Myocardial infarction （MI） and osteoporosis （OP）， as two prevalent metabolic diseases with high morbidity and mortality rates， are respectively characterized by cardiovascular system dysfunction and bone homeostasis imbalance， collectively posing significant global public health challenges. While clinically often considered as independent diseases， recent studies have revealed shared pathological mechanisms between the two. This study initiated its exploration from the traditional Chinese medicine concept of the "heart-bone" axis， systematically analyzing the correlation between MI and OP from perspectives including hemodynamics， neuroendocrinology， calcium homeostasis， inflammation and vascular injury， as well as hormone levels. By discussing the pathological mechanisms of "heart disease affecting the bones and bone disease affecting the heart"， the study also elucidated advancements in both Western and traditional Chinese medicine treatments. The goal is to provide novel insights and methodologies for the prevention and treatment of "heart-bone comorbidities"， thereby facilitating comprehensive management of cardiovascular and skeletal diseases.

Myocardial infarction （MI） and osteoporosis （OP）， as two prevalent metabolic diseases with high morbidity and mortality rates， are respectively characterized by cardiovascular system dysfunction and bone homeostasis imbalance， collectively posing significant global public health challenges. While clinically often considered as independent diseases， recent studies have revealed shared pathological mechanisms between the two. This study initiated its exploration from the traditional Chinese medicine concept of the "heart-bone" axis， systematically analyzing the correlation between MI and OP from perspectives including hemodynamics， neuroendocrinology， calcium homeostasis， inflammation and vascular injury， as well as hormone levels. By discussing the pathological mechanisms of "heart disease affecting the bones and bone disease affecting the heart"， the study also elucidated advancements in both Western and traditional Chinese medicine treatments. The goal is to provide novel insights and methodologies for the prevention and treatment of "heart-bone comorbidities"， thereby facilitating comprehensive management of cardiovascular and skeletal diseases.

Cemental tear is a rare and indetectable condition unless obvious clinical signs present with the involvement of surrounding periodontal and periapical tissues. Due to its clinical manifestations similar to common dental issues, such as vertical root fracture, primary endodontic diseases, and periodontal diseases, as well as the low awareness of cemental tear for clinicians, misdiagnosis often occurs. The critical principle for cemental tear treatment is to remove torn fragments, and overlooking fragments leads to futile therapy, which could deteriorate the conditions of the affected teeth. Therefore, accurate diagnosis and subsequent appropriate interventions are vital for managing cemental tear. Novel diagnostic tools, including cone-beam computed tomography (CBCT), microscopes, and enamel matrix derivatives, have improved early detection and management, enhancing tooth retention. The implementation of standardized diagnostic criteria and treatment protocols, combined with improved clinical awareness among dental professionals, serves to mitigate risks of diagnostic errors and suboptimal therapeutic interventions. This expert consensus reviewed the epidemiology, pathogenesis, potential predisposing factors, clinical manifestations, diagnosis, differential diagnosis, treatment, and prognosis of cemental tear, aiming to provide a clinical guideline and facilitate clinicians to have a better understanding of cemental tear.
Humans ; Dental Cementum/injuries* ; Consensus ; Diagnosis, Differential ; Cone-Beam Computed Tomography ; Tooth Fractures/therapy*

Pyroptosis is an identified programmed cell death that has been highly linked to endoplasmic reticulum (ER) dynamics. However, the crucial proteins for modulating dynamic ER membrane curvature change that trigger pyroptosis are currently not well understood. In this study, a biotin-labeled chemical probe of potent pyroptosis inducer α-mangostin (α-MG) was synthesized. Through protein microarray analysis, reticulon-4 (RTN4/Nogo), a crucial regulator of ER membrane curvature, was identified as a target of α-MG. We observed that chemically induced proteasome degradation of RTN4 by α-MG through recruiting E3 ligase UBR5 significantly enhances the pyroptosis phenotype in cancer cells. Interestingly, the downregulation of RTN4 expression significantly facilitated a dynamic remodeling of ER membrane curvature through a transition from tubules to sheets, consequently leading to rapid fusion of the ER with the cell plasma membrane. In particular, the ER-to-plasma membrane fusion process is supported by the observed translocation of several crucial ER markers to the "bubble" structures of pyroptotic cells. Furthermore, α-MG-induced RTN4 knockdown leads to pyruvate kinase M2 (PKM2)-dependent conventional caspase-3/gasdermin E (GSDME) cleavages for pyroptosis progression. In vivo, we observed that chemical or genetic RTN4 knockdown significantly inhibited cancer cells growth, which further exhibited an antitumor immune response with anti-programmed death-1 (anti-PD-1). In translational research, RTN4 high expression was closely correlated with the tumor metastasis and death of patients. Taken together, RTN4 plays a fundamental role in inducing pyroptosis through the modulation of ER membrane curvature remodeling, thus representing a prospective druggable target for anticancer immunotherapy.
Pyroptosis/immunology* ; Humans ; Endoplasmic Reticulum/immunology* ; Animals ; Nogo Proteins/antagonists & inhibitors* ; Mice ; Cell Line, Tumor ; Xanthones/pharmacology* ; Neoplasms/pathology* ; Mice, Nude

Lung cancer is the most common malignant tumor worldwide, ranking first in both incidence and mortality rates. According to the latest statistics from the International Agency for Research on Cancer (IARC), approximately 2.5 million new cases and around 1.8 million deaths from lung cancer occurred in 2022, placing a tremendous burden on global healthcare systems. The high mortality rate of lung cancer is closely linked to its subtle early symptoms, which often lead to diagnosis at advanced stages. This not only complicates treatment but also results in substantial economic losses. Current treatment options for lung cancer include surgery, radiotherapy, chemotherapy, targeted drug therapy, and immunotherapy. Among these, immunotherapy has emerged as the most groundbreaking advancement in recent years, owing to its unique antitumor mechanisms and impressive clinical benefits. Unlike traditional therapies such as radiotherapy and chemotherapy, immunotherapy activates or enhances the patient’s immune system to recognize and eliminate tumor cells. It offers advantages such as more durable therapeutic effects and relatively fewer toxic side effects. The main approaches to lung cancer immunotherapy include immune checkpoint inhibitors, tumor-specific antigen-targeted therapies, adoptive cell therapies, cancer vaccines, and oncolytic virus therapies. Among these, immune checkpoint inhibitors and tumor-specific antigen-targeted therapies have received approval from the U.S. Food and Drug Administration (FDA) for clinical use in lung cancer, significantly improving outcomes for patients with advanced non-small cell lung cancer. Although other immunotherapy strategies are still in clinical trials, they show great potential in improving treatment precision and efficacy. This article systematically reviews the latest research progress in lung cancer immunotherapy, including the development of novel immune checkpoint molecules, optimization of treatment strategies, identification of predictive biomarkers, and findings from recent clinical trials. It also discusses the current challenges in the field and outlines future directions, such as the development of next-generation immunotherapeutic agents, exploration of more effective combination regimens, and the establishment of precise efficacy prediction systems. The aim is to provide a valuable reference for the continued advancement of lung cancer immunotherapy.

Purpose To measure the spatial resolution in MRI quality control testing automatically based on the American College of Radiology(ACR)phantom using the support vector machine(SVM)method,and the feasibility,accuracy and measurement speed of this method are explored.Materials and Methods Quality control tests were performed using eight MRI devices at Beijing Friendship Hospital of Capital Medical University.A retrospective study was conducted on 71 MRI quality control test images collected based on ACR phantoms between 2017 and 2019.The images were preprocessed by binarization,extraction region of interest and so on.An SVM-based classification model was constructed for analyzing the spatial resolution of dot arrays in row and column directions.The dataset was randomly split into a training set and a test set.The generalization performance of the classification model in this study was evaluated through accuracy,precision,recall and F1 score on the test set.Comparing the results of spatial resolution measurements obtained by both manual and automatic method,we demonstrated the feasibility and accuracy of the method.Additionally,the time taken for the automatic spatial resolution measurement was recorded.Results In this study,the proposed method of automatically measuring the spatial resolution of ACR phantom test images using SVM was feasible,high accuracy and short time.In classification performance test,the accuracy of the spatial resolution of the row directional latices was 95%,the precision was 100%.The accuracy of the spatial resolution of the column directional latices was 97%,the precision was 100%.Among the test cases,the results of automatic measurements matched those of manual measurements in 13 out of 14 cases.On average,automatic spatial resolution measurement took 0.158 seconds per case.Conclusion This study achieves automatic measurement of spatial resolution in MRI quality control based on the ACR phantom using SVM method.The method demonstrates high accuracy and fast measurement speeds,holding significant implications for future rapid MRI quality control stability testing.

Purpose To explore an automatic detection method for quality control performance indicators of radio frequency coils based on American College of Radiology(ACR)phantom,and verify its accuracy stability and computational efficiency.Materials and Methods A retrospective study was conducted on 50 quality control images collected based on ACR phantom in Beijing Friendship Hospital,Capital Medical University from May 2017 to July 2019.The measurement and calculation methods of signal noise ratio(SNR),percent image uniformity(PIU)and percent signal ghosting(PSG)were used to automatically calculate the above indicators using a self-designed program in Python.A simple linear regression analysis on the automatically calculated SNR,PSG and PIU values compared to the manually measured results was performed,and Bland-Altman analysis was used to calculate the percentage difference to evaluate the consistency and bias between the performance indicators calculated by the two methods.The time consumption of two detection methods was compared to verify their computational complexity and efficiency.Results There was a strong correlation between the performance indicators SNR,PSG and PIU of radio frequency coils measured and calculated automatically and manually(r=0.991 4,0.992 8 and 0.909 8,all P<0.0001).The Bland-Altman results showed that most of the data fall within the 95%confidence interval and were evenly distributed.In terms of computational complexity and efficiency,compared to the complex manual delineation and calculation of 2-3 minutes per case,automatic detection could simultaneously obtain SNR,PSG and PIU values in less than 1 second.Conclusion The automatic and manual measurement methods have good consistency,and the automatic detection method is easy to operate,which is helpful for the daily quality control work and performance monitoring of radio frequency coils.

Vascular cognitive impairment (VCI), caused by cerebrovascular dysfunction, severely impacts the quality of life in the elderly population, yet effective therapeutic approaches remain limited. Mitophagy, a selective mitochondrial quality-control mechanism, has emerged as a critical focus in neurological disease research. Accumulating evidence indicates that mitophagy modulates oxidative stress, neuroinflammation, and neuronal apoptosis. Key signaling pathways associated with mitophagy—including PINK1/Parkin, BNIP3/Nix, FUNDC1, PI3K/Akt/mTOR, and AMPK—have been identified as potential therapeutic targets for VCI. This review summarizes the mechanistic roles of mitophagy in VCI pathogenesis and explores emerging therapeutic strategies targeting these pathways, aiming to provide novel insights for clinical intervention and advance the development of effective treatments for VCI.

In recent years,significant breakthroughs have been achieved in the immunotherapy for Alzheimer's disease.In line with global advancements,two anti-amyloid-β monoclonal antibodies have been approved and successfully launched in China for clinical use.Lecanemab and Donanemab were officially used in June 2024 and April 2025 in China,respectively.In order to standardize the rational and safe application of anti-amyloid-β monoclonal antibodies for Alzheimer's disease in China,this article integrates recom-mendations from the clinical trials and real-world experience from the author's team and domestic peers to further update the recom-mendations for the clinical use of anti-amyloid-β monoclonal antibody based on the 2024 version.It includes indications for therapy,pre-treatment evaluation and preparation,administration protocols and safety measures during treatment,and post-treatment monitor-ing strategies.