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.

OBJECTIVE: Treating peripheral nerve injury (PNI) presents a clinical challenge due to limited axon regeneration. Strychni Semen, a traditional Chinese medicine, is clinically used for numbness and hemiplegia. However, its role in promoting functional recovery after PNI and the related mechanisms have not yet been systematically studied. METHODS: A mouse model of sciatic nerve crush (SNC) injury was established and the mice received drug treatment via intragastric gavage, followed by behavioral assessments (adhesive removal test, hot-plate test and Von Frey test). Transcriptomic analyses were performed to examine gene expression in the dorsal root ganglia (DRGs) from the third to the sixth lumbar vertebrae, so as to identify the significantly differentially expressed genes. Immunofluorescence staining was used to assess the expression levels of superior cervical ganglia neural-specific 10 protein (SCG10). The ultra-trace protein detection technique was used to evaluate changes in gene expression levels. RESULTS: Strychni Semen and its active compounds (brucine and strychnine) improved functional recovery in mice following SNC injury. Transcriptomic data indicated that Strychni Semen and its active compounds initiated transcriptional reprogramming that impacted cellular morphology and extracellular matrix remodeling in DRGs after SNC, suggesting potential roles in promoting axon regeneration. Imaging data further confirmed that Strychni Semen and its active compounds facilitated axon regrowth in SNC-injured mice. By integrating protein-protein interaction predictions, ultra-trace protein detection, and molecular docking analysis, we identified myeloperoxidase as a potentially critical factor in the axon regenerative effects conferred by Strychni Semen and its active compounds. CONCLUSION Strychni Semen and its active compounds enhance sensory function by promoting axonal regeneration after PNI. These findings establish a foundation for the future applications of Strychni Semen and highlight novel therapeutic strategies and drug targets for axon regeneration. Please cite this article as: Zhang Y, Zhao XY, Liu MT, Zhou ZC, Cheng HB, Jiang XH, Zheng YR, Chen Z. Strychni Semen and its active compounds promote axon regeneration following peripheral nerve injury by suppressing myeloperoxidase in the dorsal root ganglia. J Integr Med. 2025; 23(2): 169-181.
Animals ; Nerve Regeneration/drug effects* ; Mice ; Peripheral Nerve Injuries/physiopathology* ; Male ; Ganglia, Spinal/enzymology* ; Axons/physiology* ; Peroxidase/antagonists & inhibitors* ; Mice, Inbred C57BL ; Drugs, Chinese Herbal/pharmacology* ; Disease Models, Animal ; Strychnine/pharmacology*

OBJECTIVE: Humans are exposed to complex mixtures of environmental chemicals and other factors that can affect their health. Analysis of these mixture exposures presents several key challenges for environmental epidemiology and risk assessment, including high dimensionality, correlated exposure, and subtle individual effects. METHODS: We proposed a novel statistical approach, the generalized functional linear model (GFLM), to analyze the health effects of exposure mixtures. GFLM treats the effect of mixture exposures as a smooth function by reordering exposures based on specific mechanisms and capturing internal correlations to provide a meaningful estimation and interpretation. The robustness and efficiency was evaluated under various scenarios through extensive simulation studies. RESULTS: We applied the GFLM to two datasets from the National Health and Nutrition Examination Survey (NHANES). In the first application, we examined the effects of 37 nutrients on BMI (2011-2016 cycles). The GFLM identified a significant mixture effect, with fiber and fat emerging as the nutrients with the greatest negative and positive effects on BMI, respectively. For the second application, we investigated the association between four pre- and perfluoroalkyl substances (PFAS) and gout risk (2007-2018 cycles). Unlike traditional methods, the GFLM indicated no significant association, demonstrating its robustness to multicollinearity. CONCLUSION GFLM framework is a powerful tool for mixture exposure analysis, offering improved handling of correlated exposures and interpretable results. It demonstrates robust performance across various scenarios and real-world applications, advancing our understanding of complex environmental exposures and their health impacts on environmental epidemiology and toxicology.
Humans ; Environmental Exposure/analysis* ; Linear Models ; Nutrition Surveys ; Environmental Pollutants ; Body Mass Index

Objective To compare the clinical efficacy between liposuction combined with circumareolar small incision and three-port endoscopic surgery for the treatment of Simon Ⅱ gynecomastia (GYN). Methods Comparative case data of 120 patients with GYN were retrospectively analyzed, 61 patients in the open group underwent circumareolar small incision mastectomy after liposuction, and 59 patients in the endoscopic group underwent three-port endoscopic mastectomy after liposuction. The two groups were compared in terms of surgery-related indexes, occurrence of postoperative complications and patient satisfaction. Results The unilateral operation time of the open group was shorter than that of the endoscopic group, the unilateral gland resection weight in the open group was more than that in the endoscopic group, the hospitalization cost of the open group was less than that of the endoscopic group (all P<0.01). There was no significant difference in unilateral liposuction volume, drainage volume on the first postoperative day, and time to drain removal between the two groups (P>0.05). The incidence of complications in the open group and the endoscopic group were 8.2% and 13.6% respectively, and there was no significant difference between the two groups (P>0.05). The difference in the overall satisfaction scores between the two groups was not statistically significant (P>0.05). Conclusions Liposuction combined with circumareolar small incision or three-port endoscopic surgery both has good cosmetic effects in the treatment of Simon Ⅱ GYN. The operation with circumareolar small incision is simple, has a shorter operation time, costs less, and does not require special equipment, which is suitable for promotion and application in medical institutions.

Varicocele, the most common and treatable cause of male infertility, significantly impacts fertility. The pathophysiological mechanisms of varicocele have not been fully understood yet. Recent studies have focused on the pathophysiology of varicocele-induced infertility, highlighting inflammation and oxidative stress as key contributing factors. We reviewed recent research on the roles of inflammation and oxidative stress in the pathophysiology of varicocele and found that they negatively impact semen parameters, spermatogenesis, and testicular and epididymal function. In addition, this article summarizes the related factors of inflammation and oxidative stress caused by varicocele. Finally, a brief consideration on the treatments to address inflammation and oxidative stress is proposed. This review may provide treatment options and targets for varicocele-induced infertility. However, the relationship between inflammation and oxidative stress in varicocele still needs further study.
Varicocele/physiopathology* ; Humans ; Oxidative Stress/physiology* ; Infertility, Male/metabolism* ; Male ; Inflammation/physiopathology* ; Spermatogenesis/physiology*

This study aims to explore the correlation between plasma homocysteine (Hcy) levels and the clinical grading of varicocele (VC) when analyzing the potential pathogenesis of endothelial cells injury by Hcy. A total of 184 VC patients, aged 18-46 years, were included in this study. These patients visited The Second Hospital of Dalian Medical University (Dalian, China), between January 2022 and September 2024. Patients were divided into three groups based on clinical grading: Group A (59 cases, Grade I), Group B (28 cases, Grade II), and Group C (97 cases, Grade III). Additionally, 120 individuals with normal fertility test results during the same period were selected as the control group. Routine blood and biochemical indices were collected from the patients. Differences in clinical indices between groups were compared, and univariate and multivariate linear regression analyses were performed to identify factors associated with clinical grading. The results showed that the median Hcy levels in the control group and in patients with Grade I, II, and III VC were 9.56 (interquartile range [IQR]: 8.66, 14.02) µmol l -1 , 11.28 (IQR: 9.71, 14.55) µmol l -1 , 11.84 (IQR: 10.14, 15.60) µmol l -1 , and 12.27 (IQR: 9.52, 15.40) µmol l -1 , respectively. The differences between the four groups were statistically significant ( χ2 = 12.41, P = 0.006). Multivariate regression analysis indicated that Hcy is a factor associated with the clinical grading of VC ( t = 2.53, P = 0.013). Hcy is associated with the clinical grading and may have clinical value in assessing severity of VC.
Humans ; Varicocele/pathology* ; Male ; Homocysteine/blood* ; Adult ; Middle Aged ; Adolescent ; Young Adult ; Severity of Illness Index ; Case-Control Studies

Debates persist regarding the efficacy and safety of azvudine, particularly its real-world outcomes. This study involved patients aged ≥60 years who were admitted to 25 hospitals in mainland China with confirmed SARS-CoV-2 infection between December 1, 2022, and February 28, 2023. Efficacy outcomes were all-cause mortality during hospitalization, the proportion of patients discharged with recovery, time to nucleic acid-negative conversion (T _NANC), time to symptom improvement (T _SI), and time of hospital stay (T _HS). Safety was also assessed. Among the 5884 participants identified, 1999 received azvudine, and 1999 matched controls were included after exclusion and propensity score matching. Azvudine recipients exhibited lower all-cause mortality compared with controls in the overall population (13.3% vs. 17.1%, RR, 0.78; 95% CI, 0.67-0.90; P = 0.001) and in the severe subgroup (25.7% vs. 33.7%; RR, 0.76; 95% CI, 0.66-0.88; P < 0.001). A higher proportion of patients discharged with recovery, and a shorter T _NANC were associated with azvudine recipients, especially in the severe subgroup. The incidence of adverse events in azvudine recipients was comparable to that in the control group (2.3% vs. 1.7%, P = 0.170). In conclusion, azvudine showed efficacy and safety in older patients hospitalized with COVID-19 during the SARS-CoV-2 omicron wave in China.

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*