Although many models have been proposed to accurately predict the response of drugs in cell lines recent years, understanding the genome related to drug response is also the key for completing oncology precision medicine. In this paper, based on the cancer cell line gene expression and the drug response data, we established a reliable and accurate drug response prediction model and found predictor genes for some drugs of interest. To this end, we first performed pre-selection of genes based on the Pearson correlation coefficient and then used ElasticNet regression model for drug response prediction and fine gene selection. To find more reliable set of predictor genes, we performed regression twice for each drug, one with IC50 and the other with area under the curve (AUC) (or activity area). For the 12 drugs we tested, the predictive performance in terms of Pearson correlation coefficient exceeded 0.6 and the highest one was 17-AAG for which Pearson correlation coefficient was 0.811 for IC50 and 0.81 for AUC. We identify common predictor genes for IC50 and AUC, with which the performance was similar to those with genes separately found for IC50 and AUC, but with much smaller number of predictor genes. By using only common predictor genes, the highest performance was AZD6244 (0.8016 for IC50, 0.7945 for AUC) with 321 predictor genes.

Although many models have been proposed to accurately predict the response of drugs in cell lines recent years, understanding the genome related to drug response is also the key for completing oncology precision medicine. In this paper, based on the cancer cell line gene expression and the drug response data, we established a reliable and accurate drug response prediction model and found predictor genes for some drugs of interest. To this end, we first performed pre-selection of genes based on the Pearson correlation coefficient and then used ElasticNet regression model for drug response prediction and fine gene selection. To find more reliable set of predictor genes, we performed regression twice for each drug, one with IC50 and the other with area under the curve (AUC) (or activity area). For the 12 drugs we tested, the predictive performance in terms of Pearson correlation coefficient exceeded 0.6 and the highest one was 17-AAG for which Pearson correlation coefficient was 0.811 for IC50 and 0.81 for AUC. We identify common predictor genes for IC50 and AUC, with which the performance was similar to those with genes separately found for IC50 and AUC, but with much smaller number of predictor genes. By using only common predictor genes, the highest performance was AZD6244 (0.8016 for IC50, 0.7945 for AUC) with 321 predictor genes.

Modeling vocal-fold vibration is extremely significant in realizing the vibration properties of human vocal folds and investigating their physiological and pathological characteristics. A combined model presented is two mass-finite element (T-F) model, which integrates all merits of both the finite element method (FEM) model and the asymmetric two-mass model of vocal folds. The high-speed glottis graph (HGG) can also be synthesized by the model. The result shows that T-F model can simulate the vibration behavior of normal and pathological vocal folds in a more realistic way with competitively computational speed. Therefore, the T-F model is helpful to gaining a thorough understanding of the vibration properties of vocal folds.
Computer Simulation ; Finite Element Analysis ; Humans ; Models, Biological ; Speech ; physiology ; Vibration ; Video Recording ; instrumentation ; Vocal Cord Paralysis ; diagnosis ; physiopathology ; Vocal Cords ; physiology

Objective:To discuss the inhibitory effect of chelerythrine(CHE)on the migration,invasion,and epithelial-mesenchymal transition(EMT)of the human ovarian cancer SKOV3 cells,and to clarify the associated mechanism.Methods:The SKOV3 cells were cultured in vitro and divided into control group and 2.5,5.0,10.0,20.0,and 40.0 μmol·L-1 CHE groups.Methylthiazolydiphenyl-tetrazolium(MTT)assay was used to detect the inhibitory rates of proliferation of the cells in various groups.The SKOV3 cells were cultured in vitro and divided into control group,transforming growth factor-β1(TGF-β1)group,TGF-β1+5 μmol·L-1 CHE group,and TGF-β1+10 μmol·L-1 CHE group.Cell scratch assay was used to detect the migration rates of the cells in various groups;Transwell chamber assay was used to detect the numbers of migration and invasion cells in various groups;Western blotting method was used to detect the expression levels of E-cadherin,N-cadherin,and Vimentin proteins in the cells in various groups;immunofluorescence staining method was used to detect the fluorescence intensities of E-cadherin and N-cadherin in the cells in various groups.Results:The MTT assay results showed that compared with control group,the inhibitory rates of proliferation of the cells in 5.0,10.0,20.0,and 40.0 μmol·L-1 CHE groups were significantly increased(P<0.05 or P<0.01).The cell scratch assay results showed that compared with control group,the migration rate of the cells in TGF-β1 group was increased(P<0.01);compared with TGF-β1 group,the migration rates of the cells in TGF-β1+5 μmol·L-1 CHE group and TGF-β1+10 μmol·L-1 CHE group were significantly decreased(P<0.01).The Transwell chamber assay results showed that compared with control group,the numbers of migration and invasion cells in TGF-β1 group were significantly increased(P<0.05);compared with TGF-β1 group,the numbers of migration and invasion cells in TGF-β1+5 μmo·l L-1 CHE group and TGF-β1+10 μmo·l L-1 CHE group were significantly decreased(P<0.01).The Western blotting results showed that compared with control group,the expression level of E-cadherin protein in the cells in TGF-β1 group was significantly decreased(P<0.01),while the expression levels of N-cadherin and Vimentin proteins were increased(P<0.05 or P<0.01);compared with TGF-β1 group,the expression levels of E-cadherin protein in the cells in TGF-β1+5 μmol·L-1 CHE group and TGF-β1+10 μmol·L-1 CHE group were significantly increased(P<0.01),and the expression levels of N-cadherin and Vimentin proteins were significantly decreased(P<0.01).The immunofluorescence staining results showed that compared with control group,the fluorescence intensity of E-cadherin in the cells in TGF-β1 group was decreased,and the fluorescence intensity of N-cadherin was increased;compared with TGF-β1 group,the fluorescence intensities of E-cadherin in the cells in TGF-β 1+5 μmol·L-1 CHE group and TGF-β1+10 μmol·L-1 CHE group were significantly increased,and the fluorescence intensities of N-cadherin were decreased.Conclusion:CHE can inhibit the proliferation,migration,invasion,and EMT of the human ovarian cancer SKOV3 cells.

Objective:To investigate the regulatory role of defferentially expressed LOC107987438 in the pathogenesis of depressive disorder and provide a theoretical basis for its clinical application in depressive disorder.Methods:Differential expression of LOC107987438 was verified by quantitative real-time polymerase chain reaction(qRT-PCR)in peripheral blood monocular cells(PBMCs)of 60 patients with depressive disorder and 60 health controls. In addition, its diagnostic value was assessed by receiver operating characteristic(ROC)curves. Based on the ceRNA mechanism of lncRNA, the miRDB database was applied to predict the target miRNAs of LOC107987438, and the miRNAs with target score ≥ 80 among them were screened out.The screened miRNAs were then used to predict their potential target mRNAs through four databases which were TargetScan 8.0, miRTarBase, mirDIP and miRPathDB. Moreover, the predicted target mRNAs were annotated for gene ontology(GO)function annotation and tokoyo encyclopedia of genes and genomes(KEGG) pathway enrichment analysis via ClusterProfiler 4.0.5 package of R 4.1.1. Finally, a protein-protein interaction network was constructed using the STRING 11.5 platform to retrieve the interacting genes.Results:The qRT-PCR results showed that normalized expression of LOC107987438 in PBMCs of patients with depressive disorder was higher than that in health controls(depressive disorder: 2.084±1.357, health controls: 1.000±0.660, P<0.001). The ROC curve results showed that the area under curves(AUC)of LOC107987438 was 0.759(95% CI: 0.675-0.842, P<0.05), indicating its high potential diagnostic value. Bioinformatics analysis showed that hsa-miR-4670-3p, hsa-miR-619-3p, hsa-miR-6721-5p and hsa-miR-297 were the miRNAs with high bindings to LOC107987438. The results of KEGG signaling pathway enrichment revealed that hypoxia-inducible factor 1(HIF-1)signaling pathway, phosphatidylinositol 3-kinase-AKT(PI3K-Akt) signaling pathway and erythroblastic oncogene B(ErbB) signaling pathway were closely associated with depressive disorder. Among the top ten key genes screened by the protein-protein interaction network, kirsten rats arcomaviral oncogene homolog(KRAS), androgen receptor(AR), cyclic-AMP response binding protein1(CREB1), insulin-like growth factor 1(IGF1), cyclin-dependent kinase inhibitor 1B(CDKN1B) and calcium/calmodulin-dependent protein kinase type Ⅱ alpha(CAMK2A)were strongly associated with depressive disorder. Conclusion:The establishment of ceRNA regulatory network of LOC107987438 provides a theoretical basis for exploring the pathophysiology of depressive disorders.

Major depressive disorder (MDD) has become an increasingly serious public health issue, characterized by high incidence and high disability rates. It often coexists with other mental health problems and physical diseases, with a significant negative impact on patients' quality of life. In clinical practice, MDD is considered a heterogeneous disease. The complexity of the pathological mechanisms and the variability in treatment responses lead to a lack of clear therapeutic targets, which complicates the treatment process. In recent years, with advancements in neuroscience, the crucial role of microglia in the pathogenesis of MDD has been revealed. As the main immune cells in the brain, microglia are not only involved in the regulation of neuroinflammation but also play important roles in neurogenesis and neuronal regulation in MDD. This article mainly discusses the role of microglia in the pathophysiological mechanisms of MDD, aiming to provide a theoretical basis for microglia as a potential target for the treatment of MDD.

Objective:To evaluate the enrollment rate, mutation rate and causes of variability the clinical pathway of bronchopneumonia.Methods:The enrollment rate, completion rate, variation and reasons of the clinical pathway in Beijing Children′s Hospital, Capital Medical University from January 2012 to December 2016 were retrospectively collected.Data of patients after the clinical pathway of bronchopneumonia in other tertiary class A hospitals were gathered by questionnaires, and the enrollment rate, completion rate, variation rate and reasons were analyzed.Results:(1)At the end of 2016, 11 of the 13 hospitals included in this study had implemented the clinical pathway for 5 years, 1 hospital for 3 years, and 1 hospital for 2 years.(2) Eleven hospitals provided their enrollment rates.The enrollement rate of 2 hospitals was<50%, and that of 9 hospitals was>80%.The annual completion rate of Beijing Children′s Hospital was ≥75%, and the completion rates offered by 8 hospitals were basically >70%.(3) Since the implementation of the clinical pathway for 5 years in Beijing Children′s Hospital, a total of 427 cases were enrolled of which 93 cases were mutated (variability 21.78%). The variability of 5 hospitals was maintained at <15%.The variability of 3 hospitals decreased with the implementation years, and became qualified.The variability of 1 hospital first rebounded and then controlled; 1 hospital increased by 27.65%; 1 hospital was first controlled and rebounded; 1 hospital was always >15%.The main cause of the mutation was coexisting diseases, complications, progression of the disease, or correction of the first diagnosis, etc.Conclusions:The completion rate of tertiary class A hospitals meets the requirements of national policy.However, the enrollment rate needs to be improved, and the variation rate among different hospitals differs a lot.Further implementation of the clinical pathway should be strengthened and monitored.

Deep phenotyping is a precise and comprehensive approach used for the precise analysis and comprehensive assessment of multi-system phenotypes of the patients. The approach uses symptoms, signs, various medical examination and laboratory results, and other relevant medical information. In the clinical diagnosis and medical research of rare bone diseases, deep phenotyping plays a pivotal role. The realization of precision medicine primarily comprises three key dimensions: deep phenotyping, stratified medicine, and targeted therapy. The deep phenotyping is the basis for the latter two. Deep phenotyping not only facilitates fine subtyping of diseases, but also allows for the in-depth understanding of genetic data. The use of deep phenotyping requires stand- ardized terminology and specific procedures. Moreover, deep phenotyping shows substantial potential using the application of artificial intelligence technology particularly when combining with multi-omics techniques.

Blau syndrome is a rare genetic disorder characterized by the a mix of granulomatous arthritis, uveitis, and dermatitis. Patients typically manifest multisystem involvement, including ocular, skin, and skeletal abnormalities. Blau syndrome is extremely rare, with a global incidence of less than one in a million among children. In this multidisciplinary consultation, we present a case of a 21-year-old young female patient having multisystemic involvement since early childhood. She was presented with multiple joint swelling, skin lesions, increased eye discharge, and accompanied by hypertension and arterial abnormalities, and received a diagnosis of uveitis. The patient had been receiving steroid treatment since the age of 6 and has tried various medications, with some improvement in joint swelling and ocular symptoms. Through this rare disease multidisciplinary consultation, we aim to provide guidance in the molecular diagnosis of the patient, multisystem assessment, and the selection and formulation of treatment plans. Additionally, we hope that by reporting this case, clinical physicians can gain a better understanding of the diagnosis and comprehensive treatment strategies for Blau syndrome, thereby improving the management and treatment of rare diseases.