Engineering Modular DNA Reaction Networks for Signal Processing.

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.

A DNA Finite-State Machine Based on the Programmable Allosteric Strategy of DNAzyme.

Living organisms can produce corresponding functions by responding to external and internal stimuli, and this irritability plays a pivotal role in nature. Inspired by such natural temporal responses, the development and design of nanodevices with the ability to process time-related information could facilitate the development of molecular information processing systems. Here, we proposed a DNA finite-state machine that can dynamically respond to sequential stimuli signals. To build this state machine, a programmable allosteric strategy of DNAzyme was developed. This strategy performs the programmable control of DNAzyme conformation using a reconfigurable DNA hairpin. Based on this strategy, we first implemented a finite-state machine with two states. Through the modular design of the strategy, we further realized the finite-state machine with five states. The DNA finite-state machine endows molecular information systems with the ability of reversible logic control and order detection, which can be extended to more complex DNA computing and nanomachines to promote the development of dynamic nanotechnology.

Spatial Vulnerability of Network Systems under Spatially Local Hazards.

A hazard is often spatially local in a network system, but its impact can spread out through network topology and become global. To qualitatively and quantitatively assess the impact of spatially local hazards on network systems, this article develops a new spatial vulnerability model by taking into account hazard location, area covered by hazard, and impact of hazard (including direct impact and indirect impact), and proposes an absolute spatial vulnerability index (ASVI) and a relative spatial vulnerability index (RSVI). The relationship between the new model and some relevant traditional network properties is also analyzed. A case study on the spatial vulnerability of the Chinese civil aviation network system is conducted to demonstrate the effectiveness of the model, and another case study on the Beijing subway network system to verify its relationship with traditional network properties.

How earthquake-induced direct economic losses change with earthquake magnitude, asset value, residential building structural type and physical environment: An elasticity perspective.

Diagnosing all components of risk is essential in earthquake loss attribution science, but quantitative estimates on how sensitive the earthquake-induced direct economic losses (DELs) are to changes in hazard, exposure and vulnerability is rarely known. Here the relationship between earthquake DELs and earthquake magnitude (Ms), asset value exposure (K), proportion of non-steel-concrete residential buildings (H) and physical environment instability (E) is quantified using the concept of economic elasticity. Earthquake disaster event-based DEL records over the period from 1990 to 2016 for the mainland of China are fitted to a regression model. Elasticity values for Ms, K, H and E are 7.63, 0.75, 4.92 and 0.91, respectively, indicating that on average, DEL changes are more sensitive to changes in Ms and H-a 13% increase in Ms or a 20% increase in H would double earthquake DELs, while it may take a 133% increase in K or a 110% increase in E to cause the same economic losses. In turn, this suggests that human factors-decreasing H and K-could be efficient ways to reduce earthquake risk, while these two factors will become increasingly relevant for risk assessment in the future with continued economic growth. The elasticity estimate results could be used for studying future change in earthquake risks and for supporting disaster risk reduction strategies.

Development of an Asset Value Map for Disaster Risk Assessment in China by Spatial Disaggregation Using Ancillary Remote Sensing Data.

The extent of economic losses due to a natural hazard and disaster depends largely on the spatial distribution of asset values in relation to the hazard intensity distribution within the affected area. Given that statistical data on asset value are collected by administrative units in China, generating spatially explicit asset exposure maps remains a key challenge for rapid postdisaster economic loss assessment. The goal of this study is to introduce a top-down (or downscaling) approach to disaggregate administrative-unit level asset value to grid-cell level. To do so, finding the highly correlated "surrogate" indicators is the key. A combination of three data sets-nighttime light grid, LandScan population grid, and road density grid, is used as ancillary asset density distribution information for spatializing the asset value. As a result, a high spatial resolution asset value map of China for 2015 is generated. The spatial data set contains aggregated economic value at risk at 30 arc-second spatial resolution. Accuracy of the spatial disaggregation reflects redistribution errors introduced by the disaggregation process as well as errors from the original ancillary data sets. The overall accuracy of the results proves to be promising. The example of using the developed disaggregated asset value map in exposure assessment of watersheds demonstrates that the data set offers immense analytical flexibility for overlay analysis according to the hazard extent. This product will help current efforts to analyze spatial characteristics of exposure and to uncover the contributions of both physical and social drivers of natural hazard and disaster across space and time.

Developed and developing world responsibilities for historical climate change and CO2 mitigation.

At the United Nations Framework Convention on Climate Change Conference in Cancun, in November 2010, the Heads of State reached an agreement on the aim of limiting the global temperature rise to 2 °C relative to preindustrial levels. They recognized that long-term future warming is primarily constrained by cumulative anthropogenic greenhouse gas emissions, that deep cuts in global emissions are required, and that action based on equity must be taken to meet this objective. However, negotiations on emission reduction among countries are increasingly fraught with difficulty, partly because of arguments about the responsibility for the ongoing temperature rise. Simulations with two earth-system models (NCAR/CESM and BNU-ESM) demonstrate that developed countries had contributed about 60-80%, developing countries about 20-40%, to the global temperature rise, upper ocean warming, and sea-ice reduction by 2005. Enacting pledges made at Cancun with continuation to 2100 leads to a reduction in global temperature rise relative to business as usual with a 1/3-2/3 (CESM 33-67%, BNU-ESM 35-65%) contribution from developed and developing countries, respectively. To prevent a temperature rise by 2 °C or more in 2100, it is necessary to fill the gap with more ambitious mitigation efforts.

Local spatial and temporal factors influencing population and societal vulnerability to natural disasters.

The identification of societal vulnerable counties and regions and the factors contributing to social vulnerability are crucial for effective disaster risk management. Significant advances have been made in the study of social vulnerability over the past two decades, but we still know little regarding China's societal vulnerability profiles, especially at the county level. This study investigates the county-level spatial and temporal patterns in social vulnerability in China from 1980 to 2010. Based on China's four most recent population censuses of 2,361 counties and their corresponding socioeconomic data, a social vulnerability index for each county was created using factor analysis. Exploratory spatial data analysis, including global and local autocorrelations, was applied to reveal the spatial patterns of county-level social vulnerability. The results demonstrate that the dynamic characteristics of China's county-level social vulnerability are notably distinct, and the dominant contributors to societal vulnerability for all of the years studied were rural character, development (urbanization), and economic status. The spatial clustering patterns of social vulnerability to natural disasters in China exhibited a gathering-scattering-gathering pattern over time. Further investigations indicate that many counties in the eastern coastal area of China are experiencing a detectable increase in social vulnerability, whereas the societal vulnerability of many counties in the western and northern areas of China has significantly decreased over the past three decades. These findings will provide policymakers with a sound scientific basis for disaster prevention and mitigation decisions.

Collaborative modelling-based shelter planning analysis: a case study of the Nagata Elementary School Community in Kobe City, Japan.

This study, based on a questionnaire survey and workshops, and with a focus on the impact of an earthquake on the Nagata Elementary School Community in Kobe City, Japan, develops a collaborative model to assess the allocation of residents to shelters. The current official allocation plan is compared with three alternative allocations developed within the framework of this model. The collaborative model identifies accessibility, amenity, capacity, connectivity, continuity, security, and stability as the basic, necessary criteria for shelter planning. The three alternative allocations are very similar to the local residents' own choice of shelters, but they are quite different from the current official allocation plan, which is supposed to be followed but has achieved relatively low satisfaction among households. The proposed collaborative approach provides an effective tool to assess the officially determined allocation plan by taking into account the viewpoints of local residents, and the results are useful for enhancing community evacuation planning.

The Inverted U-Shaped Relationship Between Socio-Economic Status and Infections During the COVID-19 Pandemic.

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.

Bubble DNA tweezer: A triple-conformation sensor responsive to concentration-ratios.

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.

Substantially reducing global PM2.5-related deaths under SDG3.9 requires better air pollution control and healthcare.

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.

Recent Jishishan earthquake ripple hazard provides a new explanation for the destruction of the prehistoric Lajia Settlement 4000a B.P.

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.

Programming DNA Reaction Networks Using Allosteric DNA Hairpins.

The construction of DNA reaction networks with complex functions using various methods has been an important research topic in recent years. Whether the DNA reaction network can perform complex tasks and be recycled directly affects the performance of the reaction network. Therefore, it is very important to design and implement a DNA reaction network capable of multiple tasks and reversible regulation. In this paper, the hairpin allosteric method was used to complete the assembly task of different functional nucleic acids. In addition, information conversion of the network was realized. In this network, multiple hairpins were assembled into nucleic acid structures with different functions to achieve different output information through the cyclic use of trigger strands. A method of single-input dual-output information conversion was proposed. Finally, the network with signal amplification and reversible regulation was constructed. In this study, the reversible regulation of different functional nucleic acids in the same network was realized, which shows the potential of this network in terms of programmability and provides new ideas for constructing complex and multifunctional DNA reaction networks.

Construction of DNA-based molecular circuits using normally open and normally closed switches driven by lambda exonuclease.

Building synthetic molecular circuits is an important way to realize ion detection, information processing, and molecular computing. However, it is still challenging to implement the NOT logic controlled by a single molecule input in synthetic molecular circuits wherein the presence or absence of the molecule represents the ON or OFF state of the input. Here, based on lambda exonuclease (λ exo), for the first time, we propose the normally open (NO) and normally closed (NC) switching strategy with a unified signal transmission mechanism to build molecular circuits. Specifically, the opposite logic can be output with or without a single signal, and the state of the switch can be adjusted by the addition order and time interval of the upstream signal and switch signal, which endows the switch with time-responsive characteristics. In addition, a time-delay relay with the function of delayed disconnection is developed to realize quantitative control of outputs, which has the potential to meet the automation control need of the system. Finally, digital square and square root circuits are constructed by cascading the NO and NC switches, which demonstrates the versatility of switches. Our design can be extended to time logic and complex digital computing circuits for use in information processing and nanomachines.

Reconfigurable DNA triplex structure for pH responsive logic gates.

The DNA triplex is a special DNA structure often used as a logic gate substrate due to its high stability, programmability, and pH responsiveness. However, multiple triplex structures with different C-G-C+ proportions must be introduced into existing triplex logic gates due to the numerous logic calculations involved. This requirement complicates circuit design and results in many reaction by-products, greatly restricting the construction of large-scale logic circuits. Thus, we designed a new reconfigurable DNA triplex structure (RDTS) and constructed the pH-responsive logic gates through its conformational change that uses two types of logic calculations, 'AND' and 'OR'. The use of these logic calculations necessitates fewer substrates, further enhancing the extensibility of the logic circuit. This result is expected to promote the development of the triplex in molecular computing and facilitate the completion of large-scale computing networks.

Biomolecule-Driven Two-Factor Authentication Strategy for Access Control of Molecular Devices.

The rise of DNA nanotechnology is promoting the development of molecular security devices and marking an essential change in information security technology, to one that can resist the threats resulting from the increase in computing power, brute force attempts, and quantum computing. However, developing a secure and reliable access control strategy to guarantee the confidentiality of molecular security devices is still a challenge. Here, a biomolecule-driven two-factor authentication strategy for access control of molecular devices is developed. Importantly, the two-factor is realized by applying the specificity and nicking properties of the nicking enzyme and the programmable design of the DNA sequence, endowing it with the characteristic of a one-time password. To demonstrate the feasibility of this strategy, an access control module is designed and integrated to further construct a role-based molecular access control device. By constructing a command library composed of three commands (Ca, Cb, Ca and Cb), the authorized access of three roles in the molecular device is realized, in which the command Ca corresponds to the authorization of role A, Cb corresponds to the authorization of role B, and Ca and Cb corresponds to the authorization of role C. In this way, when users access the device, they not only need the correct factor but also need to apply for role authorization in advance to obtain secret information. This strategy provides a highly robust method for the research on access control of molecular devices and lays the foundation for research on the next generation of information security.

Surface oxygen concentration on the Qinghai-Tibet Plateau (2017-2022).

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.