OBJECTIVE To study the improvement effect and mechanism of Tripterygium wilfordii multiglucoside （TWM） on nephrotic syndrome in rats. METHODS The nephrotic syndrome model was established by intravenous injection of adriamycin via the tail vein. The modeling rats were randomly divided into the model group （distilled water）， prednisone group （10 mg/kg）， and TWM high- and low-dose groups （10 and 5 mg/kg， respectively）. Additionally， blank group （distilled water） without model induction was established. Each group consisted of 9 rats. Rats in each group were administered the corresponding drugs or distilled water by gavage， once a day， for 6 consecutive weeks. The histopathological morphology of kidney tissues in rats was observed； the levels of 24-hour urinary protein （24 h-UTP） and serum biochemical indicators [albumin （ALB）， blood urea nitrogen （BUN）， serum creatinine （SCr）， cholesterol （CHOL）， and triglyceride （TG）] in rats were determined； the levels of oxidative stress indicators [superoxide dismutase （SOD）， malondialdehyde （MDA）] in kidney tissue of rats were determined； expressions of hypoxia-inducible factor-1α （HIF-1α）/microRNA-155-5p （miR-155-5p）/nuclear factor erythriod 2- related factor 2 （Nrf2） signaling pathway-related mRNA and protein in the renal tissues of rats were detected. RESULTS Compared with the blank group， the rats in the model group exhibited disordered renal tissue structure， with a small amount of glomerular necrosis and edema of the renal tubular epithelial cells. 24 h-UTP， serum levels of SCr， BUN， CHOL and TG， MDA content， mRNA and protein expressions of HIF-1α and Keap1 as well as the expression of miR-155-5p in renal tissues were increased significantly （ P ＜0.05）. Serum level of ALB， SOD level in renal tissue as well as mRNA and protein expressions of Nrf2 were decreased significantly （ P ＜0.05）. Compared with the model group， TWM high-dose and low-dose groups exhibited significant improvements in renal injury， with notable reversals in the levels of the above quantitative indicators （ P ＜0.05）. CONCLUSIONS TWM can alleviate oxidative stress-induced damage and thereby improve nephrotic syndrome in rats by regulating the HIF-1α/miR-155-5p/Nrf2 signaling pathway.

OBJECTIVE To construct a predictive model for evaluating the efficacy of a triple antiemetic regimen （neurokinin- 1 receptor antagonist+5-hydroxytryptamine 3 receptor antagonist+dexamethasone） for preventing nausea and vomiting induced by highly emetogenic chemotherapy （HEC） based on interpretable deep learning algorithms. METHODS Clinical data of cancer patients who received HEC and were treated with the standard triple antiemetic regimen in the oncology department of Tianjin Medical University General Hospital from January 2018 to December 2022 were collected retrospectively. Demographic， clinical and metabolism-related variables were integrated. After data pre-processing， two deep learning algorithms （deep random forest and dense neural network） and four machine learning algorithms （support vector machine， categorical boosting， random forest and decision tree） were used to build predictive models. Subsequently， model performance evaluation and model interpretability analysis were conducted. RESULTS Among the six candidate models， the deep random forest model demonstrated the best predictive performance on the test set， with an area under the receiver operating characteristic curve of 0.850， an accuracy of 0.911， a precision of 0.805， a recall of 0.783， an F1 score of 0.793， and a Brier score of 0.075. Interpretability analysis revealed that creatinine clearance rate （Ccr） was the key predictive factor， and low Ccr levels， female gender， younger age， highly emetogenic drugs （particularly cisplatin-containing chemotherapy regimens）， and anticipatory nausea and vomiting were positively correlated with the risk of HEC-related nausea and vomiting. CONCLUSIONS The deep random forest model exhibits the best performance in predicting the efficacy of triple antiemetic regimen for preventing HEC-related nausea and vomiting. The key predictors in this model primarily include Ccr，anticipatory nausea and vomiting， gender， age， and highly emetogenic drugs.

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.

Plant-derived extracellular vesicles (PDEVs) are nanoscale extracellular vesicles secreted by plant cells, characterized by a lipid bilayer structure. These vesicles carry a variety of bioactive molecules, including proteins, nucleic acids, and lipids, and play essential roles in intercellular communication and physiological regulation in plants. Compared to animal-derived extracellular vesicles, PDEVs offer several advantages, such as a broad range of sources, high biocompatibility, low immunogenicity, and low production costs. Furthermore, PDEVs have demonstrated remarkable potential as natural nanocarriers for drug delivery, due to their ability to efficiently traverse biological barriers, such as the blood-brain barrier, making them promising candidates for drug delivery systems. This review systematically elaborates on the complex composition of PDEVs, which consists of lipids, proteins, and nucleic acids, the typical structural characteristics of their lipid bilayers ranging from 30 to 150 nm, and their versatile loading capabilities as drug carriers, efficiently encapsulating various types of therapeutic agents such as hydrophilic small molecules, hydrophobic drugs, nucleic acids, and proteins. We systematically summarize the recent advancements in strategies for enhancing the loading efficiency of PDEVs, which include methods such as co-incubation, ultrasound-assisted loading, electroporation, freeze-thaw cycles, and microfluidic technology. These techniques are evaluated based on their underlying principles, suitable drug types, and their respective advantages. In addition to loading strategies, we focus on the engineered approaches to achieve targeted delivery using PDEVs, such as genetic engineering modifications, chemical ligand conjugation, membrane fusion technology, and polyethylene glycol (PEG) modification. We discuss the mechanisms of these strategies in enhancing targeting efficiency, prolonging in vivo circulation time, and improving therapeutic efficacy. Further, this review highlights the application of PDEVs in various disease models, including tumor, skin inflammation, metabolic disorders, and neurodegenerative diseases, showcasing their therapeutic potential as multifunctional delivery platforms. The ability of PDEVs to encapsulate diverse therapeutic agents and target specific tissues or cells opens up new avenues for the treatment of complex diseases, offering advantages over conventional drug delivery systems. However, despite the promising applications of PDEVs, several challenges remain in their development and clinical translation. These challenges include variability in source materials, standardization of preparation processes, quality control, scalability of production, and the need for clinical validation. To overcome these obstacles, the integration of advanced technologies such as artificial intelligence-assisted design and multi-omics analysis is proposed as a way to facilitate the precise development of PDEVs. These emerging technologies hold the potential to further enhance the precision and effectiveness of plant-based drug delivery systems, ultimately advancing the field of precision medicine. In conclusion, the use of PDEVs as a platform for drug delivery represents a promising area of research with the potential to revolutionize therapeutic strategies. Their ability to encapsulate and deliver a wide variety of bioactive molecules, along with their inherent advantages in biocompatibility and versatility, makes them a valuable tool in the development of more efficient and targeted therapeutic interventions. Continued research and innovation in this field will pave the way for the clinical implementation of PDEVs in the treatment of various diseases, offering new hope for more effective and sustainable therapeutic options.

Objective To investigate the diagnostic value of bronchoalveolar lavage fluid(BALF)met-agenomic next-generation sequencing(mNGS)in pulmonary infection in children.Methods The clinical data of 109 children with pulmonary infection who were hospitalized in Gansu Provincial Maternal and Child Health Hospital from March 1,2023 to March 1,2024 were analyzed.BALF was collected for the etiological detection of mNGS,and the results were compared with those of conventional microbiology testing(CMT).Results The detection rate of BALF mNGS in 109 cases(96.3％)was higher than that of CMT(66.1％),and the difference was statistically significant(P＜0.01).A total of 280 strains of pathogens were detected in BALF mNGS and 130 strains were detected in CMT.Compared with CMT,mNGS could detect more patho-gens,especially the detection rate of viruses is much higher than that of CMT.Among the 70 mNGS and CMT double-positive samples,42 cases were completely or partially matched with the results of mNGS and CMT,48％of the matched samples were Haemophilus influenzae,19％were Mycoplasma pneumoniae,and 17％were Streptococcus pneumoniae.The pathogenic bacteria characteristics of BALF mNGS in children with se-vere pneumonia were analyzed.The detection rates of Haemophilus influenzae,Parainfluenza virus and Human metapneumovirus in children with severe pneumonia were higher than those in children without severe pneu-monia,and the differences were statistically significant(P＜0.05).In the comparative analysis of BALF mNGS detection results between full-term normal weight children and premature low weight children with birth information,it was found that the detection rate of Pseudomonas aeruginosa mNGS in premature low weight children was higher than that in full-term normal weight children,and the detection rate of Pseudo-monas aeruginosa mNGS in premature low weight children with complications was higher than that in prema-ture low weight children without complications,and the differences were statistically significant(P＜0.05).The detection rate of Mycoplasma pneumoniae mNGS in full-term normal weight children was higher than that in preterm low weight children,and the detection rate of Mycoplasma pneumoniae mNGS in full-term normal weight children without complications was higher than that in full-term normal weight children with complications,and the differences were statistically significant(P＜0.05).Conclusion BALF mNGS has a higher microbiological assay in children with pulmonary infection positive rate of detection,especially for severe infec-tions and complex cases,and BALF mNGS is an important supplement to routine etiological detection.

Objective:To investigate the effects of metformin on esophageal squamous cell carcinoma cell growth, migration and angiogenesis by regulating the expression of ALKBH3.Methods:Human esophageal cancer TE-1 cells were treated with different concentrations (0, 0.5, 1.0, 2.0, 4.0, 8.0 mmol/L) of metformin, and they were divided into a blank control group, low- (0.5 mmol/L), medium- (1.0 mmol/L), and high- (2.0 mmol/L) concentration metformin groups, a metformin (2.0 mmol/L) +pcDNA-NC group, and a metformin (2.0 mmol/L) +pcDNA-ALKBH3 group. The cell viability was determined by the CCK-8 method. The cell proliferation ability was detected by the clone formation assay. The cell migration and invasion abilities were examined by the Transwell assay. The cell apoptosis was detected by flow cytometry. The tube formation ability of cells was detected by the angiogenesis assay. A xenograft tumor model was constructed using 4- to 6-week-old male BALB/c thymus-less nude mice, which were divided into a model control group, a metformin group, a metformin+pcDNA-NC group, and a metformin+pcDNA-ALKBH3 group using a random number table method, and with six in each group. And the volume and weight of the tumor were measured. The protein expression levels of apoptosis-related proteins Bcl-2, Bax, ALKBH3 and vascular endothelial growth factor A (VEGF-A) were detected by Western blotting. The expression of CD31 protein was detected by immunohistochemistry.Results:After treating TE-1 cells with 0, 0.5, 1.0, 2.0, 4.0, and 8.0 mmol/L metformin for 48 hours, the cell viability was (100.00±0.00) %, (90.31±5.23) %, (81.25±8.65) %, (63.52±6.80) %, (54.64±5.35) %, and (31.48±4.21) %, respectively, with a statistically significant difference ( F=98.11, P<0.001). There were statistically significant differences in cell viability between 0.5, 1.0, 2.0, 4.0, 8.0 mmol/L and 0 mmol/L (all P<0.05). The IC 50 of metformin for TE-1 cells was 4.46 mmol/L. The numbers of colony formations of TE-1 cells in the blank control group, low-, medium-, and high-concentration metformin groups, metformin+pcDNA-NC group, and metformin+pcDNA-ALKBH3 group were 153.15±13.55, 134.80±11.62, 116.24±10.43, 93.17±8.85, 89.39±8.46, 110.26±7.21, respectively, with a statistically significant difference ( F=34.28, P<0.001); the numbers of colony formations of TE-1 cells in the metformin groups at different concentrations decreased significantly with the increase in metformin concentration (both P<0.05); compared with the metformin+pcDNA-NC group, the number of colony formations of cells in the metformin+pcDNA-ALKBH3 group increased ( P<0.05). The numbers of migration of TE-1 cells of 6 groups were 152.13±13.40, 133.85±10.72, 115.28±8.64, 91.16±7.89, 85.39±7.23, 116.85±8.36, the numbers of invasion were 135.22±10.77, 112.07±9.53, 86.30±7.45, 69.53±6.74, 65.81±5.65, 79.80±6.32, respectively, with statistically significant differences ( F=41.35, P<0.001; F=69.06, P<0.001); the numbers of migrated and invaded cells in the metformin groups at different concentrations decreased significantly with the increase in metformin concentration (all P<0.05); compared with the metformin+pcDNA-NC group, the numbers of migrated and invaded cells in the metformin+pcDNA-ALKBH3 group increased significantly (both P<0.05). The apoptosis rates of TE-1 cells in 6 groups were (3.22±1.13) %, (13.82±1.90) %, (22.67±2.53) %, (29.18±3.24) %, (26.84±2.75) %, and (16.36±1.63) %, respectively, with a statistically significant difference ( F=103.66, P<0.001); the apoptosis rates of cells in the metformin groups at different concentrations gradually increased with the increase in metformin concentration (both P<0.05); compared with the metformin+pcDNA-NC group, the apoptosis rate of cells in the metformin+pcDNA-ALKBH3 group was relatively lower ( P<0.05). The tubular structure of cells in blank control group was intact, and there were different degrees of damage to the tubular structure of cells in the low-, medium-, high- concentration metformin groups, the degree of damage to the tubular structure of cells in the metformin+pcDNA-ALKBH3 group was reduced. The numbers of cellular tubular structures of TE-1 cells in the 6 groups were 38.35±3.20, 27.15±2.64, 15.92±3.14, 7.39±1.50, 8.61±1.37, and 29.33±4.20, respectively, with a statistically significant difference ( F=113.92, P<0.001); the number of cellular tubular structures in the low-, medium-, and high- concentration metformin groups gradually decreased (both P<0.05); the number of cellular tubular structures in the metformin+pcDNA-ALKBH3 group was more than that in the metformin+pcDNA-NC group ( P<0.05). There were statistically significant differences in the protein expressions of Bcl-2, Bax, ALKBH3, and VEGF-A in TE-1 cells among 6 groups ( F=56.36, P<0.001; F=57.26, P<0.001; F=159.30, P<0.001; F=132.89, P<0.001); compared with the blank control group, the protein expressions of Bcl-2, ALKBH3, and VEGF-A in the metformin groups at different concentrations decreased, while the protein expression of Bax increased (all P<0.05); compared with the metformin+pcDNA-NC group, the protein expressions of Bcl-2, ALKBH3, and VEGF-A in the metformin+pcDNA-ALKBH3 group increased, and the expression level of Bax decreased (all P<0.05). The weights of tumors in the model control group, metformin group, metformin+pcDNA-NC group, and metformin+pcDNA-ALKBH3 group were (1.16±0.12), (0.46±0.05), (0.50±0.06), (1.19±0.14) g, the volumes of tumors were (878.36±108.93), (413.59±50.23), (439.78±51.39), (793.75±96.98) mm 3, with statistically significant differences ( F=96.61, P<0.001; F=51.90, P<0.001); the weight of tumors were lower and the volume of tumors were smaller in the metformin group than those in the model control group (both P<0.05), the weight of tumors were higher and the volume of tumors were bigger in the metformin+pcDNA-ALKBH3 group than those in the metformin group and the metformin+pcDNA-NC group (all P<0.05). CD31 was mainly distributed in the cytoplasm and cell membrane of tumor cells. There were statistically significant differences in the positive rates of CD31 and the protein expression levels of VEGF-A in transplanted tumor tissues among 4 groups ( F=7.12, P=0.002; F=48.81, P<0.001); the positive rate of CD31 and the protein expression level of VEGF-A in the metformin group were lower than those in the model control group; the positive rate of CD31 and the protein expression level of VEGF-A in the metformin+pcDNA-ALKBH3 group were higher than those in the metformin group and the metformin+pcDNA-NC group (all P<0.05) . Conclusions:Metformin may inhibit the proliferation, migration, and tumor angiogenesis of esophageal squamous cell carcinoma by reducing ALKBH3 expression.

The core pathogenesis of disease caused by latent toxin is deficiency of healthy qi and lingering pathogen, which is characterized by lingering and recurrent courses, and onset upon exogenous induction. The biological mechanisms of disease caused by latent toxin present multi-dimensional and synergistic characteristics. Immune dysfunction and inflammatory response serve as the core links, involving the abnormal activation of signaling pathways such as Wnt/β-catenin, PI3K/Akt/mTOR, TLR, and NF-κB; the accumulation of metabolites, as the microscopic carrier of latent toxin, participates in chronic complications of diabetes by damaging vascular endothelium and inhibiting repair pathways; immune escape and tolerance, as well as weakened tumor suppressor function, supplement the potential mechanisms of latent toxin from the perspectives of pathogen/tumor cell latency and congenital insufficiency; the imbalance of tissue repair and remodeling, and the imbalance of protein metabolism and cellular homeostasis further improve the mechanism network of latent toxin. Among these, immune dysfunction, tumor suppressor gene mutation, and regulatory dysfunction may be the microscopic manifestations of "healthy qi deficiency"; inflammatory factors, metabolites, viruses, and tumor cells may be the microscopic manifestations of "latent toxin". Current studies have limitations, such as unclear specific biomarkers for different types of latent toxin, insufficient research on the interaction of multiple mechanisms, and lack of clinical verification. It is suggested that future research should be further carried out around "latent toxin classification-mechanism-efficacy".

Objective To observe the clinical efficacy of mind-regulating and meridians-dredging acupuncture combined with rehabilitation training in treating limb dysfunction in recovery period of cerebral infarction(CI).Methods A total of 110 cases of patients with limb dysfunction in recovery period of CI were randomly divided into observation group and control group,55 cases in each group,the control group was given routine rehabilitation training,and the observation group was treated with mind-regulating and meridians-dredging acupuncture on the basis of intervention of the control group,the course of treatment covered two consecutive weeks.After two weeks of treatment,the clinical efficacy of the two groups was evaluated,and the changes of scores of traditional Chinese medicine(TCM)syndrome,Fugl-Meyer Assessment(FMA),Berg Balance Scale(BBS)and Modified Barthel Index(MBI)before and after treatment of patients in the two groups were observed.The changes of electromyographic signal before and after treatment were compared between the two groups.And the safety and the occurrence of adverse reactions in the two groups were evaluated.Results(1)The total effective rate was 98.18%(54/55)in the observation group and 87.27%(48/55)in the control group.The efficacy of the observation group was superior to that of the control group,the difference being statistically significant(P<0.05).(2)After treatment,the TCM syndrome scores of patients in the two groups were significantly improved(P<0.05),and the improvement in the observation group was significantly superior to that in the control group,with a statistically significant difference(P<0.05).(3)After treatment,the FMA scores of patients in the two groups improved significantly(P<0.05),and the improvement in the observation group was significantly superior to that in the control group,the difference being statistically significant(P<0.05).(4)After treatment,the BBS scores and MBI scores of the patients in the two groups improved significantly(P<0.05),and the improvement in the observation group was significantly superior to that in the control group,the difference being statistically significant(P<0.05).(5)After treatment,the root mean square value(RMS)of biceps brachii muscle elbow flexion and triceps brachii muscle elbow extention of the two groups of patients improved significantly(P<0.05),and the improvement in the observation group was significantly superior to that in the control group,the difference being statistically significant(P<0.05).(6)During the treatment,there were no obvious adverse reactions occurred in both groups.Conclusion Mind-regulating and meridians-dredging acupuncture combined with rehabilitation training in treating limb dysfunction in recovery period of CI can significantly improve the motor ability of patients,and adjust the electromyographic signals of the affected limbs,with high safety.

During long-duration space missions,astronauts face health challenges such as bone density loss,muscle atrophy,cardiovascular dysfunction,immune function suppression caused by microgravity,as well as mental health issues in a confined environment.There is an urgent need for real-time,continuous,and multi-dimensional health monitoring technologies to safeguard the health and safety of astronauts.This paper systematically reviews the technical requirements and current development status of astronaut on-orbit health monitoring,with a focus on analyzing breakthroughs in technologies such as dynamic electrocardiography,non-invasive blood pressure assessment,flexible electronic skin,and molecular probe spectroscopy.It also elaborates on how the integration of artificial intelligence and bionics technologies is propelling the monitoring system towards intelligence and autonomy,providing a reference for the medical support of astronauts during long-duration spaceflight missions.