An innovative method based on Gaussian cloud distribution and sample information richness for eutrophication assessment of Yangtze's lakes and reservoirs under uncertainty.

The precise assessment of a water body's eutrophication status is essential for making informed decisions in water environment management. However, conventional approaches frequently fail to consider the randomness, fuzziness, and inherent hidden information of water quality indicators. These would result in an unreliable assessment. An enhanced method was proposed for the eutrophication assessment under uncertainty in this study. The multi-dimension gaussian cloud distribution was introduced to capture the randomness and fuzziness. The Shannon entropy based on various sample size and trophic levels was proposed to maximize valuable information hidden in the datasets. Twenty-seven significant lakes and reservoirs located in the Yangtze River Basin were selected to demonstrate the proposed method. The sensitivity and consistency were used to evaluate the accuracy of the proposed method. Results indicate that the proposed method has the capability to effectively assess the eutrophication status of lakes and reservoirs under uncertainty and that it has a better sensitivity since it can identify more than 33-50% trophic levels compared to the traditional methods. Further scenario experiments analysis revealed that the sample information richness, i.e., sample size and the number of trophic levels is of great significance to the accuracy/robustness of the method. Moreover, a sample size of 60 can offer the most favorable balance between accuracy/robustness and the monitoring expenses. These findings are crucial to optimizing the eutrophication assessment.

Construction of a 5-methylcytosine-Related Molecular Signature to Inform the Prognosis and Immunotherapy of Lung Squamous Cell Carcinoma.

BACKGROUND: Methylation of cytosine residues resulting in 5-methylcytosine (5-mC) is an important epigenetic modification associated with tumorigenesis. The present study explored the relationship between methylation, prognosis, and immunotherapy of patients suffering from lung squamous cell carcinoma (LUSC). METHODS: RNA sequencing data and corresponding clinical information were downloaded, and preprocessed, and unsupervised consistent cluster analysis was used to identify 5-mC-related clusters and gene clusters. 5-mC scores were calculated using principal component analysis, and a Boruta algorithm was used to evaluate the relationship between tumor mutation burden (TMB), immune checkpoint inhibitor response, and prognosis of individual LUSC patients. RESULTS: : Two 5-mC clusters and three gene clusters with different prognoses were identified. Patients with higher 5-mC scores showed worse prognoses, which was confirmed in multiple cohorts. Some immune-related biological functions and pathways were enriched in the high-5-mC score subtype. CONCLUSION: The 5-mC score is a potential biomarker independent of TMB, which can be a decisive factor regarding immune treatment responses. Further, patients with low 5-mC scores may respond better to immunotherapy. The 5-mC score can thus be used as a potential biomarker for the prognosis of LUSC patients and their response to immunotherapy.

The valuation of China's environmental degradation from 2004 to 2017.

This paper aims to evaluate the cost of environmental degradation by adopting the conventional environmental economic methodology in China from 2004 to 2017 and summarize the change in both the causes and costs of China's environmental degradation. Results from this study revealed the following: i. The environmental degradation cost in China increased from 511 billion yuan to 1,892 billion yuan from 2004 to 2017, and its share in the GDP decreased from 3.05% to 2.23%; ii. The environmental degradation cost growth rate was lower than the GDP growth rate. The environmental degradation cost growth rate decreased sharply, by dropping from 10% in 2014 to 2% in 2017. The environmental benefits of industrial transformation have emerged; iii. The provinces of Shandong, Hebei, Jiangsu, Henan, and Guangdong had the highest environmental degradation costs. The annual average growth rate of the environmental degradation costs in Jiangsu, Guangdong, and Zhejiang were lower than their growth rate of the GDP respectively; iv. Consideration of environmental degradation cost in decision-making could contribute to the high-quality development of China.

Effect of etoposide-induced alteration of the Mdm2-Rb signaling pathway on cellular senescence in A549 lung adenocarcinoma cells.

The present study aimed to investigate the effect of various concentrations of etoposide (VP-16) on the E3 ubiquitin-protein ligase Mdm2 (Mdm2)-retinoblastoma (Rb) signaling pathway in the cellular senescence of A549 lung adenocarcinoma cells. A549 cells were randomly divided into the following four groups: Control group (no treatment), group 1 (1 µmol/l VP-16), group 2 (5 µmol/l VP-16) and group 3 (25 µmol/l VP-16). Each group was cultured for 48 h after treatment prior to observation of the alterations to cellular morphology. The cell cycle distribution of each group was also detected by flow cytometry. In addition, the activity of cellular senescence-associated ß-galactosidase, and the expression of Mdm2 and phosphorylated (p-) Rb protein, was measured. The percentage of senescent cells was significantly higher following VP-16 treatment compared with the control group. The percentage of G1 phase cells, and p-Rb protein and Mdm2 protein expression were also significantly different following VP-16 treatment compared with the control group. VP-16 increased the activity of ß-galactosidase in the A459 cells. VP-16 also decreased the expression level of Mdm2 and p-Rb protein and inhibited cell cycle progression in G1. These results indicate that VP-16 induces the cellular senescence of A549 cells via the Mdm2-Rb signaling pathway. However, further investigations are required to validate the mechanisms underlying these effects of VP-16.

Change in the Green-Up Dates for Quercus mongolica in Northeast China and Its Climate-Driven Mechanism from 1962 to 2012.

The currently available studies on the green-up date were mainly based on ground observations and/or satellite data, and few model simulations integrated with wide coverage satellite data have been reported at large scale over a long time period (i.e., > 30 years). In this study, we combined phenology mechanism model, long-term climate data and synoptic scale remote sensing data to investigate the change in the green-up dates for Quercus mongolica over 33 weather stations in Northeast China and its climate-driven mechanism during 1962-2012. The results indicated that the unified phenology model can be well parameterized with the satellite derived green-up dates. The optimal daily mean temperature for chilling effect was between -27°C and 1°C for Q. mongolica in Northeast China, while the optimal daily mean temperature for forcing effect was above -3°C. The green-up dates for Q. mongolica across Northeast China showed a delayed latitudinal gradient of 2.699 days degree-1, with the earliest date on the Julian day 93 (i.e., 3th April) in the south and the latest date on the Julian day 129 (i.e., 9th May) in the north. The green-up date for Q. mongolica in Northeast China has advanced 6.6 days (1.3 days decade-1) from 1962 to 2012. With the prevailing warming in autumn, winter and spring in Northeast China during the past 51 years, the chilling effect for Q. mongolica has been weakened, while the forcing effect has been enhanced. The advancing trend in the green-up dates for Q. mongolica implied that the enhanced forcing effect to accelerate green-up was stronger than the weakened chilling effect to hold back green-up while the changes of both effects were caused by the warming climate.