[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。

ObjectivePrimary liver cancer, predominantly hepatocellular carcinoma (HCC), is a significant global health issue, ranking as the sixth most diagnosed cancer and the third leading cause of cancer-related mortality. Accurate and early diagnosis of HCC is crucial for effective treatment, as HCC and non-HCC malignancies like intrahepatic cholangiocarcinoma (ICC) exhibit different prognoses and treatment responses. Traditional diagnostic methods, including liver biopsy and contrast-enhanced ultrasound (CEUS), face limitations in applicability and objectivity. The primary objective of this study was to develop an advanced, light-weighted classification network capable of distinguishing HCC from other non-HCC malignancies by leveraging the automatic analysis of brightness changes in CEUS images. The ultimate goal was to create a user-friendly and cost-efficient computer-aided diagnostic tool that could assist radiologists in making more accurate and efficient clinical decisions. MethodsThis retrospective study encompassed a total of 161 patients, comprising 131 diagnosed with HCC and 30 with non-HCC malignancies. To achieve accurate tumor detection, the YOLOX network was employed to identify the region of interest (ROI) on both B-mode ultrasound and CEUS images. A custom-developed algorithm was then utilized to extract brightness change curves from the tumor and adjacent liver parenchyma regions within the CEUS images. These curves provided critical data for the subsequent analysis and classification process. To analyze the extracted brightness change curves and classify the malignancies, we developed and compared several models. These included one-dimensional convolutional neural networks (1D-ResNet, 1D-ConvNeXt, and 1D-CNN), as well as traditional machine-learning methods such as support vector machine (SVM), ensemble learning (EL), k-nearest neighbor (KNN), and decision tree (DT). The diagnostic performance of each method in distinguishing HCC from non-HCC malignancies was rigorously evaluated using four key metrics: area under the receiver operating characteristic (AUC), accuracy (ACC), sensitivity (SE), and specificity (SP). ResultsThe evaluation of the machine-learning methods revealed AUC values of 0.70 for SVM, 0.56 for ensemble learning, 0.63 for KNN, and 0.72 for the decision tree. These results indicated moderate to fair performance in classifying the malignancies based on the brightness change curves. In contrast, the deep learning models demonstrated significantly higher AUCs, with 1D-ResNet achieving an AUC of 0.72, 1D-ConvNeXt reaching 0.82, and 1D-CNN obtaining the highest AUC of 0.84. Moreover, under the five-fold cross-validation scheme, the 1D-CNN model outperformed other models in both accuracy and specificity. Specifically, it achieved accuracy improvements of 3.8% to 10.0% and specificity enhancements of 6.6% to 43.3% over competing approaches. The superior performance of the 1D-CNN model highlighted its potential as a powerful tool for accurate classification. ConclusionThe 1D-CNN model proved to be the most effective in differentiating HCC from non-HCC malignancies, surpassing both traditional machine-learning methods and other deep learning models. This study successfully developed a user-friendly and cost-efficient computer-aided diagnostic solution that would significantly enhances radiologists’ diagnostic capabilities. By improving the accuracy and efficiency of clinical decision-making, this tool has the potential to positively impact patient care and outcomes. Future work may focus on further refining the model and exploring its integration with multimodal ultrasound data to maximize its accuracy and applicability.

This study aims to explore the mechanism of Jiaotai Pills in treating depression based on metabolomics and network pharmacology. The chemical constituents of Jiaotai Pills were identified by UHPLC-Orbitrap Exploris 480, and the targets of Jiaotai Pills and depression were retrieved from online databases. STRING and Cytoscape 3.7.2 were used to construct the protein-protein interaction network of core targets of Jiaotai Pills in treating depression and the "compound-target-pathway" network. DAVID was used for Gene Ontology(GO) function and Kyoto Encyclopedia of Genes and Genomes(KEGG) pathway enrichment analyses of the core targets. The mouse model of depression was established with chronic unpredictable mild stress(CUMS) and treated with different doses of Jiaotai Pills. The behavioral changes and pathological changes in the hippocampus were observed. UHPLC-Orbitrap Exploris 120 was used for metabolic profiling of the serum, from which the differential metabolites and related metabolic pathways were screened. A "metabolite-reaction-enzyme-gene" network was constructed for the integrated analysis of metabolomics and network pharmacology. A total of 34 chemical components of Jiaotai Pills were identified, and 143 core targets of Jiaotai Pills in treating depression were predicted, which were mainly involved in the arginine and proline, sphingolipid, and neurotrophin metabolism signaling pathways. The results of animal experiments showed that Jiaotai Pills alleviated the depression behaviors and pathological changes in the hippocampus of the mouse model of CUMS-induced depression. In addition, Jiaotai Pills reversed the levels of 32 metabolites involved in various pathways such as arginine and proline metabolism, sphingolipid metabolism, and porphyrin metabolism in the serum of model mice. The integrated analysis showed that arginine and proline metabolism, cysteine and methionine metabolism, and porphyrin metabolism might be the key pathways in the treatment of depression with Jiaotai Pills. In conclusion, metabolomics combined with network pharmacology clarifies the antidepressant mechanism of Jiaotai Pills, which may provide a basis for the clinical application of Jiaotai Pills in treating depression.
Animals ; Drugs, Chinese Herbal/chemistry* ; Depression/genetics* ; Mice ; Network Pharmacology ; Metabolomics ; Male ; Disease Models, Animal ; Humans ; Protein Interaction Maps/drug effects* ; Antidepressive Agents

OBJECTIVE: To illustrate the role of dehydrocorydaline (DHC) in chronic constriction injury (CCI)-induced neuropathic pain and the underlying mechanism. METHODS: C57BL/6J mice were randomly divided into 3 groups by using a random number table, including sham group (sham operation), CCI group [intrathecal injection of 10% dimethyl sulfoxide (DMSO)], and CCI+DHC group (intrathecal injection of DHC), 8 mice in each group. A CCI mouse model was conducted to induce neuropathic pain through ligating the right common sciatic nerve. On day 14 after CCI modeling or sham operation, mice were intrathecal injected with 5 µL of 10% DMSO or 10 mg/kg DHC (5 µL) into the 5th to 6th lumbar intervertebral space (L5-L6). Pregnant ICR mice were sacrificed for isolating primary spinal neurons on day 14 of embryo development for in vitro experiment. Pain behaviors were evaluated by measuring the paw withdrawal mechanical threshold (PWMT) of mice. Immunofluorescence was used to observe the activation of astrocytes and microglia in mouse spinal cord. Protein expressions of inducible nitric oxide synthase (iNOS), tumor necrosis factor alpha (TNF-α), interleukin 6 (IL-6), phosphorylation of N-methyl-D-aspartate receptor subunit 2B (p-NR2B), and NR2B in the spinal cord or primary spinal neurons were detected by Western blot. RESULTS: In CCI-induced neuropathic pain model, mice presented significantly decreased PWMT, activation of glial cells, overexpressions of iNOS, TNF-α, IL-6, and higher p-NR2B/NR2B ratio in the spinal cord (P<0.05 or P<0.01), which were all reversed by a single intrathecal injection of DHC (P<0.05 or P<0.01). The p-NR2B/NR2B ratio in primary spinal neurons were also inhibited after DHC treatment (P<0.05). CONCLUSION An intrathecal injection of DHC relieved CCI-induced neuropathic pain in mice by inhibiting the neuroinflammation and neuron hyperactivity.
Animals ; Neuralgia/etiology* ; Mice, Inbred C57BL ; Analgesics/pharmacology* ; Neuroinflammatory Diseases/pathology* ; Constriction ; Male ; Receptors, N-Methyl-D-Aspartate/metabolism* ; Nitric Oxide Synthase Type II/metabolism* ; Mice, Inbred ICR ; Microglia/pathology* ; Spinal Cord/drug effects* ; Female ; Mice ; Tumor Necrosis Factor-alpha/metabolism* ; Disease Models, Animal ; Constriction, Pathologic/complications* ; Interleukin-6/metabolism* ; Astrocytes/metabolism* ; Chronic Disease ; Neurons/metabolism*

Objective:To explore the factors influencing adherence to voice therapy among patients with voice disorders in China. Methods:Patients with voice disorders who visited the Voice Therapy Center at Sun Yat-sen Memorial Hospital, Sun Yat-sen University, from February to May 2022 were enrolled in the study. Adherence was assessed using the URICA-Voice scale, while influencing factors were assessed through the Voice Handicap Index（VHI） scale and a general information questionnaire. Correlation analysis was conducted using univariate and multivariate logistic regression analysis. Results:A total of 247 patients were included in the study, comprising 57 males（23.08%） and 190 females（76.92%）. The results revealed that: ①Female patients demonstrated higher likelihood of being in the contemplation stage（OR=0.22） compared to males. ②Patients with a monthly family income per capita>6 000 yuan were more likely to be in the contemplation stage than those with<3 000 yuan with an OR = 13.94. ③High vocal-demand occupations increased contemplation stage probability（OR=7.70） compared to moderate-demand occupations. ④Residence within 30-minute commute predicted action/maintenance stages（OR=7.14） versus≥60-minute commute. ⑤Patients whose occupations had high voice demands were more likely to be in the action and maintenance stages than those with average voice demands, with an OR of 16.20. Conclusion:Gender, monthly family income per capita, occupational voice demands, and distance to the hospital significantly impact the URICA-Voice compliance stages of patients. Patients who are female, have higher family income, have occupations with high voice demands, and live closer to the hospital exhibit higher compliance with voice training.
Humans ; Male ; Female ; Voice Disorders/therapy* ; Patient Compliance ; Voice Training ; Surveys and Questionnaires ; China ; Middle Aged ; Adult ; Voice Quality ; Logistic Models ; Aged

Alzheimer's disease (AD) is the major form of dementia in the elderly and is closely related to the toxic effects of microglia sustained activation. In AD, sustained microglial activation triggers impaired synaptic pruning, neuroinflammation, neurotoxicity, and cognitive deficits. Accumulating evidence has demonstrated that aberrant expression of deubiquitinating enzymes is associated with regulating microglia function. Here, we use RNA sequencing to identify a deubiquitinase YOD1 as a regulator of microglial function and AD pathology. Further study showed that YOD1 knockout significantly improved the migration, phagocytosis, and inflammatory response of microglia, thereby improving the cognitive impairment of AD model mice. Through LC-MS/MS analysis combined with Co-IP, we found that Myosin heavy chain 9 (MYH9), a key regulator maintaining microglia homeostasis, is an interacting protein of YOD1. Mechanistically, YOD1 binds to MYH9 and maintains its stability by removing the K48 ubiquitin chain from MYH9, thereby mediating the microglia polarization signaling pathway to mediate microglia homeostasis. Taken together, our study reveals a specific role of microglial YOD1 in mediating microglia homeostasis and AD pathology, which provides a potential strategy for targeting microglia to treat AD.

This study investigated the role of the nuclear factor of activated T cells c3 (NFATc3) in vascular smooth muscle cells (VSMCs) during aortic aneurysm and dissection (AAD) progression and the underlying molecular mechanisms. Cytoplasmic and nuclear NFATc3 levels were elevated in human and mouse AAD. VSMC-NFATc3 deletion reduced thoracic AAD (TAAD) and abdominal aortic aneurysm (AAA) progression in mice, contrary to VSMC-NFATc3 overexpression. VSMC-NFATc3 deletion reduced extracellular matrix (ECM) degradation and maintained the VSMC contractile phenotype. Nuclear NFATc3 targeted and transcriptionally upregulated matrix metalloproteinase 9 (MMP9) and MMP2, promoting ECM degradation and AAD development. NFATc3 promoted VSMC phenotypic switching by binding to eukaryotic elongation factor 2 (eEF2) and inhibiting its phosphorylation in the VSMC cytoplasm. Restoring eEF2 reversed the beneficial effects in VSMC-specific NFATc3-knockout mice. Cabamiquine-targets eEF2 and inhibits protein synthesis-inhibited AAD development and progression in VSMC-NFATc3-overexpressing mice. VSMC-NFATc3 promoted VSMC switch and ECM degradation while exacerbating AAD development, making it a novel potential therapeutic target for preventing and treating AAD.