Combined with elastic network model (ENM), the perturbation response scanning (PRS) has emerged as a robust technique for pinpointing allosteric interactions within proteins. Here, we proposed the PRS analysis of drug-target networks (DTNs), which could provide a promising avenue in network medicine. We demonstrated the utility of the method by introducing a deep learning and network perturbation-based framework, for drug repurposing of multiple sclerosis (MS). First, the MS comorbidity network was constructed by performing a random walk with restart algorithm based on shared genes between MS and other diseases as seed nodes. Then, based on topological analysis and functional annotation, the neurotransmission module was identified as the "therapeutic module" of MS. Further, perturbation scores of drugs on the module were calculated by constructing the DTN and introducing the PRS analysis, giving a list of repurposable drugs for MS. Mechanism of action analysis both at pathway and structural levels screened dihydroergocristine as a candidate drug of MS by targeting a serotonin receptor of serotonin 2B receptor (HTR2B). Finally, we established a cuprizone-induced chronic mouse model to evaluate the alteration of HTR2B in mouse brain regions and observed that HTR2B was significantly reduced in the cuprizone-induced mouse cortex. These findings proved that the network perturbation modeling is a promising avenue for drug repurposing of MS. As a useful systematic method, our approach can also be used to discover the new molecular mechanism and provide effective candidate drugs for other complex diseases.

Combined with elastic network model(ENM),the perturbation response scanning(PRS)has emerged as a robust technique for pinpointing allosteric interactions within proteins.Here,we proposed the PRS analysis of drug-target networks(DTNs),which could provide a promising avenue in network medicine.We demonstrated the utility of the method by introducing a deep learning and network perturbation-based framework,for drug repurposing of multiple sclerosis(MS).First,the MS comorbidity network was constructed by performing a random walk with restart algorithm based on shared genes between MS and other diseases as seed nodes.Then,based on topological analysis and functional annotation,the neurotransmission module was identified as the"therapeutic module"of MS.Further,perturbation scores of drugs on the module were calculated by constructing the DTN and introducing the PRS analysis,giving a list of repurposable drugs for MS.Mechanism of action analysis both at pathway and structural levels screened dihydroergocristine as a candidate drug of MS by targeting a serotonin receptor of se-rotonin 2B receptor(HTR2B).Finally,we established a cuprizone-induced chronic mouse model to evaluate the alteration of HTR2B in mouse brain regions and observed that HTR2B was significantly reduced in the cuprizone-induced mouse cortex.These findings proved that the network perturbation modeling is a promising avenue for drug repurposing of MS.As a useful systematic method,our approach can also be used to discover the new molecular mechanism and provide effective candidate drugs for other complex diseases.

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.

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.

Stapled peptides with significantly enhanced pharmacological profiles have emerged as promising therapeutic molecules due to their remarkable resistance to proteolysis and performance to penetrate cells. The all-hydrocarbon peptide stapling technique has already widely adopted with great success, yielding numerous potent peptide-based molecules. Based on our prior efforts, we conceived and prepared a double-stapled peptide in this study, termed FRNC-1, which effectively attenuated the bone resorption capacity of mature osteoclasts in vitro through specific inhibition of phosphorylated GSK-3β. The double-stapled peptide FRNC-1 displayed notably improved helical contents and resistance to proteolysis than its linear form. Additionally, FRNC-1 effectively prevented osteoclast activation and improved bone density for ovariectomized (OVX) mice after intravenous injection and importantly, after oral (intragastric) administration. The double-stapled peptide FRNC-1 is the first orally effective peptide that has been validated to date as a therapeutic candidate for postmenopausal osteoporosis (PMOP).

Artificial Intelligence ; Forecasting ; Humans ; Rare Diseases ; Urinary Bladder Neoplasms/diagnosis*

We reviewed and developed an indicator system framework for assessing teaching effect of laparoscopic simulation training through literature research, expert consultation, analytic hierarchy process and factor analysis. We also made an empirical study on the constructed index system. The system included 3 domains (A1: evaluation of laparoscopic simulator; A2: operation evaluation of experimental animals; A3: evaluation of clinical practice), 10 second-level indicators and 23 third-level indicators for assessing teaching effect of laparoscopic simulation training. The indicator system framework has good internal consistency (Cronbach α= 0.968) and external consistency (>0.72). The empirical study found that: in the results of A1-A3 in the first level indicator, the score of the experienced group was significantly higher than that of the inexperienced group ( P<0.05). In the evaluation results of the 10 secondary indicators in the secondary indicators B1-B10, the score of the experienced group was significantly higher than that of the inexperienced group ( P<0.01). For the first time, we have established and evaluated a comprehensive evaluation indicator system which is reliable and effective and can be used for further evaluation of teaching effect of laparoscopic simulation training. The following empirical studies have verified the effectiveness and practicability of the evaluation system.

In recent years,antibiotics have been playing more and more important roles in maintaining human health with the increasing variety and quantity.However,under the influence of different reasons caused by subjective or objective factors,antibiotics irrational use has induced bacterial resistance and adverse reactions,which are becoming more and more serious.The paper put forward the countermeasures of antibiotics irrational use and provided reference for rational use of antibiotics based on the present situation analysis in China and foreign experience in order to control the irrational use.

Objective · To investigate the clinical effects of photo-activated disinfection (PAD)-assisted non-surgical therapy on the treatment of chronic periodontitis. Methods · Eleven patients with chronic periodontitis (totally 118 selected sites) were randomly enrolled. A split-mouth self-control method was adopted. Selected sites with the probing depth (PD) of bilateral homonymous teeth ≥ 5 mm were randomly assigned to the group A (receiving scaling and root planning, SRP) and the group B (receiving SRP+ PAD). Periodontal clinical indexes, inflammation indexes, and periodontal pathogens at selected sites were examined at baseline and 6 and 12 weeks after treatment. Results · Both SRP alone and SRP+PAD improved the periodontal inflammation significantly. The positive rate of bleeding on probing (BOP) 12 weeks after treatment was remarkably lower in the group B than in the group A (37.3% vs 57.6%, P=0.042). Both SRP and SRP+PAD effectively decreased matrix metalloproteinase-8 (MMP-8) and interleukin-1β (IL-1β) levels in gingival crevicular fluid. The IL-1β levels 6 and 12 weeks after treatment were significantly lower in the group B than in the group A [(17.99±14.26) pg/mL vs (32.64±30.69) pg/mL, P=0.007; (11.37±10.25) pg/mL vs (23.85±15.55) pg/mL, P=0.000]. Both treatments decreased the ratio of P. gingivalis and F.nucleatum in total bacteria. Conclusion · PAD can serve as a potential adjunctive therapy to conventional SRP in the treatment of chronic periodontitis with better improvement of bleeding gums and control of periodontal inflammation.

Objective To evaluate the effects of handholding and providing information on physiology and psychology in patients undergoing percutaneous transforaminal endoscopic discectomy under local anesthesia. Methods A total of 74 patients receiving percutaneous transforaminal endoscopic discectomy under local anesthesia in China-Japan Friendship Hospital in Beijing were selected and randomly divided into the intervention group and the control group by random number table, with 60 cases in each. During surgery,the patients in the control group only received routine cares, in the intervention group, except the routine cares, nurses held the hands of patients for 20-30 seconds every 10 minnutes and provided them with spoken information. Then the State-Anxiety Inventory (SAI) scale and Visual Analogue Scale (VAS) were used for assessment of anxiety and pain of two groups of patients. Results The results showed that there was no statistically significant difference in SAI score between both groups the day before surgery and before surgery in operation room (P>0.05). The SAI scores of the control group (42.30 ± 10.14) was lower than that of the intervention group (35.35 ± 8.00), there was statistically significant difference between both groups (t=3.273, P=0.002);the VAS score in the control group (54.16 ± 22.02) was lower than that of the intervention group (41.68 ± 15.30), there was statistically significant difference between both groups (t=2.832,P=0.006). Conclusions The nursing method of handholding and providing information for patients who undergoing percutaneous transforaminal endoscopic discectomy under local anesthesia is very useful intervention, it can mitigate surgical anxiety,pain degree. It makes patients more comfortable whether in physiology or psychology and better fit surgery.