Objective To investigate the effect and mechanism of circular RNA_0009910(circ_0009910)on the proliferation and apoptosis of non-small cell lung cancer cells.Methods A549 cells were randomly divided into groups and transfected as follows:si-NC group,si-circ_0009910 group,miR-NC group,miR-34a-5p group,si-circ_0009910+anti-miR-NC group,and si-circ_0009910+anti-miR-34a-5p group.After successful transfec-tion,cell proliferation was measured using the CCK-8 assay.Dual-luciferase reporter assays were used to vali-date the target gene of circ_0009910.Apoptosis of A549 cells was analyzed by flow cytometry.Protein expres-sion levels of B-cell lymphoma-2(Bcl-2),transmembrane receptor protein 1(Notch1),cell proliferation-asso-ciated nuclear antigen(Ki-67),Bcl-2-associated X protein(Bax),and cysteine aspartic acid protease-3(Caspase-3)were detected by Western blot.Cells from each group were subcutaneously injected into the abdo-mens of male nude mice to establish xenograft models.Tumor volume,tumor weight,and protein expression in tumor tissues were measured.Results Compared with the si-NC group,the si-circ_0009910 group showed significantly reduced A549 cell proliferation,increased apoptosis,decreased expression of Ki-67,Notch1,and Bcl-2,and increased expression of Bax and Caspase-3(P＜0.05).Compared with the miR-NC group,the miR-34a-5p group exhibited significantly reduced luciferase activity after transfection with wild-type circ_0009910(P＜0.05).The si-circ_0009910 group showed upregulated miR-34a-5p expression compared to the si-NC group.The miR-34a-5p group demonstrated weaker proliferation,higher apoptosis,downregulated Bcl-2,Notch1,and Ki-67,and upregulated Bax and Caspase-3 compared to the miR-NC group(P＜0.05).Compared with the si-circ_0009910+anti-miR-NC group,the si-circ_0009910+anti-miR-34a-5p group exhibited en-hanced proliferation,reduced apoptosis,upregulated Bcl-2,Notch1,and Ki-67,and downregulated Bax and Caspase-3(P＜0.05).In vivo,the si-circ_0009910 and miR-34a-5p groups showed smaller tumor volumes and weights,downregulated Notch1,Ki-67,and Bcl-2,and upregulated Bax and Caspase-3 in tumor tissues com-pared to their respective control groups(P＜0.05).Conclusion Low expression of circ_0009910 inhibits A549 cell proliferation and promotes apoptosis,potentially via the miR-34a-5p/Notch1 signaling pathway.

Objective: To explore the risk of endometrial polyp (EP) based on lipid metabolism and vaginal micro- ecology combined with uterine volume line drawing model. Methods: 143 EP patients treated by hysteroscopic sur- gery were selected as the experimental group , and 113 healthy women were selected as the control group at the same time. The data were randomly divided into training set and validation set according to the ratio of 7 : 3. The clinical data of the two groups were collected and recorded , and t/χ2 test , LASSO regression and multifactorial lo- gistic regression analysis were used to screen the independent risk factors , construct the prediction model , and draw the column line graph. The performance of the model was evaluated by applying subject operating characteristic (ROC) curves , calibration curves , Hosmer-Lemeshow test and clinical decision-making (DCA) curves. Results: Multifactorial logistic regression analysis showed that total cholesterol ( TC) , low-density lipoprotein cholesterol (LDL-C) , vaginal microecological balance , and uterine volume were independent risk factors for the development of EP. ROC curve analysis showed that the AUC values of the training and validation sets of the column line graph model were 0. 935 and 0. 887 , respectively , and its sensitivity and specificity were 90. 21% , 83. 46% and 86. 29% , 80. 66% respectively , The Hosmer-Lemeshow test showed that the model fits well ( training set : χ2 = 2. 261 , P = 0. 840 ; validation set : χ2 = 4. 837 , P = 0. 441) and the calibration curves of the training and validation sets were close to the ideal curves , which indicated that the model had good prediction accuracy; the analysis of DCA curves of the training and validation sets both showed that the column-line graph model had a good clinical benefit rate in predicting EP. Conclusion TC , LDL-C , vaginal microecological balance and uterine volume are independent risk factors for EP , and the column-line diagram model constructed by the model has high clinical ben- efit , calibration and accuracy in predicting the risk of EP.

Loss-of-function variants in CSDE1 have been strongly linked to neuropsychiatric disorders, yet the precise role of CSDE1 in neurogenesis remains elusive. In this study, we demonstrate that knockout of Csde1 during cortical development in mice results in impaired neural progenitor proliferation, leading to abnormal cortical lamination and embryonic lethality. Transcriptomic analysis revealed that Csde1 upregulates the transcription of genes involved in the cell cycle network. Applying a dual thymidine-labelling approach, we further revealed prolonged cell cycle durations of neuronal progenitors in Csde1-knockout mice, with a notable extension of the G1 phase. Intersection with CLIP-seq data demonstrated that Csde1 binds to the 3' untranslated region (UTR) of mRNA transcripts encoding cell cycle genes. Particularly, we uncovered that Csde1 directly binds to the 3' UTR of mRNA transcripts encoding Cdk6, a pivotal gene in regulating the transition from the G1 to S phases of the cell cycle, thereby maintaining its stability. Collectively, this study elucidates Csde1 as a novel regulator of Cdk6, sheds new light on its critical roles in orchestrating brain development, and underscores how mutations in Csde1 may contribute to the pathogenesis of neuropsychiatric disorders.
Animals ; Neurogenesis/genetics* ; Cell Cycle/genetics* ; Mice, Knockout ; Mice ; Neural Stem Cells/metabolism* ; DNA-Binding Proteins/metabolism* ; Cyclin-Dependent Kinase 6/genetics* ; Cell Proliferation ; 3' Untranslated Regions ; Cerebral Cortex/embryology* ; RNA-Binding Proteins ; Mice, Inbred C57BL

Patients with periodontal disease often require combined periodontal-orthodontic interventions to restore periodontal health, function, and aesthetics, ensuring both patient satisfaction and long-term stability. Managing these patients involving orthodontic tooth movement can be particularly challenging due to compromised periodontal soft and hard tissues, especially in severe cases. Therefore, close collaboration between orthodontists and periodontists for comprehensive diagnosis and sequential treatment, along with diligent patient compliance throughout the entire process, is crucial for achieving favorable treatment outcomes. Moreover, long-term orthodontic retention and periodontal follow-up are essential to sustain treatment success. This expert consensus, informed by the latest clinical research and practical experience, addresses clinical considerations for orthodontic treatment of periodontal patients, delineating indications, objectives, procedures, and principles with the aim of providing clear and practical guidance for clinical practitioners.
Humans ; Consensus ; Orthodontics, Corrective/standards* ; Periodontal Diseases/complications* ; Tooth Movement Techniques/methods* ; Practice Guidelines as Topic

Chirality is not only a natural phenomenon but also a bridge between chemistry and life sciences. An effective way to obtain a single enantiomer is through racemates resolution. Recent literature shows that chiral metal-organic frameworks (CMOFs) have many applications in various fields because of their diverse topologies and functionalities. This review outlines the design idea and summarizes the latest synthesis strategies and applications of CMOFs. It highlights key advances and issues in the separation domain. In conclusion, the review provides perspectives on the challenges and prospective advancements of CMOFs materials and CMOFs-based separation technologies.

ObjectiveTo investigate the epidemiological characteristics of human parainfluenza virus (HPIV) in Pudong New Area, Shanghai, and to provide a basis for the prevention and control of HPIV infections in this area. MethodsA total of 8 180 cases with acute respiratory infection (ARI)/influenza-like illness (ILI) attending the fever outpatient clinics, pediatric outpatient clinics, respiratory outpatient clinics, pediatric wards, emergency departments, respiratory wards, and intensive care units (ICUs) and other monitoring departments in 9 sentinel hospitals in Pudong New Area from 2017 to 2022 were selected as the research subjects, and their nasopharyngeal/ throat swabs were collected. Polymerase chain reaction (PCR) method was performed for testing the respiratory virus such as influenza virus, human adenovirus, human parainfluenza virus, respiratory syncytial virus (RSV), human enterovirus, rhinovirus, et al. HPIV serotypes were analyzed, and the detection rates of HPIV were compared between different times, seasons, and population groups. ResultsThe overall HPIV detection rate of ARI/ILI cases in Pudong New Area was 3.73% (305/8 180) in 2017‒2022, with HPIV-3 being the predominant serotype. The detection rate of HPIV decreased significantly in 2017‒2022, peaking at 7.66% (99/1 293) in 2017 and falling to 0.80% (13/1 617) in 2021. Statistically significant differences were observed in HPIV detection rates across different years (χ²_trend=80.037, P_trend<0.001). The detection rate was higher in 2017‒2019 than that in 2020‒2022 (χ²_trend=38.990, P_trend<0.001). HPIV exhibited seasonal patterns in 2017‒2019, with higher detection rates in summer and autumn and lower in spring and winter, whereas no seasonal patterns were observed in 2020‒2022. Children aged <6 years had the highest detection rate (7.07%, 139/1 967), followed by adults aged ≥60 years (4.78%, 85/1 779). Statistically significant differences were observed in the detection rates of HPIV among different age groups (χ²=111.210, P<0.001). Symptoms of HPIV infection were predominantly cough, fever, and runny nose in pre-school children, fever, cough, and sore throat in school-age children, and adults, and cough, expectoration, and fever in the elderly. ConclusionThe HPIV detection rate in Pudong New Area was low in 2017‒2022. The seasonal pattern of HPIV circulation in Pudong New Area disappeared in 2020‒2022 due to the influence of infectious disease epidemics. Young children and the elderly should be prioritized in HPIV prevention and control efforts.

Recent studies have shown that shorter periods of ejaculatory abstinence may enhance certain sperm parameters, but the molecular mechanisms underlying these improvements are still unclear. This study explored whether reduced abstinence periods could improve semen quality, particularly for use in assisted reproductive technologies (ART). We analyzed semen samples from men with normal sperm counts ( n = 101) and those with low sperm motility or concentration ( n = 53) after 3-7 days of abstinence and then after 1-3 h of abstinence, obtained from the Reproductive & Genetic Hospital of CITIC-Xiangya (Changsha, China). Physiological and biochemical sperm parameters were evaluated, and the dynamics of transfer RNA (tRNA)-derived fragments (tRFs) were analyzed using deep RNA sequencing in five consecutive samples from men with normal sperm counts. Our results revealed significant improvement in sperm motility and a decrease in the DNA fragmentation index after the 1- to 3-h abstinence period. Additionally, we identified 245 differentially expressed tRFs, and the mitogen-activated protein kinase (MAPK) signaling pathway was the most enriched. Further investigations showed significant changes in tRF-Lys-TTT and its target gene mitogen-activated protein kinase kinase 2 ( MAP2K2 ), which indicates a role of tRFs in improving sperm function. These findings provide new insights into how shorter abstinence periods influence sperm quality and suggest that tRFs may serve as biomarkers for male fertility. This research highlights the potential for optimizing ART protocols and improving reproductive outcomes through molecular approaches that target sperm function.
Male ; Humans ; Spermatozoa/metabolism* ; RNA, Transfer/genetics* ; Sperm Motility/genetics* ; Adult ; Semen Analysis ; Sexual Abstinence/physiology* ; Sperm Count ; DNA Fragmentation

Objective To explore the predictive efficacy of several multimodal MRI-based machine learning models for the promoter methylation states of O6-methylguanine-DNA methyltransferase(MGMT)of glioblastoma muliforme(GBM)patients in terms of the GBM heterogeneity and the complexity of the tumor microenvironment.Methods Firstly,the multimodal MRI images of 317 GBM patients from The University of Pennsylvania Glioblastoma(UPENN-GBM)dataset were pre-processed,with four sequences involved in including T1-weighted imaging(T1WI)sequence,T1-weighted contrast-enhanced imaging(T1CE)sequence,T2-weighted imaging(T2WI)sequence and fluid-attenuated inversion recovery(FLAIR)sequence,and the radiomics features were extracted for two regions of interest(ROIs)such as the tumor core region and the tumor edema region.Secondly,the data of the 317 GBM patients were randomly divided into a training set(254 cases)and a test set(63 cases),which underwent normalization with Z-scores and feature selection and dimensionality reduction with Lasso regression.Finally,three models were established respectively with particle swarm optimization-support vector machine(PSO-SVM),C-support vector classification(C-SVC)and adaptive boosting(adaptive boosting(Adaboost)algorithms,and the predictive efficacy of the three models for glioblastoma multiforme MGMT promoter methylation states were evaluated in terms of accuracy and AUC.Results The Adaboost model based on T2WI sequence and radiomics features of the tumor core region had the highest predictive efficacy with accuracy and AUC values of 67％and 0.74,respectively,higher than those of other combinations of sequences,models and regions of interest.Conclusion The multimodal MRI-based machine learning models can be used for the prediction of glioblastoma multiforme MGMT promoter methylation states,which provides powerful support for personalized treatment and prognostic assessment of GBM.[Chinese Medical Equipment Journal,2025,46(6):7-13]

Objective:To construct a machine learning classification prediction model using planning-omics (planomics) features to predict the γ pass rate of intensity-modulated radiotherapy (IMRT) plan dose verification in fixed-field thoracic tumors, and evaluate the application of planomics in radiotherapy quality assurance.Methods:The fixed-field IMRT plans of 240 patients with chest tumors admitted to Department of Radiotherapy, Henan Cancer Hospital from August 2022 to March 2023 were retrospectively analyzed. All plans underwent dose verification using the electronic portal imaging system detector on the Varian accelerator to collect field dose data. The dose verification results were analyzed through Portal Dosimetry in the treatment planning system of Eclipse. The γ pass rate standard was set at 2%/2 mm with a 10% dose threshold. From the planning documents, 48 conventional planning features, 2476 planomics features, and the combination of the previous two feature sets were extracted. Subsequently, an auto-encoder classification model was constructed. To evaluate the classification efficacy of various feature sets, 20 random train-test divisions were conducted by calculating the area under the receiver operating characteristic curve (AUC) values along with the accuracy rates.Results:After the feature selection, 2 conventional features and 16 planomics features were finally selected. In the testing set, the AUC values for the model using combined features, planomics features, and conventional planned features were 0.802±0.030, 0.740±0.069, and 0.673±0.083, respectively. In contrast, in the training set, these AUC values were 0.844±0.074, 0.816±0.047, and 0.687±0.036, respectively. The accuracy rates were 0.752±0.083, 0.703±0.110, and 0.648±0.081 in the testing set, and 0.753±0.098, 0.751±0.075, and 0.624±0.054 in the training set for the combined, planomics, and conventional planning feature sets, respectively.Conclusions:For thoracic fixed-field adjusted radiotherapy planning, the machine learning method based on planomics features can be utilized to build a classification model for predicting the γ pass rate. Combining planomics features with conventional planned features can enhance the predictive performance of the classification models.