ObjectiveThe accuracy of Y-chromosome haplogroup assignment is crucial for tracing paternal lineage in male samples. With the advancement of high-throughput sequencing technologies, high-density Y-SNP genotyping from whole-genome or array-based data has become a standard method for determiningY-chromosome haplogroups. This study systematically evaluated the performance of 4 commonly used high-density SNP genotyping systems—namely, the Global Screening Array (GSA), Chinese Genotyping Array (CGA), Affymetrix array, and the 1240K capture panel—for haplogroup assignment. This work provides a reference for data comparison across different systems. MethodsWe extracted genotype data for the 4 Y-SNP panels from 30× whole-genome sequencing (WGS) data of 1 590 male samples from the 1000 Genomes Project. Additionally, GSA array genotype data from 384 relative pairs (spanning 1st- to 12th-degree relationships) from 109 Chinese Han families were collected. Haplogroup assignment was performed using Y-LineageTracker v1.3.0 software. We assessed the concordance and resolution of haplogroup assignments between the four Y-SNP panels and the WGS data. The consistency and resolution of haplogroup assignments were also evaluated for both the 1000 Genomes Project samples and the 109 family samples collected in this study. Furthermore, the impact of varying numbers of Y-SNPs on haplogroup assignment was examined. ResultsThe GSA and CGA panels demonstrated superior resolution and discrimination of haplogroup subclades compared with the other two panels. The haplogroup assignments from the GSA, CGA, and 1240K panels showed high concordance with WGS data, with consistency rates exceeding 88.70%, whereas the Affymetrix platform exhibited a significantly lower consistency rate of 61.89%. Specifically, the GSA and CGA panels consistently demonstrated superior performance compared with the other two panels in the assignment of haplogroups O-M175 and H-L901, achieving complete concordance (100%) for both haplogroups. In contrast, the Affymetrix panel erroneously assigned all individuals belonging to haplogroup O-M175 to haplogroup K2-M526. Furthermore, its accuracy for haplogroup H-L901 was exceedingly low, at merely 1.41%. This poor performance was characterized by the misassignment of 98.59% of H-L901 samples—specifically, 1.41% to J-M304 and a predominant 97.18% to F-M89. For haplogroup R-M207, all four panels exhibited uniformly high levels of consistency, with concordance values exceeding 94.00%. Notably, for haplogroup E-M96, the 1240K and Affymetrix panels outperformed the GSA and CGA panels in terms of concordance, representing the first instance in which these two panels surpassed the latter. Conversely, for haplogroups J-M304, Q-M242, and I-M170, all 4 panels showed relatively elevated misclassification rates, with the Affymetrix array demonstrating the poorest overall performance. None of the four panels showed any discordant haplogroup assignments among the familial relative pairs analyzed. A positive correlation was observed between the number of Y-SNPs (ranging from 1 000 to 10 000) and classification consistency; however, classification consistency plateaued when the number of Y-SNPs exceeded 10 000. Furthermore, a random sampling analysis conducted on the GSA and CGA panels demonstrated that the haplogroup misclassification rate exhibited negligible fluctuation across the Y-SNP range of 500 to 1 000. Conversely, a marked enhancement in classification consistency was observed as the number of markers increased from 1 000 to 5 000, ultimately reaching a plateau within the interval of 5 000 to 8 000 markers. ConclusionThese findings indicate that the GSA and CGA panels provide high resolution and concordance, delivering reliable Y-haplogroup assignment for forensic investigations.

ObjectiveThis Study was conducted to investigate the interaction mechemisms between gutmicrobiota dysregulation and ischemic stroke by establishing a rat model of ischemic stroke and employing fecal microbiota transplantation (FMT). MethodsA preliminary experiment was conducted to establish an antibiotic-induced pseudo-sterile (ABX) rat model through antibiotic treatment, and a cerebral ischemia model was prepared using the middle cerebral artery occlusion (MCAO) method. Fecal microbiota from stroke patients and healthy individuals were transplanted via FMT, followed by behavioral testing. 16S rRNA sequencing was used to analyze the microbial community, hematoxylin and eosin (HE) staining to observe histopathological status, transmission electron microscopy (TEM) to examine the tight junction structure of the small intestine, and enzyme-linked immunosorbent assay (ELISA) to detect levels of inflammatory factors and intestinal barrier-related markers. Results16S rRNA sequencing of fecal samples showed that compared with the normal control group and the metronidazole group, the abundance and diversity of fecal microorganisms in the quadruple antibiotic group were significantly reduced, indicating successful establishment of the ABX model. After transplanting fecal microbiota from stroke patients into ABX rats, significant changes in gut microbiota composition were observed. Behavioral tests revealed that the MCAO model group showed significant decreases in both horizontal movement and vertical exploration abilities. ELISA results indicated that IL-17 concentration in the ABX+mFMT (antibiotic-treated+model fecal microbiota transplantation) group was lower than in the ABX+cFMT (antibiotic-treated+control fecal microbiota transplantation) group, suggesting that IL-17 may serve as a key inflammatory indicator for evaluating the impact of stroke intervention on gut microbiota. Triphenyltetrazolium chloricle staining (TTC) staining suggested that gut microbiota intervention may increase the risk of stroke. HE staining showed that, except for the control group, all groups exhibited ischemic changes and inflammatory infiltration in brain tissues. TEM revealed that microvilli of small intestinal epithelial cells in the ABX+mFMT group were sparser than those in the ABX+cFMT group, indicating that microbial intervention affects intestinal barrier function. ConclusionThe ABX model established using broad-spectrum antibiotics showed no significant differences in physiological characteristics compared to normal rats, and the findings were consistent with those from germ-free rat models. Stroke prognosis appears to be influenced by intestinal dysbiosis, accompanied by significantly elevated levels of the pro-inflammatory cytokine IL-17, which may exacerbate neural injury via the gut-brain axis. Behavioral experiments indicated that transplantation of gut microbiota from stroke rats impaired cognitive function. Furthermore, IL-17 demonstrated sensitivity to alterations in the gut microbiota, suggesting its potential as a key therapeutic target for stroke intervention.

ObjectiveCleft palate (CP) is a common congenital deformity often associated with velopharyngeal insufficiency (VPI), which disrupts the physiological coupling between respiration and speech. Conventional clinical assessments, such as nasometry and spirometry, provide limited static data and fail to visualize the dynamic spatiotemporal distribution of lung ventilation during phonation. This study introduces spatiotemporal electrical impedance tomography (ST-EIT) to evaluate speech-respiratory functional features in CP patients compared to normal controls (NC). The aim is to characterize multi-domain respiratory patterns and to validate an interpretable machine learning framework for providing objective, quantitative evidence for clinical assessment. MethodsSeventy-five participants were enrolled in this study, comprising 37 patients with surgically repaired CP and 38 healthy volunteers matched for age, gender, and body mass index (BMI). All subjects performed standardized sustained phonation tasks while undergoing synchronous monitoring with a 16-electrode EIT system and a pneumotachograph. A comprehensive feature engineering pipeline was developed to extract physiological parameters across 3 complementary domains. (1) Temporal domain: including inspiratory/expiratory phase duration (tPhase), time constants (Tau), and inspiratory-to-expiratory time ratios (TI/TE); (2) airflow domain: comprising mean flow, peak flow, and instantaneous flow at 25%, 50%, and 75% of tidal volume; and (3) spatial domain: quantifying global and regional tidal impedance variation (TIV), global inhomogeneity (GI), and center of ventilation (CoV). Extreme Gradient Boosting (XGBoost) classifiers were trained using 5 distinct data sources (Spirometry, Nasometry, Inspiratory-EIT, Expiratory-EIT, and fused ST-EIT). Model performance was rigorously evaluated via stratified 5-fold cross-validation, and Shapley additive explanations (SHAP) were employed to quantify global and local feature contributions. ResultsThe CP group exhibited a distinct respiratory phenotype compared to controls. In the temporal domain, CP patients showed significantly shorter inspiratory (1.60 s vs.1.85 s, P<0.001) and expiratory phase durations (2.45 s vs. 3.95 s, P<0.001), indicating a rapid, shallow breathing rhythm. In the airflow domain, while inspiratory flows were comparable, the CP group demonstrated significantly elevated mean and peak flows during the expiratory phase (P<0.001), reflecting compensatory respiratory effort. Spatially, CP patients presented significant ventilation redistribution, characterized by higher regional TIV in the right-anterior (ROI1) and left-posterior (ROI4) quadrants, but lower TIV in the left-anterior (ROI2) quadrant. In terms of diagnostic accuracy, the multi-modal ST-EIT model achieved the highest performance (AUC: 0.915±0.012, Accuracy: 0.843±0.019, F1-score: 0.872±0.017), substantially outperforming models based on spirometry (AUC: 0.721) or nasometry (AUC: 0.625) alone. Interpretability analysis revealed that spatial domain features were the most critical, contributing 53.4% to the model’s decision-making, followed by temporal (25.0%) and airflow (21.6%) features. ConclusionST-EIT successfully captures the temporal, airflow, and spatial deviations in CP speech respiration that are undetectable by conventional methods—specifically, rapid phase transitions, hyperdynamic expiratory airflow, and regional ventilation heterogeneity. This study validates ST-EIT as a robust, non-invasive, and radiation-free tool for characterizing speech-respiratory dysfunction, offering high clinical value for bedside screening, rehabilitation planning, and longitudinal monitoring of patients with cleft palate.

ObjectiveThe accuracy of Y-chromosome haplogroup assignment is crucial for tracing paternal lineage in male samples. With the advancement of high-throughput sequencing technologies, high-density Y-SNP genotyping from whole-genome or array-based data has become a standard method for determiningY-chromosome haplogroups. This study systematically evaluated the performance of 4 commonly used high-density SNP genotyping systems—namely, the Global Screening Array (GSA), Chinese Genotyping Array (CGA), Affymetrix array, and the 1240K capture panel—for haplogroup assignment. This work provides a reference for data comparison across different systems. MethodsWe extracted genotype data for the 4 Y-SNP panels from 30× whole-genome sequencing (WGS) data of 1 590 male samples from the 1000 Genomes Project. Additionally, GSA array genotype data from 384 relative pairs (spanning 1st- to 12th-degree relationships) from 109 Chinese Han families were collected. Haplogroup assignment was performed using Y-LineageTracker v1.3.0 software. We assessed the concordance and resolution of haplogroup assignments between the four Y-SNP panels and the WGS data. The consistency and resolution of haplogroup assignments were also evaluated for both the 1000 Genomes Project samples and the 109 family samples collected in this study. Furthermore, the impact of varying numbers of Y-SNPs on haplogroup assignment was examined. ResultsThe GSA and CGA panels demonstrated superior resolution and discrimination of haplogroup subclades compared with the other two panels. The haplogroup assignments from the GSA, CGA, and 1240K panels showed high concordance with WGS data, with consistency rates exceeding 88.70%, whereas the Affymetrix platform exhibited a significantly lower consistency rate of 61.89%. Specifically, the GSA and CGA panels consistently demonstrated superior performance compared with the other two panels in the assignment of haplogroups O-M175 and H-L901, achieving complete concordance (100%) for both haplogroups. In contrast, the Affymetrix panel erroneously assigned all individuals belonging to haplogroup O-M175 to haplogroup K2-M526. Furthermore, its accuracy for haplogroup H-L901 was exceedingly low, at merely 1.41%. This poor performance was characterized by the misassignment of 98.59% of H-L901 samples—specifically, 1.41% to J-M304 and a predominant 97.18% to F-M89. For haplogroup R-M207, all four panels exhibited uniformly high levels of consistency, with concordance values exceeding 94.00%. Notably, for haplogroup E-M96, the 1240K and Affymetrix panels outperformed the GSA and CGA panels in terms of concordance, representing the first instance in which these two panels surpassed the latter. Conversely, for haplogroups J-M304, Q-M242, and I-M170, all 4 panels showed relatively elevated misclassification rates, with the Affymetrix array demonstrating the poorest overall performance. None of the four panels showed any discordant haplogroup assignments among the familial relative pairs analyzed. A positive correlation was observed between the number of Y-SNPs (ranging from 1 000 to 10 000) and classification consistency; however, classification consistency plateaued when the number of Y-SNPs exceeded 10 000. Furthermore, a random sampling analysis conducted on the GSA and CGA panels demonstrated that the haplogroup misclassification rate exhibited negligible fluctuation across the Y-SNP range of 500 to 1 000. Conversely, a marked enhancement in classification consistency was observed as the number of markers increased from 1 000 to 5 000, ultimately reaching a plateau within the interval of 5 000 to 8 000 markers. ConclusionThese findings indicate that the GSA and CGA panels provide high resolution and concordance, delivering reliable Y-haplogroup assignment for forensic investigations.

ObjectiveThis Study was conducted to investigate the interaction mechemisms between gutmicrobiota dysregulation and ischemic stroke by establishing a rat model of ischemic stroke and employing fecal microbiota transplantation (FMT). MethodsA preliminary experiment was conducted to establish an antibiotic-induced pseudo-sterile (ABX) rat model through antibiotic treatment, and a cerebral ischemia model was prepared using the middle cerebral artery occlusion (MCAO) method. Fecal microbiota from stroke patients and healthy individuals were transplanted via FMT, followed by behavioral testing. 16S rRNA sequencing was used to analyze the microbial community, hematoxylin and eosin (HE) staining to observe histopathological status, transmission electron microscopy (TEM) to examine the tight junction structure of the small intestine, and enzyme-linked immunosorbent assay (ELISA) to detect levels of inflammatory factors and intestinal barrier-related markers. Results16S rRNA sequencing of fecal samples showed that compared with the normal control group and the metronidazole group, the abundance and diversity of fecal microorganisms in the quadruple antibiotic group were significantly reduced, indicating successful establishment of the ABX model. After transplanting fecal microbiota from stroke patients into ABX rats, significant changes in gut microbiota composition were observed. Behavioral tests revealed that the MCAO model group showed significant decreases in both horizontal movement and vertical exploration abilities. ELISA results indicated that IL-17 concentration in the ABX+mFMT (antibiotic-treated+model fecal microbiota transplantation) group was lower than in the ABX+cFMT (antibiotic-treated+control fecal microbiota transplantation) group, suggesting that IL-17 may serve as a key inflammatory indicator for evaluating the impact of stroke intervention on gut microbiota. Triphenyltetrazolium chloricle staining (TTC) staining suggested that gut microbiota intervention may increase the risk of stroke. HE staining showed that, except for the control group, all groups exhibited ischemic changes and inflammatory infiltration in brain tissues. TEM revealed that microvilli of small intestinal epithelial cells in the ABX+mFMT group were sparser than those in the ABX+cFMT group, indicating that microbial intervention affects intestinal barrier function. ConclusionThe ABX model established using broad-spectrum antibiotics showed no significant differences in physiological characteristics compared to normal rats, and the findings were consistent with those from germ-free rat models. Stroke prognosis appears to be influenced by intestinal dysbiosis, accompanied by significantly elevated levels of the pro-inflammatory cytokine IL-17, which may exacerbate neural injury via the gut-brain axis. Behavioral experiments indicated that transplantation of gut microbiota from stroke rats impaired cognitive function. Furthermore, IL-17 demonstrated sensitivity to alterations in the gut microbiota, suggesting its potential as a key therapeutic target for stroke intervention.

ObjectiveCleft palate (CP) is a common congenital deformity often associated with velopharyngeal insufficiency (VPI), which disrupts the physiological coupling between respiration and speech. Conventional clinical assessments, such as nasometry and spirometry, provide limited static data and fail to visualize the dynamic spatiotemporal distribution of lung ventilation during phonation. This study introduces spatiotemporal electrical impedance tomography (ST-EIT) to evaluate speech-respiratory functional features in CP patients compared to normal controls (NC). The aim is to characterize multi-domain respiratory patterns and to validate an interpretable machine learning framework for providing objective, quantitative evidence for clinical assessment. MethodsSeventy-five participants were enrolled in this study, comprising 37 patients with surgically repaired CP and 38 healthy volunteers matched for age, gender, and body mass index (BMI). All subjects performed standardized sustained phonation tasks while undergoing synchronous monitoring with a 16-electrode EIT system and a pneumotachograph. A comprehensive feature engineering pipeline was developed to extract physiological parameters across 3 complementary domains. (1) Temporal domain: including inspiratory/expiratory phase duration (tPhase), time constants (Tau), and inspiratory-to-expiratory time ratios (TI/TE); (2) airflow domain: comprising mean flow, peak flow, and instantaneous flow at 25%, 50%, and 75% of tidal volume; and (3) spatial domain: quantifying global and regional tidal impedance variation (TIV), global inhomogeneity (GI), and center of ventilation (CoV). Extreme Gradient Boosting (XGBoost) classifiers were trained using 5 distinct data sources (Spirometry, Nasometry, Inspiratory-EIT, Expiratory-EIT, and fused ST-EIT). Model performance was rigorously evaluated via stratified 5-fold cross-validation, and Shapley additive explanations (SHAP) were employed to quantify global and local feature contributions. ResultsThe CP group exhibited a distinct respiratory phenotype compared to controls. In the temporal domain, CP patients showed significantly shorter inspiratory (1.60 s vs.1.85 s, P<0.001) and expiratory phase durations (2.45 s vs. 3.95 s, P<0.001), indicating a rapid, shallow breathing rhythm. In the airflow domain, while inspiratory flows were comparable, the CP group demonstrated significantly elevated mean and peak flows during the expiratory phase (P<0.001), reflecting compensatory respiratory effort. Spatially, CP patients presented significant ventilation redistribution, characterized by higher regional TIV in the right-anterior (ROI1) and left-posterior (ROI4) quadrants, but lower TIV in the left-anterior (ROI2) quadrant. In terms of diagnostic accuracy, the multi-modal ST-EIT model achieved the highest performance (AUC: 0.915±0.012, Accuracy: 0.843±0.019, F1-score: 0.872±0.017), substantially outperforming models based on spirometry (AUC: 0.721) or nasometry (AUC: 0.625) alone. Interpretability analysis revealed that spatial domain features were the most critical, contributing 53.4% to the model’s decision-making, followed by temporal (25.0%) and airflow (21.6%) features. ConclusionST-EIT successfully captures the temporal, airflow, and spatial deviations in CP speech respiration that are undetectable by conventional methods—specifically, rapid phase transitions, hyperdynamic expiratory airflow, and regional ventilation heterogeneity. This study validates ST-EIT as a robust, non-invasive, and radiation-free tool for characterizing speech-respiratory dysfunction, offering high clinical value for bedside screening, rehabilitation planning, and longitudinal monitoring of patients with cleft palate.

Malignant tumors represent a major threat to global health. Conventional anti-tumor pharmacotherapy often encounters challenges such as drug resistance, highlighting an urgent need for the development of novel therapeutic strategies. Fatty acid synthase (FASN), the key enzyme catalyzing de novo fatty acid synthesis, is subject to precise regulation at multiple levels, including transcriptional control, various post-translational modifications such as ubiquitination and phosphorylation, as well as modulation by diverse signaling pathways. Recent studies have revealed that FASN is aberrantly overexpressed in various malignant tumors and is closely associated with tumor progression and poor patient prognosis. FASN is a homodimer composed of seven functional domains that catalyzes the NADPH-dependent condensation of acetyl-CoA and malonyl-CoA to generate saturated fatty acids, primarily palmitic acid. Its stability is regulated by multiple ubiquitin ligases and deubiquitinating enzymes. Additionally, FASN is subject to upstream regulation via neural precursor cell-expressed developmentally downregulated 8 (Nedd8) modification and the phosphatidylinositol 3-kinase (PI3K)/protein kinase B (AKT)/mammalian target of rapamycin (mTOR) pathway, thereby establishing a metabolic-signaling positive feedback loop. As a core executor of metabolic reprogramming, FASN promotes tumorigenesis through dual mechanisms. First, its fatty acid synthesis product, palmitate, participates in membrane phospholipid synthesis, lipid raft formation, and protein palmitoylation, thereby activating several key oncogenic signaling pathways, including PI3K/AKT/mTOR, wingless-type MMTV integration site family member (Wnt)/β‑catenin, and signal transducer and activator of transcription 3 (STAT3)/matrix metalloproteinase (MMP), leading to tumor development and progression. Second, FASN plays a pivotal role in modulating the anti-tumor functions of immune cells and remodeling the tumor immune microenvironment. Specifically, FASN enhances immune checkpoint inhibition by inducing programmed death-ligand 1 (PD-L1) palmitoylation, suppresses the activation of cytotoxic T lymphocytes and natural killer cells, and promotes the polarization of M2-type macrophages, consequently facilitating tumor immune evasion and malignant progression. Precisely due to its significant overexpression in tumor cells, its critical functional role, and its differential expression compared to normal cells, FASN has emerged as a highly promising target for anti-tumor drug development. Highly selective small-molecule inhibitors, notably represented by TVB-2640, have advanced to clinical trial stages and demonstrated favorable anti-tumor activity. Furthermore, the combination of FASN inhibitors with other chemotherapeutic agents or targeted drugs can overcome the limitations of monotherapy through synergistic effects or by resensitizing tumor cells to conventional drugs, achieving a “1+1>2” therapeutic outcome. With the advancement of modern traditional Chinese medicine (TCM), numerous active ingredients derived from TCM have been confirmed to exert anti-tumor effects by modulating FASN-related pathways. This integrated approach leverages the precision of Western medicine while simultaneously harnessing the holistic regulatory benefits of TCM to alleviate the side effects of radiotherapy and chemotherapy. Despite the promising prospects of FASN-targeted therapies, challenges remain, including tumor cell metabolic plasticity, tumor context-dependent responses, and heterogeneity. This review systematically summarizes the molecular structure, physiological functions, and mechanisms of FASN in tumorigenesis, as well as recent advances in targeted therapies. Future directions—including the precise identification of responsive patient populations using spatial transcriptomics, the development of novel combination regimens, and the active exploration of integrative strategies combining traditional Chinese and Western medicine—will facilitate the clinical translation of FASN-targeted therapies and open new avenues for improving the quality of life and prognosis of cancer patients.

By analyzing the current status of randomized controlled trials （RCTs） on functional dyspepsia （FD） and irritable bowel syndrome （IBS） comorbidity， we identified several critical issues which include insufficient repor-ting of FD and IBS subtypes， inadequate risk assessment of drug combination， lack of composite， objective， and long-term outcomes， and weak evidence support for clinical practice guidelines. It is suggested that future clinical research on FD-IBS comorbidity should further strengthen the application of real-world studies. The use of composite outcomes and long-term follow-up is recommended to improve the quality of evidence， while greater attention should be paid to patients' preferences and self-management to enhance the applicability of findings. Based on the existing issues in clinical studies of traditional Chinese medicine （TCM） for FD-IBS comorbidity， we propose to consolidate the foundation of TCM-specific efficacy evaluation to better reflect the advantages of syndrome differentiation and treatment， optimize real-world study designs to better support clinical decision- making， and introduce intelligent objective evaluation technologies to improve the objectivity and accuracy of TCM clinical efficacy assessment.

As a critical measure for treating patients with end-stage organ failure, organ donation and transplantation has become an important benchmark reflecting a country’s comprehensive capacity in healthcare, modernization of governance and progress in social civilization. In 2024, the total number of organ transplant procedures worldwide exceeded 180 000, representing an annual growth rate of 2.4%. China ranked second globally with 24 000 transplant procedures, accounting for 13.8% of the global total. Meanwhile, driven by the growing burden of transplantation-related non-communicable diseases, the global demand for organ transplantation has reached an all-time high. At present, the global development of organ donation and transplantation features a landscape of coexisting strategic opportunities and risks and challenges. On the one hand, technological breakthroughs and institutional innovations have accelerated the rapid development of the field. On the other hand, issues such as uneven regional development, supply-demand imbalance, and lagging governance remain to be addressed. This study integrates multi-dimensional authoritative monitoring data, systematically summarizes twelve key characteristics of the global organ donation and transplantation sector, distills ten major developmental features and regional leading effects of China at the current stage, and elaborates on the practical connotation and contemporary value of the “Chinese Model”. The findings not only provide important references for countries to promote the sustainable development of the industry, narrow regional development gaps, and improve the equitable access to medical resources, but also offer comprehensive research support and scientific decision-making basis for China to consolidate its developmental advantages, refine Chinese solutions, and deeply participate in the construction of the global organ donation and transplantation governance system.

Currently, driven by rigid health demands, technological iteration and innovation, and the reshaping of the global development landscape, the global field of organ donation and transplantation presents a development trend featuring "continuous expansion of transplantation scale, diversified donor sources, multiple breakthroughs in core technologies, and sustained optimization of supporting policies". Meanwhile, it still faces profound challenges including prominent contradiction between supply and demand, unbalanced regional development, increasing governance difficulties, and lack of dynamic adaptation of ethical norms. Under the continuous initiative and promotion of the United Nations, the World Health Organization and relevant international academic groups, organ donation and transplantation have become an important issue for promoting the harmonious development of human society and improving global public health governance. At the present stage, the reshaping of the global development pattern and the impact of uncertainties in the international situation cannot be ignored, which not only brings challenges to transnational cooperation in the field of organ donation and transplantation, but also forces all countries to accelerate the construction of an independent, controllable, safe and efficient working system. Based on the development characteristics revealed by data insights, this paper further sorts out the innovative practical progress, policy evolution context and latest orientations of countries around the world in solving the development dilemmas of organ donation and transplantation in recent years, analyzes the core challenges and prospectively judges future policy trends. It not only provides experience reference for countries to carry out industrial governance, but also consolidates the decision-making foundation for China to build an independent knowledge system and a discourse system with Chinese characteristics, and deeply participate in the construction of the global governance system.