Rational engineering of biological systems is often complicated by the complex but unwanted interactions between cellular components at multiple levels. Here we address this issue at the level of prokaryotic transcription by insulating minimal promoters and operators to prevent their interaction and enable the biophysical modeling of synthetic transcription without free parameters. This approach allows genetic circuit design with extraordinary precision and diversity, and consequently simplifies the design-build-test-learn cycle of circuit engineering to a mix-and-match workflow. As a demonstration, combinatorial promoters encoding NOT-gate functions were designed from scratch with mean errors of <1.5-fold and a success rate of >96% using our insulated transcription elements. Furthermore, four-node transcriptional networks with incoherent feed-forward loops that execute stripe-forming functions were obtained without any trial-and-error work. This insulation-based engineering strategy improves the resolution of genetic circuit technology and provides a simple approach for designing genetic circuits for systems and synthetic biology.

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Fusing multiple change detection results has great potentials in dealing with the spectral variability in multitemporal very high-resolution (VHR) remote sensing images. However, it is difficult to solve the problem of uncertainty, which mainly includes the inaccuracy of each candidate change map and the conflicts between different results. Dempster-Shafer theory (D-S) is an effective method to model uncertainties and combine multiple evidences. Therefore, in this paper, we proposed an urban change detection method for VHR images by fusing multiple change detection methods with D-S evidence theory. Change vector analysis (CVA), iteratively reweighted multivariate alteration detection (IRMAD), and iterative slow feature analysis (ISFA) were utilized to obtain the candidate change maps. The final change detection result is generated by fusing the three evidences with D-S evidence theory and a segmentation object map. The experiment indicates that the proposed method can obtain the best performance in detection rate, false alarm rate, and comprehensive indicators.

At present, the complex pathogenesis, the difficult-to-overcome blood–brain barrier (BBB), the development of the disease course which cannot be prevented, and other problems are serious challenges in the treatment of Alzheimer’s disease (AD). In order to enhance the therapeutic effect of drugs through BBB, we synthesized simple and easy-to-obtain selenium quantum dots (SeQDs), with a multitarget therapeutic effect. This new type of SeQDs has an ultrasmall size and can quickly penetrate the BBB. According to the fluorescence characteristics of SeQDs, we can diagnose and track AD. The experimental results show that SeQDs have strong free-radical scavenging activity, protect cells from oxidative stress induced by different stimuli, and show broad-spectrum antioxidant activity. The SeQDs can not only effectively inhibit Aβ aggregation and significantly reduce Aβ-mediated cytotoxicity, thus preventing AD cascade reaction, but also effectively reduce tau protein phosphorylation by down-regulating PHF1 and CP13 and further reduce oxidative stress, restore mitochondrial functions, and maintain nerve cell stability and protect nerve cells from oxidative stress. In vivo studies demonstrate that SeQDs can continuously accumulate in the brain after rapid passage of BBB and can quickly alleviate AD, significantly improve the memory impairment of AD mice, and improve their learning and memory ability. Therefore, the use of SeQDs in the treatment of AD has great advantages compared with traditional single-target drugs and provides a new direction for the combination of prevention and treatment of neurodegenerative diseases.

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Land use is of great importance for urban planning, environmental monitoring, and transportation management. Several methods have been proposed to obtain land use maps of urban areas, and these can be classified into two categories: remote sensing methods and social sensing methods. However, remote sensing and social sensing approaches have specific disadvantages regarding the description of social and physical features, respectively. Therefore, an appropriate fusion strategy is vital for large-area land use mapping. To address this issue, we propose an efficient land use mapping method that combines remote sensing imagery (RSI) and mobile phone positioning data (MPPD) for large areas. We implemented this method in two steps. First, a support vector machine was adopted to classify the RSI and MPPD. Then, the two classification results were fused using a decision fusion strategy to generate the land use map. The proposed method was applied to a case study of the central area of Beijing. The experimental results show that the proposed method improved classification accuracy compared with that achieved using MPPD alone, validating the efficacy of this new approach for identifying land use. Based on the land use map and MPPD data, activity density in key zones during daytime and nighttime was analyzed to illustrate the volume and variation of people working and living across different regions.

Rreactive oxygen species (ROS) mediated anti-cancer therapy hold the advantages of tumor specificity, high curative effect, and low toxic side effects, which shows powerful potential for cancer treatment.However, hypoxia in...