We designed and constructed a genetic sequential logic circuit that can function as a push-on push-off switch. The circuit consists of a bistable switch module and a NOR gate module.The bistable switch module and NOR gate module were rationally designed and constructed.The two above modules were coupled by two interconnecting parts, cIind- and lacI. When optimizing the defined function, we fine-tuned the expression of the two interconnecting parts by directed evolution.Three control circuits were constructed to show the interconnecting parts are essential for achieving the defined function.
Prediction of popularity has profound impact for social media, since it offers opportunities to reveal individual preference and public attention from evolutionary social systems. Previous research, although achieves promising results, neglects one distinctive characteristic of social data, i.e., sequentiality. For example, the popularity of online content is generated over time with sequential post streams of social media. To investigate the sequential prediction of popularity, we propose a novel prediction framework called Deep Temporal Context Networks (DTCN) by incorporating both temporal context and temporal attention into account. Our DTCN contains three main components, from embedding, learning to predicting. With a joint embedding network, we obtain a unified deep representation of multi-modal user-post data in a common embedding space. Then, based on the embedded data sequence over time, temporal context learning attempts to recurrently learn two adaptive temporal contexts for sequential popularity. Finally, a novel temporal attention is designed to predict new popularity (the popularity of a new userpost pair) with temporal coherence across multiple time-scales. Experiments on our released image dataset with about 600K Flickr photos demonstrate that DTCN outperforms state-of-the-art deep prediction algorithms, with an average of 21.51% relative performance improvement in the popularity prediction (Spearman Ranking Correlation).
Context and purposeThere is an urgent need to develop vitamin D dietary recommendations for dark-skinned populations resident at high latitude. Using data from randomised controlled trials (RCTs) with vitamin D 3 -supplements/fortified foods, we undertook an individual participant data-level meta-regression (IPD) analysis of the response of wintertime serum 25-hydroxyvitamin (25(OH)D) to total vitamin D intake among dark-skinned children and adults residing at ≥ 40° N and derived dietary requirement values for vitamin D. Methods IPD analysis using data from 677 dark-skinned participants (of Black or South Asian descent; ages 5-86 years) in 10 RCTs with vitamin D supplements/fortified foods identified via a systematic review and predefined eligibility criteria. Outcome measures were vitamin D intake estimates across a range of 25(OH)D thresholds. Results To maintain serum 25(OH)D concentrations ≥ 25 and 30 nmol/L in 97.5% of individuals, 23.9 and 27.3 µg/day of vitamin D, respectively, were required among South Asian and 24.1 and 33.2 µg/day, respectively, among Black participants. Overall, our age-stratified intake estimates did not exceed age-specific Tolerable Upper Intake Levels for vitamin D. The vitamin D intake required by dark-skinned individuals to maintain 97.5% of winter 25(OH)D concentrations ≥ 50 nmol/L was 66.8 µg/day. This intake predicted that the upper 2.5% of individuals could potentially achieve serum 25(OH)D concentrations ≥ 158 nmol/L, which has been linked to potential adverse effects in older adults in supplementation studies. Conclusions Our IPD-derived vitamin D intakes required to maintain 97.5% of winter 25(OH)D concentrations ≥ 25, 30 and 50 nmol/L are substantially higher than the equivalent estimates for White individuals. These requirement estimates are also higher than those currently recommended internationally by several agencies, which are based predominantly on data from Whites and derived from standard meta-regression based on aggregate data. Much more work is needed in dark-skinned populations both in the dose-response relationship and risk characterisation for health outcomes. Trail registration PROSPERO International Prospective Register of SystematicReviews (Registration Number: CRD42018097260)
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