Search to Fine-tune Pre-trained Graph Neural Networks for Graph-level Tasks

Recently, graph neural networks (GNNs) have shown its unprecedented success in many graph-related tasks. However, GNNs face the label scarcity issue as other neural networks do. Thus, recent efforts try to pre-train GNNs on a large-scale unlabeled graph and adapt the knowledge from the unlabeled graph to the target downstream task. The adaptation is generally achieved by fine-tuning the pre-trained GNNs with a limited number of labeled data. Despite the importance of fine-tuning, current GNNs pre-training works often ignore designing a good fine-tuning strategy to better leverage transferred knowledge and improve the performance on downstream tasks. Only few works start to investigate a better fine-tuning strategy for pre-trained GNNs. But their designs either have strong assumptions or overlook the data-aware issue for various downstream datasets. Therefore, we aim to design a better fine-tuning strategy for pre-trained GNNs to improve the model performance in this paper. Given a pre-trained GNN, we propose to search to fine-tune pre-trained graph neural networks for graph-level tasks (S2PGNN), which adaptively design a suitable fine-tuning framework for the given labeled data on the downstream task. To ensure the improvement brought by searching fine-tuning strategy, we carefully summarize a proper search space of fine-tuning framework that is suitable for GNNs. The empirical studies show that S2PGNN can be implemented on the top of 10 famous pre-trained GNNs and consistently improve their performance. Besides, S2PGNN achieves better performance than existing fine-tuning strategies within and outside the GNN area. Our code is publicly available at \url{https://anonymous.4open.science/r/code_icde2024-A9CB/}

Numerical simulation and thermo-hydro-mechanical coupling model of in situ mining of low-mature organic-rich shale by convection heating

The in situ efficient exploitation of low-mature organic-rich shale resources is critical for alleviating the current oil shortage. Convection heating is the most critical and feasible method for in situ retortion of shale. In this study, a thermo-hydro-mechanical coupling mathematical model for in situ exploitation of shale by convection heating is developed. The dynamic distribution of the temperature, seepage, and stress fields during the in situ heat injection of shale and the coupling effect between multiple physical fields are studied. When the operation time increases from 1 to 2.5 years, the temperature of most shale formations between heat injection and production wells increases significantly (from less than 400 to 500 °C), which is a period of significant production of shale oil and pyrolysis gas. The fluid pore pressure gradually decreases from the peak point of the heat injection well to the surrounding. Compared with shale formation, bedrock permeability is poor, pore pressure increases slowly, and a lag phenomenon exists. The pore pressure difference between bedrock and shale is minimal by 1 year. When the heat injection time is 2.5 years, the permeability coefficient of shale formation in the area from the heat injection well to the production wells increases nearly 100 times the initial permeability coefficient. With increasing formation temperature, the vertical stress gradually evolves from compressive stress to tensile stress. Meanwhile, the action area of tensile stress expands outward with time with the heat injection well as the center. In general, increasing tensile stress enlarges the pore volume. It extends the fracture width, creating favorable conditions for the injection of high-temperature fluids and the production of oil and gas.Cited as: Zhao, J., Wang, L., Liu, S., Kang, Z., Yang, D., Zhao, Y. Numerical simulation and thermo-hydro-mechanical coupling model of in situ mining of low-mature organic-rich shale by convection heating. Advances in Geo-Energy Research, 2022, 6(6): 502-514. https://doi.org/10.46690/ager.2022.06.0

Diet-induced bacterial immunogens in the gastrointestinal tract of dairy cows: Impacts on immunity and metabolism

Dairy cows are often fed high grain diets to meet the energy demand for high milk production or simply due to a lack of forages at times. As a result, ruminal acidosis, especially subacute ruminal acidosis (SARA), occurs frequently in practical dairy production. When SARA occurs, bacterial endotoxin (or lipopolysaccharide, LPS) is released in the rumen and the large intestine in a large amount. Many other bacterial immunogens may also be released in the digestive tract following feeding dairy cows diets containing high proportions of grain. LPS can be translocated into the bloodstream across the epithelium of the digestive tract, especially the lower tract, due to possible alterations of permeability and injuries of the epithelial tissue. As a result, the concentration of blood LPS increases. Immune responses are subsequently caused by circulating LPS, and the systemic effects include increases in concentrations of neutrophils and the acute phase proteins such as serum amyloid-A (SAA), haptoglobin (Hp), LPS binding protein (LBP), and C-reactive protein (CRP) in blood. Entry of LPS into blood can also result in metabolic alterations. Blood glucose and nonesterified fatty acid concentrations are enhanced accompanying an increase of blood LPS after increasing the amount of grain in the diet, which adversely affects feed intake of dairy cows. As the proportions of grain in the diet increase, patterns of plasma β-hydoxybutyric acid, cholesterol, and minerals (Ca, Fe, and Zn) are also perturbed. The bacterial immunogens can also lead to reduced supply of nutrients for synthesis of milk components and depressed functions of the epithelial cells in the mammary gland. The immune responses and metabolic alterations caused by circulating bacterial immunogens will exert an effect on milk production. It has been demonstrated that increases in concentrations of ruminal LPS and plasma acute phase proteins (CRP, SAA, and LBP) are associated with declines in milk fat content, milk fat yield, 3.5% fat-corrected milk yield, as well as milk energy efficiency

Tumour suppressor SIRT3 deacetylates and activates manganese superoxide dismutase to scavenge ROS

Tumour suppressor SIRT3 deacetylates and activates manganese superoxide dismutase to scavenge ROSMitochondria manganese superoxide dismutase (SOD2) is a major antioxidant enzyme associated with several diseases. This study shows that SOD2 is inhibited by acetylation and activated by SIRT3-mediated deacetylation in response to reactive oxygen species (ROS).Mitochondria manganese superoxide dismutase (SOD2) is an important antioxidant enzyme, deficiency of which is associated with various human diseases. The known primary regulation of SOD2 is through transcriptional activation. Here, we report that SOD2 is acetylated at Lys 68 and that this acetylation decreases SOD2 activity. Mitochondrial deacetylase SIRT3 binds to, deacetylates and activates SOD2. Increase of reactive oxygen species (ROS) levels stimulates SIRT3 transcription, leading to SOD2 deacetylation and activation. SOD2-mediated ROS reduction is synergistically increased by SIRT3 co-expression, but is cancelled by SIRT3 depletion. These results reveal a new post-translational regulation of SOD2 by means of acetylation and SIRT3-dependent deacetylation in response to oxidative stress