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Abstract Background As one of the most common traffic-related pollutants, diesel exhaust (DE) confers high risk for cardiovascular and respiratory diseases. However, its impact on pulmonary vessels is still unclear. Methods To explore the effects of DE exposure on pulmonary vascular remodeling, our study analyzed the number and volume of small pulmonary vessels in the diesel engine testers (the DET group) from Luoyang Diesel Engine Factory and the controls (the non-DET group) from the local water company, using spirometry and carbon content in airway macrophage (CCAM) in sputum. And then we constructed a rat model of chronic DE exposure, in which 12 rats were divided into the DE group (6 rats with 16-week DE exposure) and the control group (6 rats with 16-week clean air exposure). During right heart catheterization, right ventricular systolic pressure (RVSP) was assessed by manometry. Macrophage migration inhibitory factor (MIF) in lung tissues and bronchoalveolar lavage fluid (BALF) were measured by qRT-PCR and ELISA, respectively. Histopathological analysis for cardiovascular remodeling was also performed. Results In DET cohort, the number and volume of small pulmonary vessels in CT were positively correlated with CCAM in sputum (P

Due to the complexity of environmental exposure factors and the low levels of exposure in the general population, identifying the key environmental factors associated with diabetes and understanding their potential mechanisms present significant challenges. This study aimed to identify key polycyclic aromatic hydrocarbons (PAHs) contributing to increased fasting blood glucose (FBG) concentrations and to explore their potential metabolic mechanisms. We recruited a highly PAH-exposed diesel engine exhaust testing population and healthy controls. Our findings found a positive association between FBG concentrations and PAH metabolites, identifying 1-OHNa, 2-OHPh, and 9-OHPh as major contributors to the rise in FBG concentrations induced by PAH mixtures. Specifically, each 10 % increase in 1-OHNa, 2-OHPh, and 9-OHPh concentrations led to increases in FBG concentrations of 0.201 %, 0.261 %, and 0.268 %, respectively. Targeted metabolomics analysis revealed significant alterations in metabolic pathways among those exposed to high levels of PAHs, including sirtuin signaling, asparagine metabolism, and proline metabolism pathway. Toxic function analysis highlighted differential metabolites involved in various dysglycemia-related conditions, such as cardiac arrhythmia and renal damage. Mediation analysis revealed that 2-aminooctanoic acid mediated the FBG elevation induced by 2-OHPh, while 2-hydroxyphenylacetic acid and hypoxanthine acted as partial suppressors. Notably, 2-aminooctanoic acid was identified as a crucial intermediary metabolic biomarker, mediating significant portions of the associations between the multiple different structures of OH-PAHs and elevated FBG concentrations, accounting for 16.73 %, 10.84 %, 10.00 %, and 11.90 % of these effects for 1-OHPyr, 2-OHFlu, the sum concentrations of 2- and 9-OHPh, and the sum concentrations of total OH-PAHs, respectively. Overall, our study explored the potential metabolic mechanisms underlying the elevated FBG induced by PAHs and identified 2-aminooctanoic acid as a pivotal metabolic biomarker, presenting a potential target for intervention.

Background: Benzo(a)pyrene (B[a]P) is the most widely concerned polycyclic aromatic hydrocarbons (PAHs), which metabolizes benzo(a)pyrene-7,8-dihydrodiol-9,10-epoxide (BPDE) in vivo to produce carcinogenic effect on the body. Currently, there is limited research on the role of the variation of metabolic enzymes in this process. Methods: We carried out a study including 752 participants, measured the concentrations of 16 kinds PAHs in both particle and gaseous phases, urinary PAHs metabolites, leukocyte BPDE-DNA adduct and serum BPDE- Albumin (BPDE-Alb) adduct, and calculated daily intake dose (DID) to assess the cumulative exposure of PAHs. We conducted single nucleotide polymorphism sites (SNPs) of metabolic enzymes, explored the exposure–response relationship between the levels of exposure and BPDE adducts using multiple linear regression models. Result: Our results indicated that an interquartile range (IQR) increase in B[a]P, PAHs, BaPeq, 1-hydroxypyrene (1-OHP), 1-hydroxynaphthalene (1-OHNap) and 2-hydroxynaphthalene (2-OHNap) were associated with 26.53 %, 24.24 %, 28.15 %, 39.15 %, 12.85 % and 14.09 % increase in leukocyte BPDE-DNA adduct (all P 0.05). Besides, we also found the polymorphism of CYP1A1(Gly45Asp), CYP2C9 (Ile359Leu), and UGT1A1(downstream) may affect BPDE adducts level. Conclusion: Our results indicated that leukocyte BPDE-DNA adduct could better reflect the exposure to PAHs. Furthermore, the polymorphism of CYP1A1, CYP2C9 and UGT1A1affected the content of BPDE adducts.

Abstract The development of high‐performance artificial synaptic neuromorphic devices poses a significant challenge in the creation of biomimetic sensing neural systems that seamlessly integrate both sensory and computational functionalities. In pursuit of this objective, promising bionic opto‐olfactory co‐sensory artificial synapse devices are constructed utilizing the BP‐C/CNT (2D/1D) hybrid filter membrane as the resistive layer. Experimental results demonstrated that the devices seamlessly integrated the light modulation, gas detection, and biological synaptic functions into a single device while addressing the challenge with separating artificial synaptic devices from sensors. These devices offered the following advantages: 1) Simulating visual synapses, they can effectively replicate fundamental synaptic functions under both electrical and optical stimulation. 2) By emulating olfactory synapse responses to specific gases, they can achieve ultra‐low detection limits and rapid identification of ethanol and acetone gases. 3) They enable photo‐olfactory co‐sensing simulations that mimic synaptic function under light‐modulated pulse conditions in distinct gas environments, facilitating the study of synaptic learning rules and Pavlovian responses. This work provides a pioneering approach for exploring highly stable 2D BP‐based optoelectronics and advancing the development of biomimetic neural systems.

Trichloroethylene (TCE)-induced hypersensitivity syndrome (THS) has been a concern for many researchers in the field of environmental and occupational health. Currently, there is no specific treatment for THS, leaving patients to contend with severe infections arising from extensive skin lesions, consequently leading to serious adverse effects. However, the pathogenesis of severe skin damage in THS remains unclear. This study aims to investigate the specific danger signals and mechanisms underlying skin damage in THS through in vivo and in vitro experiments. We identified that cell supernatant containing 15 kDa granulysin (GNLY), released from activated CD3-CD56+NK cells or CD3+CD56+NKT cells in PBMC induced by TCE or its metabolite, promoted apoptosis in HaCaT cells. The apoptosis level decreased upon neutralization of GNLY in the supernatant by a GNLY-neutralizing antibody in HaCaT cells. Subcutaneous injection of recombinant 15 kDa GNLY exacerbated skin damage in the THS mouse model and better mimicked patients’ disease states. Recombinant 15 kDa GNLY could directly induce cellular communication disorders, inflammation, and apoptosis in HaCaT cells. In addition to its cytotoxic effects, GNLY released from TCE-activated NK cells and NKT cells or synthesized GNLY alone could induce aberrant expression of the E3 ubiquitin ligase PDZRN3, causing dysregulation of the ubiquitination of the cell itself. Consequently, this resulted in the persistent opening of gap junctions composed of connexin43, thereby intensifying cellular inflammation and apoptosis through the “bystander effect”. This study provides experimental evidence elucidating the mechanisms of THS skin damage and offers a novel theoretical foundation for the development of effective therapies targeting severe dermatitis induced by chemicals or drugs.

Abstract The introduction of defect layers into one-dimensional parity-time (PT) symmetric photonic crystals gives rise to resonances within the photonic bandgaps. These resonances can be effectively explained by our generalized temporal coupled mode theory. The scattering properties and dispersion relation of defect modes exhibit distinct characteristics compared to conventional one-dimensional Hermitian photonic crystals with defect layers. By tuning the non-Hermiticity or other model parameters, the modulus of the generalized decay rate can be reduced, consequently, the electric field concentrated within the defect layer strengthens. This arises due to the unique band structure of one-dimensional PT-symmetric photonic crystals, which differs significantly from that of traditional one-dimensional Hermitian photonic crystals. Furthermore, the interaction between multiple resonances is investigated through the introduction of multiple defect layers. Our study not only provides insights into resonance phenomena in defective non-Hermitian systems but also contributes to the design of relevant optical resonance devices.

To study the evolution law of water and mud inrush disasters in the fractured zones of water-rich faults in deep buried tunnels, a self-developed 3D physical model test system was used to conduct experimental research about the evolution process. Additionally, MIDAS GTS NX 2022 version was used to analyze the evolution laws of displacement, stress, pore water pressure, and seepage flow velocity during the excavation process. The findings indicate that in the model testing, tunnel excavation caused different changes in the stress magnitude of the surrounding rock at different positions. The pore water pressure increases correspondingly with the loading water pressure at the same location. The function relationship between the relative water pressure coefficient of any point in the outburst-prevention rock mass, and the vertical distance from that point to the upper boundary of the fault, was obtained through nonlinear fitting. In numerical simulation, excavation affects the vertical displacement of the arch vault more than the arch ring, while it has a greater impact on the horizontal displacement of the arch ring compared to the arch vault. The maximum and minimum principal stresses show significant changes; the pore water pressure at each monitoring point decreases with the increase in excavation distance. The flow velocity of seepage shows a trend of first increasing and then decreasing. The research results can provide relevant references for the prevention of water and mud inrush disasters in fault areas.

The dynamic characteristics of single DNA molecules translocating within micro/nano-channels are fundamental for a wide range of applications such as stretching, separating, mapping, and even sequencing of DNA molecules. In this study, a type of tapered microchannel chip with uniform height for all configurations was fabricated, with the major tapered structure having a length of 13 μm and a width that tapers from 5 μm to 20 μm. The dynamic characteristics such as the trajectories and velocities of λ-DNA molecules translocating from different positions driven by an external DC electric field force were systematically investigated by single-molecule fluorescence imaging technology. Some dynamic characteristics of DNA molecules translocation were found. Considering simply the effects of electrophoretic force and electro-osmotic force on the DNA molecules, the dynamic characteristics of DNA molecules are well understood. For example, the velocity of the DNA molecule is inversely proportional to the diameter of the tapered channel and the turning phenomena of the trajectory of the DNA molecules translocating through microchannels. This study is helpful and proposes new ideas for the design and development of microfluidic chips for the quantitative manipulation of DNA molecules.

In this study, hot compression experiments were conducted on cast TC21 titanium alloy using a Gleeble-1500D thermal simulation compression tester, and the hot-compressed specimens were heat-treated. The data obtained after analyzing the thermal compression of cast TC21 titanium alloy were analyzed to construct a thermal machining diagram with a strain of 0.8 and to optimize the machining window. This study investigated the microstructure of the alloy after hot pressing experiments and heat treatment, applying the study of the microstructure evolution law of cast TC21 titanium alloy. The analysis of the tissue evolution law established the dynamic and static recrystallization volume fraction as a function of heat deformation parameters. The results show that the optimal processing window for cast TC21 titanium alloy is a deformation temperature in the range of 1373 K–1423 K and a strain rate of 0.1 s−1. The increase in deformation volume and deformation temperature both favor recrystallization and make the recrystallization volume fraction increase, but the increase in strain rate will inhibit the increase in the recrystallization degree to some extent. The dynamic and static recrystallization equations for the cast TC21 titanium alloy at different temperatures were constructed. The experimental measurements of recrystallization volume fraction are in good agreement with the predicted values.

Beta transus temperature (βtr) is one of the most crucial features of titanium alloys. It is typically used as the index while designing the heat treatment process for titanium alloys. The βtr is also a significant parameter to optimize the processing technology of titanium alloys. Four machine learning algorithms and one empirical formula is developed in this study to estimate the βtr of titanium alloys: Artificial Neural Networks (ANN), Gauss Processing Regression (GPR), Super Vector Machine (SVM), and Ensemble Regression Trees (ERT). According to the correlation coefficient (R), Mean Absolute Error (MAE) and Root Mean Square Error (RMSE) to verify the accuracy of models, and the experimentally measured phase transition temperature of Ti600 alloy was also used to verify the generalization ability of the model. Choosing the best model to analyze the sensitivity of the elements and determine how each component affects the βtr. The result demonstrated that the ANN model has the highest prediction accuracy among the five models, and different model structures have different effects on predicting new data. The ANN model with 10 neurons has the highest prediction accuracy, while the ANN model with 8 neurons has the strongest generalization ability. The results of the sensitivity analysis proved that all the alloy compositions used as input parameters were valid parameters.

Rainfall interception (I) can considerably influence the transport process of water. The revised sparse Gash model (RSGM) is a tool for determining the I, which assumes that the two climate parameters in the model are equal for all storms. However, few studies have provided additional cases to reexamine the correctness of this assumption and investigated the response of I of single storms to the time-step variability in climatic parameters. Hence, rainfall partitioning was measured during the growing season in 2017 for Pinus tabuliformis, Platycladus orientalis, and Acer truncatum in Northern China, and we ran RSGM on an event basis using different time-step climatic parameters (storm-based, monthly, and fixed) to estimate I. In summary, the modeling accuracy of both cumulative I and individual I was enhanced by increasing the time step of the climatic parameters in this study. These positively support the assumption in the RSGM. These results suggest that it is more appropriate to run the RSGM using fixed climate parameters to estimate I for these tree species during the growing season in northern China. Additionally, the assumption in the RSGM should be appealed to be further confirmed across the widest possible range of species, regions, and time scales. HIGHLIGHTS The reasonableness of an assumption in the revised sparse Gash model (RSGM) was reexamined.; Effects of time-step climatic parameters on the RSGM were compared.; Fixed climatic parameters were more appropriate for the simulation in the studied species.; Simulations of single intercepted events are problematic no matter the time step.; Good model accuracy is from complementation between small and large rainfall events.;

China is plagued by water security and its associated environmental issues under climate change. Clarifying the spatial and temporal changing patterns of ecosystem water yield (WYe) and its driving factors is essential for optimizing climate-resilient development strategies and achieving sustainable development goals. However, the understanding of the spatial and temporal dynamics of WYe changes in China based on continuous time series and their dominant factors has been limited. This creates a challenge to accurately assess water resource dynamics and environmental sustainability under climate change. Therefore, this study explored WYe dynamic trends in China at the grid-scale from 2001 to 2020 based on water balance and remote-sensing datasets. The contribution and dominance of vegetation (leaf area index and net primary productivity), climate (temperature, wind speed, relative humidity, and net radiation), and human activities, were examined. Results showed that WYe changes exhibited an overall increasing trend (3.0 mm/yr, p = 0.1) in China, with 61.5 % and 38.5 % of the regions showing increasing and decreasing trends, respectively. Climate change (dominant area share, 43.6 %) was the primary driver of WYe dynamics in China, followed by vegetation change (23.8 %) and human activities (21.5 %). The dominant driving factors contributing to WYe dynamics in nine river basins were temperature, net primary productivity, net radiation, and relative humidity. The results emphasize that the high spatial heterogeneity of climate-driven WYe changes may exacerbate regional inequalities in water resources. Future vegetation-driven climate intervention programs and ecological restoration should be implemented more cautiously, and regional adaptive programs must be considered to avoid worsening water scarcity further.

Ecological deterioration and water scarcity motivate people to seek a balance between ecological reserves and water consumption in cities located in Semi-humid regions. This study is designed to develop a method for evaluating cooling water-saving characteristics of green space structures. Land surface temperature (TS), vegetation quantity (VQ) and evapotranspiration (ET) of typical green vegetation structures in 50 plots with an average area of 10,000 m2 were studied. Parameters were obtained based on data from three temporal remote sensing images; the surface energy balance algorithm for land (SEBAL) model, single-channel algorithm, and normalized difference vegetation index (NDVI) were utilized in the calculation. The relationships between the TS, VQ, and ET of green land were explored using regression analysis. A comprehensive index (EWI) was proposed to evaluate the cooling and water-saving abilities of different green space structures. Based on assessment results, species were classified into three: good (EWI ≥ 0.795), common (0.795 > EWI ≥ 0.419), and weak (EWI < 0.419). The characteristics of 17 species or species compositions with good cooling and water-saving abilities were summarized as: 1) a mix of the arbor, shrub, and herb, and 2) complete cover of green space by shrub.

The diatom test is a forensic technique that can provide supportive evidence in the diagnosis of drowning but requires the laborious observation and counting of diatoms using a microscopy with too much effort, and therefore it is promising to introduce artificial intelligence (AI) to make the test process automatic. In this article, we propose an artificial intelligence solution based on the YOLOv5 framework for the automatic detection and recognition of the diatom genera. To evaluate the performance of this AI solution in different scenarios, we collected five lab-grown diatom genera and samples of some organic tissues from drowning cases to investigate the potential upper/lower limits of the capability in detecting the diatoms and recognizing their genera. Based on the study of the article, a recall score of 0.95 together with the corresponding precision score of 0.9 were achieved on the samples of the five lab-grown diatom genera via cross-validation, and the accuracy of the evaluation in the cases of kidney and liver is above 0.85 based on the precision and recall scores, which demonstrate the effectiveness of the AI solution to be used in drowning forensic routine.

Among the factors affecting rock mass failure, the stress state has the greatest influence on the mechanical behavior of rock. The mechanical behavior of rock depends on the change of stress path, and the stress of rock mass is closely related to deformation and failure. In order to study the influence of surrounding rock stress state on the failure mode of surrounding rock, based on the theory of elastic mechanics and fracture mechanics, this paper analyzed the stress state of surrounding rock element and crack propagation of surrounding rock, and estimated the potential failure mode of surrounding rock in different areas of a phosphate mine in Yichang. The results showed that: the surrounding rock element is affected by the gradient stress, and a larger stress gradient corresponds to a larger principal stress ratio and variation direction of the surrounding rock. The failure mode of surrounding rock is affected by the coupling effect of principal stress ratio and principal stress direction. Under the action of certain crack angle and appropriate confining pressure, different fracture mechanisms may occur in the surrounding rock compression. But the partition of surrounding rock failure mode region can predict the surrounding rock failure mode to a certain extent.

Ecological restoration (ER) programs play an important role in local and global climate change and carbon management policy interventions. Water resource is a key criterion for assessing the sustainability of ERs. Herein, we explored the spatiotemporal patterns of rainfall interception (RI, an important component of ecosystem water budgets), and its drivers after ER implementation in China. Further, we assessed whether ERs are sustainable by analyzing the trends of RI and water supply. As expected, we found that ERs caused an increase in RI in China from 2001 to 2018 (0.64 mm yr ^−1 , p < 0.01). Changes in the normalized difference vegetation index and leaf area index contributed to a higher change in RI compared with other drivers. The decrease in RI was mainly recorded in the Qinghai–Tibet Plateau in Southwest, northern North, and southern Central and Southern China. Conversely, an increasing trend of RI was recorded in the Loess Plateau in Northwest, Northeast, and East China. Moreover, ERs are not always unsustainable in China, especially in Northeast, East, Central and Southern, and high-latitude regions of northern North China. Even in the Loess Plateau, which was criticized by previous studies, the unsustainability occurred only in the semi-humid region. Future ERs should be prioritized in southern parts of Eastern, Central, and Southern China, and must be appropriately considered in the Northeast and high-latitude regions in North China. It should be alert to the pressures of ERs on water supply, and its demand remains vigilant in the Qinghai–Tibet Plateau and semihumid areas of the Loess Plateau. This study provides new ideas for accurately evaluating the impact of ERs on water security and the sustainability of ERs.