MNCLCDA: predicting circRNA-drug sensitivity associations by using mixed neighbourhood information and contrastive learning.

BACKGROUND: circRNAs play an important role in drug resistance and cancer development. Recently, many studies have shown that the expressions of circRNAs in human cells can affect the sensitivity of cells to therapeutic drugs, thus significantly influencing the therapeutic effects of these drugs. Traditional biomedical experiments required to verify this sensitivity relationship are not only time-consuming but also expensive. Hence, the development of an efficient computational approach that can accurately predict the novel associations between drug sensitivities and circRNAs is a crucial and pressing need. METHODS: In this research, we present a novel computational framework called MNCLCDA, which aims to predict the potential associations between drug sensitivities and circRNAs to assist with medical research. First, MNCLCDA quantifies the similarity between the given drug and circRNA using drug structure information, circRNA gene sequence information, and GIP kernel information. Due to the existence of noise in similarity information, we employ a preprocessing approach based on random walk with restart for similarity networks to efficiently capture the useful features of circRNAs and drugs. Second, we use a mixed neighbourhood graph convolutional network to obtain the neighbourhood information of nodes. Then, a graph-based contrastive learning method is used to enhance the robustness of the model, and finally, a double Laplace-regularized least-squares method is used to predict potential circRNA-drug associations through the kernel matrices in the circRNA and drug spaces. RESULTS: Numerous experimental results show that MNCLCDA outperforms six other advanced methods. In addition, the excellent performance of our proposed model in case studies illustrates that MNCLCDA also has the ability to predict the associations between drug sensitivity and circRNA in practical situations. CONCLUSIONS: After a large number of experiments, it is illustrated that MNCLCDA is an efficient tool for predicting the potential associations between drug sensitivities and circRNAs, thereby can provide some guidance for clinical trials.

Runoff Losses in Nitrogen and Phosphorus From Paddy and Maize Cropping Systems: A Field Study in Dongjiang Basin, South China.

Surface runoff is one of the predominant routes for agricultural nitrogen (N) and phosphorus (P) losses, yet their characteristics and corresponding control measures are not fully understood. In 2019 and 2020, field-scale plot experiments were performed at Dongjiang Basin in South China to investigate the characteristics of N and P runoff losses from paddy and maize cropping systems. The results showed that N and P losses from maize fields via surface runoff (27.85 and 1.24 kg ha-1 year-1) were significantly higher than those from paddy fields (15.37 and 0.8 kg ha-1 year-1). The main forms of N losses were nitrate ( NO 3 - -N) and ammonium ( NH 4 + -N) in paddy and maize fields, respectively, whereas particulate P form predominated in surface runoff losses from both the paddy and maize fields. Considerable proportions of agricultural N and P (71-83% of the total runoff loss) were lost during basal fertilization and first topdressing application. Moreover, frequent rainfall events following fertilizer application triggered N and P losses from the monitored fields. About 26.22 and 37.48% of N fertilizer was recovered from grains and straw of paddy and maize, respectively, whereas only 12.35 and 19.51% of P fertilizer were recovered during the crop harvesting stage. Surface runoff was one of the dominant liquid pathways in N loss, whereas most of P loss (introduced from fertilizers without crops utilization) was fixed in the soil. Principal component analysis (PCA) proved that the primary sources of N and P losses were fertilizers rather than N and P in the soil. The current results suggest controlled management relating to fertilization, irrigation, and tillage strategies are effective measures for reducing N and P losses, thereby controlling agricultural non-point source pollution. It is hoped that this study will provide comprehensive field-based inputs on characteristics of N and P runoff losses and formulate appropriate control strategies to protect aquatic environments from eutrophication.

Bacterial community composition and function succession under aerobic and anaerobic conditions impacts the biodegradation of 17ß-estradiol and its environmental risk.

The widespread detection of 17ß-estradiol (E2) in the environment has become an emerging concern worldwide due to its endocrine disrupting effects. This work focuses on the aerobic and anaerobic biodegradations of E2 in various sedimentary environments with different availabilities of electron acceptors, including O2, NO3-, Fe3+, SO42-, or HCO3-. The highest removal efficiency (98.9%) and shortest degradation half-life of E2 (t1/2 = 5.0 d) were achieved under aerobic condition, followed by nitrate-reducing, ferric-reducing, sulfate-reducing and methanogenic conditions. We propose four different degradation pathways of E2 based on the metabolites identified under various redox conditions. Although most of E2 was effectively removed under aerobic condition, the potential environmental risk still needs to be considered due to the residual estrogenic activity induced by estrone (E1) formation. The endocrine-disrupting activities, as indicated by estradiol equivalent (EEQ) values, were related to E2 degradation rate and metabolite formation. We further analyzed the succession of bacterial community compositions and functions using Illumina HiSeq sequencing and Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt). The findings herein evidenced that bacterial community compositions and metabolic functions associated with different redox conditions impact the biodegradation of E2 and its endocrine-disrupting activity. This knowledge will be useful in predicting the environmental fates of estrogenic hormones in various sedimentary environments and aid in establishing appropriate strategies for eliminating potential environmental risks.

Biodegradation of petroleum hydrocarbons and changes in microbial community structure in sediment under nitrate-, ferric-, sulfate-reducing and methanogenic conditions.

In the present study, the biodegradation behaviors of petroleum hydrocarbons under various reducing conditions were investigated. n-Alkanes and polycyclic aromatic hydrocarbons (PAHs) were degraded with NO3-, Fe3+, SO42-, or HCO3- as terminal electron acceptors (TEAs), which link to four typical reducing conditions (i.e., nitrate-reducing, ferric-reducing, sulfate-reducing and methanogenic conditions, respectively) in sediment. The fastest degradation rates were achieved under sulfate-reducing conditions with half-lives of 49.51 days for n-alkanes and 58.74 days for PAHs. For short-chain n-alkanes and low-molecular weight (LMW) PAHs, relatively higher removal efficiencies were achieved under nitrate- and ferric-reducing conditions. The degradation of long-chain n-alkanes and high-molecular weight (HMW) PAHs coupled to methanogenesis was the most favored as compared with other reducing conditions. Carboxylation was found to be the principle mechanism for regulating n-alkane degradation coupled to denitrification, while the activation of n-alkanes by the addition of fumarate was the principle mechanism for the n-alkane degradation under sulfate-reducing conditions. The anaerobic metabolism of n-alkanes may not proceed via fumarate addition or carboxylation under ferric-reducing and methanogenic conditions. Illumina HiSeq sequencing revealed dissimilar structures of the microbial communities under various reducing conditions. It is hypothesized that the utilization of different TEAs for n-alkane and PAH degradation resulted in distinct microbial community structures, which were highly correlated with the varied degradation behaviors of petroleum hydrocarbons in sediment. The current results may provide reference value on better understanding the biodegradation behaviors of n-alkanes and PAHs in association with the induced microbial communities in sedimentary environments under the four typical reducing conditions.