Glioma, the most prevalent primary tumor of the central nervous system (CNS), is also the most lethal primary malignant tumor. Currently, there are limited chemotherapeutics available for glioma treatment, necessitating further research to identify and develop new chemotherapeutic agents. A significant approach to discovering anti-glioma drugs involves isolating antitumor active ingredients from natural products (NPs) and optimizing their structures. Additionally, targeted drug delivery systems (TDDSs) are employed to enhance drug solubility and stability and overcome the blood-brain barrier (BBB). TDDSs can penetrate deep into the brain, increase drug concentration and retention time in the CNS, and improve the targeting efficiency of NPs, thereby reducing adverse effects and enhancing anti-glioma efficacy. This paper reviews the research progress of anti-glioma activities of NPs, including alkaloids, polyphenols, flavonoids, terpenoids, saponins, quinones, and their synthetic derivatives over the past decade. The review also summarizes anti-glioma mechanisms, such as suppression of related protein expression, regulation of reactive oxygen species (ROS) levels, control of apoptosis signaling pathways, reduction of matrix metalloproteinases (MMPs) expression, blocking of vascular endothelial growth factor (VEGF), and reversal of immunosuppression. Furthermore, the functions and advantages of NP-based TDDSs in anti-glioma therapy are examined. The key information presented in this review will be valuable for the research and development of NP-based anti-glioma drugs and related TDDSs.
Humans ; Glioma/metabolism* ; Biological Products/therapeutic use* ; Animals ; Brain Neoplasms/genetics* ; Drug Delivery Systems ; Antineoplastic Agents/therapeutic use* ; Blood-Brain Barrier/metabolism* ; Apoptosis/drug effects*

Objective:To investigate the molecular markers involved in death related to acute myocardial infarction (AMI) and provide new targets for early intervention.Methods:Consecutive patients who hospitalized in department of cardiology, Xuanwu Hospital, Capital Medical University from January 2017 to December 2021 and diagnosed with AMI were enrolled. The clinical factors and markers associated with in-hospital death after AMI were analyzed. In addition, patients diagnosed with AMI hospitalized in department of cardiology, Xuanwu Hospital, Capital Medical University from September 2022 to April 2023 were enrolled. We prospectively analyzed the plasma protein of death related to AMI via Olink Precision Proteomics based on proximity extension assay (PEA) technology.Results:In the retrospective study, 2 325 patients with AMI were analyzed, including 75 patients in the in-hospital death group and 2 250 subjects in the survival group. The overall mortality rate during hospitalization was 3.23% (75/2325). The patients in the death group were older: 72 (64, 80) years vs. 63 (55, 71) years. And Interleukin-6 (IL-6), hypersensitive C-reactive protein (Hs-CRP), leukocyte counts and neutrophil counts were markedly higher in the death group than those in the survival group: 69.0 (26.7, 136.6) ng/L vs. 18.2 (9.4, 36.5) ng/L, 45.7 (28.7, 50.5) mg/L vs. 5.5 (2.0, 17.2) mg/L, 12.0 (9.8, 14.1) ×10 9/L vs. 8.9 (7.2, 11.2) × 10 9/L, 9.8 (7.8, 12.1) ×10 9/L vs. 6.5(4.7, 8.8) ×10 9/L ( P<0.01). In this prospective study, 86 patients with AMI were analyzed. 61 proteins including Insulin-like growth factor-binding protein 1, 2 (IGFBP-1, IGFBP-2), Chitotriosidase-1 (CHIT1), Complement component C1q receptor (CD93) were independently associated with in-hospital death related to AMI ( P<0.05). The differential proteins were mainly enriched in inflammatory response, cell adhesion, cytokine signaling pathway and apoptosis. Moreover, 22 proteins including Urokinase plasminogen activator surface receptor (U-PAR), Trefoil factor 3 (TFF3), Perlecan (PLC), Growth differentiation factor 15 (GDF-15), Junctional adhesion molecule A (JAM-A) were plotted according to a logistic regression model, and the area under the curve (AUC) was more than 0.9, showing the high accuracy in predicting in-hospital death after AMI. Conclusions:Molecular markers of the inflammatory response, cell adhesion, cell growth and apoptosis might be involved in death related to AMI, which provides new targets for early intervention.

Maxillofacial fractures are common and frequently occurring diseases in Oral and Maxillofacial Surgery.The traditional clinical diagnosis and treatment process is easily affected by complex maxillofacial anatomy and differences in doctors' experience in reading X-rays and making diagnoses.In recent years,artificial intelligence technology has provided new solutions for the accurate diag-nosis and treatment planning of maxillofacial fractures.Automating image analysis through computer vision methods improves diagnostic accuracy and efficiency and assists in formulating treatment plans,showing broad application prospects and value.This article reviews and summarizes the research on the application of artificial intelligence in the auxiliary diagnosis and treatment of maxillofacial fractures at home and abroad,analyzes its advantages and disadvantages,and looks forward to future research trends.

Objective To investigate the clinical features of autonomic seizures in adults， and to improve the awareness， diagnosis， and treatment of this disease. Methods The clinical features of 10 adult patients with autonomic seizures were summarized， including 1 case from our hospital and 9 cases from the PubMed database. Results The age of onset of the 10 patients ranged from 19 to 70 years， and clinical symptoms included tachycardia， gastrointestinal symptoms， sweating， and general discomfort. Of all patients， 3 had autonomic status epilepticus and 7 had recurrent autonomic seizures. The etiology of this disease included cerebral infarction， meningioma， autoimmune encephalitis， and traumatic brain injury. EEG showed the presence of slow wave， sharp wave， θ wave or δ wave. Antiepileptic treatment was effective. Conclusion For adults with autonomic seizures， especially those with status epilepticus， EEG and radiological examination showed be performed actively， and antiepileptic treatment should be given in a timely manner.

Objective:To investigate the control status of out-of-hospital blood glucose and blood lipids in patients with acute myocardial infarction (AMI) complicated with diabetes mellitus and its correlation with prognosis.Methods:The clinical data of 406 patients with AMI complicated with diabetes mellitus from January 2017 to December 2022 in Xuanwu Hospital, Capital Medical University were retrospectively analyzed. The demographic and out-of-hospital clinical information of patients were recorded, and the control level of out-of-hospital risk factors and the occurrence of major adverse cardiovascular event (MACCE) were also recorded. The patients were grouped according to the levels of glycosylated hemoglobin (HbA 1c) and low-density lipoprotein cholesterol (LDL-C). HbA 1c<6.0% was the low HbA 1c group, HbA 1c 6.0% to 7.0% was the medium HbA 1c group, and HbA 1c>7.0% was the high HbA 1c group; LDL-C<1.4 mmol/L was low LDL-C group, LDL-C 1.4 to 1.8 mmol/L was medium LDL-C group, and LDL-C>1.8 mmol/L was high LDL-C group. Multivariate Cox regression analysis was used to analyze the independent risk factors for out-of-hospital MACCE in patients with AMI complicated with diabetes mellitus. Results:The HbA 1c data of 249 patients were recorded in detail, and only 51.0% (127/249) of patients with HbA 1c≤7%. There were statistical differences in the history of cerebral infarction, out-of-hospital fasting blood glucose, out-of-hospital total cholesterol (TC) and out-of-hospital LDL-C among the low HbA 1c group (24 cases), medium HbA 1c group (103 cases) and high HbA 1c group (122 cases) ( P<0.05). The incidences of out-of-hospital MACCE in low HbA 1c group, medium HbA 1c group and high HbA 1c group were 20.8%(5/24), 12.6%(13/103) and 32.0%(39/122), respectively. The incidence of out-of-hospital MACCE in high HbA 1c group was significantly higher than that in medium HbA 1c group, and there was statistical difference ( P<0.05); there was no statistical difference between low HbA 1c group and high HbA 1c group ( P>0.05). Among the 406 patients, 53.4%(217/406) had LDL-C≤1.8 mmol/L, and only 20.0%(81/406) had LDL-C<1.4 mmol/L. There were statistical differences in hyperlipidemia, out-of-hospital HbA 1c, out-of-hospital fasting blood glucose, out-of-hospital alanine aminotransferase (ALT), out-of-hospital TC and out-of-hospital triglyceride (TG) among low LDL-C group (81 cases), medium LDL-C group (136 cases) and high LDL-C group (189 cases) ( P<0.05). The incidences of MACCE in low LDL-C group, medium LDL-C group and high LDL-C group were 18.5% (15/81), 25.7% (35/136) and 36.5% (69/189), respectively. The incidence of MACCE in high LDL-C group was significantly higher than that in low LDL-C group, and there was statistical difference ( P<0.05); there was no statistical difference between low LDL-C group and medium LDL-C group ( P>0.05). In the different HbA 1c groups, multivariate Cox regression analysis result showed that HbA 1c>7% and high out-of-hospital fasting blood glucose were independent risk factors for out-of-hospital MACCE in patients with AMI complicated with diabetes mellitus ( OR = 2.575 and 1.064, 95% CI 1.345 to 4.927 and 1.005 to 1.128, P<0.01 and <0.05). In different LDL-C groups, multivariate Cox regression analysis result showed that high out-of-hospital HbA 1c was an independent risk factor for out-of-hospital MACCE in patients with AMI complicated with diabetes mellitus ( OR = 1.303, 95% CI 1.144 to 1.485, P<0.01). Conclusions:The control rates of out-of-hospital blood glucose and blood lipids are low in patients with AMI complicated with diabetes mellitus, and HbA 1c level can independently predict the risk of out-of-hospital MACCE in patients with AMI complicated with diabetes mellitus.

Objective:To investigate the correlation of neutrophil-to-albumin ratio (NAR) and glucose-to-lymphocyte ratio (GLR) with in-hospital death in patients with acute myocardial infarction (AMI).Methods:The clinical data of 2 657 patients with AMI from January 2017 to December 2022 in Xuanwu Hospital, Capital Medical University were retrospectively analyzed. Using receiver operating characteristic (ROC) curve to determine the optimal cutoff values of GLR and NAR (6.02 and 0.25) for predicting in-hospital mortality in patients with AMI, the patients were divided into high GLR group (GLR≥6.02, 768 cases) and low GLR group (GLR<6.02, 1 889 cases), high NAR group (NAR≥0.25, 547 cases) and low NAR group (NAR<0.25, 2 110 cases) according the optimal cutoff values. The baseline characteristics and occurrence of in-hospital major adverse cardiovascular events (MACE) were recorded. Multivariate Logistic regression was used to analyze the independent risk factors for in-hospital death in patients with AMI.Results:Among the 2 657 patients with AMI, 265 patients had in-hospital MACE (10.0%), and 50 patients (1.9%) died. The age, proportion of Killip≥ 2 grade, proportion of diabetes, proportion of myocardial infarction, proportion of cerebral infarction history, proportion of ST-elevation myocardial infarction (STEMI), thrombolysis in myocardial infarction clinical trial score (TIMI score), global registry of acute coronary event score (GRACE score), fibrinogen, fasting blood glucose, glycated hemoglobin, high-density lipoprotein cholesterol (HDL-C), cardiac troponin I (cTnI) peak, N-terminal B-type natriuretic peptide (NT-proBNP), hypersensitive C-reactive protein (hs-CRP), interleukin-6 (IL-6), NAR, GLR, neutrophil count, left ventricular end-diastolic diameter (LVEDD) in high GLR group were significantly higher than those in low GLR group, the proportion of males, body mass index (BMI), proportion of smoking history, proportion of non-ST elevation myocardial infarction (NSTEMI), albumin, estimated glomerular filtration rate (eGFR), total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), triglyceride (TG), lymphocyte count, monocyte count and left ventricular ejection fraction (LVEF) were significantly lower than those in low GLR group, and there were statistical differences ( P<0.01 or <0.05). The proportion of Killip≥2 grade, proportion of STEMI, TIMI score, GRACE score, fibrinogen, fasting blood glucose, TC, LDL-C, cTnI peak, hs-CRP, IL-6, NAR, GLR, white blood cell count, neutrophil count and monocyte count in high NAR group were significantly higher than those in low NAR group, the age, proportion of myocardial infarction history, proportion of NSTEMI, albumin, lymphocyte count, left atrial diameter (LAD) and LVEF were significantly lower than those in low NAR group, and there were statistical differences ( P<0.01 or <0.05). The incidences of in-hospital MACE, death, ventricular fibrillation or pulseless ventricular tachycardia, atrial fibrillation, cardiac arrest and bleeding in high GLR group were significant higher than those in low GLR group: 15.2% (117/768) vs. 7.8% (148/1 889), 4.6% (35/768) vs. 0.8% (15/1 889), 5.3% (41/768) vs. 2.9% (54/1 889), 6.9% (53/768) vs. 4.0% (75/1 889), 4.7% (36/768) vs. 1.4% (26/1 889) and 2.3% (18/768) vs. 0.7% (13/1 889), and there were statistical differences ( P<0.01); there was no statistical difference in the incidence of heart rupture between two groups ( P>0.05). The incidence of in-hospital MACE, death, ventricular fibrillation or pulseless ventricular tachycardia, cardiac arrest, cardiac rupture and bleeding in high NAR group were significantly higher than those in low NAR group: 16.6% (91/547) vs. 8.2% (174/2 110), 5.9% (32/547) vs. 0.9% (18/2 110), 8.0% (44/547) vs. 2.4% (51/2 110), 5.9% (32/547) vs. 1.4% (30/2 110), 1.6% (9/547) vs. 0.4% (9/2 110) and 2.4% (13/547) vs. 0.9% (18/2 110), and there were statistical differences ( P<0.01); there was no statistical difference in the incidence of atrial fibrillation between two groups ( P>0.05). Multivariate Logistic regression analysis result showed that the Killip 3 and 4 grades, high NAR, high GRACE score, high fasting glucose and low LVEF were independent risk factors for in-hospital death in patients with AMI ( OR = 3.827, 4.660, 3.779, 1.020, 1.095 and 0.962; 95% CI 1.158 to 12.649, 1.184 to 18.344, 1.856 to 7.649, 1.009 to 1.032, 1.027 to 1.167 and 0.932 to 0.993; P<0.05 or <0.01). Conclusions:The NAR can independently predict the risk of in-hospital death in patients with AMI.

Objective:To investigate the control status of out-of-hospital blood glucose and blood lipids in patients with acute myocardial infarction (AMI) complicated with diabetes mellitus and its correlation with prognosis.Methods:The clinical data of 406 patients with AMI complicated with diabetes mellitus from January 2017 to December 2022 in Xuanwu Hospital, Capital Medical University were retrospectively analyzed. The demographic and out-of-hospital clinical information of patients were recorded, and the control level of out-of-hospital risk factors and the occurrence of major adverse cardiovascular event (MACCE) were also recorded. The patients were grouped according to the levels of glycosylated hemoglobin (HbA 1c) and low-density lipoprotein cholesterol (LDL-C). HbA 1c<6.0% was the low HbA 1c group, HbA 1c 6.0% to 7.0% was the medium HbA 1c group, and HbA 1c>7.0% was the high HbA 1c group; LDL-C<1.4 mmol/L was low LDL-C group, LDL-C 1.4 to 1.8 mmol/L was medium LDL-C group, and LDL-C>1.8 mmol/L was high LDL-C group. Multivariate Cox regression analysis was used to analyze the independent risk factors for out-of-hospital MACCE in patients with AMI complicated with diabetes mellitus. Results:The HbA 1c data of 249 patients were recorded in detail, and only 51.0% (127/249) of patients with HbA 1c≤7%. There were statistical differences in the history of cerebral infarction, out-of-hospital fasting blood glucose, out-of-hospital total cholesterol (TC) and out-of-hospital LDL-C among the low HbA 1c group (24 cases), medium HbA 1c group (103 cases) and high HbA 1c group (122 cases) ( P<0.05). The incidences of out-of-hospital MACCE in low HbA 1c group, medium HbA 1c group and high HbA 1c group were 20.8%(5/24), 12.6%(13/103) and 32.0%(39/122), respectively. The incidence of out-of-hospital MACCE in high HbA 1c group was significantly higher than that in medium HbA 1c group, and there was statistical difference ( P<0.05); there was no statistical difference between low HbA 1c group and high HbA 1c group ( P>0.05). Among the 406 patients, 53.4%(217/406) had LDL-C≤1.8 mmol/L, and only 20.0%(81/406) had LDL-C<1.4 mmol/L. There were statistical differences in hyperlipidemia, out-of-hospital HbA 1c, out-of-hospital fasting blood glucose, out-of-hospital alanine aminotransferase (ALT), out-of-hospital TC and out-of-hospital triglyceride (TG) among low LDL-C group (81 cases), medium LDL-C group (136 cases) and high LDL-C group (189 cases) ( P<0.05). The incidences of MACCE in low LDL-C group, medium LDL-C group and high LDL-C group were 18.5% (15/81), 25.7% (35/136) and 36.5% (69/189), respectively. The incidence of MACCE in high LDL-C group was significantly higher than that in low LDL-C group, and there was statistical difference ( P<0.05); there was no statistical difference between low LDL-C group and medium LDL-C group ( P>0.05). In the different HbA 1c groups, multivariate Cox regression analysis result showed that HbA 1c>7% and high out-of-hospital fasting blood glucose were independent risk factors for out-of-hospital MACCE in patients with AMI complicated with diabetes mellitus ( OR = 2.575 and 1.064, 95% CI 1.345 to 4.927 and 1.005 to 1.128, P<0.01 and <0.05). In different LDL-C groups, multivariate Cox regression analysis result showed that high out-of-hospital HbA 1c was an independent risk factor for out-of-hospital MACCE in patients with AMI complicated with diabetes mellitus ( OR = 1.303, 95% CI 1.144 to 1.485, P<0.01). Conclusions:The control rates of out-of-hospital blood glucose and blood lipids are low in patients with AMI complicated with diabetes mellitus, and HbA 1c level can independently predict the risk of out-of-hospital MACCE in patients with AMI complicated with diabetes mellitus.

Objective:To investigate the correlation of neutrophil-to-albumin ratio (NAR) and glucose-to-lymphocyte ratio (GLR) with in-hospital death in patients with acute myocardial infarction (AMI).Methods:The clinical data of 2 657 patients with AMI from January 2017 to December 2022 in Xuanwu Hospital, Capital Medical University were retrospectively analyzed. Using receiver operating characteristic (ROC) curve to determine the optimal cutoff values of GLR and NAR (6.02 and 0.25) for predicting in-hospital mortality in patients with AMI, the patients were divided into high GLR group (GLR≥6.02, 768 cases) and low GLR group (GLR<6.02, 1 889 cases), high NAR group (NAR≥0.25, 547 cases) and low NAR group (NAR<0.25, 2 110 cases) according the optimal cutoff values. The baseline characteristics and occurrence of in-hospital major adverse cardiovascular events (MACE) were recorded. Multivariate Logistic regression was used to analyze the independent risk factors for in-hospital death in patients with AMI.Results:Among the 2 657 patients with AMI, 265 patients had in-hospital MACE (10.0%), and 50 patients (1.9%) died. The age, proportion of Killip≥ 2 grade, proportion of diabetes, proportion of myocardial infarction, proportion of cerebral infarction history, proportion of ST-elevation myocardial infarction (STEMI), thrombolysis in myocardial infarction clinical trial score (TIMI score), global registry of acute coronary event score (GRACE score), fibrinogen, fasting blood glucose, glycated hemoglobin, high-density lipoprotein cholesterol (HDL-C), cardiac troponin I (cTnI) peak, N-terminal B-type natriuretic peptide (NT-proBNP), hypersensitive C-reactive protein (hs-CRP), interleukin-6 (IL-6), NAR, GLR, neutrophil count, left ventricular end-diastolic diameter (LVEDD) in high GLR group were significantly higher than those in low GLR group, the proportion of males, body mass index (BMI), proportion of smoking history, proportion of non-ST elevation myocardial infarction (NSTEMI), albumin, estimated glomerular filtration rate (eGFR), total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), triglyceride (TG), lymphocyte count, monocyte count and left ventricular ejection fraction (LVEF) were significantly lower than those in low GLR group, and there were statistical differences ( P<0.01 or <0.05). The proportion of Killip≥2 grade, proportion of STEMI, TIMI score, GRACE score, fibrinogen, fasting blood glucose, TC, LDL-C, cTnI peak, hs-CRP, IL-6, NAR, GLR, white blood cell count, neutrophil count and monocyte count in high NAR group were significantly higher than those in low NAR group, the age, proportion of myocardial infarction history, proportion of NSTEMI, albumin, lymphocyte count, left atrial diameter (LAD) and LVEF were significantly lower than those in low NAR group, and there were statistical differences ( P<0.01 or <0.05). The incidences of in-hospital MACE, death, ventricular fibrillation or pulseless ventricular tachycardia, atrial fibrillation, cardiac arrest and bleeding in high GLR group were significant higher than those in low GLR group: 15.2% (117/768) vs. 7.8% (148/1 889), 4.6% (35/768) vs. 0.8% (15/1 889), 5.3% (41/768) vs. 2.9% (54/1 889), 6.9% (53/768) vs. 4.0% (75/1 889), 4.7% (36/768) vs. 1.4% (26/1 889) and 2.3% (18/768) vs. 0.7% (13/1 889), and there were statistical differences ( P<0.01); there was no statistical difference in the incidence of heart rupture between two groups ( P>0.05). The incidence of in-hospital MACE, death, ventricular fibrillation or pulseless ventricular tachycardia, cardiac arrest, cardiac rupture and bleeding in high NAR group were significantly higher than those in low NAR group: 16.6% (91/547) vs. 8.2% (174/2 110), 5.9% (32/547) vs. 0.9% (18/2 110), 8.0% (44/547) vs. 2.4% (51/2 110), 5.9% (32/547) vs. 1.4% (30/2 110), 1.6% (9/547) vs. 0.4% (9/2 110) and 2.4% (13/547) vs. 0.9% (18/2 110), and there were statistical differences ( P<0.01); there was no statistical difference in the incidence of atrial fibrillation between two groups ( P>0.05). Multivariate Logistic regression analysis result showed that the Killip 3 and 4 grades, high NAR, high GRACE score, high fasting glucose and low LVEF were independent risk factors for in-hospital death in patients with AMI ( OR = 3.827, 4.660, 3.779, 1.020, 1.095 and 0.962; 95% CI 1.158 to 12.649, 1.184 to 18.344, 1.856 to 7.649, 1.009 to 1.032, 1.027 to 1.167 and 0.932 to 0.993; P<0.05 or <0.01). Conclusions:The NAR can independently predict the risk of in-hospital death in patients with AMI.

Maxillofacial fractures are common and frequently occurring diseases in Oral and Maxillofacial Surgery.The traditional clinical diagnosis and treatment process is easily affected by complex maxillofacial anatomy and differences in doctors' experience in reading X-rays and making diagnoses.In recent years,artificial intelligence technology has provided new solutions for the accurate diag-nosis and treatment planning of maxillofacial fractures.Automating image analysis through computer vision methods improves diagnostic accuracy and efficiency and assists in formulating treatment plans,showing broad application prospects and value.This article reviews and summarizes the research on the application of artificial intelligence in the auxiliary diagnosis and treatment of maxillofacial fractures at home and abroad,analyzes its advantages and disadvantages,and looks forward to future research trends.

Objective:To investigate the molecular markers involved in death related to acute myocardial infarction (AMI) and provide new targets for early intervention.Methods:Consecutive patients who hospitalized in department of cardiology, Xuanwu Hospital, Capital Medical University from January 2017 to December 2021 and diagnosed with AMI were enrolled. The clinical factors and markers associated with in-hospital death after AMI were analyzed. In addition, patients diagnosed with AMI hospitalized in department of cardiology, Xuanwu Hospital, Capital Medical University from September 2022 to April 2023 were enrolled. We prospectively analyzed the plasma protein of death related to AMI via Olink Precision Proteomics based on proximity extension assay (PEA) technology.Results:In the retrospective study, 2 325 patients with AMI were analyzed, including 75 patients in the in-hospital death group and 2 250 subjects in the survival group. The overall mortality rate during hospitalization was 3.23% (75/2325). The patients in the death group were older: 72 (64, 80) years vs. 63 (55, 71) years. And Interleukin-6 (IL-6), hypersensitive C-reactive protein (Hs-CRP), leukocyte counts and neutrophil counts were markedly higher in the death group than those in the survival group: 69.0 (26.7, 136.6) ng/L vs. 18.2 (9.4, 36.5) ng/L, 45.7 (28.7, 50.5) mg/L vs. 5.5 (2.0, 17.2) mg/L, 12.0 (9.8, 14.1) ×10 9/L vs. 8.9 (7.2, 11.2) × 10 9/L, 9.8 (7.8, 12.1) ×10 9/L vs. 6.5(4.7, 8.8) ×10 9/L ( P<0.01). In this prospective study, 86 patients with AMI were analyzed. 61 proteins including Insulin-like growth factor-binding protein 1, 2 (IGFBP-1, IGFBP-2), Chitotriosidase-1 (CHIT1), Complement component C1q receptor (CD93) were independently associated with in-hospital death related to AMI ( P<0.05). The differential proteins were mainly enriched in inflammatory response, cell adhesion, cytokine signaling pathway and apoptosis. Moreover, 22 proteins including Urokinase plasminogen activator surface receptor (U-PAR), Trefoil factor 3 (TFF3), Perlecan (PLC), Growth differentiation factor 15 (GDF-15), Junctional adhesion molecule A (JAM-A) were plotted according to a logistic regression model, and the area under the curve (AUC) was more than 0.9, showing the high accuracy in predicting in-hospital death after AMI. Conclusions:Molecular markers of the inflammatory response, cell adhesion, cell growth and apoptosis might be involved in death related to AMI, which provides new targets for early intervention.