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Summary: Binary data subject to one type of misclassification exist in various fields. It is collected in a double‐sampling scheme that includes a gold standard test and a fallible test. The main parameter of interest for this type of data is the positive probability p$$ p $$ of the gold standard test. Existing intervals are unreliable because the given nominal level 1−α$$ 1-\alpha $$ is not achieved. In this paper, we construct an exact interval by inverting the E+M score tests and improve it by the general h$$ h $$‐function method. We find that the total length of the improved interval is shorter than the exact intervals that are also the improved intervals when we apply the h$$ h $$‐function to several existing approximate intervals, including the score and Bayesian intervals. Therefore, it is recommended for practice. We are also interested in two other parameters: p∗$$ {p}^{\ast } $$—the difference between the two positive rates for the fallible and gold standard tests—and ξ$$ \xi $$—the false positive rate for the fallible test. To the best of our knowledge, the research on these two parameters is limited. For p∗$$ {p}^{\ast } $$, we find that any interval for p$$ p $$ can be converted to an interval for p∗$$ {p}^{\ast } $$. So, the interval converted from the aforementioned recommended interval for p$$ p $$ is recommended for inferring p∗$$ {p}^{\ast } $$. For ξ$$ \xi $$, the improved interval by the h$$ h $$‐function method over the E+M score interval is derived. We use an example to illustrate how the intervals are computed and provide a real data analysis. [ABSTRACT FROM AUTHOR]

The relative risk and odds ratio are widely used in many fields, including biomedical research, to compare two treatments. Extensive research has been done to infer the two parameters through approximate or exact confidence intervals. However, these intervals may be liberal or conservative. A natural question is whether the intervals can be further improved in maintaining the correct confidence coefficient of an approximate interval or shortening an exact but conservative interval. In this article, when two independent binomials are observed we offer an effort to improve any of the existing intervals by applying the h$$ h $$‐function method. In particular, if the given interval is approximate, then the improved interval is exact; if the given interval is exact, then the improved interval is a subset of the given interval. This method is also applied multiple times to the improved intervals until the final resultant interval cannot be shortened any further. To demonstrate the effectiveness of the method, we use three real datasets to illustrate in detail how several good intervals in practice are improved. Two exact intervals are then recommended for estimating each of the two parameters in different scenarios. [ABSTRACT FROM AUTHOR]

Recently, researchers have been attempting to control pluripotent stem cell fate or generate self-organized tissues from stem cells. Advances in bioengineering enable generation of organotypic structures, which capture the cellular components, spatial cell organization and even some functions of tissues or organs in development. However, only a few engineering tools have been utilized to regulate the formation and organization of spatially complex tissues derived from stem cells. Here, we provide a review of recent progress in the culture of organotypic structures in vitro, focusing on how microengineering approaches including geometric confinement, extracellular matrix (ECM) property modulation, spatially controlled biochemical factors, and external forces, can be utilized to generate organotypic structures. Moreover, we will discuss potential technologies that can be applied to further control both soluble and insoluble factors spatiotemporally in vitro. In summary, advanced engineered approaches have a great promise in generating miniaturized tissues and organs in a reproducible fashion, facilitating the cellular and molecular understanding of embryogenesis and morphogenesis processes. [ABSTRACT FROM AUTHOR]