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In recent years, DNA origami-based nanocarriers have been extensively utilized for efficient cancer therapy. However, developing a nanocarrier capable of effectively protecting cargos such as RNA remains a challenge. In this study, we designed a compact and controllable DNA tubular origami (DTO) measuring 120 nm in length and 18 nm in width. The DTO exhibited appropriate structural characteristics for encapsulating and safeguarding cargo. Inside the DTO, we incorporated 20 connecting points to facilitate the delivery of cargoes to various ovarian and normal epithelial cell lines. Specifically, fluorescent-labeled DNA strands were attached to these sites as cargoes. The DTO was engineered to open upon encountering miR-21 through RNA/DNA strand displacement. Significantly, for the first time, we inhibited fluorescence using the compact DNA nanotube and observed dynamic fluorescent signals, indicating the controllable opening of DTO through live-cell imaging. Our results demonstrated that the DTO remained properly closed, exhibited effective internalization in ovarian cancer cells in vitro, showcasing marked differential expression of miR-21, and efficiently opened with short-term exposure to miR-21. Leveraging its autonomous behavior and compact design, the DTO emerges as a promising nanocarrier for various clinically relevant materials. It holds significant application prospects in anti-cancer therapy and the development of flexible biosensors.

Oceanic biogenic emissions exert a significant impact on the atmospheric environment within the marine boundary layer (MBL). This study employs the extreme gradient boosting (XGBoost) machine learning method and clustering method combined with satellite observations and model simulations to discuss the effects of marine biogenic emissions on MBL formaldehyde (HCHO). The study reveals that HCHO columnar concentrations peaked in summer with 8.25 × 1015 molec/cm2, but the sea–air exchange processes controlled under the wind and sea surface temperature (SST) made marine biogenic emissions represented by isoprene reach their highest levels in winter with 95.93 nmol/m2/day. Analysis was conducted separately for factors influencing marine biogenic emissions and affecting MBL HCHO. It was found that phytoplankton functional types (PFTs) and biological degradation had a significant impact on marine biogenic emissions, with ratio range of 0.07~15.87 and 1.02~5.42 respectively. Machine learning methods were employed to simulate the conversion process of marine biogenic emissions to HCHO in MBL. Based on the SHAP values of the learning model, the importance results indicate that the factors influencing MBL HCHO mainly included NO2, as well as temperature (T) and relative humidity (RH). Specifically, the influence of NO2 on atmospheric HCHO was 1.3 times that of T and 1.6 times that of RH. Wind speed affected HCHO by influencing both marine biogenic emission and the atmospheric physical conditions. Increased marine biogenic emissions in air masses heavily influenced by human activities can reduce HCHO levels to some extent. However, in areas less affected by human activities, marine biogenic emissions can lead to higher levels of HCHO pollution. This research explores the impact of marine biogenic emissions on the HCHO status of the MBL under different atmospheric chemical conditions, offering significant insights into understanding chemical processes in marine atmospheres.

Nucleolin protein expression is higher on the ovarian cancer cell surface. AS1411, a DNA aptamer, can bind with nucleolin protein specifically. In this study, we developed HA and ST DNA tiles to assemble six AS1411 aptamers to deliver doxorubicin. In addition, to superior serum stability and drug loading, HA-6AS and ST-6AS outperformed TDN-AS in cellular uptake. HA-6AS and ST-6AS exhibited satisfactory targeted cytotoxicity and achieved resounding lysosomal escape. Moreover, when injected into nude mice subcutaneous xenograft models, HA-6AS reached the peak in tumor more quickly than ST-6AS, and better expressed the active targeting ability of AS1411. Our study suggests that designing appropriate DNA tiles to assemble different aptamers to deliver different chemotherapeutic drugs is a promising treatment for ovarian cancer.

Atmospheric ammonia (NH _3 ) plays a significant role in the nitrogen cycle, and can have impacts on air quality, ecological balance and climate change. While NH _3 associated with natural and agricultural processes has long been considered the primary source, the contribution of combustion-related NH _3 , particularly from vehicular emissions, keeps on the rise. We found that high on-road NH _3 concentrations occurred in a metropolitan city based on mobile measurement, and inferred that urban vehicular NH _3 emission was likely underestimated in the past. NH _3 emission factors (EFs) were derived from ring roads and tunnels, showing levels 74% and 20% higher than the latest standard proposed by Euro VII, respectively. To quantify the underestimation, two methods based on car ownership and traffic flow were used to estimate the annual vehicular NH _3 emission in Shanghai as 2.59 and 1.76 Gg, respectively, substantially surpassing the predicted results by the Dynamic Projection model for Emissions in China. Given these discoveries, we recommend that it is urgent and imperative to establish relevant national standards and limits aiming at regulation on vehicular NH _3 emissions. And more representative EFs measurements should be adopted to improve the accuracy of inventory estimation.

An unprecedented city-wide lockdown took place in Shanghai from April to May 2022 to curb the spread of COVID-19, which caused socio-economic disruption but a significant reduction of anthropogenic emissions in this metropolis. However, the ground-based monitoring data showed that the concentration of ozone (O3) remained at a high level. This study applied Tropospheric Monitoring Instrument (TROPOMI) observations to examine changes in tropospheric vertical column density (VCD) of nitrogen dioxide (NO2) and formaldehyde (HCHO), which are precursors of O3. Compared with the same period in 2019–2021, VCDs of NO2 and HCHO decreased respectively by ~50% and ~20%. Multiple regression analysis showed that the lockdown effect played a dominant role in this dramatic decline rather than meteorological impacts. Using the exponentially-modified Gaussian method, this study quantified nitrogen oxides (NOX) emission in Shanghai as 32.60 mol/s with a decrease of 50–80%, which was mainly contributed by the transportation and industrial sectors. The significant reduction of NOX emission in Shanghai is much higher than that of volatile organic compounds (VOCs), which led to dramatic changes in formaldehyde-to-nitrogen dioxide ratio (HCHO/NO2, FNR). Thus, when enforcing regulation on NOx emission control in the future, coordinately reducing VOCs emission should be implemented to mitigate urban O3 pollution.

The long-path differential optical absorption spectroscopy (LP-DOAS) technique was deployed in Shanghai to continuously monitor ozone (O3), formaldehyde (HCHO), nitrogen dioxide (NO2), nitrous acid (HONO), and nitrate radical (NO3) mixing ratios from September 2019 to August 2020. Through a clustering method, four typical clusters of the O3 diurnal pattern were identified: high during both the daytime and nighttime (cluster 1), high during the nighttime but low during the daytime (cluster 2), low during both the daytime and nighttime (cluster 3), and low during the nighttime but high during the daytime (cluster 4). The drivers of O3 variation for the four clusters were investigated for the day- and nighttime. Ambient NO caused the O3 gap after midnight between clusters 1 and 2 and clusters 3 and 4. During the daytime, vigorous O3 generation (clusters 1 and 4) was found to accompany higher temperature, lower humidity, lower wind speed, and higher radiation. Moreover, O3 concentration correlated with HCHO for all clusters except for the low O3 cluster 3, while O3 correlated with HCHO/NOx, but anti-correlated with NOx for all clusters. The lower boundary layer height before midnight hindered O3 diffusion and accordingly determined the final O3 accumulation over the daily cycle for clusters 1 and 4. The interactions between the O3 diel profile and other atmospheric reactive components established that higher HONO before sunrise significantly promoted daytime O3 generation, while higher daytime O3 led to a higher nighttime NO3 level. This paper summarizes the interplays between day- and nighttime oxidants and oxidation products, particularly the cause and effect for daytime O3 generation from the perspective of nighttime atmospheric components.

During the period of April and May 2022, Shanghai implemented city-wide static management measures to control the spread of the Omicron variant. Compared to the lockdown in early 2020, the static management in 2022 occurred during the high-ozone season and lasted for a longer duration. It can be considered as a "large-scale field experiment" to study the response of ambient ozone levels to emission reductions. During this period, we conducted comprehensive observations at Fudan University Jiangwan Campus in the northeast corner of Shanghai. Similar experiments were also conducted during the same period in 2020 and 2021. Despite the significant reduction of approximately 30% in VOCs and around 50% in NO2 due to static management in 2022, the average ozone level increased by nearly 23%. This suggests that the reduction in ozone precursors and other pollutants did not lead to a corresponding decrease in ozone concentrations as expected. Cluster analysis of diurnal patterns of ozone concentration revealed four distinct types of diurnal ozone variations. Cluster 3 and Cluster 4, with high ozone levels, experienced significant increases in their share during static management, ultimately leading to an overall increase in average ozone levels in 2022. According to the Observation-Based Model (OBM) simulation analysis, the average peak concentrations of OH, HO2, and RO2 in 2022 were estimated to be 5.3 × 106, 4.9 × 108, and 2.6 × 108 molecules cm-3, respectively, representing an increase of over 30% compared to the levels in 2020 and 2021. Although HONO photolysis was the main contributor to the primary source of ROx radicals, the radical cycling process remained dominant for the overall production of ROx radicals. Due to a significant decrease in NO2 concentration relative to VOCs, the average VOCs/NO2 ratio increased from 1.6 in 2020 to 3.0 in 2022, which is also reflected in the radical cycling. The ratio of OH radical propagation (OH+VOCs) to termination (OH+NO2) was 2.10, higher than 1.03 in 2020 and 1.60 in 2021, indicating that the different reduction proportions of precursors led to a higher VOCs/NO2 ratio, strengthening the radical cycling. The differential reduction in precursor VOCs and NO2 levels due to static management is the underlying cause for the increase in ozone concentration in Shanghai. [ABSTRACT FROM AUTHOR]

In light of the high bit error rate in satellite network links, the traditional transmission control protocol (TCP) fails to distinguish between congestion and wireless losses, and existing loss differentiation methods lack heterogeneous ensemble learning models, especially feature selection for loss differentiation, individual classifier selection methods, effective ensemble strategies, etc. A loss differentiation method based on heterogeneous ensemble learning (LDM-HEL) for low-Earth-orbit (LEO) satellite networks is proposed. This method utilizes the Relief and mutual information algorithms for selecting loss differentiation features and employs the least-squares support vector machine, decision tree, logistic regression, and K-nearest neighbor as individual learners. An ensemble strategy is designed using the stochastic gradient descent method to optimize the weights of individual learners. Simulation results demonstrate that the proposed LDM-HEL achieves higher accuracy rate, recall rate, and F1-score in the simulation scenario, and significantly improves throughput performance when applied to TCP. Compared with the integrated model LDM-satellite, the above indexes can be improved by 4.37%, 4.55%, 4.87%, and 9.28%, respectively.

Low-Earth orbit (LEO) satellites have limited on-board resources, user terminals are unevenly distributed in the constantly changing coverage area, and the service requirements vary significantly. It is urgent to optimize resource allocation under the constraint of limited satellite spectrum resources and ensure the fairness of service admission control. Therefore, we propose an intelligent hierarchical admission control (IHAC) strategy based on deep reinforcement learning (DRL). This strategy combines the deep deterministic policy gradient (DDPG) and the deep Q network (DQN) intelligent algorithm to construct upper and lower hierarchical resource allocation and admission control frameworks. The upper controller considers the state features of each ground zone and satellite resources from a global perspective, and determines the beam resource allocation ratio of each ground zone. The lower controller formulates the admission control policy based on the decision of the upper controller and the detailed information of the users’ services. At the same time, a designed reward and punishment mechanism is used to optimize the decisions of the upper and lower controllers. The fairness of users’ services admissions in each ground zone is achieved as far as possible while ensuring the reasonable allocation of beam resources among zones. Finally, online decision-making and offline learning were combined, so that the controller could make full use of a large number of historical data to learn and generate intelligent strategies with stronger adaptive ability while interacting with the network environment in real time. A large number of simulation results show that IHAC has better performance in terms of a successful service admission rate, service drop rate, and fair resource allocation. Among them, the number of accepted services increased by 20.36% on average, the packet loss rate decreased by 17.56% on average, and the resource fairness increased by 17.16% on average.

Purpose Three-dimensional (3D) scans with flat detector angiographic systems are widely used for neurointerventions by providing detailed vascular information. However, its associated radiation dose and streak metal artifact generated by implanted treatment devices remain issues. This work evaluates the feasibility and clinical value of volume of interest imaging combined with metal artifact reduction (V0I+MAR) to generate high quality 3D images with reduced radiation dose and metal artifacts. Material and methods Full volume (FV) and VOI scans were acquired in 25 patients with intracranial aneurysms and treated with either endovascular coiling (n=9) or stent assisted coiling (n=16) procedures. FV and VOI scans were reconstructed with conventional syngo DynaCT and VOI +MAR prototype software, respectively. Results Quantitative evaluation results demonstrated that compared with standard FV syngo DynaCT images, overall image quality was improved in the VOI+MAR reconstructed images, with streak metal artifacts considerably reduced or even removed; details of soft tissue in the vicinity of the metal devices was well preserved or recovered in the majority of cases. Radiation dose to patients calculated by dose area product was found to be significantly reduced using VOI scans. Conclusion This study confirmed the feasibility of using VOI+MAR prototype software to achieve high image quality of a small volume of clinical interest and to reduce radiation dose. This technique has potential to improve patient safety and treatment outcomes. [ABSTRACT FROM AUTHOR]

Aim To evaluate the accuracy of three-dimensional (3D) images from two modalities--CT angiography (CTA) and digital subtraction angiography (DSA). Additionally, to explore the value of using preprocedural CTA for real-time guidance during neurointerventional procedures. Materials and methods 25 patients with CTA-confirmed cerebral arterial lesions were enrolled. For 12 of these patients, 3D DSA images of the contrast medium-enhanced target vessel were acquired during the intervention and registered with the preprocedurally acquired CTA images for evaluation of the accuracy of image fusion, focusing on the target vessel and the lesion. For the other 13 patients, a low-dose noncontrast 3D angiographic scan was performed. The preprocedurally acquired CTA image was then registered with the coordinate of angiography and overlaid onto the live fluoroscopic image to provide interventional guidance. Results Based on visual inspection by two experienced physicians and quantitative evaluation, excellent accuracy in the 3D registration of the CTA and DSA was achieved for all 12 patients examined. Additionally, CTA could be used successfully to guide the interventional procedures, including both diagnostic DSA and stent treatment. The radiation dose and contrast medium use were compared with those used by conventional interventional procedures and both were found to be significantly reduced. Conclusions 3D CTA and angiographic image fusion was approved as highly accurate for neurovasculature. Additionally, using the fusion technique to guide interventional procedures enhanced the workflow, and required much less radiation exposure and contrast medium use, thus helping to reduce potential risks and increase treatment safety. [ABSTRACT FROM AUTHOR]