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Exploring the cross-sensitivity between land use transformation and ecological service values in rare earth mining areas is of great significance for the development of ecological protection and restoration in rare earth mining areas. To study the impact of land use changes on ecosystem service functions in rare earth mining areas, firstly, the land use change trends in the study area from 2009 to 2019 were analyzed using the land transfer matrix; then the distribution of ecosystem service values and the flow direction of ecosystem service values in the study area were measured based on the ecosystem service value equivalents; a spatial autocorrelation analysis was done on the ecosystem service values to explore their spatial distribution patterns; and finally, the cross-sensitivity coefficient was used to quantitatively assess the extent and direction of the impact of land use change on ecosystem service values. The results show that the land use types in the study area are mainly forest land and farmland, with woodland accounting for the highest proportion of the study area. The ESV changes in the study area are consistent with the trend of land use transformation, with the overall increase and decrease being comparable, and the decrease in ESV is mainly concentrated in the areas with a large increase in mining land and construction land; during the study period, the study area was significantly reduced with low—low cluster areas and the ecological environment was improved; from 2009 to 2014, the ecological sensitivity coefficient is more variable, and is more sensitive to the net conversion between water and desert, from 2014 to 2019, the ecological sensitivity coefficient is less variable, and the most sensitive is the net conversion between cultivated land and water. The study area should be reasonably developed for rare earth resources and the ecological environment around the mining area should be reasonably protected to build an ecological security pattern.

Resveratrol is widely used in the fields of medicine and health supplements; however, its poor stability and low relative bioavailability limit its applications. This study aimed to compare the plasma drug concentrations and key pharmacokinetic parameters of two resveratrol solid formulations, T1 and T2. A single-center, randomized, open-label, two-formulation, single-dose, two-period, crossover trial was conducted involving 12 healthy subjects. Blood samples were collected after a single dose for pharmacokinetic (PK) analysis, including C max , AUC 0 − t , AUC 0−∞ , T max , and T 1/2 . The concentrations of resveratrol and its metabolites in human plasma were determined using HPLC-MS/MS. The results showed for total resveratrol, the C max of T1 was 4.8 times higher than that of T2, while the AUC 0 − t of T1 was 1.7 times that of T2. The T max of T1 was also markedly shorter, whereas the t 1/2 of T2 was slightly longer than that of T1. This suggests that T1 demonstrated superior absorption extent and rate, with overall pharmacokinetic performance surpassing that of T2. In addition, all drugs were well tolerated, no severe adverse reactions occurred. In conclusion, following single-dose oral administration of the two resveratrol formulations, T1 and T2, both formulations were demonstrating good safety profiles. Compared to T2, the modified formulation of T1 significantly enhanced the absorption rate, extent, and relative bioavailability of resveratrol. The test formulation T1 was overall superior to the test formulation T2.

Olanzapine is associated with a high risk of hepatic steatosis as a commonly used atypical antipsychotic. In this study, we observed differential susceptibility to olanzapine‐induced fatty liver disease in both rats and patients. Notably, patients with olanzapine‐induced liver damage exhibited an altered gut microbiota composition, with Akkermansia muciniphila showing the most pronounced alteration. To explore its therapeutic potential, we administered A. muciniphila to olanzapine‐treated rats, which significantly reduced hepatic lipid accumulation and liver injury. Gut microbiome analysis revealed significant alterations in microbial diversity and composition following A. muciniphila treatment. Transcriptomic analysis further identified differentially expressed genes in the liver, highlighting the involvement of IGFBP2 and APOA1 in the protective effects of A. muciniphila . Functional validation demonstrated that overexpression of IGFBP2 and APOA1 alleviated olanzapine‐induced hepatic steatosis in both cellular and animal models. These findings suggest that A. muciniphila exerts hepatoprotective effects via the gut microbiota‐IGFBP2/APOA1‐liver axis, offering a potential microbiota‐targeted strategy to mitigate olanzapine‐induced metabolic dysfunction. Olanzapine induces hepatic steatosis with differential susceptibility observed in both rats and patients, while A. muciniphila alleviates liver lipid accumulation and injury by modulating gut microbiota and hepatic gene expression. Overexpression of IGFBP2 and APOA1 further protects against olanzapine‐induced hepatic steatosis.

In intelligent meter reading and other applications, power line communication can use relay technology to solve the problem of cross-station or long-distance reliable communication. This study investigates the combined impact of the physical and Media Access Control (MAC) layers on power line relay communication system performance. To this end, cross-layer modeling, optimization, and simulation analysis integrating both layers are conducted. Based on the CSMA algorithm of IEEE 1901 protocol, a cross-layer performance analysis model of two-hop relay power line communication system is established considering the influence of non-ideal channel transmission at physical layer and competitive access at MAC layer on system performance. In order to reduce the high collision probability caused by two competitions of packets in the above scheme, an improved two-hop transmission algorithm based on CSMA-TDMA is proposed. The cross-layer performance of the system under different single-hop and two-hop schemes is compared, and the mechanism of how parameters such as the MAC layer and the physical layer affect the cross-layer performance of the power line communication system is analyzed. And the optimal power allocation factor is obtained by using the sequential quadratic programming method for the joint system throughput and packet loss rate optimization model with the two-hop power constraint. Simulation results show that the two-hop transmission scheme based on CSMA-TDMA can avoid the second-hop competition and backoff process, and has better performance in terms of throughput, packet loss rate, and delay.

Due to the increase in bacterial resistance, improving the anti-infectious immunity of the host is rapidly becoming a new strategy for the prevention and treatment of bacterial pneumonia. However, the specific lung immune responses and key immune cell subsets involved in bacterial infection are obscure. Actinobacillus pleuropneumoniae (APP) can cause porcine pleuropneumonia, a highly contagious respiratory disease that has caused severe economic losses in the swine industry. Here, using high-dimensional mass cytometry, the major immune cell repertoire in the lungs of mice with APP infection was profiled. Various phenotypically distinct neutrophil subsets and Ly-6C + inflammatory monocytes/macrophages accumulated post-infection. Moreover, a linear differentiation trajectory from inactivated to activated to apoptotic neutrophils corresponded with the stages of uninfected, onset, and recovery of APP infection. CD14 + neutrophils, which mainly increased in number during the recovery stage of infection, were revealed to have a stronger ability to produce cytokines, especially IL-10 and IL-21, than their CD14 − counterparts. Importantly, MHC-II + neutrophils with antigen-presenting cell features were identified, and their numbers increased in the lung after APP infection. Similar results were further confirmed in the lungs of piglets infected with APP and Klebsiella pneumoniae infection by using a single-cell RNA-seq technique. Additionally, a correlation analysis between cluster composition and the infection process yielded a dynamic and temporally associated immune landscape where key immune clusters, including previously unrecognized ones, marked various stages of infection. Thus, these results reveal the characteristics of key neutrophil clusters and provide a detailed understanding of the immune response to bacterial pneumonia.

Single-cell encapsulation, by constructing cell-scale microenvironments, enables precise protection, regulation, and functional enhancement of individual cells, holding significant importance in biomedical fields such as bioanalysis and cell therapy. Although various materials—including polymers, nanoparticles, hydrogels, polyphenols, and inorganic minerals—have been explored for single-cell encapsulation, limitations in controllability, biocompatibility, and multifunctional integration remain. In contrast, DNA nanomaterials offer unique advantages, including programmable architecture, high biocompatibility, precise spatial control, and modular functionality, making them highly suitable for the development of intelligent single-cell encapsulation systems. In this review, a systematic summary of recent advances in DNA nanomaterial-based single-cell encapsulation is presented. The fundamental encoding and assembly principles underlying the engineered encapsulation of cells at the membrane interface using DNA nanostructures are elucidated. Subsequently, the distinctive merits of DNA-based cell encapsulation and its applications in biomedical research are comprehensively summarized. Finally, the prevailing challenges and future directions in this burgeoning field are critically discussed, aiming to provide novel insights and perspectives for the advancement of advanced functional materials in both academic and clinical research pertaining to single-cell encapsulation.

IL-21/IL-21R signaling is crucial in various immune diseases and cellular development, however, its role in bacterial pneumonia remains unclear. Here, IL-21R knockout (IL-21R − /− ) mice were more susceptible to Actinobacillus pleuropneumoniae (APP) than wild-type (WT) mice. High-dimensional mass cytometry analysis revealed that IL-21R deficiency inhibited neutrophil activation, decreased the numbers of monocytes and proinflammatory macrophages, and augmented the defective CD3 low T cells in the lungs. Intracellular cytokine staining showed decreased IFN-γ/TNF-α/IL-6 production in IL-21R − /− mice, particularly in CD8⁺ T cells. Furthermore, a previously unrecognized Ly6C + Ly6G + CD4 + T cell subset emerged only in the lungs of WT mice post-APP infection, which was in an activated status with stronger secretion capacities of IL-10, IL-21, granzyme B, and perforin by flow cytometry. These cells polarized macrophages into M2- or M1- phenotype without/with infection, respectively, and enhanced proliferation, phagocytosis, and macrophage extracellular traps/ROS-mediated bactericidal activity of macrophages against-APP, Klebsiella pneumoniae , or Escherichia coli infection. Thus, our study demonstrated that IL-21 drives the differentiation of neutrophils, monocytes, and macrophages into pro-inflammatory subsets. IL-21-induced Ly6C + Ly6G + CD4 + T cells cooperate with macrophages to enhance bacterial clearance, providing a promising target for preventing bacterial pneumonia.

Implant surfaces with a nanoscaled pattern can dominate the blood coagulation process resulting in a defined clot structure and its degradation behavior, which in turn influence cellular response and the early phase of osseointegration. Long non-coding (Lnc) RNAs are known to regulate many biological processes in the skeletal system; however, the link between the LncRNA derived from the cells within the clot and osseointegration has not been investigated to date. Hence, the sequence analysis of LncRNAs expressed within the clot formed on titania nanotube arrays (TNAs) with distinct nano-scaled diameters (TNA 15 of 15 nm, TNA 60 of 60 nm, TNA 120 of 120 nm) on titanium surfaces was profiled for the first time. LncRNA LOC103346307, LOC103352121, LOC108175175, LOC103348180, LOC108176660, and LOC108176465 were identified as the pivotal players in the early formed clot on the nano-scaled surfaces. Further bioinformatic prediction results were used to generate co-expression networks of LncRNAs and mRNAs. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analyses revealed that distinct nano-scaled surfaces could regulate the biological functions of target mRNAs in the clot. LOC103346307, LOC108175175, and LOC108176660 upregulated mRNAs related to cell metabolism and Wnt, TGF-beta, and VEGF signaling pathways in TNA 15 compared with P-Ti, TNA 60, and TNA 120, respectively, whereas LOC103352121, LOC103348180, and LOC108176465 downregulated mRNAs related to bone resorption and inflammation through negatively regulating osteoclast differentiation, TNF, and NF-kappa signaling pathways. The results indicated that surface nano-scaled characteristics can significantly influence the clot-derived LncRNAs expression profile, which affects osseointegration through multiple signaling pathways of the targeted mRNAs, thus paving a way for better interpreting the link between the properties of a blood clot formed on the nano-surface and de novo bone formation.

Precise and reliable monthly runoff prediction plays a vital role in the optimal management of water resources, but the nonstationarity and skewness of monthly runoff time series can pose major challenges for developing appropriate prediction models. To address these issues, this paper proposes a novel hybrid prediction model by introducing variational mode decomposition (VMD) and Box–Cox transformation (BC) into the Elman neural network (Elman), named the VMD-BC-Elman model. First, the observed runoff is decomposed into sub-time series using VMD for better frequency resolution. Second, the input datasets are transformed into a normal distribution using Box–Cox, and as a result, skewedness in the data is removed, and the correlation between the input and output variables is enhanced. The proposed VMD-BC preprocessing technology is expected to overcome the problems arising from nonstationary and skewed runoff data. Finally, Elman is used to simulate the respective sub-time series. The proposed model is evaluated using monthly runoff time series at Zhangjiashan, Zhuangtou and Huaxian hydrological stations in the Wei River Basin in China. The model performances are compared with those of single models (SVM, Elman), decomposition-based (VMD-SVM, VMD-Elman et al.) and BC-based models (BC-SVM and BC-Elman) by employing four metrics. The results show that the hybrid models outperform single models, and the VMD-BC-Elman model performs best in all considered hybrid models with an NSE greater than 0.95, R greater than 0.98, NMSE less than 4.7%, and PBIAS less than 0.4% in both the training and testing periods. The study indicates that the VMD-BC-Elman model is a satisfactory data-driven approach to predict nonstationary and skewed monthly runoff time series, representing an effective tool for predicting monthly runoff series.