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.

Objective Pancreatic cancer(PC)is a malignant tumor of the digestive tract that is difficult to diagnose early,easily metastasizes and relapses,and resistant to conventional chemotherapy.PC is a very difficult disease to treat.The key regulatory factors of PC resistance,such as epithelial-mesenchymal transition phenotypic cells,tumor stem cells,and miRNAs,have been reviewed in the past few years,and some new regulatory factors have been discovered as supplements.This review mainly focuses on the characteristics and properties of the key regulatory factors of PC chemotherapy resistance including long noncoding RNAs,nuclear factor KB and exosomes,drug resistance mechanisms,and treatment related strategies,and future treatment directions were predicted.

Objective To observe the clinical efficacy and safety of spironolactone combined with sacubitril/valsartan in the treatment of patients with hypertensive nephropathy.Methods The patients with hypertensive nephropathy were randomly divided into control group and treatment group.The control group was treated with sacubitril/valsartan(100-200 mg·d-1 in the morning),and treatment group was combined with low-dose spironolactone treatment(20 mg·d-1 in the morning)on the basis of control group.Both groups were treated continuously for 12 weeks.The clinical efficacy was compared;the blood pressure,urinary microalbumin(mAlb),urinary β2 microglobulin(β2-MG)and serum cystatin C(Cys-C),transforming growth factor-β1(TGF-β1),connective tissue growth factor(CTGF)and angiotensin Ⅱ(Ang Ⅱ)and adverse drug reactions were observed before and after treatment.Results There were 87 cases in treatment group and 86 cases in control group were included respectively.After treatment,the total effective rates in treatment group and control group were 95.40％(83 cases/87 cases)and 82.56％(71 cases/86 cases),with significant difference(P＜0.05).After treatment,the systolic blood pressure values in treatment group and control group were(124.65±9.65)and(130.27±8.93)mmHg,the diastolic blood pressure values were(75.08±7.14)and(80.45±7.35)mmHg,urinary mAlb levels were(42.58±5.65)and(51.28±6.64)mg·L-1,urinary β2-MG levels were(0.46±0.17)and(0.75±0.25)mg·L-1,24 h urinary protein quantitation levels were(138.49±46.64)and(216.48±65.27)mg,serum Cys-C levels were(0.63±0.26)and(0.85±0.24)mg·L-1,TGF-β1 levels were(98.67±21.43)and(112.46±26.72)pg·mL-1,CTGF levels were(1 206.54±236.56)and(1 340.51±248.25)pg·mL-1,Ang Ⅱ levels were(101.55±17.62)and(115.65±20.08)pg·mL-1,all with significant difference(all P＜0.05).The incidence of adverse drug reactions in treatment group and control group were 6.90％(6 cases/87 cases)and 2.33％(2 cases/86 cases),with no significant difference(P＞0.05).Conclusion Compared with sacubitril/valsartan alone,spironolactone combined with sacubitril/valsartan can better reduce blood pressure,improve renal function and delay progression of renal fibrosis in the treatment of hypertensive nephropathy,and has definite efficacy,with good safety.

The advent of gene editing represents one of the most transformative breakthroughs in life science, making genome manipulation more accessible than ever before. While traditional CRISPR/Cas-based gene editing, which involves double-strand DNA breaks (DSBs), excels at gene disruption, it is less effective for accurate gene modification. The limitation arises because DSBs are primarily repaired via non-homologous end joining (NHEJ), which tends to introduce indels at the break site. While homology-directed repair (HDR) can achieve precise editing when a donor DNA template is provided, the reliance on DSBs often results in unintended genome damage. HDR is restricted to specific cell cycle phases, limiting its application. Currently, gene editing has evolved to unprecedented levels of precision without relying on DSB and HDR. The development of innovative systems, such as base editing, prime editing, and CRISPR-associated transposases (CASTs), now allow for precise editing ranging from single nucleotides to large DNA fragments. Base editors (BEs) enable the direct conversion of one nucleotide to another, and prime editors (PEs) further expand gene editing capabilities by allowing for the insertion, deletion, or alteration of small DNA fragments. The CAST system, a recent innovation, allows for the precise insertion of large DNA fragments at specific genomic locations. In recent years, the optimization of these precise gene editing tools has led to significant improvements in editing efficiency, specificity, and versatility, with advancements such as the creation of base editors for nucleotide transversions, enhanced prime editing systems for more efficient and precise modifications, and refined CAST systems for targeted large DNA insertions, expanding the range of applications for these tools. Concurrently, these advances are complemented by significant improvements in in vivo delivery methods, which have paved the way for therapeutic application of precise gene editing tools. Effective delivery systems are critical for the success of gene therapies, and recent developments in both viral and non-viral vectors have improved the efficiency and safety of gene editing. For instance, adeno-associated viruses (AAVs) are widely used due to their high transfection efficiency and low immunogenicity, though challenges such as limited cargo capacity and potential for immune responses remain. Non-viral delivery systems, including lipid nanoparticles (LNPs), offer an alternative with lower immunogenicity and higher payload capacity, although their transfection efficiency can be lower. The therapeutic potential of these precise gene editing technologies is vast, particularly in treating genetic disorders. Preclinical studies have demonstrated the effectiveness of base editing in correcting genetic mutations responsible for diseases such as cardiomyopathy, liver disease, and hereditary hearing loss. These technologies promise to treat symptoms and potentially cure the underlying genetic causes of these conditions. Meanwhile, challenges remain, such as optimizing the safety and specificity of gene editing tools, improving delivery systems, and overcoming off-target effects, all of which are critical for their successful application in clinical settings. In summary, the continuous evolution of precise gene editing technologies, combined with advancements in delivery systems, is driving the field toward new therapeutic applications that can potentially transform the treatment of genetic disorders by targeting their root causes.

Through a compound induction method, combined with neurobehavioral, macroscopic characterization and objective pathological evaluation indicators, a murine depression model of liver depression transforming into fire syndrome was constructed and confirmed. The model was constructed using a combination of sleep deprivation, light exposure, and alternate-day food deprivation. Evaluation was conducted at three levels: face validity, constructs validity, and predictive validity. The establishment of the liver depression transforming into fire syndrome depression model was further validated through the counterproof of traditional Chinese medicine formulas. In terms of face validity, compared to the control group, mice in the model group exhibited typical depressive symptoms in neurobehavioral assessments; the general observation of the model group mice reveals disheveled and lackluster fur, along with delayed and easily agitated responses. Additionally, there is a substantial increase in water consumption. In the sleep phase detection of mouse, the model group showed a significant increase in the proportion of time spent in the wake phase during sleep, accompanied by a significant decrease in the proportions of time spent in both non-rapid eye movement (NREM) and rapid eye movement (REM) sleep phases. There are significant differences in physiological indicators such as average blood flow velocity, blood flow rate, tongue, urine, and claw color (r values) in the internal carotid artery. Structural validity demonstrated that levels of 5-hydroxytryptamine (5-HT), dopamine (DA), and γ-aminobutyric acid (GABA) in the hippocampus of model mice decreased significantly, while acetylcholine (ACh), tryptophan (Try), and glutamic acid (Glu) levels increased significantly. Treatment with Danzhi Xiaoyao San led to varying degrees of restoration in the aforementioned neurotransmitters. In terms of predictive validity, the antidepressant paroxetine effectively ameliorated depressive behaviors in the model mice, and the classic formula Danzhi Xiaoyao San demonstrated varying degrees of improvement in depression-related indicators. In conclusion, this study has established a novel animal model of liver-stagnation with the fire depression, thereby expanding the repertoire of traditional Chinese medicine depression models. This development contributes to the diversification of melancholic syndrome models in Chinese medicine, offering a broader spectrum of options for scientific exploration, efficacy evaluation, and drug screening in the future prevention and treatment of depression with traditional Chinese medicine. Animal experiments were conducted with the approval and supervision of the Animal Ethics Committee of Jiangxi University of Traditional Chinese Medicine (ethics number: 20230313040).

The purpose of this study was to enrich the genomic information and provide a basis for further development and utilization of Polygonatum kingianum. The fresh rhizome of P. kingianum was used as the experimental material, and the full-length transcriptome was sequenced by PacBio Sequel platform. The final measured polymerase reads were 1 120 485, with a total of 77.73 GB of data. In NR database, 41 864 homologous sequence alignments were aligned to 5 species; 40 506 were annotated in the KOG database and classified into 26 categories based on their functionality; 69 060 GO annotated 32 functional groups divided into 3 categories: cellular components, molecular functions, and biological processes; 45 779 annotations were added to 145 metabolic pathways in the KEGG database. Among them, there are 127 identified transcripts related to polysaccharide synthesis in the glycolysis/gluconeogenesis metabolic pathway, 144 in the starch and sucrose metabolic pathway, 85 in the amino acid sugar and nucleotide sugar metabolic pathway, and 69 in the fructose and mannose metabolic pathway. In addition, 1 781 transcription factors were detected, distributed in 37 transcription factor families; 180 293 SSR loci were detected, among which single base repeats accounted for the most, accounting for 30.48% of all base repeats, and at least five base repeats, accounting for only 0.14% of single base repeats. The results of this study provide important data supporting for enriching the genomic information of P. kingianum and exploring its effective biosynthetic pathway.

This paper applied gas chromatography-mass spectrometry (GC-MS), network pharmacology and nuclear magnetic resonance hydrogen spectroscopy (¹H NMR) metabolomics techniques to study the material basis and mechanism of action of Ning Shen Essential Oil in anti-insomnia. The main volatile components of Ning Shen Essential Oil were analyzed by gas chromatography-mass spectrometry (GC-MS), and the insomnia-related targets were predicted using the Traditional Chinese Medicine Systematic Pharmacology Database and Analytical Platform (TCMSP) and the databases of GeneCards, OMIM and Drugbank. The insomnia model of rats was replicated by intraperitoneal injection of 4-chloro-DL-phenylalanine (PCPA). Animal experiments were approved by the Animal Ethics Committee of Shandong University of Traditional Chinese Medicine (Ethics No.: SDUTCM20221025010). The modulating effect of Compound Ning Shen Essential Oil on anxiety behavior of rats was evaluated by behavioral related indexes. The serum levels of corticotropin-releasing hormone (CRH), adrenotropic corticotropic hormone (ACTH) and melatonin (MT) were measured by enzyme-linked immunoassay (ELISA). Rat serum and hippocampus were taken for nuclear magnetic resonance (¹H NMR) metabolomics to detect the changes of endogenous metabolites in rat serum hippocampus, to designate the differential metabolites and to construct metabolic pathways. The results showed that the exercise distance in the open field experiment and the number of times and time to enter the open arm in the elevated cross maze experiment of the rats in the model group were significantly reduced (P < 0.05, P < 0.01). The behavioral indexes of rats improved to different degrees after the administration of Ning Shen Essential Oil. The serum CRH and ACTH levels of rats in the model group increased significantly (P < 0.05, P < 0.01), and the MT level decreased significantly (P < 0.01); After the intervention, serum CRH and ACTH levels were reduced to different degrees, and MT levels could be regressed. ¹H NMR metabolomics screened 10 potential biomarkers related to insomnia, which involved in 6 potential metabolic pathways. A total of 35 components of Ning Shen Essential Oil were detected by GC-MS, the main component targets of Ning Shen Essential Oil and insomnia disease targets were intersected, a total of 172 intersecting genes were screened, and 26 core targets were identified. The study demonstrated that Ning Shen Essential Oil had protective effects against PCPA-induced insomnia in rats, which was probably correlated with regulation of the hypothalamic-pituitary-adrenal axis (HPA) related hormones and metabolism of amino acids, lipids and choline.