Generation of Human Epidermis-Derived Mesenchymal Stem Cell-like Pluripotent Cells and their reprogramming in mouse chimeras

Stem cells can be derived from the embryo (embryonic stem cells, ESCs), from adult tissues (adult stem cells, ASCs), and by induction of fibroblasts (induced pluripotent stem cells, iPSs). Ethical problems, immunological rejection, and difficulties in obtaining human tissues limit the use of ESCs in clinical medicine. Induced pluripotent stem cells are difficult to maintain in vitro and carry a greater risk of tumor formation. Furthermore, the complexity of maintenance and propagation is especially difficult in the clinic. Adult stem cells can be isolated from several adult tissues and present the possibility of self-transplantation for the clinical treatment of a variety of human diseases. Recently, several ASCs have been successfully isolated and cultured in vitro, including hematopoietic stem cells (HSCs) , mesenchymal stem cells (MSCs), epidermis stem cells, neural stem cells (NSCs), adipose-derived stem cells (ADSCs), islet stem cells, and germ line stem cells. Human mesenchymal stem cells originate mainly from bone marrow, cord blood, and placenta, but epidermis-derived MSCs have not yet been isolated. We isolated small spindle-shaped cells with strong proliferative potential during the culture of human epidermis cells and designed a medium to isolate and propagate these cells. They resembled MSCs morphologically and demonstrated pluripotency in vivo; thus, we defined these cells as human epidermis-derived mesenchymal stem cell-like pluripotent cells (hEMSCPCs). These hEMSCPCs present a possible new cell resource for tissue engineering and regenerative medicine

The impacts of environmental benefit concern of enterprises on competitive supply chain economic and environmental benefits

To promote the sustainable development of supply chains, numerous manufacturers are embracing corporate environmental responsibility to mitigate the ecological consequences of production activities. The environmental benefit concern (EBC) of enterprises not only affects their operations strategies but also impacts other enterprises within the supply chains. Therefore, it is essential to study the influences of EBC behaviors on supply chain performances under various competitive scenarios. This paper examines a supply chain comprising two manufacturers and one retailer under two distinct competitive settings: Competition between non-green and green products (OE), and competition between green products from small and big brands (SB). The study analyzes the effects of unilateral, bilateral or multilateral EBC behaviors on both the economic and environmental benefits of the supply chain. Key findings emerge from this study. Firstly, prioritizing environmental benefits throughout the supply chain has the potential to enhance environmental performance. Secondly, unilateral EBC behavior can lead to a vertical altruistic effect, where the focus on environmental benefit by a manufacturer (retailer) increases the retailer's (manufacturer) profit but reduces its own profit. Additionally, unilateral EBC behavior among manufacturers creates a competitive squeezing effect on each other, potentially diminishing competitor profits. Notably, the retailer's focus on environmental benefit can also reduce the profit of the non-green manufacturer. Thirdly, when the levels of EBC are relatively low, bilateral or multilateral through EBC leads to a positive effect on economic performance, resulting in increased profits for both the green manufacturers and retailer. In conclusion, bilateral EBC has the potential to enhance both economic and environmental benefits in the OE scenario.</p

Identifying latent grouped patterns in cointegrated panels

Ministry of Education, Singapore under its Academic Research Funding Tier 2; Lee Kong Chian Fund for Excellenc

Identify latent group structures in panel data: The classifylasso command

In this article, we introduce a new command, classifylasso, that implements the classifier-lasso method (Su, Shi, and Phillips, 2016, Econometrica 84: 2215–2264) to simultaneously identify and estimate unobserved parameter heterogeneity in panel-data models using penalized techniques. We document the functionality of this command, including 1) penalized least-squares estimation of group-specific coefficients and classification of unknown group membership under a certain number of groups; 2) two lasso-type estimators with robust standard errors, namely, classifier-lasso and postlasso; and 3) determination of the number of groups based on an information criterion. We further develop some postestimation commands to display and visualize the estimation results

Designing multi-target salesforce incentive contract

Multi-target incentive contracts are widely observed in practice to stimulate salesforce effort. However, little is known about their effectiveness and the issues involved in designing them. In this thesis, we investigate the incentive contracting problem between a manufacturer and an agent when the realized sales of a product are affected by both the agent\u27s selling effort and the type of the agent. The agent\u27s type is uncertain to the manufacturer, whereas the agent can observe the actual type when exerting her selling effort. Again, this is unobservable by the manufacturer. For contract design problem, we develop a principal-agent model with both moral hazard and adverse selection. We examine the manufacturer\u27s optimal contract parameter decisions employing a single multi-target contract for the agent who can be of different types. Because menu contracts are commonly studied in literature for the adverse selection problem, we also study a menu of single-target contracts; and examine the manufacturer\u27s optimal contract parameter decisions. We then compare the performance between the two types of contract. We arrive at a number of managerial insights regarding the design and the performance of multi-target contract and menu contract