This paper aimed to explore the antidepressant effect of the essential oil from Schizonepeta tenuifolia Briq.(EOST) on the treatment of depression and its mechanism by using a combination of network pharmacology and the mouse model of lipopolysaccharide(LPS)-induced depression. The chemical components in EOST were identified using gas chromatography-mass spectrometer(GC-MS), and 12 active components were selected as the study objects. The targets related to EOST were obtained by Traditional Chinese Medicines Systems Pharmacology(TCMSP) and SwissTargetPrediction database. The targets related to depression were screened out through GeneCards, Therapeutic Target Database(TTD), and Online Mendelian Inheritance in Man(OMIM) database. The Venny 2.1 was applied to screen out the common targets of EOST and depression. The targets were imported into Cytoscape 3.7.2 to generate "drug-active component-diease-target" network diagram. The protein-protein interaction(PPI) network was constructed using STRING 11.5 database and Cytoscape 3.7.2, and the core targets were screened out. DAVID 6.8 database was used for Gene Ontology(GO) func-tional enrichment analysis and Kyoto Encyclopedia of Genes and Genomes(KEGG) pathway enrichment analysis, and subsequently the enrichment results were visualized through the bioinformatics platform. The mouse model of depression was induced by intraperitoneally injecting with LPS in mice. Before modeling, mice were administrated orally with EOST. The antidepressant effect of EOST was evalua-ted by tail suspension test(TST), forced swimming test(FST), and novelty suppressed feeding test(NSFT) after modeling. The content of interleukin(IL)-1β was determined by enzyme-linked immunosorbent assay(ELISA), and the protein expression levels of IL-1β and pro IL-1β in the hippocampus were determined by Western blot. There were 12 main components and 179 targets in EOAT, of which, 116 targets were related to depression, mainly involved in neuroactive ligand-receptor interaction, calcium signaling pathway, and cyclic adenosine monophosphate(cAMP) signaling pathway. Biological processes such as synaptic signal transduction, G-protein coupled receptor signaling pathway, and chemical synaptic transmission were involved. Molecular functions such as neurotransmitter receptor activity, RNA polymerase Ⅱ transcription factor activity, and heme binding were involved. In mice experiments, the results showed that EOST at 100 mg·kg~(-1) and 50 mg·kg~(-1) significantly shortened the immobility time in TST and FST as well as the feeding latency in NSFT compared with the model group, decreased the levels of serum IL-1β and NO, and reduced the protein expression levels of IL-1β and pro IL-1β in the hippocampus. In conclusion, EOST shows a good antidepressant effect in a multi-component, multi-target, and multi-pathway manner. The mechanism may be attributed to the fact that EOST can down-regulate the protein expression levels of IL-1β and pro IL-1β, decrease the release of inflammatory factors, and reduce neuroinflammation response.
Animals ; Mice ; Oils, Volatile ; Depression ; Lipopolysaccharides ; Network Pharmacology ; Databases, Genetic ; Calcium Signaling ; Disease Models, Animal

OBJECTIVES: To derive general formulas for calculating commonly used kinship index (KI). METHODS: By introducing the Kronecker symbol, the formulas used to calculate the same KI under different genotype combinations were summarized into a unified expression. RESULTS: The general formulas were successfully derived for KI in various case situations, including the paternity index, full sibling index, half sibling index, avuncular index, grandpaternity index, first-cousin index, and second-cousin index between two individuals without or with the mother being involved; grandpaternity index between grandparents and a grandchild without or with the mother being involved; half sibling index between two children with two mothers being involved; full sibling index among three children; and half sibling index among three children with no, one, or two mothers being involved. CONCLUSIONS The general formulas given in this study simplify the calculation of KIs and facilitate fast and accurate calculation through programming.
Female ; Child ; Humans ; Paternity ; Siblings ; Genotype ; Mothers ; Models, Genetic

The generation of a tau-V337M point mutation mouse model using gene editing technology can provide an animal model with fast disease progression and more severe symptoms, which facilitate the study of pathogenesis and treatment of Alzheimer's disease (AD). In this study, single guide RNAs (sgRNA) and single-stranded oligonucleotides (ssODN) were designed and synthesized in vitro. The mixture of sgRNA, Cas9 protein and ssODN was microinjected into the zygotes of C57BL/6J mice. After DNA cutting and recombination, the site homologous to human 337 valine (GTG) in exon 11 was mutated into methionine (ATG). In order to improve the efficiency of recombination, a Rad51 protein was added. The female mice mated with the nonvasectomy male mice were used as the surrogates. Subsequently, the 2-cell stage gene edited embryos were transferred into the unilateral oviduct, and the F0 tau-V337M mutation mice were obtained. Higher mutation efficiency could be obtained by adding Rad51 protein. The F0 tau-V337M point mutation mice can pass the mutation on to the F1 generation mice. In conclusion, this study successfully established the first tau-V337M mutation mouse by using Cas9, ssODN and Rad51. These results provide a new method for developing AD mice model which can be used in further research on the pathogenesis and treatment of AD.
Animals ; Male ; Female ; Mice ; Humans ; CRISPR-Cas Systems/genetics* ; RNA, Guide, CRISPR-Cas Systems ; Rad51 Recombinase/genetics* ; Mice, Inbred C57BL ; Disease Models, Animal ; Recombination, Genetic

OBJECTIVE: To compare the accuracy of five warfarin-dosing algorithms and warfarin stable dose model (2.5 mg/day) for Shandong population. METHODS: One hundred and twenty five patients who achieved stable warfarin dose were enrolled. Clinical and genetic data were used to evaluate the value of each algorithm by calculating the percentage of patients whose predicted warfarin dose was within 20% of the actual stable therapeutic dose and mean absolute error (MAE). RESULTS: The frequency of patients with CYP2C9*1/*1, CYP2C9*1/*3 and CYP2C9*1/*2 genotype was 92.00%, 7.20%, 0.80%, respectively. That of VKORC1-1639 AA, AG and GG genotype was 82.40%, 15.20%, 2.40%, respectively. CYP4F2*1/*1, *1/*3, *3/*3 genotype was 50.40%, 39.20%, 10.40%, respectively. With the same genotypes for other loci, patients who carried at least one VKORC1-16398G mutant allele had increased warfarin stable daily dose compared with VKORC1-1639AA. Compared with CYP4F2*1/*1, those carrying at least one CYP4F2*3 mutant allele had warfarin stable daily dose increased by 5.9%-13.00%. The percentage of ideal prediction calculated from IWPC model (59.20%), Huang model (57.60%) and Ohno model (52.80%) were higher than others. The MAE were 0.35 (95%CI: 0.11-0.49), 0.15 (95%CI: 0.10-0.32), 0.39 (95%CI: 0.12-0.51), respectively. CONCLUSION The polymorphisms of CYP2C9, VKORC1 and CYP4F2 genes can influence the stable dose of warfarin in Shandong population. IWPC algorithm is suitable for guiding the use of warfarin in this population.
Anticoagulants ; administration & dosage ; Aryl Hydrocarbon Hydroxylases ; Cytochrome P-450 CYP2C9 ; genetics ; Cytochrome P450 Family 4 ; genetics ; Dose-Response Relationship, Drug ; Genotype ; Humans ; Models, Theoretical ; Polymorphism, Genetic ; Vitamin K Epoxide Reductases ; genetics ; Warfarin ; administration & dosage

The 2019 novel coronavirus disease (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has occurred in China and around the world. SARS-CoV-2-infected patients with severe pneumonia rapidly develop acute respiratory distress syndrome (ARDS) and die of multiple organ failure. Despite advances in supportive care approaches, ARDS is still associated with high mortality and morbidity. Mesenchymal stem cell (MSC)-based therapy may be an potential alternative strategy for treating ARDS by targeting the various pathophysiological events of ARDS. By releasing a variety of paracrine factors and extracellular vesicles, MSC can exert anti-inflammatory, anti-apoptotic, anti-microbial, and pro-angiogenic effects, promote bacterial and alveolar fluid clearance, disrupt the pulmonary endothelial and epithelial cell damage, eventually avoiding the lung and distal organ injuries to rescue patients with ARDS. An increasing number of experimental animal studies and early clinical studies verify the safety and efficacy of MSC therapy in ARDS. Since low cell engraftment and survival in lung limit MSC therapeutic potentials, several strategies have been developed to enhance their engraftment in the lung and their intrinsic, therapeutic properties. Here, we provide a comprehensive review of the mechanisms and optimization of MSC therapy in ARDS and highlighted the potentials and possible barriers of MSC therapy for COVID-19 patients with ARDS.
Adoptive Transfer ; Alveolar Epithelial Cells ; pathology ; Animals ; Apoptosis ; Betacoronavirus ; Body Fluids ; metabolism ; CD4-Positive T-Lymphocytes ; immunology ; Clinical Trials as Topic ; Coinfection ; prevention & control ; therapy ; Coronavirus Infections ; complications ; immunology ; Disease Models, Animal ; Endothelial Cells ; pathology ; Extracorporeal Membrane Oxygenation ; Genetic Therapy ; methods ; Genetic Vectors ; administration & dosage ; therapeutic use ; Humans ; Immunity, Innate ; Inflammation Mediators ; metabolism ; Lung ; pathology ; physiopathology ; Mesenchymal Stem Cell Transplantation ; methods ; Mesenchymal Stem Cells ; physiology ; Multiple Organ Failure ; etiology ; prevention & control ; Pandemics ; Pneumonia, Viral ; complications ; immunology ; Respiratory Distress Syndrome, Adult ; immunology ; pathology ; therapy ; Translational Medical Research

OBJECTIVE: To compare gynecological cancer risk management between women with BRCA variants of unknown significance (VUS) to women with negative genetic testing METHODS: Ninety-nine patients whose BRCA genetic testing yielded VUS were matched with 99 control patients with definitive negative BRCA results at a single institution. Demographics and risk management decisions were obtained through chart review. Primary outcome was the rate of risk-reducing bilateral salpingo-oophorectomy (RRBSO). Chi square tests, t-tests, and logistic regression were performed, with significance of p<0.05. RESULTS: VUS patients were more likely to be non-Caucasian (p=0.000) and of Ashkenazi-Jewish descent (p=0.000). There was no difference in gynecologic oncology referrals or recommendations to screen or undergo risk-reducing surgery for VUS vs. negative patients. Ultimately, 44 patients (22%) underwent RRBSO, with no significant difference in surgical rate based on the presence of VUS. Ashkenazi-Jewish descent was associated with a 4.5 times increased risk of RRBSO (OR=4.489; 95% CI=1.484–13.579) and family history of ovarian cancer was associated with a 2.6 times risk of RRBSO (OR=2.641; 95% CI=1.107–6.299). CONCLUSION: In our institution, patients with VUS were surgically managed similarly to those with negative BRCA testing. The numbers of patients with VUS are likely to increase with the implementation of multi-gene panel testing. Our findings underscore the importance of genetic counseling and individualized screening and prevention strategies in the management of genetic testing results.
Demography ; Female ; Genetic Counseling ; Genetic Testing ; Hereditary Breast and Ovarian Cancer Syndrome ; Humans ; Logistic Models ; Mass Screening ; Ovarian Neoplasms ; Referral and Consultation ; Risk Assessment ; Risk Management

OBJECTIVES: Psychological stress has been known to increase the risk of schizophrenia. Because stress responses are mainly mediated by cortisol, the action of the glucocorticoid receptors (Nuclear Receptor Subfamily 3 Group C Member 1, NR3C1) is possibly related to the pathogenesis of schizophrenia. In this study, we investigated the associations between polymorphisms of NR3C1 and schizophrenia.METHODS: Four single nucleotide polymorphisms (SNPs) (rs17100236, rs2963155, rs9324924, and rs7701443) of NR3C1 were genotyped in 208 patients with schizophrenia and 339 healthy individuals. A chi-square test was performed to test differences in allele distributions among groups. A multiple logistic regression model was used to calculate odds ratios (ORs) and 95% confidence intervals (CIs), and multiple inheritance models to analyze the associations between schizophrenia and SNPs (the dominant, recessive and additive models).RESULTS: The minor allele frequencies of two SNPs were significantly higher in the schizophrenia group than in those of the control group (rs2963155 G > A : 0.25 vs. 0.18, p = 0.0066 ; rs7701443 A > G : 0.40 vs. 0.33, p = 0.012). The genotype frequencies of two SNPs were found to be significantly different between patients with schizophrenia and controls in the dominant model (rs2963155 : AG/GG vs. AA, OR = 1.66, 95% CI = 1.16–2.38, p = 0.0055, rs7701443 : AG/AA vs. GG, OR = 1.61, 95% CI = 1.11–2.34, p = 0.01) and the log-additive model (rs2963155 : AG vs. GG vs. AA, OR = 1.54, 95% CI = 1.13–2.10, p = 0.0067).CONCLUSIONS: This study showed significant associations between NR3C1 polymorphisms and schizophrenia. It suggests that NR3C1 may play a role in the pathogenesis of schizophrenia.
Alleles ; Gene Frequency ; Genetic Predisposition to Disease ; Genotype ; Humans ; Hydrocortisone ; Logistic Models ; Odds Ratio ; Polymorphism, Genetic ; Polymorphism, Single Nucleotide ; Receptors, Glucocorticoid ; Schizophrenia ; Stress, Psychological ; Wills

Psychiatric disorder as dysfunctional behavioural syndrome is a paradoxical phenomenon that is difficult to explain evolutionarily because moderate prevalence rate, high heritability and relatively low fitness are shown. Several evolutionary genetic models have been proposed to address this paradox. In this paper, I explain each model by dividing it into selective neutrality, mutation-selection balance, and balancing selection hypothesis, and discuss the advantages and disadvantages of them. In addition, the feasibility of niche specialization and frequency dependent selection as the plausible explanation about the central paradox is briefly discussed.
Mental Disorders ; Models, Genetic ; Prevalence

OBJECTIVE: Deep learning models, including recurrent neural network (RNN) and gated recurrent unit (GRU), were used to construct the clinical prognostic prediction models for peritoneal dialysis (PD) patients based on routine clinical data. The performance of the RNN and GRU were compared with logistic regression (LR), which is commonly used in medical researches. The possible underlining clinical implications based on the result from the GRU model were also investigated. METHODS: We used the clinical data from the PD center of Peking University Third Hospital as the data source. Both the baseline data at the beginning of dialysis, and the follow-up and prognostic data of the patients were used by the RNN and GRU prediction models. The hyper-parameters were tuned based on the 10-fold cross-validation. The risk prediction performance of each model was evaluated via area under the receiver operation characteristic curve (AUROC), recall rate and F1-score on the testset. RESULTS: A total of 656 patients with the 261 occurrences of death were included in the experiment. The total number of all diagnostic records were 13 091. The results on the testset showed that the AUROC of the LR model, RNN model, and GRU model was 0.701 4, 0.786 0, and 0.814 7, respectively. The predictive performances of the GRU and RNN models were significantly better than that of the LR model. The performances of the GRU and RNN models assessed by recall rate and F1-score were also significantly better than that of the LR model, in which the GRU model reached the best performance. In addition, the recall rates were different among different causes of death or by different prediction time windows. CONCLUSION The recurrent neural network model, especially the GRU model, is more effective in predicting PD patients' prognosis as compared with the LR model. This new model may be helpful for clinicians to provide timely intervention, thus improving the quality of care of PD.
Databases, Genetic ; Humans ; Logistic Models ; Neural Networks, Computer ; Peritoneal Dialysis ; Prognosis

Objective: To describe the genetic structure of populations in different areas of China, and explore the effects of different strategies to control the confounding factors of the genetic structure in cohort studies. Methods: By using the genome-wide association study (GWAS) on data of 4 500 samples from 10 areas of the China Kadoorie Biobank (CKB), we performed principal components analysis to extract the first and second principal components of the samples for the component two-dimensional diagram generation, and then compared them with the source of sample area to analyze the characteristics of genetic structure of the samples from different areas of China. Based on the CKB cohort data, a simulation data set with cluster sample characteristics such as genetic structure differences and extensive kinship was generated; and the effects of different analysis strategies including traditional analysis scheme and mixed linear model on the inflation factor (λ) were evaluated. Results: There were significant genetic structure differences in different areas of China. Distribution of the principal components of the population genetic structure was basically consistent with the geographical distribution of the project area. The first principal component corresponds to the latitude of different areas, and the second principal component corresponds to the longitude of different areas. The generated simulation data showed high false positive rate (λ=1.16), even if the principal components of the genetic structure was adjusted or the area specific subgroup analysis was performed, λ could not be effectively controlled (λ>1.05); while, by using a mixed linear model adjusting for the kinship matrix, λ was effectively controlled regardless of whether the genetic structure principal component was further adjusted (λ=0.99). Conclusions: There were large differences in genetic structure among populations in different areas of China. In molecular epidemiology studies, bias caused by population genetic structure needs to be carefully treated. For large cohort data with complex genetic structure and extensive kinship, it is necessary to use a mixed linear model for association analysis.
China ; Genetic Structures ; Genome-Wide Association Study ; Humans ; Linear Models ; Principal Component Analysis