Exploring potential circRNA biomarkers for cancers based on double-line heterogeneous graph representation learning.

BACKGROUND: Compared with the time-consuming and labor-intensive for biological validation in vitro or in vivo, the computational models can provide high-quality and purposeful candidates in an instant. Existing computational models face limitations in effectively utilizing sparse local structural information for accurate predictions in circRNA-disease associations. This study addresses this challenge with a proposed method, CDA-DGRL (Prediction of CircRNA-Disease Association based on Double-line Graph Representation Learning), which employs a deep learning framework leveraging graph networks and a dual-line representation model integrating graph node features. METHOD: CDA-DGRL comprises several key steps: initially, the integration of diverse biological information to compute integrated similarities among circRNAs and diseases, leading to the construction of a heterogeneous network specific to circRNA-disease associations. Subsequently, circRNA and disease node features are derived using sparse autoencoders. Thirdly, a graph convolutional neural network is employed to capture the local graph network structure by inputting the circRNA-disease heterogeneous network alongside node features. Fourthly, the utilization of node2vec facilitates depth-first sampling of the circRNA-disease heterogeneous network to grasp the global graph network structure, addressing issues associated with sparse raw data. Finally, the fusion of local and global graph network structures is inputted into an extra trees classifier to identify potential circRNA-disease associations. RESULTS: The results, obtained through a rigorous five-fold cross-validation on the circR2Disease dataset, demonstrate the superiority of CDA-DGRL with an AUC value of 0.9866 and an AUPR value of 0.9897 compared to existing state-of-the-art models. Notably, the hyper-random tree classifier employed in this model outperforms other machine learning classifiers. CONCLUSION: Thus, CDA-DGRL stands as a promising methodology for reliably identifying circRNA-disease associations, offering potential avenues to alleviate the necessity for extensive traditional biological experiments. The source code and data for this study are available at https://github.com/zywait/CDA-DGRL .

Introduction of multilayered quantum dot nanobeads into competitive lateral flow assays for ultrasensitive and quantitative monitoring of pesticides in complex samples.

A competitive fluorescent lateral flow assay (CFLFA) is proposed for direct, ultrasensitive, quantitative detection of common pesticides imidacloprid (IMI) and carbendazim (CBZ) in complex food samples by using silica-core multilayered quantum dot nanobeads (SiO2-MQB) as liquid fluorescent tags. The SiO2-MQB nanostructure comprises a 200-nm SiO2 core and a shell of hundreds of carboxylated QDs (excitation/emission maxima ~365/631 nm), and can generate better stability, superior dispersibility, and higher luminescence than traditional fluorescent beads, greatly improving the sensitivity of current LFA methods for pesticides. Moreover, using liquid SiO2-MQB directly instead of via the conjugate pad both simplifies the structure of LFA system and improves the efficiency of immunobinding reactions between nanotags and the targets. Applying these methods, the established CFLFA realized the stable and accurate detection of IMI and CBZ in 12 min, with detection limits down to 1.94 and 14.79 pg/mL, respectively. The SiO2-MQB-CFLFA is practicable for application to real food samples (corn, apple, cucumber, and cabbage), and undoubtedly a promising and low-cost tool for on-site monitoring of trace pesticide residues.

Integrated analysis of transcriptomic and proteomic analyses reveals different metabolic patterns in the livers of Tibetan and Yorkshire pigs.

OBJECTIVE: Tibetan pigs, predominantly originating from the Tibetan Plateau, have been subjected to long-term natural selection in an extreme environment. To characterize the metabolic adaptations to hypoxic conditions, transcriptomic and proteomic expression patterns in the livers of Tibetan and Yorkshire pigs were compared. METHODS: RNA and protein were extracted from liver tissue of Tibetan and Yorkshire pigs (n = 3, each). Differentially expressed genes and proteins were subjected to gene ontology and Kyoto encyclopedia of genes and genomes functional enrichment analyses. RESULTS: In the RNA-Seq and isobaric tags for relative and absolute quantitation analyses, a total of 18,791 genes and 3,390 proteins were detected and compared. Of these, 273 and 257 differentially expressed genes and proteins were identified. Evidence from functional enrichment analysis showed that many genes were involved in metabolic processes. The combined transcriptomic and proteomic analyses revealed that small molecular biosynthesis, metabolic processes, and organic hydroxyl compound metabolic processes were the major processes operating differently in the two breeds. The important genes include retinol dehydrogenase 16, adenine phosphoribosyltransferase, prenylcysteine oxidase 1, sorbin and SH3 domain containing 2, ENSSSCG00000036224, perilipin 2, ladinin 1, kynurenine aminotransferase 1, and dimethylarginine dimethylaminohydrolase 1. CONCLUSION: The findings of this study provide novel insight into the high-altitude metabolic adaptation of Tibetan pigs.

Reduction of pyruvate orthophosphate dikinase activity is associated with high temperature-induced chalkiness in rice grains.

Global warming affects both rice (Oryza sativa) yields and grain quality. Rice chalkiness due to high temperature during grain filling would lower the grain quality. The biochemical and molecular mechanisms responsible for the increased occurrence of chalkiness under high temperature are not fully understood. Previous research suggested that cytosolic pyruvate orthophosphate dikinase (cyPPDK, EC 2.7.9.1) in rice modulates carbon metabolism. The objective of this study was to determine the relationship between cyPPDK and high temperature-induced chalkiness. High temperature treatments were applied during the grain filling of two rice cultivars (9311 and TXZ-25) which had different sensitivity of chalkiness to high temperature. Chalkiness was increased significantly under high temperature treatment, especially for TXZ-25. A shortened grain filling duration and a decreased grain weight in both cultivars were caused by high temperature treatment. A reduction in PPDK activities due to high temperature was observed during the middle and late grain filling periods, accompanied by down regulated cyPPDK mRNA and protein levels. The temperature effects on the developmental regulation of PPDK activity were confirmed at transcription, translation and post-translational levels. PPDK activities were insensitive to variation in PPDK levels, suggesting the rapid phosphorylation mechanism of this protein. The two varieties showed similar responses to the high temperature treatment in both PPDK activities and chalkiness. We concluded that high temperature-induced chalkiness was associated with the reduction of PPDK activity.

Different effects of night versus day high temperature on rice quality and accumulation profiling of rice grain proteins during grain filling.

High temperature has adverse effects on rice yield and quality. The different influences of night high temperature (NHT) and day high temperature (DHT) on rice quality and seed protein accumulation profiles during grain filling in indica rice '9311' were studied in this research. The treatment temperatures of the control, NHT, and DHT were 28°C/20°C, 27°C/35°C, and 35°C/27°C, respectively, and all the treatments were maintained for 20 days. The result of rice quality analysis indicated that compared with DHT, NHT exerted less effect on head rice rate and chalkiness, whereas greater effect on grain weight. Moreover, the dynamic accumulation change profiles of 61 protein spots, differentially accumulated and successfully identified under NHT and DHT conditions, were performed by proteomic approach. The results also showed that the different suppressed extent of accumulation amount of cyPPDKB might result in different grain chalkiness between NHT and DHT. Most identified isoforms of proteins, such as PPDK and pullulanase, displayed different accumulation change patterns between NHT and DHT. In addition, compared with DHT, NHT resulted in the unique accumulation patterns of stress and defense proteins. Taken together, the mechanisms of seed protein accumulation profiles induced by NHT and DHT during grain filling should be different in rice, and the potential molecular basis is discussed in this study.