Stability of Uncertain Impulsive Stochastic Genetic Regulatory Networks with Time-Varying Delay in the Leakage Term

This paper is concerned with the stability problem for a class of uncertain impulsive stochastic genetic regulatory networks (UISGRNs) with time-varying delays both in the leakage term and in the regulator function. By constructing a suitable Lyapunov-Krasovskii functional which uses the information on the lower bound of the delay sufficiently, a delay-dependent stability criterion is derived for the proposed UISGRNs model by using the free-weighting matrices method and convex combination technique. The conditions obtained here are expressed in terms of LMIs whose feasibility can be checked easily by MATLAB LMI control toolbox. In addition, three numerical examples are given to justify the obtained stability results

The relationships between vertical variations of shallow gas and pore water geochemical characteristics in boreholes from the inner shelf of the East China Sea

Shallow gas was widely recognized in the coastal region, especially in the estuarine delta areas with high organic matter (OM) burial flux. In this study, the vertical variations of shallow gas and the related geochemical indicators from two boreholes in the coastal region of the East China Sea (ECS) were investigated. Two gas-bearing layers were identified in the sediments from the Holocene and late Pleistocene series. Both boreholes exhibit a “typical” and an “inverse” Sulfate Methane Transition Zone (SMTZ). The “typical” SMTZs (SMTZ1 and SMTZ3) were in the upper part of the gas-bearing layers, where sulfate levels decrease and methane levels increase with depth. Conversely, the “inverse” SMTZs (SMTZ2 and SMTZ4) were in the lower part of the gas-bearing layers, exhibiting an increase in sulfate levels and a decrease in methane levels with depth, a phenomenon rarely documented in previous research. The downward variations of pore water geochemical characteristics indicates that these ions were related to Anaerobic Oxidation of Methane (AOM) processes. The increase in Ca2+ and Ba2+ concentrations and the gradual decrease in sulfate at the SMTZ reflect a series of biogeochemical processes resulting from the dissolution of carbonate and other minerals by AOM. The research indicates that sulfate in AOM may originate from multiple sources. Through analyzing the vertical distribution of shallow gas and the geochemical properties of pore water, this study elucidates the shallow gas formation mechanism and the features of the SMTZ, laying the groundwork for further investigations

Enhancing student learning and engagement with object-oriented block-based programming tool

Technologies have been adopted and integrated into various aspects of life, including education and learning. Gamified learning is effective to promote student learning and motivations. Object-Oriented Programming (OOP) is a fundamental topic taught to university students, and in certain countries, it is introduced as an enrichment course for younger students. It is beneficial to develop young students on the interests in software programming. Equipping younger students with essential programming skills will be helpful and better prepare them to excel in the digital age in the future. This research leverages the benefits of gamification to enhance student engagement by developing an educational game for teaching OOP. The developed educational visual programming tool simplifies complex OOP concepts and engagingly presents them through the medium of a game. It provides an alternative learning approach to visualizing and understanding OOP. The study yielded positive results, with improved test scores and a more consistent performance. It highlights the effectiveness of this approach in teaching OOP. The positive feedback from students regarding their enjoyment of gameplay also shows the potential of gamified learning in enhancing engagement

Diurnal RNAPII-tethered chromatin interactions are associated with rhythmic gene expression in rice

Background: The daily cycling of plant physiological processes is speculated to arise from the coordinated rhythms of gene expression. However, the dynamics of diurnal 3D genome architecture and their potential functions underlying the rhythmic gene expression remain unclear. Results: Here, we reveal the genome-wide rhythmic occupancy of RNA polymerase II (RNAPII), which precedes mRNA accumulation by approximately 2 h. Rhythmic RNAPII binding dynamically correlates with RNAPII-mediated chromatin architecture remodeling at the genomic level of chromatin interactions, spatial clusters, and chromatin connectivity maps, which are associated with the circadian rhythm of gene expression. Rhythmically expressed genes within the same peak phases of expression are preferentially tethered by RNAPII for coordinated transcription. RNAPII-associated chromatin spatial clusters (CSCs) show high plasticity during the circadian cycle, and rhythmically expressed genes in the morning phase and non-rhythmically expressed genes in the evening phase tend to be enriched in RNAPII-associated CSCs to orchestrate expression. Core circadian clock genes are associated with RNAPII-mediated highly connected chromatin connectivity networks in the morning in contrast to the scattered, sporadic spatial chromatin connectivity in the evening; this indicates that they are transcribed within physical proximity to each other during the AM circadian window and are located in discrete “transcriptional factory” foci in the evening, linking chromatin architecture to coordinated transcription outputs. Conclusion: Our findings uncover fundamental diurnal genome folding principles in plants and reveal a distinct higher-order chromosome organization that is crucial for coordinating diurnal dynamics of transcriptional regulation

Comparative analysis of liver transcriptome reveals adaptive responses to hypoxia environmental condition in Tibetan chicken

Objective Tibetan chickens, which have unique adaptations to extreme high-altitude environments, exhibit phenotypic and physiological characteristics that are distinct from those of lowland chickens. However, the mechanisms underlying hypoxic adaptation in the liver of chickens remain unknown. Methods RNA-sequencing (RNA-Seq) technology was used to assess the differentially expressed genes (DEGs) involved in hypoxia adaptation in highland chickens (native Tibetan chicken [HT]) and lowland chickens (Langshan chicken [LS], Beijing You chicken [BJ], Qingyuan Partridge chicken [QY], and Chahua chicken [CH]). Results A total of 352 co-DEGs were specifically screened between HT and four native lowland chicken breeds. Gene ontology and Kyoto encyclopedia of genes and genomes enrichment analyses indicated that these co-DEGs were widely involved in lipid metabolism processes, such as the peroxisome proliferator-activated receptors (PPAR) signaling pathway, fatty acid degradation, fatty acid metabolism and fatty acid biosynthesis. To further determine the relationship from the 352 co-DEGs, protein-protein interaction network was carried out and identified eight genes (ACSL1, CPT1A, ACOX1, PPARC1A, SCD, ACSBG2, ACACA, and FASN) as the potential regulating genes that are responsible for the altitude difference between the HT and other four lowland chicken breeds. Conclusion This study provides novel insights into the molecular mechanisms regulating hypoxia adaptation via lipid metabolism in Tibetan chickens and other highland animals

Fusarium head blight monitoring in wheat ears using machine learning and multimodal data from asymptomatic to symptomatic periods

The growth of the fusarium head blight (FHB) pathogen at the grain formation stage is a deadly threat to wheat production through disruption of the photosynthetic processes of wheat spikes. Real-time nondestructive and frequent proxy detection approaches are necessary to control pathogen propagation and targeted fungicide application. Therefore, this study examined the ch\lorophyll-related phenotypes or features from spectral and chlorophyll fluorescence for FHB monitoring. A methodology is developed using features extracted from hyperspectral reflectance (HR), chlorophyll fluorescence imaging (CFI), and high-throughput phenotyping (HTP) for asymptomatic to symptomatic disease detection from two consecutive years of experiments. The disease-sensitive features were selected using the Boruta feature-selection algorithm, and subjected to machine learning-sequential floating forward selection (ML-SFFS) for optimum feature combination. The results demonstrated that the biochemical parameters, HR, CFI, and HTP showed consistent alterations during the spike–pathogen interaction. Among the selected disease sensitive features, reciprocal reflectance (RR=1/700) demonstrated the highest coefficient of determination (R2) of 0.81, with root mean square error (RMSE) of 11.1. The multivariate k-nearest neighbor model outperformed the competing multivariate and univariate models with an overall accuracy of R2 = 0.92 and RMSE = 10.21. A combination of two to three kinds of features was found optimum for asymptomatic disease detection using ML-SFFS with an average classification accuracy of 87.04% that gradually improved to 95% for a disease severity level of 20%. The study demonstrated the fusion of chlorophyll-related phenotypes with the ML-SFFS might be a good choice for crop disease detection

Survival effect of PDGF-CC rescues neurons from apoptosis in both brain and retina by regulating GSK3β phosphorylation

Platelet-derived growth factor CC (PDGF-CC) is the third member of the PDGF family discovered after more than two decades of studies on the original members of the family, PDGF-AA and PDGF-BB. The biological function of PDGF-CC remains largely to be explored. We report a novel finding that PDGF-CC is a potent neuroprotective factor that acts by modulating glycogen synthase kinase 3β (GSK3β) activity. In several different animal models of neuronal injury, such as axotomy-induced neuronal death, neurotoxin-induced neuronal injury, 6-hydroxydopamine–induced Parkinson’s dopaminergic neuronal death, and ischemia-induced stroke, PDGF-CC protein or gene delivery protected different types of neurons from apoptosis in both the retina and brain. On the other hand, loss-of-function assays using PDGF-C null mice, neutralizing antibody, or short hairpin RNA showed that PDGF-CC deficiency/inhibition exacerbated neuronal death in different neuronal tissues in vivo. Mechanistically, we revealed that the neuroprotective effect of PDGF-CC was achieved by regulating GSK3β phosphorylation and expression. Our data demonstrate that PDGF-CC is critically required for neuronal survival and may potentially be used to treat neurodegenerative diseases. Inhibition of the PDGF-CC–PDGF receptor pathway for different clinical purposes should be conducted with caution to preserve normal neuronal functions