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The spread of the COVID-19 since the end of 2019 has reached an epidemic level and has quickly become a global public health crisis. During this period, the responses for COVID-19 were highly diverse and decentralized across countries and regions. Understanding the dynamics of human mobility change at high spatial temporal resolution is critical for assessing the impacts of non-pharmaceutical interventions (such as stay-at-home orders, regional lockdowns and travel restrictions) during the pandemic. However, this requires collecting traffic data at scale, which is time-consuming, cost-prohibitive and often not available (e.g., in underdeveloped countries). Therefore, spatiotemporal analysis through processing periodical remote-sensing images is very beneficial to enable efficient monitoring at the global scale. In this paper, we present a novel study that utilizes high temporal Planet multispectral images (from November 2019 to September 2020, on average 7.1 days of frequency) to detect traffic density in multiple cities through a proposed morphology-based vehicle detection method and evaluate how the traffic data collected in such a manner reflect mobility pattern changes in response to COVID-19. Our experiments at city-scale detection, demonstrate that our proposed vehicle detection method over this 3 m resolution data is able to achieve a detection level at an accuracy of 68.26% in most of the images, and the observations’ trends coincide with existing public data of where available (lockdown duration, traffic volume, etc.), further suggesting that such high temporal Planet data with global coverage (although not with the best resolution), with well-devised detection algorithms, can sufficiently provide traffic details for trend analysis to better facilitate informed decision making for extreme events at the global level.

Diabetic macroangiopathy is a leading cause of diabetes-related mortality worldwide. Both genetic and environmental factors, through a multitude of underlying molecular mechanisms, contribute to the pathogenesis of diabetic macroangiopathy. MicroRNAs (miRNAs), a class of non-coding RNAs known for their functional diversity and expression specificity, are increasingly recognized for their roles in the initiation and progression of diabetes and diabetic macroangiopathy. In this review, we will describe the biogenesis of miRNAs, and summarize their functions in diabetic macroangiopathy, including atherosclerosis, peripheral artery disease, coronary artery disease, and cerebrovascular disease, which are anticipated to provide new insights into future perspectives of miRNAs in basic, translational and clinical research, ultimately advancing the diagnosis, prevention, and treatment of diabetic macroangiopathy.

Background Ischemic stroke, accounting for 85% of stroke cases, leads to severe disabilities and increased mortality. Its global incidence rose by 87.55% from 1990 to 2019, posing significant health and economic burdens. The BRICS-plus nations—Brazil, Russia, India, China, South Africa, and five others—represent a large global population, presenting unique public health challenges. This study aims to evaluate the epidemiological trends and variations in the burden of ischemic stroke across BRICS-plus nations in a timely manner. Methods Data on the number, all-age rate, age-standardized rate, and relative change in ischemic stroke disability-adjusted life years (DALYs) from 1992 to 2021 within BRICS-plus were obtained from the Global Burden of Disease Study (GBD) 2021. Relationships between the DALYs rate and the Socio-demographic Index (SDI) were evaluated using Pearson correlation analyses. Additionally, age-period-cohort modeling was employed to estimate net drift, local drift, age, period, and cohort effects over the past three decades. Results From 1992 to 2021, total DALYs due to ischemic stroke increased by 47.14%, while the age-standardized DALYs rate decreased by 33.79%. All BRICS-plus countries exhibited a declining trend in the age-standardized DALYs rate over the past three decades. Egypt reported the highest age-standardized DALYs rate (2,462.60 per 100,000 population) in 2021, whereas the most substantial reduction of 59.37% was observed in Brazil. The annual net drift in the ischemic stroke DALYs rate ranged from -3.04% for Brazil to -0.48% for Egypt among the ten countries. A significant positive correlation was observed between the DALYs rate of ischemic stroke and SDI values. Countries exhibited similar age effect patterns, with an increasing risk of DALYs rate with advancing age. Period and cohort effects highlighted declines in observed nations, indicating improved ischemic stroke management strategies. Conclusion The burden of ischemic stroke showed an overall declining trend across the BRICS-plus from 1992 to 2021, but persistent health inequalities between these countries were driven by socioeconomic disparities. Furthermore, it emphasizes the necessity for targeted interventions across age, period, and cohort dimensions to address the distinct challenges posed by ischemic stroke in these rapidly developing countries.

Computational imaging spectrometers using broad-bandpass filter arrays with distinct transmission functions are promising implementations of miniaturization. The number of filters is limited by the practical factors. Compressed sensing is used to model the system as linear underdetermined equations for hyperspectral imaging. This paper proposes the following method: parallel dictionary reconstruction and fusion for spectral recovery in computational imaging spectrometers. Orthogonal systems are the dictionary candidates for reconstruction. According to observation of ground objects, the dictionaries are selected from the candidates using the criterion of incoherence. Parallel computations are performed with the selected dictionaries, and spectral recovery is achieved by fusion of the computational results. The method is verified by simulating visible-NIR spectral recovery of typical ground objects. The proposed method has a mean square recovery error of ≤1.73 × 10−4 and recovery accuracy of ≥0.98 and is both more universal and more stable than those of traditional sparse representation methods.

The rapid emergence of SARS-CoV-2 variants of concern, the complexity of infection, and the functional redundancy of host factors, underscore an urgent need for broad-spectrum antivirals against the continuous COVID-19 pandemic, with drug repurposing as a viable therapeutic strategy. Here we report the potential of RNA G-quadruplex (RG4)-targeting therapeutic strategy for SARS-CoV-2 entry. Combining bioinformatics, biochemical and biophysical approaches, we characterize the existence of RG4s in several SARS-CoV-2 host factors. In silico screening followed by experimental validation identify Topotecan (TPT) and Berbamine (BBM), two clinical approved drugs, as RG4-stabilizing agents with repurposing potential for COVID-19. Both TPT and BBM can reduce the protein level of RG4-containing host factors, including ACE2, AXL, FURIN, and TMPRSS2. Intriguingly, TPT and BBM block SARS-CoV-2 pseudovirus entry into target cells in vitro and murine tissues in vivo . These findings emphasize the significance of RG4 in SARS-CoV-2 pathogenesis and provide a potential broad-spectrum antiviral strategy for COVID-19 prevention and treatment.

Objective To explore the application effect of the direct reporting system of adverse nursing events and special continuous nursing quality improvement measures in the management of these adverse events. Methods The implementation time of continuous nursing improvement based on the direct reporting system was the demarcation point. We retrospectively collected and analyzed nursing adverse event reports and hospitalization data from Xiangtan Central Hospital before implementation (2015–2018) and after implementation (2019–2022). The active reporting rate of adverse events, the composition of these events and the processing time were compared between the two groups. Results The rate of active reporting of adverse events before the implementation was lower than that after the implementation (6.7% vs. 8.1%, X 2  = 25.561, P  < 0.001). After the implementation of the direct reporting system for nursing events and the continuous improvement of nursing quality, the reporting proportion of first-level and second-level events decreased significantly. Moreover, the reporting proportion of third-level events increased significantly. The proportion of falls and medication errors decreased, and the proportion of unplanned extubation, infusion xerostomia and improper operation increased. The processing time of the reported nursing adverse events was significantly reduced (31.87 ± 7.83 vs. 56.87 ± 8.21, t  = 18.73, P  < 0.001). Conclusion The direct reporting system of adverse nursing events and the continuous improvement measures for nursing quality can effectively improve the active reporting rate of adverse events, change their composition and reduce their processing time, as well as help create a safe psychological environment for both patients and nursing staff.

Quantifying the colors of objects is useful in a wide range of applications, including medical diagnosis, agricultural monitoring, and food safety. Accurate colorimetric measurement of objects is a laborious process normally performed through a color matching test in the laboratory. A promising alternative is to use digital images for colorimetric measurement, due to their portability and ease of use. However, image-based measurements suffer from errors caused by the non-linear image formation process and unpredictable environmental lighting. Solutions to this problem often perform relative color correction among multiple images through discrete color reference boards, which may yield biased results due to the lack of continuous observation. In this paper, we propose a smartphone-based solution, that couples a designated color reference board with a novel color correction algorithm, to achieve accurate and absolute color measurements. Our color reference board contains multiple color stripes with continuous color sampling at the sides. A novel correction algorithm is proposed to utilize a first-order spatial varying regression model to perform the color correction, which leverages both the absolute color magnitude and scale to maximize the correction accuracy. The proposed algorithm is implemented as a “human-in-the-loop” smartphone application, where users are guided by an augmented reality scheme with a marker tracking module to take images at an angle that minimizes the impact of non-Lambertian reflectance. Our experimental results show that our colorimetric measurement is device independent and can reduce up to 90% color variance for images collected under different lighting conditions. In the application of reading pH values from test papers, we show that our system performs 200% better than human reading. The designed color reference board, the correction algorithm, and our augmented reality guiding approach form an integrated system as a novel solution to measure color with increased accuracy. This technique has the flexibility to improve color reading performance in systems beyond existing applications, evidenced by both qualitative and quantitative experiments on example applications such as pH-test reading.

The immune microenvironment plays a critical role in pathogenesis and treatment response of cervical cancer. This review comprehensively examines the cellular and molecular components of the tumor immune microenvironment (TIME) in cervical cancer, encompassing patterns of immune cell infiltration (T cells, B cells, NK cells, DCs, TAMs), immune checkpoint molecules, and cytokine/chemokine networks. We emphasize recent advances in understanding TIME heterogeneity, enabled by high-resolution spatial mapping and single-cell sequencing technologies, focusing specifically on differences across disease stages and treatment approaches. The review systematically evaluates immunotherapeutic strategies, such as immune checkpoint inhibitors, adoptive cell therapies, and therapeutic vaccines, discussing their mechanisms of action, clinical efficacy, and challenges. By synthesizing insights from both preclinical and clinical studies, our aim is to offer a translational perspective on targeting the TIME to enhance outcomes for cervical cancer patients.

PurposeSoil washing with chelators is a viable treatment alternative for remediating multi-contaminated soils. The aim of this study was to investigate the removal efficiencies of Cd, Zn, Pb, and Cu in alkaline and acid multi-metal-contaminated soils by washing with the mixed chelators (MC).Materials and methodsThe batch experiments were carried out to evaluate the removal efficiencies of heavy metals in contaminated soils by the MC with different molar ratios of EDTA, GLDA, and citric acid, and evaluated the washing factors, including contact time, pH, MC concentration, and single and multiple washings at the same MC dose, on the removal efficiencies.Results and discussionResults showed that the removal efficiencies for Cd, Zn, Pb, and Cu by the MC (the molar ratio of EDTA, GLDA, and citric acid was 1:1:3) were as much as those of the only EDTA washing from both soil at the same application dose of total chelators; moreover, the application dose of EDTA decreased by 80%. For the alkaline-contaminated soil, the removal efficiencies of Cd, Zn, Pb, and Cu decreased with the increasing of the solution pH, which was opposite to acid-contaminated soil. This was attributed to that the metal-ligand complex could be obviously re-adsorbed on the soil surface sites, particularly in low pH values. The removal efficiencies of Cd, Zn, Pb, and Cu depended on MC concentration. A higher MC concentration led to a more effective removal of Cd, Zn, Pb, and Cu in alkaline-contaminated soil; however, their changes were slightly increased in acid-contaminated soil. At the same dose of MC, single washing with higher MC concentration might be favorable to remove heavy metals, moreover, with much less wastewater generation.ConclusionsThe MC (the molar ratio of EDTA, GLDA, and citric acid was 1:1:3) may be a useful, environmentally friendly, and cost-effective chelators to remediate heavily multi-metal-contaminated soil.

Alloys have many advantages over pure metals, but in most cases, it is difficult to get a proper surface due to various factors. To solve the problem of poor surface quality, the surface of cobalt-chromium-molybdenum (Co-Cr-Mo) alloy formed using selective laser melting (SLM) was investigated by chemical corrosion-assisted magnetic abrasive finishing (MAF). First, Co-Cr-Mo alloy was formed by the SLM method, the heat-treated forming parts were chemically etched with a mixture of HCl: H 2 O 2 = 1:1, etched for 5 min, and then MAF tests were carried out; respectively. The response surface approach was employed to finalize the experimental setup, which resulted in the specification of MAF’s operational parameters. These included a spindle speed of 1050 revolutions per minute, a machining clearance of 1.8 millimeters, and a feed speed fixed at 15 millimeters per minute. The experimental outcomes indicate that the initial specimen exhibits a surface roughness measurement of approximately 6.5 micrometers, the roughness after chemical corrosion is reduced to about 0.7 μm, and the roughness after magnetic grinding is reduced to 0.070 μm. It can be seen from the two-dimensional contour, three-dimensional topography, and image effect diagram that the unfused powder and burrs adhering to the surface of the sample are removed, the sample obtains a good residual stress state, and the corrosion resistance is improved.