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.

Objective To investigate the factors influencing the occurrence of coma in patients with acute basilar artery occlusion(BAO)and the favorable prognosis in the coma patients after receiving mechanical thrombectomy(MT).Methods The clinical data and imaging materials of 102 patients with acute BAO,who received MT at the First Affiliated Hospital of Soochow University of China from January 2016 to April 2024,were retrospectively analyzed.According to whether the patient had a coma or not on admission,the patients were divided into non-coma group and coma group.The clinical data and imaging findings were compared between the two groups.Multivariate logistic regression analysis was performed to identify the factors influencing the occurrence of coma.The modified Rankin scale(mRS)score was used to evaluate 90-day clinical prognosis.The patients of coma group were further divided into favorable prognosis subgroup(mRS:0-3 points)and poor prognosis subgroup(mRS:4-6 points).Baseline date and surgical data were compared between the two subgroups,and multivariate logistic regression analysis was conducted to identify the factors associated with a favorable prognosis in coma patients after receiving mechanical thrombectomy.Results Of the 102 patients with acute BAO,54 were in unconscious state on admission(coma group)and 48 were in conscious state(non-coma group)on admission.Multivariate logistic regression analysis revealed that coexisting cardiovascular diseases with severe cardiac insufficiency or moderate to severe coronary artery stenosis(P=0.009)and low BATMAN score(P＜0.001)were the independent risk factors for the occurrence of coma in acute BAO patients.Among the 54 unconscious patients who received MT treatment,favorable prognosis was obtained in 13 and poor prognosis was seen in 41.Multivariate logistic regression analysis indicated that high BATMAN score(P=0.017)was the independent influencing factor for favorable prognosis in acute BAO patients with coma after receiving MT therapy.Conclusion Acute BAO patients having coexisting cardiovascular diseases with severe cardiac insufficiency or moderate to severe coronary artery stenosis or having low BATMAN score are more likely to develop coma.Acute BAO patients with coma having high BATMAN score are more likely to obtain a favorable prognosis after receiving MT therapy.

Mitochondria, functioning not only as the central hub of cellular energy metabolism but also as semi-autonomous organelles, orchestrate cellular fate decisions through their endogenous mitochondrial DNA (mtDNA), which encodes core components of the electron transport chain. Emerging research has identified microRNAs localized within mitochondria, termed mitochondria-located microRNAs (mitomiRs). Recent studies have revealed that mitomiRs are transcribed from nuclear DNA (nDNA), processed and matured in the cytoplasm, and subsequently transported into mitochondria. mitomiRs regulate mtDNA through diverse mechanisms, including modulation of mtDNA expression at the translational level and direct binding to mtDNA to influence transcription. Aberrant expression of mitomiRs leads to mitochondrial dysfunction and contributes to the pathogenesis of metabolic diseases. Restoring mitomiR expression to physiological levels using mitomiRs mimics or inhibitors has been shown to improve mitochondrial function and alleviate related diseases. Consequently, the regulatory mechanisms of mitomiRs have become a major focus in mitochondrial research. Given that mitomiRs are located in mitochondria, targeted delivery strategies designed for mtDNA can be adapted for the delivery of mitomiRs mimics or inhibitors. However, numerous intracellular and extracellular barriers remain, highlighting the need for more precise and efficient delivery systems in the future. The regulation of mtDNA expression mediated by mitomiRs not only expands our understanding of miRNA functions in post-transcriptional gene regulation but also provides promising molecular targets for the treatment of mitochondrial-related diseases. This review systematically summarizes recent research progress on mitomiRs in regulating mtDNA expression and discusses the underlying mechanisms of mitomiRs-mtDNA interactions. Additionally, it provides new perspectives on precision therapeutic strategies, with a particular emphasis on mitomiRs-based regulation of mitochondrial function in mitochondrial-related diseases.

Activity cliffs (ACs) are generally defined as pairs of similar compounds that only differ by a minor structural modification but exhibit a large difference in their binding affinity for a given target. ACs offer crucial insights that aid medicinal chemists in optimizing molecular structures. Nonetheless, they also form a major source of prediction error in structure-activity relationship (SAR) models. To date, several studies have demonstrated that deep neural networks based on molecular images or graphs might need to be improved further in predicting the potency of ACs. In this paper, we integrated the triplet loss in face recognition with pre-training strategy to develop a prediction model ACtriplet, tailored for ACs. Through extensive comparison with multiple baseline models on 30 benchmark datasets, the results showed that ACtriplet was significantly better than those deep learning (DL) models without pre-training. In addition, we explored the effect of pre-training on data representation. Finally, the case study demonstrated that our model's interpretability module could explain the prediction results reasonably. In the dilemma that the amount of data could not be increased rapidly, this innovative framework would better make use of the existing data, which would propel the potential of DL in the early stage of drug discovery and optimization.

OBJECTIVE: To investigate the role and mechanism of the cyclic guanosine monophosphate-adenosine monophosphate synthase/stimulator of interferon gene (cGAS/STING) pathway in oleic acid-induced acute lung injury (ALI) in mice. METHODS: Male wild-type C57BL/6J mice were randomly divided into five groups (each n = 10): normal control group, ALI model group, and 5, 50, 500 μg/kg inhibitor pretreatment groups. The ALI model was established by tail vein injection of oleic acid (7 mL/kg), while the normal control group received no intervention. The inhibitor pretreatment groups were intraperitoneally injected with the corresponding doses of cGAS inhibitor RU.521 respectively 1 hour before modeling. At 24 hours post-modeling, blood was collected, and mice were sacrificed. Lung tissue pathological changes were observed under light microscopy after hematoxylin-eosin (HE) staining, and pathological scores were assessed. Western blotting was used to detect the protein expressions of cGAS, STING, phosphorylated TANK-binding kinase 1 (p-TBK1), phosphorylated interferon regulatory factor 3 (p-IRF3), and phosphorylated nuclear factor-κB p65 (p-NF-κB p65) in lung tissue. Immunohistochemistry was performed to observe STING and p-NF-κB positive expressions in lung tissue. Serum interferon-β (IFN-β) levels were measured by enzyme-linked immunosorbent assay (ELISA). RESULTS: Compared with the normal control group, the ALI model group exhibited significant focal alveolar thickening, intra-alveolar hemorrhage, pulmonary capillary congestion, and neutrophil infiltration in the pulmonary interstitium and alveoli, along with markedly increased pathological scores (10.33±0.58 vs. 1.33±0.58, P < 0.05). Protein expressions of cGAS, STING, p-TBK1, p-IRF3, and p-NF-κB p65 in lung tissue significantly increased [cGAS protein (cGAS/β-actin): 1.24±0.02 vs. 0.56±0.02, STING protein (STING/β-actin): 1.27±0.01 vs. 0.55±0.01, p-TBK1 protin (p-TBK1/β-actin): 1.34±0.03 vs. 0.22±0.01, p-IRF3 protein (p-IRF3/β-actin): 1.23±0.02 vs. 0.36±0.01, p-NF-κB p65 protein (p-NF-κB p65/β-actin): 1.30±0.02 vs. 0.53±0.02, all P < 0.05], positive expressions of STING and p-NF-κB in lung tissue were significantly elevated [STING (A value): 0.51±0.03 vs. 0.30±0.07, p-NF-κB (A value): 0.57±0.05 vs. 0.31±0.03, both P < 0.05], and serum IFN-β levels were also significantly higher (ng/L: 256.02±3.84 vs. 64.15±1.17, P < 0.05). The cGAS inhibitor pretreatment groups showed restored alveolar structural integrity, reduced inflammatory cell infiltration, and decreased hemorrhage area, along with dose-dependent lower pathological scores as well as the protein expressions of cGAS, STING, p-TBK1, p-IRF3 and p-NF-κB p65 in lung tissue, with significant differences between the 500 μg/kg inhibitor group and ALI model group [pathological score: 2.67±0.58 vs. 10.33±0.58, cGAS protein (cGAS/β-actin): 0.56±0.03 vs. 1.24±0.02, STING protein (STING/β-actin): 0.67±0.03 vs. 1.27±0.01, p-TBK1 protein (p-TBK1/β-actin): 0.28±0.01 vs. 1.34±0.03, p-IRF3 protein (p-IRF3/β-actin): 0.32±0.01 vs. 1.23±0.02, p-NF-κB p65 protein (p-NF-κB p65/β-actin): 0.63±0.01 vs. 1.30±0.02, all P < 0.05]. Compared with the ALI model group, positive expressions of STING and p-NF-κB in lung tissue were significantly reduced in the 500 μg/kg inhibitor group [STING (A value): 0.40±0.01 vs. 0.51±0.03, p-NF-κB (A value): 0.43±0.02 vs. 0.57±0.05, both P < 0.05], and serum IFN-β levels were also markedly reduced (ng/L: 150.03±6.19 vs. 256.02±3.84, P < 0.05). CONCLUSIONS The cGAS/STING pathway is activated in oleic acid-induced ALI, leading to exacerbated inflammatory responses and increased lung damage. RU.521 can inhibit cGAS, thereby down-regulating the expression of pathway proteins and cytokines, and providing protection to lung tissue.
Animals ; Acute Lung Injury/chemically induced* ; Male ; Nucleotidyltransferases/metabolism* ; Mice ; Signal Transduction ; Mice, Inbred C57BL ; Membrane Proteins/metabolism* ; Oleic Acid/adverse effects* ; Transcription Factor RelA/metabolism* ; Lung/pathology* ; Interferon Regulatory Factor-3/metabolism* ; Disease Models, Animal

Accurate prediction of drug-target interactions (DTIs) plays a pivotal role in drug discovery, facilitating optimization of lead compounds, drug repurposing and elucidation of drug side effects. However, traditional DTI prediction methods are often limited by incomplete biological data and insufficient representation of protein features. In this study, we proposed KG-CNNDTI, a novel knowledge graph-enhanced framework for DTI prediction, which integrates heterogeneous biological information to improve model generalizability and predictive performance. The proposed model utilized protein embeddings derived from a biomedical knowledge graph via the Node2Vec algorithm, which were further enriched with contextualized sequence representations obtained from ProteinBERT. For compound representation, multiple molecular fingerprint schemes alongside the Uni-Mol pre-trained model were evaluated. The fused representations served as inputs to both classical machine learning models and a convolutional neural network-based predictor. Experimental evaluations across benchmark datasets demonstrated that KG-CNNDTI achieved superior performance compared to state-of-the-art methods, particularly in terms of Precision, Recall, F1-Score and area under the precision-recall curve (AUPR). Ablation analysis highlighted the substantial contribution of knowledge graph-derived features. Moreover, KG-CNNDTI was employed for virtual screening of natural products against Alzheimer's disease, resulting in 40 candidate compounds. 5 were supported by literature evidence, among which 3 were further validated in vitro assays.
Alzheimer Disease/drug therapy* ; Biological Products/therapeutic use* ; Humans ; Neural Networks, Computer ; Machine Learning ; Drug Discovery/methods* ; Algorithms ; Drug Evaluation, Preclinical/methods*

The medical mask,which is used as an important tool of preventing the spread of respiratory diseases,can effectively block the transmission of biological aerosols.The detection for the filtration efficiency of bacteria in medical mask is particular importance.The Andersen sampler,is one kind of device that samples microbial aerosols,is widely used in the inspection for the filtration efficiency for bacteria in medical masks.It mainly consists of six impactors with different pore sizes.It simulates the deposition process of the most of particles at different positions in respiratory system through the bacterial particles in biological aerosols impact respectively the surface of petri dishes with agar under different pore sizes.This paper explored the development background,structure and sampling principle,operation and counting procedures of the Andersen sampler,as well as its application and importance in the inspection for the filtration efficiency for bacteria in medical mask.

Aim To study the effect of evodiamine(EVO)regulating forkhead box protein Ml(FOXM1)on the proliferation and apoptosis of colorectal cancer-resistant cells HCT8/5-FU.Methods CCK-8 assay and EdU assay were used to detect the effect of EVO on cell proliferation ability.Clone formation assay was employed to detect the effect of EVO on the clone for-mation ability of cells.Flow cytometric counting was applied to detect apoptosis.Western blot was utilized to detect the expression of cellular Bcl-2,Bax,FOXM1,β-catenin,c-MYC,and CyclinD1;Molecular docking was used to explore the EVO-FOXM1 interac-tion.Nude mouse transplant tumor model was estab-lished to validate the effect of EVO on HCT8/5-FU cells in vivo.Results CCK-8 assay showed that EVO inhibited the proliferation of HCT8/5-FU cells in a time-and concentration-dependent manner.EdU assay found that the newly proliferated cells in the EVO-trea-ted group were significantly reduced.The results of the clone formation assay showed that EVO inhibited the clone-forming ability of HCT8/5-FU cells.Flow cyto-metric counting found that apoptosis rate of the cells in the EVO group significantly increased.Western blot showed that FOXM1 and β-catenin were significantly highly expressed in HCT8/5-FU cells,and EVO down-regulated the expression of FOXM1,β-cateniin,c-MYC,CyclinD1,and Bcl-2,and up-regulated the ex-pression of Bax.Molecular docking revealed strong in-teractions between EVO and FOXM1.The in vivo ex-perimental results demonstrated that EVO exerted a substantial inhibitory effect on the growth of subcutane-ously implanted HCT8/5-FU xenograft tumors and regulated the expression of related proteins.HE stai-ning revealed significant nuclear consolidation and fragmentation of tumor cells in the EVO group.Con-clusions The findings suggest that EVO could sup-press the activation of the Wnt signaling pathway through a mechanism involving the downregulation of FOXM1 protein expression,thus inhibiting the prolifer-ation of HCT8/5-FU cells and induce their apoptosis.

Aim To investigate the effects of Mdivi-1 on A1 astrocyte activation and its associated signaling molecules.Methods CTX-TNA2 astrocytes were di-vided into the control,ACM,and low-,medium-,and high-dose Mdivi-1 groups based on concentration screening via CCK-8 assay.ACM,a DMEM high-glu-cose medium containing preset concentrations of IL-1α,TNF-α,and C1q,was used to induce A1 activa-tion.The ACM group was stimulated with ACM for 24 hours.Mdivi-1 groups were pretreated with correspond-ing concentrations of Mdivi-1 for 2 hours,followed by ACM stimulation for 24 hours.Real-time quantitative PCR and Western blot were employed to assess mRNA levels and protein expression of IL-1β,C3,and iNOS in all groups.Immunofluorescence and Western blot were used to detect the expression of signaling molecules NLRP3,caspase-1,and ASC.DHE labeling was used to assess and flow cytometry was used to examine reac-tive oxygen species(ROS)levels.Results The CCK-8 assay identified 5,10,and 25 μmol·L-1as ap-propriate concentrations for Mdivi-1 intervention in CTX-TNA2 cells.Real-time quantitative PCR and Western blot results indicated that,compared to the control group,IL-1 β,C3,and iNOS mRNA levels and protein expression were significantly elevated in the ACM group(P＜0.05).In contrast,these levels were significantly reduced in the 10 and 25 μmnol·L-1 Mdi-vi-1 groups compared to the ACM group(P＜0.05).Immunofluorescence and Western blot results confirmed that ACM stimulation significantly activated the NLRP3 inflammasome in astrocytes,while Mdivi-1 intervention effectively reversed the ACM-induced upregulation of NLRP3,caspase-1,and ASC.DHE staining results demonstrated that 5,10,and 25 μmol·L-1Mdivi-1 in-terventions partially reversed the ACM-induced in-crease in ROS levels in a dose-dependent manner.Conclusion Mdivi-1 effectively inhibits A1 astrocyte activation,potentially through modulation of ROS and the NLRP3 inflammasomes.

Objective To design an intelligent monitoring platform for adverse drug reactions(ADRs)to solve the problems of the traditional ADR monitoring mode.Methods The ADR intelligent monitoring platform was designed based on artificial intelligence and big data technologies,which was developed with Browser/Server(B/S)architecture,C#programming language and.NET development tool.There were five functional modules involved in the platform for ADR knowledge base,monitoring rule setting,intelligent monitoring,report management and statistical analysis.Results The platform realized the full-process management of ADR intelligent monitoring,reporting,review and statistical analysis,which enhanced the ADR report in quantity,quality and timeliness.Conclusion The platform contributes to improving the monitoring of ADR and patient medication safety.[Chinese Medical Equipment Journal,2025,46(9):33-38]