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Assessing street walkability is a critical agenda in urban planning and multidisciplinary research, as it facilitates public health, community cohesion, and urban sustainability. Existing evaluation systems primarily focus on objective measurements, often neglecting subjective assessments and the diverse walking needs influenced by different urban spatial elements. This study addresses these gaps by constructing a comprehensive evaluation framework that integrates both subjective and objective dimensions, combining three neighbourhood indicators: Macro-Scale Index, Micro-Scale Index, and Street Walking Preferences Index. A normalization weighting method synthesizes these indicators into a comprehensive index. We applied this framework to assess the street environment within Beijing’s Fifth Ring Road. The empirical results demonstrate that: (1) The framework reliably reflects the distribution of walkability. (2) The three indicators show both similarities and differences, underscoring the need to consider the distinct roles of community and street-level elements and the interaction between subjective and objective dimensions. (3) In high-density cities with ring-road development patterns, the Macro-Scale Index closely aligns with the Comprehensive Index, demonstrating its accuracy in reflecting walkability. The proposed framework and findings offer new insights for street walkability research and theoretical support for developing more inclusive, sustainable and walkable cities.

In order to promote the development of the basic public service system, it also needs to enhance the affordability and fairness of surrounding communities of rail transit stations. Based on this, the example for this research has been selected as the area within the 6 th Ring Road of Beijing. This paper is aimed at finding out the difference between the openness of the environment around the rail transit station and the population density. This simulation and examination on rail transit station regions’ accessibility employed the Gaussian-based two-step floating catchment area approach and the Gaode Map service Application Programming Interface (API) four transport modes: walking, cycling, driving a car, and taking public transport. By combining the calculation results with population distribution data, the current state of accessibility equity is assessed. The IPA analysis method is employed to determine the priority order for different area modifications and to propose corresponding suggestions for optimization. The findings are as follows: (1) Within the urban core and urban sub-center area, accessibility is higher compared to other regions across different travel modes; (2) Within the study area, there is a significant positive correlation between the accessibility of rail transit station areas and the travel mode; (3) Within the maturely developed areas, there are notable differences in the equity and accessibility of rail transit station areas across different travel modes. According to the Gini coefficient, accessibility is most equitable when traveling by car or bicycle, and least equitable when traveling on foot or by public transit; (4) Local bivariate spatial correlation analysis indicates that cycling and driving can improve the accessibility equity within the urban core compared to walking and public transit; (5) Importance-Performance Analysis (IPA) results show that the area from western fringe area of the urban core has the highest priority for redevelopment, and the accessibility equity northern fringe of the city can be improved by promoting cycling to enhance accessibility of walking and public transit. The findings of this study can be applied to urban rail transit accessibility improvement projects.

With industrial transformation and the rise in the 15 min community life circle, optimizing walkability and preserving industrial heritage are key to revitalizing former industrial areas. This study, focusing on Shijingshan District in Beijing, proposes a walkability evaluation framework integrating multi-source big data and street-level perception. Using Points of Interest (POI) classification, which refers to the categorization of key urban amenities, pedestrian network modeling, and street view image data, a Walkability Friendliness Index is developed across four dimensions: accessibility, convenience, diversity, and safety. POI data provide insights into the spatial distribution of essential services, while pedestrian network data, derived from OpenStreetMap, model the walkable road network. Street view image data, processed through semantic segmentation, are used to assess the quality and safety of pedestrian pathways. Results indicate that core communities exhibit higher Walkability Friendliness Index scores due to better connectivity and land use diversity, while older and newly developed areas face challenges such as street discontinuity and service gaps. Accordingly, targeted optimization strategies are proposed: enhancing accessibility by repairing fragmented alleys and improving network connectivity; promoting functional diversity through infill commercial and service facilities; upgrading lighting, greenery, and barrier-free infrastructure to ensure safety; and delineating priority zones and balanced enhancement zones for differentiated improvement. This study presents a replicable technical framework encompassing data acquisition, model evaluation, and strategy development for enhancing walkability, providing valuable insights for the revitalization of industrial districts worldwide. Future research will incorporate virtual reality and subjective user feedback to further enhance the adaptability of the model to dynamic spatiotemporal changes.

Background Uncontrollable inflammation and nerve cell apoptosis are the most destructive pathological response after spinal cord injury (SCI). So, inflammation suppression combined with neuroprotection is one of the most promising strategies to treat SCI. Engineered extracellular vesicles with anti-inflammatory and neuroprotective properties are promising candidates for implementing these strategies for the treatment of SCI. Results By combining nerve growth factor (NGF) and curcumin (Cur), we prepared stable engineered extracellular vesicles of approximately 120 nm from primary M2 macrophages with anti-inflammatory and neuroprotective properties (Cur@EVs −cl−NGF ). Notably, NGF was coupled with EVs by matrix metalloproteinase 9 (MMP9)-a cleavable linker to release at the injured site accurately. Through targeted experiments, we found that these extracellular vesicles could actively and effectively accumulate at the injured site of SCI mice, which greatly improved the bioavailability of the drugs. Subsequently, Cur@EVs −cl−NGF reached the injured site and could effectively inhibit the uncontrollable inflammatory response to protect the spinal cord from secondary damage; in addition, Cur@EVs −cl−NGF could release NGF into the microenvironment in time to exert a neuroprotective effect against nerve cell damage. Conclusions A series of in vivo and in vitro experiments showed that the engineered extracellular vesicles significantly improved the microenvironment after injury and promoted the recovery of motor function after SCI. We provide a new method for inflammation suppression combined with neuroprotective strategies to treat SCI. Graphical Abstract

Spinal cord injury (SCI) is a traumatic disease that can cause severe nervous system dysfunction. SCI often causes spinal cord mitochondrial dysfunction and produces glucose metabolism disorders, which affect neuronal survival. Zinc is an essential trace element in the human body and plays multiple roles in the nervous system. This experiment is intended to evaluate whether zinc can regulate the spinal cord and neuronal glucose metabolism and promote motor functional recovery after SCI. Then we explore its molecular mechanism. We evaluated the function of zinc from the aspects of glucose uptake and the protection of the mitochondria in vivo and in vitro. The results showed that zinc elevated the expression level of GLUT4 and promoted glucose uptake. Zinc enhanced the expression of proteins such as PGC-1α and NRF2, reduced oxidative stress, and promoted mitochondrial production. In addition, zinc decreased neuronal apoptosis and promoted the recovery of motor function in SCI mice. After administration of AMPK inhibitor, the therapeutic effect of zinc was reversed. Therefore, we concluded that zinc regulated the glucose metabolism of the spinal cord and neurons and promoted functional recovery after SCI through the AMPK pathway, which is expected to become a potential treatment strategy for SCI.

Spinal cord injury (SCI) leads to severe inflammation and neuronal damage, resulting in permanent loss of motor and sensory functions. Zinc ions have shown potential in modulating inflammation and cellular survival, making them a promising therapeutic approach for SCI. This study investigates the mechanisms of zinc ion treatment in SCI, focusing on its effects on inflammation. We used transcriptomic analysis to identify key pathways and genes involved in the inflammatory response in a mouse model of SCI. studies assessed the impact of zinc ions on inflammation, cell polarization, and apoptosis. IKBα expression was evaluated as a potential target of zinc ions, both in cultured cells and . Transcriptomic analysis revealed that zinc ions modulate inflammatory pathways through IKBα, which inhibits NF-κB activity. , zinc treatment upregulated IKBα expression, reducing inflammation, polarization, and apoptosis. These results were confirmed in the SCI mouse model, where zinc ions also reduced inflammation and cell death. Our findings highlight a novel mechanism by which zinc ions regulate inflammation in SCI by upregulating IKBα and inhibiting NF-κB activation. This suggests potential therapeutic applications of zinc ions in SCI and other inflammatory conditions, warranting further investigation into their clinical benefits.

While zinc promotes motor function recovery after spinal cord injury (SCI), the precise mechanisms involved are not fully understood. The present study aimed to elucidate the effects of zinc and granulocyte colony stimulating factor (G-CSF) on neuronal recovery after SCI. The SCI model was established by Allen's method. Injured animals were given glucose and zinc gluconate (ZnG; 30 mg/kg) for the first time at 2 h after injury, the same dose was given for 3 days. A cytokine antibody array was used to screen changes in inflammation at the site of SCI lesion. Immunofluorescence was used to detect the distribution of cytokines. Magnetic beads were also used to isolate cells from the site of SCI lesion. We then investigated the effect of Zinc on apoptosis after SCI by Transferase UTP Nick End Labeling (TUNEL) staining and Western Blotting. Basso Mouse Scale (BMS) scores and immunofluorescence were employed to investigate neuronal apoptosis and functional recovery. We found that the administration of zinc significantly increased the expression of 19 cytokines in the SCI lesion. Of these, G-CSF was shown to be the most elevated cytokine and was secreted by microglia/macrophages (M/Ms) the nuclear factor-kappa B (NF-κB) signaling pathway after SCI. Increased levels of G-CSF at the SCI lesion reduced the level of neuronal apoptosis after SCI, thus promoting functional recovery. Collectively, our results indicate that the administration of zinc increases the expression of G-CSF secreted by M/Ms, which then leads to reduced levels of neuronal apoptosis after SCI.

Carbon dots (CDs) have been widely used as antimicrobials due to their active surface, but some CDs suffer instability. Therefore, the relative applications such as the antibacterial activity may not be reliable for long-term use. Herein, we synthesize CDs with blue fluorescence by a hydrothermal process. Thereafter, polyethylenimine was applied for the assembly of CDs into CDs-based frameworks (CDFs). The CDFs exhibited quenched fluorescence but showed more stable properties based on the scanning electron microscope and zeta potential investigations. Both CDs and CDFs show antibacterial activity toward Gram-negative Escherichia coli (E. coli) and Gram-positive Staphylococcus aureus (S. aureus), but CDFs exhibited better antibacterial performance, and S. aureus could be completely inhibited with the minimum inhibitory concentration of 30 μg/mL. This reveals CDFs magnify both the stability and antibacterial activity, which would be more promising for practical applications.Graphic abstract

The outbreak of COVID-19 in Beijing has been sporadic since the beginning of 2022 and has become increasingly severe since October. In China’s policy of insisting on dynamic clearance, fine-grained management has become the focus of current epidemic prevention and control. In this paper, we conduct a refined COVID-19 risk prediction and identification of its influencing factors in Beijing based on neighborhood-scale spatial statistical units. We obtained geographic coordinate data of COVID-19 cases in Beijing and quantified them into risk indices of each statistical unit. Additionally, spatial autocorrelation was used to analyze the epidemic risk clustering characteristics. With the multi-source data, 20 influencing elements were constructed, and their spatial heterogeneity was explored by screening 8 for Multiscale Geographically weighted regression (MGWR) model analysis. Finally, a neural network classification model was used to predict the risk of COVID-19 within the sixth ring of Beijing. The MGWR model and the neural network classification model showed good performance: the R2 of the MGWR model was 0.770, and the accuracy of the neural network classification model was 0.852. The results of this study show that: (1) COVID-19 risk is uneven, with the highest clustering within the Fifth Ring Road of Beijing; (2) The results of the MGWR model show that population structure, population density, road density, residential area density, and living service facility density have significant spatial heterogeneity on COVID-19 risk; and (3) The prediction results show a high COVID-19 risk, with the most severe risk being in the eastern, southeastern and southern regions. It should be noted that the prediction results are highly consistent with the current epidemic situation in Shijingshan District, Beijing, and can provide a strong reference for fine-grained epidemic prevention and control in Beijing.