Objective:To investigate the influence of prealbumin on cerebral infarction severity, hemorrhage transformation and 1-year prognosis.Methods:A retrospective study was conducted to select 752 patients with cerebral infarction who were treated in Beijing Tiantan Hospital,Capital Medical University from December 2018 to December 2019 as the study objects. Personal information and laboratory indicators of the patients were collected including prealbumin, hemoglobin, white blood cell count, etc.Patients were divided into group B1 (<238 mg/L) and group B2 (≥238 mg/L) based on median prealbumin. By inquiry patient's case, NIHSS score (<16 was classified as mild, ≥16 as moderate and severe)and cerebral infarction volume (<20 cm 3 as small infarct, >20 cm 3 as large infarct) were recorded to evaluate the severity of the disease, and whether hemorrhage transformation occurred during hospitalization was recorded. Patients were followed up 1 year after discharge, and prognostic information of patients was recorded, including neurological function recovery (mRS score <3 was classified as good recovery, ≥3 as poor recovery),all-cause case fatality rate, and recurrence of cardio-cerebrovascular events. Normally distributed measurement data were expressed as xˉ±s, non-normally distributed measurement data were expressed as median and quartiles[ M( Q1, Q3)], categorical variable were expressed as ratio and percent(%). Comparison between groups of measurement data were performed by independent sample t test and Mann-Whitney U test. Chi-square test were used on comparison between groups of categorical variable. Single-factor comparison, Spearman correlation analysis and multiple Logistic regression were used to analyze the correlation between prealbumin and other laboratory indicators, cerebral infarction severity, hemorrhage transformation and 1-year prognosis, respectively. Results:The NIHSS score and infarct volume of patients in group B1 were 5(2,10) and 3.18(0.72,18.00) cm 3, and those in group B2 were 3(2,7) and 2.0(0.5,10.0) cm 3, respectively, which were higher in group B1 than in group B2, the differences were statistically significant ( Z=3.85, P<0.001, Z=2.81, P=0.005). The proportion of mRS Score ≥3 in group B1 was 28.8%(107/371), and the all-cause case fatality rate was 7.5%(28/371), both higher than 20.5%(78/381) and 3.1%(12/381) in group B2, with statistical significance ( χ2=7.10, P=0.008, χ2=7.22, P=0.007). Hemorrhage transformation and recurrence of cardio-cerebrovascular events were 13.5%(50/371) and 11.6%(43/371) in group B1 and 9.2% (35/381) and 8.7%(33/381) in group B2, respectively, with no significant difference between the two groups ( χ2=3.45, P=0.063, χ2=1.78, P=0.183). Multivariate logistic regression analysis showed that, after adjusted for potential confounding factors, prealbumin was protective factor of NIHSS ( OR and 95% CI: 0.990(0.984-0.997), P=0.035), poor neurological recovery(mRS≥3) ( OR and 95% CI:0.992(0.988-0.997), P<0.001) and all-cause case fatality rate ( OR and 95% CI:0.991(0.983-0.999), while prealbumin had no significant influence on cardiocerebrovascular recurrence events ( OR and 95% CI: 0.999(0.993-1.005), P=0.729). Conclusion:Prealbumin is significantly associated with the severity of cerebral infarction and poor prognosis 1 year after discharge, and low prealbumin was an independent risk factor for NIHSS score(≥16), poor neurological recovery (mRS≥3) and all-cause case fatality rate.

Objectives:To explore the effects of infarct volume, infarct type, inflammation, and coagulation indicators on hemorrhagic transformation in patients with acute cerebral infarction.Methods:711 patients with cerebral infarction admitted to Beijing Tiantan Hospital were retrospectively included as the study objects from December 2018 to December 2019 [535 males and 176 females, age 22-95 years, mean age (59.6±12.1) years]. Clinical data, laboratory indicators such as inflammation and coagulation function of patients were collected, and information such as location, volume and type of infarction were recorded. The patients were divided into hemorrhage transformation group and non-hemorrhage transformation group according to whether hemorrhage transformation occurred during hospitalization. Normally distributed measurement data were expressed as xˉ± s, non-normally distributed measurement data were expressed as median and quartiles [ M( Q1, Q3)], categorical variable were expressed as ratio and percent (%). Comparison between groups of measurement data were performed by independent sample t test and Mann-Whitney U test. χ2 test were used on comparison between groups of categorical variable. Univariate comparison and multivariate Logistic regression were used to analyze the correlation between hemorrhage transformation and infarct volume, infarction type and laboratory indicators, respectively, to explore the risk factors of hemorrhage transformation. ROC curve analysis was used to evaluate the diagnostic value of indicators. Results:The rates of coronary heart disease and atrial fibrillation history in the hemorrhage transformation group were 23.5% (20/85) and 22.4% (19/85), respectively, which were significantly higher than those in the non-hemorrhage transformation group (13.9% (87/626) and 5.8% (36/626), respectively), and the difference between the two groups was statistically significant ( χ2=5.43, χ2=28.90, P=0.020, P<0.001, respectively). The NIHSS score [10(4,17) points] and infarct volume [46.50 (14.21,118.42) mL] in the hemorrhage transformation group were significantly higher than those in the non-hemorrhage transformation group [4(2,7) points, 2.00(0.51,8.94) mL]. The difference between the two groups was statistically significant ( Z values were 6.69 and 10.69, respectively, P<0.001). The results of multivariate Logistic regression analysis showed that atrial fibrillation (OR=2.604, 95% CI: 1.186-5.716, P=0.107), infarct volume (OR=1.009, 95% CI: 1.004-1.015, P=0.001), infarct type of Chinese ischemic stroke subclassfication (OR=1.371, 95% CI: 1.085-1.731, P=0.008) and neutrophil/lymphocyte ratio (OR=1.047, 95% CI: 1.006-1.090, P=0.023) were independent risk factors for hemorrhage transformation. ROC curve analysis showed that the area under curve (AUC) of infarct volume and neutrophil/lymphocyte ratio were 0.861 (0.821-0.901) and 0.684 (0.626-0.741), respectively, which were effective in predicting hemorrhage transformation after cerebral infarction. The prediction of infarct volume was more efficient. Conclusion:History of atrial fibrillation, classification of cardioembolic stroke, infarct volume, and neutrophil/lymphocyte ratio are all risk factors for hemorrhagic transformation after acute cerebral infarction.

BACKGROUND:Early diagnosis of pulmonary fibrosis is the foundation for timely antifibrotic drug therapy.Therefore,exploring and discovering ideal biomarkers that can be effectively used for the early diagnosis of pulmonary fibrosis is crucial for the treatment of the disease.OBJECTIVE:To conduct an in-depth analysis of key autophagy-related genes involved in the process of pulmonary fibrosis by means of bioinformatics and machine learning techniques,in order to investigate whether autophagy-related core genes of pulmonary fibrosis can be used as reliable biomarkers in the assessment of the progression of pulmonary fibrosis.METHODS:Two datasets of pulmonary fibrosis,GSE24206 and GSE110147,were downloaded from the Gene Expression Omnibus(GEO)database(a public database developed and maintained by the U.S.National Center for Biotechnology Information to store and share bioinformatics data),and the gene expression matrices of these two datasets were normalized by using the"limma"package in R software.The autophagy-related genes were extracted from GeneCards database(a database created by the U.S.National Center for Biotechnology Information,which automatically integrates gene-centric data from about 200 Web sources,including genomic,transcriptomic,proteomic,genetic,clinical,and functional information).Differential gene analysis was performed on the pulmonary fibrosis dataset,and the common genes were extracted by cross-comparing the differential genes with the autophagy genes,so as to identify autophagy genes that may play a role in the process of pulmonary fibrosis.The intersecting genes were analyzed for functional enrichment and cellular immune infiltration by gene ontology and Kyoto Encyclopedia of Genes and Genomes.Core genes of pulmonary fibrosis associated with autophagy were screened by protein-protein interactions and machine learning,and core genes were subjected to the enrichment analysis.Diagnostic models were constructed from the identified core genes.Calibration curves were used to assess the predictive ability of the line graph model.An external dataset,GSE21369,was used to perform a receiver operating characteristic curve analysis to validate the expression profiles of pulmonary fibrosis genes associated with autophagy,as well as to predict Chinese herbs associated with the genes IL6 and COL1A2 via the Coremine database.Finally,human embryonic lung fibroblasts were cultured and modelled by transforming growth factor-β1 treatment,and the relative expression of genes in the model cells was verified using qRT-PCR.RESULTS AND CONCLUSION:(1)A total of 51 pulmonary fibrosis differential genes and 25 genes intersecting with autophagy genes were obtained.Gene ontology analysis showed that the 25 intersecting genes were related to extracellular matrix tissue,collagen metabolism,collagen pro-fibroblasts,and growth factor binding,etc.The results of Kyoto Encyclopedia of Genes and Genomes enrichment analysis indicated that they were mainly related to the Phosphatidylinositol 3-kinase/protein kinase B signaling pathway and the signaling pathway of the extracellular matrix-receptor interactions.(2)Immunoinfiltration analysis revealed that the expression of activated memory CD4+T cells,M0 macrophages,and resting dendritic cells was significantly elevated in the pulmonary fibrosis group(P＜0.05),showing a strong correlation.(3)Two autophagy signature genes involved in the progression of pulmonary fibrosis were identified:COL1A2 and IL6.The column-line diagram model showed that the two core genes predicted the onset of pulmonary fibrosis more accurately,and the receiver operating characteristic curve analysis showed that the two characteristic genes had diagnostic significance.COL1A2 and IL6 were related to the cell-cycle pathway,mitogen-activated protein kinase signaling pathway,Janus kinase-signal transduction and activator of transcription signaling pathway and cytokine-cytokine receptor interactions.A total of 20 Chinese herbs were predicted to be related to COL1A2 and IL6 genes,and their efficacies were mainly to clear away heat and detoxify toxins and to invigorate blood and move qi.COL1A2 and IL6 were verified to be highly expressed in pulmonary fibrosis.To conclude,COL1A2 and IL6 may be potential diagnostic biomarkers for pulmonary fibrosis,but its specificity to pulmonary fibrosis needs to be further investigated.

Objective:To investigate the combined application of cytology, cell block histology and immunohistochemistry to improve the diagnostic accuracy of solid pancreatic lesions in endoscopic ultrasound-guided fine needle aspiration (EUS-FNA) samples.Methods:The pathological data of EUS-FNA in 311 cases of solid pancreatic lesions submitted to the Second Hospital of Hebei Medical University, Shijiazhuang, China from May 2019 to September 2023 were retrospectively analyzed. The cases included pancreatic ductal adenocarcinoma (PDAC, 172 cases), solid pseudopapillary neoplasm (SPN, 12 cases), neuroendocrine tumors (PNET, 14 cases) and chronic pancreatitis (113 cases). The cytological features of smears, the histology of cell block sections and the diagnostic markers in PDAC, SPN and PNET were analyzed. The diagnostic accuracies of cytology, cell block histology/immunohistochemistry and combination of the two methods for classifying these pancreatic solid lesions were evaluated.Results:Irregular arrangement of atypical (cancer) cells, anisonucleosis and nuclear atypia were the typical cytological features of PDAC, while presence of pseudopapillae with a myxoid/hyalinized fibrovascular core and low adhesion/salt-and-pepper chromatin were diagnostic features of SPN and NET, respectively. Immunohistochemical results showed that CK7 and CK19 were the most sensitive markers of pancreatic ductal epithelia, and the diffuse strong expression of S-100P (102/111, 91.9%) and aberrant expression of p53 (80/111, 72.1%) were important immunophenotypic markers of PDAC. Various degrees of CDX2 expression could be found in 66.4% PDAC. The expression of CD10, PR, vimentin, CD99 and cyclinD1 and the aberrant expression of β-catenin were the immunophenotypic features of SPN, while the expression of CgA, Syn and CD56 were indispensable immunemarkers for the diagnosis of PNET. Overall, cytology had higher sensitivity than cell block histology (93.9% versus 82.8%) and lower specificity (92.9% versus 99.1%), while the combination of the two methods significantly improved the sensitivity to 96.9% in solid pancreatic lesions. The combination of cytology and cell block histology could significantly improve the diagnostic efficacy of EUS-FNA in PDAC.Conclusions:Integrated diagnosis based on cytology (including rapid on-site evaluation), cell block histology and immunohistochemical findings could significantly improve the diagnostic yield of EUS-FNA in classifying solid pancreatic lesions.

Objective To develop a virtual reality rehabilitation support system and evaluate its effects on improving discharge readiness in caregivers of laryngectomy patients.Methods The system is equipped with a virtual reality-based home nursing skills guidance module for post-laryngectomy patients and an evidence-based artificial intelligence Q&A module.A convenience sampling method was adopted to select 64 caregivers of patients who underwent laryngectomy for the first time in the otorhinolaryngology head and neck surgery department of a tertiary A hospital in Beijing from July 2024 to January 2025 for a systematic study on application effects.To avoid cross-contamination between an experimental group and a control group,ward-based grouping was applied.A coin toss was used to assign Ward 1 to an experimental group and Ward 2 to a control group,with 32 cases in each group.The experimental group received discharge guidance based on the virtual reality technology,while the control group was provided with conventional verbal and written discharge instructions.The readiness for hospital discharge and the quality of discharge teaching scores of caregivers were compared between the 2 groups after the intervention.Results No sample detachment.After the intervention,the patient caregivers in the experimental group scored significantly higher than those in the control group in terms of discharge readiness and quality of discharge guidance,with a statistically significant difference(P＜0.001).Conclusion This study developed the virtual reality rehabilitation system for laryngeal cancer patients demonstrated good feasibility and effectiveness.The application of this system for discharge education significantly improved discharge readiness of caregivers and quality of discharge guidance for post-laryngectomy patients.It also helped with the optimization of health education models,enhancement of nursing resource utilization efficiency,and improvement of transitional care.

Objective:To explore the application of contrast-enhanced ultrasound in the preoperative evaluation of carotid body tumor (CBT).Methods:The clinical data of 13 CBT patients undergoing contrast enhanced ultrasound test and surgical treatment at Peking Union Medical College Hospital from Nov 2017 to Aug 2021 was retrospectively analyzed.Results:Among the 13 patients, 7 patients had bilateral lesions. 18 tumors were identified by contrast enhanced ultrasound, which showed rich blood supply, with marked enhancement in 13 tumors and moderate enhancement in 5 tumors. The origins of the arterial supply for tumors were identified by contrast enhanced ultrasound. Time-intensity curve analysis showed that the tumors had enhancement characteristics of fast wash in and slow wash out. The mean contrast wash in time was (3.33±1.40) s, the mean peak intensity was (10.41±1.74) dB, and the mean wash out time was (56.47±22.28) s. A total of 13 cases underwent successful surgical removal. Five cases of external carotid artery ligation and 2 cases of internal carotid artery reconstruction were performed during surgery. Postoperative transient neurological injury occurred in 5 cases. There were no cases of cerebral infarction or death in the perioperative period. Mean postoperative follow-up was 14.31 months. Five cases of neurological injury had satisfactory recovery and no other adverse events occurred.Conclusions:Contrast enhanced ultrasound is an effective method of preoperative imaging assessment for CBT, which helps the surgical planning and preoperative preparation.

Objective To explore the mechanism of excessive mechanical stress regulated ferroptosis induced by Piezo1 channel in mouse chondrocytes.Methods The experiment was performed on mouse ATDC5 chondrocytes.siRNA-Piezo1 interference plasmid and Piezo1 overexpression plasmid were used to transfect chondrocytes,and mechanical stress stimulation was given.The control group,the mechanical stress stimulation group(MS group),the MS+siRNA-Piezo1 group(MS+sh group)and the MS+Piezo1 overexpression group(MS+OV group)were constructed,respectively.The cell viability,Fe2+,ROS levels,the expression of ferroptosis-related proteins SLC7A11 and GPX4,and the expression of Collagen Ⅱ,MMP-13,Aggrecan and p53 proteins were detected in each group.Results Compared with the control group,the cell viability was decreased in the MS group(P＜0.05).Levels of Fe2+,reactive oxygen species(ROS)and malondialdehyde(MDA)were increased(P＜0.05).Levels of reduced glutathione(GSH)and superoxide dismutase(SOD)were decreased(P＜0.05),and the mitochondrial ridge was decreased detected by transmission electron microscopy.Protein levels of SLC7A11,GPX4,Collagen Ⅱ and Aggrecan were decreased(P＜0.05),while protein levels of p53 and MMP-13 were increased(P＜0.05).Compared with the MS group,Fe2+,ROS and MDA levels were decreased in the MS+sh group(P＜0.05),GSH and SOD levels were increased(P＜0.05),and protein levels of SLC7A11,Collagen Ⅱ,GPX4 and Aggrecan were increased(P＜0.05).The protein levels of MMP-13 and p53 were decreased(P＜0.05).Compared with the MS group,cell viability was decreased(P＜0.05),Fe2+,ROS and MDA levels were increased(P＜0.05),GSH and SOD levels were decreased(P＜0.05),and protein levels of SLC7A11,Collagen Ⅱ,GPX4 and Aggrecan were decreased in the MS+OV group(P＜0.05).Levels of MMP-13 and p53 protein were increased(P＜0.05).Conclusion Excessive mechanical stress can induce chondrocyte ferroptosis and promote extracellular matrix degradation via Piezo1 channel protein.

Objective:To investigate the influence of prealbumin on cerebral infarction severity, hemorrhage transformation and 1-year prognosis.Methods:A retrospective study was conducted to select 752 patients with cerebral infarction who were treated in Beijing Tiantan Hospital,Capital Medical University from December 2018 to December 2019 as the study objects. Personal information and laboratory indicators of the patients were collected including prealbumin, hemoglobin, white blood cell count, etc.Patients were divided into group B1 (<238 mg/L) and group B2 (≥238 mg/L) based on median prealbumin. By inquiry patient's case, NIHSS score (<16 was classified as mild, ≥16 as moderate and severe)and cerebral infarction volume (<20 cm 3 as small infarct, >20 cm 3 as large infarct) were recorded to evaluate the severity of the disease, and whether hemorrhage transformation occurred during hospitalization was recorded. Patients were followed up 1 year after discharge, and prognostic information of patients was recorded, including neurological function recovery (mRS score <3 was classified as good recovery, ≥3 as poor recovery),all-cause case fatality rate, and recurrence of cardio-cerebrovascular events. Normally distributed measurement data were expressed as xˉ±s, non-normally distributed measurement data were expressed as median and quartiles[ M( Q1, Q3)], categorical variable were expressed as ratio and percent(%). Comparison between groups of measurement data were performed by independent sample t test and Mann-Whitney U test. Chi-square test were used on comparison between groups of categorical variable. Single-factor comparison, Spearman correlation analysis and multiple Logistic regression were used to analyze the correlation between prealbumin and other laboratory indicators, cerebral infarction severity, hemorrhage transformation and 1-year prognosis, respectively. Results:The NIHSS score and infarct volume of patients in group B1 were 5(2,10) and 3.18(0.72,18.00) cm 3, and those in group B2 were 3(2,7) and 2.0(0.5,10.0) cm 3, respectively, which were higher in group B1 than in group B2, the differences were statistically significant ( Z=3.85, P<0.001, Z=2.81, P=0.005). The proportion of mRS Score ≥3 in group B1 was 28.8%(107/371), and the all-cause case fatality rate was 7.5%(28/371), both higher than 20.5%(78/381) and 3.1%(12/381) in group B2, with statistical significance ( χ2=7.10, P=0.008, χ2=7.22, P=0.007). Hemorrhage transformation and recurrence of cardio-cerebrovascular events were 13.5%(50/371) and 11.6%(43/371) in group B1 and 9.2% (35/381) and 8.7%(33/381) in group B2, respectively, with no significant difference between the two groups ( χ2=3.45, P=0.063, χ2=1.78, P=0.183). Multivariate logistic regression analysis showed that, after adjusted for potential confounding factors, prealbumin was protective factor of NIHSS ( OR and 95% CI: 0.990(0.984-0.997), P=0.035), poor neurological recovery(mRS≥3) ( OR and 95% CI:0.992(0.988-0.997), P<0.001) and all-cause case fatality rate ( OR and 95% CI:0.991(0.983-0.999), while prealbumin had no significant influence on cardiocerebrovascular recurrence events ( OR and 95% CI: 0.999(0.993-1.005), P=0.729). Conclusion:Prealbumin is significantly associated with the severity of cerebral infarction and poor prognosis 1 year after discharge, and low prealbumin was an independent risk factor for NIHSS score(≥16), poor neurological recovery (mRS≥3) and all-cause case fatality rate.

Objectives:To explore the effects of infarct volume, infarct type, inflammation, and coagulation indicators on hemorrhagic transformation in patients with acute cerebral infarction.Methods:711 patients with cerebral infarction admitted to Beijing Tiantan Hospital were retrospectively included as the study objects from December 2018 to December 2019 [535 males and 176 females, age 22-95 years, mean age (59.6±12.1) years]. Clinical data, laboratory indicators such as inflammation and coagulation function of patients were collected, and information such as location, volume and type of infarction were recorded. The patients were divided into hemorrhage transformation group and non-hemorrhage transformation group according to whether hemorrhage transformation occurred during hospitalization. Normally distributed measurement data were expressed as xˉ± s, non-normally distributed measurement data were expressed as median and quartiles [ M( Q1, Q3)], categorical variable were expressed as ratio and percent (%). Comparison between groups of measurement data were performed by independent sample t test and Mann-Whitney U test. χ2 test were used on comparison between groups of categorical variable. Univariate comparison and multivariate Logistic regression were used to analyze the correlation between hemorrhage transformation and infarct volume, infarction type and laboratory indicators, respectively, to explore the risk factors of hemorrhage transformation. ROC curve analysis was used to evaluate the diagnostic value of indicators. Results:The rates of coronary heart disease and atrial fibrillation history in the hemorrhage transformation group were 23.5% (20/85) and 22.4% (19/85), respectively, which were significantly higher than those in the non-hemorrhage transformation group (13.9% (87/626) and 5.8% (36/626), respectively), and the difference between the two groups was statistically significant ( χ2=5.43, χ2=28.90, P=0.020, P<0.001, respectively). The NIHSS score [10(4,17) points] and infarct volume [46.50 (14.21,118.42) mL] in the hemorrhage transformation group were significantly higher than those in the non-hemorrhage transformation group [4(2,7) points, 2.00(0.51,8.94) mL]. The difference between the two groups was statistically significant ( Z values were 6.69 and 10.69, respectively, P<0.001). The results of multivariate Logistic regression analysis showed that atrial fibrillation (OR=2.604, 95% CI: 1.186-5.716, P=0.107), infarct volume (OR=1.009, 95% CI: 1.004-1.015, P=0.001), infarct type of Chinese ischemic stroke subclassfication (OR=1.371, 95% CI: 1.085-1.731, P=0.008) and neutrophil/lymphocyte ratio (OR=1.047, 95% CI: 1.006-1.090, P=0.023) were independent risk factors for hemorrhage transformation. ROC curve analysis showed that the area under curve (AUC) of infarct volume and neutrophil/lymphocyte ratio were 0.861 (0.821-0.901) and 0.684 (0.626-0.741), respectively, which were effective in predicting hemorrhage transformation after cerebral infarction. The prediction of infarct volume was more efficient. Conclusion:History of atrial fibrillation, classification of cardioembolic stroke, infarct volume, and neutrophil/lymphocyte ratio are all risk factors for hemorrhagic transformation after acute cerebral infarction.

BACKGROUND:Early diagnosis of pulmonary fibrosis is the foundation for timely antifibrotic drug therapy.Therefore,exploring and discovering ideal biomarkers that can be effectively used for the early diagnosis of pulmonary fibrosis is crucial for the treatment of the disease.OBJECTIVE:To conduct an in-depth analysis of key autophagy-related genes involved in the process of pulmonary fibrosis by means of bioinformatics and machine learning techniques,in order to investigate whether autophagy-related core genes of pulmonary fibrosis can be used as reliable biomarkers in the assessment of the progression of pulmonary fibrosis.METHODS:Two datasets of pulmonary fibrosis,GSE24206 and GSE110147,were downloaded from the Gene Expression Omnibus(GEO)database(a public database developed and maintained by the U.S.National Center for Biotechnology Information to store and share bioinformatics data),and the gene expression matrices of these two datasets were normalized by using the"limma"package in R software.The autophagy-related genes were extracted from GeneCards database(a database created by the U.S.National Center for Biotechnology Information,which automatically integrates gene-centric data from about 200 Web sources,including genomic,transcriptomic,proteomic,genetic,clinical,and functional information).Differential gene analysis was performed on the pulmonary fibrosis dataset,and the common genes were extracted by cross-comparing the differential genes with the autophagy genes,so as to identify autophagy genes that may play a role in the process of pulmonary fibrosis.The intersecting genes were analyzed for functional enrichment and cellular immune infiltration by gene ontology and Kyoto Encyclopedia of Genes and Genomes.Core genes of pulmonary fibrosis associated with autophagy were screened by protein-protein interactions and machine learning,and core genes were subjected to the enrichment analysis.Diagnostic models were constructed from the identified core genes.Calibration curves were used to assess the predictive ability of the line graph model.An external dataset,GSE21369,was used to perform a receiver operating characteristic curve analysis to validate the expression profiles of pulmonary fibrosis genes associated with autophagy,as well as to predict Chinese herbs associated with the genes IL6 and COL1A2 via the Coremine database.Finally,human embryonic lung fibroblasts were cultured and modelled by transforming growth factor-β1 treatment,and the relative expression of genes in the model cells was verified using qRT-PCR.RESULTS AND CONCLUSION:(1)A total of 51 pulmonary fibrosis differential genes and 25 genes intersecting with autophagy genes were obtained.Gene ontology analysis showed that the 25 intersecting genes were related to extracellular matrix tissue,collagen metabolism,collagen pro-fibroblasts,and growth factor binding,etc.The results of Kyoto Encyclopedia of Genes and Genomes enrichment analysis indicated that they were mainly related to the Phosphatidylinositol 3-kinase/protein kinase B signaling pathway and the signaling pathway of the extracellular matrix-receptor interactions.(2)Immunoinfiltration analysis revealed that the expression of activated memory CD4+T cells,M0 macrophages,and resting dendritic cells was significantly elevated in the pulmonary fibrosis group(P＜0.05),showing a strong correlation.(3)Two autophagy signature genes involved in the progression of pulmonary fibrosis were identified:COL1A2 and IL6.The column-line diagram model showed that the two core genes predicted the onset of pulmonary fibrosis more accurately,and the receiver operating characteristic curve analysis showed that the two characteristic genes had diagnostic significance.COL1A2 and IL6 were related to the cell-cycle pathway,mitogen-activated protein kinase signaling pathway,Janus kinase-signal transduction and activator of transcription signaling pathway and cytokine-cytokine receptor interactions.A total of 20 Chinese herbs were predicted to be related to COL1A2 and IL6 genes,and their efficacies were mainly to clear away heat and detoxify toxins and to invigorate blood and move qi.COL1A2 and IL6 were verified to be highly expressed in pulmonary fibrosis.To conclude,COL1A2 and IL6 may be potential diagnostic biomarkers for pulmonary fibrosis,but its specificity to pulmonary fibrosis needs to be further investigated.