Discussion on the Difference Between the Business Model and Profit Model

In recent years, the business model and profit model has attracted wide attentions of the domestic and foreign academic circles and enterprise circles, however, during the studies, most of them confuse the commercial mode and profit mode. It will cover the creation of enterprise value, brings the barrier to true methods of accurately reveal the enterprise profits. This paper introduced the definition of the business model and profit model, and then analyzes the relationship and differences between them. Key words: Business model; Profit model; Definition; Relationship; Difference

Cellular and Molecular Mechanisms of Hepatic Fibrosis

The occurrence of hepatic fibrosis is a multi-factor involved process. The key is the activation of hepatic stellate cells (HSC). Synthesis of extracellular matrix in the liver cells increases while degradation decreases. This paper reviews the tissue factors and the mechanism closely related to the forming of hepatic fibrosis

Death effector domain-containing protein induces vulnerability to cell cycle inhibition in triple-negative breast cancer

Lacking targetable molecular drivers, triple-negative breast cancer (TNBC) is the most clinically challenging subtype of breast cancer. In this study, we reveal that Death Effector Domain-containing DNA-binding protein (DEDD), which is overexpressed in > 60% of TNBCs, drives a mitogen-independent G1/S cell cycle transition through cytoplasm localization. The gain of cytosolic DEDD enhances cyclin D1 expression by interacting with heat shock 71 kDa protein 8 (HSC70). Concurrently, DEDD interacts with Rb family proteins and promotes their proteasome-mediated degradation. DEDD overexpression renders TNBCs vulnerable to cell cycle inhibition. Patients with TNBC have been excluded from CDK 4/6 inhibitor clinical trials due to the perceived high frequency of Rb-loss in TNBCs. Interestingly, our study demonstrated that, irrespective of Rb status, TNBCs with DEDD overexpression exhibit a DEDD-dependent vulnerability to combinatorial treatment with CDK4/6 inhibitor and EGFR inhibitor in vitro and in vivo. Thus, our study provided a rationale for the clinical application of CDK4/6 inhibitor combinatorial regimens for patients with TNBC

Identification and validation of a novel CD8+ T cell-associated prognostic model based on ferroptosis in acute myeloid leukemia

Acute myeloid leukemia (AML) is a highly aggressive cancer with great heterogeneity and variability in prognosis. Though European Leukemia Net (ELN) 2017 risk classification has been widely used, nearly half of patients were stratified to “intermediate” risk and requires more accurate classification via excavating biological features. As new evidence showed that CD8+ T cell can kill cancer cells through ferroptosis pathway. We firstly use CIBERSORT algorithm to divide AMLs into CD8+ high and CD8+ low T cell groups, then 2789 differentially expressed genes (DEGs) between groups were identified, of which 46 ferroptosis-related genes associated with CD8+ T cell were sorted out. GO, KEGG analysis and PPI network were conducted based on these 46 DEGs. By jointly using LASSO algorithm and Cox univariate regression, we generated a 6-gene prognostic signature comprising VEGFA, KLHL24, ATG3, EIF2AK4, IDH1 and HSPB1. Low-risk group shows a longer overall survival. We then validated the prognostic value of this 6-gene signature using two independent external datasets and patient sample collection dataset. We also proved that incorporation of the 6-gene signature obviously enhanced the accuracy of ELN risk classification. Finally, gene mutation analysis, drug sensitive prediction, GSEA and GSVA analysis were conducted between high-risk and low-risk AML patients. Collectively, our findings suggested that the prognostic signature based on CD8+ T cell-related ferroptosis genes can optimize the risk stratification and prognostic prediction of AML patients

The <i>Sinocyclocheilus</i> cavefish genome provides insights into cave adaptation

BACKGROUND: An emerging cavefish model, the cyprinid genus Sinocyclocheilus, is endemic to the massive southwestern karst area adjacent to the Qinghai-Tibetan Plateau of China. In order to understand whether orogeny influenced the evolution of these species, and how genomes change under isolation, especially in subterranean habitats, we performed whole-genome sequencing and comparative analyses of three species in this genus, S. grahami, S. rhinocerous and S. anshuiensis. These species are surface-dwelling, semi-cave-dwelling and cave-restricted, respectively. RESULTS: The assembled genome sizes of S. grahami, S. rhinocerous and S. anshuiensis are 1.75 Gb, 1.73 Gb and 1.68 Gb, respectively. Divergence time and population history analyses of these species reveal that their speciation and population dynamics are correlated with the different stages of uplifting of the Qinghai-Tibetan Plateau. We carried out comparative analyses of these genomes and found that many genetic changes, such as gene loss (e.g. opsin genes), pseudogenes (e.g. crystallin genes), mutations (e.g. melanogenesis-related genes), deletions (e.g. scale-related genes) and down-regulation (e.g. circadian rhythm pathway genes), are possibly associated with the regressive features (such as eye degeneration, albinism, rudimentary scales and lack of circadian rhythms), and that some gene expansion (e.g. taste-related transcription factor gene) may point to the constructive features (such as enhanced taste buds) which evolved in these cave fishes. CONCLUSION: As the first report on cavefish genomes among distinct species in Sinocyclocheilus, our work provides not only insights into genetic mechanisms of cave adaptation, but also represents a fundamental resource for a better understanding of cavefish biology. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12915-015-0223-4) contains supplementary material, which is available to authorized users

Fourier series-based learning control of nonlinear systems with backlash

System with Backlash is a kind of nonlinear system, which is studied widely. In the field of industrial manufacture and robotics, those backlashes occur in the motion transmission, which really spoils the performance. The backlash makes the system unconnected at some time when the system is running. In the unconnected period, the control commands can not be transformed to the part separated by backlash. This leads a time delay problem. In this thesis, the dynamic performance of backlash is studied by establishing a model. The impact phenomenon during the dynamic process of backlash is concerned. In the study of model, the velocity of motion is analyzed and shows that it varies fast and greatly in some period. The conventional method, digital differential, introduces great noises in the measurement which makes the control performance poor. A motion measurement system, including an FPGA PC card, is established according to the requirement of measurement. The accuracy analysis of the method is studied, which gives a direction to the design of FPGA program. Also, the sources of noises are studied and methods on eliminating those noises are given. A learning controller based on Fourier analysis is developed and utilized on a backlash system. The learning controller is performed in the frequency domain which can compensate the time delay from backlash, which is a big flow for those systems. The convergence of the controller is also proved. Experiments are operated and the results illustrate the effectiveness of the controller and the improved motion measurement system. Thus, it can be widely used in motion control systems

Influence of Artificial intelligent in Industrial Economic sustainability development problems and Countermeasures

Economic Sustainability Development (ESD) helps improve the sustainable values needed to conserve resources via optimum use, recovery, and recycling. There should be a direct relationship between countermeasures and the cause of economic losses due to improper design of ESD. Therefore, combining big data and cutting-edge technology may facilitate real-time monitoring, encourage consumers to engage in more sustainable practices and foster the development of industry sustainability. However, countermeasures have unforeseen consequences and tradeoffs that are difficult to predict in ESD. In this research, ESD uses big data to enhance their operations and customer service, develop targeted marketing strategies, and boost sales and profitability. In ESD, Data analytics is being used by human resources to improve decision-making throughout the recruiting process and in evaluating employee performance. In the long run, Artificial Intelligence (AI) adoption may boost productivity and produce new goods, creating jobs and boosting the economy. AI may have a net beneficial impact on ESD. Therefore, ESD-AI helps to overcome the problems by minimizing costs and boosting the economy. AI-integrated ESD helps analyze vast amounts of data, which may increase the speed at which things are done and substantially enhance decision-making. Hence, a balanced approach is essential to guarantee that AI systems can tackle sustainability challenges without adversely compromising other aims to boost the economy

Evolutionary Game Analysis of Government and Residents&rsquo; Participation in Waste Separation Based on Cumulative Prospect Theory

Government and residents&rsquo; participation in waste separation is a complex non-cooperative game process, and the evolutionary game can explain the behavior of participating subjects well. Considering that the traditional evolutionary game cannot satisfactorily explain the irrational psychology and risk preference factors of the participating issues, this study combines the prospect theory and evolutionary game, uses the prospect value function to supplement and improve the parameters of the evolutionary game payment matrix, and analyzes the evolutionary stabilization strategy. To verify the theoretical results, simulation experiments and impact analysis were conducted, and meaningful results were obtained: There are two stable evolutionary strategies in the system, namely higher participation benefits for residents and lower participation costs and opportunity costs, and reasonable direct benefit distribution coefficients all help to increase the participation rate of waste separation. This study can provide some scientific suggestions for the government to design and build a waste-separation system