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.

Objective To evaluate the efficacy and safety of polyethylene glycol electrolyte powder(PEG)combined with linaclotide(Lin)for bowel preparation in elderly constipated patients before colonoscopy.Methods In this prospective,randomized controlled trial,90 elderly patients with constipation undergoing colonoscopy were recruited at our hospital from June 2022 to December 2023.Participants were randomly assigned to three groups(n=30 each):PEG-3L alone,PEG-3L+Lin,and PEG-2L+Lin.Primary outcome was Boston Bowel Preparation Scale(BBPS)score and secondary outcomes included adverse event rates,colonoscopy completion rate,withdrawal time,and polyp detection rate.Statistical analysis was performed using independent t-tests and chi-square tests.Results The PEG-3L+Lin group achieved significantly higher BBPS scores than both PEG-3L alone and PEG-2L+Lin groups did(both P<0.001).The PEG-2L+Lin group also outperformed the PEG-3L alone group in cleansing efficacy(90.0%vs.76.7%,P=0.008).The PEG-2L+Lin group demonstrated the best tolerability and lowest adverse event rate,the PEG-3L group had the longest withdrawal time(P<0.05),but the three groups showed no significant difference in polyp detection rates.Conclusion PEG combined with linaclotide significantly improves bowel cleansing in elderly constipated patients.PEG-2L+Lin regimen provides optimal balance between efficacy,safety,and tolerability,making it a preferable choice for this population.

Digital technologies have become an integral part of complete denture restoration. With advancement in computer-aided design and computer-aided manufacturing (CAD/CAM), tools such as intraoral scanning, facial scanning, 3D printing, and numerical control machining are reshaping the workflow of complete denture restoration. Unlike conventional methods that rely heavily on clinical experience and manual techniques, digital technologies offer greater precision, predictability, and efficacy. They also streamline the process by reducing the number of patient visits and improving overall comfort. Despite these improvements, the clinical application of digital complete denture restoration still faces challenges that require further standardization. The major issues include appropriate case selection, establishing consistent digital workflows, and evaluating long-term outcomes. To address these challenges and provide clinical guidance for practitioners, this expert consensus outlines the principles, advantages, and limitations of digital complete denture technology. The aim of this review was to offer practical recommendations on indications, clinical procedures and precautions, evaluation metrics, and outcome assessment to support digital restoration of complete denture in clinical practice.
Humans ; Denture, Complete ; Computer-Aided Design ; Denture Design/methods* ; Consensus ; Printing, Three-Dimensional

Since the promulgation of the first Drug Administration Law of the People's Republic of China 40 years ago in 1984, China has undergone four main stages in the traditional Chinese medicine(TCM) regulation: the initial establishment of TCM regulation rules(1984-1997), the formation of a modern TCM regulatory system(1998-2014), the reform of the review and approval system for new TCM drugs(2015-2018), and the construction of a scientific regulation system for TCM(2019-2024). Over the past five years, a series of milestone achievements of TCM regulation in China have been achieved in the six aspects, including its strategic objectives and the establishment of a science-based regulatory system, the reform of the review and approval system for new TCM drugs, the optimization and improvement of the TCM standard system and its formation mechanism, comprehensive enhancement of regulatory capabilities for TCM safety, international harmonization of TCM regulation and its role in promoting innovation. Looking ahead, centered on advancing TCMRS to establish a sound regulatory framework tailored to the unique characteristics of TCM, TCM regulation will evolve into new reform patterns, advancing and extending across eight critical fronts, including the legal framework and policy architecture, the review and approval system for new TCM drugs, the quality standard and management system of TCM, the comprehensive quality & safety regulation and traceability system, the research and transformation system for TCMRS, AI-driven innovations in TCM regulation, the coordination between high-quality industrial development and high-level regulation, and the leadership in international cooperation and regulatory harmonization. In this way, a unique path for the development of modern TCM regulation with Chinese characteristics will be pioneered.
Humans ; China ; Drugs, Chinese Herbal/standards* ; History, 20th Century ; History, 21st Century ; Medicine, Chinese Traditional/trends*

Motor imagery (MI) is a mental process that can be recognized by electroencephalography (EEG) without actual movement. It has significant research value and application potential in the field of brain-computer interface (BCI) technology. To address the challenges posed by the non-stationary nature and low signal-to-noise ratio of MI-EEG signals, this study proposed a Riemannian spatial filtering and domain adaptation (RSFDA) method for improving the accuracy and efficiency of cross-session MI-BCI classification tasks. The approach addressed the issue of inconsistent data distribution between source and target domains through a multi-module collaborative framework, which enhanced the generalization capability of cross-session MI-EEG classification models. Comparative experiments were conducted on three public datasets to evaluate RSFDA against eight existing methods in terms of classification accuracy and computational efficiency. The experimental results demonstrated that RSFDA achieved an average classification accuracy of 79.37%, outperforming the state-of-the-art deep learning method Tensor-CSPNet (76.46%) by 2.91% ( P < 0.01). Furthermore, the proposed method showed significantly lower computational costs, requiring only approximately 3 minutes of average training time compared to Tensor-CSPNet's 25 minutes, representing a reduction of 22 minutes. These findings indicate that the RSFDA method demonstrates superior performance in cross-session MI-EEG classification tasks by effectively balancing accuracy and efficiency. However, its applicability in complex transfer learning scenarios remains to be further investigated.
Electroencephalography/methods* ; Brain-Computer Interfaces ; Humans ; Imagination/physiology* ; Signal Processing, Computer-Assisted ; Movement/physiology* ; Signal-To-Noise Ratio ; Deep Learning ; Algorithms

Definitive treatment of lung cancer with radiotherapy is challenging, as respiratory motion and anatomical changes can increase the risk of severe off-target effects during radiotherapy. Online adaptive radiotherapy (ART) is an evolving approach that enables timely modification of a treatment plan during the interfraction of radiotherapy, in response to physiologic or anatomic variations, aiming to improve the dose distribution for precise targeting and delivery in lung cancer patients. The effectiveness of online ART depends on the seamless integration of multiple components: sufficient quality of linear accelerator-integrated imaging guidance, deformable image registration, automatic recontouring, and efficient quality assurance and workflow. This review summarizes the present status of online ART for lung cancer, including key technologies, as well as the challenges and areas of active research in this field.
Humans ; Lung Neoplasms/radiotherapy* ; Radiotherapy Planning, Computer-Assisted/methods*

Research on IgG4-related disease (IgG4-RD), an autoimmune condition recognized to be a unique disease entity only two decades ago, has processed from describing patients' symptoms and signs to summarizing its critical pathological features, and further to investigating key pathogenic mechanisms. Challenges in gaining a better understanding of the disease, however, stem from its relative rarity-potentially attributed to underrecognition-and the absence of ideal experimental animal models. Recently, with the development of various high-throughput techniques, "omics" studies at different levels (particularly the single-cell omics) have shown promise in providing detailed molecular features of IgG4-RD. While, the application of omics approaches in IgG4-RD is still at an early stage. In this paper, we review the current progress of omics research in IgG4-RD and discuss the value of machine learning methods in analyzing the data with high dimensionality.
Humans ; Immunoglobulin G4-Related Disease/metabolism* ; Immunoglobulin G/metabolism* ; Machine Learning ; Animals ; Proteomics/methods*

Purpose: This study assessed the performance of the ultrasound-guided attenuation parameter (UGAP) in diagnosing and grading hepatic steatosis in patients with metabolic dysfunctionassociated steatotic liver disease (MASLD). Magnetic resonance imaging proton density fat fraction (MRI-PDFF) served as the reference standard. Methods: Patients with hepatic steatosis were enrolled in this prospective study and underwent UGAP measurements. MRI-PDFF values of ≥5%, ≥15%, and ≥25% were used as references for the diagnosis of steatosis grades ≥S1, ≥S2, and S3, respectively. Spearman correlation coefficients and area under the receiver operating characteristic curves (AUCs) were calculated. Results: Between July 2023 and June 2024, the study included 88 patients (median age, 40 years; interquartile range [IQR], 36 to 46 years), of whom 54.5% (48/88) were men and 45.5% (40/88) were women. Steatosis grades exhibited the following distribution: 22.7% (20/88) had S0, 50.0% (44/88) had S1, 21.6% (19/88) had S2, and 5.7% (5/88) had S3. The success rate for UGAP measurements was 100%. The median UGAP value was 0.74 dB/cm/MHz (IQR, 0.65 to 0.82 dB/ cm/MHz), and UGAP values were positively correlated with MRI-PDFF (r=0.77, P<0.001). The AUCs of UGAP for the diagnoses of ≥S1, ≥S2, and S3 steatosis were 0.91, 0.90, and 0.88, respectively. In the subgroup analysis, 98.4% (60/61) of patients had valid controlled attenuation parameter (CAP) values. UGAP measurements were positively correlated with CAP values (r=0.65, P<0.001). Conclusion Using MRI-PDFF as the reference standard, UGAP demonstrates good diagnostic performance in the detection and grading of hepatic steatosis in patients with MASLD.

Glaucoma is a group of optic nerve disorders characterized by progressive optic nerve atrophy and visual field defects, which can lead to irreversible blindness. Early diagnosis of glaucoma is essential for preventing visual loss. However, due to the absence of obvious early symptoms, the diagnosis of glaucoma remains challenging. Visual electrophysiological examinations, an objective approach for evaluating visual function, have the potential to be used in the early diagnosis of glaucoma. This review integrates the latest publications to introduce visual electrophysiological examination techniques, including electroretinography(ERG)and visual evoked potential(VEP). It also explores the mechanisms underlying these techniques and their application value in the early diagnosis of glaucoma. In addition, this review summarizes the advantages, limitations, and applicable scenarios of different visual electrophysiological techniques. Finally, the review provides an outlook on the development prospects of visual electrophysiological techniques in the early diagnosis of glaucoma. The findings of this review can assist clinicians in selecting appropriate diagnostic methods, promote the innovation and development of early visual electrophysiological diagnostic techniques for glaucoma, and contribute to reducing the risk of blindness caused by glaucoma.

Purpose: This study assessed the performance of the ultrasound-guided attenuation parameter (UGAP) in diagnosing and grading hepatic steatosis in patients with metabolic dysfunctionassociated steatotic liver disease (MASLD). Magnetic resonance imaging proton density fat fraction (MRI-PDFF) served as the reference standard. Methods: Patients with hepatic steatosis were enrolled in this prospective study and underwent UGAP measurements. MRI-PDFF values of ≥5%, ≥15%, and ≥25% were used as references for the diagnosis of steatosis grades ≥S1, ≥S2, and S3, respectively. Spearman correlation coefficients and area under the receiver operating characteristic curves (AUCs) were calculated. Results: Between July 2023 and June 2024, the study included 88 patients (median age, 40 years; interquartile range [IQR], 36 to 46 years), of whom 54.5% (48/88) were men and 45.5% (40/88) were women. Steatosis grades exhibited the following distribution: 22.7% (20/88) had S0, 50.0% (44/88) had S1, 21.6% (19/88) had S2, and 5.7% (5/88) had S3. The success rate for UGAP measurements was 100%. The median UGAP value was 0.74 dB/cm/MHz (IQR, 0.65 to 0.82 dB/ cm/MHz), and UGAP values were positively correlated with MRI-PDFF (r=0.77, P<0.001). The AUCs of UGAP for the diagnoses of ≥S1, ≥S2, and S3 steatosis were 0.91, 0.90, and 0.88, respectively. In the subgroup analysis, 98.4% (60/61) of patients had valid controlled attenuation parameter (CAP) values. UGAP measurements were positively correlated with CAP values (r=0.65, P<0.001). Conclusion Using MRI-PDFF as the reference standard, UGAP demonstrates good diagnostic performance in the detection and grading of hepatic steatosis in patients with MASLD.