Programmable protein circuits in living cells Gao, Xiaojing J; Chong, Lucy S; Kim, Matthew S ...
Science (American Association for the Advancement of Science),
09/2018, Letnik:
361, Številka:
6408
Journal Article
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Synthetic protein-level circuits could enable engineering of powerful new cellular behaviors. Rational protein circuit design would be facilitated by a composable protein-protein regulation system in ...which individual protein components can regulate one another to create a variety of different circuit architectures. In this study, we show that engineered viral proteases can function as composable protein components, which can together implement a broad variety of circuit-level functions in mammalian cells. In this system, termed CHOMP (circuits of hacked orthogonal modular proteases), input proteases dock with and cleave target proteases to inhibit their function. These components can be connected to generate regulatory cascades, binary logic gates, and dynamic analog signal-processing functions. To demonstrate the utility of this system, we rationally designed a circuit that induces cell death in response to upstream activators of the Ras oncogene. Because CHOMP circuits can perform complex functions yet be encoded as single transcripts and delivered without genomic integration, they offer a scalable platform to facilitate protein circuit engineering for biotechnological applications.
The gold standard for diagnosing sleep disorders is polysomnography, which generates extensive data about biophysical changes occurring during sleep. We developed the National Sleep Research Resource ...(NSRR), a comprehensive system for sharing sleep data. The NSRR embodies elements of a data commons aimed at accelerating research to address critical questions about the impact of sleep disorders on important health outcomes.
We used a metadata-guided approach, with a set of common sleep-specific terms enforcing uniform semantic interpretation of data elements across three main components: (1) annotated datasets; (2) user interfaces for accessing data; and (3) computational tools for the analysis of polysomnography recordings. We incorporated the process for managing dataset-specific data use agreements, evidence of Institutional Review Board review, and the corresponding access control in the NSRR web portal. The metadata-guided approach facilitates structural and semantic interoperability, ultimately leading to enhanced data reusability and scientific rigor.
The authors curated and deposited retrospective data from 10 large, NIH-funded sleep cohort studies, including several from the Trans-Omics for Precision Medicine (TOPMed) program, into the NSRR. The NSRR currently contains data on 26 808 subjects and 31 166 signal files in European Data Format. Launched in April 2014, over 3000 registered users have downloaded over 130 terabytes of data.
The NSRR offers a use case and an example for creating a full-fledged data commons. It provides a single point of access to analysis-ready physiological signals from polysomnography obtained from multiple sources, and a wide variety of clinical data to facilitate sleep research.
Direct laser writing (DLW) is a three-dimensional (3D) manufacturing technology that offers vast architectural control at submicron scales, yet remains limited in cases that demand microstructures ...comprising more than one material. Here we present an accessible microfluidic multi-material DLW (μFMM-DLW) strategy that enables 3D nanostructured components to be printed with average material registration accuracies of 100 ± 70 nm (ΔX) and 190 ± 170 nm (ΔY) - a significant improvement versus conventional multi-material DLW methods. Results for printing 3D microstructures with up to five materials suggest that μFMM-DLW can be utilized in applications that demand geometrically complex, multi-material microsystems, such as for photonics, meta-materials, and 3D cell biology.
Individuals possess different beliefs regarding the malleability of intelligence, also known as intelligence mindsets. Despite evidence demonstrating a link between a growth mindset of ...intelligence—the belief that intelligence can develop through effort—and academic achievement, this link has not been closely examined from a mental health perspective. Given the increasing prevalence of mental health conditions, such as anxiety and depression, among undergraduate students, an important question is whether the well-established link between mental health symptom severity and academic outcomes depends on the intelligence mindset beliefs that individuals possess. A growth mindset of intelligence might buffer the negative impact of anxiety and depression on academic outcomes, whereas a fixed mindset—the belief that intelligence cannot be changed—might exacerbate this negative relationship. The present study examined data collected from 660 undergraduate psychology students in the United States to test whether intelligence mindset beliefs moderated the relationship between mental health symptom severity and various indicators of academic outcomes: academic self-efficacy, GPA, and perceived academic standing. Results revealed that intelligence mindset beliefs did not moderate the observed negative association between mental health symptom severity and academic outcomes. Findings indicate that promoting a growth mindset of intelligence might not be a particularly effective strategy for buffering university students from the negative impact of anxiety and depression on academic outcomes. However, this conclusion is limited by the cross-sectional design of the study, and future prospective research is necessary to further clarify the relationship between intelligence mindset, mental health, and academic outcomes.
Executive functions (EF) are domain-general cognitive skills that predict foundational academic skills such as literacy and numeracy. However, less is known about the relation between EFs and science ...achievement. The nature of this relation might be explained by the theory of mutualism, which states that development is the result of complex and interacting processes, in which growth in one domain influences growth in another domain. The present study examined the bidirectional associations between science achievement and children's cognitive flexibility and working memory in a nationally representative sample of children in the United States (Early Childhood Longitudinal Study: Kindergarten Class of 2010-2011 ECLS-K:2011; N = 18,174). Using random intercepts cross-lagged panel modeling, results revealed a heterogeneous pattern of associations between EF and science achievement, consistent with mutualism theory. Trait-like and construct stability emerged in the between-person and within-person estimates of EF and science. Cognitive flexibility and working memory in kindergarten each predicted science achievement in first grade. Science achievement at the beginning of first grade predicted cognitive flexibility at the end of first grade. There were also bidirectional associations between working memory and science achievement from the beginning to the end of the first grade year. Although effect sizes were small, findings reveal the complex interplay between EF and science achievement during early childhood and highlight a core tenet of mutualism theory-that small gains in academic and cognitive domains are positively associated with future skills and abilities within and across domains.
Professional sleep societies have identified a need for strategic research in multiple areas that may benefit from access to and aggregation of large, multidimensional datasets. Technological ...advances provide opportunities to extract and analyze physiological signals and other biomedical information from datasets of unprecedented size, heterogeneity, and complexity. The National Institutes of Health has implemented a Big Data to Knowledge (BD2K) initiative that aims to develop and disseminate state of the art big data access tools and analytical methods. The National Sleep Research Resource (NSRR) is a new National Heart, Lung, and Blood Institute resource designed to provide big data resources to the sleep research community. The NSRR is a web-based data portal that aggregates, harmonizes, and organizes sleep and clinical data from thousands of individuals studied as part of cohort studies or clinical trials and provides the user a suite of tools to facilitate data exploration and data visualization. Each deidentified study record minimally includes the summary results of an overnight sleep study; annotation files with scored events; the raw physiological signals from the sleep record; and available clinical and physiological data. NSRR is designed to be interoperable with other public data resources such as the Biologic Specimen and Data Repository Information Coordinating Center Demographics (BioLINCC) data and analyzed with methods provided by the Research Resource for Complex Physiological Signals (PhysioNet). This article reviews the key objectives, challenges and operational solutions to addressing big data opportunities for sleep research in the context of the national sleep research agenda. It provides information to facilitate further interactions of the user community with NSRR, a community resource.
Introduction:
Although advancing age is known to influence the formation of thyroid nodules, the precise relationship remains unclear. Furthermore, it is uncertain whether age influences the risk ...that any thyroid nodule may prove cancerous.
Aim:
The aim was to determine the impact of patient age on nodule formation, multinodularity, and risk of thyroid malignancy.
Method:
We conducted a prospective cohort analysis of consecutive adults (ages 20–95 y) who presented for evaluation of nodular disease from 1995 to 2011. A total of 6391 patients underwent ultrasound and fine-needle aspiration of 12 115 nodules ≥1 cm. Patients were divided into six age groups and compared using sonographic, cytological, and histological endpoints.
Result:
The prevalence of thyroid nodular disease increases with advancing age. The mean number of nodules at presentation increased from 1.5 in the youngest cohort (age, 20–30 y) to 2.2 in the oldest cohort (age, >70 y; P < .001), demonstrating a 1.6% annual increased risk for multinodularity (odds ratio, 1.02; P < .001). In contrast, the risk of malignancy in a newly identified nodule declined with advancing age. Thyroid cancer incidence per patient was 22.9% in the youngest cohort, but 12.6% in the oldest cohort (odds ratio, 0.972; P < .001), demonstrating a 2.2% decrease per year in the relative risk of malignancy between ages 20 and 60 years, which stabilized thereafter. Despite a lower likelihood of malignancy, identified cancers in older patients demonstrated higher risk histological phenotypes. Although nearly all malignancies in younger patients were well-differentiated, older patients were more likely to have higher risk papillary thyroid carcinoma variants, poorly differentiated cancer, or anaplastic carcinoma (P < .001).
Conclusion:
With advancing age, the prevalence of clinically relevant thyroid nodules increases, whereas the risk that such nodules are malignant decreases. Nonetheless, when thyroid cancer is detected in older individuals, a higher-risk histological phenotype is more likely. These data provide insight into the clinical paradox that confronts physicians managing this common illness.
Abstract Children possess different beliefs regarding their ability to succeed in math and science, as well as different levels of enjoyment and interest in these topics. These motivational processes ...are important because they often shape learning‐related behaviours which in turn predict academic outcomes, over and above previous performance. But, what are the potential sources of influence that could explain individual differences in children's academic self‐concept and interest in math and science? In this registered report, we adopted a situated expectancy‐value theory framework to examine the potential role of teacher instructional practices that emphasize conceptual understanding in enhancing these motivational processes. We focused on practices emphasizing conceptual understanding given science‐driven recommendations to implement them across the United States. Contrary to our hypotheses, a multilevel analysis of grade 4 U.S. data from the 2015 release of the Trends in International Mathematics and Science Study (TIMSS) revealed that the self‐reported frequency of instructional practices emphasizing conceptual understanding were unrelated to math or science self‐concept and interest. Our null findings prompt greater attention to other factors, such as the quality and implementation of instructional practices, differences between instructional goals and actual practices, and classroom composition, that could enhance ability beliefs and values in math and science.
Entry into formal schooling is a signature developmental milestone for young children and their families and represents an important period of cognitive, social, and emotional development. Until ...recently, few researchers have attempted to isolate the unique impact of schooling on children’s developmental and academic outcomes. The application of quasiexperimental methods has provided researchers with the tools to examine when and how schooling shapes children’s development. In this article, we summarize three main insights from this work: (a) Schooling produces major, unique changes in children’s growth across a wide range of psychological processes important for learning; (b) the effects of schooling are not universal across all domains; and (c) schooling impacts cognitive processes that are not explicitly taught. We also propose that a deeper look at classroom instruction and brain development can expand our understanding of how schooling influences academic success and positive life outcomes and provide a model for developmental science more broadly.
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