Visualized Tracking and Multidimensional Assessing of Mitochondria-Associated Pyroptosis in Cancer Cells by a Small-Molecule Fluorescent Probe.

Pyroptosis is closely related to the development and treatment of various cancers; thus, comprehensive studies of the correlations between pyroptosis and its inductive or inhibitive factors can provide new ideas for the intervention and diagnosis of tumors. The dysfunction of mitochondria may induce pyroptosis in cancer cells, which can be reflected by the fluctuations of the microenvironmental parameters in mitochondria as well as the changes of mitochondrial DNA level and morphology, etc. To precisely track and assess the mitochondria-associated pyroptosis process, simultaneous visualization of changes in multiphysiological parameters in mitochondria is highly desirable. In this work, we reported a nonreaction-based, multifunctional small-molecule fluorescent probe Mito-DK with the capability of crosstalk-free response to polarity and mtDNA as well as mitochondrial morphology. Accurate assessment of mitochondria-associated pyroptosis induced by palmitic acid/H2O2 was achieved through monitoring changes in mitochondrial multiple parameters with the help of Mito-DK. In particular, the pyroptosis-inducing ability of an antibiotic doxorubicin and the pyroptosis-inhibiting capacity of an anticancer agent puerarin were evaluated by Mito-DK. These results provide new perspectives for visualizing mitochondria-associated pyroptosis and offer new approaches for screening pyroptosis-related anticancer agents.

A conserved viral amphipathic helix governs the replication site-specific membrane association.

Positive-strand RNA viruses assemble their viral replication complexes (VRCs) on specific host organelle membranes, yet it is unclear how viral replication proteins recognize and what motifs or domains in viral replication proteins determine their destinations. We show here that an amphipathic helix, helix B in replication protein 1a of brome mosaic virus (BMV), is necessary for 1a's localization to the nuclear endoplasmic reticulum (ER) membrane where BMV assembles its VRCs. Helix B is also sufficient to target soluble proteins to the nuclear ER membrane in yeast and plant cells. We further show that an equivalent helix in several plant- and human-infecting viruses of the Alsuviricetes class targets fluorescent proteins to the organelle membranes where they form their VRCs, including ER, vacuole, and Golgi membranes. Our work reveals a conserved helix that governs the localization of VRCs among a group of viruses and points to a possible target for developing broad-spectrum antiviral strategies.

Host GRXC6 restricts Tomato yellow leaf curl virus infection by inhibiting the nuclear export of the V2 protein.

Geminiviruses cause serious symptoms and devastating losses in crop plants. With a circular, single-stranded DNA genome, geminiviruses multiply their genomic DNA in the nucleus, requiring the nuclear shuttling of viral proteins and viral genomic DNAs. Many host factors, acting as proviral or antiviral factors, play key roles in geminivirus infections. Here, we report the roles of a tomato glutaredoxin (GRX), SlGRXC6, in the infection of Tomato yellow leaf curl virus (TYLCV), a single-component geminivirus. The V2 protein of TYLCV specifically and preferentially interacts with SlGRXC6 among the 55-member tomato GRX family that are broadly involved in oxidative stress responses, plant development, and pathogen responses. We show that overexpressed SlGRXC6 increases the nuclear accumulation of V2 by inhibiting its nuclear export and, in turn, inhibits trafficking of the V1 protein and viral genomic DNA. Conversely, the silenced expression of SlGRXC6 leads to an enhanced susceptibility to TYLCV. SlGRXC6 is also involved in symptom development as we observed a positive correlation where overexpression of SlGRXC6 promotes while knockdown of SlGRXC6 expression inhibits plant growth. We further showed that SlGRXC6 works with SlNTRC80, a tomato NADPH-dependent thioredoxin reductase, to regulate plant growth. V2 didn't interact with SlNTRC80 but competed with SlNTR80 for binding to SlGRXC6, suggesting that the V2-disrupted SlGRXC6-SlNTRC80 interaction is partially responsible for the virus-caused symptoms. These results suggest that SlGRXC6 functions as a host restriction factor that inhibits the nuclear trafficking of viral components and point out a new way to control TYLCV infection by targeting the V2-SlGRXC6 interaction.

RGD and Scutellarin Conjugate (WK001) Targeting Platelet Glycoprotein IIb/IIIa Receptor Protects from Myocardial Ischemia/Reperfusion Injury: Synthesis, Characterization, and Bioactivity Evaluation.

Myocardial ischemia/reperfusion (MI/R) injury is an unresolved clinical challenge. The blockade of binding fibrinogen by glycoprotein IIb/IIIa (GPIIb-IIIa) inhibitors has become a new therapeutic approach against MI/R injury. In this study, we modified the RGD structure to combine with scutellarin and synthesized a novel peptide, scutellarin-HomoArg-Gly-Asp-Trp-NH2 (WK001). Herein, reported experimental and docking evidence indicates that WK001 provides immediate and potent platelet inhibition, with stronger inhibition of platelet aggregation than eptifibatide and scutellarin. In particular, it is administered intravenously to prevent thrombus formation and attenuate myocardial fibrosis progression in vivo. Therefore, WK001 could be developed as an antiplatelet drug to treat thrombosis-associated diseases, such as stroke and myocardial infarction.

Optical bistability in a heterodimer composed of a quantum dot and a metallic nanoshell.

We theoretically explore the conditions for generating optical bistability (OB) in a heterodimer comprised of a semiconductor quantum dot (SQD) and a metallic nanoshell (MNS). The MNS is made of a metallic nanosphere as a core and a dielectric material as a shell. For the specific hybrid system considered, the bistable effect appears only if the frequency of the pump field is equal to (or slightly less than) the exciton frequency for a proper shell thickness. Bistability phase diagrams, when plotted, show that the dipole-induced bistable region can be greatly broadened by changing the shell thickness of the MNS in a strong exciton-plasmon coupling regime. In particular, we demonstrate that the multipole polarization not only narrows the bistable zone but also enlarges the corresponding thresholds for a given intermediate scaled pumping intensity. On the other hand, when the SQD couples strongly with the MNS, the multipole polarization can also significantly broaden the bistable region and induce a great suppression of the FWM (four-wave mixing) signal for a fixed shell thickness. These interesting findings offer a fresh understanding of the bistability conditions in an SQD/MNS heterodimer, and may be useful in the fabrication of high-performance and low-threshold optical bistable nanodevices.

The applicability of the Second Revision of the International Staging System for patients with multiple myeloma receiving immunomodulatory drugs or proteasome inhibitor-based regimens as induction treatment: A real-world analysis.

The Second Revision of the International Staging System (R2-ISS) was recently introduced to improve risk stratification over that provided by the extensively applied standard revised International Staging System (R-ISS). In addition to the variables included in the R-ISS, the R2-ISS incorporates chromosome 1q gain/amplification and divides the patients into 4 groups with different survival outcomes, better stratifying patients within the R-ISS intermediate-risk. The new model was developed based on a great quantity of data from patients participating in uniform clinical trials and has not been validated in real-world clinical practice. Therefore, we retrospectively analyzed the prognostic value of the R2-ISS in 474 consecutive patients with multiple myeloma receiving immunomodulatory drugs or proteasome inhibitor-based regimens as their first-line treatment. According to the R2-ISS, 41 (8.6%), 76 (16%), 275 (58%), and 82 (17.3%) patients were identified as R2-ISS I, R2-ISS II, R2-ISS III, and R2-ISS IV, respectively. The median progression-free survival (PFS) was 48 (95% CI: 38-58), 35 (95% CI: 23-47), 24 (95% CI: 21-27), and 12 (95% CI: 7-17) months, and the estimated median overall survival (OS) was 110 (95% CI: 42-178), 88 (95% CI: 75-101), 50 (95% CI: 43-57), and 26 (95% CI: 19-33) months (p < 0.001) in the 4 groups, respectively. The R2-ISS could also classify groups with distinct survival among patients with renal impairment or classified as R-ISS II. Adjusted by age, sex, treatment approaches and transplantation status, the R2-ISS was an independent prognostic factor associated with OS with a hazard ratio of 7.055 (95% CI: 3.626-13.726) (p < 0.001) for R2-ISS IV versus R2-ISS I and 2.707 (95% CI: 1.436-5.103) (p = 0.002) for R2-ISS III versus R2-ISS I. In conclusion, our results suggest that the R2-ISS is a simple and robust risk stratification tool for patients with multiple myeloma treated with novel drugs and could be used in everyday clinical practice.

Accurate Prediction of Soil Heavy Metal Pollution Using an Improved Machine Learning Method: A Case Study in the Pearl River Delta, China.

In traditional soil heavy metal (HM) pollution assessment, spatial interpolation analysis is often carried out on the limited sampling points in the study area to get the overall status of heavy metal pollution. Unfortunately, in many machine learning spatial information enhancement algorithms, the additional spatial information introduced fails to reflect the hierarchical heterogeneity of the study area. Therefore, we designed hierarchical regionalization labels based on three interpolation techniques (inverse distance weight, ordinary kriging, and trend surface interpolation) as new spatial covariates for a machine learning (ML) model. It was demonstrated that regional spatial information improved the prediction performance of the model (R2 > 0.7). On the basis of the prediction results, the status of HM pollution in the Pearl River Delta (PRD) region was evaluated: cadmium (Cd) and copper (Cu) were the most serious pollutants in the PRD (the point overstandard rates are 18.77% and 12.95%, respectively). The analysis of index importance and bivariate local indicators of spatial association (LISA) shows that the key factors affecting the spatial distribution of heavy metals are geographical and climatic conditions [namely, altitude, humidity index, and normalized vegetation difference index (NDVI)] and some industrial activities (such as metal processing, printing and dyeing, and electronics industry). This study develops a novel approach to improve existing spatial interpolation techniques, which will enable more precise and scientific soil environmental management.

Fermi-level shift, electron separation, and plasmon resonance change in Ag nanoparticle-decorated TiO2 under UV light illumination.

Noble metal nanoparticles are widely used as co-catalysts for storing and separating electrons in semiconductor photocatalysis. Thus, evaluating this ability is important and meaningful to understand the photocatalytic mechanism. Employing Ag nanoparticles, the present study combined in situ photoconductance and theoretical analysis to evaluate the Fermi-level (EF) shift in a UV-illuminated Ag/TiO2 system under gaseous conditions. Based on this, the role of the Ag nanoparticles in storing and separating electrons was discussed. It was found that the EF of Ag/TiO2 is located deeper in the gap and a variation in temperature has less effect on the EF of Ag/TiO2 compared to the undecorated TiO2. The analysis showed that ∼46 electrons can be stored in 10 nm Ag nanoparticles under our experimental conditions, which does not change with temperature. The electron traps in TiO2 can affect the electron distribution in the TiO2 and Ag nanoparticles. It was observed that the localized surface plasmon resonance (LSPR) of the Ag nanoparticles exhibited a blue-shift under UV light illumination, which is generally ascribed to the electron storage in the Ag nanoparticles. However, we showed that the blue-shift is not related to the electron storage in the Ag nanoparticles, and thus it cannot be used as an indicator for evaluating their electron-storage ability. The in situ XPS analysis also does not support that the LSPR blue shift is associated with the reduction in the Ag2O layer and TiO2.

Digital mapping of soil organic carbon density in China using an ensemble model.

The soil organic carbon stock (SOCS) is considered as one of the largest carbon reservoirs in terrestrial ecosystems, and small changes in soil can cause significant changes in atmospheric CO2 concentration. Understanding organic carbon accumulation in soils is crucial if China is to meet its dual carbon target. In this study, the soil organic carbon density (SOCD) in China was digitally mapped using an ensemble machine learning (ML) model. First, based on SOCD data obtained at depths of 0-20 cm from 4356 sampling points (15 environmental covariates), we compared the performance of four ML models, namely random forest (RF), extreme gradient boosting (XGBoost), support vector machine (SVM), and artificial neural network (ANN) models, in terms of coefficient of determination (R2), mean absolute error (MAE), and root mean square error (RMSE) values. Then, we ensembled four models using Voting Regressor and the principle of stacking. The results showed that ensemble model (EM) accuracy was high (RMSE = 1.29, R2 = 0.85, MAE = 0.81), so that it could be a good choice for future research. Finally, the EM was used to predict the spatial distribution of SOCD in China, which ranged from 0.63 to 13.79 kg C/m2 (average = 4.09 (±1.90) kg C/m2). The SOC storage amount in surface soil (0-20 cm) was 39.40 Pg C. This study developed a novel, ensemble ML model for SOC prediction, and improved our understanding of the spatial distribution of SOC in China.

Comparison and application of SOFM, fuzzy c-means and k-means clustering algorithms for natural soil environment regionalization in China.

Soil attributes and their environmental drivers exhibit different patterns in different geographical directions, along with distinct regional characteristics, which may have important effects on substance migration and transformation such as organic matter and soil elements or the environmental impacts of pollutants. Therefore, regional soil characteristics should be considered in the process of regionalization for environmental management. However, no comprehensive evaluation or systematic classification of the natural soil environment has been established for China. Here, we established an index system for natural soil environmental regionalization (NSER) by combining literature data obtained based on bibliometrics with the analytic hierarchy process (AHP). Based on the index system, we collected spatial distribution data for 14 indexes at the national scale. In addition, three clustering algorithms-self-organizing feature mapping (SOFM), fuzzy c-means (FCM) and k-means (KM)-were used to classify and define the natural soil environment. We imported four cluster validity indexes (CVI) to evaluate different models: Davies-Bouldin index (DB), Silhouette index (Sil) and Calinski-Harabasz index (CH) for FCM and KM, clustering quality index (CQI) for SOFM. Analysis and comparison of the results showed that when the number of clusters was 13, the FCM clustering algorithm achieved the optimal clustering results (DB = 1.16, Sil = 0.78, CH = 6.77 × 106), allowing the natural soil environment of China to be divided into 12 regions with distinct characteristics. Our study provides a set of comprehensive scientific research methods for regionalization research based on spatial data, it has important reference value for improving soil environmental management based on local conditions in China.

Clinical, Radiographic and Fusion Comparison of Oblique Lumbar Interbody Fusion (OLIF) stand-alone and OLIF with posterior pedicle screw fixation in patients with degenerative spondylolisthesis.

PURPOSE: To compare the outcomes and characteristics of oblique lumbar interbody fusion stand-alone (OLIF-SA) and OLIF with posterior pedicle screw fixation (OLIF-PPS) in the treatment of Grade I or Grade II degenerative lumbar spondylolisthesis. PATIENTS AND METHODS: Between January 2019 and May 2022, 139 patients with degenerative spondylolisthesis were treated with OLIF-SA (n = 85) or OLIF-PPS (n = 54). The clinical and radiographic records were reviewed. RESULTS: The clinical and radiographic outcomes were similar in both groups. The operative time and intraoperative blood loss in the OLIF-SA group were lower than those in the OLIF-PPS group (P < 0.05). However, the OLIF-PPS group had significantly better disc height (DH) and postoperative forward spondylolisthesis distance (FSD) improvement at 6 months (P < 0.05). The OLIF-PPS group had a significantly lower cage subsidence value than the OLIF-SA group (P < 0.05). Improvement of the lumbar lordotic angle (LA) and fusion segmental lordotic angle (FSA) in the OLIF-PPS group was significantly better than that in the OLIF-SA group (P < 0.05). In terms of fusion types, the OLIF-SA group tended to undergo fusion from the edge of the vertebral body. Fusion in the OLIF-PPS group began more often in the bone graft area of the central cage of the vertebral body. The fusion speed of the OLIF-SA group was faster than that of the OLIF-PPS group. CONCLUSION: OLIF-SA has the advantages of a short operative time, less intraoperative blood loss, and reduced financial burden, while PPS has incomparable advantages in the reduction of spondylolisthesis, restoration of lumbar physiological curvature, and long-term maintenance of intervertebral DH. In addition, the SA group had a unique vertebral edge fusion method and faster fusion speed.

High-Precision Carton Detection Based on Adaptive Image Augmentation for Unmanned Cargo Handling Tasks.

Unattended intelligent cargo handling is an important means to improve the efficiency and safety of port cargo trans-shipment, where high-precision carton detection is an unquestioned prerequisite. Therefore, this paper introduces an adaptive image augmentation method for high-precision carton detection. First, the imaging parameters of the images are clustered into various scenarios, and the imaging parameters and perspectives are adaptively adjusted to achieve the automatic augmenting and balancing of the carton dataset in each scenario, which reduces the interference of the scenarios on the carton detection precision. Then, the carton boundary features are extracted and stochastically sampled to synthesize new images, thus enhancing the detection performance of the trained model for dense cargo boundaries. Moreover, the weight function of the hyperparameters of the trained model is constructed to achieve their preferential crossover during genetic evolution to ensure the training efficiency of the augmented dataset. Finally, an intelligent cargo handling platform is developed and field experiments are conducted. The outcomes of the experiments reveal that the method attains a detection precision of 0.828. This technique significantly enhances the detection precision by 18.1% and 4.4% when compared to the baseline and other methods, which provides a reliable guarantee for intelligent cargo handling processes.

Near-Space Wide-Area and High-Resolution Imaging System Design and Implementation.

The near-space atmosphere is thin, and the atmospheric refraction and scattering on optical observation is very small, making it very suitable for wide-area and high-resolution surveillance using high-altitude balloon platforms. This paper adopts a 9344 × 7000 CMOS sensor to obtain high-resolution images, generating large-field-of-view imaging through the swing scanning of the photoelectric sphere and image stitching. In addition, a zoom lens is designed to achieve flexible applications for different scenarios, such as large-field-of-view and high-resolution imaging. The optical design results show that the camera system has good imaging quality within the focal length range of 320 mm-106.7 mm, and the relative distortion values at different focal lengths are less than 2%. The flight results indicate that the system can achieve seamless image stitching at a resolution of 0.2 m@20 km and the imaging field of view angle exceeds 33°. This system will perform other near-space flight experiments to verify its ultra-wide (field of view exceeding 100°) high-resolution imaging application.

Managing Secondary Phase Lead Iodide in Hybrid Perovskites via Surface Reconstruction for High-Performance Perovskite Solar Cells with Robust Environmental Stability.

Rationally managing the secondary-phase excess lead iodide (PbI2 ) in hybrid perovskite is of significance for pursuing high performance perovskite solar cells (PSCs), while the challenge remains on its conversion to a homogeneous layer that is robust stable against environmental stimuli. We herein demonstrate an effective strategy of surface reconstruction that converts the excess PbI2 into a gradient lead sulfate-silica bi-layer, which substantially stabilizes the perovskite film and reduces interfacial charge transfer barrier in the PSCs device. The perovskite films with such bi-layer could bear harsh conditions such as soaking in water, light illumination at 70 % relative humidity, and the damp-thermal (85 °C and 30 % humidity) environment. The resulted PSCs deliver a champion efficiency up to 24.09 %, as well as remarkable environmental stability, e.g., retaining 78 % of their initial efficiency after 5500 h of shelf storage, and 82 % after 1000 h of operational stability testing.

Multi-focus image fusion algorithm based on random features embedding and ensemble learning.

Multi-focus image fusion algorithm integrates complementary information from multiple source images to obtain an all-in-focus image. Most published methods will create incorrect points in their decision map which have to be refined and polished with post-processing procedure. Aim to address these problems, we present, for the first time, a novel algorithm based on random features embedding (RFE) and ensemble learning which reduced the calculation workload and improved the accuracy without post-processing. We utilize RFE to approximate a kernel function so that Support Vector Machine (SVM) can be applied to large scale data set. With ensemble learning scheme we then eliminate the abnormal points in the decision map. We reduce the risk of entrap into over-fitting predicament and boost the generalization ability by combining RFE and ensemble learning. The theoretical analysis is in consistence with the experimental results. With low computation cost, the proposed algorithm achieve high visual quality as the state-of-the-art(SOTA).

Hydrophobic microporous extraction on polyurethane sponges for convenient and sensitive analysis of organic molecules in water.

RATIONALE: Various solvent supports have been developed to overcome solvent instability during liquid-phase microextraction. The hydrophobic polyurethane sponge (PS) possesses numerous cross-linked internal microchannels and terminal micropores that can facilitate steady solvent storage capacity, high extraction efficiency, extractant loading, and recycling convenience. METHODS: In this study, an easy, convenient, and efficient PS-supported liquid-phase microextraction (PS-LPME) coupled with gas chromatography-mass spectrometry (GC-MS) method was developed for the trace analysis of different organic compounds in aqueous solutions. Different extraction solvents, PS dosages, stirring speeds, and extraction times were first investigated by extracting eight polycyclic aromatic hydrocarbons (PAHs: naphthalene, acenaphthylene, acenaphthene, fluorene, phenanthrene, anthracene, fluoranthene, and pyrene), and then applied for the analysis of triazines, amides, chloroacetamides, and organophosphorus compounds. RESULTS: High enrichment factors (approximately 208-439) were observed for the monitored PAHs. Good linearities, with determination coefficients (r2 ) greater than 0.9992, were achieved in the concentration range of 0.01-50 µg L-1 . Low limits of detection and quantification were found in the ranges of 0.3-3 ng L-1 and 1-10 ng L-1 , respectively. At three spiked concentrations (0.1, 1, and 10 µg L-1 ), good recoveries were obtained in the range of 91.6-118.5% with intra- and inter-day relative standard deviations of less than 6.4% and 11.7%, respectively. CONCLUSIONS: The developed PS-LPME method coupled with GC-MS was successfully applied in the analysis of different organic compounds in aqueous solutions and has shown great convenience and satisfactory enrichment performance in microextraction analysis.

Human health risk-based Generic Assessment Criteria for agricultural soil in Jiangsu and Zhejiang provinces, China.

Agricultural soil pollution in China poses a major threat to human health and food safety. There are no agricultural soil environmental standards based on human health in China, which prevents effective screening and assessment of risks. Jiangsu (JS) and Zhejiang (ZJ) provinces, located in the Yangtze River Delta (YRD) core region, have obvious differences in agricultural land conditions, which will result in differences in Generic Assessment Criteria (GAC). In this study, we derived and compared human health risk-based GAC using the Contaminated Land Exposure Assessment (CLEA) model for agricultural land scenarios in these two provinces. We found differences in the GAC between JS and ZJ due to differences in parameters. These differences are greatest for benzene, and cadmium (Cd). For Cd, the contribution of oral intake exceeds 90 %, and the vegetable consumption rate and mean daily intake (MDI) may be key parameters affecting GAC. For the volatile organic compound benzene, the inhalation of indoor vapor accounts for about 30 %, and the key parameters affecting the GAC for benzene may be the attenuation factor and soil organic matte (SOM). The derived GAC are generally lager (i.e., less stringent) than the GB15618-2018 and UK Suitable 4 Use Levels (S4ULs); however, the derived GAC for JS and ZJ were lower than the soil screening values (SSV) for residential land in China. This may be related to methods, land use types, and critical receptors. This work will contribute to the development of regional soil environmental standards in China.

Human health risk-based soil environmental criteria (SEC) for park soil in Beijing, China.

Urban parks are important places that allow urban residents to experience nature but are also associated with the risk of exposure to contaminated soil. Therefore, it is necessary to establish appropriate soil environment criteria (SEC) to manage park soil quality. Studies on the demographic characteristics and behavioral patterns of urban park visitors are helpful for the selection of sensitive receptors and the determination of parameters in the establishment of SEC. This study explored the park visitors' demographic characteristics and behavioral patterns, and applied the results to derive SEC. Eighty-six parks in Beijing were selected, and mobile phone data were obtained to analysis the demographic characteristics and residence time of the visitors. Kruskal-Wallis test, kernel density estimation and random forest model were used for data analysis. The CLEA model was used to derive SEC. The results showed that the demographic characteristics and behavioral patterns of visitors in different types of parks were quite different. Parks were mostly used by males and visitors aged 31-45. Most visitors stayed in the park for 1-2 h, and the distance from a given visitor's home to the park was the most important factor affecting stay time. Then, several parameters such as the parameters related to the receptors and occupation period were optimized, and the SEC of sensitive parks and non-sensitive parks were derived. Exposure frequency may be the main reason for the difference of SEC between the two types of parks. The SECs of sensitive parks were higher than the soil screening values (SSVs) for class 1 land in GB36600-2018, indicating that the current SSVs for some parks may be too conservative. This study provides a reference for the formulation and revision of soil environmental standards for park land, and suggests strengthening research on human behavioral patterns.

Characters and environmental driving factors of bacterial community in soil of Beijing urban parks.

In an era of unprecedented human influence, different human activities have different degrees of impact on specific bacteria, resulting in the regional biological homogenization of soil bacteria. However, the contribution of the impact that a large number of anthropogenic activities on bacteria remains unknown. Here, by high-throughput amplicon sequencing, we characterized the composition, diversity and influencing factors of soil microbes in Beijing urban parks at geographic space and park management aspect. It is the first time to quantify and compare the importance of the impact of up to 15 human activities on soil bacterial communities. The results show that the dominant bacterial phyla in Beijing urban parks were Actinobacteria, Proteobacteria, Acidobacteria and Chloroflexi. The environmental management of different park types, as well as the land use history and development conditions of different regions, had significant differences in soil bacterial community structure. Soil bacteria in urban parks were disturbed by direct human interference far more than natural causes. The most important factors were related to the number of tourists and residents, industrial production and land use patterns. These factors may also be related to the abundance of unknown bacteria in urban parks. This also directly shows that human activities have a non-negligible impact on soil bacteria. The ways in which different human activities brought by global urbanization and their impacting mechanisms are used should be the starting point of future research.

Asthma susceptibility in prenatal nicotine-exposed mice attributed to ß-catenin increase during CD4+ T cell development.

Cigarette smoke is a common global environmental pollutant. Asthma, the most frequent allergic airway disease, is related to maternal exposure to cigarette smoke. Our previous studies demonstrated that prenatal exposure to nicotine (PNE), the major active product of smoking, impairs fetal thymopoiesis and CD4+ T cell development after birth. This study aimed to investigate whether PNE contributes to asthma susceptibility through CD4+ T cell development alterations. First, A PNE model was established by administering 3 mg/kg/day nicotine to maternal mice, and then an ovalbumin-induced asthma model was established in the offspring. Further, ß-catenin and downstream pathways were inhibited in vitro to confirm the molecular mechanisms underlying the phenotype observed during the in vivo phase. The results showed that PNE induced Th2 and Th17 biases at developmental checkpoints and aggravated asthma symptoms in the offspring. In fetuses, PNE up-regulated α7 nAChR, activated PI3K-AKT, promoted ß-catenin level increase, and established potential Th2- and Th17-biased gene expression patterns during thymopoiesis, which persisted after birth. Similar results were also observed in 1 µM nicotine-treated thymocytes in vitro. Moreover, inhibiting PI3K-AKT by LY294002 abrogated nicotine-mediated ß-catenin level increase and thymopoiesis abnormalities, and an α7 nAChR antagonist (α-btx) also reversed nicotine-induced PI3K-AKT activation. Our findings provide strong evidence that PNE is a risk factor for T cell deviation and postnatal asthma, and revealed that nicotine-induced ß-catenin level increase induces thymopoiesis abnormalities.