Background: and Purpose Vertebrobasilar fusiform aneurysms (VBFAs) carry substantial morbidity and mortality, but optimal management for unruptured VBFAs remains unclear. We compared the safety and efficacy of conservative management (CM), stent-assisted coiling (SAC), and flow diverters (FDs) in patients with unruptured VBFAs, focusing on long-term prognosis. Methods: This study included data from a nationwide Chinese cohort of patients with vertebrobasilar dissecting aneurysms. Inverse probability of treatment weighting (IPTW) balanced confounders across groups. The primary outcome was poor prognosis (modified Rankin Scale score >2). Secondary outcomes included aneurysm rupture, ischemic stroke, compression symptoms, and VBFA-related deaths. Logistic regression estimated odds ratios (ORs) and 95% confidence intervals (CIs). Subgroup and sensitivity analyses were performed. Results: Among 1,115 patients with unruptured VBFAs, 838 (median age, 54 years; 655 men) were included. After IPTW, baseline characteristics were balanced. Median follow-up was 54 months. FD was associated with a lower risk of poor prognosis than CM (OR, 0.48 [95% CI, 0.30 to 0.77]; p=0.002), with no difference between CM and SAC. FD also reduced aneurysm rupture (OR, 0.20 [95% CI, 0.07 to 0.60]; p=0.004) and compression symptoms (OR, 0.30 [95% CI, 0.13 to 0.68]; p=0.004) versus CM. Time-to-event analyses further revealed significant differences in vertebral artery lesions and Type I–II VBFAs, whereas no significant differences were observed in basilar or vertebrobasilar junction lesions or in Type III–IV VBFAs. Conclusions Compared with CM, FD was associated with improved long-term outcomes in unruptured VBFAs, particularly in vertebral artery lesions and Type I–II VBFAs, although residual confounding cannot be excluded.

ObjectiveTo generate cynomolgus and rhesus monkey models carrying the Booroola fecundity (FecB) variant of bone morphogenetic protein receptor type 1B (BMPR1B) gene (designated BMPR1B^FecB) using adenine base edit technology and to explore genetic improvement strategies for enhancing the reproductive performance of laboratory macaques. MethodsFour single-guide RNAs (sgRNAs) were designed to target the BMPR1B c.746A>G locus in cynomolgus and rhesus monkeys. The sgRNAs were combined with the ABE8e-SpRY base editor, and the resulting editing complexes were microinjected into zygotes of both macaque species. Following in vitro culture of the injected embryos, nested PCR amplification was performed to detect the base-editing efficiency at the target site to screen for highly efficient sgRNAs. Subsequently, normally developing gene-edited embryos were transferred into the oviducts of surrogates. Seven days after birth, ear skin or peripheral blood samples were collected from the newborn monkeys for genotyping and mosaicism analysis, and the growth, development, and health status of the gene-edited monkeys were monitored. ResultsAmong the four candidate sgRNAs, sgRNA4 was identified as achieving 100% editing efficiency at the c.746A>G site. A total of 17 live monkey offspring were obtained via embryo transfer, including 8 cynomolgus monkeys and 9 rhesus monkeys. Genotyping results showed that all 8 newborn cynomolgus monkeys carried the c.746A>G point mutation, with an editing efficiency of 100% (8/8), of which 37.50% (3/8) were mosaics. Among the 9 newborn rhesus monkeys, 8 individuals carried the c.746A>G mutation, with an editing efficiency of 88.89% (8/9), of which 75.00% (6/8) were mosaics. ConclusionThe ABE8e-SpRY base-editing system enables precise editing at the c.746A>G (p.Q249R) locus of the BMPR1B gene in both cynomolgus and rhesus monkey embryos, resulting in the successful establishment of laboratory monkey models carrying the BMPR1B^FecB variant. These models provide a valuable foundation for future studies of the regulatory role of the BMPR1B^FecB variant in reproductive performance at the non‑human primate level, as well as for exploring genetic improvement strategies to enhance reproductive performance in laboratory monkeys.

Objective: To explore the therapeutic effects of different surgical methods for temporomandibular joint disc reduction and anchoring surgery, providing reference for optimizing this surgical procedure. Method: The study was approved by the hospital ethics committee. 173 patients (195 joints) who underwent temporomandibular joint disc repositioning and anchoring surgery were selected for retrospective analysis. Patients were categorized into groups A (traditional preauricular incision-scalpel/tissue scissors anterior attachment release), 35 patients (40 joints), B (traditional preauricular incision-plasma bipolar radiofrequency electrode anterior attachment release), 42 patients (46 joints), C (revised tragus incision - scalpel/tissue scissors anterior attachment release), 50 patients (58 joints), and D (revised tragus incision-plasma bipolar radiofrequency electrode anterior attachment release), 46 patients (51 joints). After a 6-month postoperative follow-up, the differences in maximum mouth opening (MMO), visual analogue scale (VAS), effective rate of joint disc reduction, incidence of preauricular numbness, obvious scars among patients in each group at 1, 3, and 6 months were compared postoperatively. Results: After surgery, the MMO of all four groups of patients initially shrunk and then gradually increased compared to before surgery. At the 1-month follow-up after surgery, the plasma bipolar radiofrequency release (B+D) group had a smaller impact on the patient’s MMO compared to the surgical knife/tissue scissors release (A+C) group (P < 0.05). Postoperative VAS scores for all four groups showed a gradual decrease from pre-operative levels, with the (B+D) group scoring significantly lower in the first month post-surgery compared to the (A+C) group (P < 0.05). Six months post-surgery, the rate of joint disc reduction of the four groups were higher than 95%, with no significant differences observed between the groups (P > 0.05). Patients in the revised tragus incision (C+D) group experienced a lower rate of preauricular numbness compared to those in the traditional preauricular incision (A+B) group (4.59% vs. 12.79%, P < 0.05), The incidence of obvious scars in the (C+D) group was significantly lower than that in the (A+B) group (3.67% vs. 23.26%, P < 0.05). Conclusion The revised tragus incision is superior to traditional preauricular incision in terms of protecting the auriculotemporal nerve and the scars were more inconspicuous. Further, the plasma bipolar radiofrequency electrode is superior to the scalpel/tissue scissors in terms of mouth opening recovery and pain control. For temporomandibular joint disc reduction and anchoring surgery, a modified tragus incision combined with plasma bipolar radiofrequency electrode to release the anterior attachment of the joint disc can be recommended as a surgical option.

Aim To reveal the mechanism of CIP4 homologs protein 1(RICH1)are involved in the regu-lation of myocardial fibrosis.Methods Mouse cardiac fibroblasts(MCFs)cells were treated with transforming growth factor-β(TGF-β1)to induce the formation of a myocardial fibrosis cell model;the level of the target protein was detected by Western blotting;and the RICH1 gene was detected by transfection of the cells with plasmid.The RICH1 gene was overexpressed(RICH 1 OE)using plasmid transfection;the RICH1 gene was silenced using siRNA fragment(siRICH1);and the expression levels of myocardial fibrosis marker genes,such as Col1 a1,Col3 a1,and Acta2,were de-tected using RT-qPCR.Results RICH1 was signifi-cantly down-regulated in TGF-β1-treated MCFs;the expression levels of myocardial fibrosis marker genes,such as Col1 a1,Col3a1,and Acta2,were down-regu-lated in the RICH1 OE+TGF-β1 group;and in the siRICH1+TGF-β1 group,myocardial fibrosis marker genes,such as Col1 a1,Col3a1 and Acta2 were up-regulated at the expression level;phosphorylated SMAD2(p-SMAD2)and phosphorylated SMAD3(p-SMAD3)levels were down-regulated in the siRICH1 OE+TGF-β1 group.p-SMAD2 and P-SMAD3 levels were upregulated in the siRICH1+TGF-β1 group.Conclusion RICH1 inhibits TGF-β1-induced myo-cardial fibrosis;RICH1 inhibits TGF-β1-induced myo-cardial fibrosis by negatively regulating the SMAD2/3 signaling pathway.

Aim To reveal the mechanism of CIP4 homologs protein 1(RICH1)are involved in the regu-lation of myocardial fibrosis.Methods Mouse cardiac fibroblasts(MCFs)cells were treated with transforming growth factor-β(TGF-β1)to induce the formation of a myocardial fibrosis cell model;the level of the target protein was detected by Western blotting;and the RICH1 gene was detected by transfection of the cells with plasmid.The RICH1 gene was overexpressed(RICH 1 OE)using plasmid transfection;the RICH1 gene was silenced using siRNA fragment(siRICH1);and the expression levels of myocardial fibrosis marker genes,such as Col1 a1,Col3 a1,and Acta2,were de-tected using RT-qPCR.Results RICH1 was signifi-cantly down-regulated in TGF-β1-treated MCFs;the expression levels of myocardial fibrosis marker genes,such as Col1 a1,Col3a1,and Acta2,were down-regu-lated in the RICH1 OE+TGF-β1 group;and in the siRICH1+TGF-β1 group,myocardial fibrosis marker genes,such as Col1 a1,Col3a1 and Acta2 were up-regulated at the expression level;phosphorylated SMAD2(p-SMAD2)and phosphorylated SMAD3(p-SMAD3)levels were down-regulated in the siRICH1 OE+TGF-β1 group.p-SMAD2 and P-SMAD3 levels were upregulated in the siRICH1+TGF-β1 group.Conclusion RICH1 inhibits TGF-β1-induced myo-cardial fibrosis;RICH1 inhibits TGF-β1-induced myo-cardial fibrosis by negatively regulating the SMAD2/3 signaling pathway.

Objective:To explore the interrelationship between brain functional networks and features in functional magnetic resonance imaging(fMRI)of patients with Alzheimer's disease(AD),and to construct mixed-function networks(MFN),and apply them in machine learning classification models to improve the accuracy of AD classification.Methods:102 AD patients and 227 healthy subjects in the Alzheimer's Neuroimaging Initiative(ADNI)dataset were retrospectively analyzed.The partial correlation brain network of the blood oxygen level dependent(BOLD)signal was calculated and fused with low-frequency wave amplitude(ALFF),fractional low-frequency wave amplitude(fALFF)and local consistency(ReHo)features to construct MFN.Network topology parameters were extracted,and a variety of machine learning classification models were constructed based on MFN topological parameters,accuracy,precision,recall and area under the curve(AUC)were used to evaluate the predictive efficiency of the models.Results:By constructed MFN and calculated intra group to inter group ratio(IIGR),35 features could be obtained from ALFF,fALFF and ReHo feature topological parameter analysis,after rank sum test and FDR correction,there were statistical differences among 28 features(P＜0.05).The classification results show that,all the five classifiers have high classification performance on the test data set.The accuracy,precision and recall rates of random forest(RF),adaptive lifting algorithm(AdaBoost),guided aggregation algorithm(Bagging)and support vector machine(SVM)were all 99.7％,and the AUC values were up to 100％,99.5％,99.1％and 99.5％,respectively.The accuracy(98.5％),precision(98.5％),recall(98.5％),and AUC(99.1％)of the multi-layer perceptron(MLP)were slightly lower than other models,but remained excellent.It was worth noting that RF has the highest AUC value of all models at 100.0％,while Bagging has the lowest AUC value(99.1％)in the integrated approach.The results of performance comparison show that,MFN classification model can significantly improve the recognition and classification of AD disease,and greatly improve the performance of various indicators of the classifier.The results showed that,MFN classification model was superior to intelligent classification based fusion,DBN-based multitask learning,PVT-TSVM,unsupervised learning and clustering,SVM and SVM of degree 3 polynomial kernel function in key indicators such as accuracy(99.13％),AUC(99.42％),recall rate(99.46％)and specificity(99.42％)with plasma proteins,machine learning algorithms.It was further proved that MFN classification model has good generalization ability and robustness in AD disease classification.Conclusion:The AD classification model constructed based on brain mixed function network topology parameters and machine learning can improve the accuracy of AD classification.

Objective To analyze and evaluate the early warning efficacy of D-dimer/albumin ratio(DAR)combined with interleukin-6(IL-6)and fibrin degradation products(FDP)in the postoperative treatment of acute Stanford type A aortic dissection(ATAAD).Methods A retrospective cohort study was conducted on 284 ATAAD patients who underwent the Sun's procedure at our hospital from July 2024 to March 2025.Patients were divided into a non-adverse outcome group(n=196)and an adverse outcome group(n=88)based on the occurrence of postop-erative complications within 30 days,including acute renal failure requiring dialysis,secondary thoracotomy for hemostasis,severe neurological complications,multiple organ failure,or all-cause mortality.Preoperative baseline data,perioperative parameters,and laboratory indicators were collected via the electronic medical record system.The Mann-Whitney U test was used to compare the differences between groups for continuous variables that did not conform to the normal distribution,and Chi-square test or Fisher's exact test was selected for statistical difference analysis according to the frequency distribution characteristics of categorical variables.On the basis of univariate analysis,multivariate logistic regression analysis was used to screen independent risk factors.Results Statistically significant differences were observed between the non-adverse and adverse outcome group in age,cardiopulmonary bypass time,lactate dehydrogenase(LDH),IL-6,D-dimer(D-D),FDP,and DAR levels(P<0.05).Multivariate analysis revealed that DAR,IL-6,D-D,FDP,and prolonged cardiopulmonary bypass time were independent risk factors for adverse postoperative outcomes(P<0.05).Combined detection analysis demonstrated that the combination of DAR,IL-6,FDP,and cardiopulmonary bypass time yielded the highest predictive efficacy,with an area under the ROC curve of 0.886(95％CI:0.846～0.927).Conclusion The combination of DAR,IL-6,FDP,and cardio-pulmonary bypass time effectively predicts adverse postoperative outcomes in ATAAD patients.This biomarker panel may serve as a robust predictive tool for postoperative risk stratification.

Objective To explore the application value of serological markers in the screening of malignant tumor bone metastasis.Methods A total of 113 patients with malignant tumor bone metastasis first diag-nosed in a hospital from June 2023 to February 2024 were selected as case group.Another 80 patients with malignant tumor without bone metastasis diagnosed in the same period were selected as the control group.The levels of serological markers[serum calcium(Ca),parathyroid hormone(PTH),Ca/PTH,procollagen type 1 amino-terminal propeptide(P1NP),beta-C-terminal telopeptide of type 1 collagen(β-CTX)and N-terminal mid-fragment of osteocalcin]were compared between the two groups.Receiver operating characteristic(ROC)curves were plotted to analyze the value of serological markers in screening for bone metastases of lung canc-er,prostate cancer and breast cancer.Multivariate Logistic regression was used to analyze the related factors of malignant tumor bone metastasis.Results The levels of Ca,Ca/PTH,β-CTX and P1NP in case group were significantly higher than those in control group,while PTH in case group was lower than that in control group,with statistical significance(P<0.05).ROC curve results showed that Ca,PTH,Ca/PTH,P1NP and β-CTX had high efficacy in screening malignant tumor bone metastases,and the area under the curve(AUC)was 0.718,0.699,0.712,0.648 and 0.593,respectively.Multivariate Logistic regression analysis showed that Ca/PTH and P1NP were the influencing factors of bone metastasis in malignant tumor(OR=5.036,1.013,P<0.05).The AUC of Ca,PTH and Ca/PTH screening for bone metastasis of lung cancer were 0.781,0.652 and 0.669,respectively.The AUC of β-CTX and P1NP screening for bone metastasis of prostate cancer were 0.800 and 0.815 respectively.The AUC of Ca and P1NP screening for breast cancer with bone metastasis was 0.751 and 0.794,respectively.Conclusion Serological markers(Ca,PTH,Ca/PTH,P1NP and β-CTX)are valuable in screening for malignant tumor bone metastasis.

Bone metastasis is a serious complication in the course of malignant tumors and has a poor prog-nosis.The incidence of breast cancer,prostate cancer and lung cancer is the highest.A highly sensitive and highly specific test method for the early diagnosis of malignant bone metastases of these tumors,which is es-sential for reducing the incidence of bone-related events and improving the prognosis of patients with malig-nant tumors,is urgently needed.At present,the diagnosis of bone metastasis in patients with malignant tumors mainly relies on imaging.However,due to limitations in the development of imaging technology,its clinical use is still limited by sensitivity,cost-effectiveness,availability,and others.Close clinical follow-up and monitoring of patients diagnosed with malignant tumors are essential for effective patient management.Based on the current literature,this review aims to summarize the early diagnosis and detection methods for bone metastases in breast cancer,prostate cancer and lung cancer,including imaging techniques,pathology,bio-chemistry and molecular methods,and to review the development trends of future diagnostic techniques.

Large language models (LLMs) such as ChatGPT, Claude, Llama, and Qwen are emerging as transformative technologies for the diagnosis and treatment of various diseases. With their exceptional long-context reasoning capabilities, LLMs are proficient in clinically relevant tasks, particularly in medical text analysis and interactive dialogue. They can enhance diagnostic accuracy by processing vast amounts of patient data and medical literature and have demonstrated their utility in diagnosing common diseases and facilitating the identification of rare diseases by recognizing subtle patterns in symptoms and test results. Building on their image-recognition abilities, multimodal LLMs (MLLMs) show promising potential for diagnosis based on radiography, chest computed tomography (CT), electrocardiography (ECG), and common pathological images. These models can also assist in treatment planning by suggesting evidence-based interventions and improving clinical decision support systems through integrated analysis of patient records. Despite these promising developments, significant challenges persist regarding the use of LLMs in medicine, including concerns regarding algorithmic bias, the potential for hallucinations, and the need for rigorous clinical validation. Ethical considerations also underscore the importance of maintaining the function of supervision in clinical practice. This paper highlights the rapid advancements in research on the diagnostic and therapeutic applications of LLMs across different medical disciplines and emphasizes the importance of policymaking, ethical supervision, and multidisciplinary collaboration in promoting more effective and safer clinical applications of LLMs. Future directions include the integration of proprietary clinical knowledge, the investigation of open-source and customized models, and the evaluation of real-time effects in clinical diagnosis and treatment practices.
Humans ; Large Language Models ; Tomography, X-Ray Computed