Objective:To construct a thyroid nodule segmentation model using ultrasound dynamic images and explore its potential for assisting in the screening of thyroid nodules.Methods:A total of 126 patients with thyroid nodules（comprising 150 nodules）who were diagnosed and treated at Xuzhou Cancer Hospital from April 2024 to December 2024 were prospectively enrolled. Two-dimensional ultrasound was performed to capture short-axis and long-axis video images of thyroid nodules，forming a dynamic ultrasound image dataset. The dataset was divided into training，validation，and test sets in a ratio of 6∶1∶3. After the training loss curve converged，the model that performed well on the validation set was selected for testing. Three-fold cross-validation was employed for training and testing. All 300 ultrasound videos were divided into three subsets. In each experiment，two subsets were used as the training set，and one subset was used as the test set to evaluate the model's generalization ability. A collaborative spatiotemporal diffusion model was established based on the dynamic trends and tissue texture details of thyroid nodules. Six widely used segmentation metrics were employed to evaluate the model's application capabilities.Results:The study included 126 patients with 150 thyroid nodules，300 dynamic ultrasound images，and video lengths of 3-4 seconds per nodule，resulting in 12 312 segmented images. The size of the thyroid nodules was（10.7 ± 10.6）mm（transverse diameter）×（8.4 ± 6.3）mm（anteroposterior diameter）. Among the nodules，62（41.3%）had clear boundaries，while 88（58.7%）had indistinct boundaries；61（40.7%）exhibited regular shapes，while 89（59.3%）were irregular；66（44.0%）had a taller-than-wide aspect ratio；and 70（46.7%）showed microcalcifications. The collaborative diffusion model based on dynamic ultrasound image segmentation achieved the following scores：a Jaccard score of（69.22 ± 0.03）%，a Dice score of（79.16 ± 0.18）%，a Precision score of（86.70 ± 0.17）%，a Recall score of（77.82 ± 0.04）%，an Sα score of（85.26 ± 0.01）%，and an Eθmn score of（90.58 ± 0.17）%. Compared to other models，this model demonstrated significant improvements across all evaluation metrics，achieving the highest values in each metric with increments of over 8% and 1%，respectively. Conclusions:The collaborative diffusion model with a dynamic controller，constructed based on dynamic ultrasound images of thyroid nodules，demonstrates excellent performance in ultrasound image segmentation. It improves the accuracy of thyroid nodule screening，thereby providing a valuable auxiliary diagnostic tool for clinical practice.

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.

Objective : To identify autophagy-related genes involved in pulmonary infection caused by the highly drug-resistant and virulent methicillin-resistant Staphylococcus aureus strain USA300 ( USA300) ，and to explore the underlying molecular mechanisms ， thereby providing potential targets for immunotherapy． Methods: The GSE220943 dataset of a USA300-induced pulmonary infection mouse model was obtained from the GEO database． Differentially expressed genes ( DEGs ) were identified using the DESeq2 package． Autophagy-related genes ( ARGs) were retrieved from the MSigDB and Autophagy databases．Weighted gene co-expression network analysis ( WGCNA) was performed to construct gene co-expression modules．Genes overlapping among DEGs，ARGs，and WGCNA modules were identified as autophagy-related DEGs．Gene Ontology ( GO) enrichment analysis was con- ducted using the clusterProfiler R package，while Kyoto Encyclopedia of Genes and Genomes ( KEGG) pathway en- richment analysis was performed via the Metascape platform．Immune cell infiltration was analyzed using the Immu- CellAI-mouse website．A protein - protein interaction ( PPI) network was constructed using the STRING database， and hub genes were identified through topological analysis in Cytoscape． Receiver operating characteristic curve ( ROC) curves were plotted via the website https: / /www．bioinformatics．com．cn． Finally，key gene expression was validated in mouse lung tissues by real-time quantitative reverse transcription PCR ( RT-qPCR) ． Results: A total of 6 135，4 075，3 680，and 2 342 differentially expressed genes ( DEGs) were identified at 12，24，48，and 96 hours post-infection，respectively．By integrating DEGs，autophagy-related genes ( ARGs) ，and WGCNA mod- ules，19 autophagy-related DEGs were identified． GO and KEGG enrichment analyses indicated that these genes were mainly involved in CD4 + T cell activation and regulation，innate immune responses，and autophagosome mem- brane formation．Immune infiltration analysis revealed that innate immune cells such as neutrophils and dendritic cells predominated during the early phase of infection，while γδ T cells and M2 macrophages became more promi- nent in the later stages．PPI network analysis identified 12 hub autophagy-related genes，among which three upreg- ulated key genes ( Eif2ak2，Ikbke，and Nfkbiz) were further confirmed．The area under the ROC curve for all three genes was 1. 000．RT-qPCR validation demonstrated significantly elevated expression of these three genes in lung tissues at 24 hours post-infection ( all P＜0. 05) ． Conclusion Eif2ak2，Ikbke，and Nfkbiz may be involved in the pulmonary infection caused by USA300 by promoting autophagy and hold promise as potential targets for immuno- therapy．

Originating in Huangdi Neijing,this theory was pioneered by ZHANG Zhongjing,who established the principles of concurrent heart-lung treatment and integrated therapeutic approaches.It further developed during the Ming-Qing period and has been widely applied in modern clinical practice.This article systematically traces the developmental trajectory of the heart-lung correlation theory in traditional Chinese medicine and analyzes its clinical application in elucidating the pathogenesis and therapeutic strategies for lung cancer complicated by cardiovascular comorbidities.According to this theoretical framework,lung cancer accompanied by cardiovascular comorbidities exhibits a pathomechanism characterized by fundamental deficiency with symptomatic excess.The deficiency manifests as qi-blood depletion or impaired descent of gathering qi,while the excess is reflected in phlegm-stasis coagulation or heat-toxin accumulation.Key pathological features include progressive transformation,meridian disharmony,deteriorating vital substances,and disruption of inter-organ relationships.Treatment adheres to the principles of concurrent heart-lung intervention,integrated cardiopulmonary modulation,and reciprocal organ regulation.Core therapeutic strategies involve eliminating pathogenic factors,promoting circulation,tonifying deficiencies,and harmonizing functions with specific interventions determined through pattern differentiation.For the pattern of phlegm and blood stasis coagulation affecting both the heart and lung,treatment is guided by the principle of simultaneous treatment of phlegm and stasis,coordinated regulation of heart-lung function,and prioritization of qi circulation.Commonly used formulas include Gualou Xiebai Banxia Decoction and Xuefu Zhuyu Decoction.In cases of heat toxin accumulation in the heart and lungs,therapy follows the principle of clearing heart-lung fire and dredging collaterals,often using combinations of insect-derived medicines and vine-derived herbs,such as earthworm and Chinese star jasmine stem.In instances of heart-lung qi-blood deficiency,the therapeutic approach emphasizes simultaneous fortification and qi and blood circulation.Formulas such as modified Renshen Yangrong Decoction or Shengxian Decoction,combined with Taohong Siwu Decoction,are commonly used.These formulas strengthen qi without stagnating blood,promote blood circulation without harming healthy qi,and gradually eliminate pathogens.These three treatment approaches embody the characteristics of integrated heart-lung therapy,emphasizing dynamic regulation and holistic concepts.The focus remains on addressing both manifestation and root causes through flexible herb selection to achieve optimal therapeutic outcomes.

Originating in Huangdi Neijing,this theory was pioneered by ZHANG Zhongjing,who established the principles of concurrent heart-lung treatment and integrated therapeutic approaches.It further developed during the Ming-Qing period and has been widely applied in modern clinical practice.This article systematically traces the developmental trajectory of the heart-lung correlation theory in traditional Chinese medicine and analyzes its clinical application in elucidating the pathogenesis and therapeutic strategies for lung cancer complicated by cardiovascular comorbidities.According to this theoretical framework,lung cancer accompanied by cardiovascular comorbidities exhibits a pathomechanism characterized by fundamental deficiency with symptomatic excess.The deficiency manifests as qi-blood depletion or impaired descent of gathering qi,while the excess is reflected in phlegm-stasis coagulation or heat-toxin accumulation.Key pathological features include progressive transformation,meridian disharmony,deteriorating vital substances,and disruption of inter-organ relationships.Treatment adheres to the principles of concurrent heart-lung intervention,integrated cardiopulmonary modulation,and reciprocal organ regulation.Core therapeutic strategies involve eliminating pathogenic factors,promoting circulation,tonifying deficiencies,and harmonizing functions with specific interventions determined through pattern differentiation.For the pattern of phlegm and blood stasis coagulation affecting both the heart and lung,treatment is guided by the principle of simultaneous treatment of phlegm and stasis,coordinated regulation of heart-lung function,and prioritization of qi circulation.Commonly used formulas include Gualou Xiebai Banxia Decoction and Xuefu Zhuyu Decoction.In cases of heat toxin accumulation in the heart and lungs,therapy follows the principle of clearing heart-lung fire and dredging collaterals,often using combinations of insect-derived medicines and vine-derived herbs,such as earthworm and Chinese star jasmine stem.In instances of heart-lung qi-blood deficiency,the therapeutic approach emphasizes simultaneous fortification and qi and blood circulation.Formulas such as modified Renshen Yangrong Decoction or Shengxian Decoction,combined with Taohong Siwu Decoction,are commonly used.These formulas strengthen qi without stagnating blood,promote blood circulation without harming healthy qi,and gradually eliminate pathogens.These three treatment approaches embody the characteristics of integrated heart-lung therapy,emphasizing dynamic regulation and holistic concepts.The focus remains on addressing both manifestation and root causes through flexible herb selection to achieve optimal therapeutic outcomes.

Objective:To construct a thyroid nodule segmentation model using ultrasound dynamic images and explore its potential for assisting in the screening of thyroid nodules.Methods:A total of 126 patients with thyroid nodules（comprising 150 nodules）who were diagnosed and treated at Xuzhou Cancer Hospital from April 2024 to December 2024 were prospectively enrolled. Two-dimensional ultrasound was performed to capture short-axis and long-axis video images of thyroid nodules，forming a dynamic ultrasound image dataset. The dataset was divided into training，validation，and test sets in a ratio of 6∶1∶3. After the training loss curve converged，the model that performed well on the validation set was selected for testing. Three-fold cross-validation was employed for training and testing. All 300 ultrasound videos were divided into three subsets. In each experiment，two subsets were used as the training set，and one subset was used as the test set to evaluate the model's generalization ability. A collaborative spatiotemporal diffusion model was established based on the dynamic trends and tissue texture details of thyroid nodules. Six widely used segmentation metrics were employed to evaluate the model's application capabilities.Results:The study included 126 patients with 150 thyroid nodules，300 dynamic ultrasound images，and video lengths of 3-4 seconds per nodule，resulting in 12 312 segmented images. The size of the thyroid nodules was（10.7 ± 10.6）mm（transverse diameter）×（8.4 ± 6.3）mm（anteroposterior diameter）. Among the nodules，62（41.3%）had clear boundaries，while 88（58.7%）had indistinct boundaries；61（40.7%）exhibited regular shapes，while 89（59.3%）were irregular；66（44.0%）had a taller-than-wide aspect ratio；and 70（46.7%）showed microcalcifications. The collaborative diffusion model based on dynamic ultrasound image segmentation achieved the following scores：a Jaccard score of（69.22 ± 0.03）%，a Dice score of（79.16 ± 0.18）%，a Precision score of（86.70 ± 0.17）%，a Recall score of（77.82 ± 0.04）%，an Sα score of（85.26 ± 0.01）%，and an Eθmn score of（90.58 ± 0.17）%. Compared to other models，this model demonstrated significant improvements across all evaluation metrics，achieving the highest values in each metric with increments of over 8% and 1%，respectively. Conclusions:The collaborative diffusion model with a dynamic controller，constructed based on dynamic ultrasound images of thyroid nodules，demonstrates excellent performance in ultrasound image segmentation. It improves the accuracy of thyroid nodule screening，thereby providing a valuable auxiliary diagnostic tool for clinical practice.

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.

Objective:To explore the efficacy and safety of tetrandrine in the treatment of rheumatoid arthritis.Methods:Randomized controlled studies of tetrandrine in the treatment of rheumatoid arthritis were searched in CNKI,VIP,Wanfang database,SinoMed,PubMed,Springer,Web of Science and Cochrane Central Register of Controlled Trails databases.A meta-analysis was conducted using R 3.5.3 software to evaluate the clinical outcomes,including the total effective rate,erythrocyte sedimentation rate(ESR),C-reactive protein(CRP),rheumatoid factor(RF),visual analogue scale(VAS),disease activity score(DAS),tender joint count(TJC),swollen joint count(SJC),and morning stiffness duration,as well as adverse events of rheumatoid arthritis patients.Results:A total of 10 articles were included in the study.The meta-analysis indicated that tetrandrine significantly improved the total effective rate(OR=3.27,95%CI:2.01-5.37,P<0.01),ESR(SMD=1.12,95%CI:0.06-2.19,P<0.05),CRP(SMD=0.75,95%CI:0.28-1.22,P<0.01),VAS(SMD=0.64,95%CI:0.29-1.00,P<0.01),TJC(SMD=1.16,95%CI:0.58-1.74,P<0.01),SJC(SMD=0.85,95%CI:0.40-1.31,P<0.01),and morning stiffness(SMD=1.09,95%CI:0.68-1.50,P<0.01).However,no statistical significance was found in RF(SMD=1.70,95%CI:-1.10-4.51,P>0.05)and DAS(SMD=0.26,95%CI:-0.59-1.11,P>0.05).The overall incidence of adverse events associated with tetrandrine treatment for rheumatoid arthritis was 20%(95%CI:12%-27%,I2=60%,P<0.05),with mild severity and favorable outcomes.Conclusion:Tetrandrine is effective in the treatment of RA patients with a mild degree of adverse events.

OBJECTIVE To evaluate the consistency between the quetiapine LC-MS/MS kit and the laboratory-built method(reference method) in the detection results of quetiapine therapeutic drug monitoring. METHODS A total of 120 remaining plasma samples were collected from patients receiving quetiapine therapeutic drug monitoring from March to October in 2021. The plasma concentration of quetiapine was detected by kit and reference method respectively. The analysis of correlations and consistency was performed by outlier analysis, linear regression and Bland-Altman method. RESULTS No outliers were detected. The linear regression equation was Y=1.018X+4.400(r=0.998), indicating a good correlation. The Bland-Altman plot analysis showed good agreement between the two measurements. CONCLUSION The detection results of quetiapine LC-MS/MS kit and reference method are in good agreement. The kit can be used for clinical quetiapine treatment drug monitoring.

Objective:To utilize routinely available clinical parameters to uncover the clinical features of different clusters in patients with chronic rhinosinusitis with nasal polyp (CRSwNP) through unsupervised clustering analysis.Methods:The clinical data from 155 CRSwNP patients undergoing nasal endoscopic surgery at Renmin Hospital of Wuhan University from 2021 to 2023 were prospectively collected, including 112 males and 43 females, aged from 7 to 87 years. Unsupervised clustering analysis was conducted using various clinical parameters, including age, gender, smoking and drinking history, local eosinophil (EOS) and neutrophil (NEU) counts, comorbid allergic rhinitis (AR), comorbid asthma, recurrence status, serum-specific IgE, total IgE, cytokine levels, peripheral blood EOS count and percentage, Lund-Mackay CT score, the ratio of CT scores for the maxillary sinus and ethmoid sinus (E/M ratio), visual analogue scale (VAS) score, Lund-Kennedy endoscopic score, and other common clinical indicators to elucidate the clinical characteristics of each cluster. Statistical analysis was conducted using GraphPad Prism 9.5 software.Results:Hierarchical clustering analysis identified four main clusters (Cluster A1-A4), showcasing distinct characteristics such as mild nasal polyps with higher peripheral blood cytokines levels, nasal polyps accompanied by allergies and asthma, a subtype of nasal polyps with high recurrence rates dominated by neutrophils, and nasal polyps with high eosinophil levels. Further subset clustering revealed two clusters of mild polyps (Cluster B1-B2) featuring high cytokine expression and comorbid AR; and two clusters of severe polyps (Cluster B3-B4) presented with severe symptoms, high Lund-Mackay CT score, and high Lund-Kennedy endoscopic score. Variations between Cluster B3 and B4 included symptom complexity, the degree of eosinophil infiltration, and the probability of comorbid asthma. Further clustering analysis for eosinophilic nasal polyps revealed a cluster characterized by highly neutrophilic infiltration and recurrent nasal polyps. The comprehensive analysis of multi-index correlations demonstrated valuable insights into the relationships between common clinical parameters of nasal polyps, providing valuable information for a deeper understanding of the pathogenesis of CRSwNP.Conclusion:The clustering analysis in this study categorizes CRSwNP patients into different clusters based on clinical features and disease outcomes, providing a new perspective for more precise clinical treatment strategies.