OBJECTIVE: To observe the effect of the direct stimulation of acupuncture at extraocular muscle attachment point on acquired extraocular muscle palsy. METHODS: Thirteen patients with acquired extraocular muscle palsy were treated with acupuncture directly at extraocular muscle (paralytic muscle) attachment point. Firstly, the intraocular conjunctival sac drops of topical anesthetic (procaine hydrochloride eye drops) were administered, 0.2 mL each time, once every 10 minutes, for a total of 3 times. Acupuncture was delivered immediately after the third drop. The sterile acupuncture needle for single use, 0.25 mm×25 mm, was inserted at the anatomical location of the corneal limbal attachment of paralytic extraocular muscle, with an angle of 10° to 15° formed between the needle tip and extraocular muscle, and a depth of 0.3 mm to 0.5 mm. Pivoted by the needle tip, the eyeball was moved passively towards the direction of normal action of orbital muscle, 30 to 50 times until the patient felt soreness of the eyeball; afterwards, the needle was removed. After acupuncture, levofloxacin eye drops were administered once (0.2 mL) at the affected eye. The treatment was given twice a week, and completed when diplopia disappeared. Before and after treatment, the diplopia and the synoptophore circumference were observed respectively. RESULTS: After 7 to 24 (15.46±5.56) times of direct stimulation with acupuncture at extraocular muscle attachment point, the symptoms of diplopia disappeared in 13 patients, the eye position restored to orthophoria, and the circumference of synoptophore was reduced to be (4.04±0.82)° from (19.38±3.98)° detected before treatment (P<0.05). CONCLUSION Acupuncture directly at extraocular muscle attachment can attenuate diplopia and improve ocular muscle function in patients with acquired extraocular muscle palsy.
Humans ; Acupuncture Therapy ; Male ; Female ; Middle Aged ; Adult ; Oculomotor Muscles/physiopathology* ; Aged ; Acupuncture Points ; Ophthalmoplegia/physiopathology*

Objective To systematically evaluate the CIinical indexes of western medicine combined with salvianolate in patients affected with diabetes and chronic microvascular complications.Methods Relevant RCTs in China National Knowledge(CNKI),Wanfang Date,Chinese Scientific Journal Database(VIP),PubMed and other databases were searched by computer,and the search time was limited from the foundation of each database to December,2023.Rev Man 5.3 and Stata 15.0 software were used for meta analysis,and TSA 0.9.5.10 Beta software was used for trial sequential analysis(TSA).Results A total of 33 RCTs(2690 patients)were finally involved.The meta-analysis results showed that compared with western medicine,combined with alvianolate could significantly improve the Clinical total effective rate,decrease fasting and postprandial blood glucose,improve vascellum endothelial function{ET-1[MD=-82.46,95%CI(-122.25,-42.67),P<0.05]、NO[MD=11.50,95%CI(7.22,15.78),P<0.05]},lower oxidative stress{SOD[MD=13.18,95%CI(10.26,16.11),P<0.05]、MDA[SMD=-1.43,95%CI(-1.94,-0.92),P<0.05]、Hcy[MD=-6.85,95%CI(-10.58,-3.12),P<0.05]},reduce inflammatory markers{hs-CRP[MD=-3.77,95%CI(-4.90,-2.64),P<0.05]、sICAM-1[MD=-212.59,95%CI(-289.48,-135.70),P<0.05]、IL-6[MD=-14.14,95%CI(-17.73,-10.54),P<0.05]},improve renal function{Scr[MD=-18.69,95%CI(-28.34,-9.03),P<0.05]、BUN[MD=-1.30,95%CI(-1.92,-0.67),P<0.05]、UAER[MD=-37.75,95%CI(-49.40,-26.10),P<0.05].There was no statistical difference in the incidence of adverse reactions between the two groups(P>0.05).TSA further affirmed salvianolate had beneficial effect on serum ET-1、SOD、IL-6、Scr and BUN.Conclusion Compared with the conventional therapy of western medicine,the combined medication of salvianolate and chemical medicine achieves much better Clinical effects on diabetes and chronic microvascular complications.Considering the limitations of the included studies,more large sample and high-quality randomized controlled trials are needed to prove our conclusions.

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 systematically evaluate the CIinical indexes of western medicine combined with salvianolate in patients affected with diabetes and chronic microvascular complications.Methods Relevant RCTs in China National Knowledge(CNKI),Wanfang Date,Chinese Scientific Journal Database(VIP),PubMed and other databases were searched by computer,and the search time was limited from the foundation of each database to December,2023.Rev Man 5.3 and Stata 15.0 software were used for meta analysis,and TSA 0.9.5.10 Beta software was used for trial sequential analysis(TSA).Results A total of 33 RCTs(2690 patients)were finally involved.The meta-analysis results showed that compared with western medicine,combined with alvianolate could significantly improve the Clinical total effective rate,decrease fasting and postprandial blood glucose,improve vascellum endothelial function{ET-1[MD=-82.46,95%CI(-122.25,-42.67),P<0.05]、NO[MD=11.50,95%CI(7.22,15.78),P<0.05]},lower oxidative stress{SOD[MD=13.18,95%CI(10.26,16.11),P<0.05]、MDA[SMD=-1.43,95%CI(-1.94,-0.92),P<0.05]、Hcy[MD=-6.85,95%CI(-10.58,-3.12),P<0.05]},reduce inflammatory markers{hs-CRP[MD=-3.77,95%CI(-4.90,-2.64),P<0.05]、sICAM-1[MD=-212.59,95%CI(-289.48,-135.70),P<0.05]、IL-6[MD=-14.14,95%CI(-17.73,-10.54),P<0.05]},improve renal function{Scr[MD=-18.69,95%CI(-28.34,-9.03),P<0.05]、BUN[MD=-1.30,95%CI(-1.92,-0.67),P<0.05]、UAER[MD=-37.75,95%CI(-49.40,-26.10),P<0.05].There was no statistical difference in the incidence of adverse reactions between the two groups(P>0.05).TSA further affirmed salvianolate had beneficial effect on serum ET-1、SOD、IL-6、Scr and BUN.Conclusion Compared with the conventional therapy of western medicine,the combined medication of salvianolate and chemical medicine achieves much better Clinical effects on diabetes and chronic microvascular complications.Considering the limitations of the included studies,more large sample and high-quality randomized controlled trials are needed to prove our conclusions.

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 clinical significance of combined cerebrospinal fluid(CSF)and routine blood parameter analysis in differentiating between multiple cerebral glioma(MCG)and primary central nervous system lymphoma(PCNSL).Methods We Rretrospectively analyzed the clinical data,CSF and routine blood indicators levels of 62 MCG patients and 56 PCNSL patients admitted to Beijing Tiantan Hospital,Capital Medical University from November 2017 to March 2023.Additionally,we assessed the diagnostic value of individual meaningful indicators as well as their combinations in distinguishing between MCG and PCNSL.Results The levels of CSF total cell count,CSF white cell count,CSF:pro,lactate,routine bloodperipheral neutrophil count,and neu-trophil percentage were significantly higher in the MCG group than in the PCNSL group(P<0.05);while the levels of CSF:Glu,CSF:cl,routine blood lymphocyte count,eosinophil,lymphocyte percentage,and eosinophil percent-age were significantly higher in the PCNSL group than in the MCG group(P<0.05).The AUCs of CSF cell count,CSF white cell count,CSF:pro,lactate,routine blood neutrophil count,neutrophil percentage for differentiating MCG from PCNSL were 0.900,0.899,0.797,0.867,0.828 and 0.772 respectively;sensitivities were 72.4%,77.6%,63.8%,67.2%,72.4%,82.8%,77.6%and 81%,with sensitivities of 97.1%,100%,88.2%,91.2%,88.2%,64.7%,100%and 94.1%,respectively.In addition,the combined detection of CSF total cell count,CSF white cell count,CSF:pro,routine blood neutrophil count and neutrophil percentage in CSF had an AUC of 0.919 for differentiating MCG from PCNSL,with a sensitivity and specificity of 77.6%and 100%,respectively.Conclusions Combined detection of CSF indicators including CSF total cell count,CSF white cell count,CSF:pro,along with routine blood markers such as neutrophil count and neutrophil percentage,holds significant clinical utility for differ-entiating between MCG and PCNSL.