BACKGROUND:Studies have shown that lipid metabolism and related diseases can affect the development of osteoporosis.OBJECTIVE:Using bibliometric visualization analysis software to analyze and summarize the frontier content and research hotspots in the field of lipid metabolism affecting osteoporosis.METHODS:Using the Web of Science core collection database as the retrieval platform,relevant literature regarding the effect of lipid metabolism on osteoporosis from 2004 to 2024 was retrieved.VOSviewer and CiteSpace were used for bibliometric and visual analyses.RESULTS AND CONCLUSION:A total of 1 277 articles were included,and the number of articles on the effect of lipid metabolism on osteoporosis at home and abroad was increasing year by year.The number of articles published in China was 417,ranking first,and the United States was 243,ranking second.Shanghai Jiao Tong University ranked first with 30 articles.Professor Rosen Clifford J from Tufts University School of Medicine and Professor Recker Robert R from Clayton University were the most cited authors.The number of documents published in BONE in the Netherlands ranked first,and the JOURNAL OF CLINICAL ENDOCRINOLOGY & METABOLISM in England was the most cited journal.Bone mineral density,bone metabolism,menopause,and obesity were the core keywords,and they were also research hotspots in this field.The above results show that in the past 20 years,research in the field of lipid metabolism affecting osteoporosis has focused on the role of abnormal lipid metabolism in bone mineral density and bone metabolism,thereby regulating osteoporosis and post-menopause osteoporosis.Clarifying the pathway of this mechanism and"bone-lipid balance"is the future research idea and direction.

BACKGROUND:Studies have shown that lipid metabolism and related diseases can affect the development of osteoporosis.OBJECTIVE:Using bibliometric visualization analysis software to analyze and summarize the frontier content and research hotspots in the field of lipid metabolism affecting osteoporosis.METHODS:Using the Web of Science core collection database as the retrieval platform,relevant literature regarding the effect of lipid metabolism on osteoporosis from 2004 to 2024 was retrieved.VOSviewer and CiteSpace were used for bibliometric and visual analyses.RESULTS AND CONCLUSION:A total of 1 277 articles were included,and the number of articles on the effect of lipid metabolism on osteoporosis at home and abroad was increasing year by year.The number of articles published in China was 417,ranking first,and the United States was 243,ranking second.Shanghai Jiao Tong University ranked first with 30 articles.Professor Rosen Clifford J from Tufts University School of Medicine and Professor Recker Robert R from Clayton University were the most cited authors.The number of documents published in BONE in the Netherlands ranked first,and the JOURNAL OF CLINICAL ENDOCRINOLOGY & METABOLISM in England was the most cited journal.Bone mineral density,bone metabolism,menopause,and obesity were the core keywords,and they were also research hotspots in this field.The above results show that in the past 20 years,research in the field of lipid metabolism affecting osteoporosis has focused on the role of abnormal lipid metabolism in bone mineral density and bone metabolism,thereby regulating osteoporosis and post-menopause osteoporosis.Clarifying the pathway of this mechanism and"bone-lipid balance"is the future research idea and direction.

Radiotherapy is a crucial treatment modality for head and neck tumors. However, while effectively killing tumor cells, it significantly disrupts the homeostasis of the oral microecology, which is closely associated with various complications such as radiation-induced oral mucositis. Literature review indicates that as radiotherapy doses accumulate and treatment durations extend, the richness and diversity of the oral microbiota show a declining trend, with the genus Streptococcus decreasing most markedly. In contrast, radiotherapy selectively promotes the proliferation of bacterial phyla such as Proteobacteria and Bacteroidetes, which are rich in opportunistic pathogens. Mechanistically, radiotherapy activates the nuclear factor-kappa B pathway, triggering chronic inflammation and oxidative stress, damaging the epithelial barrier, suppressing local immunity, and causing damage to organs such as the salivary glands. It can also induce systemic diseases via the oral-gut axis, forming a multi-level, interconnected pathogenic network. In terms of interventions, treatment strategies including probiotics and prebiotics have shown promising efficacy against side effects such as radiation-induced oral mucositis. Saliva-based oral microbiota transplantation is an emerging strategy that is expected to become widely utilized for restoring oral microecological balance. Existing interventions provide preliminary pathways for clinical practice, but this field still faces several key scientific questions. The association between oral microecology and systemic diseases remains largely correlative, lacking causal evidence. Furthermore, critical parameters for oral microbiota transplantation, such as donor screening criteria, transplantation protocols, and long-term safety, are not yet well-defined. Therefore, future research should focus on conducting large-scale clinical trials to establish standardized protocols and safety evaluation systems for oral microecological interventions, and explore combined treatment therapies such as probiotics, prebiotics, and microbiota transplantation to advance the development of personalized precision modulation. These will enable more effective management of radiotherapy-induced oral microecological dysbiosis and improve treatment outcomes and quality of life for patients with head and neck tumors.

ObjectiveTo explore the possible mechanism of Yigan Fupi Prescription （抑肝扶脾方， YFP） in treating diarrhea-type irritable bowel syndrome （IBS-D） by investigating the AKT/mTOR signaling pathway. MethodsSixty SD rats were randomly divided into control group， model group， YFP low-， medium-， and high-dose group， and pinaverium bromide group， with 10 rats in each group. All groups but the control group， were subjected to 21 days of tail-clamping stimulation and 14 days of senna leaf gavage to establish a liver stagnation and spleen deficiency-type IBS-D rat model. After successful modeling， the YFP low-， medium-， and high-dose group were administered 0.96， 1.93， and 3.87 g/（kg·d） of the prescription， respectively. The pinaverium bromide group was given 13.5 mg/（kg·d）， while the control and model groups were given 10 ml/（kg·d） distilled water. All groups were administered once daily for 14 consecutive days. General conditions of the rats were recorded during the experiment， and after modeling and drug administration， body weight， Bristol stool score， abdominal withdrawal reflex （AWR） score， and histo pathology of colon tissue were observed under HE staining. ELISA was used to detect serum levels of tumor necrosis factor α （TNF-α）， interleukin-1β （IL-1β）， and interleukin-6 （IL-6）. Immunofluorescence was employed to detect the levels of AKT/mTOR pathway-related proteins including phosphorylated AKT （p-AKT）/AKT and phosphorylated mTOR （p-mTOR）/mTOR in the colon tissue. Western Blotting was used to detect the levels of autophagy-related proteins， including UNC-51-like kinase 1 （ULK1）， Beclin1 and LC3， and tight junction proteins including Occludin and ZO-1 in the colon tissue. ResultsAfter modeling， compared to the control group， the body weight of rats in the other groups decreased， and Bristol stool scores， as well as AWR scores under 20， 40， 60， and 80 mmHg increased （P＜0.05 or P＜0.01）. After drug administration， compared to the control group， the model group showed reduced body weight， decreased ULK1， Beclin1， LC3Ⅱ/LC3Ⅰ， Occludin， and ZO-1 protein levels in the colon tissue （P＜0.05 or P＜0.01）， and increased Bristol stool scores， AWR scores， serum TNF-α， IL-1β， and IL-6 levels， as well as p-AKT/AKT and p-mTOR/mTOR protein relative expression levels （P＜0.05 or P＜0.01）. Pathological results showed a significant reduction in goblet cells in the upper part of the glandular layer of the colon， with mild inflammatory cell infiltration. The submucosal collagen fibers were dissolved， with unclear boundaries， pale staining， and microvascular congestion and dilation. Compared with the model group， the YFP low-， medium-， and high-dose group and the pinaverium bromide group showed increased body weight， Beclin1， Occludin， and LC3Ⅱ/LC3Ⅰ protein levels （P＜0.05 or P＜0.01）， and decreased Bristol stool scores， AWR scores under 40， 60， and 80 mmHg， serum IL-1β， IL-6， TNF-α levels， and p-AKT/AKT， p-mTOR/mTOR protein relative expression levels （P＜0.05 or P＜0.01）. The pathological morphology of the rats in the YFP groups and pinaverium bromide group showed varying degrees of improvement. Compared with the pinaverium bromide group， the YFP low- and medium-dose group showed increased AWR scores under 20， 40， and 60 mmHg （P＜0.05）. The YFP low-dose group had reduced TNF-α， IL-1β， and IL-6 levels， and increased p-mTOR/mTOR protein relative expression levels occured in all YFP groups （P＜0.05）. Compared with the YFP low-dose group， the YFP high-dose group and pinaverium bromide group showed decreased AWR scores under different pressure levels and reduced p-AKT/AKT protein relative expression levels， while the YFP medium- and high-dose group had elevated serum TNF-α， IL-1β levels and reduced p-mTOR/mTOR protein relative expression levels （P＜0.05）. ConclusionYFP can effectively improve the pathological injury of colon tissue in IBS-D model rats with liver stagnation and spleen deficiency， reduce Bristol stool and AWR scores， and its mechanism may be related to reducing level of inflammatory factors and inhibiting AKT/mTOR pathway-related proteins in colon tissue， thereby enhancing the expression of autophagy-related proteins in the colon tissue.

ObjectiveTo investigate the whole genomic characteristics and phylogenetic relationships of clinical isolates of enteroaggregative Escherichia coli (EAEC) in diarrhea outpatients in Pudong New Area, Shanghai. MethodsBased on the diarrheal disease surveillance network in Pudong New Area, Shanghai, whole-genome sequencing was performed on a total of 55 EAEC strains isolated from fecal samples of the diarrhea outpatients from January 2015 to December 2019. The genome analyses based on raw sequencing data encompassed genome size, coding genes, dispersed repeat sequences, genomic islands, and protein coding regions, and pan-genome analyses were conducted simultaneously. Contigs sequences assays were performed to analyze molecular characteristics including serotypes, antibiotic resistance genes, and virulence factors. The phylogenetic clusters and multilocus sequence typing (MLST) were identified, and a phylogenetic tree was constructed. ResultsEAEC exhibited an open pan-genome. The predominant serotype of EAEC in diarrhea outpatients in Pudong New Area was O130:H27, and the carriage rate of β-lactam resistance genes was the highest (67.27%, 37/55). A total of 29 virulence factors and 106 virulence genes were identified, phylogenic group B1 was the predominant group, and clonal group CC31 was the dominant clonal group. The strain distribution was highly heterogeneous. ConclusionThe genomic characteristics of EAEC displayed significant strain polymorphism. It is necessary to develop effective strategies for differential diagnosis and improve detection capabilities for infection with EAEC of different serotypes and genotypes.

[Objective] To determine the blood group of a patient with ABO forward and reverse typing discrepancies using PacBio third-generation sequencing (TGS) technology, and to explore the application of serological methods and molecular biological methods in identifying chimeric blood groups. [Methods] The blood group serology testing was utilized. PCR amplification and Sanger sequencing of exons 1-7 of the ABO gene were conducted. The full-length sequencing of the ABO gene and haplotype analysis were carried out by PacBio third-generation sequencing technology. Short tandem repeat typing was also performed. [Results] Serological testing suggested a suspected B subtype, which appeared mixed field of vision with anti-B antibodies and showed 2+mf strength agglutination. Sanger sequencing revealed a homozygous ABO^* O. 01. 01 genotype with the c. 261delG mutation in exon 6. PacBio TGS identified a predominant ABO^* O. 01. 01/ABO^* O. 01. 01 genotype and a low proportion of ABO^* B. 01. Nine locis of twenty short tandem repeat (STR) locis showed three or four types of genotypes in STR analysis, confirming chimerism. [Conclusion] The sample was a B/O blood group chimerism. The low proportion of ABO^* B. 01 chimerism was the true cause for the serological mixed field of vision. The PacBio third-generation sequencing technology can not only determine the ABO gene haplotype but also detect a low proportion gene chimerism in ABO blood groups.

Objective:To investigate the value of coronary CTA (CCTA)-based traditional features and radiomics of plaque in the identification of culprit lesions that caused acute myocardial infarction (AMI).Methods:This was a retrospective multicenter study. From July 2016 to November 2023, a total of 344 patients from the Affiliated Hospital of Qingdao University (training cohort, n=184), Shandong Provincial Hospital Affiliated to Shandong First Medical University (validation cohort, n=88) and Qilu Hospital of Shandong University (test cohort, n=72) who received percutaneous coronary intervention (PCI) due to AMI and underwent CCTA within 48 hours of AMI were enrolled. The culprit plaques and non-culprit plaques were identified using a combination of electrocardiogram, CCTA, and angiographic findings. The vessel, plaque location, plaque type, Coronary Artery Disease-Reporting and Data System (CAD-RADS) score, high-risk plaque characteristics, plaque length, plaque volume, and burden were analyzed, and 1 904 radiomics features were extracted for each plaque. The traditional imaging model, the radiomics model, and the combined model were established by using multivariate Logistic regression analysis. The area under the receiver operating characteristic curve (AUC) was used to evaluate the performance of each model in identifying culprit lesions. The DeLong test was used for the comparison of AUC between every two models. The net reclassification index (NRI) was used to evaluate the incremental value of the combined model to the traditional imaging model and the radiomics model. The decision curve analysis (DCA) was used to assess the clinical net benefit of these models. A correlation heatmap was used to evaluate the correlation between the radiomics score and traditional CCTA factors. The interpretable analysis of the decision process of the combined model was performed by the Shapley Additive exPlanations (SHAP). Results:In the validation cohort and the test cohort, the AUC of the traditional imaging model developed by the vessel, plaque type, positive remodeling and CAD-RADS score was 0.898 (95% CI 0.869-0.922) and 0.881 (95% CI 0.848-0.910), respectively. The radiomics model developed by six radiomics features was 0.863 (95% CI 0.831-0.891) and 0.863 (95% CI 0.827-0.864), respectively. The AUC of the combined model was 0.930 (95% CI 0.905-0.950)and 0.919 (95% CI 0.889-0.942), respectively. In the validation cohort and the test cohort, the AUC of the combined model was higher than that of the traditional imaging model ( Z=4.013, 4.272, P<0.001) and that of the radiomics model ( Z=4.819, 3.784, P<0.001), respectively. In the validation cohort, the combined model yielded an NRI of 20.43% (95% CI 10.43%-30.44%, P<0.001) and 20.21% (95% CI 9.62%-30.80%, P<0.001) for identifying culprit lesions compared with the traditional imaging model and the radiomics model, respectively. In the test cohort, the combined model yielded an NRI of 28.05% (95% CI 16.72%-39.38%, P<0.001) and 23.57% (95% CI 13.58%-33.56%, P<0.001) for identifying culprit lesions compared with the traditional imaging model and the radiomics model, respectively. DCA showed the combined model had the highest clinical net benefit. The correlation heatmap showed the radiomics score was not correlated or only weakly correlated with traditional CCTA factors. SHAP indicated the radiomics and CAD-RADS score contributed significantly to the model. Conclusion:The CCTA-based traditional features and radiomics of plaque have favorable performance for the identification of culprit plaques in patients with AMI.

Objective To observe the efficacy of nomogram model based on enhanced MRI radiomics,deep learning(DL)and clinical features for differentiating spinal tuberculosis and pyogenic spondylitis.Methods Totally 59 cases of spinal tuberculosis and 66 of pyogenic spondylitis were retrospectively enrolled.Radiomics,DL and clinical features relevant to differentiating spinal tuberculosis and pyogenic spondylitis were selected.Then a predictive model was constructed using logistic regression based on the selected optimal features,and a comprehensive nomogram model was developed through combination of the above features.The effectiveness of these models for distinguishing spinal tuberculosis from pyogenic spondylitis were visualized based on receiver operating characteristic curves,calidration curves and decision curves.Results The nomogram model demonstrated the highest area under the curve(AUC)in both training set and test set,with AUC of 0.997 and 0.920,respectively.In test set,DeLong test indicated that the difference of AUC between the nomogram model and clinical model was significant(P=0.002),while no significant difference was observed between the nomogram model and the other models(all P＞0.05).The nomogram model provided the highest overall net benefit and exhibited good calibration for distinguishing spinal tuberculosis from pyogenic spondylitis.Conclusion Nomogram model based on enhanced MRI radiomics,DL and clinical features demonstrated high efficacy for differentiating spinal tuberculosis from pyogenic spondylitis.

The integration of TCM and Western medicine in imaging aims to enrich the sources of diagnostic information by utilizing medical imaging technologies,focusing on key elements such as TCM imaging,Western medical imaging,diseases and TCM syndrome types,thereby facilitating the complementary strengths of both systems.With the advancement of digital imaging and artificial intelligence technologies,various research models and methodologies have emerged.This article discussed the development and application of integrated imaging of traditional Chinese and Western medicine,and proposed three primary research paradigms in this field:Analyzing TCM images(e.g.,tongue and face)through manual or image processing techniques to assist in the diagnosis of Western medical diagnosis;Mapping Western medical imaging signs(e.g.,computed tomography,magnetic resonance imaging and ultrasound imaging)to TCM syndrome patterns for objective evidence in TCM diagnosis and treatment;Applying imaging omics to extract and integrate features from both TCM and Western medical images for comprehensive diagnosis.This study reviewed the three paradigms,explained relevant concepts and technologies,and proposed a specific research workflow of integrated imaging omics of traditional Chinese and Western medicine,aiming to provide a reference for innovative development in this field.

Objective:To propose a deep learning（DL）-based ultrasound imaging auxiliary tool for automatic segmentation and recognition of the brachial plexus（BP），and to enhance the accuracy and safety of clinical procedures.Methods:It was a multicenter study that collected 773 healthy subjects from Peking University Third Hospital and its branch campuses，the Third Medical Center of the Chinese PLA General Hospital，and Shanghai Eighth People's Hospital between August 2024 and February 2025. Brachial plexus（BP）images in the interscalene groove were captured used high-frequency ultrasound by senior sonographers，a dataset comprising 1 289 standardized images were constructed and the improved model（CHA-TransUNet）was trained. The test set was input into 6 different models（CHA-TransUNet，R50-Unet，TransUnet，SegFormer，SwinUnet，MISSFormer）for segmentation. Segmentation accuracy was evaluated using metrics including the Dice similarity coefficient（DSC），95% Hausdorff distance（HD95）and mean intersection over union（mIoU），and was compared with the segmentation results of 3 ultrasound physicians with varying experience levels（junior physicians and senior physicians）to validate the model's segmentation efficacy.Results:The CHA-TransUNet model established based on a dataset of 1 289 standardized images achieved segmentation results for the BP with a DSC of 90.15%，mIoU of 91.02%，and HD95 of 8.08. Its accuracy was higher than other mainstream models（DSC：90.15% vs. 87.60%，87.77%，81.35%，84.78%，84.55%），significantly better than junior physicians（DSC：90.15% vs. 68.73%， Z=-127.76， P<0.001），and approached the level of senior physician（DSC：90.15% vs. 86.15%， Z=-31.33， P=0.549）. The model demonstrated superior boundary recognition in complex anatomical structures（e.g.，C6/C7 nerve roots）compared to ultrasound physicians（junior and senior）（HD95：8.08 vs. 26.34，17.44，56.80）. Conclusions:This study proposes an analysis model for BP ultrasound images，CHA-TransUNet. This model achieves segmentation and recognition of the BP with relatively complex pathways and structures. The model exhibits high accuracy and stability，outperforming current mainstream network models and junior physicians while approaching the performance level of senior physicians. It assists junior physicians or trainees in more accurately identifying and localizing the BP.