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 To explore a new model of intelligent medication education for pharmaceutical outpatient clinics by constructing dynamic HTML web pages through the DeepSeek-V3-0324 large-scale model. METHODS Clinical pharmacists integrated key clinical information such as patients’ basic information， medication history and medication precautions in real time， and generated a standardized medication education list through the DeepSeek-V3-0324 large-scale model and manual review. RESULTS The DeepSeek-V3-0324 large-scale model was applied in the pharmaceutical outpatient clinics to generate a personalized medication education list， which could effectively solve the disunity of pharmacy guidance caused by the lack of standardization of medication education and the difference of individualized experience of pharmacists in the traditional pharmaceutical outpatient clinics in the face of complex cases， and medication errors caused by forgetting or misremembering information among certain special patient populations after receiving medication education. CONCLUSIONS The transformation and application of artificial intelligence technology in pharmaceutical outpatient clinics is an innovation of pharmaceutical outpatient service means， which can provide patients with immediate and personalized medication education and improve the quality of pharmaceutical care. However， it is also necessary to face the lag of database update and the lack of risk management， as well as the lack of diversification of medication education lists.

This study aims to investigate the mechanism of Mahuang Lianqiao Chixiaodou Decoction(MHLQ) and its main active components in treating immunoglobin A nephropathy(IgAN). The rat model of IgAN was established by a combination of measures including gavage of bovine serum albumin, subcutaneous injection of carbon tetrachloride, and tail vein injection of lipopolysaccharide. The modeled rats were randomized into model, low-, medium-, and high-dose(1.773, 3.545, and 7.090 g·kg~(-1), respectively) MHLQ, phillyrin(PHI, 0.020 g·kg~(-1)), pseudoephedrine(PSE, 0.020 g·kg~(-1)), and losartan potassium(LP, 9.003 mg·kg~(-1)) groups, and Wistar rats were used as the control. Rats were administrated with corresponding drugs by gavage, and those in the control and model groups received an equal volume of normal saline. All the groups were treated for 4 consecutive weeks. Urine, serum, liver, and kidney samples were collected from rats in each group at the end of drug administration. The 24 h urine protein and renal function were examined, and staining was performed to observe the pathological changes in the renal tissue. The immunofluorescence assay was employed to detect the expression of IgA and complement C3/C3b/C3c in the renal tissue. Electron microscopy was employed to observe the ultrastructure of the renal tissue. Enzyme-linked immunosorbent assay was performed to determine the expression of complement C3 and sublytic C5b-9 in the serum and renal tissue. Western blot was performed to determine the expression levels of hepatic and renal complement C3/C3b/C3c, C5/C5a, C5b-9, and complement factor B(CFB). Immunohistochemistry(IHC) was employed to measure the expression of complement C3 in the renal tissue. The results showed that compared with the control group, the model group had elevated levels of blood urea nitrogen and serum creatinine, proliferation of glomerular mesangial cells and extracellular matrix, and glomerular deposition of IgA immune complexes or electron-dense material. In addition, the model group showcased increased serum C3 levels and up-regulated expression of CFB, C3/C3b/C3c, C5/C5a, and C5b-9 in the renal tissue and C3/C3b/C3c and C5b-9 in the hepatic tissue. After treatment with MHLQ and its active components, all of the above indexes were reversed. In conclusion, MHLQ and its active components can improve the renal function and reduce the deposition of immune complexes and pathological damage in the renal tissue of the rat model of IgAN by inhibiting the alternative pathway complement activation.
Animals ; Drugs, Chinese Herbal/administration & dosage* ; Glomerulonephritis, IGA/genetics* ; Rats ; Male ; Disease Models, Animal ; Rats, Wistar ; Complement Activation/drug effects* ; Kidney/immunology* ; Humans

This study aims to explore the mechanism of lung and gut protection by Tanreqing Capsules on the mice infected with influenza virus based on "the lung-gut axis". A total of 110 C57BL/6J mice were randomized into control group, model group, oseltamivir group, and low-and high-dose Tanreqing Capsules groups. Ten mice in each group underwent body weight protection experiments, and the remaining 12 mice underwent experiments for mechanism exploration. Mice were infected with influenza virus A/Puerto Rico/08/1934(PR8) via nasal inhalation for the modeling. The lung tissue was collected on day 3 after gavage, and the lung tissue, colon tissue, and feces were collected on day 7 after gavage for subsequent testing. The results showed that Tanreqing Capsules alleviated the body weight reduction and increased the survival rate caused by PR8 infection. Compared with model group, Tanreqing Capsules can alleviate the lung injury by reducing the lung index, alleviating inflammation and edema in the lung tissue, down-regulating viral gene expression at the late stage of infection, reducing the percentage of neutrophils, and increasing the percentage of T cells. Tanreqing Capsules relieved the gut injury by restoring the colon length, increasing intestinal lumen mucin secretion, alleviating intestinal inflammation, and reducing goblet cell destruction. The gut microbiota analysis showed that Tanreqing Capsules increased species diversity compared with model group. At the phylum level, Tanreqing Capsules significantly increased the abundance of Firmicutes and Actinobacteria, while reducing the abundance of Bacteroidota and Proteobacteria to maintain gut microbiota balance. At the genus level, Tanreqing Capsules significantly increased the abundance of unclassified＿f＿Lachnospiraceae while reducing the abundance of Bacteroides, Eubacterium, and Phocaeicola to maintain gut microbiota balance. In conclusion, Tanreqing Capsules can alleviate mouse lung and gut injury caused by influenza virus infection and restore the balance of gut microbiota. Treating influenza from the lung and gut can provide new ideas for clinical practice.
Animals ; Drugs, Chinese Herbal/administration & dosage* ; Mice ; Lung/metabolism* ; Mice, Inbred C57BL ; Capsules ; Orthomyxoviridae Infections/virology* ; Gastrointestinal Microbiome/drug effects* ; Male ; Humans ; Female ; Influenza A virus/physiology* ; Influenza, Human/virology*

This study aimed to investigate the effect and mechanism of Buyang Huanwu Decoction in regulating endoplasmic reticulum stress via the inositol-requiring enzyme 1α(IRE1α)/apoptosis signal-regulating kinase 1(ASK1)/c-Jun N-terminal kinase(JNK) pathway to improve neurological function in rats with cerebral ischemia/reperfusion injury(CIRI). SPF-grade male sprague-dawley(SD) rats were randomly divided into Sham group, model group, Buyang Huanwu Decoction group, and edaravone group. Except for the Sham group, the other groups were subjected to the modified suture method to establish a middle cerebral artery occlusion/reperfusion(MCAO/R) model. After treatment, neurological function was assessed using the Zea Longa scoring system. Gait analysis was used to detect the motor function. Detection of relative infarct area in brain tissue using 2,3,5-triphenyltetrazolium chloride(TTC) staining. Nissl staining was used to observe the structure of neuronal cells. Western blot and real-time fluorescence quantitative PCR(RT-qPCR) were used to detect IRE1α, ASK1, JNK, B cell lymphoma-2(Bcl-2), Bcl-2 related X protein(Bax), and Caspase-3 in the brain tissue. Immunohistochemistry was used to detect the positive expression of IRE1α, ASK1, and JNK. Immunofluorescence was used to detect the fluorescence expression levels of Bax, Bcl-2, and Caspase-3. The results showed that compared with the Sham group, the model group exhibited increased neurological scores(P<0.01), increased ratio of ground contact area and strength in both forelimbs(P<0.01), enlarged relative infarct area of brain tissue(P<0.05), and a reduced number of Nissl staining-positive cells(P<0.01). The protein and mRNA expression levels of IRE1α, ASK1, JNK, Bax, and Caspase-3 in brain tissue were significantly elevated, while those of Bcl-2 were decreased(P<0.05). Compared with the model group, both the Buyang Huanwu Decoction group and edaravone group showed reduced neurological scores(P<0.05), decreased ratio of ground contact area and strength in both forelimbs(P<0.05), smaller relative infarct area(P<0.05), alleviated neuronal damage, and increased number of Nissl staining-positive cells(P<0.05). The expression levels of IRE1α, ASK1, JNK, Bax, and Caspase-3 protein and mRNA in brain tissue were significantly reduced, while those of Bcl-2 were significantly increased(P<0.05). The results indicated that Buyang Huanwu Decoction can effectively improve brain injury in CIRI rats, and its mechanism of action may be related to regulating the endoplasmic reticulum stress IRE1α/ASK1/JNK signaling pathway.
Animals ; Male ; Rats, Sprague-Dawley ; Protein Serine-Threonine Kinases/genetics* ; Drugs, Chinese Herbal/administration & dosage* ; Rats ; MAP Kinase Kinase Kinase 5/genetics* ; Ischemic Stroke/physiopathology* ; Humans ; MAP Kinase Signaling System/drug effects* ; Apoptosis/drug effects* ; Endoribonucleases/genetics* ; JNK Mitogen-Activated Protein Kinases/genetics* ; Endoplasmic Reticulum Stress/drug effects* ; Multienzyme Complexes

This study aims to explore the intervention effects of isorhamnetin(Isor) on acute lung injury(ALI) and its regulatory effects on pyroptosis mediated by the NOD-like receptor family pyrin domain containing 3(NLRP3)/apoptosis-associated speck-like protein containing a CARD(ASC)/cysteine aspartate-specific protease-1(caspase-1) axis. In the in vivo experiments, 60 BALB/c mice were divided into five groups. Except for the control group, the other groups were administered Isor by gavage 1 hour before intratracheal instillation of LPS to induce ALI, and tissues were collected after 12 hours. In the in vitro experiments, RAW264.7 cells were divided into five groups. Except for the control group, the other groups were pretreated with Isor for 2 hours before LPS stimulation and subsequent assessments. Hematoxylin-eosin(HE) staining was used to observe pathological changes in lung tissue, while lung swelling, protein levels in bronchoalveolar lavage fluid(BALF), and myeloperoxidase(MPO) levels in lung tissue were measured. Cell proliferation toxicity and viability were assessed using the cell counting kit-8(CCK-8) method. Enzyme-linked immunosorbent assay(ELISA) was used to detect the levels of interleukin-1β(IL-1β), IL-6, IL-18, and tumor necrosis factor-α(TNF-α). Protein levels of NLRP3, ASC, cleaved caspase-1, and the N-terminal fragment of gasdermin D(GSDMD-N) were evaluated using immunohistochemistry, immunofluorescence, and Western blot. The results showed that in the in vivo experiments, Isor significantly improved pathological damage in lung tissue, reduced lung swelling, protein levels in BALF, MPO levels in lung tissue, and levels of inflammatory cytokines such as IL-1β, IL-6, IL-18, and TNF-α, and inhibited the high expression of the NLRP3/ASC/caspase-1 axis and the pyroptosis core gene GSDMD-N. In the in vitro experiments, the safe dose of Isor was determined through cell proliferation toxicity assays. Isor reduced cell death and inhibited the expression levels of the NLRP3/ASC/caspase-1 axis, GSDMD-N, and inflammatory cytokines. In conclusion, Isor may alleviate ALI by modulating pyroptosis mediated by the NLRP3/ASC/caspase-1 axis.
Animals ; Pyroptosis/drug effects* ; NLR Family, Pyrin Domain-Containing 3 Protein/genetics* ; Acute Lung Injury/physiopathology* ; Mice ; Mice, Inbred BALB C ; Quercetin/pharmacology* ; Caspase 1/genetics* ; CARD Signaling Adaptor Proteins/genetics* ; Male ; RAW 264.7 Cells ; Humans ; Lung/metabolism*

OBJECTIVE: To investigate chronic hepatitis C virus (HCV) infection's effect on gestational liver function, pregnancy and delivery complications, and neonatal development. METHODS: A total of 157 HCV antibody-positive (anti-HCV[+]) and HCV RNA(+) patients (Group C) and 121 anti-HCV(+) and HCV RNA(-) patients (Group B) were included as study participants, while 142 anti-HCV(-) and HCV RNA(-) patients (Group A) were the control group. Data on biochemical indices during pregnancy, pregnancy complications, delivery-related information, and neonatal complications were also collected. RESULTS: Elevated alanine aminotransferase (ALT) rates in Group C during early, middle, and late pregnancy were 59.87%, 43.95%, and 42.04%, respectively-significantly higher than Groups B (26.45%, 15.70%, 10.74%) and A (23.94%, 19.01%, 6.34%) ( P < 0.05). Median ALT levels in Group C were significantly higher than in Groups A and B at all pregnancy stages ( P < 0.05). No significant differences were found in neonatal malformation rates across groups ( P > 0.05). However, neonatal jaundice incidence was significantly greater in Group C (75.16%) compared to Groups A (42.25%) and B (57.02%) ( χ ² = 33.552, P < 0.001). HCV RNA positivity during pregnancy was an independent risk factor for neonatal jaundice ( OR = 2.111, 95% CI 1.242-3.588, P = 0.006). CONCLUSIONS Chronic HCV infection can affect the liver function of pregnant women, but does not increase the pregnancy or delivery complication risks. HCV RNA(+) is an independent risk factor for neonatal jaundice.
Humans ; Female ; Pregnancy ; Adult ; Pregnancy Complications, Infectious/epidemiology* ; Retrospective Studies ; Pregnancy Outcome ; Infant, Newborn ; Viremia/virology* ; Hepatitis C ; Hepacivirus/physiology* ; Hepatitis C, Chronic/virology* ; Young Adult ; Alanine Transaminase/blood*

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*