1.Diagnostic value of serum Mac-2 binding protein for the severity of schistosomiasis-induced liver fibrosis
Jun WU ; Meiqun LUO ; Shuying XIE ; Ronghua ZHU ; Hui XU ; Long TANG ; Fei HU ; Sheng DING
Chinese Journal of Schistosomiasis Control 2026;38(1):38-43
Objective To evaluate the value of serum Mac-2 binding protein (M2BP) for assessment of the severity of schisto somiasis-induced liver fibrosis, so as to provide insights into non-invasive diagnosis and disease surveillance of liver fibrosis caused by schistosomiasis. Methods A total of 234 individuals with a history of Schistosoma japonicum infection were sampled from Xinhua Village, Lushan City, Jiangxi Province from 2019 to 2020, and 234 serum samples were collected from all participants. All participants received B-ultrasound examinations of the liver. Serum samples were categorized into four groups (grades 0, Ⅰ, Ⅱ and Ⅲ schistosomiasis-induced liver fibrosis groups) according to B-ultrasound examination results, and then, each group was randomly divided into a receiver operating characteristic (ROC) curve group and an efficacy assessment group at a ratio of 7∶3. Serum M2BP concentration was measured in four groups using the enzyme-linked immunosorbent assay (ELISA), and differences in serum M2BP concentrations were compared with analysis of variance and Spearman correlation analysis. Serum M2BP concentration was subjected to ROC curve analysis among individuals with different grades of schistosomiasis-induced liver fibrosis in the ROC curve group to determine the optimal diagnostic threshold of M2BP concentration at different fibrosis grades, and the area under the ROC curve (AUC) was calculated to evaluate the diagnostic performance. The diagnostic accuracy was verified by comparing the accordance rate and Kappa consistency test in the efficacy assessment group. Results Among 234 serum samples, there were 79 samples with grade 0 schistosomiasis-induced liver fibrosis, 87 samples with Grade Ⅰ, 46 samples with Grade Ⅱ and 22 samples with Grade Ⅲ according to the B-ultrasound examinations. The mean serum M2BP concentrations were (0.40 ± 0.31) [95% confidence interval (CI): (0.33, 0.47)], (0.64 ± 0.48) [95% CI: (0.53, 0.74)], (1.76 ± 0.58) [95% CI: (1.59, 1.93)] μg/mL and (2.56 ± 0.93) [95% CI: (2.14, 2.97)] μg/mL in the four groups, respectively (F = 150.796, P < 0.001), and the severity of schistosomiasis-induced liver fibrosis significantly positively correlated with serum M2BP concentration (rs = 0.715, P < 0. 001). The sample sizes of grades 0, Ⅰ, Ⅱ and Ⅲ schistosomiasis-induced liver fibrosis sera were randomly allocated as follows: 55 versus 24, 61 versus 26, 32 versus 14, and 15 versus 7 in the ROC curve and efficacy assessment groups, respectively, and the serum M2BP concentrations were (0.39 ± 0.29) μg/mL and (0.42 ± 0.36) μg/mL (F = 0.196, P > 0.05), (0.59 ± 0.47) μg/mL and (0.75 ± 0.51) μg/mL (F = 1.967, P > 0.05), (1.73 ± 0.59) μg/mL and (1.85 ± 0.57) μg/mL (F = 0.417, P > 0.05), and (2.46 ± 0.64) μg/mL and (2.76 ± 1.41) μg/mL (F = 0.491, P > 0.05), respectively. ROC curve analysis showed that the optimal diagnostic thresholds of serum M2BP concentration were 0.347 86 μg/mL (AUC = 0.635, P < 0.05), 1.188 83 μg/mL (AUC = 0.938, P < 0.000 1) and 2.021 21 μg/mL (AUC = 0.821, P < 0.000 1) for grade Ⅰ, Ⅱ and Ⅲ schistosomiasis-induced liver fibrosis. In addition, the accordance rates between the optimal diagnostic threshold of serum M2BP and B-ultrasound examinations for predicting grade Ⅰ, Ⅱ and Ⅲ schistosomiasis-induceed liver fibrosis were 69.23%, 85.71% and 71.43% (χ2 = 1.340, P > 0.05), and the overall Kappa consistency test showed moderate consistency [Kappa = 0.608, 95% CI: (0.428, 0.788); Z = 6.609, P < 0.000 1]. Conclusions Serum M2BP may serve as a potential biomarker for assessing moderate to advanced schistosomiasis-induced liver fibrosis; however, its diagnostic value for early-stage schistosomiasis-induced liver fibrosis remains limited.
2.Predictive model for severe adverse reaction associated with bevacizumab based on the global trigger tool and machine learning
Yongfei FU ; Xin LONG ; Hongzhen XU ; Jian TANG ; Xiangqing LI ; Yucheng LONG ; Dong QIN
China Pharmacy 2026;37(4):497-503
OBJECTIVE To confirm trigger items for adverse drug reaction (ADR) induced by bevacizumab, to identify and analyze the occurrence of related ADR, and to establish a predictive model for severe adverse reaction (SAR) caused by this drug. METHODS Based on the global trigger tool (GTT) theory, and referencing the GTT White Paper, drug package inserts and relevant literature, trigger items for bevacizumab-related ADR were confirmed using a single-round Delphi method. Utilizing these established items, electronic medical records of relevant patients at Guilin People’s Hospital from January 2020 to September 2024 were actively screened via the China Hospital Pharmacovigilance System. Pharmacists then identified and tallied the occurrence of bevacizumab-induced ADR. Data from patients with any positive trigger item served as the study subjects (divided into training and test sets at a ratio of 7∶3), candidate feature variables were selected from 39 related variables using the Boruta algorithm, and the multivariable Logistic regression analysis was performed with the occurrence of SAR as the dependent variable. Based on these candidate features, Logistic Regression, Extreme Gradient Boosting, Light Gradient Boosting Machine, Random Forest, and Categorical Boosting models were constructed. Model performance was evaluated using metrics including the area under the curve (AUC) of receiver operating characteristic curve and recall rate. The Shapley Additive exPlanations (SHAP) method was applied to analyze and interpret the contribution of each variable. A nomogram was constructed based on the optimal model. RESULTS A total of 38 trigger items for active monitoring of bevacizumab-related ADR were determined, comprising 17 laboratory indicators, 13 clinical manifestations, and 8 intervention measures. In total, 483 patients with positive trigger items were included, and 318 patients with bevacizumab-induced ADR were identified, including 83 SARs. The positive predictive values for the trigger items and cases were 43.57% (708/1 625) and 63.84% (318/483), respectively. Bevacizumab-induced ADR involved 7 systems/organs, with the hematological system being the most frequently involved (64.15%). The Boruta algorithm selected 7 vari ables: serum potassium, hematocrit, albumin-to-globulin ratio, prealbumin, hypertension history, age and red blood cell count. Multivariable Logistic regression showed that elevated serum potassium levels were associated with a decreased risk of bevacizumab-induced SAR (OR=0.234, P =0.002), while a history of hypertension (OR=2.642, P =0.006) and increased age (OR=1.040, P =0.025) were associated with an increased risk. The Logistic Regression model demonstrated superior performance with higher AUC, F1 score and recall rate (0.761, 0.447, 0.607), compared to other models. SHAP evaluation results indicated that variables such as serum potassium, hematocrit, and age ranked highest in importance. CONCLUSIONS Totally 38 trigger entries have been successfully identified for active screening of bevacizumab-related ADR. Elevated serum potassium levels are a protective factor against bevacizumab-induced SAR, whereas the hypertension history and increased age are risk factors. The Logistic Regression model is the optimal predictive model.
3.Establishment and validation of a model for femoral head necrosis after internal fixation of femoral neck fracture using logistic regression and SHAP analysis
Long LIAO ; Zepeng ZHAO ; Zongyuan LI ; Qinglong YU ; Tao ZHANG ; Jinyuan TANG ; Nan YE ; Han XU ; Bo SHI
Chinese Journal of Tissue Engineering Research 2026;30(3):626-633
BACKGROUND:The most common complication of traumatic femoral neck fractures after internal fixation is femoral head necrosis.Currently,many studies have reported on the risk factors that affect the occurrence and development of postoperative femoral head necrosis,but there is still a lack of tools to predict the risk of femoral head necrosis after internal fixation of femoral neck fractures.OBJECTIVE:To develop a predictive model that estimates the risk of femoral head necrosis shortly after patients with femoral neck fractures receive cannulated screw internal fixation.METHODS:A retrospective analysis reviewed clinical records of 172 patients who underwent cannulated screw internal fixation for femoral neck fractures at Department of Orthopedics of Mianyang Central Hospital from January 2013 to June 2023.Patients were categorized into two groups based on the presence or absence of femoral head necrosis within one year post-operation:the necrosis group and the non-necrosis group.Univariate analysis,Lasso regression,and multivariate Logistic regression techniques were employed to identify the determinants of femoral head necrosis.A nomogram prediction model was constructed using R language's"rms"package,version 4.0.The receiver operating characteristic curve was used to evaluate the discriminatory ability of the model.The Hosmer-Lemeshow test was used to evaluate the goodness of fit of the model,and the decision curve analysis was used to determine its clinical application benefits.Internal validation of the study was conducted using the Bootstrap method,involving 1 000 repeated samplings.To delve deeper into the primary factors influencing femoral head necrosis post-internal fixation of the femoral neck,this paper employed the SHAP method for data set analysis.RESULTS AND CONCLUSION:(1)The risk factors leading to femoral head necrosis in the short term after cannulated screw fixation of femoral neck fractures include:smoking,diabetes,Garden classification,fracture line location,reduction quality,age,and operation time.(2)The prediction model demonstrated robust performance,evidenced by an area under the curve of 0.940(95%Confidence Interval:0.903 to 0.977),indicating a high level of prediction accuracy.The model achieved a sensitivity of 90.2%and a specificity of 87.6%,indicating that its diagnostic performance was stable.The Hosmer-Lemeshow goodness-of-fit test yielded a chi-square value of 6.593 with a P-value of 0.581,confirming that the model's predictions closely align with the observed outcomes.(3)The calibration curve of the model also performed well,and its overall trend was very close to the ideal curve,further proving the high accuracy of the model.(4)The internal validation was carried out by the Bootstrap method with 1 000 repeated samplings,and the area under the curve of the model internal validation was still as high as 0.939,proving that the model had good stability.(5)Through the decision curve,it is found that within the probability threshold range of 1%to 92%,the model can obtain the maximum net benefit value.(6)The SHAP analysis results show that among the risk factors analyzed in this study,the location of the fracture line serves as the most significant predictor of femoral head necrosis following internal fixation with cannulated screws in femoral neck fractures,and subcapital fractures are extremely prone to femoral head necrosis after surgery.(7)It is concluded that the validated prediction model demonstrates strong discriminative power and reliability,offering practical clinical utility.It serves as a useful reference tool for short-term risk assessment of femoral head necrosis following internal fixation of femoral neck fractures.
4.Establishment and validation of a model for femoral head necrosis after internal fixation of femoral neck fracture using logistic regression and SHAP analysis
Long LIAO ; Zepeng ZHAO ; Zongyuan LI ; Qinglong YU ; Tao ZHANG ; Jinyuan TANG ; Nan YE ; Han XU ; Bo SHI
Chinese Journal of Tissue Engineering Research 2026;30(3):626-633
BACKGROUND:The most common complication of traumatic femoral neck fractures after internal fixation is femoral head necrosis.Currently,many studies have reported on the risk factors that affect the occurrence and development of postoperative femoral head necrosis,but there is still a lack of tools to predict the risk of femoral head necrosis after internal fixation of femoral neck fractures.OBJECTIVE:To develop a predictive model that estimates the risk of femoral head necrosis shortly after patients with femoral neck fractures receive cannulated screw internal fixation.METHODS:A retrospective analysis reviewed clinical records of 172 patients who underwent cannulated screw internal fixation for femoral neck fractures at Department of Orthopedics of Mianyang Central Hospital from January 2013 to June 2023.Patients were categorized into two groups based on the presence or absence of femoral head necrosis within one year post-operation:the necrosis group and the non-necrosis group.Univariate analysis,Lasso regression,and multivariate Logistic regression techniques were employed to identify the determinants of femoral head necrosis.A nomogram prediction model was constructed using R language's"rms"package,version 4.0.The receiver operating characteristic curve was used to evaluate the discriminatory ability of the model.The Hosmer-Lemeshow test was used to evaluate the goodness of fit of the model,and the decision curve analysis was used to determine its clinical application benefits.Internal validation of the study was conducted using the Bootstrap method,involving 1 000 repeated samplings.To delve deeper into the primary factors influencing femoral head necrosis post-internal fixation of the femoral neck,this paper employed the SHAP method for data set analysis.RESULTS AND CONCLUSION:(1)The risk factors leading to femoral head necrosis in the short term after cannulated screw fixation of femoral neck fractures include:smoking,diabetes,Garden classification,fracture line location,reduction quality,age,and operation time.(2)The prediction model demonstrated robust performance,evidenced by an area under the curve of 0.940(95%Confidence Interval:0.903 to 0.977),indicating a high level of prediction accuracy.The model achieved a sensitivity of 90.2%and a specificity of 87.6%,indicating that its diagnostic performance was stable.The Hosmer-Lemeshow goodness-of-fit test yielded a chi-square value of 6.593 with a P-value of 0.581,confirming that the model's predictions closely align with the observed outcomes.(3)The calibration curve of the model also performed well,and its overall trend was very close to the ideal curve,further proving the high accuracy of the model.(4)The internal validation was carried out by the Bootstrap method with 1 000 repeated samplings,and the area under the curve of the model internal validation was still as high as 0.939,proving that the model had good stability.(5)Through the decision curve,it is found that within the probability threshold range of 1%to 92%,the model can obtain the maximum net benefit value.(6)The SHAP analysis results show that among the risk factors analyzed in this study,the location of the fracture line serves as the most significant predictor of femoral head necrosis following internal fixation with cannulated screws in femoral neck fractures,and subcapital fractures are extremely prone to femoral head necrosis after surgery.(7)It is concluded that the validated prediction model demonstrates strong discriminative power and reliability,offering practical clinical utility.It serves as a useful reference tool for short-term risk assessment of femoral head necrosis following internal fixation of femoral neck fractures.
5.Clinical significance of establishing a red blood cell alloantibody detection database
Xiao XIAO ; Long CHEN ; Zhenyu ZHAO ; Zhanghan HE ; Mengjun ZHOU ; Jie TANG
Chinese Journal of Blood Transfusion 2025;38(1):54-60
[Objective] To explore the clinical significance and application value of establishing a database for red blood cell alloantibody detection. [Methods] Patients who were scheduled for blood transfusion in our hospital from January 1, 2020 to May 1, 2024 were selected as the research subjects. A red blood cell alloantibody detection database was established using Microsoft Office Excel software to register the detection data of patients' alloantibodies and antibodies of undetermined specificity (AUS). A retrospective analysis was conducted on the clinical characteristics, antibody distribution, antibody decay and repeat positivity of the patients in the database. The LISS-IAT method was routinely used for antibody screening and identification. [Results] Among the alloantibodies, the Rh blood group system had the highest detection rate, followed by antibodies of the MNS blood group system and the Lewis blood group system. The predominant antibody in the Rh blood group system was anti-E. In the univariate analysis, the positivity of antibody was significantly associated with the patient's gender, age, blood transfusion history, pregnancy history and type of disease (all P<0.001). In the database, 48 patients experienced antibody decay, accounting for 15.24%(48/315), with an average time span of antibody decay ranging from 22 to 1 324 days. Six cases showed repeat positivity after decay, which were related to blood transfusions. The shortest interval between blood transfusions that led to antibody repeat positivity was 3 days, and the longest interval was 427 days. Among 58 cases with AUS, 3 converted into alloantibodies, among which 2 were anti-E and 1 was anti-Lea. [Conclusion] Establishing a red blood cell alloantibody detection database is an effective way to guide ambiguous cross-matching in clinical practice and is also an effective measure for the management of transfusion risks.
6.Role of SMYD3-mediated histone H3K4me3 modification in pulmonary vascular remodeling in PAH-ASD rats
Shan LONG ; Shuqi WU ; Chang PENG ; Ting TANG ; Lianmei CHEN ; Li WANG
Chinese Journal of Pathophysiology 2025;41(9):1685-1693
AIM:To investigate the role of SET and MYND domain-containing protein 3(SMYD3)-mediated histone H3 lysine 4 trimethylation(H3K4me3)dysregulation in pulmonary vascular remodeling in a rat model of pulmo-nary arterial hypertension associated with atrial septal defect(PAH-ASD).METHODS:The PAH-ASD rat model was created using transseptal puncture and radiofrequency ablation techniques.The rats were randomly assigned to 5 groups:normal,sham,PAH-ASD,PAH-ASD+vehicle(Veh),and PAH-ASD+BCI-121(SMYD3 inhibitor).Four weeks after modeling,lung tissues and pulmonary vessels were harvested for subsequent analysis.Western blot analysis was conducted to evaluate the protein levels of SMYD3,H3K4me3,transforming growth faction-β1(TGF-β1),and collagen type Ⅲ(Col Ⅲ).The mRNA expression of TGF-β1 was quantified using RT-qPCR.Histological assessment of pulmonary vascu-lar fibrosis,vascular wall thickness and smooth muscle proliferation was executed through Masson's trichrome and HE staining.Co-immunoprecipitation(Co-IP)assay was performed to investigate the interactions among SMYD3,H3K4me3,and TGF-β1.Hemodynamic parameters,including mean pulmonary artery pressure(mPAP),were quantified using a computerized physiological signal acquisition system.RESULTS:The Western blot analysis indicated a significant in-crease in the protein levels of SMYD3,TGF-β1,Col Ⅲ,and H3K4me3 in the PAH-ASD group compared with the sham group(P<0.05).RT-qPCR corroborated the elevation of TGF-β1 mRNA expression in the PAH-ASD group(P<0.05).Furthermore,Masson's trichrome and HE staining techniques revealed more pronounced pulmonary vascular fibrosis,an augmented vascular wall area,and an elevated vascular area index within the PAH-ASD group(P<0.05).Additionally,the right ventricular hypertrophy index(RVHI)and mPAP were significantly elevated in the PAH-ASD group(P<0.05).The administration of BCI-121 resulted in a significant reduction of SMYD3,TGF-β1,Col Ⅲ,and H3K4me3 levels(P<0.05),while also mitigating pulmonary vascular fibrosis,RVHI,mPAP,pulmonary vascular area,and area index(P<0.05).Co-IP confirmed direct interactions among SMYD3,H3K4me3,and TGF-β1.CONCLUSION:Histone methyl-transferase SMYD3-mediated histone H3K4me3 modification plays a role in the pulmonary vascular remodeling of PAH-ASD model rats.The underlying mechanism may involve the regulation of pulmonary vascular proliferation and fibrosis me-diated by the overexpression of TGF-β1 and Col Ⅲ.
7.High-altitude hypoxia inhibits PPAR pathway induced ferroptosis in spleen of mice
Jiayang WANG ; Ying HU ; Yuzhen XU ; Qifu LONG ; Chaoqun TANG ; Sheng YONG
Chinese Journal of Immunology 2025;41(2):263-270
Objective:To explore molecular mechanism of high-altitude hypoxia regulates PPAR signaling pathway induced ferroptosis in spleen.Methods:Hypoxia animal model was constructed,target genes were screened and predicted by combination of transcriptomics and protein omics.Key genes in PPAR and ferroptosis pathways under hypoxia exposure were explored by GO and KEGG enrichment analysis and verified by RT-qPCR and Western blot.Results:Combination of transcriptomics and protein omics showed that 95 predicted target genes(protein)showed significantly differential expression under hypoxic exposure.GO annotation analysis and KEGG enrichment analysis showed that differential genes were mainly significantly enriched in PPAR and ferroptosis signaling pathways.A negative correlation was found between PPAR and ferroptosis signaling pathways,and GSEA showed that differential gene sets of PPAR and ferroptosis signaling pathways exhibited opposite expression trend in high-altitude hypoxia group.Validation of key genes PPARA,RXRB,APOA1 and SCD-1 in PPAR signaling pathway revealed that both mRNA and protein expres-sions were down-regulated under hypoxic exposure.Subsequently,differential expression was observed in mRNA and protein expres-sions of GPX4 in endogenous pathway and SLC7A11,TRP53 and TFRC in exogenous pathway in ferroptosis signaling pathway.Corre-lations between four key genes for ferroptosis and differential inflammation-associated genes(DE-IRGs)were positively or negatively.IL-1β,IL-6,IL-12,IL-18,IFN-γ and TNF-α expressions in spleen tissue were up-regulated under hypoxic exposure.Conclusion:High-altitude hypoxia exposure further induces ferroptosis through PPAR signaling pathway-mediated lipid metabolism disorders,and accompanied by occurrence of inflammatory response,which causes damage of spleen tissue.
8.ACtriplet:An improved deep learning model for activity cliffs prediction by integrating triplet loss and pre-training
Xinxin YU ; Yimeng WANG ; Long CHEN ; Weihua LI ; Yun TANG ; Guixia LIU
Journal of Pharmaceutical Analysis 2025;15(8):1837-1847
Activity cliffs(ACs)are generally defined as pairs of similar compounds that only differ by a minor structural modification but exhibit a large difference in their binding affinity for a given target.ACs offer crucial insights that aid medicinal chemists in optimizing molecular structures.Nonetheless,they also form a major source of prediction error in structure-activity relationship(SAR)models.To date,several studies have demonstrated that deep neural networks based on molecular images or graphs might need to be improved further in predicting the potency of ACs.In this paper,we integrated the triplet loss in face recognition with pre-training strategy to develop a prediction model ACtriplet,tailored for ACs.Through extensive comparison with multiple baseline models on 30 benchmark datasets,the results showed that ACtriplet was significantly better than those deep learning(DL)models without pre-training.In addition,we explored the effect of pre-training on data representation.Finally,the case study demonstrated that our model's interpretability module could explain the prediction results reasonably.In the dilemma that the amount of data could not be increased rapidly,this innovative framework would better make use of the existing data,which would propel the potential of DL in the early stage of drug discovery and optimization.
9.Oxymatrine,a novel TLR2 agonist,promotes megakaryopoiesis and thrombopoiesis through the STING/NF-κB pathway
Chengyang NI ; Ling ZHOU ; Shuo YANG ; Mei RAN ; Jiesi LUO ; Kui CHENG ; Feihong HUANG ; Xiaoqin TANG ; Xiang XIE ; Dalian QIN ; Qibing MEI ; Long WANG ; Juan XIAO ; Jianming WU
Journal of Pharmaceutical Analysis 2025;15(1):208-229
Radiation-induced thrombocytopenia(RIT)faces a perplexing challenge in the clinical treatment of cancer patients,and current therapeutic approaches are inadequate in the clinical settings.In this research,oxy-matrine,a new molecule capable of healing RIT was screened out,and the underlying regulatory mecha-nism associated with magakaryocyte(MK)differentiation and thrombopoiesis was demonstrated.The capacity of oxymatrine to induce MK differentiation was verified in K-562 and Meg-01 cells in vitro.The ability to induce thrombopoiesis was subsequently demonstrated in Tg(cd41:enhanced green fluorescent protein(eGFP))zebrafish and RIT model mice.In addition,we carried out network pharmacological pre-diction,drug affinity responsive target stability assay(DARTS)and cellular thermal shift assay(CETSA)analyses to explore the potential targets of oxymatrine.Moreover,the pathway underlying the effects of oxymatrine was determined by Kyoto Encyclopedia of Genes and Genomes(KEGG)enrichment analyses,Western blot(WB),and immunofluorescence.Oxymatrine markedly promoted MK differentiation and maturation in vitro.Moreover,oxymatrine induced thrombopoiesis in Tg(cd41:eGFP)zebrafish and accelerated thrombopoiesis and platelet function recovery in RIT model mice.Mechanistically,oxymatrine directly binds to toll-like receptor 2(TLR2)and further regulates the downstream pathway stimulator of interferon genes(STING)/nuclear factor-kappaB(NF-κB),which can be blocked by C29 and C-176,which are specific inhibitors of TLR2 and STING,respectively.Taken together,we demonstrated that oxymatrine,a novel TLR2 agonist,plays a critical role in accelerating MK differentiation and thrombopoiesis via the STING/NF-κB axis,suggesting that oxymatrine is a promising candidate for RIT therapy.
10.Applications of Three-dimensional Facial Features in Disease Diagnosis and Treatment
Jiaqi QIANG ; Jiuzuo HUANG ; Xin TANG ; Hui PAN ; Xiao LONG ; Shi CHEN
Medical Journal of Peking Union Medical College Hospital 2025;16(6):1519-1526
With the improvement in the accuracy and portability of three-dimensional facial imaging de-vices,and the rapid development of medical image recognition technology in artificial intelligence,the analysis and automatic recognition of three-dimensional facial characteristics of diseases have been widely applied in multiple fields such as endocrine metabolic disorders,chronic respiratory diseases,neuromuscular diseases,ge-netic syndromes,and plastic surgery.We aim to systematically review and summarize the current research status and development trends of three-dimensional facial photogrammetry and image analysis techniques in disease di-agnosis,assessment of prognosis and treatment efficacy,in order to provide references and insights for scientific research and clinical applications of this field.

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