1.Clinical Study on cerebral blood flow measured by color doppler ultrasound in healthy adults
Yuguang XIA ; Yanping XIAO ; Zhenxing CAO ; Li DENG ; Baowei DING
Chinese Journal of Primary Medicine and Pharmacy 2013;20(5):667-669
Objective To explore the different changes of the adult cerebral blood flow with ages,different weight and gender,to summarize the changing characteristics of cerebral blood flow.Methods 360 cases of examination were divided into two groups according to gender,and were divided into five groups at different ages,and were divided into four groups according to body mass index,using TCD detector blood flow velocity.Results 196 cases of male physical examination,the mean cerebral blood flow was (969.37 ± 117.54)ml/min;the 164 females physical examination,the average cerebral blood flow was (987.76 ± 114.34)ml/min,there was no statistically significant difference (P > 0.05).Different ages cerebral blood flow velocity were different,20 to 29-year-old group and the 30 to 39-year-old group had no significant difference (P > 0.05) ;40 to 49-year-old group,50 to 59 years,60 to 69 years old > 70 age group significantly declined compoued with the first two groups,there was significant difference (P < 0.05) ;there were significant difference between the four groups (P < 0.05).Overweight and obese group were significantly lower than the light and the normal group,there was a statistically significant difference (P < 0.05).Conclusion TCDcan be a sensitive and accurate hemodynamic changes in the human brain,and is very important in the early diagnosis,prevention,treatment,and follow-up of cerebrovascular disease.
2.Association study of LIS1 and TSNAX genes with bipolar disorder in Chinese Han population.
Xuan LI ; Lijie GUAN ; Yin LIN ; Xiaofei ZHANG ; Wenhao DENG ; Zhenxing YANG ; Xiaohong MA ; Guohui LAO ; Biyu YE ; Weijie HUANG ; Zeyu JIANG ; Guodong MIAO ; Guiyun XU ; Wentao LIU ; Yingcheng WANG ; Tao LI ; Liping CAO
Chinese Journal of Medical Genetics 2014;31(3):357-361
OBJECTIVETo assess the association of neural development-related genes LIS1and TSNAX with bipolar disorder in a Chinese Han population.
METHODSThree hundred and eight five patients (including 188 males and 197 females) from Guangzhou Brain Hospital with bipolar disorder meeting the Diagnostic and Statistic Manual of Bipolar Disorder (BDI) (Fourth Edition) criteria and 475 healthy controls from the local community were recruited. Ten single nucleotide polymorphisms (SNPs) of the LIS1 and TSNAX genes were genotyped by GoldenGate genotyping assay on an Illumina Beadstation 500 machine. Association analyses of SNPs and haplotypes were performed with Plink 1.07 software.
RESULTSAnalysis of the total sample has failed to find any association of SNP or haplotype of the two genes with BDI (P> 0.05). When patients were divided into subgroups with or without psychotic symptom, no significant association of the two genes was found with psychotic BDI or non-psychotic BDI (P> 0.05). No significant association was found between any SNP and haplotype of two genes and female BDI or male BDI, nor were significant association found between age of onset and LIS1 and TSNAX gene polymorphisms.
CONCLUSIONOur results indicated that LIS1 and TSNAX genes are not associated with susceptibility to bipolar I disorder in Chinese Han population.
1-Alkyl-2-acetylglycerophosphocholine Esterase ; genetics ; Adolescent ; Adult ; Aged ; Aged, 80 and over ; Asian Continental Ancestry Group ; ethnology ; genetics ; Bipolar Disorder ; ethnology ; genetics ; Case-Control Studies ; DNA-Binding Proteins ; genetics ; Female ; Genetic Predisposition to Disease ; Genotype ; Humans ; Male ; Microtubule-Associated Proteins ; genetics ; Middle Aged ; Polymorphism, Single Nucleotide ; Young Adult
3.MF-SuP-pKa: Multi-fidelity modeling with subgraph pooling mechanism for pKa prediction.
Jialu WU ; Yue WAN ; Zhenxing WU ; Shengyu ZHANG ; Dongsheng CAO ; Chang-Yu HSIEH ; Tingjun HOU
Acta Pharmaceutica Sinica B 2023;13(6):2572-2584
Acid-base dissociation constant (pKa) is a key physicochemical parameter in chemical science, especially in organic synthesis and drug discovery. Current methodologies for pKa prediction still suffer from limited applicability domain and lack of chemical insight. Here we present MF-SuP-pKa (multi-fidelity modeling with subgraph pooling for pKa prediction), a novel pKa prediction model that utilizes subgraph pooling, multi-fidelity learning and data augmentation. In our model, a knowledge-aware subgraph pooling strategy was designed to capture the local and global environments around the ionization sites for micro-pKa prediction. To overcome the scarcity of accurate pKa data, low-fidelity data (computational pKa) was used to fit the high-fidelity data (experimental pKa) through transfer learning. The final MF-SuP-pKa model was constructed by pre-training on the augmented ChEMBL data set and fine-tuning on the DataWarrior data set. Extensive evaluation on the DataWarrior data set and three benchmark data sets shows that MF-SuP-pKa achieves superior performances to the state-of-the-art pKa prediction models while requires much less high-fidelity training data. Compared with Attentive FP, MF-SuP-pKa achieves 23.83% and 20.12% improvement in terms of mean absolute error (MAE) on the acidic and basic sets, respectively.
4.Kinome-wide polypharmacology profiling of small molecules by multi-task graph isomorphism network approach.
Lingjie BAO ; Zhe WANG ; Zhenxing WU ; Hao LUO ; Jiahui YU ; Yu KANG ; Dongsheng CAO ; Tingjun HOU
Acta Pharmaceutica Sinica B 2023;13(1):54-67
Prediction of the interactions between small molecules and their targets play important roles in various applications of drug development, such as lead discovery, drug repurposing and elucidation of potential drug side effects. Therefore, a variety of machine learning-based models have been developed to predict these interactions. In this study, a model called auxiliary multi-task graph isomorphism network with uncertainty weighting (AMGU) was developed to predict the inhibitory activities of small molecules against 204 different kinases based on the multi-task Graph Isomorphism Network (MT-GIN) with the auxiliary learning and uncertainty weighting strategy. The calculation results illustrate that the AMGU model outperformed the descriptor-based models and state-of-the-art graph neural networks (GNN) models on the internal test set. Furthermore, it also exhibited much better performance on two external test sets, suggesting that the AMGU model has enhanced generalizability due to its great transfer learning capacity. Then, a naïve model-agnostic interpretable method for GNN called edges masking was devised to explain the underlying predictive mechanisms, and the consistency of the interpretability results for 5 typical epidermal growth factor receptor (EGFR) inhibitors with their structure‒activity relationships could be observed. Finally, a free online web server called KIP was developed to predict the kinome-wide polypharmacology effects of small molecules (http://cadd.zju.edu.cn/kip).
5. Construction and identification of mouse model with conditional knockout of p75 neurotrophin receptor gene in epidermal cells by Cre-loxP system
Rui SUN ; Yongqian CAO ; Jiaxu MA ; Siyuan YIN ; Min ZHANG ; Ru SONG ; Hang JIANG ; Yan GAO ; Huayu ZHANG ; Zhang FENG ; Jian LIU ; Zhenxing LIU ; Yibing WANG
Chinese Journal of Burns 2019;35(10):740-745
Objective:
To construct and identify a mouse model with conditional knockout (cKO) of p75 neurotrophin receptor (p75NTR-cKO) gene in epidermis cells by Cre-loxP system.
Methods:
Five p75NTRflox/flox transgenic C57BL/6J mice (aged 6-8 weeks, male and female unlimited, the age and sex of mice used for reproduction were the same below) and five keratin 14 promotor-driven (KRT14-) Cre+ /- transgenic C57BL/6J mice were bred and hybridized via Cre-loxP system. Five p75NTRflox/+ ·KRT14-Cre+ /- mice selected from the first generation of mice were mated with five p75NTRflox/flox mice to obtain the second generation hybrids. After the second generation mice were born 20-25 days, the parts of the mice tail were cut off to identify the genotype by polymerase chain reaction method. Four p75NTR gene complete cKO mice (6 weeks old) and 4 wild-type mice (6 weeks old) were selected and sacrificed respectively. The abdominal skin tissue and brain tissue were excised to observe the expression of p75NTR in the two tissue of two types of mice by immunohistochemical staining. The abdominal skin tissue of two types of mice was obtained to observe the histomorphological changes by hematoxylin and eosin staining.
Results:
(1) Twenty second generation mice were bred. The genotype of 4 mice was p75NTRflox/flox·KRT14-Cre+ /-(p75NTR-/-), i. e. p75NTR gene complete cKO mice; the genotype of 5 mice was p75NTRflox/+ ·KRT14-Cre+ /-, i. e. p75NTR gene partial cKO mice; the genotype of 5 mice was p75NTRflox/flox·KRT14-Cre-/-, and that of 6 mice was p75NTRflox/+ ·KRT14-Cre-/-, all of which were wild-type mice. (2) The expression of p75NTR was negative in skin epidermis tissue of p75NTR gene complete cKO mice, while numerous p75NTR positive expression was observed in skin epidermis tissue of wild-type mice. Abundant p75NTR positive expression was observed in brain tissue of both wild-type mice and p75NTR gene complete cKO mice. (3) There was no abnormal growth of skin epidermis tissue in both wild-type mice and p75NTR gene complete cKO mice, with intact hair follicle structure.
Conclusions
Applying Cre-loxP system can successfully construct a p75NTR-cKO mice model in epidermis cells without obvious changes in skin histomorphology.