Simulating protein evolution via thermodynamic models

Natural proteins are results of evolution and they need to maintain certain thermodynamic stabilities in order to carry out their biological functions. By simulating protein evolution based on thermodynamic rules, we could reconstruct the evolution trajectory and analyze the evolutionary dynamics of a protein population, and further understand the protein sequence-structure-function relationship. In this study, we have used both a simplified lattice model and a high-resolution atomic model to simulate protein evolution processes. With the lattice model, we have investigated general theoretical questions about how protein structural designability would affect protein evolution, particularly how it would affect protein recombination and protein-ligand interactions in the evolution process. With the atomic model, we could simulate evolution processes for particular protein with different selection pressure. First, we simulated directed evolution processes and utilized such model to investigate the thermostabilization of T4 lysozyme. Second, we simulated neutral evolution processes for HIV protease, investigated its evolutionary dynamics and the possible drug-resistance mechanism in such neutral evolution. Overall, thermodynamic models can help us understand either general protein evolution dynamics or specific protein sequence-structure-function relationship in evolution

A simulation-based method to determine the coefficient of hyperbolic decline curve for tight oil production

 Tight oil reservoirs are characterized by the ultra low porosity and permeability, making it a great challenge to enhance oil production. Owing to the fast development in hydraulic fracturing technology of horizontal wells, tight oil has been widely explored in North America. Individual wells have a long term of low production after a rapid production decline. This causes low cumulative production in tight oil reservoirs. A rate decline curve is the most common method to forecast their production rates. The forecast can provide useful information during decision making on future development of production wells. In this paper, a relationship is developed between the parameters of a hyperbolic decline curve and the reservoir/fracture properties when a reservoir simulation model is used based on the data from a real field. Understanding of this relationship improves the application of the hyperbolic decline curve and provides a useful reference to forecast production performance in a more convenient and efficient way.Cited as: Yu, Y., Chen, Z., Xu, J. A simulation-based method to determine the coefficient of hyperbolic decline curve for tight oil production. Advances in Geo-Energy Research, 2019, 3(4): 375-380, doi: 10.26804/ager.2019.04.0

Bis{μ3-cis-N-(2-carboxyl­ato-5-chloro­phen­yl)-N′-[3-(dimethyl­amino)­prop­yl]oxamidato(3−)}bis­(perchlorato-κO)bis­(N,N,N′,N′-tetra­methyl­ethylene­diamine)­tetra­copper(II)

The title complex, [Cu4(C14H15ClN3O4)2(ClO4)2(C6H16N2)2], is a tetra­nuclear copper(II) complex lying about an inversion center wherein a cis-oxamide group is coordinated to both Cu atoms with bite angles of 84.45 (6) and 84.08 (10)°. Both Cu atoms adopt distorted square-pyramidal coordination geometries. The apical position of one Cu atom is occupied by an O atom from a perchlorate group, with a Cu—O bond length of 2.519 (7) Å, while the apical site of the other Cu atom is occupied by a carboxyl­ate O atom with a Cu—O distance of 2.281 (3) Å. The Cu atoms bridged by oxamide and carboxyl­ate-group bridges are separated by 5.204 (6) and 5.603 (2) Å, respectively. The crystal structure is consolidated by weak inter­molecular C—H⋯O inter­actions. Two perchlorate O atoms are disordered with unequal site-occupancy factors

Design Optimization of a Concrete Face Rock-Fill Dam by Using Genetic Algorithm

This paper combined with the adaptive principle to improve the genetic algorithms (GA) and applied it to optimal design of the shape of the concrete face rock-fill dam (CFRD). Based on the improved GA, a mathematical model was established for the design optimization of CFRD. CFRD utilizes dam cost as objective function and dam slope and geometries of the dam material partition as design variables. Dam stability, stress, displacement, and stress level are used as the main condition constraints. The calculation procedures were prepared, and the GA was used to optimize the design of Jishixia CFRD. Results show that the GA could solve the global optimal solution problem of complex optimization design, such as the high degree of nonlinearity and the recessiveness of constraint conditions, and using the GA to optimize the CFRD design can reduce the quantities of projects and engineering safety costs

The Short Text Matching Model Enhanced with Knowledge via Contrastive Learning

In recent years, short Text Matching tasks have been widely applied in the fields ofadvertising search and recommendation. The difficulty lies in the lack of semantic information and word ambiguity caused by the short length of the text. Previous works have introduced complement sentences or knowledge bases to provide additional feature information. However, these methods have not fully interacted between the original sentence and the complement sentence, and have not considered the noise issue that may arise from the introduction of external knowledge bases. Therefore, this paper proposes a short Text Matching model that combines contrastive learning and external knowledge. The model uses a generative model to generate corresponding complement sentences and uses the contrastive learning method to guide the model to obtain more semantically meaningful encoding of the original sentence. In addition, to avoid noise, we use keywords as the main semantics of the original sentence to retrieve corresponding knowledge words in the knowledge base, and construct a knowledge graph. The graph encoding model is used to integrate the knowledge base information into the model. Our designed model achieves state-of-the-art performance on two publicly available Chinese Text Matching datasets, demonstrating the effectiveness of our model.Comment: 11 pages,2 figure

Systemic-Lupus-Erythematosus-Related Acute Pancreatitis: A Cohort from South China

Acute pancreatitis (AP) is a rare but life-threatening complication of SLE. The current study evaluated the clinical characteristics and risk factors for the mortality of patients with SLE-related AP in a cohort of South China. Methods. Inpatient medical records of SLE-related AP were retrospectively reviewed. Results. 27 out of 4053 SLE patients were diagnosed as SLE-related AP, with an overall prevalence of 0.67%, annual incidence of 0.56‰ and mortality of 37.04%. SLE patients with AP presented with higher SLEDAI score (21.70 ± 10.32 versus 16.17 ± 7.51, P = 0.03), more organ systems involvement (5.70 ± 1.56 versus 3.96 ± 1.15, P = 0.001), and higher mortality (37.04% versus 0, P = 0.001), compared to patients without AP. Severe AP (SAP) patients had a significant higher mortality rate compared to mild AP (MAP) (75% versus 21.05%, P = 0.014). 16 SLE-related AP patients received intensive GC treatment, 75% of them exhibited favorable prognosis. Conclusion. SLE-related AP is rare but concomitant with high mortality in South Chinese people, especially in those SAP patients. Activity of SLE, multiple-organ systems involvement may attribute to the severity and mortality of AP. Appropriate glucocorticosteroid (GC) treatment leads to better prognosis in majority of SLE patients with AP