The Association between Leptin Level and Breast Cancer: A Meta-Analysis

Background

Contradictory results have been reported regarding the association between leptin level and breast cancer. Therefore, a meta-analysis was performed to investigate this issue.

Methods

Published literature from PubMed and the Chinese National Knowledge Infrastructure (CNKI) Database was retrieved. This study was performed based on different cases and control groups. The combined effect () with 95% confidence interval (CI) was calculated using fixed-effects or random-effects model analysis.

Results

Overall, the mean serum leptin level of case groups was significantly higher than that of control groups. A) For 9 studies comparing breast cancer cases and healthy controls the combined effect was 0.58 with 95% CI (0.48, 0.68). B) For 4 studies comparing premenopausal breast cancer cases and healthy controls the was 0.32 (0.12, 0.52). C) For 5 studies comparing postmenopausal cases and healthy controls the was 0.65 (0.46, 0.84). D) For 4 studies comparing breast cancer cases and breast benign controls the was 0.38 (0.17, 0.59). E) For 2 studies comparing premenopausal breast cancer cases and breast benign controls the was 0.33 (-0.25, 0.91). F) For 6 studies comparing postmenopausal breast cancer cases and breast benign controls the was 0.39 (0.19, 0.60). G) For 4 studies comparing lymph node metastasis positive cases and negative controls the was 0.72 (0.45, 1.00). H) For 3 studies comparing breast benign cases and healthy controls the was 0.71 (0.41, 1.01).

Conclusion

This meta-analysis suggests that leptin level plays a role in breast cancer and has potential for development as a diagnostic tool.     

RNAi-Directed Downregulation of Vacuolar H+ -ATPase Subunit A Results in Enhanced Stomatal Aperture and Density in Rice

Stomatal movement plays a key role in plant development and response to drought and salt stress by regulating gas exchange and water loss. A number of genes have been demonstrated to be involved in the regulation of this process. Using inverse genetics approach, we characterized the function of a rice (Oryza sativa L.) vacuolar H⁺-ATPase subunit A (OsVHA-A) gene in stomatal conductance regulation and physiological response to salt and osmotic stress. OsVHA-A was constitutively expressed in different rice tissues, and the fusion protein of GFP-OsVHA-A was exclusively targeted to tonoplast when transiently expressed in the onion epidermal cells. Heterologous expression of OsVHA-A was able to rescue the yeast mutant vma1Δ (lacking subunit A activity) phenotype, suggesting that it partially restores the activity of V-ATPase. Meanwhile, RNAi-directed knockdown of OsVHA-A led to a reduction of vacuolar H⁺-ATPase activity and an enhancement of plasma membrane H⁺-ATPase activity, thereby increasing the concentrations of extracellular H⁺ and intracellular K⁺ and Na⁺ under stress conditions. Knockdown of OsVHA-A also resulted in the upregulation of PAM3 (plasma membrane H⁺-ATPase 3) and downregulation of CAM1 (calmodulin 1), CAM3 (calmodulin 3) and YDA1 (YODA, a MAPKK gene). Altered level of the ion concentration and the gene expression by knockdown of OsVHA-A probably resulted in expanded aperture of stomatal pores and increased stomatal density. In addition, OsVHA-A RNAi plants displayed significant growth inhibition under salt and osmotic stress conditions. Taken together, our results suggest that OsVHA-A takes part in regulating stomatal density and opening via interfering with pH value and ionic equilibrium in guard cells and thereby affects the growth of rice plants.     

Expression Stabilities of Candidate Reference Genes for RT-qPCR under Different Stress Conditions in Soybean

Due to its accuracy, sensitivity and high throughput, real time quantitative PCR (RT-qPCR) has been widely used in analysing gene expression. The quality of data from such analyses is affected by the quality of reference genes used. Expression stabilities for nine candidate reference genes widely used in soybean were evaluated under different stresses in this study. Our results showed that EF1A and ACT11 were the best under salinity stress, TUB4, TUA5 and EF1A were the best under drought stress, ACT11 and UKN2 were the best under dark treatment, and EF1B and UKN2 were the best under virus infection. EF1B and UKN2 were the top two genes which can be reliably used in all of the stress conditions assessed.     

Design and Optimization of Planting Process Parameters for 2ZYX-2 Type Green Onion Ditching and Transplanting Machine

Considering the current low level of mechanization for domestic green onion planting and the high labor intensity of artificial planting, a 2ZYX-2 green onion ditching and transplanting machine, which can complete ditching, ridging, transplanting, repression, soil covering and other operations, is designed in this study. The Central Composite test design method was carried out with the speed of the transplanting machine, the depth of the opener and the horizontal position of the opener as the experimental factors and with the qualification ratio of perpendicularity, the variation coefficient of the plant spacing and the qualification ratio of the planting depth as the test index. Through the analysis of the model interaction and response surface, the change laws that the influence the machine’s forward speed, the depth of the opener and the horizontal position of the opener were studied. The regression model was optimized by Design-Expert 8.0.6 software, and the accuracy of the predicted results was verified by experiments. The optimal working parameters showed that the forward speed of the machine was 0.06 m/s, the depth of the opener was 102 mm, and the horizontal position of the opener was 29 mm. Under conditions of optimal working parameters, the qualification rate of the verticality was 86.83%, the coefficient of variation for the plant spacing was 2.77, and the pass rate of planting depth was 88.26%. The research related to the thesis can provide a reference for the mechanized planting of green onion, which is of great significance to the cost-effectiveness of the green onion industry.     

A novel peroxiredoxin from the antagonistic endophytic bacterium Enterobacter sp. V1 contributes to cotton resistance against Verticillium dahliae

Plant and Soil - [Aims] To reveal the molecular mechanism of endophytic bacteria in Verticillium wilt-resistant cottons and deeply understand the interaction between soil and plants. [Methods]...     

铜绿假单胞菌锌离子摄取系统的研究进展

锌作为一种结构、催化和信号的成分,在许多生理过程中起着关键的作用。它也是病原微生物生长所必需的,不但参与病原微生物代谢和各种毒力因子的调控,而且是病原微生物在宿主中感染和定殖所必需的。铜绿假单胞菌侵染宿主发挥毒力时,宿主会采取营养免疫的策略来限制体内环境中游离的锌离子浓度而抑制该病原菌的感染和定殖。反过来,铜绿假单胞菌则通过自身的锌离子摄取系统克服宿主的营养免疫防御。本综述重点介绍了铜绿假单胞菌中已知的3种锌离子摄取系统(ZnuABC摄取系统、HmtA摄取系统和CntRLMN摄取系统)和锌摄取调控蛋白Zur,同时分析了其他潜在的锌离子摄取途径,并进一步阐述了铜绿假单胞菌锌离子摄取系统在其侵染宿主发挥毒力时和抵御宿主营养免疫时发挥的重要作用。系统总结铜绿假单胞菌对锌离子的摄取过程,旨在为靶向锌离子摄取系统的新型抗铜绿假单胞菌药物的开发提供指导。     

Three Meta-Analyses Define a Set of Commonly Overexpressed Genes from Microarray Datasets on Astrocytomas

Glioma is one of the most common tumors of the central nervous system, and one of its main types is astrocytoma. Microarray technology has been widely used to explore the molecular mechanism of cancer. It is universally accepted that meta-analysis considerably improves the statistical robustness of results, particularly in clinical research. To obtain the maximum reliability, we used three different meta-analyses to integrate the four microarray datasets, GSE16011, GSE4290, GSE2223, and GSE19728 (local), and defined the common differentially expressed genes (DEGs) in astrocytomas compared with normal brain tissue. Four DEGs, PCNA, CDC2, CDK2 and CCNB2, which are components of the cell cycle pathway, were chosen for Real-Time Polymerase Chain Reaction (RT-PCR) and immunohistochemistry validation. PCNA is similar to the P53 gene and has been widely implicated in various cancers including gliomas. Therefore, the expression status of PCNA in our study was considered as a reference to test our whole experimental scheme, and the results indicate that our methodology is valid. Although a few studies have reported the overexpression of the CDC2, CDK2 and CCNB2 genes in glioma cell lines, we are the first to identify the statuses of these genes in human astrocytoma tissues at the mRNA and protein levels. The results of the gene validations strongly suggested that the genes play an important role in astrocytomas and could potentially be valuable in the diagnosis and treatment of astrocytoma.     

Estimating soil respiration using spectral vegetation indices and abiotic factors in irrigated and rainfed agroecosystems

Aims

Our aims were to identify the primary factors involved in soil respiration (R_s) variability and the role that spectral vegetation indices played in R_s estimation in irrigated and rainfed agroecosystems during the growing season.

Methods

We employed three vegetation indices [i.e., normalized difference vegetation index (NDVI), green edge chlorophyll index (CI_{green edge}) and enhanced vegetation index (EVI)] derived from the Moderate-resolution Imaging Spectroradiometer (MODIS) surface reflectance product as approximations of crop gross primary production (GPP) for R_s estimation. Different statistical models were used to analyze the dependencies of R_s on soil temperature, soil water content and plant photosynthesis, and accuracy of these models were compared in the irrigated and rainfed agroecosystems.

Results

The results demonstrated that a model based only on abiotic factors (e.g., soil temperature and soil water content) failed to describe part of the growing-season variability in R_s. Residual analysis indicated that R_s was influenced by a short-term gross primary production (GPP) and a longer-term (≥3 days) accumulated GPP in the irrigated and rainfed agroecosystems. Therefore, photosynthesis dependency of R_s should be included in the R_s model to describe the growing-season dynamics of R_s. Among the three VIs, CI_{green edge} showed generally better correlations with GPP at different cumulative times and canopy green leaf area index than EVI and NDVI. Adding the CI_{green edge} into the model considering only soil temperature and soil water content significantly improved the simulation accuracy of R_s.

Conclusions

Our results suggest that spectral vegetation index from remote sensing could be used to estimate R_s, which will be helpful for the development of a future R_s model over a large spatial scale.