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.

Organ transplantation is an effective treatment for end-stage organ failure, but postoperative infections and rejection reactions are key factors affecting the survival of the patients. Recently, the incidence of human parvovirus B19 (B19V) infection following transplantation has increased. B19V is a non-enveloped virus that primarily infects the upper respiratory tract and exhibits significant tropism for erythroid progenitor cells in the bone marrow, leading to the lysis of erythrocytes and hematological abnormalities. After B19V viremia, it may further infect other cells, triggering inflammatory responses and tissue damage. B19V infection may lead to chronic anemia in organ transplant patients, thereby affecting the success of the transplant and the survival of the patients. Therefore, it is essential to diagnose and monitor B19V infection post-transplantation. Due to the immunosuppressive therapy following transplantation, traditional serological detection methods, such as IgM and IgG antibody tests, are often unreliable. In contrast, molecular biological detection, especially real-time fluorescent quantitative PCR technology, provides more accurate results. However, the diversity of B19V genotypes may lead to the missed detection of some genotypes. Thus, it is necessary to use different detection techniques to improve the diagnostic accuracy of B19 virus infections. Additionally, there is a need to explore more precise diagnostic methods to enhance the early identification and management of B19V infection, further improving the survival and life quality of the patients.

Objective:To investigate the anti-heart failure mechanism of N-acetylcysteine(NAC)in diabetic cardiomyop-athy independent from coronary artery factors.Methods:A total of 40 diabetic mice after heart failure model construction were randomly divided into two groups,NAC group(n=20,NAC 100mg·kg-1·d-1)and control group(n=20,Saline 100 mg·kg-1·d-1).Echocardiography was performed to detect left ventricular end-diastolic volume(LVEDV),left ventricular end-systolic volume(LVESV),left ventricular ejection fraction(LVEF),mitral left ventricular early-dias-tolic peak flow velocity/left ventricular late-diastolic peak flow velocity(E/A),isovolumic relaxation time(IVRT)and cardiac output(CO)after 4 weeks.Terminal uridine nick-end labeling(TUNEL)was performed to detect apoptosis in-dex,and Western Blot was performed to detect the expression of extracellular regulated protein kinases(ERK)1/2 after 6 weeks in two groups.Results:Compared to those in control group,mice in NAC group had significant higher LVEF[(40.5±3.4)％vs.(36.9±3.2)％],E/A[(1.5±0.1)vs.(1.4±0.1)]and CO[(10.3±0.6)ml/min vs.(9.9±0.5)ml/min](P＜0.05 or＜0.01);and significant lower LVESV[(23.1±1.3)μl vs.(24.7±1.5)μl],apoptosis index[(31.2±0.5)％vs.(45.1±0.9)％]and the expression of ERK1/2[(2.2±0.2)vs.(3.9±0.1)](P＜0.001 all).Conclusion:NAC exerts anti-heart failure effect by attenuating apoptosis of cardiomyocytes via regulating ERK1/2 pathway.

OBJECTIVE: This study aimed to explore the association between body mass index (BMI) and mortality based on the 10-year population-based multicenter prospective study. METHODS: A general population-based multicenter prospective study was conducted at four sites in rural China between 2013 and 2023. Multivariate Cox proportional hazards models and restricted cubic spline analyses were used to assess the association between BMI and mortality. Stratified analyses were performed based on the individual characteristics of the participants. RESULTS: Overall, 19,107 participants with a sum of 163,095 person-years were included and 1,910 participants died. The underweight (< 18.5 kg/m ²) presented an increase in all-cause mortality (adjusted hazards ratio [ aHR] = 2.00, 95% confidence interval [ CI]: 1.66-2.41), while overweight (≥ 24.0 to < 28.0 kg/m ²) and obesity (≥ 28.0 kg/m ²) presented a decrease with an aHR of 0.61 (95% CI: 0.52-0.73) and 0.51 (95% CI: 0.37-0.70), respectively. Overweight ( aHR = 0.76, 95% CI: 0.67-0.86) and mild obesity ( aHR = 0.72, 95% CI: 0.59-0.87) had a positive impact on mortality in people older than 60 years. All-cause mortality decreased rapidly until reaching a BMI of 25.7 kg/m ² ( aHR = 0.95, 95% CI: 0.92-0.98) and increased slightly above that value, indicating a U-shaped association. The beneficial impact of being overweight on mortality was robust in most subgroups and sensitivity analyses. CONCLUSION This study provides additional evidence that overweight and mild obesity may be inversely related to the risk of death in individuals older than 60 years. Therefore, it is essential to consider age differences when formulating health and weight management strategies.
Humans ; Body Mass Index ; China/epidemiology* ; Male ; Female ; Middle Aged ; Prospective Studies ; Rural Population/statistics & numerical data* ; Aged ; Follow-Up Studies ; Adult ; Mortality ; Cause of Death ; Obesity/mortality* ; Overweight/mortality*

Organ transplantation is an effective treatment for end-stage organ failure, but postoperative infections and rejection reactions are key factors affecting the survival of the patients. Recently, the incidence of human parvovirus B19 (B19V) infection following transplantation has increased. B19V is a non-enveloped virus that primarily infects the upper respiratory tract and exhibits significant tropism for erythroid progenitor cells in the bone marrow, leading to the lysis of erythrocytes and hematological abnormalities. After B19V viremia, it may further infect other cells, triggering inflammatory responses and tissue damage. B19V infection may lead to chronic anemia in organ transplant patients, thereby affecting the success of the transplant and the survival of the patients. Therefore, it is essential to diagnose and monitor B19V infection post-transplantation. Due to the immunosuppressive therapy following transplantation, traditional serological detection methods, such as IgM and IgG antibody tests, are often unreliable. In contrast, molecular biological detection, especially real-time fluorescent quantitative PCR technology, provides more accurate results. However, the diversity of B19V genotypes may lead to the missed detection of some genotypes. Thus, it is necessary to use different detection techniques to improve the diagnostic accuracy of B19 virus infections. Additionally, there is a need to explore more precise diagnostic methods to enhance the early identification and management of B19V infection, further improving the survival and life quality of the patients.

Aim To investigate the neuroprotective effect of dioscin(DIO)on hippocampal neurons(HT22)after oxygen glucose deprivation/reoxygen-ation(OGD/R)and its possible mechanism.Methods HT22 cells were treated with 0,2.5,5,10,20,40,80,160,and 320 mg·L-1DIO for 24 h,and the cell proliferation rate was detected by CCK-8 method.The concentration that was non-toxic to HT 2 2 cells was se-lected for subsequent experiments.After OGD for 2 h,HT22 cells were randomly divided into the OGD/R group,1.25,2.5,and 5 mg·L-1DIO group,and posi-tive control group.HT22 cells were taken as the con-trol group.After drug intervention for 24 h,the cell proliferation rate was detected by CCK-8 method;the LDH release was detected by colorimetry;the cell ap-optosis rate was detected by TUNEL method;the ex-pression of proteins related to PARP-1/AIF pathway and caspase pathway was detected by Western blot.Results DIO intervention significantly upregulated the expression of AIF protein in mitochondria and PAR protein in nucleus of HT22 cells after OGD/R,and sig-nificantly downregulated the release of LDH,neuronal apoptosis rate,total protein expression of AIF and PAR,PARP-1,AIF in nucleus and protein expression of PAR protein in mitochondria,while the expression of Bax and caspase-3 proteins was not significantly differ-ent from that in the OGD/R group.Conclusion DIO can alleviate the apoptosis of HT22 cells induced by OGD/R by regulating the expression and translocation of proteins related to the PARP-1/AIF pathway,thus playing a neuroprotective role.

Aim To explore the mechanisms of PM2.5 exposure exacerbating bleomycin(BLM)-induced idio-pathic pulmonary fibrosis(IFP)by regulating ferropto-sis via nuclear factor 2 related factor 2(Nrf2)/solute carrier family 7 member 11(SLC7A11)/glutathione peroxidase(GPX)4 axis.Methods Forty C57BL/6J mice were randomized into the control,BLM,PM2.5,BLM+PM2.5 and sulforaphane(SFN,Nrf2 agonist)groups,with eight mice in each group.PM2.5 expo-sures were conducted to the BLM-induced IPF mice for two weeks.The lung function was measured,and the content of hydroxyproline(HYP)in lung tissue and the pathomorphology of lungs were observed.Reactive oxygen species(ROS),malondialdehyde(MDA),ferrous ion(Fe2+)and glutathione(GSH)of the lung tissue were measured by ELISA.The mRNA and pro-teins levels of Nrf2,SLC7A11,GPX4,collagen typeⅠ(COL-1),α-smooth muscle actin(α-SMA)were measured by quantitative polymerase chain reaction(qPCR)and Western blot.Results Compared with the control group,the lung function of mice was signif-icantly reduced(P＜0.01)in the BLM and PM2.5 groups,while lung tissue showed the characteristic pathological changes of pulmonary fibrosis such as a large number of inflammatory cell infiltration,alveolar wall fracture,thickening,collagen deposition,and sig-nificantly increased HYP,Fe2+,ROS,MDA(P＜0.05,P＜0.01),genes and proteins of COL-1,α-SMA(P＜0.01);and decreased GSH,Nrf2,SLC7A11,GPX4 genes and proteins(P＜0.05,P＜0.01).The above-mentioned lesions were markedly aggravated in the BLM+PM2.5 group compared with the BLM(P＜0.05)and PM2.5 groups(P＜0.01),and were also improved in the SFN group(P＜0.05,P＜0.01).Conclusions PM2.5 exposures can exac-erbate IPF-induced IPF in mice,and the regulating of Nrf2/SLC7 A1 1/GPX4 axis and ferroptosis might be in-volved in the related mechanisms.

Objective:To establish a TaqMan-MGB probe-based method for detecting the polymorphic loci C677T and A1298C of the MTHFR gene.Methods:Specific primers and TaqMan-MGB probes targeting the C677T and A1298C polymorphic loci of the MTHFR gene were designed and optimized based on the gene sequence information.A real-time quantitative PCR detection system was established.Gradient dilution experiments were conducted to determine the limit of detection,and reproducibility experiments were performed to evaluate detection consistency.Specificity was validated using wild-type and mutant plasmid templates.The method was applied to detect 56 clinical samples,and its accuracy and practicality were assessed through comparison with traditional Sanger sequencing.Results:The TaqMan-MGB probe method demonstrated high specificity for detecting the C677T and A1298C loci,with no cross-reactivity between wild-type and mutant probes,enabling accurate genotype differentiation.Sensitivity experiments revealed detection limits of 1.13 × 103 copies/μL for C677T and 8.39 × 101 copies/μL for A1298C.Reproducibility experiments showed coefficients of variation below 1％,indicating stable and reliable results.Among the 56 clinical samples,the overall detection rate for the C677T locus was 86.99％,and for the A1298C locus,it was 97.92％.The TaqMan-MGB method exhibited good concordance with Sanger sequencing results.Conclusion:The TaqMan-MGB method exhibits high specificity,sensitivity,and excellent reproducibility in detecting the polymorphic loci C677T and A1298C of the MTHFR gene,making it suitable for rapid detection in large-scale clinical samples.This method provides an effective molecular diagnostic tool for the early diagnosis and prevention of folate-related diseases.

Objective:To investigate the anti-heart failure mechanism of N-acetylcysteine(NAC)in diabetic cardiomyop-athy independent from coronary artery factors.Methods:A total of 40 diabetic mice after heart failure model construction were randomly divided into two groups,NAC group(n=20,NAC 100mg·kg-1·d-1)and control group(n=20,Saline 100 mg·kg-1·d-1).Echocardiography was performed to detect left ventricular end-diastolic volume(LVEDV),left ventricular end-systolic volume(LVESV),left ventricular ejection fraction(LVEF),mitral left ventricular early-dias-tolic peak flow velocity/left ventricular late-diastolic peak flow velocity(E/A),isovolumic relaxation time(IVRT)and cardiac output(CO)after 4 weeks.Terminal uridine nick-end labeling(TUNEL)was performed to detect apoptosis in-dex,and Western Blot was performed to detect the expression of extracellular regulated protein kinases(ERK)1/2 after 6 weeks in two groups.Results:Compared to those in control group,mice in NAC group had significant higher LVEF[(40.5±3.4)％vs.(36.9±3.2)％],E/A[(1.5±0.1)vs.(1.4±0.1)]and CO[(10.3±0.6)ml/min vs.(9.9±0.5)ml/min](P＜0.05 or＜0.01);and significant lower LVESV[(23.1±1.3)μl vs.(24.7±1.5)μl],apoptosis index[(31.2±0.5)％vs.(45.1±0.9)％]and the expression of ERK1/2[(2.2±0.2)vs.(3.9±0.1)](P＜0.001 all).Conclusion:NAC exerts anti-heart failure effect by attenuating apoptosis of cardiomyocytes via regulating ERK1/2 pathway.