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 Exploring genetic differences among geographic strains of Anopheles sinensis in China. Methods Based on the mitochondrial cytochrome oxidase subunit I(COⅠ )and ribosomal the second internal transcribed spacer(ITS2), genetic distance analyses were conducted on An. sinensis samples collected nationwide. Results Genetic differentiation was observed within An. sinensis geographic strains, primarily reflected in the genetic distances of COⅠ sequences, with some distances between samples exceeding those between closely related species. However, ITS2 sequences showed relatively low levels of differentiation within geographic strains. No significant separation was observed, and gene exchange exhibited a random pattern among geographic strains. Conclusions Significant differences in genetic distance were observed among An. sinensis samples, along with evidence of interspecific continuity among sibling species. For the identification of closely related species using wild-collected Anopheles mosquitoes samples, reliance solely on commonly used barcodes such as COⅠ and ITS2 may be insufficient. Additional molecular markers, including COⅡ and D3 gene fragments, should also be considered. Caution should be exercised when using COⅠ genes to identify cryptic species, especially within Anopheles mosquitoes.

OBJECTIVES: To investigate the risk factors for the occurrence of cardiopulmonary dysfunction following ligation of hemodynamically significant patent ductus arteriosus (hsPDA) in preterm infants. METHODS: A retrospective collection of clinical data was conducted on preterm infants with a gestational age of <34 weeks who were admitted to the Maternal and Child Health Hospital of Hubei Province, Tongji Medical College, Huazhong University of Science and Technology from January 2018 to August 2024. These infants underwent hsPDA ligation after 1-2 courses of failed ibuprofen treatment. Based on the occurrence of blood pressure changes and oxygenation or ventilation failure postoperatively, the infants were divided into a cardiopulmonary dysfunction group (19 cases) and a non-cardiopulmonary dysfunction group (40 cases). Binary logistic regression analysis was performed to explore risk factors for postoperative cardiopulmonary dysfunction. RESULTS: Binary logistic regression analysis indicated that a faster average weight gain rate preoperatively and low levels of free triiodothyronine (FT₃) within one week before surgery were risk factors for cardiopulmonary dysfunction following hsPDA ligation (P<0.05). Receiver operating characteristic curve analysis showed that an average weight gain rate >11.45 g/(kg·d) and FT₃ levels <2.785 pmol/L within one week before surgery had predictive value for postoperative cardiopulmonary dysfunction (P<0.05). The combination of these two indicators provided the highest predictive value (P<0.05), with an area under the curve of 0.825, a sensitivity of 79%, and a specificity of 75%. CONCLUSIONS An average weight gain rate exceeding 11.45 g/(kg·d) and FT₃ levels below 2.785 pmol/L within one week before surgery are risk factors affecting cardiopulmonary function after hsPDA ligation. Preoperative assessment and intervention should be strengthened to reduce the risk of postoperative complications.
Humans ; Ductus Arteriosus, Patent/physiopathology* ; Risk Factors ; Female ; Infant, Newborn ; Male ; Retrospective Studies ; Infant, Premature ; Ligation/adverse effects* ; Hemodynamics ; Postoperative Complications/etiology* ; Logistic Models ; Lung Diseases/etiology*

OBJECTIVES: To investigate the protective effects and underlying mechanisms of Gynostemma pentaphyllum (GP)ethanol extract on motor dysfunction in a mouse model of Parkinson's disease (PD). METHODS: Eighty C57BL/6 male mice were randomly divided into five groups: control group, model group, levodopa group (positive control group), low-dose GP group, and high-dose GP group, with 16 mice per group. The PD model was induced by injection of 6-hydroxydopamine into the substantia nigra pars reticulata of the mice. Two weeks after 6-hydroxydopamine, positive control group received intraperitoneal injection of levodopa 10 mg·kg^－1·d^－1, while low-dose GP and high-dose GP groups received GP extract 100 or 200 mg·kg^－1·d^－1 orally for three weeks. After a 3-week-treatment, the effects of GP on motor dysfunction in 6-hydroxydopamine-induced PD were assessed using open field and CatWalk gait tests, while the effects on muscle strength were evaluated by forelimb grip strength. Immunofluorescence staining was used to detect the number of tyrosine hydroxylase (TH) positive neurons. The levels of dopamine and serotonin in the midbrain were determined by enzyme-linked immunosorbent assay. In addition, Western blotting was performed to detect the expression of mitogen-activated protein kinase (MAPK) family proteins such as p-extracellular signal-regulated kinase (ERK)1/2, p-p38 and p-c-Jun N-terminal kinase (JNK)1/2, and mitochondrial apoptosis pathway proteins such as B-cell lymphoma (Bcl)-2, Bcl-2 associated X protein (Bax), and cleaved-cysteine aspartic acid specific protease (caspase)-3. RESULTS: Behavioral experiments showed that GP significantly improved the spontaneous activity and motor coordination of PD mice (P<0.05). The forelimb grip strength was also increased by GP treatment (P<0.05), compared to the PD model group. In addition, compared with the model group, the number of TH-positive neurons in substantia nigra pars reticulata region, the levels of dopamine and serotonin in midbrain and the expression of p-ERK1/2 were significantly increased by GP treatment (all P<0.05), whereas the expression of p-p38 and p-JNK1/2, the ratio of Bax/Bcl-2 and cleaved-caspase-3/caspase-3 were significantly decreased (all P<0.05). CONCLUSIONS The results indicate that GP might increase dopamine and serotonin levels in the midbrain and promote the survival of dopaminergic neurons in substantia nigra pars reticulata by regulating the expression of phosphorylation of MAPK family proteins and the expression of mitochondrial apoptosis-related proteins, thereby ameliorating motor deficits in PD mice.
Animals ; Mice ; Male ; Gynostemma/chemistry* ; Mice, Inbred C57BL ; Apoptosis/drug effects* ; Plant Extracts/therapeutic use* ; Parkinson Disease/metabolism* ; Disease Models, Animal ; Neurons/pathology*

Benign prostatic hyperplasia (BPH) is one of the most common diseases in elderly men, the incidence of which gradually increases with age and leads to lower urinary tract symptoms (LUTS), which seriously affects the quality of life of patients. Chinese herbal medicines (CHMs) are widely used for the treatment of BPH in China and some other countries. To explore the molecular mechanisms of CHMs for BPH, we conducted a review based on peer-reviewed English-language publications in PubMed and Web of Science databases from inception to December 31, 2023. This article primarily reviewed 32 papers on the use of CHMs and its active compounds in the treatment of BPH, covering animal and cell experiments, and identified relevant mechanisms of action. The results suggest that the mechanisms of action of CHMs in treating BPH may involve the regulation of sex hormones, downregulation of cell growth factors, anti-inflammatory and antioxidative effects, inhibition of cell proliferation, and promotion of apoptosis. CHMs also exhibit α-blocker-like effects, with the potential to relax urethral smooth muscle and alleviate LUTS. Additionally, we also reviewed 4 clinical trials and meta-analyses of CHMs for the treatment of BPH patients, which provided initial evidence of the safety and effectiveness of CHMs treatment. CHMs treatment for BPH shows advantages as a multi-component, multi-target, and multi-pathway therapy, which can mitigate the severity of the disease, improve LUTS, and may become a reliable treatment option in the future.
Prostatic Hyperplasia/drug therapy* ; Humans ; Drugs, Chinese Herbal/pharmacology* ; Male ; Animals

The inference of tissue origin of body fluid stains is crucial for case investigation and court proceedings.However,traditional methods for identification of body fluid stains,such as morpho-logical,chemical,and immunoassay identifications have certain limitations,and there is an urgent need for more efficient methods for confirmatory experiments.In recent years,the rapid development of tran-scriptomics technology has provided new means for the identification of tissue origin of body fluid stains.Different types of RNA in the transcriptome have their own advantages.This paper elaborates in detail on the application of different types of RNA,such as mRNA,miRNA,circRNA,lncRNA,piRNA and microbial transcriptomics in body fluid identification,and summarizes their respective ad-vantages and limitations,in order to provide a reference for related research.

Objective:To analyze the epidemiological characteristics of cases involving monkey injuries at medical institutions surrounding Qianlingshan Park in Guiyang City, and to provide a reference basis for preventive measures to reduce monkey injuries and standardized post-exposure treatment.Methods:A retrospective cross-sectional study was conducted, collecting 1 900 cases of monkey-induced injuries in Qianlingshan Park treated at the outpatient clinic of Guizhou Provincial Center for Disease Control and Prevention and the Department of Surgery at Qianling Hospital, Guiyang City, from 2021 to 2024. Statistical analysis was performed using Pearson′s chi-square test.Results:Total of 1 900 cases of monkey-related injuries in Qianlingshan Park were collected from 2021 to 2024. The exposure time distribution exhibited significant seasonality, with 48.58% of cases occurring during July and August, totaling 923 cases, indicating a peak in the summer. There were 774 male patients and 1 126 female patients, with a ratio of 1∶1.45.and significant differences were observed between different age groups and genders (χ2=195.00, P<0.001), with the highest number of cases occurring in the 0-9 and 20-29 age groups, accounting for 22.05%(419 cases) and 21.79%(414 cases), respectively. The upper limbs were the most common injury site, accounting for 50.84% of the total cases(966 cases in total), with significant differences between gender and injury location (χ2=22.00, P<0.001), Among females, the proportion of injuries to the upper and lower limbs (30.11% and 16.47%, respectively) was higher than that among males (20.74% and 8.63%, respectively). The majority of injuries were classified as Grade Ⅲ, making up 57.38% of cases(1 069 cases in total). Self-treatment after exposure was the most common approach(60.44%), with significant differences observed between wound severity and treatment method (χ2=6.90, P=0.032), Patients with Grade Ⅱ and Grade Ⅲ wounds were more likely to choose self-management (26.84% and 33.23%, respectively) than outpatient management (15.14% and 24.15%). Approximately 98.05% (1 863 cases) of monkey-injured patients had received rabies vaccinations. Conclusions:This study analyzes monkey-related injuries in Qianlingshan Park from 2021 to 2024, clarifying the temporal distribution of injuries, demographic characteristics, injury sites, and treatment methods. The findings provide references for optimizing human-monkey conflict management and the prevention and control of zoonotic diseases in urban ecological parks.

Objective:To investigate the association of the interaction and combined effect of renal function and body mass index (BMI) with the risk for all-cause death in patients with type 2 diabetes mellitus (T2DM) in communities of Jiangsu Province.Methods:The study subjects were from the Comprehensive Research Project of Diabetes Prevention and Control conducted in Jiangsu from December 2013 to January 2014, and follow up was conducted for them until September 30, 2023. A total of 20 025 subjects were included in the study. Cox proportional hazards regression model was used to analyze the association of renal function with risk for death in T2DM patients, and the association of interaction between renal function and BMI and their combined effect with all-cause death risk in T2DM patients.Results:In the follow up for 198 370 person-years, a total of 4 459 deaths were recorded. Cox proportional hazards regression model analysis showed that renal dysfunction was associated with 71% risk of all-cause mortality in all T2DM patients [hazard ratio ( HR) =1.71, 95% CI: 1.59-1.84], as well as in all BMI subgroups. Likelihood ratio test indicated an interaction between renal function and BMI (interaction for P=0.030). Compared with patients with normal renal function and normal BMI, those with normal renal function and over weight or obesity had a lower risk of all-cause mortality, and those with renal dysfunction and low weight had the highest risk for death ( HR=2.78, 95% CI: 1.87-4.14). Conclusions:There is association of interaction between renal function and BMI with all-cause mortality in T2DM patients. T2DM patients with renal dysfunction and low body weight had significant higher risk for death.