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Abstract Background Recent studies have highlighted type 2 diabetes (T2DM) as a significant risk factor for the development of metabolic dysfunction-associated fatty liver disease (MAFLD). This investigation aimed to assess electroacupuncture’s (EA) impact on liver morphology and function in T2DM rats, furnishing experimental substantiation for its potential to stall MAFLD progression in T2DM. Methods T2DM rats were induced by a high-fat diet and a single intraperitoneal injection of streptozotocin, and then randomly assigned to five groups: the T2DM group, the electroacupuncture group, the metformin group, combination group of electroacupuncture and metformin, combination group of electroacupuncture and Compound C. The control group received a standard diet alongside intraperitoneal citric acid - sodium citrate solution injections. After a 6-week intervention, the effects of each group on fasting blood glucose, lipids, liver function, morphology, lipid droplet infiltration, and fibrosis were evaluated. Techniques including Western blotting, qPCR, immunohistochemistry, and immunofluorescence were employed to gauge the expression of key molecules in AMPK-associated glycolipid metabolism, insulin signaling, autophagy, and fibrosis pathways. Additionally, transmission electron microscopy facilitated the observation of liver autophagy, lipid droplets, and fibrosis. Results Our studies indicated that hyperglycemia, hyperlipidemia and IR promoted lipid accumulation, pathological and functional damage, and resulting in hepatic steatosis and fibrosis. Meanwhile, EA enhanced the activation of AMPK, which in turn improved glycolipid metabolism and autophagy through promoting the expression of PPARα/CPT1A and AMPK/mTOR pathway, inhibiting the expression of SREBP1c, PGC-1α/PCK2 and TGFβ1/Smad2/3 signaling pathway, ultimately exerting its effect on ameliorating hepatic steatosis and fibrosis in T2DM rats. The above effects of EA were consistent with metformin. The combination of EA and metformin had significant advantages in increasing hepatic AMPK expression, improving liver morphology, lipid droplet infiltration, fibrosis, and reducing serum ALT levels. In addition, the ameliorating effects of EA on the progression of MAFLD in T2DM rats were partly disrupted by Compound C, an inhibitor of AMPK. Conclusions EA upregulated hepatic AMPK expression, curtailing gluconeogenesis and lipogenesis while boosting fatty acid oxidation and autophagy levels. Consequently, it mitigated blood glucose, lipids, and insulin resistance in T2DM rats, thus impeding liver steatosis and fibrosis progression and retarding MAFLD advancement.

ABSTRACTPoverty continues to pose significant global challenges. Analyzing poverty distribution is pivotal for identifying spatial and demographic disparities, informing targeted policy interventions, and fostering inclusive and equitable development. The absence of a worldwide pixel-scale time-series poverty dataset has hampered effective policy formulation. To address this gap, we employ the international wealth index (IWI) derived from household survey data to represent poverty levels. Subsequently, a random forest regression model was constructed, with IWI serving as the dependent variable and representative features extracted from nighttime lights, land cover, digital elevation model, and World Bank statistical data serving as independent variables. This yielded a global map of the IWI for low- and middle-income nations at a 10-km resolution spanning 2005 to 2020. The model demonstrated robust performance with an R2 value of 0.74. Over the studied period, areas and populations with IWI ≤ 50 decreased by 8.85% and 16.17%, indicating a steady decrease in global poverty regions. Changes in the IWI at the pixel scale indicate that areas closer to cities have faster growth rates. Furthermore, our poverty estimation models present a novel method for real-time pixel-scale poverty assessments. This study provides valuable insights into the dynamics of poverty, both globally and nationally.

Abstract With the advantages of high energy density, abundant resources and environmental friendliness, Aqueous Zinc‐ion Batteries (AZIBs) are considered as one of the promising new energy systems. However, its practical application is limited by the problems of irregular dendrite growth and interfacial side reaction in zinc anode. In view of the above problems, relevant researchers have given solutions such as the construction of artificial protective layer and the regulation of substrate structure. This paper summarizes the relevant literatures in order to help the future research of zinc‐ion batteries.

Urban built-up areas are the main space carrier of population and urban activities. It is of great significance to accurately identify urban built-up area for monitoring urbanization dynamics and their impact on Sustainable Development Goals. Using only nighttime light (NTL) remote sensing data will lead to omission phenomena in urban built-up area extraction, especially for SDGSAT-1 glimmer imager (GLI) data with high spatial resolution. Therefore, this study proposed a novel nighttime Lights integrate Building Volume (LitBV) index by integrating NTL intensity information from SDGSAT-1 GLI data and building volume information from Digital Surface Model (DSM) data to extract built-up areas more accurately. The results indicated that the LitBV index achieved remarkable results in the extraction of built-up areas, with the overall accuracy of 81.25%. The accuracy of the built-up area extraction based on the LitBV index is better than the results based on only NTL data and only building volume. Moreover, experiments at different spatial resolutions (10 m, 100 m, and 500 m) and different types of NTL data (SDGSAT-1 GLI data, Luojia-1 data, and NASA’s Black Marble data) showed that the LitBV index can significantly improve the extraction accuracy of built-up areas. The LitBV index has a good application ability and prospect for extracting built-up areas with high-resolution SDGSAT-1 GLI data.

Artificial light at night, as captured by nighttime light (NTL) remote sensing, typically consists of two components: static urban lighting facilities and dynamic outdoor human activities. Separating these components can improve our understanding of the mechanism underlying NTL remote sensing and broaden its applications. In this paper, we introduce the concept of Nighttime Light Background Value (NLBV) to represent NTL emitted solely by static urban lighting facilities, excluding the influence of outdoor human activities. By utilizing a random forest method, we derived the pixel-level NLBV for Shanghai from NTL data. Comparative analysis demonstrates that NLBV exhibits a stronger correlation with building density and road density compared to the original NTL data. Our empirical findings demonstrate that the definition and application of NLBV can significantly enhance NTL-based applications for extracting urban physical attributes and estimating socioeconomic variables. Firstly, the urban built-up area extracted based on NLBV outperforms the original NTL data, especially in highly urbanized. Secondly, separating static urban lighting and dynamic human activity enables a more accurate estimation of socioeconomic variables with different contributions. Moreover, our results highlight the significant potential of incorporating NLBV in NTL-based applications across various disciplines. Overall, this study demonstrates the significance of NLBV in improving the accuracy and applicability of NTL data, opening up new opportunities for research and practical applications across various domains.

The new visible infrared imaging radiometer suite (VIIRS) onboard the National Oceanic and Atmospheric Administration-20 satellite (NOAA-20) is capable of imaging the Earth during both daytime and nighttime. The NOAA-20 VIIRS’ day/night band (DNB) enables a new generation of nighttime imaging applications. However, few studies investigated the ability of NOAA-20 DNB nighttime light data in modeling socioeconomic indicators [such as the gross domestic product (GDP) and electric power consumption (EPC)] and extracting urban areas. In this article, we first used a simple linear regression model to investigate the potential of NOAA-20 nighttime light data for estimating GDP and EPC at multiple scales; we then extracted urban areas from NOAA-20 nighttime light data by using support vector machines. Taking mainland China as the study area, we found that the correlation coefficient of determination R2 between NOAA-20 nighttime light data and GDP/EPC at both provincial and prefectural scales are higher than 0.7. By comparing the results with NPP-VIIRS nighttime light data, similar R2 values were obtained at both two scales, indicating that NOAA-20 nighttime light data and NPP-VIIRS data are comparable in estimating socioeconomic indicators. Moreover, NOAA-20 also shows a similar detection ability with NPP-VIIRS in extracting urban areas. This article demonstrated that NOAA-20 and NPP-VIIRS are comparable in economic statistics estimation and urban area extraction. The NOAA-20 nighttime light data can be a useful data source for enlightening more applications in the fields of socioeconomic and urban studies.

Recycled polypropylene (rPP) often contains a small amount of polyethylene (PE), which frequently compromises the performance of the material and needs to be monitored. In the current work, near-infrared (NIR) and Raman spectrometries were investigated to establish convenient and accurate methods to analyze PE content in rPP. Various spectrum pretreatment methods, including multivariate scattering correction (MSC), standard normal variate transformation (SNV), baseline correction, normalization, smoothing, and first derivative, were tested to reduce noise and improve spectrum quality for partial least squares (PLS) regression. Forward and backward interval partial least squares (FiPLS/BiPLS) methods were employed to optimize spectral range selection. The best NIR model had an R2 of 0.9971 and a root-mean-square error of prediction (RMSEP) of 0.2761 PE wt% in independent validation, and the best Raman model achieved an R2 of 0.9945 and an RMSEP of 0.3818 wt%. The models were further validated with rPP samples. The best Raman model obtained an R2 of 0.9954 and an RMSEP of 0.2404 wt% on non-colored rPP, but it failed to be applied to colored rPP. The best NIR model had a slightly weaker performance on non-colored rPP (R2: 0.9246; RMSEP: 0.9710 wt%), but it was successfully applied to grey commercial rPP samples. This work would help quality assurance of recycled PP materials.

The Turkey–Syria earthquake on 6 February 2023 resulted in losses such as casualties, road damage, and building collapses. We mapped and quantified the areas impacted by the earthquake at different distances and directions using NOAA-20 VIIRS nighttime light (NTL) data. We then explored the relationship between the average changes in the NTL intensity, population density, and building density using the bivariate local indicators of the spatial association (LISA) method. In Turkey, Hatay, Gaziantep, and Sanliurfa experienced the largest NTL losses. Ar Raqqah was the most affected city in Syria, with the highest NTL loss rate. A correlation analysis showed that the number of injured populations in the provinces in Turkey and the number of pixels with a decreased NTL intensity exhibited a linear correlation, with an R-squared value of 0.7395. Based on the changing value of the NTL, the areas with large NTL losses were located 50 km from the earthquake epicentre in the east-by-south and north-by-west directions and 130 km from the earthquake epicentre in the southwest direction. The large NTL increase areas were distributed 130 km from the earthquake epicentre in the north-by-west and north-by-east directions and 180 km from the earthquake epicentre in the northeast direction, indicating a high resilience and effective earthquake rescue. The areas with large NTL losses had large populations and building densities, particularly in the areas approximately 130 km from the earthquake epicentre in the south-by-west direction and within 40 km of the earthquake epicentre in the north-by-west direction, which can be seen from the low–high (L-H) pattern of the LISA results. Our findings provide insights for evaluating natural disasters and can help decision makers to plan post-disaster reconstruction and determine risk levels on a national or regional scale.

Graphical Abstract

Quercetin, one of the major natural flavonoids, has demonstrated great pharmacological potential as an antioxidant and in overcoming drug resistance. However, its low aqueous solubility and poor stability limit its potential applications. Previous studies suggest that the formation of quercetin-metal complexes could increase quercetin stability and biological activity. In this paper, we systematically investigated the formation of quercetin-iron complex nanoparticles by varying the ligand-to-metal ratios with the goal of increasing the aqueous solubility and stability of quercetin. It was found that quercetin-iron complex nanoparticles could be reproducibly synthesized with several ligand-to-iron ratios at room temperature. The UV-Vis spectra of the nanoparticles indicated that nanoparticle formation greatly increased the stability and solubility of quercetin. Compared to free quercetin, the quercetin-iron complex nanoparticles exhibited enhanced antioxidant activities and elongated effects. Our preliminary cellular evaluation suggests that these nanoparticles had minimal cytotoxicity and could effectively block the efflux pump of cells, indicating their potential for cancer treatment.

Objective: To search for specific metabolites in the lungs of pneumonia rats fed with a high-calorie diet, as well as explore the changes in the lung metabolites of young rats treated with Yinlai Decoction (YD) and its effects on inflammation-related metabolic pathways. Methods: Lipopolysaccharides (LPS) and a special high-calorie diet were used to induce Sprague Dawley (SD) rats to simulate the intestinal state of infant pneumonia. Liquid chromatography-mass spectrometry technology (LC-MS/MS) was used to detect metabolites in each group. Supervised orthogonal partial least squares discriminant analysis (OPLS-DA) model values were used for the detection results to find the differential metabolites. The metabolic pathways that are involved with the differential metabolites were clarified through enrichment analysis and topological analysis. Finally, the T cell receptor signaling pathway (TCR) signal conversion was analyzed by the network pharmacology method. Results: In the high-calorie diet combined with pneumonia group (M3), a total of 55 metabolites were determined to be different from the normal group (N). A total of 36 metabolites were determined to be different from those in the lung metabolites of the YD treatment group (T1). YD had a regulatory effect on glutathione metabolism, arginine and proline metabolism, ascorbic acid and aldehyde metabolism and phenylalanine metabolism. And the small molecule metabolites could act on the FYN and lymphocyte-specific protein tyrosine kinase (LCK) target proteins in the TCR signaling pathway, thereby affecting the immune function of the lungs. Conclusion: A high-calorie diet can cause abnormal sphingolipid metabolism in the lungs of young rats, thereby creating chronic lung inflammation in young rats. YD has a beneficial effect when used to treat young rats with LPS-induced pneumonia fed on high-calorie diets. Its mechanisms of action may affect the body’s immune pathways by regulating the oxidative stress pathway affected by glutathione metabolism.

Objective: Bushen Chengyun granule (BCG) is an empirical treatment for female infertility (FI) caused by low endometrial receptivity (LER) involving a poorly understood mechanism. In this study, network pharmacology was used to explore the potential therapeutic mechanism of BCG on FI caused by LER. Methods: The corresponding herb targets were obtained by conducting a search in the Traditional Chinese Medicine Systems Pharmacology Database and PubMed-reported literature. Disease targets were obtained from the following databases: Comparative Toxicogenomics Database, Human Phenotype Ontology, and Therapeutic Target Database. Treatments for LER using BCG have used target matching (BCG – LER target). Then, the predicted targets were uploaded to the Search Tool for the Retrieval of Interacting Genes/Proteins database for gene ontology enrichment and Kyoto Encyclopedia of Genes and Genomes pathway analyses. Furthermore, triptorelin acetate for injection + menotrophin + chorionic gonadotropin for injection were used to establish a mouse model of blastocyst implantation disorder and to evaluate the in vivo effect of BCG on blastocyst implantation. Results: Overall, 156 bioactive chemical components and 1092 targets of BCG were identified. The results indicated that 482 biological processes (FDR

Chemically deuterated cellulose fiber was expected to provide novel applications due to its spectral, biological, and kinetic isotope effect. In this research, the performance of the chemically deuterated cotton fibers, including their mechanical property, enzymatic degradation performance, effect on bacterial treatment, and fast identification (near-infrared modeling) was investigated. The breaking tenacity of the deuterated cotton fibers was slightly lower, which might be attributed to the structural damage during the chemical deuteration. The glucose yield by enzymatic hydrolysis was less than that of the protonic cotton fibers, implying the deuterated fibers are less sensitive to enzymatic degradation. Furthermore, the deuterated fibers could promote the growth of bacteria such as Escherichia. coli, which was associated with the released low-level deuterium content. At last, the near-infrared technique combined with partial least squares regression successfully achieved a fast identification of the protiated and deuterated cotton fibers, which significantly promoted the potential application of deuterated cellulose as anticounterfeiting materials (e.g., special paper).

Objective: Pediatric pneumonia is a common respiratory disease and Yinlai Decoction (YLD) is a commonly used treatment in China. We explored the anti-inflammatory mechanism of action of this traditional Chinese medicine for pneumonia. Methods: We studied, by experimentation, the mechanism of action of YLD in treating pneumonia according to network pharmacology. By comparing YLD with dexamethasone (DXMS), we investigated the efficacy of YLD in treating pneumonia induced by lipopolysaccharide (LPS) in juvenile rats. Results: In an aqueous extract of YLD, 22 chemical compounds were identified, among which 10 were related to inflammation, involving 78 target genes and 16 signaling pathways. Among them, 45 core target proteins were related to biologic processes and functions, such as response to stimuli, biologic regulation, cell communication and protein binding. Animal experiments showed that YLD relieved pulmonary inflammation and demonstrated no significant damage to the liver, spleen or kidneys of rats. YLD could regulate expression of inflammatory cytokines in serum and inflammation-related proteins in lung tissues to some extent, but its effect is less significant than that of DXMS. Conclusions: YLD protected juvenile rats against LPS-induced pneumonia, and showed fewer side effects in comparison with DXMS. YLD could be efficacious treatment for pediatric respiratory infections and even pneumonia. Keywords: Pediatric pneumonia, Yinlai decoction, Traditional Chinese medicine, Network pharmacology, Immunity

The outbreak of new infectious pneumonia caused by SARS-CoV-2 has posed a significant threat to public health, but specific medicines and vaccines are still being developed. Traditional Chinese medicine (TCM) has thousands of years of experience in facing the epidemic disease, such as influenza and viral pneumonia. In this study, we revealed the efficacy and pharmacological mechanism of Ma Xing Shi Gan (MXSG) Decoction against COVID-19. First, we used liquid chromatography–electrospray ionization tandem mass spectrometry (LC-ESI-MS/MS) to analyze the chemical components in MXSG and identified a total of 97 components from MXSG. Then, the intervention pathway of MXSG based on these components was analyzed with network pharmacology, and it was found that the pathways related to the virus infection process were enriched in some of MXSG component targets. Simultaneously, through literature research, it was preliminarily determined that MXSG, which is an essential prescription for treating COVID-19, shared the feature of antiviral, improving clinical symptoms, regulating immune inflammation, and inhibiting lung injury. The regulatory mechanisms associated with its treatment of COVID-19 were proposed. That MXSG might directly inhibit the adsorption and replication of SARS-CoV-2 at the viral entry step. Besides, MXSG might play a critical role in inflammation and immune regulatory, that is, to prevent cytokine storm and relieve lung injury through toll-like receptors signaling pathway. Next, in this study, the regulatory effect of MXSG on inflammatory lung injury was validated through transcriptome results. In summary, MXSG is a relatively active and safe treatment for influenza and viral pneumonia, and its therapeutic effect may be attributed to its antiviral and anti-inflammatory effects.

Chimeric antigen receptor- (CAR-) T cell therapy is one of the most recent innovative immunotherapies and is rapidly evolving. Like other technologies, CAR-T cell therapy has undergone a long development process, and persistent explorations of the actions of the intracellular signaling domain and make several improvements have led to the superior efficacy when anti-CD19 CAR-T cell treatments in B cell cancers. At present, CAR-T cell therapy is developing rapidly, and many clinical trials have been established on a global scale, which has great commercial potential. This review mainly describes the toxicity of CAR-T cell therapy and the challenges of CAR-T cells in the treatment of solid tumors, and looks forward to future development and opportunities for immunotherapy and reviews major breakthroughs in CAR-T cell therapy.

Environmentally friendly face masks with high filtration efficiency are in urgent need to fight against the COVID-19 pandemic, as well as other airborne viruses, bacteria and particulate matters. In this study, coaxial electrospinning was employed to fabricate a lithium chloride enhanced cellulose acetate/thermoplastic polyurethanes (CA/TPU-LiCl) face mask nanofiber filtration membrane, which was biodegradable and reusable. The analysis results show that the CA/TPU-LiCl membrane had an excellent filtration performance: when the filtration efficiency reached 99.8%, the pressure drop was only 52 Pa. The membrane also had an outstanding reusability. The filtration performance maintained at 98.2% after 10 test cycles, and an alcohol immersion disinfection treatment showed no effect on its filtration performance. In summary, the CA/TPU-LiCl nanofiber membrane made in this work is a promising biodegradable and reusable filtration material with a wide range of potential applications, including high-performance face mask.

Abstract Degumming is the dominant method to obtain lignocellulosic fibers in the textile industry. Traditionally, wet chemistry methods are used to monitor the evolution of major chemical components during the degumming process. However, these methods lack the ability to provide spatial information for these heterogeneous materials. In this study, besides wet chemistry and scanning electron microscopy (SEM) analysis, a Fourier-transform infrared microspectroscopy (FTIRM) method was employed to monitor the changes in spatial distribution of the main chemical components on the kenaf surface during a steam explosion followed by chemical degum process. The results showed that hemicellulose and lignin were degummed at different rates, and the mechanisms of their degumming are different. The infrared microspectral images revealed the distribution changes of chemical components on the fiber bundle surface during the process, indicating that FTIRM is an effective tool to analyze the degumming process and improve degumming methods.

Artemisia vulgaris is an economic plant that is spreading widely in central China. Its unused bast generates a large amount of biomass waste annually. Utilizing the fibers in Artemisia vulgaris bast may provide a new solution to this problem. This research attempts to strengthen the understanding of Artemisia vulgaris by analyzing its fiber compositions and preparing micro- and nano-cellulose fibers, which can be used as raw materials for composites. In this work, Artemisia vulgaris bast powder (AP) and microcellulose and nanocellulose fibers (AMFs and ANFs) were produced and characterized by optical microscopy, transmission electron microscopy (TEM), X-ray diffraction (XRD), thermogravimetric analysis (TG), and bacteriostatic test. The results indicated that cellulose, hemicellulose, and lignin were the main components in the Artemisia vulgaris bast. The cellulose content reached 40.9%. The Artemisia vulgaris single fibers were microcellulose fibers with an average length of 850.6 μm and a diameter of 14.4 μm. Moreover, the AMF had considerable antibacterial ability with an antibacterial ratio of 36.6%. The ANF showed a length range of 250−300 nm and a diameter of 10−20 nm, and it had a higher crystallinity (76%) and a lower thermal stability (initial degradation temperature of 183 °C) compared with raw ANF (233 °C). This study provides fundamental information on Artemisia vulgaris bast cellulose for its subsequent utilization.