Association between social support and mutual-support needs among the rural adults in China: a cross-sectional study

BackgroundIn rural China, there is now a huge gap between the supply and demand for old-age care. To close the gap, developing rural mutual old-age services is extremely important. The purpose of this study is to clarify the relationship among social support, mutual support need, and mutual support willingness.MethodsWe conducted an online questionnaire survey using a Chinese Internet research company; 2,102 valid responses were received. The measures comprised the Social Support Rating Scale, the Mutual Support Willingness Questionnaire, and the Mutual Support Needs Scale. We calculated Pearson correlations to explore the association of social support with mutual-support need and mutual-support-need willingness. Multivariate analyses were also conducted using these factors as dependent variables.ResultsThe total score for the mutual support need for the adults in rural areas was 58.0 ± 12.1 and 36.96 ± 6.40 for social support, approximately 86.8% of the participants were willing to participate in mutual support. Furthermore, mutual support needs were positively correlated with subjective support (p < 0.01) and support utilization (p < 0.01), but negatively correlated with willingness to support each other (p < 0.05). The need for mutual support was also associated with age, sex, education level, dissatisfaction with the current economic situation, health status, and so on.ConclusionIt is necessary for government and health care providers to assess the different needs of rural older people and encourage individuals and organizations to provide mutual support for older people, especially to enhance emotional care for older people and improve their use of support. This is of great significance for developing mutual support services in rural China

Using Multispectral Imaging to Reveal the Relationship between UV Absorbance and Sulphur Dioxide Concentration

The sulphur dioxide (SO2) concentration can be monitored via its absorbance in the ultraviolet (UV) region. To address the absence of a systematic study on the UV absorbance of varying SO2 concentrations, a multispectral imaging method was implemented in the present study. SO2 concentrations and various environmental conditions were controlled by a purpose-built environmental control system with a light path of 4.2 m. Five narrow-band-pass filters in front of a UV camera were used to implement multispectral imaging. Regression models of the relationship between UV absorbance and SO2 concentration at each wavelength are presented. Their residuals were kept relatively small by adopting Jenks natural breaks analysis, with a maximum standard deviation of 0.086. Temperature and SO2 concentrations were significantly associated with UV absorbance. Furthermore, smoothed look-up tables were developed to explicitly elucidate the correlation between UV absorbance and SO2. These have been represented as heat maps, showcasing an example of library construction using a combination of abundant research data

Amino acid metabolism regulated by lncRNAs: the propellant behind cancer metabolic reprogramming

Abstract Metabolic reprogramming is one of the main characteristics of cancer cells and plays pivotal role in the proliferation and survival of cancer cells. Amino acid is one of the key nutrients for cancer cells and many studies have focused on the regulation of amino acid metabolism, including the genetic alteration, epigenetic modification, transcription, translation and post-translational modification of key enzymes in amino acid metabolism. Long non-coding RNAs (lncRNAs) are composed of a heterogeneous group of RNAs with transcripts of more than 200 nucleotides in length. LncRNAs can bind to biological molecules such as DNA, RNA and protein, regulating the transcription, translation and post-translational modification of target genes. Now, the functions of lncRNAs in cancer metabolism have aroused great research interest and significant progress has been made. This review focuses on how lncRNAs participate in the reprogramming of amino acid metabolism in cancer cells, especially glutamine, serine, arginine, aspartate, cysteine metabolism. This will help us to better understand the regulatory mechanism of cancer metabolic reprogramming and provide new ideas for the development of anti-cancer drugs. Video Abstrac

Towards a Smart City: Development and Application of an Improved Integrated Environmental Monitoring System

Environmental deprivation is an issue influencing the urban wellbeing of a city. However, there are limitations to spatiotemporally monitoring the environmental deprivation. Thus, recent studies have introduced the concept of “Smart City” with the use of advanced technology for real-time environmental monitoring. In this regard, this study presents an improved Integrated Environmental Monitoring System (IIEMS) with the consideration on nine environmental parameters: temperature, relative humidity, PM2.5, PM10, CO, SO2, volatile organic compounds (VOCs), UV index, and noise. This system was comprised of a mobile unit and a server-based platform with nine highly accurate micro-sensors in-coupling into the mobile unit for estimating these environmental exposures. A calibration test using existing monitoring station data was conducted in order to evaluate the systematic errors. Two applications with the use of the new system were also conducted under different scenarios: pre- and post-typhoon days and in areas with higher and lower vegetation coverage. Linear regressions were applied to predict the changes in environmental quality after a typhoon and to estimate the difference in environmental exposures between urban roads and green spaces. The results show that environmental exposures interact with each other, while some exposures are also controlled by location. PM2.5 had the highest change after a typhoon with an estimated 8.0 μg/m³ decrease that was controlled by other environmental factors and geographical location. Sound level and temperature were significantly higher on urban roads than in urban parks. This study demonstrates the potential to use IIEMS for environmental quality measurements under the greater framework of a Smart City and for sustainability research

Maize Canopy and Leaf Chlorophyll Content Assessment from Leaf Spectral Reflectance: Estimation and Uncertainty Analysis across Growth Stages and Vertical Distribution

Accurate estimation of the canopy chlorophyll content (CCC) plays a key role in quantitative remote sensing. Maize (Zea mays L.) is a high-stalk crop with a large leaf area and deep canopy. It has a non-uniform vertical distribution of the leaf chlorophyll content (LCC), which limits remote sensing of CCC. Therefore, it is crucial to understand the vertical heterogeneity of LCC and leaf reflectance spectra to improve the accuracy of CCC monitoring. In this study, CCC, LCC, and leaf spectral reflectance were measured during two consecutive field growing seasons under five nitrogen treatments. The vertical LCC profile showed an asymmetric ‘bell-shaped’ curve structure and was affected by nitrogen application. The leaf reflectance also varied greatly between spatio–temporal conditions, which could indicate the influence of vertical heterogeneity. In the early growth stage, the spectral differences between leaf positions were mainly concentrated in the red-edge (RE) and near-infrared (NIR) regions, whereas differences were concentrated in the visible region during the mid-late filling stage. LCC had a strong linear correlation with vegetation indices (VIs), such as the modified red-edge ratio (mRER, R2 = 0.87), but the VI–chlorophyll models showed significant inversion errors throughout the growth season, especially at the early vegetative growth stage and the late filling stage (rRMSE values ranged from 36% to 87.4%). The vertical distribution of LCC had a strong correlation with the total chlorophyll in canopy, and sensitive leaf positions were identified with a multiple stepwise regression (MSR) model. The LCC of leaf positions L6 in the vegetative stage (R2-adj = 0.9) and L11 + L14 in the reproductive stage (R2-adj = 0.93) could be used to evaluate the canopy chlorophyll status (L12 represents the ear leaf). With a strong relationship between leaf spectral reflectance and LCC, CCC can be estimated directly by leaf spectral reflectance (mRER, rRMSE = 8.97%). Therefore, the spatio–temporal variations of LCC and leaf spectral reflectance were analyzed, and a higher accuracy CCC estimation approach that can avoid the effects of the leaf area was proposed

Maize Canopy and Leaf Chlorophyll Content Assessment from Leaf Spectral Reflectance: Estimation and Uncertainty Analysis across Growth Stages and Vertical Distribution

Accurate estimation of the canopy chlorophyll content (CCC) plays a key role in quantitative remote sensing. Maize (Zea mays L.) is a high-stalk crop with a large leaf area and deep canopy. It has a non-uniform vertical distribution of the leaf chlorophyll content (LCC), which limits remote sensing of CCC. Therefore, it is crucial to understand the vertical heterogeneity of LCC and leaf reflectance spectra to improve the accuracy of CCC monitoring. In this study, CCC, LCC, and leaf spectral reflectance were measured during two consecutive field growing seasons under five nitrogen treatments. The vertical LCC profile showed an asymmetric ‘bell-shaped’ curve structure and was affected by nitrogen application. The leaf reflectance also varied greatly between spatio–temporal conditions, which could indicate the influence of vertical heterogeneity. In the early growth stage, the spectral differences between leaf positions were mainly concentrated in the red-edge (RE) and near-infrared (NIR) regions, whereas differences were concentrated in the visible region during the mid-late filling stage. LCC had a strong linear correlation with vegetation indices (VIs), such as the modified red-edge ratio (mRER, R2 = 0.87), but the VI–chlorophyll models showed significant inversion errors throughout the growth season, especially at the early vegetative growth stage and the late filling stage (rRMSE values ranged from 36% to 87.4%). The vertical distribution of LCC had a strong correlation with the total chlorophyll in canopy, and sensitive leaf positions were identified with a multiple stepwise regression (MSR) model. The LCC of leaf positions L6 in the vegetative stage (R2-adj = 0.9) and L11 + L14 in the reproductive stage (R2-adj = 0.93) could be used to evaluate the canopy chlorophyll status (L12 represents the ear leaf). With a strong relationship between leaf spectral reflectance and LCC, CCC can be estimated directly by leaf spectral reflectance (mRER, rRMSE = 8.97%). Therefore, the spatio–temporal variations of LCC and leaf spectral reflectance were analyzed, and a higher accuracy CCC estimation approach that can avoid the effects of the leaf area was proposed

STUB1-mediated ubiquitination regulates the stability of GLUD1 in lung adenocarcinoma

Summary: The dysregulation of glutamine metabolism provides survival advantages for tumors by supplementing tricarboxylic acid cycle. Glutamate dehydrogenase 1 (GLUD1) is one of the key enzymes in glutamine catabolism. Here, we found that enhanced protein stability was the key factor for the upregulation of GLUD1 in lung adenocarcinoma. We discovered that GLUD1 showed a high protein expression in lung adenocarcinoma cells or tissues. We elucidated that STIP1 homology and U-box-containing protein 1 (STUB1) was the key E3 ligase responsible for ubiquitin-mediated proteasomal degradation of GLUD1. We further showed that lysine 503 (K503) was the main ubiquitination site of GLUD1, inhibiting the ubiquitination at this site promoted the proliferation and tumor growth of lung adenocarcinoma cells. Taken together, this study clarifies the molecular mechanism of GLUD1 in maintaining protein homeostasis in lung adenocarcinoma, which provides a theoretical basis for the development of anti-cancer drugs targeting GLUD1