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.

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.

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.

ObjectiveTo systematically identify the main chemical components of Linggui Zhugan granules （LGZGG）， and to explore the pharmacodynamic substance basis for the treatment of metabolic dysfunction-associated steatohepatitis （MASH）. MethodsThe chemical components of LGZGG were systematically analyzed by ultra-performance liquid chromatography-quadrupole-time-of-flight tandem mass spectrometry （UPLC-Q-TOF-MS/MS）. The protein-protein interaction （PPI） network and "compound prescription-disease-component-target" network were constructed by network target analysis to predict the potential pharmacodynamic substances and core targets of LGZGG in the treatment of MASH. The potential pharmacodynamic substances were enriched by macroporous adsorption resin， and the chemical composition of the LGZGG-50% ethanol elution fraction （LGZGG-50） was analyzed by UPLC-Q-TOF-MS/MS. The mouse model of MASH was established by feeding a high-fat， high-cholesterol， and high-fructose diet for 12 weeks. Mice were randomly allocated into normal， model， positive drug （MGL-3196， 1 mg·kg^-1）， LGZGG （crude drug， 34 g·kg^-1·d^-1）， LGZGG-50 （crude drug， 34 g·kg^-1·d^-1） groups. The levels of aspartate aminotransferase （AST）， alanine aminotransferase （ALT）， total cholesterol （TC）， triglyceride （TG）， low-density lipoprotein cholesterol （LDL-C）， and high-density lipoprotein cholesterol （HDL-C） in the serum were measured， and the pathological changes in the liver tissue were observed by hematoxylin-eosin （HE） and Sirius red staining. The in vivo efficacy of LGZGG and LGZGG-50 in the treatment of MASH was evaluated on the basis of the findings. The expression levels of adenosine monophosphate-activated protein kinase （AMPK）， phosphorylated AMPK （p-AMPK）， silent information regulator 2-related enzyme 1 （SIRT1）， peroxisome proliferator-activated receptor α （PPARα）， and carnitine palmitoyltransferase 1A （CPT1A） in the liver tissue were determined by Western blot to verify the regulatory effects of core targets. ResultsA total of 83 chemical components were identified from LGZGG， including 20 flavonoids， 13 terpenoids， 17 organic acids， 7 amino acids， 11 glycosides， 3 nucleosides， 3 aromatics， 3 alkaloids， 2 phenylpropanoids， 2 sugars， 1 nucleic acid， and 1 steroid. A total of 134 common targets were obtained by network target analysis. The core targets included SIRT1， PPARα， nuclear factor-kappa B subunit 1 （NF-κB1）， and interleukin-6 （IL-6）. Kyoto Encyclopedia of Genes and Genomes （KEGG） enrichment analysis revealed that the targets were mainly enriched in the AMPK， PPAR and other signaling pathways. The topological analysis of the "compound prescription-disease-component-target" network showed that the potential pharmacodynamic substances of LGZGG against MASH were flavonoids and terpenoids. The relative content of flavonoids and terpenes in LGZGG-50 were 74.00% and 62.41% in positive and negative ion modes， respectively， indicating that LGZGG-50 effectively enriched total flavonoids and total terpenoids. The results of in vivo efficacy showed that compared with the model group， LGZGG and LGZGG-50 reducef the body weight， liver weight， serum TG， GLU， and ALT levels of MASH mice （P<0.05，P<0.01）， and LGZGG additionally increased the HDL-C level （P<0.01）. Both groups alleviated the pathological damage in the liver tissue. The results of Western blot showed that compared with the model group， the protein levels of p-AMPK/AMPK， SIRT1， PPARα， and CPT1A were up-regulated in the LGZGG group （P<0.05，P<0.01）， and those of p-AMPK/AMPK and CPT1A were up-regulated in the LGZGG-50 group （P<0.01）. ConclusionLGZGG ameliorates MASH， with the main pharmacodynamic substances being flavonoids and terpenoids. The mechanism may be related to the regulation of AMPK/SIRT1/PPARα signaling pathway， improvement of lipid metabolism， and alleviation of pathological damage in the liver tissue.

Lung cancer constitutes the most prevalent and lethal malignant tumor in China. Approximately 85% of lung cancer diagnoses correspond to the non-small cell histological subtype [non-small cell lung cancer (NSCLC)]. Despite surgery being the mainstay for early-stage disease, postoperative recurrence remains high and adjuvant chemotherapy offers limited benefit. In recent years, targeted therapy has demonstrated substantial advantages in driver mutation-positive NSCLC. To this end, the Lung Cancer Medical Education Committee of the Chinese Medical Education Association developed guidelines based on a systematic review of evidence through November 2025, using the Grading of Recommendations, Assessment, Development and Evaluations (GRADE) approach and a modified Delphi method. Focusing on epidermal growth factor receptor (EGFR) and anaplastic lymphoma kinase (ALK), and addressing ROS proto-oncogene 1 (ROS1), B-Raf proto-oncogene serine/threonine kinase (BRAF) V600E mutation, and mesenchymal-epithelial transition factor (MET) exon 14 (METex14) skipping, the guideline covers molecular testing, neoadjuvant/adjuvant therapy, perioperative strategies, minimal residual disease monitoring, and postoperative surveillance. It defines testing requirements, specifies stage-directed and subtype-specific treatments, and standardizes minimal residual disease monitoring. These recommendations emphasize precision and feasibility to improve survival and quality of life.

Hepatocellular carcinoma(HCC), the third leading cause of cancer-related death worldwide, is characterized by high mortality and recurrence rates. Common treatments include hepatectomy, liver transplantation, ablation therapy, interventional therapy, radiotherapy, systemic therapy, and traditional Chinese medicine(TCM). While exhibiting specific advantages, these approaches are associated with varying degrees of adverse effects. To alleviate patients' suffering and burdens, it is crucial to explore additional treatments and elucidate the pathogenesis of HCC, laying a foundation for the development of new TCM-based drugs. With emerging research on gut microbiota, it has been revealed that microbiota plays a vital role in the development of HCC by influencing intestinal barrier function, microbial metabolites, and immune regulation. TCM, with its multi-component, multi-target, and multi-pathway characteristics, has been increasingly recognized as a vital therapeutic treatment for HCC, particularly in patients at intermediate or advanced stages, by prolonging survival and improving quality of life. Recent global studies demonstrate that TCM exerts anti-HCC effects by modulating gut microbiota, restoring intestinal barrier function, regulating microbial composition and its metabolites, suppressing inflammation, and enhancing immune responses, thereby inhibiting the malignant phenotype of HCC. This review aims to elucidate the mechanisms by which gut microbiota contributes to the development and progression of HCC and highlight the regulatory effects of TCM, addressing the current gap in systematic understanding of the "TCM-gut microbiota-HCC" axis. The findings provide theoretical support for integrating TCM with western medicine in HCC treatment and promote the transition from basic research to precision clinical therapy through microbiota-targeted drug development and TCM-based interventions.
Humans ; Gastrointestinal Microbiome/drug effects* ; Carcinoma, Hepatocellular/microbiology* ; Liver Neoplasms/microbiology* ; Drugs, Chinese Herbal/administration & dosage* ; Animals ; Medicine, Chinese Traditional

The therapeutic effects of Yueju Pills on depression and cardiovascular diseases have been widely recognized. Previous studies have shown that the drug can significantly improve depressive-like behaviors induced by chronic unpredictable mild stress(CUMS) combined with atherosclerosis(AS). Given the complex pathogenesis of psychocardiac diseases, this study integrated metabolomics and network pharmacology to systematically elucidate the mechanism of Yueju Pills in alleviating depressive symptoms in psychocardiac diseases. The results demonstrate that, after Yueju Pill intervention, the levels of 9 abnormal metabolites in the hippocampus restore to normal ranges, primarily involving key pathways or signaling pathways, including the cyclic adenosine monophosphate(cAMP), mammalian target of rapamycin(mTOR), glycine/serine/threonine metabolism, and aminoacyl-tRNA biosynthesis. In a high-fat diet-induced CUMS ApoE~(-/-) mouse model, Yueju Pills significantly increases adenosine monophosphate(AMP) levels and decreases L-alanine and D-glyceric acid levels in the hippocampus. In conclusion, Yueju Pills exert antidepressant effects by regulating multiple metabolic axes, including glycine/serine/threonine metabolism and the cAMP, mTOR signaling pathways. Network pharmacology predictions reveal that the treatment of CUMS combined with AS by its core active components may be realized through modulating pathways concerning neuroinflammation and synaptic plasticity, including serine/threonine-protein kinase 1(AKT1), mitogen-activated protein kinase 1(MAPK1), and prostaglandin-endoperoxide synthase 2(PTGS2). This study provides a theoretical reference for the clinical application of Yueju Pills in alleviating the depressive symptoms of psychocardiac diseases.
Animals ; Network Pharmacology ; Mice ; Drugs, Chinese Herbal/administration & dosage* ; Metabolomics ; Male ; Depression/genetics* ; Humans ; Hippocampus/drug effects* ; Mice, Inbred C57BL ; Signal Transduction/drug effects*

OBJECTIVE: To explore the current research status and hotspots in the field of biomechanics of diabetic foot by bibliometric analysis methods. METHODS: Literatures related to biomechanics of diabetic foot published in the Web of Scienc Core Collection (WoSCC) from 1981 to 2024 were searched. CiteSpace software and R language bibliometrics plugin were used to conduct a visual analysis of annual publication volume of the literature, including publication volume of each country and region, the publication situation of authors and institutions, the citation situation of individual literature, and the co-occurrence network of keywords. RESULTS: Totally 996 literatures were included, and the number of published papers increased steadily. The United States (261 papers) and China (89 papers) were the top two countries in terms of the number of published papers. The mediating centrality of the United States was 0.94, and that of China was 0.01. Scholars such as Cavanagh and institutions like the Cleveland Clinic were at the core of research in this field. High-frequency keywords include plantar pressure (plantar pressure), diabetic foot (diabetic foot), ulceration (ulcer), etc. The research focuses on plantar pressure, ulcer formation and prevention, etc. CONCLUSION Biomechanical research on diabetic foot mainly focuses on the pressure distribution on the sole of the foot, callus formation, mechanical analysis of soft tissues on the sole of the foot, and the study of plantar decompression caused by Achilles tendon elongation. The research trend has gradually shifted from focusing on joint range of motion to gait and the design of braces and assistive devices, and has begun to pay attention to muscle strength, gait imbalance and proprioception abnormalities.
Humans ; Diabetic Foot/physiopathology* ; Biomechanical Phenomena ; Bibliometrics