Sphere Formation Permits Oct4 Reprogramming of Ciliary Body Epithelial Cells into Induced Pluripotent Stem Cells

Somatic cells can be reprogrammed to induced pluripotent stem (iPS) cells by defined sets of transcription factors. We previously described reprogramming of monolayer-cultured adult mouse ciliary body epithelial (CE) cells by Oct4 and Klf4, but not with Oct4 alone. In this study, we report that Oct4 alone is sufficient to reprogram CE cells to iPS cells through sphere formation. Furthermore, we demonstrate that sphere formation induces a partial reprogramming state characterized by expression of retinal progenitor markers, upregulation of reprogramming transcription factors, such as Sall4 and Nanog, demethylation in the promoter regions of pluripotency associated genes, and mesenchymal to epithelial transition. The Oct4-iPS cells maintained normal karyotypes, expressed markers for pluripotent stem cells, and were capable of differentiating into derivatives of all three embryonic germ layers in vivo and in vitro. These findings suggest that sphere formation may render somatic cells more susceptible to reprogramming

Facile and Efficient Reprogramming of Ciliary Body Epithelial Cells into Induced Pluripotent Stem Cells

Induced pluripotent stem (iPS) cells are attractive for cell replacement therapy, because they overcome ethical and immune rejection issues that are associated with embryonic stem cells. iPS cells have been derived from autonomous fibroblasts at low efficiency using multiple ectopic transcription factors. Recent evidence suggests that the epigenome of donor cell sources plays an important role in the reprogramming and differentiation characteristics of iPS cells. Thus, identification of somatic cell types that are easily accessible and are more amenable for cellular reprogramming is critical for regenerative medicine applications. Here, we identify ciliary body epithelial cells (CECs) as a new cell type for iPS cell generation that has higher reprogramming efficiency compared with fibroblasts. The ciliary body is composed of epithelial cells that are located in the anterior portion of the eye at the level of the lens and is readily surgically accessible. CECs also have a reduced reprogramming requirement, as we demonstrate that ectopic Sox2 and c-Myc are dispensable. Enhanced reprogramming efficiency may be due to increased basal levels of Sox2 in CECs. In addition, we are the first to report a cellular reprogramming haploinsufficiency observed when reprogramming with fewer factors (Oct4 and Klf4) in Sox2 hemizygous cells. Taken together, endogenous Sox2 levels are critical for the enhanced efficiency and reduced exogenous requirement that permit facile cellular reprogramming of CECs

Process-Oriented Evaluation of Climate and Weather Forecasting Models

Realistic climate and weather prediction models are necessary to produce confidence in projections of future climate over many decades and predictions for days to seasons. These models must be physically justified and validated for multiple weather and climate processes. A key opportunity to accelerate model improvement is greater incorporation of process-oriented diagnostics (PODs) into standard packages that can be applied during the model development process, allowing the application of diagnostics to be repeatable across multiple model versions and used as a benchmark for model improvement. A POD characterizes a specific physical process or emergent behavior that is related to the ability to simulate an observed phenomenon. This paper describes the outcomes of activities by the Model Diagnostics Task Force (MDTF) under the NOAA Climate Program Office (CPO) Modeling, Analysis, Predictions and Projections (MAPP) program to promote development of PODs and their application to climate and weather prediction models. MDTF and modeling center perspectives on the need for expanded process-oriented diagnosis of models are presented. Multiple PODs developed by the MDTF are summarized, and an open-source software framework developed by the MDTF to aid application of PODs to centers’ model development is presented in the context of other relevant community activities. The paper closes by discussing paths forward for the MDTF effort and for community process-oriented diagnosis

Challenges in quantifying changes in the global water cycle

Human influences have likely already impacted the large-scale water cycle but natural variability and observational uncertainty are substantial. It is essential to maintain and improve observational capabilities to better characterize changes. Understanding observed changes to the global water cycle is key to predicting future climate changes and their impacts. While many datasets document crucial variables such as precipitation, ocean salinity, runoff, and humidity, most are uncertain for determining long-term changes. In situ networks provide long time-series over land but are sparse in many regions, particularly the tropics. Satellite and reanalysis datasets provide global coverage, but their long-term stability is lacking. However, comparisons of changes among related variables can give insights into the robustness of observed changes. For example, ocean salinity, interpreted with an understanding of ocean processes, can help cross-validate precipitation. Observational evidence for human influences on the water cycle is emerging, but uncertainties resulting from internal variability and observational errors are too large to determine whether the observed and simulated changes are consistent. Improvements to the in situ and satellite observing networks that monitor the changing water cycle are required, yet continued data coverage is threatened by funding reductions. Uncertainty both in the role of anthropogenic aerosols, and due to large climate variability presently limits confidence in attribution of observed changes

Development of High-Performance Soft Robotic Fish by Numerical Coupling Analysis

To design a soft robotic fish with high performance by a biomimetic method, we are developing a soft robotic fish using piezoelectric fiber composite (PFC) as a flexible actuator. Compared with the conventional rigid robotic fish, the design and control of a soft robotic fish are difficult due to large deformation of flexible structure and complicated coupling dynamics with fluid. That is why the design and control method of soft robotic fish have not been established and they motivate us to make a further study by considering the interaction between flexible structure and surrounding fluid. In this paper, acoustic fluid-structural coupling analysis is applied to consider the fluid effect and predict the dynamic responses of soft robotic fish in the fluid. Basic governing equations of soft robotic fish in the fluid are firstly described. The numerical coupling analysis is then carried out based on different structural parameters of soft robotic fish. Through the numerical analysis, a new soft robotic fish is finally designed, and experimental evaluation is performed. It is confirmed that the larger swimming velocity and better fish-like swimming performance are obtained from the new soft robotic fish. The new soft robotic fish is developed successfully for high performance

Genetic programming in robot exploration

Exploration using mobile robots is an active research area. In general, an optimal robot exploration strategy is difficult to obtain. In this paper an investigation is conducted using genetic programming (GP) to solve this problem. GP is a form of artificial intelligence capable of automatically creating and developing computer programs to solve problems using the theory of evolution. However, like many other learning algorithms, GP is a computationally expensive and time-consuming process. This characteristic can impede its application where learning time is limited, such as in real-time robotic control applications. Therefore, this paper further investigates the possibility of developing a time-efficient GP algorithm to reduce evolution time. This is done by directly incorporating the amount of time evolved solutions take to form into the fitness function, in order to encourage time efficient problem solving. Experimental results have shown that while the time efficient aspect of the proposed GP algorithm is not conclusive, the robot exploration using GP produces promising outcomes

Motion control of nonholonomic mobile underactuated manipulator

Motion control is investigated for a nonholonomic mobile manipulator using hybrid joints, which could be switched to either active (actuated) or passive (underactuated) mode. The mobile platform is driven with two independent wheels and the arm has hybrid joints in the horizontal plane. The dynamic constraints are shown to be a first-order nonholonomic for the mobile base and a second-order nonholonomic for the link when one of hybrid joints is underactuated. Two Different motion control methods for mobile underactuated manipulator with one passive joint are proposed. Simulation and experimental studies show the effectiveness of the proposed methods. ©2006 IEEE.Link_to_subscribed_fulltex