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Expansion microscopy (ExM) facilitates nanoscale imaging under conventional microscopes, but it frequently encounters challenges such as fluorescence losses, low signal-to-noise ratio (SNR), and limited detection throughput. To address these issues, a method of orthogonal DNA self-assembly-based ExM (o-DAExM) platform is developed, which employs hybridization chain reaction instead of conventional fluorescence labeling units, showcasing signal amplification efficacy, enhancement of SNR, and expandable multiplexing capability at any stage of the ExM process. In this work, o-DAExM has been applied to compare with immunofluorescence-based ExM for cellular cytoskeleton imaging, and the resolved nanoscale spatial distributions of cytoskeleton show outstanding performance and reliability of o-DAExM. Furthermore, the study demonstrates the utility of o-DAExM in accurately revealing exosome heterogeneous information and multiplexed analysis of protein targets in single cells, which provides infinite possibilities in super-resolution imaging of cells and other samples. Therefore, o-DAExM offers a straightforward expansion and signal labeling method, highlighting future prospects to study nanoscale structures and functional networks in biological systems.
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Color encoding plays a crucial role in painting, digital photography, and spectral analysis. Achieving accurate, target-responsive color encoding at the molecular level has the potential to revolutionize scientific research and technological innovation, but significant challenges persist. Here, we propose a multibit DNA self-assembly system based on computer-aided design (CAD) technology, enabling accurate, target-responsive, amplified color encoding at the molecular level, termed fluorescence encoding (FLUCO). As a model, we establish a quaternary FLUCO system using four-bit DNA self-assembly, which can accurately encode 51 colors, presenting immense potential in applications such as spatial proteomic imaging and multitarget analysis. Notably, FLUCO enables the simultaneous imaging of multiple targets exceeding the limitations of channels using conventional imaging equipment, and marks the integration of computer science for molecular encoding and decoding. Overall, our work paves the way for target-responsive, controllable molecular encoding, facilitating spatial omics analysis, exfoliated cell analysis, and high-throughput liquid biopsy.
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Climate change is increasing the frequency and intensity of heatwaves, raising concerns about their detrimental effects on air quality. However, a role for heatwave-human-environment interactions in air pollution exacerbation has not been established. In the summer of 2022, record-breaking heatwaves struck China and Europe. In this study, we use integrated observational data and machine learning to elucidate the formation mechanism underlying one of the most severe ozone pollution seasons on record in central eastern China, an area that encompasses approximately half of China's total population and sown land. Our findings reveal that the worsened ozone and nitrogen dioxide pollution resulted from a mismatch between energy demand and supply, which was driven by both heatwaves and energy policy-related factors. The observed adverse heatwave-energy-environment feedback loop highlights the need for the diversification of clean energy sources, more resilient energy structures and power policies, and further emission control to confront the escalating climate challenge in the future.
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Accurate and efficient molecular recognition plays a crucial role in the fields of molecular detection and diagnostics. Conventional trial-and-error-based molecular recognition approaches have always been challenged in distinguishing minimal differences between targets and non-targets, such as single nucleotide polymorphisms (SNPs) of oligonucleotides. To address these challenges, here, a novel concept of dynamic addressing analysis is proposed. In this concept, by dissecting the regions of the target and creating a corresponding recognizer, it is possible to eliminate the inaccuracy and inefficiency of recognition. To achieve this concept, a Dynamic Addressing Molecular Robot (DAMR), a DNA-based dynamic addressing device is developed which is capable of dynamically locating targets. DAMR is designed to first bind to the conserved region of the target while addressing the specific region dynamically until accurate recognition is achieved. DAMR has provided an approach for analyzing low-resolution targets and has been used for analyzing SNP of miR-196a2 in both cell and serum samples, which has opened new avenues for effective and efficient molecular recognition.
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In 2022, many Chinese cities experienced lockdowns and heatwaves. We analyzed ground and satellite data using machine learning to elucidate chemical and meteorological drivers of changes in O3 pollution in 27 major Chinese cities during lockdowns. We found that there was an increase in O3 concentrations in 23 out of 27 cities compared with the corresponding period in 2021. Random forest modeling indicates that emission reductions in transportation and other sectors, as well as the changes in meteorology, increased the level of O3 in most cities. In cities with over 80% transportation reductions and temperature fluctuations within -2 to 2 °C, the increases in O3 concentrations were mainly attributable to reductions in nitrogen oxide (NOx) emissions. In cities that experienced heatwaves and droughts, increases in the O3 concentrations were primarily driven by increases in temperature and volatile organic compound (VOC) emissions, and reductions in NOx concentrations from ground transport were offset by increases in emissions from coal-fired power generation. Despite 3-99% reduction in passenger volume, most cities remained VOC-limited during lockdowns. These findings demonstrate that to alleviate urban O3 pollution, it will be necessary to further reduce industrial emissions along with transportation sources and to take into account the climate penalty and the impact of heatwaves on O3 pollution.
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Functional imaging (FI) techniques have revolutionized tumor imaging by providing information on specific tumor functions, such as glycometabolism. However, tumor cells lack unique molecular characteristics at the molecular level and metabolic pathways, resulting in limited metabolic differences compared to normal cells and increased background signals from FI. To address this limitation, we developed a novel imaging technique termed proximity-enhanced functional imaging (PEFI) for accurate visualization of tumors. By using "two adjacent chemically labeled glycoproteins" as output signals, we significantly enhance the metabolic differences between tumor and normal cells by PEFI, thereby reducing the background signals for analysis and improving the accuracy of tumor functional imaging. Our results demonstrate that PEFI can accurately identify tumors at the cellular, tissue, and animal level, and has potential value in clinical identification and analysis of tumor cells and tissues, as well as in the guidance of clinical tumor resection surgery.
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Neoplasias Encefálicas , Diagnóstico por Imagen , AnimalesRESUMEN
Particulate organic nitrates (pONs) have drawn growing interests due to their effects on nitrogen cycling, air pollution, and regional climate. While secondary formation is typically considered as the major source of pONs, direct emissions from various sources remain poorly explored. Ship exhausts have been known as an important source of reactive nitrogen species, yet pONs emissions from ship have been rarely characterized. In this study, we conducted atmospheric measurement of pONs during a ship-based cruise measurement campaign in the East China Sea and also emission measurement of pONs from ship exhausts. During the ship-based cruise, total five typical kinds of pONs were determined and the average total concentrations of five pONs were 479 ± 193 and 250 ± 139 ng m-3 when sampling was influenced by ship emissions or not, respectively, indicating the notable impact of ship exhaust plumes on ambient pONs. Further, five typical pONs were successfully identified and quantified from ship exhausts, with the average total concentration of 1123 ± 406 µg m-3. The much higher pONs levels in ship exhausts than in ambient particulate matters demonstrated ship emission as an important source for pONs. Additionally, their emission factors from ship exhausts were determined as at a range of 0.1-12.6 mg kWh-1. The chemical transport model simulations indicate that direct pONs emissions from ship exert a significant contribution to atmospheric pONs, especially in the clean marine atmosphere. These findings provide compelling evidence for direct emission of pONs from ship and its considerable effects. We call for further studies to better characterize the direct pONs emissions from ship and other potential sources, which should be incorporated into global and regional models.
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Contaminantes Atmosféricos , Contaminación del Aire , Contaminantes Atmosféricos/análisis , Navíos , Monitoreo del Ambiente , Material Particulado/análisis , Contaminación del Aire/análisis , Emisiones de Vehículos/análisis , Polvo , Carbón Mineral , ChinaRESUMEN
Bioactive molecules are highly worthwhile to recognize and explore the latent pathogenic mechanism. Conventional methods for bioactive molecule detection, including mass spectrometry and fluorescent probe imaging, are limited due to the complex processing and signal interference. Here, we designed enzyme-reaction-assisted programmable transcriptional switches for the detection of bioactive molecules. The approach is based on the use of programmable enzyme site-specific cleavage-assisted DNA triplex-based conformational switches that, upon responding to bioactive molecules, can trigger the transcription of fluorescent light-up aptamers. Thanks to the programmable nature of the sensing platform, the method can be adapted to different bioactive molecules, and we demonstrated the enzyme-small molecule catalytic reaction combination of myeloperoxidase (MPO)-hydrogen peroxide (H2O2) as a model that transcriptional switches was capable of detecting H2O2 and possessed the specificity and anti-interference ability in vitro. Furthermore, we successfully applied the switches into cells to observe the detection feasibility in vivo, and dynamically monitored changes of H2O2 in cellular oxidative stress levels. Therefore, we attempt to amalgamate the advantages of enzyme reaction with the pluripotency of programmable transcriptional switches, which can take both fields a step further, which may promote the research of biostimuli and the construction of DNA molecular devices.
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ADN , Peróxido de Hidrógeno , ADN/química , Estrés Oxidativo , Conformación de Ácido Nucleico , Colorantes Fluorescentes/químicaRESUMEN
Gaseous nitrous acid (HONO) is a critical source of hydroxyl radicals (OH) in the troposphere. While both direct and secondary sources contribute to atmospheric HONO, direct emissions have traditionally been considered minor contributors. In this study, we developed δ15N and δ18O isotopic fingerprints to identify six direct HONO emission sources and conducted a 1-y case study on the isotopic composition of atmospheric HONO at rural and urban sites. Interestingly, we identified that livestock farming is a previously overlooked direct source of HONO and determined its HONO to ammonia (NH3) emission ratio. Additionally, our results revealed that spatial and temporal variations in atmospheric HONO isotopic composition can be partially attributed to direct emissions. Through a detailed HONO budget analysis incorporating agricultural sources, we found that direct HONO emissions accounted for 39~45% of HONO production in rural areas across different seasons. The findings were further confirmed by chemistry transport model simulations, highlighting the significance of direct HONO emissions and their impact on air quality in the North China Plain. These findings provide compelling evidence that direct HONO emissions play a more substantial role in contributing to atmospheric HONO than previously believed. Moreover, the δ15N and δ18O isotopic fingerprints developed in this study may serve as a valuable tool for further research on the atmospheric chemistry of reactive nitrogen gases.
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Nitrate (NO3-) is a major component of atmospheric fine particles. Recent studies in eastern China have shown the increasing trend of NO3- in contrast to the ongoing control of nitrogen oxide (NOx). Here, we elucidate the effects of reduced sulfur dioxide (SO2) on the enhancement of NO3- formation based on field measurements at the summit of Mt. Tai (1534 m a.s.l.) and present detailed modelling analyses. From 2007 to 2018, the measured springtime concentrations of various primary pollutants and fine sulfate (SO42-) decreased sharply (-16.4 % to -89.7 %), whereas fine NO3- concentration increased by 22.8 %. The elevated NO3- levels cannot be explained by the changes in meteorological conditions or other related parameters but were primarily attributed to the considerable reduction in SO42- concentrations (-73.4 %). Results from a multi-phase chemical box model indicated that the reduced SO42- levels decreased the aerosol acidity and prompted the partitioning of HNO3 into the aerosol phase. WRF-Chem model analyses suggest that such a negative effect is a regional phenomenon throughout the planetary boundary layer over eastern China in spring. This study provides new insights into the worsening situation of NO3- aerosol pollution and has important implications for controlling haze pollution in China.
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Artificial molecular machines have captured the imagination of researchers, given their clear potential to mimic and influence human life. Key to behavior simulation is to reproduce the specific properties of physical or abstract systems. Dice throwing, as a stochastic model, is commonly used for result judgment or plan decision in real life. In this perspective we utilize DNA cube framework for the design of a dice device at the nanoscale to reproduce probabilistic events in different situations: equal probability, high probability, and low probability. We first discuss the randomness of DNA cube, or dice, adsorbing on graphene oxide, or table, and then explore a series of events that change the probability through the way in which the energy released from entropy-driven strand displacement reactions or changes in intermolecular forces. As such, the DNA nano-dice system provides guideline and possibilities for the design, engineering, and quantification of behavioral probability simulation, a currently emerging area of molecular simulation research.
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ADN , Juicio , Humanos , Probabilidad , Simulación por Computador , ImaginaciónRESUMEN
Surface ozone pollution has become the biggest issue in China's air pollution since particulate matters have been improved in the atmosphere. Compared with normal winter/summer, extremely cold/hot weather sustained several days and nights by unfavorable meteorology is more impactful in this regard. However, ozone changes in extreme temperatures and their driving processes remain rarely understood. Here, we combine comprehensive observational data analysis and 0-D box models to quantify the contributions of different chemical processes and precursors to ozone change in these unique environments. Analyses of radical cycling indicate that temperature accelerates OH-HO2-RO2, optimizing ozone production efficiency in higher temperatures. The HO2 + NO â OH + NO2 reaction was the most influenced by temperature change, followed by OH + VOCs â HO2/RO2. Although most reactions in ozone formation increased with temperature, the increase in ozone production rates was greater than the rate of ozone loss, leading to a fast net ozone accumulation in heat waves. Our results also show that the ozone sensitivity regime is VOC-limited in extreme temperatures, highlighting the significance of volatile organic compound (VOC) control (particularly the control of alkenes and aromatics). In the context of global warming and climate change, this study helps us deeply understand ozone formation in extreme environments and design abatement policies for ozone pollution in such conditions.
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Cardiovascular disease (CVD), a type of circulatory system disease related to the lesions of the cardiovascular system, has become one of the main diseases that endanger human health. Currently, the clinical diagnosis of most CVDs relies on a combination of imaging technology and blood biochemical test. However, the existing technologies for diagnosis of CVDs still have limitations in terms of specificity, detection range, and cost. In order to break through the current bottleneck, microfluidic with the advantages of low cost, simple instruments and easy integration, has been developed to play an important role in the early prevention, diagnosis and treatment of CVDs. Here, we have reviewed the recent various applications of microfluidic in the clinical diagnosis and treatment of CVDs, including microfluidic devices for detecting CVD markers, the cardiovascular models based on microfluidic, and the microfluidic used for CVDs drug screening and delivery. In addition, we have briefly looked forward to the prospects and challenges of microfluidics in diagnosis and treatment of CVDs.
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Enfermedades Cardiovasculares , Microfluídica , Humanos , Microfluídica/métodos , Enfermedades Cardiovasculares/diagnóstico , Enfermedades Cardiovasculares/tratamiento farmacológico , Dispositivos Laboratorio en un ChipRESUMEN
Volatile organic compounds (VOCs) management has been recently given a high priority in China to mitigate ozone (O3) air pollution. However, there is a relatively poor understanding of VOCs due to their complexity and fewer observations. To better understand the pollution characteristics of VOCs and their impact on O3 pollution, two-year continuous measurements were conducted at four representative sites in Ji'nan, eastern China. These four sites cover urban, background, and industrial areas (within a petroleum refinery). Ambient VOCs showed higher concentrations at industrial site than at urban and background sites, owing to intensive emissions from petrochemical industry. The VOCs compositions present spatial heterogeneity with alkenes dominated in total reactivity at urban and background sites, while alkenes and aromatics together dominated at industrial site. The VOCs emission profile from petrochemical industry was calculated based on observational data, which revealed a huge impact on light alkanes (C2-C5), light alkenes (ethene), and aromatics (toluene and m/p-xylene). The positive matrix factorization (PMF) model analysis further refined the impact of different petrochemical industrial processes. Alkanes and alkenes dominated the emissions during refining process, while aromatics dominated during solvent usage process. Analysis by an observation-based model indicated stronger in-situ O3 production and higher sensitivity to nitrogen oxides at industrial site compared to urban and background sites. The reduction of VOCs emissions from petrochemical industry would significantly reduce the O3 concentrations. The analyses underline the significant impact of petrochemical industry on VOCs and O3 pollution, and provide important reference for the formulation of refined and effective control strategies.
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Ciudades , Monitoreo del Ambiente , Compuestos Orgánicos Volátiles , ChinaRESUMEN
Ozone (O3) pollution has emerged as a major air quality issue in China. Here we emphasize the great challenges in controlling O3 pollution by analyzing the recent experience of the Pearl River Delta (PRD) in southern China in reducing the autumn O3 peaks. Despite significant reductions in the concentration of O3 precursors, i.e., nitrogen oxides (NOx) and volatile organic compounds (VOCs), regional O3 pollution in the PRD was largely worse in autumn 2019 than in autumn 2018. We found that the supra-regional and regional background concentrations of O3 increased significantly in the PRD in autumn 2019 due to increased concentrations of O3 in the vast surrounding areas. We also observed slight increases in the concentrations of PRD-regionally and Guangzhou-locally produced O3. A chemical box-model analysis confirmed a slight increase in the in-situ production of O3 and revealed that increased biogenic VOCs (BVOCs) and decreased NOx levels negated the effect of significant decrease in the anthropogenic VOCs. Taken together, these aspects exacerbated O3 pollution in the PRD region in autumn 2019 relative to autumn 2018. The findings from this study highlight the strong interactions of O3 pollution over multiple regions and the need for collaborative inter-regional efforts to control O3 pollution. The experience of PRD also underlines the key role of BVOCs and the importance of science-based strategies to decrease VOCs and NOx.
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Contaminantes Atmosféricos , Contaminación del Aire , Ozono , Compuestos Orgánicos Volátiles , Ozono/análisis , Compuestos Orgánicos Volátiles/análisis , Contaminantes Atmosféricos/análisis , Monitoreo del Ambiente , Contaminación del Aire/análisis , Políticas , ChinaRESUMEN
Although various nanomaterials have been designed as intracellular delivery tools, the following aspects have become obstacles to limit their development, like a complex and time-consuming synthesis process, as well as relatively limited application areas (i.e. biosensing or cell imaging). Here, we developed a novel nano-delivery system called "nano-sperm" with low cytotoxicity and high biocompatibility. In this system, we used DNA oligonucleotides as a backbone to synthesize a nanostructure with silver nanoclusters in the head and functional fragments in the tail, which is shaped like a sperm, to achieve dual functions of ultrafast delivery and imaging/therapy. As a model, we analyzed the possibility of the "nano-sperm" carrying DNA with different structures for imaging or survivin-asDNA for tumor therapy. Therefore, this work reports a novel bifunctional high-speed delivery vehicle, which successfully fills the gap in the field of tumor therapy using DNA-templated nanoclusters as a delivery vehicle.
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Nanopartículas del Metal , Nanoestructuras , Neoplasias , ADN/química , ADN sin Sentido , Humanos , Nanopartículas del Metal/química , Nanoestructuras/química , Plata/químicaRESUMEN
Coal is well known as the primary energy consumption in China, and the coal chemical industry (CCI) can serve as an important source of volatile organic compounds (VOCs) emissions. However, the characteristics of VOCs emitted from CCI along with their environmental consequences are still poorly understood. To pin down this, an intensive field campaign was carried out at a typical CCI city in northwestern China (Yulin) from February 26 to March 7, 2021. Results showed that VOC compositions in Yulin were distinct from those in the megacities of China as well as in the typical oilfields over the world. The concentration of naphthalene (1.6 ± 1.1 ppbv), an important byproduct of CCI, was significantly higher than that in other cities (<0.2 ppbv). Positive matrix factorization (PMF) model analysis revealed that the direct contribution of the CCI source for VOC emissions is 8.8 ± 1.8%. More importantly, these VOCs emitted from the CCI can account for 17.9 ± 6.8% of ozone (O3) formation potential and 16.9 ± 7.4% of OH reactivity of VOCs, suggesting the significant impacts of the CCI on the air quality and atmospheric oxidizing capacity. During the observation, a rapid increase in O3 concentration after a snowfall was encountered. The changing rate of O3 concentration in the daytime was significantly higher than in its peripheral cities. The increased O3 formation was partially attributed to the CCI, and this enhancement can be further magnified by snow cover due to the increment of surface albedo. These findings deepen the understanding of the characteristics and air quality impact of VOCs related to the CCI and provide valuable insights for the development of air quality control measures in the region influenced by intensive coal chemical production.
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Contaminantes Atmosféricos , Ozono , Compuestos Orgánicos Volátiles , Contaminantes Atmosféricos/análisis , Industria Química , China , Ciudades , Carbón Mineral/análisis , Monitoreo del Ambiente/métodos , Ozono/análisis , Emisiones de Vehículos/análisis , Compuestos Orgánicos Volátiles/análisisRESUMEN
Immunofluorescence imaging of cells plays a vital role in biomedical research and clinical diagnosis. However, when it is applied to relative quantification of proteins, it suffers from insufficient fluorescence intensity or partial overexposure, resulting in inaccurate relative quantification. Herein, we report a computer-aided design of DNA self-limited assembly (CAD-SLA) technology and apply it for relative quantification of membrane proteins, a concept proposed for the first time. CAD-SLA can achieve exponential cascade signal amplification in one pot and terminate at any desired level. By conjugating CAD-SLA with immunofluorescence, in situ imaging of cell membrane proteins is achieved with a controllable amplification level. Besides, comprehensive fluorescence intensity information from fluorescent images can be obtained, accurately showing relative quantitative information. Slight protein expression differences previously indistinguishable by immunofluorescence or Western blotting can now be discriminated, making fluorescence imaging-based relative quantification a promising tool for membrane protein analysis. From the perspectives of both DNA self-assembly technology and immunofluorescence technology, this work has solved difficult problems and provided important reference for future development.