ObjectiveTo explore the mechanisms of action of Ganlu Xiaodu Dan in treating viral pneumonia by combining network pharmacology and molecular docking with in vivo experimental validation. MethodsNetwork pharmacology and molecular docking were used to predict the core components， target genes， and major pathways of Ganlu Xiaodu Dan. Molecular docking was then applied to verify the interactions between the core components and key targets. Sixty male C57BL/6 mice were randomly divided into six groups （n = 10 per group）， including blank， model， dexamethasone， and Ganlu Xiaodu Dan low-， medium-， and high-dose groups. The blank and model groups were gavaged with physiological saline （10 mL·kg^-1） every 12 h. The dexamethasone group received intraperitoneal injections of dexamethasone （5 mg·kg^-1）. The low-， medium-， and high-dose groups of Ganlu Xiaodu Dan were gavaged with solutions at concentrations of 7.2， 14.4， and 21.6 g·kg^-1， respectively， every 12 h. Lung wet/dry weight ratio （W/D） was measured. Hematoxylin-eosin （HE） staining was used to observe pathological changes in lung tissue. Enzyme-linked immunosorbent assay （ELISA） was employed to determine the expression levels of tumor necrosis factor-α （TNF-α）， interleukin （IL）-17， and IL-1β in bronchoalveolar lavage fluid （BALF）. Western blot was performed to detect the expression of phosphoinositide 3-kinase （PI3K） and protein kinase B （Akt） in lung tissue for further validation. ResultsTwelve potential active components of Ganlu Xiaodu Dan were identified through network pharmacology. A total of 306 overlapping target genes were obtained between Ganlu Xiaodu Dan and viral pneumonia. PPI network analysis identified the top 20 key targets， and GO and KEGG enrichment analyses revealed the top 20 signaling pathways. An “active component–target–pathway” network was constructed. Molecular docking demonstrated strong affinity between the core components of Ganlu Xiaodu Dan and key targets related to viral pneumonia. In animal experiments， compared with the blank group， the model group showed severe bronchial epithelial damage， disordered alveolar structure， massive inflammatory cell infiltration， widened alveolar septa， and obvious interstitial edema. W/D， levels of IL-1β， TNF-α， and IL-17 in BALF， and protein expression of p-PI3K/PI3K and p-Akt/Akt in lung tissue were all significantly increased （P<0.05）. Compared with the model group， lung injury in the Ganlu Xiaodu Dan groups and the dexamethasone group was alleviated. W/D and TNF-α levels were significantly decreased （P<0.05）. IL-1β and IL-17 levels were significantly reduced in the medium- and high-dose groups and the dexamethasone group， and the protein expression levels of p-PI3K/PI3K and p-Akt/Akt in lung tissue were significantly decreased （P<0.05）. ConclusionGanlu Xiaodu Dan can alleviate lung injury in viral pneumonia by suppressing the inflammatory response， and its mechanism may be related to the inhibition of PI3K/Akt pathway activation.

ObjectiveTo explore the mechanisms of action of Ganlu Xiaodu Dan in treating viral pneumonia by combining network pharmacology and molecular docking with in vivo experimental validation. MethodsNetwork pharmacology and molecular docking were used to predict the core components， target genes， and major pathways of Ganlu Xiaodu Dan. Molecular docking was then applied to verify the interactions between the core components and key targets. Sixty male C57BL/6 mice were randomly divided into six groups （n = 10 per group）， including blank， model， dexamethasone， and Ganlu Xiaodu Dan low-， medium-， and high-dose groups. The blank and model groups were gavaged with physiological saline （10 mL·kg^-1） every 12 h. The dexamethasone group received intraperitoneal injections of dexamethasone （5 mg·kg^-1）. The low-， medium-， and high-dose groups of Ganlu Xiaodu Dan were gavaged with solutions at concentrations of 7.2， 14.4， and 21.6 g·kg^-1， respectively， every 12 h. Lung wet/dry weight ratio （W/D） was measured. Hematoxylin-eosin （HE） staining was used to observe pathological changes in lung tissue. Enzyme-linked immunosorbent assay （ELISA） was employed to determine the expression levels of tumor necrosis factor-α （TNF-α）， interleukin （IL）-17， and IL-1β in bronchoalveolar lavage fluid （BALF）. Western blot was performed to detect the expression of phosphoinositide 3-kinase （PI3K） and protein kinase B （Akt） in lung tissue for further validation. ResultsTwelve potential active components of Ganlu Xiaodu Dan were identified through network pharmacology. A total of 306 overlapping target genes were obtained between Ganlu Xiaodu Dan and viral pneumonia. PPI network analysis identified the top 20 key targets， and GO and KEGG enrichment analyses revealed the top 20 signaling pathways. An “active component–target–pathway” network was constructed. Molecular docking demonstrated strong affinity between the core components of Ganlu Xiaodu Dan and key targets related to viral pneumonia. In animal experiments， compared with the blank group， the model group showed severe bronchial epithelial damage， disordered alveolar structure， massive inflammatory cell infiltration， widened alveolar septa， and obvious interstitial edema. W/D， levels of IL-1β， TNF-α， and IL-17 in BALF， and protein expression of p-PI3K/PI3K and p-Akt/Akt in lung tissue were all significantly increased （P<0.05）. Compared with the model group， lung injury in the Ganlu Xiaodu Dan groups and the dexamethasone group was alleviated. W/D and TNF-α levels were significantly decreased （P<0.05）. IL-1β and IL-17 levels were significantly reduced in the medium- and high-dose groups and the dexamethasone group， and the protein expression levels of p-PI3K/PI3K and p-Akt/Akt in lung tissue were significantly decreased （P<0.05）. ConclusionGanlu Xiaodu Dan can alleviate lung injury in viral pneumonia by suppressing the inflammatory response， and its mechanism may be related to the inhibition of PI3K/Akt pathway activation.

Objective To explore the diagnostic value of a combined model based on clinicopathological and MRI features in BRCA-mutated ovarian cancer.Methods The data of 132 patients with ovarian cancer who underwent pathology and BRCA gene tes-ting were analyzed retrospectively,including 52 cases of BRCA mutation group and 80 cases of BRCA wild group.The differences of MRI features and clinicopathological features between BRCA mutation group and BRCA wild group were compared.Binary logistic regression was used to construct a joint prediction model and analyze its diagnostic efficiency.Results There were significant differ-ences in cytokeratin 7(CK7),estrogen receptor(ER),Ki-67 and lymphovascular invasion(LVI)between the BRAC mutation group and the BRAC wild group(P＜0.05).Univariate analysis showed that CK7,ER,Ki-67,LVI and the apparent diffusion coefficient(ADC)value of the cystic part of tumor were risk factors for BRCA-mutated ovarian cancer.The combined model based on CK7,ER,Ki-67,LVI,and the ADC value of the cystic part of tumor for the diagnosis of BRCA-mutated ovarian cancer had an area under the curve(AUC)of 0.765.Conclusion CK7,ER,Ki-67,LVI and the ADC value of the cystic part of tumor are risk factors for BRCA-mutated ovarian cancer.The combined model based on the above characteristics demonstrates good diagnostic efficacy for BRCA-mutated ovarian cancer.

Objective To establish an intelligent ICD coding management system to solve the current difficulties in hos-pital ICD coding management,reduce the error rate of information uploading,and improve the accuracy of coding.Methods An ICD coding management system was constructed,with the national clinical version of ICD coding as the main index system.The mapping relationship between the main index coding and the medical insurance version of ICD coding,as well as the hospital ver-sion of ICD coding,was established to achieve real-time maintenance and adjustment.In accordance with the requirements of na-tional public hospital performance evaluation and hospital level assessment,we will establish the ICD coding"label"function and knowledge base for evaluation indicators,embed them into electronic medical record system(EMR),and implement intelligent prompting functions for clinicians to facilitate systematic statistical analysis of data.Results After the establishment of the sys-tem,the error rate of mapping and uploading information such as disease diagnosis and procedures coding decreased significantly(1.2‰ vs 0.3‰,P＜0.05).The accuracy of the main discharge diagnosis and procedures coding has significantly improved(82％vs 91％,P＜0.05;78％vs 88％,P＜0.05).The satisfaction of clinicians and coders increased significantly(65％vs 82％,P＜0.05;79％vs 88％,P＜0.05).Conclusion This system can reduce the error rate of mapping and uploading infor-mation,improve the accuracy and completeness of coding,enhance the management level of ICD coding,and promote the high-quality development of medical care.

Objective To establish an intelligent ICD coding management system to solve the current difficulties in hos-pital ICD coding management,reduce the error rate of information uploading,and improve the accuracy of coding.Methods An ICD coding management system was constructed,with the national clinical version of ICD coding as the main index system.The mapping relationship between the main index coding and the medical insurance version of ICD coding,as well as the hospital ver-sion of ICD coding,was established to achieve real-time maintenance and adjustment.In accordance with the requirements of na-tional public hospital performance evaluation and hospital level assessment,we will establish the ICD coding"label"function and knowledge base for evaluation indicators,embed them into electronic medical record system(EMR),and implement intelligent prompting functions for clinicians to facilitate systematic statistical analysis of data.Results After the establishment of the sys-tem,the error rate of mapping and uploading information such as disease diagnosis and procedures coding decreased significantly(1.2‰ vs 0.3‰,P＜0.05).The accuracy of the main discharge diagnosis and procedures coding has significantly improved(82％vs 91％,P＜0.05;78％vs 88％,P＜0.05).The satisfaction of clinicians and coders increased significantly(65％vs 82％,P＜0.05;79％vs 88％,P＜0.05).Conclusion This system can reduce the error rate of mapping and uploading infor-mation,improve the accuracy and completeness of coding,enhance the management level of ICD coding,and promote the high-quality development of medical care.

Objective To explore the diagnostic value of a combined model based on clinicopathological and MRI features in BRCA-mutated ovarian cancer.Methods The data of 132 patients with ovarian cancer who underwent pathology and BRCA gene tes-ting were analyzed retrospectively,including 52 cases of BRCA mutation group and 80 cases of BRCA wild group.The differences of MRI features and clinicopathological features between BRCA mutation group and BRCA wild group were compared.Binary logistic regression was used to construct a joint prediction model and analyze its diagnostic efficiency.Results There were significant differ-ences in cytokeratin 7(CK7),estrogen receptor(ER),Ki-67 and lymphovascular invasion(LVI)between the BRAC mutation group and the BRAC wild group(P＜0.05).Univariate analysis showed that CK7,ER,Ki-67,LVI and the apparent diffusion coefficient(ADC)value of the cystic part of tumor were risk factors for BRCA-mutated ovarian cancer.The combined model based on CK7,ER,Ki-67,LVI,and the ADC value of the cystic part of tumor for the diagnosis of BRCA-mutated ovarian cancer had an area under the curve(AUC)of 0.765.Conclusion CK7,ER,Ki-67,LVI and the ADC value of the cystic part of tumor are risk factors for BRCA-mutated ovarian cancer.The combined model based on the above characteristics demonstrates good diagnostic efficacy for BRCA-mutated ovarian cancer.

Objective To observe the value of dual-source CT(DECT)virtual monoenergetic imaging(VMI)for differentiating prostate cancer(PC)and benign prostatic hyperplasia(BPH).Methods Thirty-three patients with PC(PC group)and 44 patients with BPH(BPH group)were retrospectively enrolled,and 40-100 keV(with 10 keV interval)VMI were reconstructed based on arterial phase DECT images,respectively.Clinical data,focal CT value and contrast-to-noise ratio(CNR)of VMI with different energy levels and conventional linear fusion images of arterial phase were compared between groups.Binary logistic regression models were constructed based on clinical data being significantly different between groups,focal CT value of VMI with energy level with the highest CNR,also focal CT value of conventional linear fusion images of arterial phase,respectively.The area under the receiver operating characteristic curve(AUC)was calculated to evaluate the efficacy of each model for differentiating PC and BPH.Results Free prostate-specific antigen(f-PSA),total prostate-specific antigen(t-PSA),focal CT value of 40-100 keV VMI and conventional linear fusion images of arterial phase in PC group were all higher,while short diameter in PC group was smaller than those in BPH group(all P＜0.05).Logistic regression models were constructed based on f-PSA,t-PSA,short diameter,CT value at 40 keV VMI and CT value at conventional linear fusion images of arterial phase,respectively,with AUC for differentiating PC and BPH of 0.879,0.902,0.701,0.911 and 0.857,respectively.Conclusion DECT VMI could be used as a supplementary examination for prostate diseases,and 40 keV VMI had the best efficacy for differentiating PC and BPH.

OBJECTIVETo investigate miR-20a expression in human glioma and normal brain tissues and its effect on the proliferation of glioma cells in vitro.

METHODSThe expression of miR-20a was detected in human normal brain tissues and glioma tissues by real-time RT-PCR. miR-20a mimics were synthesized and transfected into U251 cells via liposome, and the cell proliferation were detected using MTT assay and flow cytometry.

RESULTSThe glioma tissues showed significantly up-regulated expression of miR-20a compared with normal brain tissues (P=0.035). The expression level of miR-20a was higher in high-grade than in low-grade gliomas. miR-20a mimics significantly enhanced the proliferation of U251 cells and the percentage of S-phase cells.

CONCLUSIONmiR-20a shows potent effect in promoting the growth of glioma cells, suggesting its important role in the pathogenesis of human glioma.

Adult ; Brain Neoplasms ; genetics ; metabolism ; pathology ; Cell Line, Tumor ; Cell Proliferation ; Female ; Glioma ; genetics ; metabolism ; pathology ; Humans ; Male ; MicroRNAs ; genetics ; metabolism ; Middle Aged ; Real-Time Polymerase Chain Reaction ; Young Adult