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Characterizing changes in rock properties is essential for the hydraulic fracture and re-fracture parameter optimization of shale formations. This paper proposed a hydraulic fracturing model to investigate the changes in rock properties during hydraulic fracturing using SPH, and the changes in the stress field and rock properties were quantitatively characterized. The simulation results indicated that the minimum horizontal principal stress increased by 10 MPa~15 MPa during fracture propagation, which is the main reason for the uneven propagation in multi-fracture propagation. Affected by the stress disturbance, the stimulated area was divided into four parts based on the changes in Young's modulus and permeability; the more seriously the stress disturbance was affected, the higher the permeability of the stimulated zone was, and the smaller the stimulated zone was. Meanwhile, a zone with reduced permeability appeared due to the compression effect caused by the high injection pressure, and this increased with the increase in stress disturbance. The main reason for this was that strain formed because of the compression effect from the high injection pressure. The higher the stress disturbance, the higher the accumulated strain. This new model provides a new method for fracture parameter optimization, which also provides a foundation for the re-fracture parameter optimization of shale formations. [ABSTRACT FROM AUTHOR]

Resistance to chemotherapy remains a formidable obstacle in acute myeloid leukemia (AML) therapeutic management, necessitating the exploration of optimal strategies to maximize therapeutic benefits. Venetoclax with 3+7 daunorubicin and cytarabine (DAV regimen) in young adult de novo AML patients is evaluated. 90% of treated patients achieved complete remission, underscoring the potential of this regimen as a compelling therapeutic intervention. To elucidate underlying mechanisms governing response to DAV in AML, quantitative phosphoproteomics to discern distinct molecular signatures characterizing a subset of DAV‐sensitive patients is used. Cluster analysis reveals an enrichment of phosphoproteins implicated in chromatin organization and RNA processing within DAV‐susceptible and DA‐resistant AML patients. Furthermore, kinase activity profiling identifies AURKB as a candidate indicator of DAV regimen efficacy in DA‐resistant AML due to AURKB activation. Intriguingly, AML cells overexpressing AURKB exhibit attenuated MCL‐1 expression, rendering them receptive to DAV treatment and maintaining them resistant to DA treatment. Moreover, the dataset delineates a shared kinase, AKT1, associated with DAV response. Notably, AKT1 inhibition augments the antileukemic efficacy of DAV treatment in AML. Overall, this phosphoproteomic study identifies the role of AURKB as a predictive biomarker for DA, but not DAV, resistance and proposes a promising strategy to counteract therapy resistance in AML. [ABSTRACT FROM AUTHOR]

The virtual teaching and research platform is a cognitive and practical activity for relevant teachers engaged in education and teaching research to improve and improve the quality of education and teaching, relying on the unique functions and resource advantages of the network, using information technology and various network tools to carry out teaching, feedback, etc., and to carry out education and teaching exchange, discussion and other education and teaching research with other administrative organizations or teachers in space regions. It can break the constraints of time, space, organization and other factors. It is an effective form of educational and teaching activities carried out for common goals. It integrates teaching, guidance, discussion, exchange, resource sharing and other functions, and is an important part of the "double training plan". The collaborative innovation ability training mode selection of virtual teaching and research platforms as a multi-attribute group decision making (MAGDM) problem. In this paper, the Evaluation Based on Distance from Average Solution (EDAS) method is extended to the single-valued neutrosophic sets (SVNSs) and single-valued neutrosophic EDAS method (SVN-EDAS) is proposed to solve MAGDM problem. Finally, the collaborative innovation ability training mode selection of virtual teaching and research platforms is given to show the SVN-EDAS model and some comparative analysis is conduct to depict the advantages of SVN-EDAS. [ABSTRACT FROM AUTHOR]