Optical imaging is highly valued for its superior temporal and spatial resolution. This is particularly important in near-infrared II (NIR-II, 1 000-3 000 nm) imaging, which offers advantages such as reduced tissue absorption, minimal scattering, and low autofluorescence. These characteristics make NIR-II imaging especially suitable for deep tissue visualization, where high contrast and minimal background interference are critical for accurate diagnosis and monitoring. Currently, inorganic fluorescent probes—such as carbon nanotubes, rare earth nanoparticles, and quantum dots—offer high brightness and stability. However, they are hindered by ambiguous structures, larger sizes, and potential accumulation toxicity in vivo. In contrast, organic fluorescent probes, including small molecules and polymers, demonstrate higher biocompatibility but are limited by shorter emission wavelengths, lower quantum yields, and reduced stability. Recently, gold clusters have emerged as a promising class of nanomaterials with potential applications in biocatalysis, fluorescence sensing, biological imaging, and more. Water-soluble gold clusters are particularly attractive as fluorescent probes due to their remarkable optical properties, including strong photoluminescence, large Stokes shifts, and excellent photostability. Furthermore, their outstanding biocompatibility—attributed to good aqueous stability, ultra-small hydrodynamic size, and high renal clearance efficiency—makes them especially suitable for biomedical applications. Gold clusters hold significant potential for NIR-II fluorescence imaging. Atomic-precision gold clusters, typically composed of tens to hundreds of gold atoms and measuring only a few nanometers in diameter, possess well-defined three-dimensional structures and clear spatial coordination. This atomic-level precision enables fine-tuned structural regulation, further enhancing their fluorescence properties. Variations in cluster size, surface ligands, and alloying elements can result in distinct physicochemical characteristics. The incorporation of different atoms can modulate the atomic and electronic structures of gold clusters, while diverse ligands can influence surface polarity and steric hindrance. As such, strategies like alloying and ligand engineering are effective in enhancing both fluorescence and catalytic performance, thereby meeting a broader range of clinical needs. In recent years, gold clusters have attracted growing attention in the biomedical field. Their application in NIR-II imaging has led to significant progress in vascular, organ, and tumor imaging. The resulting high-resolution, high signal-to-noise imaging provides powerful tools for clinical diagnostics. Moreover, biologically active gold clusters can aid in drug delivery and disease diagnosis and treatment, offering new opportunities for clinical therapeutics. Despite the notable achievements in fundamental research and clinical translation, further studies are required to address challenges related to the standardized synthesis and complex metabolic behavior of gold clusters. Resolving these issues will help accelerate their clinical adoption and broaden their biomedical applications.

T7 RNA polymerase (T7 RNAP) is one of the simplest known RNA polymerases. Its unique structural features make it a critical model for studying the mechanisms of RNA synthesis. This review systematically examines the static crystal structure of T7 RNAP, beginning with an in-depth examination of its characteristic “thumb”, “palm”, and “finger” domains, which form the classic “right-hand-like” architecture. By detailing these structural elements, this review establishes a foundation for understanding the overall organization of T7 RNAP. This review systematically maps the functional roles of secondary structural elements and their subdomains in transcriptional catalysis, progressively elucidating the fundamental relationships between structure and function. Further, the intrinsic flexibility of T7 RNAP and its applications in research are also discussed. Additionally, the review presents the structural diagrams of the enzyme at different stages of the transcription process, and through these diagrams, it provides a detailed description of the complete transcription process of T7 RNAP. By integrating structural dynamics and kinetics analyses, the review constructs a comprehensive framework that bridges static structure to dynamic processes. Despite its advantages, T7 RNAP has a notable limitation: it generates double-stranded RNA (dsRNA) as a byproduct. The presence of dsRNA not only compromises the purity of mRNA products but also elicits nonspecific immune responses, which pose significant challenges for biotechnological and therapeutic applications. The review provides a detailed exploration of the mechanisms underlying dsRNA formation during T7 RNAP catalysis, reviews current strategies to mitigate this issue, and highlights recent progress in the field. A key focus is the semi-rational design of T7 RNAP mutants engineered to minimize dsRNA generation and enhance catalytic performance. Beyond its role in transcription, T7 RNAP exhibits rapid development and extensive application in fields, including gene editing, biosensing, and mRNA vaccines. This review systematically examines the structure-function relationships of T7 RNAP, elucidates the mechanisms of dsRNA formation, and discusses engineering strategies to optimize its performance. It further explores the engineering optimization and functional expansion of T7 RNAP. Furthermore, this review also addresses the pressing issues that currently need resolution, discusses the major challenges in the practical application of T7 RNAP, and provides an outlook on potential future research directions. In summary, this review provides a comprehensive analysis of T7 RNAP, ranging from its structural architecture to cutting-edge applications. We systematically examine: (1) the characteristic right-hand domains (thumb, palm, fingers) that define its minimalistic structure; (2) the structure-function relationships underlying transcriptional catalysis; and (3) the dynamic transitions during the complete transcription cycle. While highlighting T7 RNAP’s versatility in gene editing, biosensing, and mRNA vaccine production, we critically address its major limitation—dsRNA byproduct formation—and evaluate engineering solutions including semi-rationally designed mutants. By synthesizing current knowledge and identifying key challenges, this work aims to provide novel insights for the development and application of T7 RNAP and to foster further thought and progress in related fields.

Cardiovascular disease (CVD) remains one of the leading causes of mortality among adults globally, with continuously rising morbidity and mortality rates. Metabolic disorders are closely linked to various cardiovascular diseases and play a critical role in their pathogenesis and progression, involving multifaceted mechanisms such as altered substrate utilization, mitochondrial structural and functional dysfunction, and impaired ATP synthesis and transport. In recent years, the potential role of peroxisome proliferator-activated receptors (PPARs) in cardiovascular diseases has garnered significant attention, particularly peroxisome proliferator-activated receptor alpha (PPARα), which is recognized as a highly promising therapeutic target for CVD. PPARα regulates cardiovascular physiological and pathological processes through fatty acid metabolism. As a ligand-activated receptor within the nuclear hormone receptor family, PPARα is highly expressed in multiple organs, including skeletal muscle, liver, intestine, kidney, and heart, where it governs the metabolism of diverse substrates. Functioning as a key transcription factor in maintaining metabolic homeostasis and catalyzing or regulating biochemical reactions, PPARα exerts its cardioprotective effects through multiple pathways: modulating lipid metabolism, participating in cardiac energy metabolism, enhancing insulin sensitivity, suppressing inflammatory responses, improving vascular endothelial function, and inhibiting smooth muscle cell proliferation and migration. These mechanisms collectively reduce the risk of cardiovascular disease development. Thus, PPARα plays a pivotal role in various pathological processes via mechanisms such as lipid metabolism regulation, anti-inflammatory actions, and anti-apoptotic effects. PPARα is activated by binding to natural or synthetic lipophilic ligands, including endogenous fatty acids and their derivatives (e.g., linoleic acid, oleic acid, and arachidonic acid) as well as synthetic peroxisome proliferators. Upon ligand binding, PPARα activates the nuclear receptor retinoid X receptor (RXR), forming a PPARα-RXR heterodimer. This heterodimer, in conjunction with coactivators, undergoes further activation and subsequently binds to peroxisome proliferator response elements (PPREs), thereby regulating the transcription of target genes critical for lipid and glucose homeostasis. Key genes include fatty acid translocase (FAT/CD36), diacylglycerol acyltransferase (DGAT), carnitine palmitoyltransferase I (CPT1), and glucose transporter (GLUT), which are primarily involved in fatty acid uptake, storage, oxidation, and glucose utilization processes. Advancing research on PPARα as a therapeutic target for cardiovascular diseases has underscored its growing clinical significance. Currently, PPARα activators/agonists, such as fibrates (e.g., fenofibrate and bezafibrate) and thiazolidinediones, have been extensively studied in clinical trials for CVD prevention. Traditional PPARα agonists, including fenofibrate and bezafibrate, are widely used in clinical practice to treat hypertriglyceridemia and low high-density lipoprotein cholesterol (HDL-C) levels. These fibrates enhance fatty acid metabolism in the liver and skeletal muscle by activating PPARα, and their cardioprotective effects have been validated in numerous clinical studies. Recent research highlights that fibrates improve insulin resistance, regulate lipid metabolism, correct energy metabolism imbalances, and inhibit the proliferation and migration of vascular smooth muscle and endothelial cells, thereby ameliorating pathological remodeling of the cardiovascular system and reducing blood pressure. Given the substantial attention to PPARα-targeted interventions in both basic research and clinical applications, activating PPARα may serve as a key therapeutic strategy for managing cardiovascular conditions such as myocardial hypertrophy, atherosclerosis, ischemic cardiomyopathy, myocardial infarction, diabetic cardiomyopathy, and heart failure. This review comprehensively examines the regulatory roles of PPARα in cardiovascular diseases and evaluates its clinical application value, aiming to provide a theoretical foundation for further development and utilization of PPARα-related therapies in CVD treatment.

ObjectiveTobacco-related diseases remain one of the leading preventable public health challenges worldwide and are among the primary causes of premature death. In recent years, accumulating evidence has supported the classification of nicotine addiction as a chronic brain disease, profoundly affecting both brain structure and function. Despite the urgency, effective diagnostic methods for smoking addiction remain lacking, posing significant challenges for early intervention and treatment. To address this issue and gain deeper insights into the neural mechanisms underlying nicotine dependence, this study proposes a novel graph neural network framework, termed TI-GNN. This model leverages functional magnetic resonance imaging (fMRI) data to identify complex and subtle abnormalities in brain connectivity patterns associated with smoking addiction. MethodsThe study utilizes fMRI data to construct functional connectivity matrices that represent interaction patterns among brain regions. These matrices are interpreted as graphs, where brain regions are nodes and the strength of functional connectivity between them serves as edges. The proposed TI-GNN model integrates a Transformer module to effectively capture global interactions across the entire brain network, enabling a comprehensive understanding of high-level connectivity patterns. Additionally, a spatial attention mechanism is employed to selectively focus on informative inter-regional connections while filtering out irrelevant or noisy features. This design enhances the model’s ability to learn meaningful neural representations crucial for classification tasks. A key innovation of TI-GNN lies in its built-in causal interpretation module, which aims to infer directional and potentially causal relationships among brain regions. This not only improves predictive performance but also enhances model interpretability—an essential attribute for clinical applications. The identification of causal links provides valuable insights into the neuropathological basis of addiction and contributes to the development of biologically plausible and trustworthy diagnostic tools. ResultsExperimental results demonstrate that the TI-GNN model achieves superior classification performance on the smoking addiction dataset, outperforming several state-of-the-art baseline models. Specifically, TI-GNN attains an accuracy of 0.91, an F1-score of 0.91, and a Matthews correlation coefficient (MCC) of 0.83, indicating strong robustness and reliability. Beyond performance metrics, TI-GNN identifies critical abnormal connectivity patterns in several brain regions implicated in addiction. Notably, it highlights dysregulations in the amygdala and the anterior cingulate cortex, consistent with prior clinical and neuroimaging findings. These regions are well known for their roles in emotional regulation, reward processing, and impulse control—functions that are frequently disrupted in nicotine dependence. ConclusionThe TI-GNN framework offers a powerful and interpretable tool for the objective diagnosis of smoking addiction. By integrating advanced graph learning techniques with causal inference capabilities, the model not only achieves high diagnostic accuracy but also elucidates the neurobiological underpinnings of addiction. The identification of specific abnormal brain networks and their causal interactions deepens our understanding of addiction pathophysiology and lays the groundwork for developing targeted intervention strategies and personalized treatment approaches in the future.

Aim To prepare tripterygium glycoside nanoparticles and probe into their therapeutic effect on collagen-induced arthritis ( CIA) rats. Methods Tripterygium glycosides polyglycoside nanoparticles were prepared by thin film dispersion method and their quality was assessed. The CIA model was established and drug intervention performed. The body weight, toe swelling degree and arthritis index were measured. The pathological changes of the organs, knee and ankle synovium were observed. The serum levels of kidney function and inflammatory cytokine expression were detected in rats. Results The prepared tripterygium wil-fordii polyglycoside nanoparticles were round particles with uniform distribution and stable properties under electron microscope. Compared with the model group, the swelling of the left and right toes of medication group significantly decreased (P < 0. 01), and the ar-thritis index markedly decreased ( P < 0. 01). Among them, the efficacy of the TG-NPs group was better than that of the TG group. Compared with the normal group, the indexes of heart, spleen, kidney and testis all significantly decreased (P <0. 05, P<0.01). TG-NPs group had a significantly reduced pathological ankle-joint injury in knee cartilage and increased apoptotic synovial cells. Compared with the model group, the serum levels of ALT and BUN and CRE in TG-NPs group were significantly lower (P < 0. 05 ), and IL-1β, TNF-α and IL-6 levels decreased significantly (P <0. 05). Conclusions TG-NPs have good therapeutic effect on CIA through induction of synovial cell apoptosis and decrease of the expression of inflammatory cytokines. By intravenous injection of blood circula-tion, slow and controlled release of drugs can be achieved, the first pass effect caused by oral drug can be avoided, the viscera toxicity can be reduced, which provides an experimental basis for the development of new nanoagents for the treatment of rheumatoid arthritis.

Aim To explore the effect of exogenous hydrogen sulfide ( H2 S ) on hypoxia/reoxygenation ( H/R) injury in glomerular mesangial cells and elucidate its relevant mechanism. Methods H/R induced mouse mesangial cell line ( SV40MES13 ) to establish cell damage model. Cell viability was detected by cell proliferation kit ( CCK8 ), the content of H

Based on the long bud stage phenotype of a new Lonicera japonica Flos variety "Huajin 6", using "Huajin 6" and "Da Mao Hua" as materials, probing the mechanism of its phenotype formation. Detection of endogenous Jasmonic acid hormones (JAs) content; the genes related to jasmonic acid (JA) synthesis were identified by transcriptome analysis of Lonicera japonica; flower buds and flowers of "Huajin 6" and "Da Mao Hua" were collected at different periods, and the qRT-PCR (quantitative real-time PCR) technique was used to analyze the trend of the expression of synthesis-related enzyme genes in Lonicera japonica Flos during the bud stage. The study found that the content of JAs in "Huajin 6" Lonicera japonica Flos was significantly lower than that in "Da Mao Hua"; applying exogenous methyl-jasmonate (MeJA) to "Huajin 6" can restore its flowering phenotype, making it close to wild type Lonicera japonica Flos; there are significant differences in the expression of two allene oxide synthase genes (AOS), three lipoxygenase genes (LOX), and two allene oxide cyclase genes (AOC) in the flowers and buds of "Huajin 6" and "Da Mao Hua" at different periods. It is hypothesized that the low expression of JA synthesis-related enzyme genes in " Huajin 6" leads to the blockage of JA synthesis, which causes the formation of the long bud phenotype. This study laid a certain foundation for the genetic breeding of Lonicera japonica, provided a new idea for the improvement of Lonicera japonica varieties, and provided a reference for the study of JAs in plant flower organs.

Objective: To compare the relative effectiveness of different exercise modalities on inhibitory control in children with attention deficit hyperactivity disorder (ADHD), so as to provide an evidence based basis for the development of effective exercise prescriptions. Methods: The databases of China National Knowledge Internet (CNKI), Pubmed, Web of Science, Embase, and Cochrane were searched to screen the literature of randomized controlled trials of exercise interventions for inhibitory control in children with ADHD up to December 31, 2022. The Cochrane risk of bias assessment tool was used for methodological quality assessment, and Stata 17.0 software was used for network Meta analysis, standardized mean difference ( SMD ) and 95% CI were used as the effect indicators to compare the difference in effect between interventions and rank the effect. Results: Twenty two papers with a total of 1 134 participants aged 6-14.5 years were finally included. Network Meta analysis showed that the impact effects of physical and mental exercises [ SMD (95% CI )=1.08(0.50-1.66)], cognition+exercise [ SMD (95% CI ) =0.81(0.13-1.48)], and ball games [ SMD (95% CI )= 1.54(0.99-2.09)] were significantly superior to that of control group, and the ball games had a significantly better effect than single aerobic exercise [ SMD (95% CI )=1.02(0.20-1.84)], and combined exercises [ SMD (95% CI )=1.08( 0.28 -1.88)]( P < 0.05 ). The results of surface under the cumulative ranking (SUCRA) showed that ball games might be the best means to improve inhibitory control in children with ADHD(SUCRA=95.3). Conclusion It is recommended to appropriately increase ball sports in sports activities to more effectively improve the inhibitory control of children with ADHD.

Objective To compare the differences in virulence-related factor aspartate protease,biofilm formation,and gene expression among clinical isolates of Candida parapsilosis(C.parapsilosis).Methods Gene sequencing and microsatellite typing(MT)method were adopted to identify C.parapsilosis isolated from patients with clinical fungal infection.The production of secreted aspartate protease and biofilm formation ability of each strain were de-tected,and the expression of biofilm formation related-genes BCR1,EFG1,and HWP1,as well as aspartate prote-ase virulence genes SAPP1,SAPP2,SAPP3 were compared among the strains.Results A total of 8 clinically iso-lated C.parapsilosis strains were collected,all of which were identified as genotype Ⅰ.Based on microsatellite ty-ping results,8 clinical strains were divided into 4 microsatellite types.G1,G2,and G3 strains isolated from the urine,peripherally inserted central catheters(PICC),and blood of patient A were of different subtypes.J1,J2,J3,J4,and J5 strains were of the same type,and isolated from blood specimens of patient B at different periods.All 8 clinical strains could form biofilm,and their biofilm formation ability was higher than that of the standard strain of C.parapsilosis(ATCC 22019).G1,G3 and J5 strains had strong biofilm formation ability,J1,J2,J3,and J4 strains had moderate biofilm formation ability,and G2 strain had weak biofilm formation ability.All of the eight clinical isolates secreted aspartate protease,and their in vitro expression levels of the enzyme were higher than that of the standard strain(ATCC 22019).G3,G1,and G2 strains showed low,moderate,and high in vitro enzyme expression respectively,with statistical differences(all P＜0.05).Enzyme expressed moderately in J1 and J5 strains,and highly in J2,J3,and J4 strains.Difference between moderate and high expressions was statistically significant(P＜0.05).The expression levels of biofilm formation genes BCR1,EFG1,and HWP1 in various strains isolated from patients A and B increased.In strains isolated from patient A,the expression level of EFG1 gene in G1 strain was higher than that in G2 strain(P＜0.05).There was no statistically significant difference in BCR1,EFG1,and HWP1 gene expression levels among strains isolated from patient B.The expression levels of as-partate protein genes(SAPP1,SAPP2,and SAPP3)in various strains isolated from patients A and B increased.The expression levels of SAPP1 and SAPP2 in strain G1 were higher than those in G2 and G3(both P＜0.05).There was no statistically significant difference in the expression levels of SAPP1,SAPP2,and SAPP3 genes in strains from patient B.Conclusion Clinical isolates of C.parapsilosis have higher biofilm formation and aspartate protease production abilities than standard strain.The expression of virulence factors varies among strains isolated from different specimens,while there is no significant difference in the expression of virulence factors among strains isolated at different periods.Patients may have been infected with different MT types of C.parapsilosis in multiple sites during the same period.

Objective To analyze the influencing factors for catheter-associated infection(CAI)in chemotherapy treated patients after indwelling peripherally inserted central catheter(PICC)based on a random forest model.Methods 400 tumor patients who received chemotherapy and PICC were selected and divided into the training set(n=300)and the test set(n=100)in a 3∶1 ratio through computer-generated random number.Patients in the training set were subdivided into the non-infection group and the infection group based on the occurrence of infec-tion.Clinical data from two groups of patients were compared.Influencing factors for the occurrence of CAI after PICC were analyzed with multivariate logistic regression model and the integrated classification algorithm of random forest model,and the predictive performance of the two methods was compared.Results Among 300 chemotherapy treated patients in the training set,32 cases(10.67％)experienced CAI.Compared with the non-infection group,patients in the infection group had more single punctures for catheterization,longer PICC retention time,larger pro-portion of catheter movement,larger proportion of complication with diabetes,higher frequency of dressing chan-ges,lower white blood cell count and immune function(all P＜0.05).PICC retention time,catheter movement,complication with diabetes,dressing change frequency,white blood cell(WBC)and immune function were inde-pendent influencing factors for CAI after PICC(all P＜0.05).The random forest model showed that ranking by the importance of different influencing factors was as following:PICC retention time,catheter movement,complication with diabetes,WBC,dressing change frequency and immune function.The integrated classification algorithm of random forest model for predicting the occurrence of CAI in chemotherapy treated patients showed that the area un-der the receiver operating characteristic(ROC)curve(AUC)was 0.872,which had better prediction performance compared with the logistic regression model(AUC=0.791).Conclusion PICC retention time,catheter movement,complicated with diabetes,dressing change frequency,WBC level and immune function are independent influencing factors for CAI in chemotherapy treated patients.The integrated classification algorithm of random forest model can be used to predict CAI in chemotherapy treated patients,and its prediction performance is better than that of the logistic regression model.