Periodontitis, a chronic inflammatory disease caused by plaque biofilm, is characterized by the irreversible pathological destruction of periodontal supporting tissues, including gums, periodontal membranes, alveolar bone, and cementum, resulting in tooth loosening and dislocation in severe cases. Currently, research on the pathogenesis, early diagnosis, and treatment of periodontitis is limited. Circular RNAs (circRNAs), previously considered “splicing noise”, have gained increasing research attention with the development of high-throughput sequencing technologies and bioinformatics. CircRNAs are non-coding RNAs lacking a 5' cap and 3' poly(A) tail, with a unique covalently closed ring structure, high expression, long half-life, and resistance to nuclease degradation, which can regulate splicing, encode proteins, and act as microRNA and RNA-binding protein sponges. In recent years, circRNAs have been reported to be involved in the occurrence and development of periodontitis, suggesting its potential role as a therapeutic target for periodontitis treatment. In this study, we described the biological function of circRNAs and their role in the development of periodontitis and the regulation of periodontal homeostasis and immune microenvironment. We found that circRNAs affect periodontal homeostasis and immune microenvironment by regulating the apoptosis of periodontal tissue cells (such as periodontal ligament stem cells and gingival fibroblasts) and regulating immune cells or cytokines, respectively. This review article summarizes the latest research progress on the association between circRNAs and periodontitis to provide a scientific basis for the development of novel diagnostic, therapeutic, and prognostic strategies for periodontitis.

The oropouche virus (OROV) poses a threat to pregnant women and fetuses, potentially causing fetal neurological defects and even stillbirth, which has caused global attention. OROV is an arthropod-borne virus belonging to the Orthobunyavirus genus in the Bunyavirales order, primarily transmitted by arthropods and causing oropouche fever. This article reviews the etiological characteristics, epidemiological distribution, clinical symptoms, detection methods, and prevention strategies of OROV. OROV is prevalent in Central and South America, with a sharp increase in cases reported in Brazil in 2024. The virus's symptoms resemble those of several other arthropod-borne viral diseases, which can lead to misdiagnosis. Currently, there are no specific drugs or vaccines available, and treatment is mainly supportive. Culicoides paraensis and Culex quinquefasciatus are among the significant vectors of OROV. Furthermore, the article analyzes the distribution of Culex quinquefasciatus in China, highlights the risk of imported cases, proposes targeted prevention and control strategies, and underscores the significance of international cooperation in disease prevention and control.

Objective To use multiple model integration to predict the potential distribution of suitable areas for Hedysari Radix in China and the main environmental factors affecting its distribution.Methods Based on 119 geographical distribution points obtained from species distribution databases,and incorporating 19 bioclimatic and topographic factors,a species distribution model was constructed using the Biomod2 software package 3.5-1 version ensemble modeling platform,integrating six algorithms including generalized linear model,gradient boosting machine,random forest,and others.Geographic information system spatial analysis methods were used to quantitatively assess the distribution characteristics of suitable habitats of Hedysari Radix under current climate conditions and under future climate scenarios,while identifying the primary environmental drivers of its distribution.Results The ensemble model showed significantly superior predictive performance.TSS value and AUC value were 0.924 and 0.992,respectively.Key environmental factors significantly influencing the distribution of Hedysari Radix included slope,aspect,daily average temperature difference,isothermity,seasonal variation coefficient of temperature,lowest temperature in the coldest month,annual precipitation,driest month precipitation,and seasonal variation coefficient of precipitation.Under current climate conditions,suitable habitats for Hedysari Radix were primarily concentrated in the regions of Longnan and Dingxi in Gansu Province,covering an area of approximately 26.17×104 km2.Under future climate scenarios,suitable habitats will gradually shift toward the northwest into lower temperature zones,with a significant reduction in area.Conclusion The habitat suitability model developed in this study provides a basis for the conservation and sustainable utilization of Hedysari Radix genetic resources,while also offering a methodological reference for ecological adaptability studies of medicinal plants.

The oropouche virus (OROV) poses a threat to pregnant women and fetuses, potentially causing fetal neurological defects and even stillbirth, which has caused global attention. OROV is an arthropod-borne virus belonging to the Orthobunyavirus genus in the Bunyavirales order, primarily transmitted by arthropods and causing oropouche fever. This article reviews the etiological characteristics, epidemiological distribution, clinical symptoms, detection methods, and prevention strategies of OROV. OROV is prevalent in Central and South America, with a sharp increase in cases reported in Brazil in 2024. The virus's symptoms resemble those of several other arthropod-borne viral diseases, which can lead to misdiagnosis. Currently, there are no specific drugs or vaccines available, and treatment is mainly supportive. Culicoides paraensis and Culex quinquefasciatus are among the significant vectors of OROV. Furthermore, the article analyzes the distribution of Culex quinquefasciatus in China, highlights the risk of imported cases, proposes targeted prevention and control strategies, and underscores the significance of international cooperation in disease prevention and control.

Objective To use multiple model integration to predict the potential distribution of suitable areas for Hedysari Radix in China and the main environmental factors affecting its distribution.Methods Based on 119 geographical distribution points obtained from species distribution databases,and incorporating 19 bioclimatic and topographic factors,a species distribution model was constructed using the Biomod2 software package 3.5-1 version ensemble modeling platform,integrating six algorithms including generalized linear model,gradient boosting machine,random forest,and others.Geographic information system spatial analysis methods were used to quantitatively assess the distribution characteristics of suitable habitats of Hedysari Radix under current climate conditions and under future climate scenarios,while identifying the primary environmental drivers of its distribution.Results The ensemble model showed significantly superior predictive performance.TSS value and AUC value were 0.924 and 0.992,respectively.Key environmental factors significantly influencing the distribution of Hedysari Radix included slope,aspect,daily average temperature difference,isothermity,seasonal variation coefficient of temperature,lowest temperature in the coldest month,annual precipitation,driest month precipitation,and seasonal variation coefficient of precipitation.Under current climate conditions,suitable habitats for Hedysari Radix were primarily concentrated in the regions of Longnan and Dingxi in Gansu Province,covering an area of approximately 26.17×104 km2.Under future climate scenarios,suitable habitats will gradually shift toward the northwest into lower temperature zones,with a significant reduction in area.Conclusion The habitat suitability model developed in this study provides a basis for the conservation and sustainable utilization of Hedysari Radix genetic resources,while also offering a methodological reference for ecological adaptability studies of medicinal plants.

Objective:To investigate the changing trends in cardiac function following xenogeneic heterotopic heart transplantation of multi-gene edited pig hearts and assess the impact of recipient immune responses on donor heart, laying experimental groundwork for the clinical application of gene editing technology.Methods:On December 16, 2023, xenogeneic heterotopic heart transplantation was performed between pigs and rhesus monkeys. Functional status of the graft under post-transplantation load conditions and recipient immune indicators were observed.Results:The recipient monkeys survived for 40 days with satisfactory functionality of both donor and recipient hearts, and no hyperacute or acute immune rejection reactions were observed.Conclusion:Multi-gene editing technology provides potential for xenotransplantation, yet further exploration is needed for its clinical application.

Objective:To develop and validate gas chromatographic methods for the determination of residual benzene in carbomer copolymer,carbomer homopolymer and carbomer interpolymer,to address the issues of the current method in the Chinese Pharmacopoeia in the actual detection process,such as low sensitivity and poor repeatability of benzene detection in the mixed reference solution,and to optimize and improve the current stand-ards for series of carbomer pharmaceutical excipients.Methods:Samples were separated on a column DB-624(30 m ×0.530 mm,3.00 μm)with temperature programming,the inlet temperature of 140 ℃,the detector tem-perature of 250 ℃,and the split ratio of 5∶1.The external standard method was adopted for the quantitative deter-mination of residual benzene.Results:The linearity was great across the range of 0.04-1.00 μg·mL-1(r=0.996 8),the injection precision of benzene was 6.8％(n=6),and the average recovery rate was 96.89％(RSD=8.1％,n=9).Conclusion:The gas chromatographic method established in this research is more specif-ic,with higher accuracy and precision compared to the current method in the Chinese Pharmacopoeia.This optimized method is more suitable for the determination of residual benzene content in carbomer copolymer,car-bomer homopolymer and carbomer interpolymer,providing reference and guidance for the quality management and the control of carbomer.

Periodontitis is a chronic inflammatory disease caused by plaque microorganisms, which is the main cause of tooth loss in adults in China. Due to the complexity of periodontitis, their pathogenesis is still unclear. Ferroptosis is a form of iron-dependent regulation of cell death, which affects the function of glutathione peroxidase (GPX4) in the cell through different signaling pathways, thus decreasing antioxidant capacity, accumulation of reactive oxygen species and lipid peroxidation, eventually causing cell and tissue damage. Recent studies have found that iron overload, oxidative stress and lipid peroxidation are closely related to the occurrence and development of periodontitis. This article reviews the characteristics of ferroptosis and the relationship between ferroptosis and inflammatory diseases, especially periodontitis, to provide new ideas for the diagnosis, treatment, and prognosis evaluation of periodontitis. ferroptosis is mainly manifested as the disruption of the body's redox homeostasis, decreased antioxidant capacity, activation of damage related molecular patterns, release of pro-inflammatory mediators, and induction or exacerbation of inflammation. Iron dependent oxidative stress and lipid peroxidation are simultaneously involved in the regulation of ferroptosis and inflammatory diseases. Pathogenic bacteria of periodontitis can induce ferroptosis of periodontal ligament stem cells, thereby activating the release of inflammatory factors such as interleukin-17, tumor necrosis factor alpha, and hypoxia inducible factor-1 alpha, exacerbating periodontitis; In addition, inflammatory factors activated by ferroptosis play an important role in alveolar bone homeostasis, and ferroptosis is involved in the process of lipopolysaccharide induced inflammation of gingival fibroblasts. Future research can focus on exploring the molecular mechanisms and therapeutic targets of ferroptosis in periodontitis, providing new strategies for the prevention and treatment of periodontal disease.

Objective This study aimed to explore the relationships between residential greenness and cardiometabolic risk factors among rural adults in Xinjiang Uygur Autonomous Region(Xinjiang)and thus provide a theoretical basis and data support for improving the health of residents in this region. Methods We recruited 9,723 adult rural residents from the 51st Regiment of the Third Division of the Xinjiang Production and Construction Corps in September 2016.The normalized difference vegetation index(NDVI)was used to estimate residential greenness.The generalized linear mixed model(GLMM)was used to examine the association between residential greenness and cardiometabolic risk factors. Results Higher residential greenness was associated with lower cardiometabolic risk factor prevalence.After adjustments were made for age,sex,education,and marital status,for each interquartile range(IQR)increase of NDVI500-m,the risk of hypertension was reduced by 10.3%(OR=0.897,95%CI=0.836-0.962),the risk of obesity by 20.5%(OR=0.795,95%CI=0.695-0.910),the risk of type 2 diabetes by 15.1%(OR=0.849,95%CI=0.740-0.974),and the risk of dyslipidemia by 10.5%(OR=0.895,95%CI=0.825-0.971).Risk factor aggregation was reduced by 20.4%(OR=0.796,95%CI=0.716-0.885)for the same.Stratified analysis showed that NDVI500-m was associated more strongly with hypertension,dyslipidemia,and risk factor aggregation among male participants.The association of NDVI500-m with type 2 diabetes was stronger among participants with a higher education level.PM10 and physical activity mediated 1.9%-9.2%of the associations between NDVI500-m and obesity,dyslipidemia,and risk factor aggregation. Conclusion Higher residential greenness has a protective effect against cardiometabolic risk factors among rural residents in Xinjiang.Increasing the area of green space around residences is an effective measure to reduce the burden of cardiometabolic-related diseases among rural residents in Xinjiang.

Objective To explore the predictive markers of senescence-associated secretory phenotype(SASP)in osteoarthritis(OA).Methods OA datasets were screened by the Gene Expression Omnibus(GEO)database,while SASP-related genes were collected by PubMed.Three machine learning algorithms,including least absolute shrinkage and selection operator(LASSO),support vector machines recursive feature elimination(SVM-RFE),and random forest(RF),were used to screen the candidate predictive markers of SASP genes in OA,and the OA prediction model was constructed using the overlapping genes identified by the machine learning algo-rithms.CIBERSORT was used to explore the degree of peripheral blood immune cell infiltration in OA versus normal samples.The miRNA-transcription factor-mRNA regulatory network of the model genes was predicted using Cytoscape.The most valuable genes of the predic-tion model were experimentally verified by real-time quantitative polymerase chain reaction(RT-qPCR)in OA rats and normal control rats(n= 6 per group).Results One OA dataset was screened by the GEO database,and 125 OA-related SASP genes were isolated.A total of seven intersection genes were obtained by the three machine learning algorithms.The area under the curve of the prediction model was 0.891.The CIBERSORT immune infiltration results showed a significant difference in plasma cell infiltration level between OA and normal samples(P= 0.001 3).The RT-qPCR results showed that the expression level of TNFRSF1Awas significantly higher in the OA versus normal group(P<0.0001).Conclusion TNFRSF1Ais highly expressed in OA and may be a potential predictive marker for it.