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Diversified molecular information-processing methods have significant implications for nanoscale manipulation and control, monitoring and disease diagnosis of organisms, and direct intervention in biological activities. However, as an effective approach for implementing multifunctional molecular information processing, DNA reaction networks (DRNs) with numerous functionally specialized molecular structures have challenged them on scale design, leading to increased network complexity, further causing problems such as signal leakage, attenuation, and cross-talk in network reactions. Our study developed a strategy for performing various signal-processing tasks through engineering modular DRNs. This strategy is based on a universal core unit with signal selection capability, and a time-adjustable signal self-resetting module is achieved by combing the core unit and self-resetting unit, which improves the time controllability of modular DRNs. In addition, multi-input and -output signal cross-catalytic and continuously adjustable signal delay modules were realized by combining core and threshold units, providing a flexible, precise method for modular DRNs to process the signal. The strategy simplifies the design of DRNs, helps generate design ideas for large-scale integrated DRNs with multiple functions, and provides prospects in biocomputing, gene regulation, and biosensing.
Assuntos
DNA , DNA/química , Técnicas Biossensoriais/métodosRESUMO
Although the World Health Organization has declared that the COVID-19 pandemic no longer qualifies as a global public health emergency, it still needs to explore the response of society to the COVID-19 pandemic. Socio-economic status (SES) was proven to be linearly associated with the COVID-19 pandemic, although this relationship may be more complex due to regional differences. In the study, we analyzed and revealed the effects and mechanisms of SES on infections among low, lower-middle, upper-middle and high SES group (LSG, LMSG, UMSG, and HSG, respectively). The results showed that the relationship between SES and infections was inverted U-shaped, especially in the first three phases. In Phase I, UMSG had the highest number of infections, with an average of 238.31/1M people (95%CI: 135.47-341.15/1M people). In Phases II and III, infections decreased insignificantly with increasing SES (r = -0.01, p = 0.92; r = -0.11, p = 0.22) and the highest number of infections were found in the LMSG. In Phase IV, SES was positively related to the number of infections (r = 0.54, p < 0.001). Furthermore, the nonlinear impact of multiple factors related to SES on the infections explains the complex relationships between SES and infections. SES affected infections mainly through medical resources, demographics and vaccination, and differed across the SES groups. Particularly, demographics could exert an impact on population mobility, subsequently influencing infections in LMSG, with an indirect effect of 0.01 (p < 0.05) in Phase II. This study argues for greater attention to countries with middle SES and the need for future targeted measures to cope with infectious diseases.
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DNA tweezers, with their elegant simplicity and flexibility, have been pivotal in biosensing and DNA computing. However, conventional tweezers are confined to a binary transformation pre/post target signal recognition, limiting them to presence/absence judgments. This study introduces bubble DNA tweezers (BDT), capable of three distinct conformations based on variable target signal ratios. In contrast to traditional compact tweezers, BDT features a looser structure centered around a non-complementary bubble domain located between the tweezer arms' connecting axis and target signal recognition jaws. This bubble triggers toehold-free DNA strand displacement, leading to three conformational changes at different target signal concentrations. BDT detects presence/absence and true concentration with remarkable specificity and sensitivity. This adaptability is not confined to ideal scenarios, proving valuable in complex, noisy environments. Our method facilitates target DNA/miRNA signal quantification within a specific length range, promising applications in clinical research and environmental detection, while inspiring future biological assay innovations.
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The United Nations' Sustainable Development Goal (SDG) 3.9 calls for a substantial reduction in deaths attributable to PM2.5 pollution (DAPP). However, DAPP projections vary greatly and the likelihood of meeting SDG3.9 depends on complex interactions among environmental, socio-economic, and healthcare parameters. We project potential future trends in global DAPP considering the joint effects of each driver (PM2.5 concentration, death rate of diseases, population size, and age structure) and assess the likelihood of achieving SDG3.9 under the Shared Socioeconomic Pathways (SSPs) as quantified by the Scenario Model Intercomparison Project (ScenarioMIP) framework with simulated PM2.5 concentrations from 11 models. We find that a substantial reduction in DAPP would not be achieved under all but the most optimistic scenario settings. Even the development aligned with the Sustainability scenario (SSP1-2.6), in which DAPP was reduced by 19%, still falls just short of achieving a substantial (≥20%) reduction by 2030. Meeting SDG3.9 calls for additional efforts in air pollution control and healthcare to more aggressively reduce DAPP.
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Poluentes Atmosféricos , Poluição do Ar , Poluição do Ar/efeitos adversos , Poluição do Ar/análise , Poluição Ambiental , Conservação dos Recursos Naturais , Material Particulado/efeitos adversos , Atenção à Saúde , Poluentes Atmosféricos/toxicidade , Poluentes Atmosféricos/análiseRESUMO
The Jishishan Ms 6.2 earthquake occurred at 23:59 on December 18, 2023 in Gansu Province, China. We conducted a field survey to assess the hazards and damages caused by the earthquake and its associated geo-activities. Subsequently, we organized a seminar to discuss the possible causes of the destruction of a prehistoric site-Lajia Settlement-dated back to four thousand years B.P. and located only several kilometers away from the epicenter of the Jishishan earthquake. The Jishishan earthquake was unique for its hazard and disaster process, which featured ground shaking and a series of complex geological and geomorphological activities: sediment and soil spray piles, liquefaction, collapse, landslide, and mudflow along water channels. We define this phenomenon as the Jishishan earthquake ripple hazard (JERH). The most recent evidence from the JERH suggests that a prehistoric earthquake similar to the JERH, instead of riverine floods or earthquake-induced landslide dam outburst flood, as previously hypothesized, destroyed the Lajia Settlement.
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For the ecologically vulnerable Qinghai-Tibet Plateau (QTP), hypoxia is increasingly becoming an extremely important environmental risk factor that significantly affects the health of both humans and livestock in the plateau region, as well as hindering high-quality development. To focus on the problem of hypoxia, it is especially urgent to study the surface oxygen concentration (i.e., oxygen concentration). However, the existing research is not sufficient, and there is a lack of oxygen concentration data collected on the QTP. In this study, through the Second Tibetan Plateau Scientific Expedition and Research and field measurements, the oxygen concentration data and corresponding geographic environmental data were collected at 807 measurement points on the QTP from 2017 to 2022, and the spatiotemporal oxygen concentration patterns were estimated. This work filled the gaps in the measurement and research of oxygen concentrations on the QTP while providing data support for analyses of the influencing factors and spatiotemporal characteristics of oxygen concentrations, which is of great significance for promoting the construction of ecological civilization in the QTP region.