miR-196a targeting LRIG3 promotes the proliferation and migration of cervical cancer cells.

In recent years, studies have found that miR-RNA plays a role in cell proliferation, differentiation, apoptosis and metabolism. Among them, miR-196a is closely related to cervical cancer. Therefore, this experiment investigates the effect of mir-196a expression on cervical cancer cells and related mechanisms. The expression level of miR-196a in the cervical cancer cell line was assayed with the RT-PCR method, and liposome transfection was used to investigate its up-regulation or down-regulation in cervical cancer cells. The CCK-8 method and flow cytometry were used to measure cervical cancer cell proliferation and apoptosis, while the Transwell assay was used to determine cell migration and invasion of each transfection group. Bioinformatics was used to predict the target gene of miR-196a, which was verified using dual luciferase report experiment and Western blot, and miR-196a was further transfected with si-LRIG3 to detect its reversal effect on miR-196a regulation. Inhibition of the expression of miR-196a significantly reduced the proliferation, migration and invasion of cervical cancer cells, and promoted their apoptosis. Results from dual luciferase assay showed that miR-196a and LRIG3 had direct targeting effects. Cell proliferation, migration and invasion were enhanced by a reduction in the expression level of LRIG3 protein after miR-196a inhibitor cells were transfected with si-LRIG3. The expression of miR-196a is up-regulated in cervical cancer, and it promotes the growth of cervical cancer by its targeting effect on LRIG3 expression, resulting in enhancement of the proliferation, migration and invasion ability of cervical cancer cells, and inhibition of apoptosis.

Identification and analysis of vulnerable populations for malaria based on K-prototypes clustering.

Malaria is a serious public health threat in Yunnan Province of China and has been frequently reported in some endemic regions, such as Tengchong County, with high morbidity. It is essential to analyze the characteristics of malaria cases and identify vulnerable populations. Previous studies about vulnerable populations have mostly used a statistical grouping method to count frequence from a single aspect rather than defined clustered groups. Based on descriptive analysis of the temporal variation and demographic structure of the populations with malaria infection, we used a k-prototypes clustering algorithm to cluster vulnerable populations in Tengchong County in three dimensions, according to sex, age, and occupation. The results indicated that a high incidence of malaria occurred mainly in young male farmers and young or middle-aged male migrant workers. Imported cases, low education level, lack of mosquito bite prevention, and risk behaviors contributed to the high malaria incidence in these groups. Double verification ensured the reliability of this method and reasonability of the results. In addition, we highlighted the importance of targeting prevention and control of malaria for vulnerable groups. We provided suggestions of policies and measures to be implemented by regional governments and at household and individual levels for farmers and migrant workers respectively. Using the k-prototypes clustering algorithm, we efficiently identified those populations at greatest risk of malaria infection. Our results may serve as scientific guidance for targeted malaria prevention and control in Yunnan Province.

Differentiating drought legacy effects on vegetation growth over the temperate Northern Hemisphere.

In view of future changes in climate, it is important to better understand how different plant functional groups (PFGs) respond to warmer and drier conditions, particularly in temperate regions where an increase in both the frequency and severity of drought is expected. The patterns and mechanisms of immediate and delayed impacts of extreme drought on vegetation growth remain poorly quantified. Using satellite measurements of vegetation greenness, in-situ tree-ring records, eddy-covariance CO2 and water flux measurements, and meta-analyses of source water of plant use among PFGs, we show that drought legacy effects on vegetation growth differ markedly between forests, shrubs and grass across diverse bioclimatic conditions over the temperate Northern Hemisphere. Deep-rooted forests exhibit a drought legacy response with reduced growth during up to 4 years after an extreme drought, whereas shrubs and grass have drought legacy effects of approximately 2 years and 1 year, respectively. Statistical analyses partly attribute the differences in drought legacy effects among PFGs to plant eco-hydrological properties (related to traits), including plant water use and hydraulic responses. These results can be used to improve the representation of drought response of different PFGs in land surface models, and assess their biogeochemical and biophysical feedbacks in response to a warmer and drier climate.

The Impact of Technological Progress in the Energy Sector on Carbon Emissions: An Empirical Analysis from China.

This paper investigates the relationship between technological progress in the energy sector and carbon emissions based on the Environment Kuznets Curve (EKC) and data from China during the period of 1995-2012. Our study confirms that the situation in China conforms to the EKC hypothesis and presents the inverted U-curve relationship between per capita income and carbon emissions. Furthermore, the inflection point will be reached in at least five years. Then, we use research and development (R & D) investment in the energy industry as the quantitative indicator of its technological progress to test its impact on carbon emissions. Our results show that technological progress in the energy sector contributes to a reduction in carbon emissions with hysteresis. Furthermore, our results show that energy efficiency improvements are also helpful in reducing carbon emissions. However, climate policy and change in industrial structure increase carbon emissions to some extent. Our conclusion demonstrates that currently, China is not achieving economic growth and pollution reduction simultaneously. To further achieve the goal of carbon reduction, the government should increase investment in the energy industry research and improve energy efficiency.

Assessment of SIP Buildings for Sustainable Development in Rural China Using AHP-Grey Correlation Analysis.

Traditional rural residential construction has the problems of high energy consumption and severe pollution. In general, with sustainable development in the construction industry, rural residential construction should be aimed towards low energy consumption and low carbon emissions. To help achieve this objective, in this paper, we evaluated four different possible building structures using AHP-Grey Correlation Analysis, which consists of the Analytic Hierarchy Process (AHP) and the Grey Correlation Analysis. The four structures included the traditional and currently widely used brick and concrete structure, as well as structure insulated panels (SIPs). Comparing the performances of economic benefit and carbon emission, the conclusion that SIPs have the best overall performance can be obtained, providing a reference to help builders choose the most appropriate building structure in rural China.