BACKGROUND Golgi phosphoprotein 3 (GOLPH3) has been reported to be involved in the development of several human cancers. Our previous study showed that GOLPH3 expression in glioma tissues was related to the severity of the malignancy of the cancer. However, the mechanism by which GOLPH3 affects cell apoptosis is largely unknown. The present study was designed to explore the possible mechanism of GOLPH3 in cell apoptosis. MATERIAL AND METHODS To analyze the biological role of GOLPH3 in glioma cells, we used GOLPH3 small interference RNA in apoptosis of glioma cells. The apoptosis of glioma cells was detected by flow cytometry. The expression level of GOLPH3 and NDRG1 protein was determined by Western blot analyses and immunohistochemical staining, respectively, to evaluate their association with glioma. Tumor tissues were collected from patients with glioma. Normal cerebral tissues were acquired from cerebral trauma patients undergoing internal decompression surgery. RESULTS We confirm that the decrease of GOLPH3 that promotes the apoptosis of glioma cells may be regulated by the activation of NDRG1 and cleaved capcase 3. There was a inverse association between GOLPH3 and NDRG1 in glioma samples. CONCLUSIONS Our findings indicate that GOLPH3 and NDRG1 both play an important role in glioma etiology. Either GOLPH3 or NDRG1 might be a potential candidate for malignant glioma therapy.
Abstract γ -aminobutyric acid (GABA) is closely related to the growth, development and stress resistance of plants. Combined with the previous study of GABA to promote the cotton against abiotic stresses, the characteristics and expression patterns of GABA branch gene family laid the foundation for further explaining its role in cotton stress mechanism. Members of GAD, GAB-T and SSADH (three gene families of GABA branch) were identified from the Gossypium hirsutum , Gossypium barbadense , Gossypium arboreum and Gossypium raimondii genome. The GABA branch genes were 10 GAD genes, 4 GABA-T genes and 2 SSADH genes. The promoter sequences of genes mainly contains response-related elements such as light, hormone and environment.Phylogenetic analysis shows that GAD indicating that even in the same species, the homologous sequences in the family. The GABA-T gene of each cotton genus was in sum the family had gene loss in the process of dicotyledon evolution. SSADH families Gossypium hirsutum , Gossypium barbadense , Gossypium arboreum and Gossypium raimondii were closely related to the dicot plants.GABA gene is involved in the regulation of salt stress and high temperature in Gossypium hirsutum .GABA attenuated part of the abiotic stress damage by increasing leaf protective enzyme activity and reducing reactive oxygen species production.This lays the foundation for a thorough analysis of the mechanism of GABA in cotton stress resistance.
The purpose was to explore the correlation between hematological parameters and the progression of WHO grade II meningioma, and establish a clinical prognostic model based on hematological parameters and clinical prognostic factors to predict the progression-free survival (PFS) of patients.A total of 274 patients with WHO grade II meningiomas were included. Patients were randomly divided into a training cohort (192, 70%) and a test cohort (82, 30%). In the training cohort, the least absolute shrinkage and selection operator Cox regression analysis were used to screen for hematological parameters with prognostic value, and the hematological risk model (HRM) was constructed based on these parameters; univariate and multivariate Cox regression analyses were utilized to screen for clinical prognostic factors, and a clinical prognostic model was constructed based on clinical prognostic factors and HRM. The prognostic stability and accuracy of the HRM and clinical prognostic model were verified in the test cohort. Subgroup analysis was performed according to the patients' different clinical characteristics.Preoperative neutrophil-to-lymphocyte ratio, lymphocyte-to-monocyte ratio, platelet-to-lymphocyte ratio, albumin-to-globulin ratio, D-dimer, fibrinogen, and lactate dehydrogenase were associated with the PFS of patients. The areas under curve of the HRM were 0.773 (95% confidence interval [CI] 0.707-0.839) and 0.745 (95% CI 0.637-0.852) in the training cohort and test cohort, respectively. The progression risk was higher in the high-risk group than that in the low-risk group categorized by the optimal cutoff value (2.05) of hematological risk scores. The HRM, age, tumor location, tumor size, peritumoral edema, extent of resection, Ki-67 index, and postoperative radiotherapy were the prognostic factors for the progression of meningiomas. The corrected C-index of the clinical prognosis model was 0.79 in the training cohort. Clinical decision analysis showed that the clinical prognostic model could be used to obtain favorable clinical benefits. In the subgroup analysis, the HRM displayed excellent prognostic stability and general applicability in different subgroups.Preoperative hematological parameters are associated with the postoperative progression of WHO grade II meningiomas. The clinical prognosis model constructed based on hematological parameters and clinical prognostic factors has favorable predictive accuracy and clinical benefits.
Abstract Farmers' participation in food safety governance is an important part of food safety social co-governance, and the accurate identification of its influencing factors and their related paths is of guiding significance to the scientific decision-making of food safety governance. The system of influencing factors of farmers' participation in food safety governance was constructed from four dimensions, and the influence network of each dimension was revealed by decision laboratory analysis (DEMATEL). The hierarchical structure and correlation path of influencing factors were determined by interpretive structural model (ISM), and the attributes of influencing factors were further classified by cross influence matrix multiplication (MICMAC). The results show that the influencing factors of farmers' participation in food safety governance can be divided into seven levels, among which the level of education and the status of village cadres are the fundamental characteristic factors. the degree of rural informatization, the intensity of government supervision, the promotion of village committees, the response of the government and the degree of disclosure of government information are the deep core factors, and risk cognition, political trust and family eating habits are special factors. Taking the importance and attribute status of farmers' participation in food safety governance into decision-making considerations is of great significance to improve the efficiency of food safety governance.
Landslides are among the most prevalent geological hazards and are characterized by their high frequency, significant destructive potential, and considerable incident rate. Annually, these events lead to substantial casualties and property losses. Thus, conducting landslide susceptibility assessments in the regions vulnerable to such hazards has become crucial. In recent years, the coupling of traditional statistical methods with machine learning techniques has shown significant advantages in assessing landslide risk. This study focused on Sichuan Province, China, a region characterized by its vast area and diverse climatic and geological conditions. We selected 13 influencing factors for the analysis: elevation, slope, aspect, plan curve, profile curve, valley depth, precipitation, the stream power index (SPI), the topographic wetness index (TWI), the topographic position index (TPI), surface roughness, fractional vegetation cover (FVC), and slope height. This study incorporated the certainty factor method (CF), the information value method (IV), and their coupling with the decision tree C5.0 model (DT) and a logistic regression model (LR) as follows: IV-LR, IV-DT, CF-LR, and CF-DT. The results, validated by an ROC curve analysis, demonstrate that the evaluation accuracy of all six models exceeded 0.750 (AUC > 0.750). The IV-LR model exhibited the highest accuracy, with an AUC of 0.848. When comparing the accuracy among the models, it is evident that the coupling models outperformed the individual statistical models. Based on the results of the six models, a landslide susceptibility map was generated, categorized into five levels. High and very high landslide risk zones are mainly concentrated in the eastern and southeastern regions, covering nearly half of Sichuan Province. Medium-risk areas form linear distributions from northeast to southwest, occupying a smaller proportion of the area. Extremely low- and low-risk zones are predominantly located in the western and northwestern regions. The density of the landslide points increases with higher risk levels across the regions. This further validates the suitability of this research methodology for landslide susceptibility studies on a large scale. Consequently, this methodology can provide crucial insights for landslide prevention and mitigation efforts in this region.
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