Objective To analyze the effect of releasing the lower pulmonary ligament on right residual lung expansion after right upper lobe resection under different body mass index (BMI) levels. Methods The clinical data of patients who underwent thoracoscopic right upper lobe resection in the First Affiliated Hospital with Nanjing Medical University from 2021 to 2022 were retrospectively analyzed. Patients were divided into a group A (17 kg/m2＜BMI≤23 kg/m2), a group B (23 kg/m2＜BMI≤29 kg/m2) and a group C (BMI＞29 kg/m2) according to BMI. The presence of residual cavity was judged by chest X-ray at 7-10 days after operation, the degree of compensation change of the right main bronchus angle was measured, and the changes in lung volume were determined by CT three-dimensional reconstruction. Results A total of 157 patients who underwent thoracoscopic right upper lobe resection were included, including 71 males and 86 females, with an average age of (59.7±11.2) years. There were 50 patients in the group A, 75 patients in the group B, and 32 patients in the group C. In the group A, compared with those without releasing the lower pulmonary ligament, patients with releasing had a lower incidence of postoperative residual cavity (P=0.016), greater changes in bronchus angle (P<0.001), and smaller changes in lung volume (P<0.001). In the group B and C, there was no significant effect of releasing the lower pulmonary ligament on postoperative residual cavity, bronchus angle, and lung volume changes (P>0.05). Conclusion For patients with thin and long body shape and low BMI, releasing the lower pulmonary ligament is helpful to promote the expansion of the residual lung after right upper lobe resection and reduce the occurrence of postoperative residual cavity in patients.

ObjectiveTo clarify the expression of TRIM28 in non-M3 acute myeloid leukemia （AML） and its correlation with clinical indicators and prognosis， and to further explore the effect of TRIM28 expression levels on the proliferation and apoptosis of AML cells using small interfering RNA. MethodsThe GSE34577 dataset was analyzed using R software to compare TRIM28 expression between healthy controls and non-M3 acute myeloid leukemia （AML） patients. Clinical samples from non-M3 AML patients were collected， with TRIM28 expression levels measured using real-time quantitative PCR （qPCR）. The analysis focused on correlations between TRIM28 expression and various clinical indicators， treatment efficacy， and patient prognosis. Furthermore， small interfering RNA （siRNA） technology was employed to downregulate TRIM28 expression in human primary AML cells （HL60 cell line）. The effects on cell proliferation and apoptosis were then assessed through CCK-8 assays and flow cytometry， respectively. ResultsThe results showed that TRIM28 was up-regulated in non-M3 AML of both online database GSE34577 and clinical samples （P<0.000 1）， TRIM28 expression of new diagnosis group and relapsed refractory group was higher than iron deficiency anemia group （P<0.01）， and there was no significance between different French-American-British classification systems subtype. TRIM28 expression was higher in non-M3 AML patients with a poor genetic prognosis stratified as moderate than in the good prognosis group， and TRIM28 expression was associated with NPM1 combined with the FLT3-ITD mutation， positively correlated with age， bone marrow blast， peripheral blood blast and white blood cell， negatively correlated with hemoglobin. In addition， interference TRIM28 greatly inhibited cell proliferation and promoted cell apoptosis. ConclusionThis study reveals that TRIM28 is highly expressed in non-M3 AML and associated with prognosis， and plays a key role in the proliferation and apoptosis of AML cells， suggesting that TRIM28 may serve as a novel therapeutic target for non-M3 AML.

ObjectiveDiscriminating atypical hepatocellular carcinoma (HCC) from other malignancies in liver nodules classified as Liver Imaging Reporting and Data System category M (LR-M) remains a significant diagnostic challenge on conventional ultrasound examination. The LR-M category, originally intended to capture non-HCC malignancies, paradoxically contains up to 63% of atypical HCCs that deviate from classic enhancement patterns, leading to potential misdiagnosis and suboptimal treatment planning. While deep learning has shown promise in HCC diagnosis, most existing models rely exclusively on single-modality ultrasound, overlooking the diagnostic benefits of integrating complementary information from multiple imaging sources. To address this gap, we propose a novel attention-weighted tri-modal ultrasound network (TUS-Net) that integrates contrast-enhanced ultrasound (CEUS), B-mode ultrasound (BUS), and time-intensity curves (TICs) to improve diagnostic accuracy for these clinically challenging lesions. MethodsOur framework incorporates a three-dimensional convolutional neural network (C3D) backbone to extract spatiotemporal features from CEUS videos, capturing dynamic vascular patterns critical for lesion characterization. To effectively fuse complementary modalities, we introduce a dual-channel feature fusion module (DCFFM) that adaptively combines features from CEUS and BUS through channel-wise attention mechanisms, allowing the model to dynamically weigh the contribution of each modality based on diagnostic relevance. Additionally, we propose a temporal intensity feature fusion module (TIFFM) that leverages quantitative hemodynamic information from TICs to guide the model’s attention toward diagnostically critical temporal phases, such as arterial wash-in and portal venous washout. The model is further enhanced by automated lesion localization using YOLOX and class activation mapping for interpretability, ensuring that predictions align with clinically meaningful imaging features. ResultsEvaluated on a tri-modal ultrasound dataset comprising 161 patients with pathologically confirmed LR-M nodules (131 atypical HCC and 30 non-HCC malignancies), our model achieved an accuracy of 86.83%, a sensitivity of 92.50%, a specificity of 75.50%, and an AUC of 89.32% in screening atypical HCC. Compared to single-modality baselines, TUS-Net demonstrated superior specificity, a clinically critical metric given the higher risk associated with misclassifying non-HCC malignancies. Ablation studies confirmed the contribution of each module, with the full model outperforming both standard C3D and 3D ResNet backbones integrated with attention mechanisms. A reader study involving junior and senior radiologists further validated the clinical utility of AI assistance, showing consistent improvements in specificity and inter-reader consistency, particularly for less experienced clinicians. ConclusionThese results surpass existing benchmark models and demonstrate the potential of our approach to enhance diagnostic precision in clinically specific cases. By intelligently fusing multi-modal ultrasound data with attention-guided mechanisms, TUS-Net offers a reliable and interpretable tool that holds promise for improving the non-invasive diagnosis of atypical HCC in challenging LR-M liver nodules.

ObjectiveDiscriminating atypical hepatocellular carcinoma (HCC) from other malignancies in liver nodules classified as Liver Imaging Reporting and Data System category M (LR-M) remains a significant diagnostic challenge on conventional ultrasound examination. The LR-M category, originally intended to capture non-HCC malignancies, paradoxically contains up to 63% of atypical HCCs that deviate from classic enhancement patterns, leading to potential misdiagnosis and suboptimal treatment planning. While deep learning has shown promise in HCC diagnosis, most existing models rely exclusively on single-modality ultrasound, overlooking the diagnostic benefits of integrating complementary information from multiple imaging sources. To address this gap, we propose a novel attention-weighted tri-modal ultrasound network (TUS-Net) that integrates contrast-enhanced ultrasound (CEUS), B-mode ultrasound (BUS), and time-intensity curves (TICs) to improve diagnostic accuracy for these clinically challenging lesions. MethodsOur framework incorporates a three-dimensional convolutional neural network (C3D) backbone to extract spatiotemporal features from CEUS videos, capturing dynamic vascular patterns critical for lesion characterization. To effectively fuse complementary modalities, we introduce a dual-channel feature fusion module (DCFFM) that adaptively combines features from CEUS and BUS through channel-wise attention mechanisms, allowing the model to dynamically weigh the contribution of each modality based on diagnostic relevance. Additionally, we propose a temporal intensity feature fusion module (TIFFM) that leverages quantitative hemodynamic information from TICs to guide the model’s attention toward diagnostically critical temporal phases, such as arterial wash-in and portal venous washout. The model is further enhanced by automated lesion localization using YOLOX and class activation mapping for interpretability, ensuring that predictions align with clinically meaningful imaging features. ResultsEvaluated on a tri-modal ultrasound dataset comprising 161 patients with pathologically confirmed LR-M nodules (131 atypical HCC and 30 non-HCC malignancies), our model achieved an accuracy of 86.83%, a sensitivity of 92.50%, a specificity of 75.50%, and an AUC of 89.32% in screening atypical HCC. Compared to single-modality baselines, TUS-Net demonstrated superior specificity, a clinically critical metric given the higher risk associated with misclassifying non-HCC malignancies. Ablation studies confirmed the contribution of each module, with the full model outperforming both standard C3D and 3D ResNet backbones integrated with attention mechanisms. A reader study involving junior and senior radiologists further validated the clinical utility of AI assistance, showing consistent improvements in specificity and inter-reader consistency, particularly for less experienced clinicians. ConclusionThese results surpass existing benchmark models and demonstrate the potential of our approach to enhance diagnostic precision in clinically specific cases. By intelligently fusing multi-modal ultrasound data with attention-guided mechanisms, TUS-Net offers a reliable and interpretable tool that holds promise for improving the non-invasive diagnosis of atypical HCC in challenging LR-M liver nodules.

To investigate the association between sleep-related phenotypes and the risk of malignancy in pulmonary nodules, and to provide complementary evidence from a general population cohort and genetic analyses.

Lung cancer remains one of the leading causes of cancer-related morbidity and mortality worldwide, and its treatment continues to face major challenges such as therapeutic resistance and tumor recurrence. Pyroptosis, a newly characterized form of programmed cell death, induces tumor cell death through gasdermin-mediated membrane pore formation and is accompanied by the release of inflammatory mediators, thereby playing complex roles in lung cancer initiation, progression, and modulation of the tumor microenvironment. Active components and herbal formulas derived from traditional Chinese medicine can modulate pyroptosis-related signaling pathways through multi-target mechanisms, showing potential advantages in inducing lung cancer cell death, inhibiting proliferation and migration, and reversing chemoresistance. This review systematically summarizes relevant studies from domestic and international sources, focusing on the molecular mechanisms of pyroptosis, its roles in lung cancer development and tumor microenvironment remodeling, and the current research progress on traditional Chinese medicine-based interventions targeting pyroptosis, with the aim of providing references for the prevention and treatment of lung cancer using traditional Chinese medicine.

Objective: To explore the association role of anxiety and depressive symptoms with Internet gaming disorder (IGD) and emotional-behavioral problems among junior high school students, so as to provide references for preventing the occurrence and progression of emotional-behavioral problems in middle school students. Methods: From September to October 2024, a random cluster sampling method was adopted to select 38 069 students from 28 junior high schools in 14 counties (cities and districts) and functional areas of Jining City, Shandong Province. Surveys were conducted by Nine item Internet Gaming Disorder Scale-Short Form, Generalized Anxiety Disorder-7, Patient Health Questionnaire-9, and Strengths and Difficulties Questionnaire. The correlation of emotional and behavioral issues, online game addiction, anxiety and depressive symptoms among junior high school students was analyzed by Speaman correlation analysis. Mediation analysis was used to explore the role of anxiety and depressive symptoms between IGD and emotional-behavioral problems among junior high school students. Results: The detection rates of emotional-behavioral problems, anxiety symptoms, depressive symptoms, and IGD among junior high school students were 19.24 %, 9.48%, 16.69%, and 19.68%, respectively. The scores of emotional-behavioral problems, anxiety symptoms, depressive symptoms and IGD were 10.00 (6.00, 15.00), 3.00 (0.00, 7.00), and 4.00 (1.00, 8.00), 13.00 (10.00, 19.00), respectively. There were positive correlations between each pair of emotional-behavioral problem, IGD, anxiety symptoms, and depressive symptoms scores ( r =0.51-0.81, all P <0.01). Anxiety and depressive symptoms played mediating roles between IGD and emotional-behavioral problems among junior high school students, with mediating effect values of 0.16 (95% CI =0.15-0.17) and 0.12 (95% CI =0.11-0.14), respectively (both P <0.01). Conclusions Anxiety and depressive symptoms mediate the relationship between IGD and emotional-behavioral problems among junior high school students. It is necessary to identify early signs of IGD among junior high school students, strengthen intervention for anxiety and depressive symptoms, to prevent the occurrence and development of emotional and behavioral issues.

BACKGROUND:Wogonin is a flavonoid extracted from the root of Scutellaria baicalensis.Previous studies have shown that baicalein has protective effects against cerebral ischemia-reperfusion injury,and can also reduce blood sugar and complications in diabetic mice,but its role and mechanism in diabetic cerebral infarction remain unclear. OBJECTIVE:To explore the effect of wogonin on nerve injury in rats with diabetic cerebral infarction and its mechanism. METHODS:Sprague-Dawley rats were randomly divided into six groups:control group,model group,low-dose wogonin group,medium-dose wogonin group,high-dose wogonin group,and high-dose wogonin+Ras homolog gene family member A(RhoA)activator group.Except for the control group,the other rats were established with diabetes and cerebral ischemia models using intraperitoneal injection of streptozotocin and middle cerebral artery occlusion.Low,medium-and high-dose wogonin groups were intragastrically given 10,20,40 mg/kg wogonin,respectively;high-dose wogonin+RhoA activator group was intragastrically given 40 mg/kg wogonin and intraperitoneally injected 10 mg/kg lysophosphatidic acid;control group and model group were given the same amount of normal saline once a day for 7 consecutive days.Rats in each group were evaluated for neurological deficits and their blood glucose levels were measured after the last dose.TTC staining was applied to detect the volume of cerebral infarction.Hematoxylin-eosin staining was applied to observe pathological changes in brain tissue.ELISA kit was applied to detect tumor necrosis factor-α,interleukin-6,malondialdehyde,and superoxide dismutase levels in brain tissue.Western blot was applied to detect the protein expression of RhoA and Rho-associated protein kinase(ROCK)2 in brain tissue. RESULTS AND CONCLUSION:Compared with the control group,the neuronal structure of rats in the model group was severely damaged,with cell necrosis and degeneration,the neurological deficit score,blood glucose level,and infarct volume were significantly elevated(P<0.05),the levels of tumor necrosis factor-α,interleukin-6,and malondialdehyde,and the protein expression of RhoA and ROCK2 in brain tissue were significantly increased(P<0.05),and the superoxide dismutase level was decreased(P<0.05).Compared with the model group,the low-,medium-,and high-dose wogonin groups showed improved neuronal damage,reduced cell degeneration and necrosis,a significant reduction in neurological deficit score,blood glucose level,infarct volume,and the levels of tumor necrosis factor-α,interleukin-6,and malondialdehyde,and the protein expression of RhoA and ROCK2 in brain tissue,and an increase in the superoxide dismutase level(P<0.05).Compared with the high-dose wogonin group,the high-dose wogonin+RhoA activator group significantly weakened the improvement in the above indexes of rats with diabetic cerebral infarction(P<0.05).To conclude,wogonin can improve the blood glucose level in rats with diabetic cerebral infarction,reduce cerebral infarction and nerve injury,and its mechanism may be related to the inhibition of RhoA/ROCK signaling pathway.

Purpose To explore the clinical value of real-time three-dimensional automatic left atrial quantification technology in evaluating left atrial volume and function in heart failure with preserved ejection fraction(HFpEF).Materials and Methods A total of 65 patients diagnosed as HFpEF at the Fourth Affiliated Hospital of Harbin Medical University from December 2021 to October 2023 were prospectively enrolled.The control group included 65 healthy subjects who underwent ultrasound examination during the same period and were matched with the HFpEF group in terms of age and gender.According to the New York Heart Association(NYHA)cardiac function classification,patients with NYHA grade Ⅰ+Ⅱ were classified into the HFpEF group A,and those with grade Ⅲ+Ⅳ into the HFpEF group B.Relevant clinical data,conventional ultrasound parameters and three-dimensional ultrasound parameters were recorded in both the HFpEF group and the control group.Left atrial volume parameters,longitudinal strain parameters and circumferential strain parameters were analyzed.The area under the receiver operating characteristic curve was used to compare the diagnostic efficacy of left atrial functional parameters for HFpEF.Results Compared with the control group,the HFpEF group exhibited significant abnormalities in cardiac structure and function.Specifically,left ventricular posterior wall thickness,interventricular septal thickness at end-diastole,and mean E/e′ were significantly increased(t=-5.127,-5.886,-16.670,all P<0.05),while the absolute value of left ventricular global longitudinal strain(LVGLS)and septal and lateral mitral annular e′ were significantly decreased(t=-17.092,40.279,45.412,all P<0.05).All left atrial volume parameters were significantly increased,whereas left atrial functional and strain parameters were significantly decreased(t=-13.632-6.912,all P<0.05).Compared with HFpEF group A,HFpEF group B showed lower left atrial total emptying fraction,left atrial expansion index,left atrial contraction strain and absolute value of LVGLS(t=2.062,3.545,-2.189,-2.586),as well as a higher left atrial minimum volume(t=-2.187),respectively(all P<0.05).Left atrial reservoir strain was negatively correlated with N-terminal pro-B-type natriuretic peptide and mean E/e′(r=-0.395,-0.626,both P<0.05),and positively correlated with the absolute value of LVGLS(r=0.602,P<0.05).The LASr and LAEI had high predictive value for HFpEF,with area under the curve of 0.898 and 0.817,cut-off values of 20.5%and 112%,sensitivities of 96.9%and 83.1%,specificities of 75.4%and 78.5%,and Youden indices of 0.723 and 0.616,respectively.Conclusion Real-time three-dimensional automatic left atrial quantification technology enables early and sensitive detection of left atrial dysfunction in HFpEF.Among the parameters derived,LASr(a strain parameter)and LAEI(a functional parameter)exhibit high diagnostic efficacy for HFpEF.

Objective:This paper investigates residents'awareness and preference for Traditional Chinese Medicine intelligent diagnostic device(hereinafter referred to as the device),and provides basis and suggestions for further promoting the integrated development of artificial intelligence and traditional Chinese medicine clinical diagnosis.Method:A random sampling survey was conducted,and a Discrete Choice Experiment was designed to conduct an offline survey in Beijing.Use chi square test,count analysis,and conditional Logit model for data analysis.Result:A total of 480 valid questionnaires were collected and surveyed.Most respondents have heard of it(58.96%),a few have used it(31.67%),and most would recommend the device(71.25%).Knowing and using experience will increase the probability of recommendation.Residents attach the highest importance to annual average expenses;More inclined to use devices in the community that can see family data,connect data and hospitals,monitor electrocardiogram,provide comprehensive health reports,and have low annual costs;Willing to pay an additional 572 yuan per year for the comprehensive health report device.Conclusion:There should be more collaboration with hospitals in usage scenarios and cloud data.In addition,manufacturers should enrich output information and service methods of the e.