Suchergebnisse

Purpose
The purpose of this paper is to argue that financial development, measured by private credit in the economy, affects exports in an inverted U-shaped manner. The authors use the new trade theory model and empirical data to analyze whether the financial system is the reason of global imbalance.


Design/methodology/approach
This paper builds a simple production model to connect financial development with a country's export or outward foreign direct investment (ODI) decision. Using a panel data covering 108 countries for the period 1990-2011, the authors find strong evidence to show that when a country is at a lower financial development level, further advancements of its financial system will boost exports.


Findings
First, an inverted U-shaped relationship between exports, imports and financial development is found in the study of 108 countries over the period 1990-2011; second, ODI provides a substitute effect to exports for financially advanced countries. These findings have provided an alternative explanation to international trade imbalances and contribute constructively to the discussion regarding whether exports and financial development are positively related or not.


Originality/value
As a result, the findings shed some light on the issue of global current account imbalances between developing and developed countries from a new perspective.

Yao Sun,1–3 Shenyu Wang,1–3 Long Zhao,2,3 Bin Zhang,2,3 Hu Chen2,31Academy of Military Medical Sciences, Beijing 100071, People's Republic of China; 2Department of Hematopoietic Stem Cell Transplantation, The Fifth Medical Center of Chinese PLA General Hospital (Former 307th, Hospital of PLA), the Research Institute of Hematopoietic Stem Cell of the People's Liberation Army, Beijing 100071, People's Republic of China; 3Beijing Key Laboratory of Hematopoietic Stem Cell Therapy and Transformation Research, Beijing 100071, People's Republic of ChinaBackground: CD123-targeted chimeric antigen receptor (CAR) T cell (CART123) for the treatment of acute myeloid leukemia (AML) and blastic plasmacytoid dendritic cell neoplasm has exhibited potential in clinical trials. However, capillary leakage syndrome, which is associated with endothelial cells damage, is under intensive focus in CART123 therapy.Purpose: The present study aimed to explore the change in CD123 in endothelial cells and the injury to endothelial cells caused by CART123.Methods: The expression of CD123 and cytotoxicity were assessed by flow cytometry. Cytokine release was assessed by ELISA. An in vitro co-culture model was designed to mimic the status, wherein CART123 was stimulated and cytokines were released.Results: In the current study, CART123 exhibited cytotoxicity and the effects of cytokine production on endothelium, and the upregulation of CD123 enhanced the cytotoxicity. The addition of interferon (IFN)-γ and tumor necrosis factor (TNF)-α neutralizing antibodies can effectively reverse the upregulation of CD123 on the endothelial cells caused by CART123, while the cytotoxicity of CART123 in AML cell lines was not affected in vitro. Second, we proved that CD123 expresses in CART123 and would be upregulated after activation, putatively causing an overactivated and fratricide effect.Conclusion: In summary, this study identified that the expression of CD123 on endothelial cells could be upregulated when co-cultured with CART123. Furthermore, IFN-γ and TNF-α could aggravate endothelial damage caused by CART123 in vitro.Keywords: chimeric antigen receptor, CD123, capillary leak syndrome, cytokine release syndrome, acute myeloid leukemia, endothelium

This study presents an innovative optimization method for resource scheduling in multi-energy storage systems, focusing on improving resource allocation while considering supply-demand flexibility and renewable energy integration. As renewable energy gains popularity and multi-energy systems become more complex, effective utilization of energy storage to achieve supply-demand balance, optimize energy scheduling, and maximize renewable energy integration is crucial. To address this challenge, a Markov dynamic model is developed to capture the dynamic changes in energy supply and demand within the multi-energy storage system. The model is then solved using a reinforcement learning approach to optimize resource scheduling decisions. Numerical simulations and case studies are conducted to validate the effectiveness and feasibility of the proposed method, showcasing its potential to enhance operational efficiency and reliability in multi-energy storage systems amidst constantly changing energy patterns. This research provides valuable insights and decision support for the design and operation of multi-energy storage systems, contributing to the advancement of sustainable energy utilization and promoting sustainable development in the energy sector.