Objective: To investigate the association between brain and muscle Arnt like protein 1( BMAL 1) gene and ambulatory blood pressure (ABP) parameters in college students, and to explore the influence of the interaction between the gene and weight status on the ABP levels, so as to provide reference for early prevention of chronic cardiovascular diseases related to hypertension. Methods: During September 2022 to June 2024, a total of 510 college students were recruited from a university in Changsha, China for on site questionnaire investigation, physical examination, ABP monitoring and genotyping testing. Multiple linear regression method was used to explore the association between the BMAL 1 gene and ABP indicators. An interaction term was included in the general linear model of multiple linear regression to analyze the interactive effects of BMAL 1 gene polymorphisms and weight status on ABP levels. Results: The prevalence of abnormal 24 hour blood pressure, abnormal daytime blood pressure, and abnormal nighttime blood pressure were 3.3%, 3.1%, and 3.9%, respectively. Multiple linear regression analysis showed that the BMAL 1/rs7950226 polymorphism was positively correlated with the 24 hour diastolic blood pressure(DBP) and the daytime DBP level after adjusting for gender, age, and body mass index( β =0.87,0.99, both P <0.05). Also, interaction between BMAL 1/ rs 11022775 and weight status on the nighttime DBP level ( P interaction =0.03) was found. The CC genotype carriers had significantly higher nighttime DBP level ( β =3.52, P <0.05) among overweight/obesity college students, but no differences in nocturnal DBP levels were observed between CC genotype carriers and TT+CT genotype carriers among college students with normal body weight( P > 0.05). Conclusions The rs 7950226 polymorphism is associated with 24 hours DBP and daytime DBP levels. Significant interaction between rs 11022775 with weight status on the nighttime DBP level is found among college students.

Objective To construct and compare logistic regression and decision tree models for predicting systemic inflammatory response syndrome (SIRS) in patients with type B aortic dissection (TBAD) after interventional surgery. Methods A retrospective analysis was conducted on clinical data of TBAD patients at Peking University Shenzhen Hospital from 2020 to 2024. The patients were divided into a SIRS group and a non SIRS group based on whether SIRS occurred within 24 hours after surgery. Multivariate logistic regression was used to analyze the influencing factors of SIRS occurrence in TBAD intervention patients, and a decision tree model was constructed using SPSS Modeler to compare the predictive performance of the two models. Results A total of 742 patients with TBAD were included, including 579 males and 163 females, aged 27-97 (58.85±10.79) years. Within 24 hours after intervention, a total of 506 patients developed SIRS, with an incidence rate of 68.19%. Logistic regression analysis showed that the extensive involvement of the dissection, the surgical time≥2 hours, PET coated stents implanted, serum creatinine, white blood cell count, C-reactive protein, monocyte (MONO), neutrophil count levels elevated, estimated glomerular filtration rate and decreased albumin levels were independent risk factors for SIRS (P<0.05). The decision tree model selected a total of 10 explanatory variables and 6 layers with 37 nodes, among which MONO was the most important predictor. The area under the decision tree model curve was 0.829 [95%CI (0.800, 0.856)], which was better than the logistic regression model's 0.690 [95%CI (0.655, 0.723)], and the difference was statistically significant (P<0.001). Conclusion The incidence of SIRS after TBAD intervention is high, and the decision tree model has better predictive performance than logistic regression. It can identify high-risk patients with higher accuracy and provide a practical tool for early clinical intervention.

The complete functional regeneration of periodontal tissues—specifically, the simultaneous reconstruction of alveolar bone, cementum, and periodontal ligament—represents a major challenge in oral regenerative medicine. Dental-derived mesenchymal stem cells (DMSCs) are regarded as ideal seed cells for achieving this goal due to their multi-lineage differentiation potential and immunomodulatory properties. As a cell carrier, hydrogels offer the key advantage of mimicking the extracellular matrix through precisely tunable physicochemical properties (e.g., matrix stiffness, topological structure, degradation kinetics), thereby constructing a mechanical and biochemical microenvironment that actively directs stem cell fate. This review summarizes the application and research progress of DMSC-laden hydrogels in periodontal tissue repair. We first analyze the material characteristics of different hydrogel systems, and then elaborate on the specific molecular mechanisms by which hydrogels regulate DMSCs’ differentiation through mechanical properties such as matrix stiffness: stiff hydrogels drive osteogenic differentiation by activating the integrin-focal adhesion kinase (FAK)-Akt/mechanistic target of rapamycin (mTOR) signaling axis; inducing cytoskeletal remodeling, and promoting dephosphorylation and nuclear translocation of Yes-associated protein (YAP)/transcriptional co-activator with PDZ-binding motif (TAZ) to initiate the transcription of osteogenesis-related genes; and stabilizing β-catenin and activating the Wnt/β-catenin signaling pathway, upregulating the expression of key osteogenic transcription factors including Runt-related transcription factor 2 (Runx2) and Osterix. Furthermore, as programmed controlled-release carriers for bioactive factors, hydrogels selectively activate Smad signaling subtypes—pro-osteogenic factors specifically activate the Smad1/5/8 pathway, whereas factors promoting periodontal ligament formation activate the Smad2/3 pathway—thereby achieving precise, directed differentiation of DMSCs toward osteogenic, cementogenic, or fibroblastic lineages. Current key scientific issues in this field include the dynamic adaptation of hydrogel properties during regeneration, stable control of the complex oral microenvironment (e.g., microbes, mechanical forces, inflammation), strategies for efficient directional differentiation of stem cells, and feasibility of clinical translation. Future research directions should focus on developing smart-responsive hydrogels, constructing personalized biomimetic scaffolds combined with three-dimensional bioprinting technology, and designing composite material systems with immunomodulatory functions, aiming ultimately to achieve integrated structural and functional regeneration of periodontal tissue.

Objective To prepare rabbit polyclonal antibodies against Coxsackievirus A6(CVA6) VP4 and identify the biological characteristics, in order to provide core antibody materials for VP4 protein function research, CVA6 clinical diagnosis and vaccine quality control.Methods The VP4 gene was amplified by RT-PCR from total RNA of RD cells infected by CVA6 3415 strain and cloned into prokaryotic expression vector pGEX-6P-1(containing GST lable)and eukaryotic expression vector pCAGGS-HA to construct recombinant plasmids pGEX-6P-1-VP4 and pCAGGS-HA-VP4, respectively. The pGEX-6P-1-VP4 was transformed into E.coli BL21(DE3) competent cells and induced to express GST-VP4 fusion protein with IPTG. After gel cutting and purification, a female Japanese white rabbit was immunized subcutaneously on the back to generate anti-VP4 polyclonal antibodies. Indirect ELISA was applied to determine antibody titer; Western blot and indirect immunofluorescence assay(IFA) were used to detect the specific recognition ability of the antibodies to eukaryotic expression VP4 and virus VP4 in CVA6-infected cells; CVA6 virus particles(EP, FP and AP) were separated by cesium chloride density gradient centrifugation. After the morphology was confirmed by transmission electron microscope, the immunoreactivity of polyclonal antibodies against different particles was verified by Western blot.Results The recombinant plasmids pGEX-6P-1-VP4 and pCAGGS-HA-VP4 were constructed correctly as identified by double enzyme digestion. The purified GST-VP4fusion protein had a relative molecular mass of about 33 000 and a concentration of 600 ??g/mL. The titer of rabbit anti-VP4polyclonal antibodies was higher than 1∶512 000, which could specifically recognize VP4 protein expressed in eukaryotic cells and VP4 and its precursor VP0 in CVA6-infected cells. IFA detection exhibited clear and specific green fluorescence.The polyclonal antibodies could also recognize VP4 protein in FP and AP, and the signal intensity of AP was weaker than that of FP. However, only VP0 but not VP4 was detected in EP.Conclusion The rabbit polyclonal antibodies against CVA6VP4 with high titer and high specificity were successfully prepared. The antibodies are suitable for Western blot and IFA detection, and can effectively distinguish different virus particle morphology of CVA6, which provide a valuable tool for the functional research of VP4 protein and the quality control of CVA6 vaccines.

Objective To explore the application effect of a standardized management method based on failure mode and effect analysis （FMEA） in optimizing the whole-process quality control system of the intravenous admixture service （PIVAS）. Methods The quality control management system of the PIVAS was optimized by establishing six quality control groups led by the head nurse, with full participation of pharmacy, nursing, and logistical staff, ensuring comprehensive coverage and traceability of all quality control links. Each group conducted risk priority number （RPN） scoring for potential failure modes in their respective quality control processes, and targeted improvement measures were formulated based on the scoring results. The RPN values of failure modes and quality control-related evaluation indicators before and after implementation were compared to achieve closed-loop management. Results After one year of management, the RPN values of the six major failure modes significantly decreased compared to those before implementation （P<0.05）. The compounding error rate dropped to 0.13%, the dispensing error rate decreased to 0.95%, the compounding efficiency increased to 98%, the delivery time was shortened by 0.45 h per batch, the intervention rate for irrational prescriptions rose to 94.87%, satisfaction improved to 96.78%, and the participation rate of quality control personnel reached 95.36% （P<0.05）. Conclusion FMEA-based identification of potential failure modes in the whole-process quality control system of the IVAS, combined with risk quantification and targeted interventions, significantly reduced high-risk failure modes, improved compounding accuracy and efficiency, and ensured the safety of clinical intravenous medication and the effectiveness of healthcare quality management.

Objective To explore the application effect of a standardized management method based on failure mode and effect analysis （FMEA） in optimizing the whole-process quality control system of the intravenous admixture service （PIVAS）. Methods The quality control management system of the PIVAS was optimized by establishing six quality control groups led by the head nurse, with full participation of pharmacy, nursing, and logistical staff, ensuring comprehensive coverage and traceability of all quality control links. Each group conducted risk priority number （RPN） scoring for potential failure modes in their respective quality control processes, and targeted improvement measures were formulated based on the scoring results. The RPN values of failure modes and quality control-related evaluation indicators before and after implementation were compared to achieve closed-loop management. Results After one year of management, the RPN values of the six major failure modes significantly decreased compared to those before implementation （P<0.05）. The compounding error rate dropped to 0.13%, the dispensing error rate decreased to 0.95%, the compounding efficiency increased to 98%, the delivery time was shortened by 0.45 h per batch, the intervention rate for irrational prescriptions rose to 94.87%, satisfaction improved to 96.78%, and the participation rate of quality control personnel reached 95.36% （P<0.05）. Conclusion FMEA-based identification of potential failure modes in the whole-process quality control system of the IVAS, combined with risk quantification and targeted interventions, significantly reduced high-risk failure modes, improved compounding accuracy and efficiency, and ensured the safety of clinical intravenous medication and the effectiveness of healthcare quality management.

The functional realization of proteins and other biological macromolecules depends on conformational dynamics and allosteric regulation, and elucidating their molecular mechanisms is an important foundation for understanding life processes. Molecular dynamics simulations are a powerful tool for investigating conformational evolution at the atomic level. However, traditional methods are limited by simulation timescales and high free-energy barriers, making it difficult to effectively capture rare conformations and their transition pathways. As a result, the development of enhanced sampling techniques has become key to overcoming this bottleneck. As a classical enhanced sampling technique, metadynamics suffers from several shortcomings, including strong dependence on collective variables and significant errors caused by bias potential accumulation. This article reviews three major improvement strategies. The first combines stochastic resetting with metadynamics, using trajectory-resetting mechanisms to improve sampling efficiency while avoiding the difficulty of optimizing collective variables. The second, SinkMeta, employs a “sinking” bias effect to enable efficient exploration of specific regions and paths. The third, OPES-based hybrid methods, improve the stability of free-energy estimation by optimizing the target distribution or the way the bias is constructed. These methods provide new ideas for characterizing free-energy landscapes and studying conformational transitions in complex biological systems, while also promoting the continued development of enhanced sampling methodologies.

Rheumatoid arthritis belongs to arthralgia in the theory of traditional Chinese medicine, with cold dampness obstruction pattern (CDO) and damp heat obstruction pattern (DHO) as the main pattern types. Fine therapeutic effects have been obtained in clinical practice following the differentiation of CDO and DHO. However, suitable animal models are not available currently. For adapting to the clinical diagnosis, as well as carrying out basic research of integrated Chinese and Western medicine and preclinical study on new Chinese medicine in a better way, the “Guidelines for Establishing Animal Models of Rheumatoid Arthritis with Cold Dampness Obstruction Pattern and Damp Heat Obstruction Pattern” (referred to as “Guidelines”) were compiled by our research group in cooperation with renowned experts in clinical, pharmaceutical, zoological, and methodological research fields. According to the theory of disease and syndrome integration, experts standardized the establishment methods for animal models of rheumatoid arthritis with CDO and DHO. The Guidelines were compiled via the nominal group method according to the principle of evidence coming in main place, consensus as the auxiliary, and experience as the references. Contents such as animal species, arthritis induction methods, external stimulation conditions, and assessment indicators were specified in the Guidelines based on the comprehensive evaluation of pathogenesis homology, behavioral phenotypic consistency, and drug therapy predictability between animal models and human diseases. The Guidelines will be applicable to the research on syndromes in rheumatoid arthritis, elucidation of acting mechanism, and development of new medicine, and provide reference for standardizing other types of animal models with the integration of disease and syndrome, to promote the modernization of Chinese medicine research.

ObjectiveThis study aimed to investigate the anti-Mycoplasma pneumoniae (MP) activity of luteolin and elucidate its underlying mechanisms. MethodsLuteolin was identified as the primary active compound from the polyphenol extract ofF. diotrys using network pharmacology. Its efficacy was evaluated against two MP strains: the standard strain M129 and the multidrug-resistant strain M19. A modified culture medium with visual characteristics was employed to determine the minimum inhibitory concentration (MIC) of luteolin. The expression of key proteins involved in MP growth and pathogenicity was assessed by qRT-PCR following luteolin treatment. Additionally, the viability of A549 cells infected with MP was compared between luteolin-treated and untreated groups. In vivo anti-MP activity was evaluated using a mouse model, and the expression of inflammatory cytokines in lung tissues was analyzed. ResultsLuteolin effectively inhibited both MP strains, with MIC₉₀ values of 100 mg/L for M19 and M129. Treatment with luteolin significantly downregulated the expression of adhesion proteins P1 and P30 in both strains. However, the expression of P65, HMW3, TrmB, and CARDS TX was reduced only in the M19 strain following luteolin intervention. Luteolin also enhanced the growth and viability of A549 cells infected with MP. In the mouse model, luteolin treatment resulted in steady weight gain and was well tolerated. The bacteriostatic rate of luteolin in lung tissues was 50.7%, significantly higher than the 25.2% observed in the roxithromycin group. Furthermore, luteolin reduced the expression of inflammatory factors, including IL-6, TNF-α, and HMGB1, in MP-infected mice. ConclusionLuteolin effectively and safely inhibits the proliferation and pathogenicity of MP, particularly the drug-resistant M19 strain, by downregulating the expression of toxicity-associated proteins (P1, P30, P65, HMW3, TrmB, CARDS TX) and modulating host inflammatory responses. These findings suggest that luteolin may offer a novel therapeutic strategy for treating MP infections, especially those caused by drug-resistant strains.

ObjectiveTo investigate the effects of lectin-like oxidized low-density lipoprotein receptor-1 （LOX-1） gene G501C on brain structure and cognitive function in patients with white matter hyperintensities （WMH）. MethodsA total of 118 patients with WMH were enrolled. All participants underwent T1-weighted and T2-fluid-attenuated inversion recovery （T2-FLAIR） MRI to assess gray matter structure and WMH burden， and completed the mini-mental state examination （MMSE） and Montreal cognitive assessment （MoCA）. Partial correlation and mediation analyses were performed to explore the impact of LOX-1 polymorphism on cognitive function. ResultsParticipants were divided into GG+GC group （n = 35） and CC group （n = 83）. The GG+GC group showed lower MMSE and MoCA scores （MMSE： P=0.003； MOCA： P=0.015）， as well as greater WMH burden （all P0.001）， compared with the CC group. Voxel-based morphometry （VBM） analysis revealed reduced left thalamic volume in the GG+GC group， which was correlated with cognitive scores （all P0.05）. Subregional thalamic analysis further showed volume reductions in the lateral， ventral， medial， and pulvinar thalamic regions （all P0.05） in the GG+GC group， all positively associated with cognitive performance （all P0.05）. Mediation analyses indicated that volumes of the medial and pulvinar thalamic regions mediated the association between genotype and cognitive function （MMSE， MoCA）， and that WMH volume mediated the effect on MoCA scores. ConclusionThe LOX-1 G501C polymorphism may indirectly affect cognitive function by influencing specific thalamic subregional volumes and white matter damage， suggesting a potential mediating role of thalamic structures between genetic background and cognitive impairment.