Aim To explore the growth inhibition effects of jasmonates on human neuroblastoma SH-SY5Y cell line,and to investigate its mechanisms.Methods After administration of 0.5~2.5 mmol?L-1 jasmonates for 6~24 hrs, the growth inhibition rates of SH-SY5Y cells were studied by MTT colorimetry.Cell cycle phases were assayed by propidium iodide staining flow cytometry. Cellular apoptosis was inspected by Hoechst 33258 fluorescent staining and Annexin V-FITC and propidium iodide staining flow cytometry.Gene expressions of PCNA, cyclin D1 and N-myc were determined by reverse transcription polymerase chain reaction.Results Jasmonates inhibited the growth of SH-SY5Y cells in a dose-and time-dependent manner,while the methyl jasmonate was the most efficient. After administration of 0.5 to 2.5 mmol?L-1 of methyl jasmonate for 24 hrs,the growth inhibition rates of cells reached 5.75%~88.7%(P

Objective To analyze the topological characteristics of the brain structural network in primary angle-closure glaucoma (PACG) patients by applying graph theoretical approaches.Methods From October 2015 to April 2017, nineteen PACG patients and nineteen gender-and age-matched healthy controls (HCs) were enrolled to undergo MRI scan. The whole brain was parceled into 90 regions by automated anatomical labeling template, and the brain structural network was constructed by the fiber distribution of continuous tracking method.Both the weighted and unweighted network analyses were performed.The global and regional properties were computed by graph theoretical analysis.To compare the brain network regional properties between two groups, two-sample t-test was utilized.The correlations between the brain structural network properties and clinical parameters were further analysed. Results Both two groups were found to follow the efficient small-world characteristics. Compared to HCs, the brain structural network in PACG patients showed no statistical significance in the small-worldness, average shortest path, clustering coefficient, global efficiency and local efficiency(P＞0.05). Compared to the HCs, the PACG patients showed decreased nodal efficiency in the right superior frontal gyrus, right inferior frontal gyrus, left median cingulate and paracingulate gyri, left amygdala and left cuneus(P＜0.05). Compared to HCs, the PACG patients showed decreased node degree in left superior frontal gyrus, medial orbital, right inferior frontal gyrus, left amygdala, left cuneus and left lingual gyrus(P＜0.05). Compared with the hub regions in healthy controls'network, we found that two hub regions disappeared.Those hubs were right inferior parietal lobule and left middle temporal gyrus. Node degree in left amygdala showed negatively correlated with visual ability (r=-0.679, P=0.001). Node degree in left lingual gyrus showed negatively correlated with vertical CDR(r=-0.791, P=0.001),which showed positively correlated with visual acuity(r=0.538, P=0.018).Conclusions The brain structural network in PACG patients showed small-worldness properties as HCs group. The alterations of local properties in visual, emotion-cognition brain regions were observed, manifesting that PACG can affect the topology properties of the structural brain network.

ObjectiveTo investigate the main risk factors for liver cirrhosis in chronic hepatitis B （CHB） patients with high metabolic risk， to establish a noninvasive predictive model， and to compare the diagnostic efficiency of this model and other models including fibrosis-4 （FIB-4）， aspartate aminotransferase-to-platelet ratio index （APRI）， gamma-glutamyl transpeptidase-to-platelet ratio （GPR）， and Forns index. MethodsA total of 527 CHB patients with high metabolic risks who were admitted to The Second Affiliated Hospital of Guangxi Medical University from September 1， 2017 to October 31， 2022 were enrolled as subjects， and they were randomly divided into modeling group with 368 patients and validation group with 159 patients at a ratio of 7∶3. The LASSO regression analysis and the multivariate Logistic regression analysis were performed for the modeling group to identify independent risk factors， and a nomogram model was established. The receiver operating characteristic （ROC） curve， the calibration curve， and the decision curve analysis were used to validate the nomogram prediction model in the modeling group and the validation group and assess its discriminatory ability， calibration， and clinical practicability. The Delong test was used to compare the area under the ROC curve （AUC） of the nomogram prediction model and other models. ResultsThe multivariate Logistic regression analysis showed that prealbumin （odds ratio ［OR］ = 0.993， 95% confidence interval ［CI］： 0.988 — 0.999， P= 0.019）， thrombin time （OR=1.182， 95% CI： 1.006 — 1.385， P=0.047）， log₁₀ total bilirubin （TBil） （OR=1.710， 95%CI： 1.239 — 2.419， P=0.001）， and log₁₀ alpha-fetoprotein （AFP） （OR=1.327， 95%CI： 1.052 — 1.683， P=0.018） were independent influencing factors for liver cirrhosis in CHB patients with high metabolic risks. A nomogram model for risk prediction was established based on the multivariate analysis， which had an AUC of 0.837 （95%CI： 0.788 — 0.888）， a specificity of 73.5%， and a sensitivity of 84.7%， as well as a significantly higher diagnostic efficiency than the models of FIB-4 （0.739）， APRI （0.802）， GPR （0.800）， and Forns index （0.709） （Z=2.815， 2.271， 1.989， and 2.722， P=0.005， 0.017， 0.045， and 0.006）. ConclusionThe nomogram model established based on prealbumin， thrombin time， log₁₀ TBil， and log₁₀ AFP has a certain clinical application value.