A portion of patients undergoing implant restoration require bone augmentation procedures to ensure that there is sufficient bone volume around the implant. For the patients with horizontal bone ridge defects at edentulous sites, with or without mild to moderate vertical bone defects, the shell technique serves as a reliable and minimally invasive bone augmentation method with effective space maintenance. The shell technique involves fixating 1 mm cortical bone blocks to the recipient site, using retention screws and filling the gap between the bone block and recipient bed with particulate bone substitute materials, and covering the barrier membrane to achieve bone augmentation. The overlying tension-free soft tissue closure seals the surgical site while local peripheral blood releases osteoclasts and cytokines that gradually degrade the bone block. The rigid fixation of the bone block ensures a stable internal environment for osteogenesis and a new bone regeneration cycle. Although this technique demonstrates favorable bone augmentation outcomes, it is highly technique-sensitive. There are certain differences in the application scenarios and osteogenic processes for autologous and allogeneic bone shells. The selection of bone blocks and particulate bone substitute materials significantly influences the osteogenic biological process and the predictability of bone augmentation results. Complications associated with the shell technique possess distinct characteristics, such as the immunogenicity of allogeneic bone fragments, soft tissue cracking, and bone fragment loosening. Their prevention and subsequent management substantially impact the success rate of osteogenesis. This article delves into the biological mechanisms of osteogenesis in the bone block technique, summarizing the indications, clinical outcomes, classification of bone blocks, and surgical workflow management, as well as complication prevention and management, aiming to provide a reference for the future application and development of the bone shell technique.

The Split-Cre system consists of two inactive polypeptides: NCre and CCre, which can be recombined into an active full-length Cre under certain conditions. This system is typically used with LoxP. To develop an efficient Split-Cre system, this study used Rma intein from Rhodothermus marinus to split Cre and screened out the split site S102 which could efficiently mediate the recombination of Cre in the "Traffic Light" reporter cell line. Moreover, the S102 Split-Cre system was delivered to mice by dual-adeno-associated virus (AAV), and it was demonstrated that the efficiency of the Rma intein-mediated S102 Split-Cre system was comparable to the full-length Cre in mice. This system lays a foundation for both basic and applied research on Split-Cre.
Inteins/genetics* ; Animals ; Integrases/biosynthesis* ; Mice ; Dependovirus/metabolism* ; Bacterial Proteins/genetics* ; Recombination, Genetic ; Humans

Follicular variant of papillary thyroid carcinoma(FVPTC)is commonly found in young and middle-aged women,and cases in children and adolescents are relatively rare.The main driving genes of FVPTC are the RAS oncogene family or B-Raf proto-oncogene serine/threonine protein kinase(BRAF),and DICER1 gene mutation is rarely reported in this subtype.This article reports a case of recurrent FVPTC with positive DICER1 mutation in an adolescent,aiming to provide reference for the clinical diagnosis and treatment of FVPTC.The patient,a 19-year-old female,underwent total thyroidectomy and central lymph node dissection due to thyroid nodules 5 years ago,and was pathologically diagnosed with follicular tumor of uncertain malignant potential(FT-UMP);after surgery,the patients did not regularly undergo thyroid-stimulating hormone(TSH)suppression therapy and follow-up as instructed.Two months ago,the patient visited the hospital due to enlarged cervical lymph nodes,imaging suggested tumor recurrence with metastases to both lungs and vertebrae,and multigene testing indicated a DICER1 gene mutation.After comprehensive multidisciplinary consultation,bilateral cervical lymph node dissection was performed,and postoperative pathology confirmed the diagnosis of metastatic FVPTC.Te clinicans should focus on rare gene mutations such as DICER1 in the FVPTC patients,and for adolescent patients,follow-up and formulation of individualized treatment plans should be emphasized to achieve early tumor identification and precise intervention,and improve the long-term prognosis of patients.

To investigate the molecular mechanisms underlying the mechanosensitive ion channel PI-EZO2 in osteoarthritis(OA),we developed a lentiviral vector for endogenous PIEZO2 overexpression and established a stable PIEZO2-high-expressing immortalized human primary chondrocyte line.By map-ping the open reading frame of the PIEZO2 locus and designing sequence-specific sgRNA,we employed the CRISPR/Cas9 synergistic activation mediator(SAM)system to precisely integrate transcriptional ac-tivation elements into the PIEZO2 promoter region.Lentiviral-mediated targeted genomic integration en-sured endogenous PIEZO2 overexpression,confirmed by mCherry fluorescence tracing coupled with flow cytometric sorting,which revealed membrane-specific localization of PIEZO2 protein(localization effi-ciency:78.49％).Quantitative PCR demonstrated a 17-fold upregulation of PIEZO2 mRNA,while Western blotting validated enhanced membrane-localized protein expression.Strikingly,PIEZO2-overex-pressing chondrocytes exhibited hallmark OA metabolic phenotypes compared to wild-type controls:typeⅡ collagen mRNA expression decreased to 50％of baseline levels,whereas matrix metalloproteinase 13(MMP13)mRNA surged by 20-fold.These alterations recapitulated the pathological matrix metabolic phenotype observed in biomechanical OA models induced by cyclic mechanical stress(10％strain,0.5 Hz,8 h/day for 2 consecutive days).Collectively,we successfully generated a human chondrocyte model with stable PIEZO2 overexpression,which faithfully mirrors mechanotransduction-driven OA progression.This engineered cellular system provides a robust platform for dissecting PIEZO2-mediated mechanosig-naling networks and advancing targeted therapeutic discovery.

Complex crown-root fractures in the esthetic zone refer to a type of dental trauma occurring in the anterior region, characterized by concurrent fractures involving both the crown and the root, with associated pulp exposure and periodontal tissue injury. These injuries consistently exhibit critical anatomical features, including a fixed palatal fracture location below the alveolar crest, compromised residual tooth structure, and frequent encroachment of the biological width. To predict treatment outcomes, a risk assessment framework based on the restoration-tooth-periodontium interface was developed. Resistance risk was evaluated by assessing the type of residual dentin ferrule and the length of the root within the alveolar bone, while periodontal risk was assessed according to gingival phenotype and alveolar bone morphology. Based on these risk dimensions and the principles of aesthetics, stability, and minimally invasive treatment, a diagnostic classification system was established to categorize fractures into three types: favorable, intervention and high-risk. Type-specific management strategies were proposed: for favorable cases, crown lengthening combined with deep margin elevation to reduce periodontal risk is recommended; for intervention cases, orthodontic extrusion or surgical extrusion is applied to simultaneously address both ferrule deficiency and biological width violation; for high-risk cases, extraction followed by implant restoration is advised due to limited root preservation value. The presented classification enables clinicians to adopt a scientific and structured approach to treatment planning for these complex crown-root fractures in the aesthetic zone.
Humans ; Tooth Fractures/therapy* ; Tooth Root/injuries* ; Risk Assessment ; Tooth Crown/injuries* ; Periodontium ; Esthetics, Dental ; Dental Restoration, Permanent/methods*

Objective To explore the application of plasma 7 microRNA (miR7) testing in the differential diagnosis of very early-stage hepatocellular carcinoma (HCC). Methods This study is a multicenter real-world study. Patients with single hepatic lesion (maximum diameter≤2 cm) who underwent plasma miR7 testing at Zhongshan Hospital, Fudan University, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Anhui Provincial Hospital, and Peking University People’s Hospital between January 2019 and December 2024 were retrospectively enrolled. Patients were divided into very early-stage HCC group and non-HCC group, and the clinical pathological characteristics of the two groups were compared. The value of plasma miR7 levels, alpha-fetoprotein (AFP), and des-gamma-carboxy prothrombin (DCP) in the differential diagnosis of very early-stage HCC was evaluated using receiver operating characteristic (ROC) curves and area under the curve (AUC). In patients with both negative AFP and DCP (AFP＜20 ng/mL, DCP＜40 mAU/mL), the diagnostic value of plasma miR7 for very early-stage HCC was analyzed. Results A total of 64 528 patients from 4 hospitals underwent miR7 testing, and 1 682 were finally included, of which 1 073 were diagnosed with very early-stage HCC and 609 were diagnosed with non-HCC. The positive rate of miR7 in HCC patients was significantly higher than that in non-HCC patients (67.9% vs 24.3%, P＜0.001). ROC curves showed that the AUCs for miR7, AFP, and DCP in distinguishing HCC patients from the non-HCC individuals were 0.718, 0.682, and 0.642, respectively. The sensitivities were 67.85%, 43.71%, and 44.45%, and the specificities were 75.70%, 92.78%, and 83.91%, respectively. The pairwise comparison of AUCs showed that the diagnostic efficacy of plasma miR7 detection was significantly better than that of AFP or DCP (P＜0.05). Although its specificity was slightly lower than AFP and DCP, the sensitivity was significantly higher. Among patients negative for both AFP and DCP, miR7 maintained an AUC of 0.728 for diagnosing very early-stage HCC, with 67.82% sensitivity and 77.73% specificity. Conclusions Plasma miR7 testing is a potential molecular marker with high sensitivity and specificity for the differential diagnosis of small hepatic nodules. In patients with very early-stage HCC lacking effective molecular markers (negative for both AFP and DCP), miR7 can serve as a novel and effective molecular marker to assist diagnosis.

Objective To explore the immediate,long-term,and delayed effects of spiral stabilizing muscle chain technique compared to static distraction and Proprioceptive Neuromuscular Facilitation(PNF)stretching techniques on the flexibility of hip flexors.Methods Ninety subjects were randomly divided intothree groups of 30 each.Group 1 underwent the static stretching of the hip joint.Group 2 received PNF stretching,and Group 3 participated in SPS training.All participants were measured for hip extension angle to assess hip flexor flexibility before training,immediately after the first training session,at the end of 4 weeks of training,and 2 weeks after training cessation.Results Within-group comparisons showed significant increases in hip extension angles after one training session,after 4 weeks of training,and after 2 weeks of cessation compared to pre-training(P＜0.05).Between-group comparisons indicated no statistically significant differences in hip extension angle improvements among the three groups after one training session,after 4 weeks of training,and after 2 weeks of cessation(P＞0.05).Conclusion SPS training,static stretching,and PNF stretching all demonstrate good immediate,long-term,and delayed effects on improving hip extension angles,with consistent stretching outcomes.

OBJECTIVES: To explore the role of oxidative stress and immune infiltration in rheumatoid arthritis (RA). METHODS: RA datasets GSE55235 (10 RA vs 10 normal samples) and GSE55457 (13 RA vs 10 normal samples) from the GEO database were merged as the test set to identify the differentially expressed genes (DEGs) in RA using R. The DEGs were intersected with oxidative stress-related genes to obtain oxidative stress-associated DEGs. KEGG and GO enrichment analyses of the DEGs were performed, and the RA-related pathways and biological processes were analyzed using GSEA. A protein-protein interaction (PPI) network was constructed using STRING and Cytoscape, and the top 10 key genes were obtained using the Degree algorithm. The validation dataset GSE1919 from GEO database was used for ROC analysis of the key genes to obtain the core genes, and their correlations with infiltrating immune cells were analyzed using CIBERSORT. The results were verified by RT-qPCR for detecting expression levels of the core genes in RA and normal joint samples. RESULTS: We identified 89 oxidative stress-associated DEGs. Enrichment analysis suggested that these DEGs were involved in the biological processes including oxidative stress, chemical stress response, reactive oxygen species response, and lipopolysaccharide response. ROC analysis showed that the 5 core genes (STAT1, MMP9, MYC, CCL5, and JUN) all had AUC values >0.7, indicating their high diagnostic sensitivity and specificity for RA. These genes were closely correlated with immune cells, particularly T cells. RT-qPCR confirmed significant differential expressions of the core genes between RA and normal samples. CONCLUSIONS Oxidative stress and diverse immune responses are features of RA, and the immune responses contribute to activation of oxidative stress. The identified core genes can potential serve as new diagnostic markers for RA.
Arthritis, Rheumatoid/genetics* ; Oxidative Stress/genetics* ; Humans ; Computational Biology ; Protein Interaction Maps ; Gene Expression Profiling ; Gene Regulatory Networks

Objective To construct 5 machine-learning models and compare their performance in predicting the associations between pre-pregnancy socio-psycho-behavioral exposures of both spouses and preconception outcomes.Methods Based on Chongqing Preconception Reproductive Health and Birth Outcome Cohort of volunteers recruited from Chongqing Health Center for Women and Children during January 2019 and March 2022,5 447 couples were recruited and surveyed through interviewer-interview for the demographic and social-psychological-behavioral data of both spouses(221 variables).According to the inclusion and exclusion criteria,4 097 couples were finally included,and randomly assigned into a training set(n=2 867 spouses)and a validation set(n=1 230 spouses)at a ratio of 7∶3.Feature analysis and collinear screening were applied to select the potential exposure factors.In consideration of difficulty to carry out semen parameters analysis in primary healthcare institutions,feature Set 1 including sperm parameters and feature Set 2 excluding semen parameters were constructed by including or excluding sperm quality simultaneously in the training set and the validation set.Five algorithms,that is,Logistic Regression,Naive Bayes,Random Forest,Gradient Boosting Machine,and Support Vector Machine,were used to construct preconception outcome prediction models,and the parameters of each model were optimized using random search combined with grid search.The predictive performance of each model was compared using precision,recall,F1 score,area under the receiver operating characteristic curve(AUC),and calibration curve.The optimal model was then selected by comparing the changes in the predictive ability of the questionnaire data for fertility outcomes with or without semen parameters.Results There were 24 variables screened out in feature Set 1,and 16 variables in feature Set 2.In feature Set 1,the gradient boosting machine performed better,with a relatively higher AUC value(0.651)and better F1 score(0.61).The logistic regression model performed stably(AUC value=0.647)and was suitable as the reference model.The random forest(AUC value=0.641),Naive Bayes(AUC value=0.641),and support vector machine(AUC value=0.634)performed second-best.By utilizing the gradient boosting machine,comparable results were found between the predictions from feature sets with or without semen parameters,as in feature Set 1,the AUC value of its validation set was 0.651(95%CI:0.629～0.681),the prediction accuracy was 0.63,the recall rate was 0.65,and the average precision value F1 was 0.61;and in feature Set 2,the AUC value of its validation set was 0.649(95%CI:0.624～0.663),and both the calibration curves were close to the ideal curve.The prediction results indicated that in feature Set 1,the features highly negatively correlated with preconception outcomes were female age,male age,and no pregnancy within 1 year without contraception,while the features highly positively correlated with preconception outcomes were female pregnancy history,total sperm vitality,and use of contraceptive measures before enrollment.Conclusion Among the 5 machine-learning algorithms performed in this cohort data,the gradient boosting machine shows slightly better performance.There are 24 factors being associated with preconception outcomes in both spouses,and the performance of the simplified model excluding semen parameters is not significantly declined.It is feasible to use machine-learning methods to predict human preconception outcomes through social-psychological-behavioral questionnaires.

Objective To explore the correlation of MET status in patients with advanced prostatic acinar adenocarcinoma with the clinical pathological parameters and prognosis. Methods The specimen from 135 patients with advanced prostatic acinar adenocarcinoma was included. The expression of c-MET protein was detected via immunohistochemistry, and MET gene amplification was assessed by fluorescence in situ hybridization. The relationships of c-MET expression and gene amplification with clinicopathological features and prognosis were analyzed. Results The positive expression rate of c-MET was 52.60% (71/135). Compared with the c-MET expression in adjacent tissues, that in tumor tissues showed lower heterogeneous expression. Among the cases, 1.71% (2/117) exhibited MET gene polyploidy, but no gene amplification was detected. Positive c-MET expression was significantly correlated with high Gleason scores and grade groups (P=0.0073). However, no significant relationship was found between c-MET expression and progression-free survival or post-treatment t-PSA levels. Conclusion c-MET protein is expressed at a relatively low level in advanced prostatic acinar adenocarcinoma, suggesting that c-MET may not be a viable target for ADC drug development in prostatic acinar adenocarcinoma.