fusion methods, such as the UKF method, the FGA method, and the NNA method, the MIFP method has high positioning accuracy and strong real-time performance. It can effectively solve the problems of weak expansion ability and large calculation amounts of current vehicle fusion positioning models. In the case of interference or mutation, the MIFP method can also suppress the influence of sudden errors on vehicle positioning.

High-performance terahertz (THz) narrow-band metamaterial absorbers (MMAs) occupy a central position in sensing application. However, the majority of current MMAs for refractive index (RI) sensing typically only perform well within a single or dual-band range, or exhibit relatively low sensing performance. In this work, a tri-band MMA based on tri-cylindrical-shell (TCS) structure Ti3C2Tx MXene is proposed and investigated numerically for the enhanced RI sensing applications in THz region. The fundamental idea behind our approach lies in harnessing the unique electromagnetic (EM) properties of Ti3C2Tx MXene to achieve multiband absorption and enhanced sensing capabilities. A comprehensive numerical simulation analysis of the designed MMA was conducted using the finite element method (FEM) and the equivalent circuit method (ECM). The simulation results demonstrate that the proposed MMA achieves remarkably high absorbance levels of 99.97%, 94.54%, and 99.65% at 1.20, 1.55, and 1.91 THz, respectively. This strong absorption is attributed to the hybrid coupling effect between waveguide modes and surface plasmon polaritons (SPPs), as evidenced by the simulated EM fields and energy distributions. Notably, the tri-band absorption characteristics of our MMA can be easily tuned by adjusting the geometric parameters of its unit-cell. Moreover, the MMA exhibits exceptional sensing performance, with sensitivities of up to 1.79, 1.40, and 1.13 THz/RIU, respectively. This combination of straightforward design, robust absorption capabilities, and heightened sensitivity makes our MMA structure a promising candidate for applications in THz biosensing, material detection, and communication systems.

In order to solve the problem of poor performance of welded joints of steel and aluminum dissimilar materials, this study proposes the use of ceramic particle-reinforced aluminum alloy as an alternative to traditional aluminum alloy for welding, effectively overcoming this problem. In this paper, the laser welding of stainless steel/6061 aluminum alloy (SA) and stainless steel/TiC–TiB2duplex nanoparticle-reinforced 6061 aluminum alloy (SRA) was realized. The effect of ceramic nanoparticles on the microstructure and mechanical properties of SRA joint was systematically studied, and the strengthening mechanism of nanoparticles was revealed. Under the same process parameters, the melting zone of SRA joint is larger and the intermetallic compound (IMCs) layer is narrower. Moreover, the grain size of the brittle Fe–Al compound phase in the IMCs layer is significantly reduced, which effectively inhibits the initiation of cracks at the steel/aluminum interface. The study shows that ceramic particles have a pinning effect on the dislocations, limiting the grain growth, reducing the thickness of the intermetallic compound layer, and decreasing the content of the brittle FeAl3phase. Moreover, ceramic nanoparticles promote the formation of Mg2Si strengthened phase at the grain boundary, further hinder the dislocation movement and improve the strength of the joint. Under the welding power of 3400 W and welding speed of 31 mm/s, SRA joint achieves the maximum tensile shear of 1718 N, which is 15% higher than the strength of SA joint.

In this article, an instantaneous power-balance-based modulation method with natural power factor correction is proposed for a single-stage bidirectional ac–dc dual active bridge (DAB) converter. The condition for realizing natural power factor at the ac port is derived, and three single-variable modulation methods (namely, phase shift, secondary duty-cycle, and primary duty-cycle) are proposed and discussed subsequently. A 500 W, 110 V/160 V experimental prototype is built to verify the theoretical analysis. It shows that near-unity power factor is naturally realized for bidirectional power transmission under the proposed instantaneous-power-balance-based modulation method without closed-loop control. The highest power factor reaches 0.994 with a minimum total harmonic distortion (THD) of 2.2%. The proposed single-stage bidirectional ac–dc DAB converter adopting the instantaneous-power-balance-based modulation has the advantages of low cost, low control complexity, high reliability, easy implementation, and so on. These advantageous features make the proposed system well suited for vehicle-to-grid systems, energy storage systems, etc.