Background Long-term exposure to ambient fine particulate matter (PM_2.5) is a significant risk factor for cardiometabolic disorders. However, the mechanisms of its interaction with the endogenous circadian system remain incompletely understood. Objective To investigate whether chronic PM_2.5 exposure interferes with the rhythmic expression of the cardiac circadian clock, thereby disrupting downstream antioxidant defenses and metabolic homeostasis, and ultimately driving cardiometabolic dysfunction. Methods Seventy-two male C57BL/6 mice were randomly divided into a PM_2.5 exposure group (PM group) and a filtered air control group (FA group). Whole-body exposure was conducted for 8 weeks in a meteorological environmental animal exposure system. Samples were collected at six distinct zeitgeber time (ZT) points post-exposure. The 24 h ambulatory blood pressure and serum lipid profiles were monitored. Rhythm parameters were derived via cosinor analysis to compare differences in Midline statistic of rhythm (Mesor), amplitude, and phase between the two groups. The rhythmic expression of core circadian clock genes and antioxidant genes in the myocardium was detected by quantitative polymerase chain reaction (qPCR). Myocardial reactive oxygen species (ROS) levels and downstream pathway protein expression were analyzed by immunofluorescence and Western blot (WB), respectively. The expression changes of the clock gene retinoic acid receptor-related orphan receptor α (RORα) were assessed at both the mRNA and protein levels. Finally, Spearman correlation analysis was used to explore the relationships among myocardial RORα expression, lipid profiles, and oxidative stress indicators. Results Compared to the FA group, mice in the PM group exhibited a blunted circadian rhythm in blood pressure, characterized by sustained elevation throughout the day. Chronic PM_2.5 exposure showed a significant interaction with ZT on systolic blood pressure (SBP), diastolic blood pressure (DBP), and mean arterial pressure (MAP) (F-interaction=9.11, 5.70, and 6.02, respectively; P<0.05), as well as on serum triglycerides (TG), total cholesterol (T-CHO), low-density lipoprotein cholesterol (LDL-C), and high-density lipoprotein cholesterol (HDL-C) (F-interaction=16.32, 11.12, 15.39, and 28.09, respectively; P<0.05). Cosinor analysis further revealed that the Mesor values of T-CHO, TG, and LDL-C were significantly increased (P<0.05), while that of HDL-C was significantly decreased in the PM group (P<0.05). The oscillation amplitudes of SBP, DBP, and MAP showed a decreasing trend, whereas those of TG and LDL-C were significantly increased (P<0.05). Furthermore, SBP, T-CHO, and HDL-C all exhibited a significant phase delay (P<0.05). Mechanistically, PM_2.5 exposure significantly suppressed the expression of the positive circadian regulator RORα in the myocardium, leading to disordered rhythmic expression of core clock genes (Bmal1, Clock, Per1/2, and Cry1/2). This exposure also inhibited the rhythmic expression of antioxidant genes (GPX1, SOD2, and CAT), resulting in increased ROS generation and elevated expression of calcium/calmodulin-dependent protein kinase II (CaMKII) and reduced nicotinamide adenine dinucleotide phosphate (NADPH) proteins. Correlation analysis further revealed that myocardial RORα expression level was negatively correlated with T-CHO, TG, and LDL-C (r=−0.55, −0.63, and −0.51, respectively; P<0.001), and positively correlated with HDL-C (r=0.37, P=0.010), and antioxidant genes GPX1, SOD2, and CAT expression (r=0.34, 0.35, and 0.56, respectively; P < 0.001). Conclusion Chronic PM_2.5 exposure induces cardiometabolic dysfunction by suppressing myocardial RORα expression. This suppression disrupts the cardiac circadian clock and the diurnal balance of oxidative stress, triggering oxidative damage and elevating expression of CaMKII/NADPH pathway proteins. Collectively, these alterations precipitate the loss of cardiac metabolic rhythms and subsequent functional impairment.

Membrane proteins are integral components of cellular membranes, accounting for approximately 30% of the mammalian proteome and serving as targets for 60% of FDA-approved drugs. They are critical to both physiological functions and disease mechanisms. Their functional protein-protein interactions form the basis for many physiological processes, such as signal transduction, material transport, and cell communication. Membrane protein interactions are characterized by membrane environment dependence, spatial asymmetry, weak interaction strength, high dynamics, and a variety of interaction sites. Therefore, in situ analysis is essential for revealing the structural basis and kinetics of these proteins. This paper introduces currently available in situ analytical techniques for studying membrane protein interactions and evaluates the characteristics of each. These techniques are divided into two categories: label-based techniques (e.g., co-immunoprecipitation, proximity ligation assay, bimolecular fluorescence complementation, resonance energy transfer, and proximity labeling) and label-free techniques (e.g., cryo-electron tomography, in situ cross-linking mass spectrometry, Raman spectroscopy, electron paramagnetic resonance, nuclear magnetic resonance, and structure prediction tools). Each technique is critically assessed in terms of its historical development, strengths, and limitations. Based on the authors’ relevant research, the paper further discusses the key issues and trends in the application of these techniques, providing valuable references for the field of membrane protein research. Label-based techniques rely on molecular tags or antibodies to detect proximity or interactions, offering high specificity and adaptability for dynamic studies. For instance, proximity ligation assay combines the specificity of antibodies with the sensitivity of PCR amplification, while proximity labeling enables spatial mapping of interactomes. Conversely, label-free techniques, such as cryo-electron tomography, provide near-native structural insights, and Raman spectroscopy directly probes molecular interactions without perturbing the membrane environment. Despite advancements, these methods face several universal challenges: (1) indirect detection, relying on proximity or tagged proxies rather than direct interaction measurement; (2) limited capacity for continuous dynamic monitoring in live cells; and (3) potential artificial influences introduced by labeling or sample preparation, which may alter native conformations. Emerging trends emphasize the multimodal integration of complementary techniques to overcome individual limitations. For example, combining in situ cross-linking mass spectrometry with proximity labeling enhances both spatial resolution and interaction coverage, enabling high-throughput subcellular interactome mapping. Similarly, coupling fluorescence resonance energy transfer with nuclear magnetic resonance and artificial intelligence (AI) simulations integrates dynamic structural data, atomic-level details, and predictive modeling for holistic insights. Advances in AI, exemplified by AlphaFold’s ability to predict interaction interfaces, further augment experimental data, accelerating structure-function analyses. Future developments in cryo-electron microscopy, super-resolution imaging, and machine learning are poised to refine spatiotemporal resolution and scalability. In conclusion, in situ analysis of membrane protein interactions remains indispensable for deciphering their roles in health and disease. While current technologies have significantly advanced our understanding, persistent gaps highlight the need for innovative, integrative approaches. By synergizing experimental and computational tools, researchers can achieve multiscale, real-time, and perturbation-free analyses, ultimately unraveling the dynamic complexity of membrane protein networks and driving therapeutic discovery.

Objective To propose a lead attention network-based ST-T change recognition algorithm to detect ECG ST-T changes accurately.Methods Firstly,heartbeat signals were extracted through R-wave localization,and a 12-lead heartbeat matrix was generated by correlation-based screening and merging to realize data augmentation.Secondly,a lead attention module was constructed by combining depthwise convolution(DWConv)with the channel attention squeeze-and-excitation block(SE-block)structure to perceive the differences in ST-T status among electrocardiogram leads.Thirdly,the mapping output by two independent attention modules was fused and splicing with the original signal residual was carried out,so that attention information extraction and original information transfer were enhanced effectively.Finally,SE-ResNet was used as the backbone network to extract signal features to complete the classification and identification of ST-T changes.To validate the recognition performance of the proposed algorithm for ST-T changes in ECG,the 12-lead ECG data of 97 472 patients containing different ECG rhythms were collected for ablation and comparison experiments at the First Affiliated Hospital of Army Medical University.Results The proposed algorithm achieved an AUC of 0.965 with a sensitivity of 90.51%,specificity of 90.23%,positive predictive value of 89.24%and overall accuracy of 90.36%on an independent test set.Comparative analysis demonstrated superior performance to four benchmark architectures,including VGG16,ResNet18,MobileNetV3-Small and ShuffleNet,in terms of both classification accuracy and computational efficiency.Conclusion The algorithm designed can accurately detect ST-T changes and can be used for wearable ECG automatic analysis to assist in the early warning of cardiovascular diseases in both acute and chronic patients and highland residents.[Chinese Medical Equipment Journal,2025,46(7):1-11]

Aim To investigate the effects of Agrimonia pilosa(AP)on the proliferation and apoptosis of non-small cell lung cancer(NSCLC)H1299 cells using non-targeted metabolomics and other methods,and to explore the underlying molecular mechanisms.Meth-ods Taking H1299 cells as the research object,the effect of AP on cell proliferation and apoptosis was de-tected through CCK-8 method,colony formation,LDH,Hoechst 33258 staining,AO/EB staining,flow cytometry detection,RT qPCR and other experiments.The main differential metabolites were detected by the metabolomics method of ultra-high phase liquid chro-matography and mass spectrometry(UHPLC-Q-Orbi-trap MS),and related metabolic pathways were ana-lyzed.Results Compared with the control group,AP treatment was able to significantly inhibit the prolifera-tion and colony formation of H1299 cells,while the re-lease of LDH increased in a dose-dependent manner.Fluorescence microscopy and flow cytometry and RT-qPCR analysis revealed that H1299 cells underwent crumpling and increased nuclear fragmentation after AP administration,blocked in G0/G1 phase,up-regulated apoptotic genes caspase-3 and Bax,and down-regulated apoptosis-inducing effects of Bcl-2.Metabolomics anal-ysis screened 35 differential metabolites,which were PC(O-30∶1),D-Glutamic acid,PE(18∶0/15∶0),etc.The main metabolic pathways involved includ-ed amino acid metabolism,glycerophospholipid metabo-lism and purine metabolism so on.Conclusions AP may exert its pharmacological effects by interfering with multiple metabolic pathways in H1299 cells,inhibiting cell proliferation and promoting apoptosis.

Objective To summarize the changing prevalence of carbapenem resistance in Enterobacterales based on the data of CHINET Antimicrobial Resistance Surveillance Program from 2015 to 2021 for improving antimicrobial treatment in clinical practice.Methods Antimicrobial susceptibility testing was performed using a commercial automated susceptibility testing system according to the unified CHINET protocol.The results were interpreted according to the breakpoints of the Clinical & Laboratory Standards Institute(CLSI)M100 31st ed in 2021.Results Over the seven-year period(2015-2021),the overall prevalence of carbapenem-resistant Enterobacterales(CRE)was 9.43％(62 342/661 235).The prevalence of CRE strains in Klebsiella pneumoniae,Citrobacter freundii,and Enterobacter cloacae was 22.38％,9.73％,and 8.47％,respectively.The prevalence of CRE strains in Escherichia coli was 1.99％.A few CRE strains were also identified in Salmonella and Shigella.The CRE strains were mainly isolated from respiratory specimens(44.23±2.80)％,followed by blood(20.88±3.40)％and urine(18.40±3.45)％.Intensive care units(ICUs)were the major source of the CRE strains(27.43±5.20)％.CRE strains were resistant to all the β-lactam antibiotics tested and most non-β-lactam antimicrobial agents.The CRE strains were relatively susceptible to tigecycline and polymyxins with low resistance rates.Conclusions The prevalence of CRE strains was increasing from 2015 to 2021.CRE strains were highly resistant to most of the antibacterial drugs used in clinical practice.Clinicians should prescribe antimicrobial agents rationally.Hospitals should strengthen antibiotic stewardship in key clinical settings such as ICUs,and take effective infection control measures to curb CRE outbreak and epidemic in hospitals.

Objective:To identify the relevant factors for the first-course remission of acute myeloid leukemia (AML) and to develop a predictive model as well as assess its predictive capability.Methods:Clinical data of 749 patients newly diagnosed with AML admitted to the Department of Hematology, the First Affiliated Hospital, Zhejiang University, School of Medicine from January 1, 2019, to April 30, 2023, were collected and randomly divided into training and validation sets. Multivariate logistic regression analysis was conducted to determine variables associated with complete remission in the first course of induction therapy, and a predictive model was established based on these variables. The receiver operating characteristic (ROC) curve of the predictive model was plotted, and the area under the curve (AUC) was calculated.Results:The indicators predicting the first remission course included peripheral blood white blood cell count during onset, CBF::MYH11 fusion gene, CEBPA bZIP region mutation, myelodysplastic syndrome-related gene mutation, and induction chemotherapy regimen selection as independent factors for the first remission course. The model’s area under the training and validation curves was 0.738 (95% CI: 0.696-0.780) and 0.726 (95% CI: 0.650-0.801), respectively. The Hosmer-Lemeshow test results yielded P-values of 0.993 and 0.335, respectively. Conclusion:In this study, the developed model demonstrates a strong predictive capability for the efficacy of the first course of patients with AML, providing valuable guidance to clinicians in assessing patient prognosis and selecting appropriate treatment strategies.

Objective In this preliminary survey,we sought to determine the composition of mosquito species inhabiting the Emeifeng Nature Reserve,Fujian Province,China.Methods Mosquito larvae were collected by straw and spoon trapping,and adult mosquitoes were collected by lamp trapping at selected breeding sites in the reserve.The specimens were initially identified based on morphology,with subsequent verification using molecular biology methods.Results A total of 34 mosquito species in 13 genera were collected,among which,there were 4 species of Anopheles(Genus Anopheles Meigen,1818),2 species of Lutzia(Genus Lutzia Theobald,1903),15 species of Culex(Genus Culex Linnaeus,1758),4 species of Stegomyia(Genus Stegomyia Theobald,1901),and single species of Hulecoeteomyia(Genus Hulecoeteomyia Theobald,1904),Luius(Genus Luius Reinert,Harbach et Kitching,2008),Aedes(Genus Aedes Meigen,1818),Downsiomyia(Genus Downsiomyia Vargas,1950),Collessius(Genus Collessius Reinert,Harbach et kitching,2006),Uranotaenia(Genus Uranotaenia Lynch 1891),Armigeres(Genus Armigeres Theobald,1901),Toxorhynchites(Genus Toxorhynchites Theobald,1901),and pestle mosquito(Genus Tripteroides Giles,1904).Conclusions The species composition of mosquitoes sampled in the Emeifeng Nature Reserve will provide a basis for further research on mosquito vectors and contribute to measures for local mosquito control.

Drug repurposing offers a promising alternative to traditional drug development and significantly re-duces costs and timelines by identifying new therapeutic uses for existing drugs.However,the current approaches often rely on limited data sources and simplistic hypotheses,which restrict their ability to capture the multi-faceted nature of biological systems.This study introduces adaptive multi-view learning(AMVL),a novel methodology that integrates chemical-induced transcriptional profiles(CTPs),knowledge graph(KG)embeddings,and large language model(LLM)representations,to enhance drug repurposing predictions.AMVL incorporates an innovative similarity matrix expansion strategy and leverages multi-view learning(MVL),matrix factorization,and ensemble optimization techniques to integrate heterogeneous multi-source data.Comprehensive evaluations on benchmark datasets(Fdata-set,Cdataset,and Ydataset)and the large-scale iDrug dataset demonstrate that AMVL outperforms state-of-the-art(SOTA)methods,achieving superior accuracy in predicting drug-disease associations across multiple metrics.Literature-based validation further confirmed the model's predictive capabilities,with seven out of the top ten predictions corroborated by post-2011 evidence.To promote transparency and reproducibility,all data and codes used in this study were open-sourced,providing resources for pro-cessing CTPs,KG,and LLM-based similarity calculations,along with the complete AMVL algorithm and benchmarking procedures.By unifying diverse data modalities,AMVL offers a robust and scalable so-lution for accelerating drug discovery,fostering advancements in translational medicine and integrating multi-omics data.We aim to inspire further innovations in multi-source data integration and support the development of more precise and efficient strategies for advancing drug discovery and translational medicine.

Venous system diseases mainly include varicose veins and venous malformations of lower limbs and the genital system. Most of them are chronic diseases that cause serious clinical symptoms to patients and affect their health and quality of life. Sclerotherapy has become the first-line therapy for venous system diseases. However, there are problems such as incomplete fibrosis and vascular recanalization after sclerotherapy, and improper operation will cause serious adverse consequences. Therefore, exploring a safe and effective sclerotherapy strategy is essential for developing clinically successful sclerotherapy. To solve the above problems, we proposed a new sclerotherapy strategy with a dual mechanism of "vascular damage and plasmin (PLA) system inhibition." We intended to construct a novel cationic surfactant (AEO_x-TA) by reacting tranexamic acid (TA), a parent structure, with fatty alcohol polyoxyethylene ether (AEO_x) by ester bonds. AEO_x-TA could damage vascular endothelium and initiate a coagulation cascade effect to induce thrombus. Furthermore, AEO_x-TA could be degraded by esterase and release the parent drug, TA, which could inhibit the PLA system to inhibit the degradation of thrombus and extracellular matrix and promote the process of vascular fibrosis. In addition, such surfactant-based sclerosants have foam-forming properties, and they can be blended with polyvinyl alcohol (PVA) to prepare a highly stable foam formulation (AEO_x-TA/P), which can achieve a precise drug delivery and prolonged drug retention time, thereby improving drug efficacy and reducing the risk of ectopic embolism. Overall, the novel cationic surfactant AEO_x-TA provides a new avenue to resolve the bottleneck: surfactant sclerosants' efficiency is relatively low in the current sclerotherapy.

Apical microsurgery is accurate and minimally invasive, produces few complications, and has a success rate of more than 90%. However, due to the lack of awareness and understanding of apical microsurgery by dental general practitioners and even endodontists, many clinical problems remain to be overcome. The consensus has gathered well-known domestic experts to hold a series of special discussions and reached the consensus. This document specifies the indications, contraindications, preoperative preparations, operational procedures, complication prevention measures, and efficacy evaluation of apical microsurgery and is applicable to dentists who perform apical microsurgery after systematic training.
Microsurgery/standards* ; Humans ; Apicoectomy ; Contraindications, Procedure ; Tooth Apex/diagnostic imaging* ; Postoperative Complications/prevention & control* ; Consensus ; Treatment Outcome