[摘 要] 目的：探讨异位表达血红蛋白亚基（HBA/HBB）对缺氧条件下嵌合抗原受体T细胞（CAR-T细胞）功能障碍的改善作用及其对肿瘤细胞的杀伤效应。方法：全基因合成技术合成靶向HER2的CAR序列，构建共表达HBA或HBB的CAR慢病毒载体，包装慢病毒后感染人原代T淋巴细胞，制备异位表达HBA/HBB的CAR-T细胞，命名为HBA CAR-T和HBB CAR-T。采用缺氧探针检测小鼠实体瘤缺氧状态。通过流式细胞术检测瘤内CAR-T细胞占比、异位表达血红蛋白亚基的CAR-T细胞阳性率及CAR-T细胞的活性氧、凋亡水平。WB法检测HBA CAR-T和HBB CAR-T内相关血红蛋白亚基表达情况，采用细胞计数板计数检测细胞增殖水平，通过萤光素酶报告基因法检测CAR-T细胞对肿瘤细胞的杀伤能力，qPCR检测CAR-T细胞中缺氧诱导因子-1α（HIF-1α）表达水平，利用MitoXpress Intra试剂盒检测CAR-T细胞内氧气含量。结果：不同细胞构建的实体瘤模型均存在明显缺氧情况，且CAR-T细胞浸润水平与缺氧程度呈显著负相关（P < 0.000 1）。HBA CAR-T与HBB CAR-T构建成功（阳性率 > 60%），相应血红蛋白亚基可稳定表达。缺氧环境下HBA CAR-T和HBB CAR-T的ROS水平、凋亡水平显著下降，增殖、对肿瘤细胞的体外杀伤能力显著强于传统CAR-T细胞（均P < 0.05）。HBA CAR-T与HBB CAR-T内HIF-1α表达降低（均P < 0.001），且缺氧程度显著降低（均P < 0.001）。结论：异位表达血红蛋白亚基可改善缺氧条件下CAR-T细胞功能障碍并增强其对肿瘤细胞的体外杀伤作用。

[摘 要] 目的：探究重楼皂苷Ⅱ（PPⅡ）抑制甲状腺癌（TC）恶性生物学行为的分子机制。方法：常规培养甲状腺癌细胞TPC1，实验分为sh-NC、sh-可溶性半乳糖凝集素3（sh-LGALS3）、OE-NC、OE-LGALS3和 OE-LGALS3 + PPⅡ组，用转染试剂将应用质粒转染至各组TPC1细胞中。qPCR法检测TPC1细胞中LGALS3 mRNA的表达，WB法检测各组TPC1细胞中LGALS3、PI3K/AKT信号通路相关蛋白的表达，CCK-8法、Transwell实验、划痕愈合实验和流式细胞术分别检测各组TPC1细胞增殖、迁移和侵袭能力，以及细胞凋亡情况。结果：PPⅡ抑制TPC1细胞的增殖、迁移和侵袭，并诱导其凋亡（均P < 0.000 1）。数据库数据分析显示LGALS3在甲状腺癌组织中高表达（P < 0.001）且是PPⅡ的靶基因。LGALS1在TPC1细胞中呈高表达（P < 0.000 1），敲减LGALS3抑制TPC1细胞的恶性生物学行为，并促进其凋亡（均P < 0.000 1），PPⅡ通过抑制LGALS3 mRNA和蛋白的表达（P < 0.01或P < 0.001）从而抑制TPC1细胞的恶性生物学行为（P < 0.01或P < 0.000 1），PPⅡ抑制LGALS3表达抑制PI3K/AKT信号通路的激活水平（P <0.001或P <0.000 1），LGALS3通过PI3K/AKT信号通路促进TPC1细胞的恶性生物行为（P < 0.000 1）。结论：PPⅡ通过抑制TPC1细胞中LGALS3的表达，缓解PI3K/AKT信号通路的过度激活从而发挥抑癌作用。

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.

Monotropein is a compound classified into iridoid which is found in herbaceous plants Morindae officinalis. It possesses anti-inflammatory, antioxidant, and anti-osteoarthritic activities. Previous study indicates that monotropein may have the potential to combat cardiovascular disease, although the related mechanism remains unclear. In this study, we constructed the model of atherosclerosis by oxidized low density lipoprotein-induced vascular smooth muscle cells and LDLR –/–mice given high-fat diet to investigate the effects of monotropein on atherosclerosis.Our results showed that monotropein treatment significantly reduced the area of atherosclerotic plaques and necrotic cores in mice, inhibited the proliferation and migration of vascular smooth muscle cells, and reduced inflammatory responses and oxidative stress, which in turn alleviated atherosclerosis. In addition, we found that monotropein reduced the expression levels of P-NF-κB and P-AP-1. In conclusion, our data suggest that monotropein inhibited the proliferation and migration of vascular smooth muscle cells by mediating the activity of NF-κB, AP-1, reducing the level of inflammation and oxidative stress, and thus resisting the development of atherosclerosis. These findings demonstrate the efficacious therapeutic impact of monotropein on atherosclerosis and elucidate its specific target.

Metabolites produced as intermediaries or end-products of microbial metabolism provide crucial signals for health and diseases, such as metabolic dysfunction-associated steatotic liver disease (MASLD). These metabolites include products of the bacterial metabolism of dietary substrates, modification of host molecules (such as bile acids [BAs], trimethylamine-N-oxide, and short-chain fatty acids), or products directly derived from bacteria. Recent studies have provided new insights into the association between MASLD and the risk of developing chronic kidney disease (CKD). Furthermore, alterations in microbiota composition and metabolite profiles, notably altered BAs, have been described in studies investigating the association between MASLD and the risk of CKD. This narrative review discusses alterations of specific classes of metabolites, BAs, fructose, vitamin D, and microbiota composition that may be implicated in the link between MASLD and CKD.

Monotropein is a compound classified into iridoid which is found in herbaceous plants Morindae officinalis. It possesses anti-inflammatory, antioxidant, and anti-osteoarthritic activities. Previous study indicates that monotropein may have the potential to combat cardiovascular disease, although the related mechanism remains unclear. In this study, we constructed the model of atherosclerosis by oxidized low density lipoprotein-induced vascular smooth muscle cells and LDLR –/–mice given high-fat diet to investigate the effects of monotropein on atherosclerosis.Our results showed that monotropein treatment significantly reduced the area of atherosclerotic plaques and necrotic cores in mice, inhibited the proliferation and migration of vascular smooth muscle cells, and reduced inflammatory responses and oxidative stress, which in turn alleviated atherosclerosis. In addition, we found that monotropein reduced the expression levels of P-NF-κB and P-AP-1. In conclusion, our data suggest that monotropein inhibited the proliferation and migration of vascular smooth muscle cells by mediating the activity of NF-κB, AP-1, reducing the level of inflammation and oxidative stress, and thus resisting the development of atherosclerosis. These findings demonstrate the efficacious therapeutic impact of monotropein on atherosclerosis and elucidate its specific target.

Monotropein is a compound classified into iridoid which is found in herbaceous plants Morindae officinalis. It possesses anti-inflammatory, antioxidant, and anti-osteoarthritic activities. Previous study indicates that monotropein may have the potential to combat cardiovascular disease, although the related mechanism remains unclear. In this study, we constructed the model of atherosclerosis by oxidized low density lipoprotein-induced vascular smooth muscle cells and LDLR –/–mice given high-fat diet to investigate the effects of monotropein on atherosclerosis.Our results showed that monotropein treatment significantly reduced the area of atherosclerotic plaques and necrotic cores in mice, inhibited the proliferation and migration of vascular smooth muscle cells, and reduced inflammatory responses and oxidative stress, which in turn alleviated atherosclerosis. In addition, we found that monotropein reduced the expression levels of P-NF-κB and P-AP-1. In conclusion, our data suggest that monotropein inhibited the proliferation and migration of vascular smooth muscle cells by mediating the activity of NF-κB, AP-1, reducing the level of inflammation and oxidative stress, and thus resisting the development of atherosclerosis. These findings demonstrate the efficacious therapeutic impact of monotropein on atherosclerosis and elucidate its specific target.

Metabolites produced as intermediaries or end-products of microbial metabolism provide crucial signals for health and diseases, such as metabolic dysfunction-associated steatotic liver disease (MASLD). These metabolites include products of the bacterial metabolism of dietary substrates, modification of host molecules (such as bile acids [BAs], trimethylamine-N-oxide, and short-chain fatty acids), or products directly derived from bacteria. Recent studies have provided new insights into the association between MASLD and the risk of developing chronic kidney disease (CKD). Furthermore, alterations in microbiota composition and metabolite profiles, notably altered BAs, have been described in studies investigating the association between MASLD and the risk of CKD. This narrative review discusses alterations of specific classes of metabolites, BAs, fructose, vitamin D, and microbiota composition that may be implicated in the link between MASLD and CKD.

BACKGROUND:Electromyographic biofeedback therapy has demonstrated unique advantages of non-invasive,real-time feedback,personalized treatment and promotion of neuroplasticity,and can promote the recovery of motor function in patients with spinal cord injury.OBJECTIVE:To review the current application status and therapeutic effects of electromyographic biofeedback combined with exercise therapy,robotic exoskeletons,and virtual reality technology in the recovery of motor function after spinal cord injury.METHODS:Relevant literature was retrieved from CNKI and PubMed databases up to May 2024.The search terms included"spinal cord injury,EMG biofeedback,physical therapy,robotic exoskeleton,VR,motor function,exercise"in both English and Chinese.Finally,71 articles were included for review.RESULTS AND CONCLUSION:Mechanisms by which electromyographic biofeedback therapy promotes spinal cord injury rehabilitation include promoting neural plasticity changes,strengthening neuromuscular connections and improving movement patterns.Electromyographic biofeedback,as an emerging tool for treating spinal cord injury,is often used in conjunction with other therapeutic methods,including exercise therapy,robotic exoskeletons,and VR,to promote the recovery of motor function after spinal cord injury.The effectiveness of combination therapy has been significantly improved.However,there are still some problems and challenges,such as the lack of detailed analysis of the mechanism,the lack of large-scale trials that provide strong evidence for combined efficacy,and the limited adaptability of the technology.Future research can focus on these aspects:to improve the personalization and accuracy of electromyographic biofeedback;to develop new rehabilitation equipment and expand the application areas of electromyographic biofeedback combined with more advanced technologies or engineering equipment;to apply electromyographic biofeedback to gait training systems,respiratory training systems,and limb-linkage rehabilitation systems,so as to improve the accuracy of the feedback and the effect of personalized treatment plans.At the same time,the ease of use and comfort of the equipment will be improved.