Search

Poplar (PopulusL.) is one of the most widely distributed tree species planted in the plains of China and plays an important role in wood products and ecological services. Accurate estimation of poplar Growing Stock Volume (GSV) is crucial for better understanding the ecological functions and economic values in plain regions. However, the striped distribution feature of poplar forests in plain regions makes traditional grid-based GSV modeling methods highly uncertain. This research took Lixin County and Yongqiao District as case studies to examine the advantages of using object-based GSV modeling approach over the traditional grid-based approaches for poplar GSV estimation. The canopy height variables and density variables were extracted from airborne LIDAR-derived Canopy Height Model (CHM) data through different grid sizes and segmentation unit for constructing the poplar GSV estimation models using the linear regression. The results indicate that (1) Significantly linear relationships exist between GSV and height percentile variables; (2) The estimation accuracy in Lixin can be effectively improved by incorporating the CHM density variables into height variables, with the coefficient of determination (R2) increasing from 0.46 to 0.71 and Root Mean Square Error (RMSE) decreasing from 20.23 to 14.94 m3/ha when a grid-based approach was implemented at grid size of 26 m by 26 m (plot size). However, CHM density variables have no effect on estimation modeling in Yongqiao district. The patch sizes and shapes considerably affect the selection of modeling variables and accuracy of modeling prediction; (3) The object-based mapping approach outperforms the grid-based approach in solving the mixed plot problem. This is especially valuable in the study areas with striped forest distribution. This study shows that differences in poplar stand structure affect the selection of modeling variables and GSV modeling performance, and an object-based modeling approach is recommended for GSV estimation in the plain areas.

Neural network pruning is a popular approach to reducing the computational complexity of deep neural networks. In recent years, as growing evidence shows that conventional network pruning methods employ inappropriate proxy metrics, and as new types of hardware become increasingly available, hardware-aware network pruning that incorporates hardware characteristics in the loop of network pruning has gained growing attention. Both network accuracy and hardware efficiency (latency, memory consumption, etc.) are critical objectives to the success of network pruning, but the conflict between the multiple objectives makes it impossible to find a single optimal solution. Previous studies mostly convert the hardware-aware network pruning to optimization problems with a single objective. In this paper, we propose to solve the hardware-aware network pruning problem with Multi-Objective Evolutionary Algorithms (MOEAs). Specifically, we formulate the problem as a multi-objective optimization problem, and propose a novel memetic MOEA, namely HAMP, that combines an efficient portfolio-based selection and a surrogate-assisted local search, to solve it. Empirical studies demonstrate the potential of MOEAs in providing simultaneously a set of alternative solutions and the superiority of HAMP compared to the state-of-the-art hardware-aware network pruning method.

Abstract Kidney fibrosis is considered to be the ultimate aggregation pathway of chronic kidney disease (CKD), but its underlying mechanism remains elusive. Protein kinase C-delta (PKC-δ) plays critical roles in the control of growth, differentiation, and apoptosis. In this study, we found that PKC-δ was highly upregulated in human biopsy samples and mouse kidneys with fibrosis. Rottlerin, a PKC-δ inhibitor, alleviated unilateral ureteral ligation (UUO)-induced kidney fibrosis, inflammation, VDAC1 expression, and cGAS-STING signaling pathway activation. Adeno-associated virus 9 (AAV9)-mediated VDAC1 silencing or VBIT-12, a VDAC1 inhibitor, attenuated renal injury, inflammation, and activation of cGAS-STING signaling pathway in UUO mouse model. Genetic and pharmacologic inhibition of STING relieved renal fibrosis and inflammation in UUO mice. In vitro, hypoxia resulted in PKC-δ phosphorylation, VDAC1 oligomerization, and activation of cGAS-STING signaling pathway in HK-2 cells. Inhibition of PKC-δ, VDAC1 or STING alleviated hypoxia-induced fibrotic and inflammatory responses in HK-2 cells, respectively. Mechanistically, PKC-δ activation induced mitochondrial membrane VDAC1 oligomerization via direct binding VDAC1, followed by the mitochondrial DNA (mtDNA) release into the cytoplasm, and subsequent activated cGAS-STING signaling pathway, which contributed to the inflammation leading to fibrosis. In conclusion, this study has indicated for the first time that PKC-δ is an important regulator in kidney fibrosis by promoting cGAS-STING signaling pathway which mediated by VDAC1. PKC-δ may be useful for treating renal fibrosis and subsequent CKD.

The maturity and patency of arteriovenous fistula (AVF) are essential for patients undergoing hemodialysis. Dysfunction of AVF due to neointimal hyperplasia (NIH) presents a significant clinical challenge. While balloon dilation therapy and open surgery can address this issue, they are associated with a higher likelihood of restenosis and reduced long-term durability. Therefore, there is an urgent need to establish a new method for inhibiting NIH to prolong the patency of AVF treatment. In this study, we developed a local vascular-encapsulated sustained-release drug delivery system containing degradable rapamycin nanofiber membrane patches (R-NFMs). During surgery, R-NFMs were wrapped around the anastomotic site of the AVF and the venous outflow tract. In vitro assessments demonstrated the consistent and stable release of rapamycin from the R-NFMs, confirming the material’s non-toxicity and its support of healthy cellular morphology. Animal studies further revealed that the experimental group showed significant reductions in neointimal and medial hyperplasia, as well as decreased expression of α-SMA, compared to controls. In conclusion, these findings suggest that R-NFMs are effective in inhibiting NIH and may serve as an innovative preventative approach to this pervasive issue.

The aerosol transmission of coronavirus disease in 2019, along with the spread of other respiratory diseases, caused significant loss of life and property; it impressed upon us the importance of real-time bioaerosol detection. The complexity, diversity, and large spatiotemporal variability of bioaerosols and their external/internal mixing with abiotic components pose challenges for effective online bioaerosol monitoring. Traditional methods focus on directly capturing bioaerosols before subsequent time-consuming laboratory analysis such as culture-based methods, preventing the high-resolution time-based characteristics necessary for an online approach. Through a comprehensive literature assessment, this review highlights and discusses the most commonly used real-time bioaerosol monitoring techniques and the associated commercially available monitors. Methods applied in online bioaerosol monitoring, including adenosine triphosphate bioluminescence, laser/light-induced fluorescence spectroscopy, Raman spectroscopy, and bioaerosol mass spectrometry are summarized. The working principles, characteristics, sensitivities, and efficiencies of these real-time detection methods are compared to understand their responses to known particle types and to contrast their differences. Approaches developed to analyze the substantial data sets obtained by these instruments and to overcome the limitations of current real-time bioaerosol monitoring technologies are also introduced. Finally, an outlook is proposed for future instrumentation indicating a need for highly revolutionized bioaerosol detection technologies.

Preparing regular time series optical remote sensing data is a difficult task due to the influences of frequently cloudy and rainy days. The irregular data and their forms severely limit the data’s ability to be analyzed and modeled for vegetation classification. However, how irregular time series data affect vegetation classification in deep learning models is poorly understood. To address these questions, this research preprocessed the 2019–2021 time series of Sentinel-2 in both unequal and equal intervals, and transformed them into an image through recurrence plot for each pixel. The initial one-dimension time series (1DTS) and recurrence plot data were then used as input data for three deep learning methods (i.e. Conv1D model based on one-dimensional convolution, GoogLeNet model based on two-dimensional convolution, and CGNet model which fused Conv1D and GoogLeNet) for vegetation classification, respectively. The class separability of the features generated by each model was evaluated and the importance of spectral and temporal features was further examined through gradient backpropagation. The equal-interval time series data significantly improved the classification accuracy with 0.04, 0.13, and 0.09 for Conv1D, GoogLeNet, and CGNet, respectively. The CGNet achieved the highest classification accuracy, indicating that the information from 1DTS and recurrence plot can be a good complementary for vegetation classification. The importance of spectral bands and time showed that the Sentinel-2 red edge-1 spectral band played a critical role in the identification of eucalyptus, loquat, and honey pomelo, but the importance order of bands varied in different vegetation types in GoogLeNet. The time importance varied across different vegetation types but is similar in these deep learning models. This study quantified the impacts of organizational form (1DTS and recurrence plot) of time series data on different models. This research is valuable for us to choose appropriate data structures and efficient deep learning models for vegetation classification.

Forest canopy height (FCH) is one of the most important variables for carbon stock estimation. While many studies have focused on extracting FCH from spaceborne LiDAR in regions with spatially continuous and large patch sizes of forested lands, limited research has addressed the challenges of FCH extraction in plain regions with sparse and fragmented forest distributions. In this study, we proposed innovative processing approaches to extract FCH from ICESat-2 photons and GEDI footprints in the plain regions of Anhui Province, China. Specifically, we proposed a sectional photon denoising method for processing ICESat-2 data and a geolocation error correction method for processing GEDI data. Airborne LiDAR data were used to validate the extracted FCH products across typical plain regions. The results demonstrated the effectiveness of the proposed methods in improving FCH extraction accuracy. Evaluation indicated that the directly extracted FCH products from ATL08 and GEDI L2A had Pearson’s correlation coefficients (r) of 0.6 and 0.93, respectively. After processing with the proposed methods, the 2019 FCH products from ICESat-2 exhibited r of 0.82 and relative root mean square error (rRMSE) of 31.11% based on 3,217 ICESat-2 segments, and the products from GEDI showed r of 0.96 and rRMSE of 18.35% based on 4,862 GEDI footprints. Further application of these methods to extract FCH products from GEDI and ICESat-2 for the years 2020, 2021, and 2022 indicated their promise for addressing sparse vegetation coverage in plain regions.

Abstract The activation of cyclic GMP‐AMP (cGAMP) synthase (cGAS) and its adaptor, stimulator of interferon genes (STING), is known to reprogram the immunosuppressive tumor microenvironment for promoting antitumor immunity. To enhance the efficiency of cGAS‐STING pathway activation, macrophage‐selective uptake, and programmable cytosolic release are crucial for the delivery of STING agonists. However, existing polymer‐ or lipid‐based delivery systems encounter difficulty in integrating multiple functions meanwhile maintaining precise control and simple procedures. Herein, inspired by cGAS being a natural DNA sensor, a modularized DNA nanodevice agonist (DNDA) is designed that enable macrophage‐selective uptake and programmable activation of the cGAS‐STING pathway through precise self‐assembly. The resulting DNA nanodevice acts as both a nanocarrier and agonist. Upon local administration, it demonstrates the ability of macrophage‐selective uptake, endosomal escape, and cytosolic release of the cGAS‐recognizing DNA segment, leading to robust activation of the cGAS‐STING pathway and enhanced antitumor efficacy. Moreover, DNDA elicits a synergistic therapeutic effect when combined with immune checkpoint blockade. The study broadens the application of DNA nanotechnology as an immune stimulator for cGAS‐STING activation.

In the context of pandemic viruses and pathogenic bacteria, triclosan (TCS), as a typical antibacterial agent, is widely used around the world. However, the health risks from TCS increase with exposure, and it is widespread in environmental and human samples. Notably, environmental transformation and human metabolism could induce potentially undesirable risks to humans, rather than simple decontamination or detoxification. This review summarizes the environmental and human exposure to TCS covering from 2004 to 2023. Particularly, health impacts from the environmental and metabolic transformation of TCS are emphasized. Environmental transformations aimed at decontamination are recognized to form carcinogenic products such as dioxins, and ultraviolet light and excessive active chlorine can promote the formation of these dioxin congeners, potentially threatening environmental and human health. Although TCS can be rapidly metabolized for detoxification, these processes can induce the formation of lipophilic ether metabolic analogs via cytochrome P450 catalysis, causing possible adverse cross-talk reactions in human metabolic disorders. Accordingly, TCS may be more harmful in environmental transformation and human metabolism. In particular, TCS can stimulate the transmission of antibiotic resistance even at trace levels, threatening public health. Considering these accruing epidemiological and toxicological studies indicating the multiple adverse health outcomes of TCS, we call on environmental toxicologists to pay more attention to the toxicity evolution of TCS during environmental transformation and human metabolism.

Bioaerosols are more likely to accumulate in the residential environment, and long-term inhalation may lead to a variety of diseases and allergies. Here, we studied the distribution, influencing factors and diffusion characteristics of indoor and outdoor microbiota pollution in six residential buildings in Guangzhou, southern China over a period of one year. The results showed that the particle sizes of bioaerosol were mainly in the range of inhalable particle size (

Background Rat models are valuable tools to study the lung microbiota in diseases. Yet the impacts of different lung parts, young and mature adult stages, and the different batches of the same conditions on the healthy rat lung microbiome have not been investigated.Methods The rat lung microbiome was analyzed to clarify the lung part-dependent and age-dependent differences and to evaluate the effects of several ‘batch environmental factors’ on normal rats, after eliminating potential contamination.Results The results showed that the contamination could be identified and excluded. The lung microbiome from left and right lung parts was very similar so one representative part could be used in the microbiome study. There were significantly different lung microbial communities between the young and mature adult groups, and also between the different feeding batches groups of the same repetitive feeding conditions, but a common lung microbiota characterized by Firmicutes, Bacteroidetes, Proteobacteria, and Actinobacteria as the most dominant phyla were present in all adult rats. It indicated that the experiment under the same condition of the same rats batch was needed to compare the difference in the lung microbiota and repeated experiments were necessary to confirm the results.Conclusion These data represented that the lung bacterial communities were dynamic and rapidly susceptible to environmental influence, clustered strongly by age or different feeding batches but similar in the different lung tissue parts. This study improved the basic understanding of the potential effects on the lung microbiome of healthy rats.

In recent years, several surrogate assisted evolutionary algorithms (SAEAs) have been proposed to solve expensive optimization problems. These problems lack explicit expressions and are characterized by high invocation costs. SAEAs leverage surrogate models to accelerate convergence towards the optimal region and reduce the number of function evaluations. While Gaussian Processes (GPs) are widely used due to their robustness and capability of providing uncertainty estimates, their applicability becomes limited in scenarios involving a large number of samples or high-dimensional spaces. This is due to their cubic time complexity in relation to the number of samples, which results in prohibitive computational demands for large-scale problems. To address the challenge, this work presents an efficient surrogate model-assisted estimation of the distribution algorithm (ESAEDA). This method employs a random forest as a surrogate model and combines it with a GP-hedge acquisition strategy to ensure the efficiency and accuracy of model-assisted selection. An improved EDA model called the variable-width histogram model with some unevaluated solutions is used to generate new solutions. To demonstrate the benefits of the proposed method, we compared ESAEDA with several state-of-the-art surrogate-assisted evaluation algorithms and the Bayesian optimization method. Experimental results demonstrate the superiority of the proposed algorithm over these comparison algorithms for two well-known test suites.

The current multi-objective particle swarm algorithms excel in convergence speed for solving complex problems but often suffer from a loss of population diversity. Conversely, composite differential evolution algorithms maintain superior solution distribution but lag in convergence efficiency. This research introduces an improved hybrid algorithm, CoDE-MOPSO, which integrates multi-objective particle swarm optimization with composite differential evolution based on clustering technology. The clustering algorithm is used for all individual clusters to analyze the distribution constructs of populations, which determines whether the new solutions come from global or local populations at a mating restriction probability. The mating restriction probability is updated at each generation. To adapt the balance between the population solution diversities and the convergence speed of the algorithm, at each generation, the control probability is adjusted by a developed adaptive strategy according to the reproduction utility of the two mechanisms of generating new solutions over the last certain generations. This research introduces the CoDE-MOPSO algorithm, designed to transcend existing multi-objective optimization methods’ limitations by optimally balancing exploration and exploitation. Our approach significantly advances evolutionary multi-objective optimization, demonstrating superior performance through lower Inverse Generational Distance and higher Hypervolume metrics, indicating enhanced efficiency in solving complex MOPs across various fields. In practical scenarios like gear reducer optimization, CoDE-MOPSO showcases remarkable effectiveness, highlighting its value in engineering applications and setting a foundation for sophisticated optimization strategies that combine speed with solution quality.

Forest carbon stock is an important indicator reflecting a forest ecosystem’s structures and functions. Its spatial distribution is valuable for managing natural resources, protecting ecosystems and biodiversity, and further promoting sustainability, but accurately mapping the forest carbon stock distribution in a large area is a challenging task. This study selected Changting County, Fujian Province, as a case study to explore a method to map the forest carbon stock distribution using the integration of airborne Lidar, Sentinel-2, and ancillary data in 2022. The Bayesian hierarchical modeling approach was used to estimate the local forest carbon stock based on airborne Lidar data and field measurements, and then the random forest approach was used to develop a regional forest carbon stock estimation model based on the Sentinel-2 and ancillary data. The results indicated that the Lidar-based carbon stock distribution effectively provided sample plots with good spatial representativeness for modeling regional carbon stock with a coefficient of determination (R2) of 0.7 and root mean square error (RMSE) of 12.94 t/ha. The average carbon stocks were 48.55 t/ha, 55.51 t/ha, and 57.04 t/ha for Masson pine, Chinese fir, and broadleaf forests, respectively. The carbon stock in non-conservation regions was 15.2–16.1 t/ha higher than that in conservation regions. This study provides a promising method through the use of airborne Lidar data as a linkage between sample plots and Sentinel-2 data to map the regional carbon stock distribution in those subtropical regions where serious soil erosion has led to a relatively sparse forest canopy density. The results are valuable for local government to make scientific decisions for promoting ecosystem restoration due to water and soil erosion.

Forest canopy height (FCH) is an important variable for estimating forest biomass and ecosystem carbon sequestration. Spaceborne LiDAR data have been used to create wall-to-wall FCH maps, such as the forest tree height map of China (FCHChina), Global Forest Canopy Height 2020 (GFCH2020), and Global Forest Canopy Height 2019 (GFCH2019). However, these products lack comprehensive assessment. This study used airborne LiDAR data from various topographies (e.g., plain, hill, and mountain) to assess the impacts of different topographical and vegetation characteristics on spaceborne LiDAR-derived FCH products. The results show that GEDI–FCH demonstrates better accuracy in plain and hill regions, while ICESat-2 ATLAS–FCH shows superior accuracy in the mountainous region. The difficulty in accurately capturing photons from sparse tree canopies by ATLAS and the geolocation errors of GEDI has led to partial underestimations of FCH products in plain areas. Spaceborne LiDAR FCH retrievals are more accurate in hilly regions, with a root mean square error (RMSE) of 4.99 m for ATLAS and 3.85 m for GEDI. GEDI–FCH is significantly affected by slope in mountainous regions, with an RMSE of 13.26 m. For wall-to-wall FCH products, the availability of FCH data is limited in plain areas. Optimal accuracy is achieved in hilly regions by FCHChina, GFCH2020, and GFCH2019, with RMSEs of 5.52 m, 5.07 m, and 4.85 m, respectively. In mountainous regions, the accuracy of wall-to-wall FCH products is influenced by factors such as tree canopy coverage, forest cover types, and slope. However, some of these errors may stem from directly using current ATL08 and GEDI L2A FCH products for mountainous FCH estimation. Introducing accurate digital elevation model (DEM) data can improve FCH retrieval from spaceborne LiDAR to some extent. This research improves our understanding of the existing FCH products and provides valuable insights into methods for more effectively extracting accurate FCH from spaceborne LiDAR data. Further research should focus on developing suitable approaches to enhance the FCH retrieval accuracy from spaceborne LiDAR data and integrating multi-source data and modeling algorithms to produce accurate wall-to-wall FCH distribution in a large area.

Due to the specific action on bacterial cell wall, β-lactam antibiotics have gained widespread usage as they exhibit a high degree of specificity in targeting bacteria, but causing minimal toxicity to host cells. Under antibiotic pressure, bacteria may opt to shed their cell walls and transform into L-form state as a means to evade the antibiotic effects. In this study, we explored and identified diverse optimal conditions for both Gram-negative bacteria (E. coli DH5α (CTX)) and Gram-positive bacteria (B. subtilis ATCC6633), which were induced to L-form bacteria using lysozyme (0.5 ppm) and meropenem (64 ppm). Notably, when bacteria transformed into L-form state, both bacterial strains showed varying degrees of increased resistance to antibiotics polymyxin E, meropenem, rifampicin, and tetracycline. E. coli DH5α (CTX) exhibited the most significant enhancement in resistance to tetracycline, with a 128-fold increase, while B. subtilis ATCC6633 showed a 32-fold increase in resistance to tetracycline and polymyxin E. Furthermore, L-form bacteria maintained their normal metabolic activity, combined with enhanced oxidative stress, served as an adaptive strategy promoting the sustained survival of L-form bacteria. This study provided a theoretical basis for comprehending antibiotic resistance mechanisms, developing innovative treatment strategies, and confronting global antibiotic resistance challenges.

With the rapid growth of aquaculture globally, large amounts of antibiotics have been used to treat aquatic disease, which may accelerate induction and spread of antibiotic-resistant bacteria (ARB) and antibiotic resistance genes (ARGs) in aquaculture environments. Herein, metagenomic and 16S rRNA analyses were used to analyze the potentials and co-occurrence patterns of pathogenome (culturable and unculturable pathogens), antibiotic resistome (ARGs), and mobilome (mobile genetic elements (MGEs)) from mariculture waters near 5000 km coast of South China. Total 207 species of pathogens were identified, with only 10 culturable species. Furthermore, more pathogen species were detected in mariculture waters than those in coastal waters, and mariculture waters were prone to become reservoirs of unculturable pathogens. In addition, 913 subtypes of 21 ARG types were also identified, with multidrug resistance genes as the majority. MGEs including plasmids, integrons, transposons, and insertion sequences were abundantly present in mariculture waters. The co-occurrence network pattern between pathogenome, antibiotic resistome, and mobilome suggested that most of pathogens may be potential multidrug resistant hosts, possibly due to high frequency of horizontal gene transfer. These findings increase our understanding of mariculture waters as reservoirs of antibiotic resistome and mobilome, and as yet another hotbed for creation and transfer of new antibiotic-resistant pathogenome.

A novel nanocomposite hydrogel with photothermal therapeutic properties, which could enhance the healing of surgical wounds, was developed. The composite comprises functionalized silica nanoparticles (FSNs) loaded with desferoxamine (DFO) as the core and a dexamethasone (Dex) filled hyaluronic acid–chitosan hydrogel (HA-CS) as the shell. Dex can effectively control inflammation at the wound site, and DFO is beneficial in proliferating the skin cells. The two drugs effectively promote wound healing at the surgical site. The aim of this approach is to demonstrate the hierarchical and continuous release of Dex and DFO from the FSNs@DFO-H@Dex system to reduce wound inflammation and promote healing. Furthermore, the controlled release of DFO can be achieved by controlling the near-infrared illumination. The composite nano hydrogel has a photothermal response, which accelerates wound healing by effectively reducing inflammation through the controlled release of drugs and regulating the immunological response of damaged skin tissue.

Abdominal adhesions have a high incidence after surgery due to fibrosis and inflammation resulting in damaged tissues caused by trauma, bleeding, infection, foreign body stimulation. The adhesions introduced persistent chronic pain because of attachment and traction seriously affects physical health patients. Recent years, various kinds of membrances, hydrogel, nanofibers were developed to inhibit post-operative abdominal adhesion by physical isolation or drug treatment. However, the integration of physical isolation and pharmaceutical therapy in one platform still has some challenges. For example, the anti-swelling property of hydrogel is not good, membrane is easy prone to displacement. Herein, we developed a nanofiber-hydrogel composite patch (FHCP) with sandwich structure providing effectively anti swelling property and wet adhesion performance. Meanwhile, the nanofiber-hydrogel composite patch achieved combining excellent physical isolation and drug treatment, the sandwich structure of patch provided hierarchical drug release drugs release, and then made the patch realized excellent anti-inflammatory, tissue regeneration, and preventing post-operative abdominal adhesion. Our results showed that the prepared patch has better effects on anti-inflammation, effectively suppressing post-operative adhesion in the abdominal cavity. Therefore, we believe that our nanofiber-hydrogel composite patch has broad clinical application prospects.

Immunoregulation is one of the important factors in wound healing. Currently, wound dressings with immunoregulation is necessary to overcome the complicated interventions, high-cost treatments and uncontrolled release behaviors. In this study, a novel Cu and Zn loaded nanofiber dressing (FM-Cu-Zn) with immunoregulation and controllable release without external intervention was prepared by electrospinning. The dressing is composed of ZnCl2, CuS nano particles, poly-3-hydroxybutyrate-co-4-hydroxybutyrate (P34HB). Where Zn2+ is the “promoter” of immunotherapeutic activity by reducing the environmental pH to trigger H2S and Cu2+ releasing from CuS. Then, H2S and Cu2+ can regulate the inflammatory response and accelerate wound healing. The results in vivo indicated the FM-Cu-Zn nanofiber dressing showed better anti-inflammatory and wound healing ability, the wound healing rate was upto 95 % after 11 days treatment by the obtianed dressing, which was much higher compared to control groups. Notably, the dressing can promote macrophage polarization toward a pro-regenerative M2 phenotype without any external intervention. Therefore, the FM-Cu-Zn nanofiber with the immunomodulatory property can serve as a promising dressing in wound healing field.

AbstractThe renal interstitial fibrosis contributes to the progression and deterioration of diabetic nephropathy (DN). Long noncoding RNA taurine-up-regulated gene 1 (TUG1) in kidneys may be down-regulated by hyperglycemia. We aim to explore its role in tubular fibrosis caused by high glucose and the possible target genes of TUG1. In this study, a streptozocin-induced accelerated DN mouse model and a high glucose-stimulated HK-2 cells model was established to evaluate TUG1 expression. Potential targets of TUG1 were analyzed by online tools and confirmed by luciferase assay. A rescue experiment and gene silencing assay were used to investigate whether TUG1 plays its regulation role via miR-145-5p/dual-specificity phosphatase 6 (DUSP6) in HK2 cells. The effects of TUG1 on inflammation and fibrosis in high glucose treated tubular cells were evaluated by in vitro study, as well as in vivo DN mice model through AAV-TUG1 delivery. Results showed TUG1was downregulated in HK2 cells incubated with high glucose while miR-145-5p was upregulated. Overexpression of TUG1 alleviated renal injury by suppressing inflammation and fibrosis in vivo. Overexpression of TUG1 inhibited HK-2 cell fibrosis and relieved the inflammation. A mechanism study demonstrated that TUG1 directly sponged to miR-145-5p, and DUSP6 was identified as a target downstream of miR-145-5p. In addition, miR-145-5 overexpression and DUSP6 inhibition countervailed the impacts of TUG1. Our findings revealed that TUG1 overexpression alleviates kidney injury in DN mice and decreases the inflammatory response and fibrosis of high glucose-stimulated HK-2 cells via miR-145-5p/DUSP6 axis.

Abstract Bioaerosol can cause the spread of disease, and therefore, capture and inactivation of bioaerosols is desirable. However, filtration systems can easily become blocked, and are often unable to inactivate the bioaerosol once it is captured. Herein, we reported a bioinspired artificial spider silk (ASS) photocatalyst, consisting of a periodic spindle structure of TiO2 on nylon fiber that can efficiently capture and concentrate airborne bacteria, followed by photocatalytic inactivation in situ, without a power-supply exhaust system. The ASS photocatalyst exhibits a higher capture capacity than the nylon fiber substrate and a photocatalytic inactivation efficiency of 99.99% obtained under 4 h irradiation. We found that the capture capacity of the ASS photocatalyst can be mainly attributed to the synergistic effects of hydrophilicity, Laplace pressure differences caused by the size of the spindle knots and surface energy gradients induced by surface roughness. The bacteria captured by the ASS photocatalyst are inactivated by photocatalysis within droplets or at the air/photocatalyst interfaces. This strategy paves the way for constructing materials for bioaerosol purification.

Personal care products (PCPs) inevitably come into contact with the skin in people’s daily life, potentially causing adverse effects on human health. The adverse effects can be exacerbated under UV irradiation but are rarely studied. In this study, to clearly understand the damage of representative PCPs to human skin and their photochemical transformation behaviors, fragrance tonalide (AHTN) was measured in the presence of amino acids as a basic building block of human tissue. The results showed that amino acids could decelerate the photochemical transformation rate of AHTN, increasing the likelihood of AHNT persisting on the skin surface and the health risk to the human being. Further, the interaction between amino acids and AHTN was investigated. AHTN could play bidirectional roles in damaging amino acids: the photosensitizer and reactive activator. As a photosensitizer, the 1O2 generated from the AHTN photosensitization was partly employed to oxidative damage amino acids. Furthermore, by combining experiments with quantum chemical computation, the carbonyl group of the activator AHTN was found to be the active site to activate the N-containing group of amino acids. The activation mechanism was the electron transfer between AHTN and amino acids. Imines formed during the photochemical transformation of AHTN with histidine/glycine were the molecular initiating event for potential skin sensitization. This study reported for the first time that skin photosensitizer formation threatens human health during the photochemical transformation of AHTN.

Metabolic associated fatty liver disease (MAFLD) ranks among the most prevalent chronic liver conditions globally. At present, the mechanism of MAFLD has not been fully elucidated. Tripartite motif (TRIM) protein is a kind of protein with E3 ubiquitin ligase activity, which participates in highly diversified cell activities and processes. It not only plays an important role in innate immunity, but also participates in liver steatosis, insulin resistance and other processes. In this review, we focused on the role of TRIM family in metabolic associated fatty liver disease. We also introduced the structure and functions of TRIM proteins. We summarized the TRIM family’s regulation involved in the occurrence and development of metabolic associated fatty liver disease, as well as insulin resistance. We deeply discussed the potential of TRIM proteins as targets for the treatment of metabolic associated fatty liver disease.

IntroductionBacterial contamination is a critical parameter for how long a medical mask will be worn.MethodsIn this study, we used the pour plate method to observe the total bacteria counts in used medical face masks. The bacterial community analysis was detected using bio-Mass spectrometry technology and 16SrRNA gene sequencing technology. The wearing time of the mask from 0.5 hours to 5 hours were studied.ResultsThese results shown that the total number of bacteria on the inside surface of the mask were higher than the outside. The total number of bacteria on the inner surface of masks worn for 0.5 h, 1 h 2 h, 4 h and 5 h was 69 CFU/m2,91.3 CFU/m2, 159.6 CFU/m2, 219 CFU/m2, and 879 CFU/m2, respectively. The total number of bacteria on the outside surface of masks worn for 0.5 h, 1 h 2 h, 4 h and 5 h was 60 CFU/m2, 82.7 CFU/m2, 119.8 CFU/m2, 200 CFU/m2, and 498 CFU/m2, respectively. The bacterial abundance obtained from bio-Mass spectrometry were consistent with the results of 16SrRNA sequencing. Both the methods discovered the maximum number of Neisseria followed by Corynebacterium species in mask worn 5 hours. The top 100 bacteria isolated from inside and outside surface of mask belong to 11 phyla.ConclusionsWe analyzed bacterial penetration efficiency of the bacteria that were detected both on the inside and outside surface of the masks. In the top 10 bacteria, no bacteria were detected both inside and outside the mask worn for four hours, while 6 bacteria species were detected on the inside and outside of the mask after wearing for five hours. Bacterial penetration rates ranged from 0.74% to 99.66% for masks worn continuously for five hours, and the penetration rate of four strains exceeded 10% in the top 10 colonies. We recommend timely replacement of masks worn for more than four hours.

Ni-based catalysts using ε-, α- and β-MnO2 crystal phases supports were prepared and applied to CO2 hydrogenation. The samples were characterized by XRD, H2-TPR, BET, SEM, (HR)TEM, CO2-TPD, Raman, quasi in situ XPS, and in situ DRIFTS. Ni/MnOx-NS (ε-MnO2) was found to exhibit stable activity (with 69.0% CO2 conversion) and selectivity to CH4 (99.0%) at 350 ℃, much higher than Ni/MnOx-R (α-MnO2) and Ni/MnOx-B (β-MnO2). Partially reduced Mn3+ and enriched defects facilitated CO2 and intermediates adsorption/activation, enabling unpaired electrons trapped in defect oxide surface to accelerate the cleavage of C-O to form CH4 assisted by active H, whereas CO production via reverse water-gas reaction was strongly suppressed. This work highlights the key role of synergistic interaction between Ni and MnOx-NS and CO2 activation abilities by various MnO2, which directed the selective CO2 hydrogenation performance.

Abstract Human immunodeficiency virus (HIV) sexual transmission among men who have sex with men (MSM) has increased markedly in Beijing, China in the past decade. Pre-exposure prophylaxis (PrEP) is a highly efficacious biomedical prevention strategy that remarkably reduces HIV-transmission risk. This study examined PrEP awareness among MSM and the factors influencing it. From April to July 2021, respondent-driven sampling was used to conduct a cross-sectional survey among MSM in Beijing, China. Demographic, behavior, and awareness data regarding PrEP were collected. The factors influencing PrEP awareness were assessed using univariate and multivariable logistic regression. In total, 608 eligible responders were included in the study. Among the respondents, 27.9% had PrEP awareness, 3.3% had taken PrEP, and 57.9% expressed interest in receiving PrEP, if required. Greater odds of PrEP awareness were associated with higher education level (adjusted odds ratio [aOR] 3.525, 95% confidence interval [CI] 2.013–6.173, P

Lidar has been regarded as the most accurate data source for forest-growing stock volume (FGSV) estimation, but inconsistent acquisition dates of lidar data with field survey often result in poor FGSV estimation accuracy. Spaceborne stereo imagery is captured at regular intervals, providing new opportunities for mapping and updating FGSV spatial distributions. Digital Surface Model derived from spaceborne stereo imagery and Digital Terrain Model (DTM) derived from airborne lidar can be used together to produce a canopy height model (CHM) (LS-CHM), which can then be used to predict FGSV spatial distributions, but this methodology has yet to be explored. Our research attempts to compare the performance of LS-CHM and lidar-CHM (L-CHM) for FGSV modeling and to explore the advantages of using the hierarchical Bayesian approach (HBA) over traditional linear regression and random forest modeling approaches when sample size is small. Considering different forest types and topographical conditions, as well as the number of sample plots for each forest type, HBA is used to develop the FGSV estimation model, and the results are compared with those from linear regression and random forest approaches. The research results in a northern subtropical forest ecosystem indicate that overall, L-CHM provides better predictions than LS-CHM using the same modeling approaches, and L-CHM is especially valuable when FGSV is small or large, but when FGSV falls within 100–200 m3/ha, LS-CHM–based variables produce better modeling accuracy than L-CHM–based variables using linear regression or HBA. The HBA based on stratification of both forest type and slope aspect provides the best FGSV estimation, using either L-CHM or LS-CHM, and solves the modeling problem due to limited sample sizes for forest types. Our research provides new insights to using the combination of satellite stereo images and lidar-derived DTM for mapping and updating FGSV in a large area.

Abstract The production of tetraethyl orthosilicate (TEOS) from biomass provides a new way for TEOS production and biomass valorization. In this study, rice straw was treated using different fractionation methods, and the content, state, and reactivity of Si in the treated samples were investigated. It was found that acid treatment and ethanol extraction kept most Si in the biomass, while alkali treatment caused significant Si loss. Si was mainly present in the SiOx, Si−O−C, and Si−O−Si states in the surface of raw rice straw, cellulose and Klason lignin. The results showed that the Si−O−Si state in rice straw was beneficial for the formation of TEOS. The removal of lipids from rice straw facilitated the production of TEOS, giving the highest TEOS yield of 76.2 %. In contrast, the production of TEOS from other samples became difficult; the simultaneous conversion of the three organic components of rice straw also facilitated the production of TEOS.

Resorcinol-bis(diphenyl)-phosphate (RDP), an emerging organophosphate flame retardant, is increasingly used as a primary alternative for decabromodiphenyl ether and is frequently detected in global environmental matrices. However, the long-term effects of its exposure to humans remain largely unknown. To investigate its intergenerational transfer capacity and health risks, female Sprague Dawley rats were orally exposed to RDP from the beginning of pregnancy to the end of the lactation period. The RDP content, gut microbiota homeostasis, and metabolic levels were determined. RDP accumulation occurred in the livers of maternal rats and offspring and increased with exposure time. 16S rRNA gene sequencing showed that exposure to RDP during pregnancy and/or lactation significantly disrupted gut microbiota homeostasis, as evidenced by decreased abundance and diversity. In particular, the abundance of Turicibacter, Adlercreutzia, and YRC22 decreased, correlating significantly with glycollipic metabolism. This finding was consistent with the reduced levels of short-chain fatty acids, the crucial gut microbial metabolites. Meanwhile, RDP exposure resulted in changes in gut microbiome-related metabolism. Nine critical overlapping KEGG metabolic pathways were identified, and the levels of related differential metabolites decreased. Our results suggest that the significant adverse impacts of RDP on gut microbiota homeostasis and metabolic function may increase the long-term risks related to inflammation, obesity, and metabolic diseases.

Soil and water erosion has long been regarded as a serious environmental problem in the world. Thus, research on reducing soil erosion has received continuous attention. Different conservation measures such as restoring low-function forests, closing hillsides for afforestation, planting trees and grass, and constructing terraces on slope land have been implemented for controlling soil erosion problems and promoting vegetation cover change. One important task is to understand the effects of different conservation measures on reducing water and soil erosion problems. However, directly conducting the evaluation of soil erosion reduction is difficult. One solution is to evaluate the patterns and magnitudes of vegetation cover change due to implementing these measures. Therefore, this research selected Changting County, Fujian Province as a case study to examine the effects of implementing conservation measures on vegetation cover change based on time series Landsat images and field survey data. Landsat images between 1986 and 2021 were used to produce time series vegetation cover data using the Google Earth Engine. Sentinel-2 images acquired in 2021 and Landsat images in 2010 were separately used to develop land cover maps using the random forest method. The spatial distribution of different conservation measures was linked to annual vegetation cover and land cover change data to examine the effects on the change in vegetation cover. The results showed a significant reduction in bare lands and increase in pine forests. The vegetation coverage increased from 42% in 1986 to 79% in 2021 in the conservation region compared with an increase from 73% to 87% in the non-conservation region during the same period. Of the different conservation measures, the change magnitude was 0.44 for restoring low-function forests and closing hillsides for afforestation and 0.65 for multiple control measures. This research provides new insights in terms of understanding the effects of taking proper measures for reducing soil and water erosion problems and provides scientific results for decisionmaking for soil erosion controls. The strategy and method used in this research are valuable for other regions in understanding the roles of different conservation measures on vegetation cover change and soil erosion reduction through employing remote sensing technologies.

Abstract Megakaryocytes are common in the bone marrow and appear less often in circulation. Most studies on circulatory megakaryocytes have implicated myelodysplastic syndromes and myeloproliferative disorders because of disruption of the bone marrow barrier and extramedullary hematopoiesis that is commonly seen in the spleen. As myeloproliferative disorders progress, particularly in the absence of the spleen, it is very likely that considerable numbers of megakaryocytes are present in the circulation. Myeloproliferation is associated with essential thrombocytosis or leukocytosis and is the leading cause of pseudo-hyperkalemia followed by reactive thrombocytosis due to splenectomy, rheumatoid arthritis, and renal cancer. The simultaneous measurement of plasma potassium is required when the platelet count exceeds 500 × 109/L and the level of serum potassium is > 5.4 mmol/L.

Hydroxylated metabolites in the living body are considered as a potential biomarker of exposure to emerging contaminations (ECs) and breast cancer, but their formation mechanism has not received enough attention. Besides, the adverse impacts of metabolites during the metabolic transformation of ECs largely remain unknown. In this study, we employed a density functional calculation combing with in-vitro incubation of human liver microsomes to explore the bio-transformation of preservative methylparaben (MPB) in human bodies. Our results showed that hydroxylated metabolites of MPB (OH-MPB) were observed experimentally, while a formation mechanism was revealed at the molecular level. That is, hydroxylated metabolite was exclusively formed via the hydrogen abstraction from the phenolic hydroxyl group of MPB followed by the OH-rebound pathway, rather than the direct hydroxylation on the benzene ring. The increasing of hydroxyl groups on ECs could improve the metabolisms. This was confirmed in the metabolism of ECs without hydroxyl group and with multiple-hydroxyl groups, respectively. Furthermore, toxicity assessments show that compared to parent MPB, the hydroxylated metabolites have increased negative impacts on the gastrointestinal system and liver. A semiquinone product exhibits potential damage in the cardiovascular system and epoxides are toxic to the blood and gastrointestinal system. The findings deepen our insight into the biotransformation of parabens in human health, especially by providing health warnings about the potential impacts caused by semiquinone and epoxides.

Inhaling airborne pathogens may cause severe epidemics showing huge threats to indoor dwellings residents. The ventilation, environmental parameters, and human activities would affect the abundance and pathogenicity of bioaerosols in indoor. However, people know little about the indoor airborne microbes especially pathogens near the industrial park polluted with organics and heavy metals. Herein, the indoor bioaerosols’ community composition, source and influencing factors near an electronic waste (e-waste) industrial park were investigated. Results showed that the average bioaerosol level in the morning was lower than evening. Bioaerosol concentration and activity in indoor (1936 CFU/m3 and 7.62 × 105 ng/m3 sodium fluorescein in average) were lower than the industrial park (4043 CFU/m3 and 7.77 × 105 ng/m3 sodium fluorescein), and higher microbial viability may be caused by other pollutants generated during e-waste dismantling process. Fluorescent biological aerosol particles occupied 17.6%−23.7% of total particles, indicating that most particles were non-biological. Bacterial communities were richer and more diverse than fungi. Furthermore, Bacillus and Cladosporium were the dominant indoor pathogens, and pathogenic fungi were more influenced by environmental factors than bacteria. SourceTracker analysis indicates that outdoor was the main source of indoor bioaerosols. The hazard quotient (

Updating eucalyptus carbon stock data in a timely manner is essential for better understanding and quantifying its effects on ecological and hydrological processes. At present, there are no suitable methods to accurately estimate the eucalyptus carbon stock in a large area. This research aimed to explore the transferability of the eucalyptus carbon stock estimation model at temporal and spatial scales and assess modeling performance through the strategy of combining sample plots, airborne LiDAR and Landsat time series data in subtropical regions of China. Specifically, eucalyptus carbon stock estimates in typical sites were obtained by applying the developed models with the combination of airborne LiDAR and field measurement data; the eucalyptus plantation ages were estimated using the random localization segmentation approach from Landsat time series data; and regional models were developed by linking LiDAR-derived eucalyptus carbon stock and vegetation age (e.g., months or years). To examine the models’ robustness, the developed models at the regional scale were transferred to estimate carbon stocks at the spatial and temporal scales, and the modeling results were evaluated using validation samples accordingly. The results showed that carbon stock can be successfully estimated using the age-based models (both age variables in months and years as predictor variables), but the month-based models produced better estimates with a root mean square error (RMSE) of 6.51 ​t·ha−1 for Yunxiao County, Fujian Province, and 6.33 ​t·ha−1 for Gaofeng Forest Farm, Guangxi Zhuang Autonomous Region. Particularly, the month-based models were superior for estimating the carbon stocks of young eucalyptus plantations of less than two years. The model transferability analyses showed that the month-based models had higher transferability than the year-based models at the temporal scale, indicating their possibility for analysis of carbon stock change. However, both the month-based and year-based models expressed relatively poor transferability at a spatial scale. This study provides new insights for cost-effective monitoring of carbon stock change in intensively managed plantation forests.

Abstract Background Cyclin-dependent kinase 4 (CDK4) when hyperactivated drives development and maintenance of most tumour types, thus prompting its use as an essential cancer treatment target and a diagnostic tool. Target-binding molecules, such as single-chain variable fragment (scFv) antibodies, hold tremendous potential for use in a wide range of cancer diagnostic and therapeutic applications. Results A human anti-CDK4 scFv antibody (AK2) derived from a human phage display library was expressed in soluble form in Escherichia coli and shown to be secreted into the culture supernatant. Next, soluble AK2 within culture supernatant was successfully purified using affinity chromatography then was shown, using enzyme-linked immunosorbent assays, to bind to recombinant human CDK4 with high affinity and specificity. Further analyses of AK2 interactions with intracellular components demonstrated that AK2 recognised and interacted specifically with endogenous CDK4 and thus could be useful for detection of CDK4 within tumour cells. Conclusions A novel anti-CDK4 scFv antibody that can recognise and interact specifically with recombinant human CDK4 and endogenous CDK4 in tumour cells was expressed and purified successfully. These results suggest that the anti-CDK4 scFv antibody may serve as a new and promising tool for achieving CDK4-targeted diagnosis, prognosis and treatment of numerous types of cancers.

Waterborne pathogens in urban rivers of estuarine areas pose a great threat to human health. In this study, both bacterial and fungal community structures of four urban rivers in the Pearl River estuarine area were investigated using high-throughput sequencing. Results showed that the diversity and richness indices of the bacterial community were higher than that of fungi. Taxonomic analysis indicated that the most abundant bacterial phylum was Actinobacteria, while the most abundant fungal phylum was Ascomycota. In addition, 35 major pathogens were found at the level of genus with Mycobacterium being the most abundant. Specifically, pathogens of Burkholderiales, Bartonella, Rhizobiales, Bordetella and Brucella were first detected in this area, although with relative low abundances. Spearman correlation analysis revealed that temperature, TOC and TDP were significant factors shaping both total microbial community and pathogenic microbial community structure. TDP was positively correlated with almost all the potential pathogenic genera. PICRUSt analysis further predicted that bacterial infectious disease was the most abundant pathway associated with microbial functions of human disease in all the studied rivers. This work provides useful information not only for in-depth understanding of bacterial and fungal communities in urban rivers of estuarine areas under anthropogenic disturbances but also for environmental risk management of potential waterborne pathogens.

Familial non-syndromic unilateral hearing loss (NS-UHL) is rare and its genetic etiology has not been clearly elucidated. This study aimed to identify the genetic cause of NS-UHL in a three-generation Chinese family. Detailed medical history consultation and clinical examination were conducted. Further, whole-exome sequencing (WES) was performed to identify the genetic etiology of the proband, and the variant was verified by Sanger sequencing. A novel missense mutation, c.533G>C (p.Arg178Thr), in the SIX homeobox 1 gene (SIX1) was identified in four patients and co-segregated with NS-UHL in a three-generation Chinese family as a dominant trait. Using bioinformatics analyses, we show that this novel mutation is pathogenic and affects the structure of SIX1 protein. These data suggest that mutations in SIX1 gene are associated with NS-UHL. Our study added the NS-UHL phenotype associated with SIX1, and thereby improving the genetic counseling provided to individuals with SIX1 mutations.

Unveiling the mechanisms of bacterial sporulation at natural mineral interfaces is crucial to fully understand the interactions of mineral with microorganism in aquatic environment. In this study, the bacterial sporulation mechanisms of Bacillus subtilis (B. subtilis) at natural sphalerite (NS) interface with and without light irradiation were systematically investigated for the first time. Under dark condition, NS was found to inactivate vegetative cells of B. subtilis and promote their sporulation simultaneously. The released Zn2+ from NS was mainly responsible for the bacterial inactivation and sporulation. With light irradiation, the photocatalytic effect from NS could increase the bacterial inactivation efficiency, while the bacterial sporulation efficiency was decreased from 8.1 % to 4.5 %. The photo-generated H2O2 and ·O2– played the major roles in enhancing bacterial inactivation and suppressing bacterial sporulation process. The intracellular synthesis of dipicolinic acid (DPA) as biomarker for sporulation was promoted by NS in dark, which was suppressed by the photocatalytic effect of NS with light irradiation. The transformation process from vegetative cells to spores was monitored by both 3D-fluerecence EEM and SEM observations. Compared with the NS alone system, the NS/light combined system induced higher level of intracellular ROSs, up-regulated antioxidant enzyme activity and decreased cell metabolism activity, which eventually led to enhanced inactivation of vegetative cells and suppressed bacterial sporulation. These results not only provide in-depth understanding about bacterial sporulation as a new mode of sub-lethal stress response at NS interface, but also shed lights on putting forward suitable strategies for controlling spore-producing bacteria by suppressing their sporulation during water disinfection.

Abstract There are two kinds of condensins in human cells, known as condensin I and condensin II. The canonical roles of condensins are participated in chromosome dynamics, including chromosome condensation and segregation during cell division. Recently, a novel function of human condensins has been found with increasing evidences that they play important roles in cellular senescence. This paper reviewed the research progress of human condensins involved in different types of cellular senescence, mainly oncogene-induced senescence (OIS) and replicative senescence (RS). The future perspectives of human condensins involved in cellular senescence are also discussed.

Methanethiol is a widely existing malodorous pollutant with health effects on the human population. However, the cytotoxicity mechanism of methanethiol in vitro and its metabolic transformation (bioactivation or detoxification) have not been fully elucidated. Herein, the metabolites of methanethiol during cell culture and the cytotoxicity of methanethiol in human bronchial epithelial (16HBE) cells were investigated. Results indicate that methanethiol (10–50 μM) was partially converted into dimethyl sulfide, mainly catalyzed by thiol S-methyltransferase in the 16HBE cells, and then it induced potent cytotoxicity and cell membrane permeability. Moreover, methanethiol induced intracellular reactive oxygen species (ROS) up to 50 μM and further activated the tumor necrosis factor (TNF) signaling pathway, which eventually led to the decline in the mitochondrial membrane potential (MMP) and cell necrosis. However, all these effects were significantly alleviated with gene silencing of the methyltransferase-like protein 7B (METTL7B). These results indicate that methanethiol may induce cell necrosis in human respiratory tract cells mainly mediated by S-methyltransferase with interfering TNF and ROS induction. Non-target metabolomics results suggest that methanethiol potently affects expression of endogenous small molecule metabolites in 16HBE cells. To some extent, this work shows the possible conversion path and potential injury mechanism of human respiratory tract cells exposed to methanethiol.

Impervious surface area (ISA) data are required for such studies as urban environmental modeling, hydrological modeling, and socioeconomic analysis, but updating these datasets in a large area remains a challenge due to the complex urban landscapes consisting of different materials and colors with various spatial patterns. This research explores the integration of multi-source remotely sensed data for mapping China’s ISA distribution at 30-m spatial resolution. The integration of Visible Infrared Imaging Radiometer Suite Day/Night Band (VIIRS DNB) and Moderate Resolution Imaging Spectroradiometer (MODIS) normalized difference vegetation index (NDVI) data were used to extract initial ISA with spatial resolution of 250 m using a thresholding approach. The Landsat-derived NDVI and Modified Normalized Difference Water Index (MNDWI) were used to remove vegetation and water areas from the mixed pixels that existed in the initial ISA data. The spectral signatures of these ISA data were further extracted from Landsat multispectral images and used to refine the ISA data using expert knowledge. The results indicate that the integration of multi-source data can successfully map ISA distribution with 30-m spatial resolution in China with producer’s and user’s accuracies of 83.1 and 91.9%, respectively. These ISA data are valuable for better management of urban landscapes and for use as an input in other studies such as socioeconomic and environmental modeling.

Polycyclic aromatic hydrocarbons (PAHs) derived from the incomplete combustion of organic materials are associated with adverse health effects. However, little is known about PAH exposure levels and their influencing factors on a large scale in developing countries. In this study, urinary monohydroxylated metabolites of PAHs (OH-PAHs), including the metabolites of naphthalene, fluorene, phenanthrene, pyrene, chrysene, and benzo[a]pyrene, were measured in 1154 samples in the general population nationwide from 26 provincial capitals in China. Concentrations of OH-PAHs ranged from 1.39 to 228 μg/L. OH-Nap, metabolite of naphthalene, was the predominant compound, accounting for 65.1% of totals. People in eastern, southwest and northeast China, such as Shanghai, Kunming, Nanning, and Changchun, suffered more PAH exposure than other regions which might associate with sampling time, living habits of the subjects, and the imbalance of economic development and energy consumption across regions. Urinary OH-PAH concentrations were associated with body mass index, gender, and age, and smoking was the main correlating factor. Inhalation and diet might be the main exposure route of human exposure to PAHs, especially for smokers by inhalation. Hazard indices showed that no subject was exposed to PAHs with potential non-carcinogenic risk. Furthermore, the carcinogenic risk was the most significant health effects, with almost all subjects having carcinogenic risk values higher than the acceptable level of 10−6. Naphthalene and phenanthrene were the main contributors. The results also suggested a possible relationship between PAH exposure and lung cancer in the Chinese population. This first nationwide study on human internal exposure to PAHs provides a large body of scientific information for governmental decision-making about associated human health and the prevention of human exposure to PAHs.

Cell lysis is a key step for studying the structure and function of proteins in cells and an important intermediate step in drug screening, cancer diagnosis, and genome analysis. The current cell lysis methods still suffer from limitations, such as the need for large instruments, a long and time-consuming process, a large sample volume, chemical reagent contamination, and their unsuitability for the small amount of bacteria lysis required for point-of-care testing (POCT) devices. Therefore, a fast, chemical-free, portable, and non-invasive device needs to be developed. In the present study, we designed an integrated microfluidic chip to achieve E. coli lysis by applying an alternating current (AC) electric field and investigated the effects of voltage, frequency, and flow rate on the lysis. The results showed that the lysis efficiency of the bacteria was increased with a higher voltage, lower frequency, and lower flow rate. When the voltage was at 10 Vp-p, the lysis efficiency was close to 100%. The study provided a simple, rapid, reagent-free, and high-efficiency cleavage method for biology and biomedical applications involving bacteria lysis.

Urban vegetation has important impacts on urban heat island, human living environments and even quality of life. The areal increase of urban vegetation has great contribution in achieving Sustainable Development Goals (SDGs) of United Nations. It is needed to accurately extract different urban vegetation types using high spatial resolution images, but the limitation of remotely sensed data and complexity of urban landscapes make it challenging. This research aims to explore the integration of multispectral and stereo imagery with high spatial resolution for vegetation classification in the urban landscape in East China. A hierarchy-based classifier based on optimization of selected variables in each tree node is developed to conduct urban vegetation classification through incorporation of canopy height features into spectral and textural data. The results show that use of canopy height features improved overall classification accuracy of 4.6% comparing with the dataset without use of canopy height features. The proposed hierarchy-based classifier can further improve the vegetation classification accuracy by 3% comparing with random forest. This research indicates that selection of proper variables from different source data, especially canopy height features, plays important roles in improving urban vegetation classification. This research provides a new insight for accurate urban vegetation classification using a hierarchy-based classification approach based on integration of spectral, spatial and canopy features.

Due to the prohibition of polybrominated diphenyl ethers, organophosphate flame retardants (OPFRs) and tetrabromobisphenol A (TBBPA) have become emerging flame retardants. However, knowledge about their occurrence, especially their transformation products, is still limited. This study collected sediment samples from two rivers, i.e., Lianjiang River (located at an e-waste dismantling area) and Xiaoqing River (situated at a flame retardant production base), to investigate the occurrence, composition, and spatiality distribution of OPFRs, TBBPA, and their transformation products. Both targets were detected in the Lianjiang River in the range of 220–1.4 × 104 and 108–3.1 × 103 ng/g dw (dry weight) for OPFRs and TBBPA, and 0.11–2.35 and 4.8–414 ng/g dw for their respective transformation products, respectively. The concentrations of OPFRs and TBBPA in the Xiaoqing River ranged from 4.15 to 31.5 and 0.76–2.51 ng/g dw, respectively, and no transformation products were detected. Different compositional characteristics of OPFRs and distinct spatial distribution from mainstream and tributary observed between the two rivers are attributed to the difference in the local industries. Spatial distribution and principal component analysis indicated that e-waste dismantling activities could be a vital source of local pollution. Besides, the confluence of tributaries seemed to determine the contaminant levels in the Xiaoqing River. Also, concentration ratios and Spearman’s correlation between metabolites and parent chemicals were analyzed. Low concentration ratios (3.6 ×10–4 to 0.16) indicated a low transformation degree, and Spearman’s correlation analysis suggested transformation products were partly stemming from commercial products. Considering the limited study of these transformation products, more studies on their sources, transform mechanism, and toxicity are required.

Commercial cooking has higher intensity and more severe instantaneous cooking pollution from volatile organic chemicals compared to home cooking, making health risk assessment of occupational exposure for chefs a priority. In this study, chefs from three cooking styles of kitchens, including steaming, frying, and grilling, were selected to investigate the external and internal exposures, health risks and effects of several typical aromatic hydrocarbons (benzene, toluene and naphthalene). Naphthalene was found to be the most concentrated contaminant in air samples among the different kitchens, while benzene had the lowest concentration. The concentration of toluene in frying kitchens was significantly higher than that in steaming kitchens. Air concentrations of toluene in frying kitchens, as well as benzene concentrations in grilling kitchens exceeded the standard level according to indoor air quality standard (GB/T18883-2002). Regarding the metabolites of pollutants in urine, the content of S-benzylmercapturic acids (S-BMA) for frying chefs was significantly higher than that for other cooking styles of chefs, which was consistent with the relatively higher air concentrations of toluene. There was a good correlation between internal and external exposure of the pollutants. The level of oxidative stress was influenced by 2-hydroxynaphthalene (2-OHN) and S-BMA, indicating the potential health risks of these occupational exposed chefs. This study indicates the need to improve the monitoring of typical aromatic hydrocarbons, as well as to investigate their potential health effects in large-scale groups, and improve the ventilation in kitchens.

Thioester-containing proteins (TEPs) superfamily is known to play important innate immune functions in vertebrates and invertebrates, and involved in recognition, and killing of invading pathogens. Here, a TEP gene (designated as Pf-TEP) was obtained from the pearl oyster Pinctada fucata by RT-PCR and rapid amplification of cDNA ends (RACE). The Pf-TEP cDNA consists of 4335 bp with an open reading frame (ORF) of 3639 bp encoding a protein of 1212 amino acids. The deduced TEP protein possessed the characteristic structure features present in its homologs and contained the A2M_N_2, A2M, A2M_comp, A2M_recep, and thioester domain, as well as the conserved Cys, His, and Glu residues. Phylogenetic analysis revealed that Pf-TEP is closely related to the TEPs from other invertebrates. Pf-TEP mRNA was expressed in all examined tissues including gill, digestive gland, adductor muscle, mantle and hemocyte, while the highest expression was found in gill. Following challenge with Vibrio alginolyticus, Pf-TEP expression was significantly induced in hemocytes. Further knockdown of Pf‐TEP by specific siRNA could significantly reduce the phagocytosis of V. alginolyticus by hemocytes in vitro. These results would help increase understanding of TEP existed as an ancient complement-like molecular and therefore provide new insights into the roles of TEP in the invertebrate immune system.

The ubiquitous presence of fragrance-associated synthetic musk is cause for serious concern due to their transformation and environmental impacts. In particular, nitro-musks are frequently detected in various matrices, including water, even though they were restricted because of carcinogenicity. Thus, using musk xylene as a model compound, the mechanism, eco-toxicity and health effects during OH-initiated transformation process were systematically studied using quantum chemistry and computational toxicology. Results indicate that musk xylene can be exclusively transformed via H-abstraction pathways from its methyl group, with total rate constants of 5.65 × 108–8.79 × 109 M−1 s−1, while the contribution of other pathways, including single-electron transfer and OH-addition pathways, were insignificant. The subsequent dehydrogenation intermediates (MX(H)) could further transform into cyclic, aldehyde and demethylation products. Based on toxicity assessments, all the transformation products exhibited decreased aquatic toxicity to fish in comparison with the parent musk xylene but they were still classified at toxic or very toxic levels, especially the cyclic products. More importantly, these products still exhibited carcinogenic activity during OH-initiated transformation and increased carcinogenicity relative to the parent musk xylene. This is the first time that the transformation mechanism and environmental impacts of nitro-musks have been explored through theoretical calculations. Keywords: Nitro-musks, Transformation mechanism, Hydroxyl radical, Carcinogenic activity, Theoretical calculation, Computational toxicology

Metropolitan Beijing is facing many environmental problems such as haze and urban heat island due to the rapid urbanization. Surface shortwave, longwave, and net radiations are key components of the surface-atmosphere radiation budget. Since megacities are affected by the thermal radiation of complex landscape structures and atmospheric environments, quantitative and spatially explicit retrieval from remotely sensed data remains a challenge. We collected the surface radiation fluxes from seven fixed sites representing different land-use types to calibrate the local parameters for remotely sensed retrieval of net radiation. We proposed a remote sensing–based surface radiation retrieval method by embedding the underlying land covers and integrating the observational data. The improved method is feasible to accurately retrieve surface radiation and delineate spatial characteristics in metropolitan areas. The accuracy evaluation indicated that the difference between remotely sensed and in situ observed net radiation ranged within 0~± 40 W· m−2. The root mean squared error of the estimated net surface radiation was 32.71 W· m−2. The strongly spatial heterogeneity of surface radiation components in metropolitan Beijing was closely related to land-cover patterns from urban area to outskirts. We also found that the surface net radiation had a decreasing trend from 1984 to 2014, and the net radiation in the urban area was lower than that in the outskirts. According to the surface radiation budgets, urbanization resulted in the cooling effect in net radiation flux in the daytime, which was stemmed from low atmospheric transmittances from massive aerosol concentration and high surface albedo from light building materials.