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7050 aluminium alloy is widely used in aerospace industry due to its excellent mechanical properties. 7050 aluminium alloy belongs to Al–Zn–Mg–Cu alloy. Due to the formation of cracks in selective laser melting (SLM) forming of Al–Zn–Mg–Cu alloys, 7050 aluminium alloy is difficult to be applied to forming and manufacturing in this technological field. In order to solve this critical problem, in this paper, titanium dioxide (TiO2) powder was mixed with 7050 aluminium alloy using ball milling method to achieve the effect of eliminating cracks. The cracks in the specimens completely disappeared when the TiO2 additions were 1.5 wt% and 2 wt%. With the addition of TiO2, the grains gradually changed from coarse columnar crystals to fine equiaxed crystals. Combined with the temperature field simulation, the grain refinement and crack elimination mechanism of TiO2 in SLM forming were analysed. The grain refinement is attributed to the formation of Al3Ti. The crack elimination was attributed to the reduction of the intergranular solid-liquid channel length. The maximum values of tensile strength and elongation of 7050 aluminium alloy formed by SLM are achieved at 2 wt% of TiO2. The values are 389 MPa and 8.8 %. The better mechanical properties were attributed to the synergistic effect of crack elimination, Hall-Petch, and Orowan strengthening. This study provides experimental guidance for the preparation of crack-free 7050 aluminium alloy.

Abstract Greenberger-Horne-Zeilinger (GHZ) states, also known as two-component Schrödinger cats, play vital roles in the foundation of quantum physics and the potential quantum applications. Enlargement in size and coherent control of GHZ states are both crucial for harnessing entanglement in advanced computational tasks with practical advantages, which unfortunately pose tremendous challenges as GHZ states are vulnerable to noise. Here we propose a general strategy for creating, preserving, and manipulating large-scale GHZ entanglement, and demonstrate a series of experiments underlined by high-fidelity digital quantum circuits. For initialization, we employ a scalable protocol to create genuinely entangled GHZ states with up to 60 qubits, almost doubling the previous size record. For protection, we take a different perspective on discrete time crystals (DTCs), originally for exploring exotic nonequilibrium quantum matters, and embed a GHZ state into the eigenstates of a tailor-made cat scar DTC to extend its lifetime. For manipulation, we switch the DTC eigenstates with in-situ quantum gates to modify the effectiveness of the GHZ protection. Our findings establish a viable path towards coherent operations on large-scale entanglement, and further highlight superconducting processors as a promising platform to explore nonequilibrium quantum matters and emerging applications.

Abstract Background Relatives of patients with mental illnesses such as schizophrenia and depression experience significant levels of anxiety. Accurately predicting their anxiety levels is crucial for the development of effective anti-anxiety interventions aimed at mitigating associated adverse outcomes. Methods In this cross-sectional study, 238 relatives of patients with mental illness were recruited, and their responses were collected using the generalised anxiety disorder-7 (GAD-7) and simplified coping style questionnaire (SCSQ) scales. One-way analysis of variance and t-test were used to assess the mean scores of GAD-7 and SCSQ among relatives with varying characteristics. Pearson’s correlations were used to examine the correlation between anxiety levels and coping style. Multi-level regression analyses were used to identify the impact of the independent variables on anxiety. Results Among all relatives of patients with mental illness who participated in this survey, 238 completed the questionnaire. Females exhibited a higher mean GAD-7 score (9.72 ± 0.25) compared to males. Among participants aged 18–25 years, the GAD-7 (8.12 ± 0.17) score was the highest. Additionally, relatives of patients experiencing their first episode or with a disease duration of

Illicit discharges into sewer systems are a widespread concern within China's urban drainage management. They can result in unforeseen environmental contamination and deterioration in the performance of wastewater treatment plants. Consequently, pinpointing the origin of unauthorized discharges in the sewer network is crucial. This study aims to evaluate an integrative method that employs numerical modeling and statistical analysis to determine the locations and characteristics of illicit discharges. The Storm Water Management Model (SWMM) was employed to track water quality variations within the sewer network and examine the concentration profiles of exogenous pollutants under a range of scenarios. The identification technique employed Bayesian inference fused with the Markov chain Monte Carlo sampling method, enabling the estimation of probability distributions for the position of the suspected source, the discharge magnitude, and the commencement of the event. Specifically, the cases involving continuous release and multiple sources were examined. For single-point source identification, where all three parameters are unknown, concentration profiles from two monitoring sites in the path of pollutant transport and dispersion are necessary and sufficient to characterize the pollution source. For the identification of multiple sources, the proposed SWMM-Bayesian strategy with improved sampling is applied, which significantly improves the accuracy. HIGHLIGHTS Identifying pollution sources can be applied for both instantaneous and continuous discharge scenarios.; To characterize a single pollution source, data from two monitoring sites along the pollutant's path are necessary and sufficient.; The strategic placement of monitoring sites and improved sampling enhance the effectiveness and precision of the Bayesian-SWMM approach for identifying multiple unauthorized discharge sources.;

Photocatalytic pathways are essential for the sustainable production of chemicals and fuels, pivotal for achieving a pollution-free planet. Electron-hole recombination is a critical problem that has, so far, limited the efficiency of the photocatalytic materials. Here, oxygen-deficient WO3-x nanosheets were in situ grown in a polymeric carbon nitride (PCN) support during the thermal polycondensation of melamine. The introduction of defect in WO3-x, accompanied by spin polarization and the formed WO3-x/PCN heterostructure, greatly accelerated the charge separation and transfer. The synthesized WO3-x/PCN composite exhibited a tenfold increase in hydrogen generation activity than pure PCN under visible-light (420 ≤ λ ≤ 780 nm). The WO3-x/PCN also demonstrated consecutive 24 h and stable photocatalytic H2 production in the aqueous plastic-containing [poly(vinyl alcohol) (PVA), poly(ethylene terephthalate) (PET) and the PET bottle] solutions under visible light. The hydrogen production rates were determined to be 111.2, 50.5, and 7.8 μmol·h−1·g−1 in PVA, PET and PET bottle, respectively. In addition, the oxygen vacancies WO3 with their localized surface plasmon resonance effect, facilitated efficient utilization of NIR photon and the hydrogen evolution rate over WO3-x/PCN reached to 120 μmol h−1·g−1 under NIR light (700 ≤ λ ≤ 780 nm). This research not only advances the potential applications of WO3-x/PCN in sustainable energy production but also provides insights into environmental remediation through the conversion of plastic wastes.

Background and purposeDistant metastasis in bladder cancer is linked to poor prognosis and significant mortality. Machine learning (ML), a key area of artificial intelligence, has shown promise in the diagnosis, staging, and treatment of bladder cancer. This study aimed to employ various ML techniques to predict distant metastasis in patients with bladder cancer.Patients and methodsPatients diagnosed with bladder cancer in the Surveillance, Epidemiology, and End Results (SEER) database from 2000 to 2021 were included in this study. After a rigorous screening process, a total of 4,108 patients were selected for further analysis, divided in a 7:3 ratio into a training cohort and an internal validation cohort. In addition, 118 patients treated at the Second Affiliated Hospital of Nanchang University were included as an external validation cohort. Features were filtered using the least absolute shrinkage and selection operator (LASSO) regression algorithm. Based on the significant features identified, three ML algorithms were utilized to develop prediction models: logistic regression, support vector machine (SVM), and linear discriminant analysis (LDA). The predictive performance of the three models was evaluated by obtaining the area under the receiver operating characteristic (ROC) curve (AUC), the precision, the accuracy, and the F1 score.ResultsAccording to the statistical results, the final probability of distant metastasis in the population was 12.0% (n = 495). LASSO regression analysis revealed that age, chemotherapy, tumor size, the examination of non-regional lymph nodes, and regional lymph node evaluation were significantly associated with distant metastasis of bladder cancer. In the internal validation cohort, the prediction accuracy rates for logistic regression, SVM, and LDA were 0.874, 0.877, and 0.845, respectively. The precision rates were 0.805, 0.769, and 0.827, respectively, and the F1 scores were 0.821, 0.819, and 0.835, respectively. The ROC curve demonstrated that the AUC for all models was greater than 0.7. In the external validation cohort, the prediction accuracy rates for logistic regression, SVM, and LDA were 0.856, 0.848, and 0.797, respectively, with the ROC curve indicating that the AUC also exceeded 0.7. The precision rates were 0.877, 0.718, and 0.736, respectively, and the F1 scores were 0.797, 0.778, and 0.762, respectively. Among the algorithms used, logistic regression demonstrated better predictive efficiency than the other two methods. The top three variables with the highest importance scores in the logistic regression were non-regional lymph nodes, age, and chemotherapy.ConclusionThe prediction model developed using three ML algorithms demonstrated strong accuracy and discriminative capability in predicting distant metastasis in patients with bladder cancer. This might help clinicians in understanding patient prognosis and in formulating personalized treatment strategies, ultimately improving the overall prognosis of patients with bladder cancer.

Minimum mortality temperature (MMT) increases with global warming due to climate adaptation, which is crucial for the precise assessment of mortality burden attributed to climate change. Nevertheless, forecasting future MMT poses a challenge given the unavailability of future mortality data. Here, we attempted to develop a novel approach to project future MMT. First, we estimated the MMT of 334 locations in China using a distributed lag nonlinear model. Then, meta regression models were applied to investigate the associations between MMT and several temperature variables(Most Frequent Temperature(MFT), average daily mean temperature, average daily minimum temperature, average daily maximum temperature and percentiles of temperature from 1st to 100th). A generalized linear regression model was employed to investigate whether significant differences existed in the relationships between MMT and temperature from the 1st to the 100th percentile. Finally, an optional indicator of MMT for projecting future values was identified. Our results indicated that temperatures in the 85th to 89th percentiles were closely associated with MMT, with the 88th percentile temperature serving as the most effective indicator, as confirmed by meta-regression models. Using the 88th percentile of temperature as alternative indicator of MMT, compared with the period of 2006–2015, the projected MMT in most districts and counties in China tended to rise under three representative concentration pathways (RCPs) in the 2030 s (2030–2039), 2060 s (2060–2069), and 2090 s (2090–2099). Our findings provide some insight to project future MMT for assessing mortality burden related to temperature change driven by global warming.

PurposeRobot-assisted laparoscopic partial nephrectomy (RAPN) has become a key technology in the treatment of renal tumors. Effective preoperative planning and precise intraoperative navigation are critical to a successful surgical outcome. This study aimed to evaluate the clinical application value of mixed reality (MR) in robotic nephron-sparing partial nephrectomy for patients with renal tumors of different complexity based on the R.E.N.A.L. score.Patients and methodsA retrospective analysis was conducted on 68 eligible patients with renal cancer who underwent RAPN at The Second Affiliated Hospital of Nanchang University from January 2021 to December 2023, with postoperative pathology confirmation. Patients were divided into two groups: the MR group, with 28 cases, and the traditional imaging (control) group, with 40 cases. All patients underwent mid-abdominal CT plain scans and enhancements. The MR group utilized three-dimensional reconstruction of CT data and employed 3D tablets and HoloLens glasses for preoperative discussions, surgical planning, and intraoperative guidance. Collect clinical data and metrics to assess surgical outcomes, as well as evaluate performance in areas such as preoperative discussions, doctor-patient communication, surgical planning, and intraoperative navigation.ResultsCompared to robot-assisted partial nephrectomy in the control group, the MR group experienced a reduction in operation time by approximately 30 min [(135.89 ± 23.494) min vs. (165.00 ± 34.320) min, P< 0.001)] and a decrease in ischemia time by around 2.5 min [(20.36 ± 3.956) min vs. (23.80± 6.889) min, P = 0.02)]. Within the subgroup with a R.E.N.A.L. score of less than 7 points, the MR group only showed a significant reduction in operation time [(134.55 ± 150.190) min vs. (150.19 ± 28.638) min, P = 0.045], with no notable differences in other parameters. For the subgroup with a R.E.N.A.L. score of 7 points or higher, the MR group exhibited shorter operation time [(140.83 ± 25.183) min vs. (195.77 ± 23.080) min, P< 0.001] and reduced warm ischemia time [(21.17 ± 2.714) min vs. (28.85 ± 7.570) min, P = 0.029]. Additionally, there was less estimated blood loss [(53.33 ± 5.164) min vs. (114.62 ± 80.376) min, P = 0.018]. All patients had negative resection margins, indicating equivalent therapeutic outcomes between the two groups.ConclusionIn comparison to traditional RAPN, MR technology demonstrates the ability to decrease operation time and warm ischemia time all the while maintaining equivalent curative outcomes. Additionally, it enhances preoperative discussions, doctor-patient interactions, preoperative strategizing, and intraoperative navigation, particularly excelling in complex renal tumor cases of RAPN, where its benefits are most pronounced.

Abstract LHPP has been shown to be a new tumor suppressor, and has a tendency to be under-expressed in a variety of cancers. Oncolytic virotheray is a promising therapeutics for lung cancer in recent decade years. Here we successfully constructed a new recombinant oncolytic adenovirus GD55-LHPP and investigated the effect of GD55-LHPP on the growth of lung cancer cells in vitro and in vivo. The results showed that LHPP had lower expression in either lung cancer cells or clinical lung cancer tissues compared with normal cells or tissues, and GD55-LHPP effectively mediated LHPP expression in lung cancer cells. GD55-LHPP could effectively inhibit the proliferation of lung cancer cell lines and rarely affected normal cell growth. Mechanically, the oncolytic adenovirus GD55-LHPP was able to induce stronger apoptosis of lung cancer cells compared with GD55 through the activation of caspase signal pathway. Notably, GD55-LHPP also activated autophagy-related signal pathway. Further, GD55-LHPP efficiently inhibited tumor growth in lung cancer xenograft in mice and prolonged animal survival rate compared with the control GD55 or PBS. In conclusion, the novel construct GD55-LHPP provides a valuable strategy for lung cancer-targeted therapy and develop the role of tumor suppress gene LHPP in lung cancer gene therapy.

Ventilation is paramount in sanitary and stormwater sewer systems to mitigate odor problems and avert pressure surges. Existing numerical models have constraints in practical applications in actual sewer systems due to insufficient airflow modeling or suitability only for steady-state conditions. This research endeavors to formulate a mathematical model capable of accurately simulating various operational conditions of sewer systems under the natural ventilation condition. The dynamic water flow is modeled using a shock-capturing MacCormack scheme. The dynamic airflow model amalgamates energy and momentum equations, circumventing laborious pressure iteration computations. This model utilizes friction coefficients at interfaces to enhance the description of the momentum exchange in the airflow and provide a logical explanation for air pressure. A systematic analysis indicates that this model can be easily adapted to include complex boundary conditions, facilitating its use for modeling airflow in real sewer networks. Furthermore, this research uncovers a direct correlation between the air-to-water flow rate ratio and the filling ratio under natural ventilation conditions, and an empirical formula encapsulating this relationship is derived. This finding offers insights for practical engineering applications. HIGHLIGHTS The non-steady conditions were considered.; Existing models were improved to address the instability issue in coupled water and air calculations.; The relationship between the airflow and the water level under non-steady conditions was investigated.; The validation of the established model was conducted, demonstrating its effectiveness and feasibility.; Factors influencing the airflow were analyzed.;

Purpose Develop an albumin nanoparticle-based nanoprobe for targeted glioblastoma (GBM) diagnosis and treatment, utilizing Angopep-2 for low-density lipoprotein receptor-related protein (LRP) targeting. Methods Combined albumin-coated superparamagnetic iron oxide (SPIO), Carmustine (BCNU), and indocyanine green (ICG). Assessed morphology, size, Zeta potential, fluorescence, and drug encapsulation. Conducted in vitro fluorescence/MRI imaging and cell viability assays, and in vivo nanoprobe accumulation evaluation in brain tumors. Results ANG-BSA/BCNU/ICG MNPs exhibited superior targeting and cytotoxicity against GBM cells in vitro. In vivo, enhanced brain tumor accumulation during imaging was observed. Conclusion This targeted imaging and drug delivery system holds promise for efficient GBM therapy and intraoperative localization, addressing Blood-brain barrier (BBB) limitations with precise drug delivery and imaging capabilities.

Neonicotinoid insecticides (NEOs) have been extensively approved for application in agricultural production both in China and globally. Previous studies indicated that human exposure to NEOs would have adverse health effects. However, studies on occurrences of NEOs in kidney injury patients and their association with nephrotoxicity are limited. This study investigates the potential correlation between exposure to NEOs and kidney injury within a subset (n = 224) of the population residing in South China. Levels of 8 NEOs and 5 metabolites were quantified in blood samples obtained from both the 110 healthy and 114 kidney injury cohorts in South China. We found that target analytes were frequently detected in samples from the healthy and kidney injury cohorts (61%–100 %). Dinotefuran is the predominant NEO in the healthy (42.3 %) and kidney injury cohort (49.6 %). Significantly positive (p

Introduction: While ambient formaldehyde (HCHO) concentrations are increasing worldwide, there was limited research on its health effects. Objectives: To assess the association of long-term exposure to ambient HCHO with the risk of respiratory (RESP) mortality and the associated mortality burden in China. Methods: Annual and seasonal RESP death and tropospheric HCHO vertical columns data were collected in 466 counties/districts across China during 2013–2016. A difference-in-differences approach combined with a generalized linear mixed-effects regression model was employed to assess the exposure-response association between long-term ambient HCHO exposure and RESP mortality risk. Additionally, we computed the attributable fraction (AF) to gauge the proportion of RESP mortality attributable to HCHO exposure. Results: This analysis encompassed 560,929 RESP deaths. The annual mean ambient HCHO concentration across selected counties/districts was 8.02×1015 ± 2.22×1015 molec.cm−2 during 2013–2016. Each 1.00×1015 molec.cm−2 increase in ambient HCHO was associated with a 1.61 % increase [excess risk (ER), 95 % confidence interval (CI): 1.20 %, 2.03 %] in the RESP mortality risk. The AF of RESP mortality attributable to HCHO was 12.16 % (95 %CI:9.33 %, 14.88 %), resulting in an annual average of 125,422 (95 %CI:96,404, 153,410) attributable deaths in China. Stratified analyses suggested stronger associations in individuals aged ≥65 years old (ER=1.87 %, 95 %CI:1.43 %, 2.32 %), in cold seasons (ER=1.00 %, 95 %CI:0.56 %, 1.44 %), in urban areas (ER=1.65 %, 95 %CI:1.15 %, 2.16 %), and in chronic obstructive pulmonary disease patients (ER=1.95 %, 95 %CI:1.42 %, 2.48 %). Conclusions: This study suggested that long-term HCHO exposure may significantly increase the risk of RESP mortality, leading to a substantial mortality burden. Targeted measures should be implemented to control ambient HCHO pollution promptly.

Background: Global warming has provoked more co-occurrence of hot extreme and dry extreme, namely compound hot-dry events (CHDEs). However, their health impacts have seldom been investigated. This study aimed to characterize CHDEs and assess its mortality burden in China from 1990 to 2100. Methods: CHDEs were defined as a day when daily maximum temperature > its 90th percentile and Standardized Precipitation Index

Rainfall-derived inflow/infiltration (RDII) modelling during heavy rainfall events is essential for sewer flow management. In this study, two machine learning algorithms, random forest (RF) and long short-term memory (LSTM), were developed for sewer flow prediction and RDII estimation based on field monitoring data. The study implemented feature engineering for extracting physically significant features in sewer flow modelling and investigated the importance of the relevant features. The results from two case studies indicated the superior capability of machine learning models in RDII estimation in the combined and separated sewer systems, and LSTM model outperformed the two models. Compared to traditional methods, machine learning models were capable of simulating the temporal variation in RDII processes and improved prediction accuracy for peak flows and RDII volumes in storm events. HIGHLIGHTS Machine learning models, particularly the LSTM model, outperformed traditional methods in estimating RDII in sewer systems.; Feature engineering techniques allowed for the extraction of physically significant features in sewer flow modelling.; Machine learning models successfully simulated the temporal variation in RDII processes, resulting in improved accuracy for predicting peak flows and RDII volumes during storm events.;

Abstract Social defeat stress is associated with endoplasmic reticulum (ER) stress, inflammation and apoptosis. ER stress is thought to contribute to many lifestyle diseases such as liver injury, cardiovascular dysfunction and depression. We investigated the expression of the ER stress markers RNA-dependent protein kinase-like ER kinase (PERK), eukaryotic translation initiation factor 2α (eIF2α) and C/EBP homologous protein (CHOP), as well as inflammatory and apoptotic factors, to assess how social defeat stress induces liver injury. Furthermore, we evaluated the effects of the ER stress inhibitor phenylbutyric acid (PBA) and ER stress inducer thapsigargin (TG) on liver injury. Adult mice were divided into the control, social defeat, social defeat + PBA, TG, PBA and TG + PBA groups. The social defeat and social defeat + PBA groups were simultaneously exposed to social defeat stress for 10 days. The social defeat + PBA, TG, PBA and TG + PBA groups were treated with PBA or TG via intraperitoneal injections. PBA was injected 1 h before the TG injection into the TG + PBA group. Liver samples from six groups of mice were analyzed by histological analysis and western blotting. Social defeat stress promoted ER stress, increased the expression of inflammatory factors and induced apoptosis in the liver of socially defeated mice, which was reversed by PBA. Moreover, ER stress induces TG-induced liver injury by initiating ER stress. Social defeat stress initiates ER stress, promotes the expression of inflammatory and apoptotic factors, and induces liver injury. PBA suppresses liver injury caused by social defeat stress and TG treatment.

As an important component of the deep tunnel drainage system for dealing with urban waterlogging, the rotating stepped dropshaft has been proposed due to its small air entrainment. However, the hydraulic characteristics inside the shaft still need to be fully studied. In this study, the flow patterns, water velocity, and pressure in the rotating stepped dropshaft under different flow rates and geometric parameters were studied using a three-dimensional numerical model. The results show that increasing the central angle of the step and reducing the step height can both reduce the terminal velocity. A theoretical formula for predicting the terminal velocity was established and well validated. The connection between the shaft and the outlet pipe poses a severe threat to the structural safety due to alternating positive and negative pressures. Wall-attached swirling flow generates a circular high-pressure zone at the bottom of the dropshaft and the larger the flow rate, the greater the pressure gradient at the center of the bottom. By using the momentum theorem and considering the impact pressure range of the swirling flow, the shaft bottom pressure can be predicted reasonably well. HIGHLIGHTS The hydraulic characteristics of rotating stepped dropshafts are analyzed and the terminal velocity is evaluated theoretically and well validated.; The pressure distribution inside rotating stepped dropshafts and the impact effect of the wall-attached swirling flow on the shaft bottom are determined.; A simplified theoretical model is established to predict the impact pressure of the shaft.;

Abstract The direct use of flue gas for the electrochemical CO2 reduction reaction is desirable but severely limited by the thermodynamically favorable oxygen reduction reaction. Herein, a photonicswitching unit 1,2-Bis(5’-formyl-2’-methylthien-3’-yl)cyclopentene (DAE) is integrated into a cobalt porphyrin-based covalent organic framework for highly efficient CO2 electrocatalysis under aerobic environment. The DAE moiety in the material can reversibly modulate the O2 activation capacity and electronic conductivity by the framework ring-closing/opening reactions under UV/Vis irradiation. The DAE-based covalent organic framework with ring-closing type shows a high CO Faradaic efficiency of 90.5% with CO partial current density of −20.1 mA cm−2 at −1.0 V vs. reversible hydrogen electrode by co-feeding CO2 and 5% O2. This work presents an oxygen passivation strategy to realize efficient CO2 electroreduction performance by co-feeding of CO2 and O2, which would inspire to design electrocatalysts for the practical CO2 source such as flue gas from power plants or air.

Chemical Exchange Saturation Transfer (CEST) is a technique that uses specific off-resonance saturation pulses to pre-saturate targeted substances. This process influences the signal intensity of free water, thereby indirectly providing information about the pre-saturated substance. Among the clinical applications of CEST, Amide Proton Transfer (APT) is currently the most well-established. APT can be utilized for the preoperative grading of gliomas. Tumors with higher APTw signals generally indicate a higher likelihood of malignancy. In predicting preoperative molecular typing, APTw values are typically lower in tumors with favorable molecular phenotypes, such as isocitrate dehydrogenase (IDH) mutations, compared to IDH wild-type tumors. For differential diagnosis, the average APTw values of meningiomas are significantly lower than those of high-grade gliomas. Various APTw measurement indices assist in distinguishing central nervous system lesions with similar imaging features, such as progressive multifocal leukoencephalopathy, central nervous system lymphoma, solitary brain metastases, and glioblastoma. Regarding prognosis, APT effectively differentiates between tumor recurrence and treatment effects, and also possesses predictive capabilities for overall survival (OS) and progression-free survival (PFS).

Objective To compare the ability of gadolinium ethoxybenzyl dimeglumine (Gd-EOB-DTPA) and gadobenate dimeglumine (Gd-BOPTA) to display the 3 major features recommended by the Liver Imaging Reporting and Data System (LI-RADS 2018v) for diagnosing hepatocellular carcinoma (HCC). Materials and Methods In this retrospective study, we included 98 HCC lesions that were scanned with either Gd-EOB-DTPA-MR or Gd-BOPTA-M.For each lesion, we collected multiple variables, including size and enhancement pattern in the arterial phase (AP), portal venous phase (PVP), transitional phase (TP), delayed phase (DP), and hepatobiliary phase (HBP). The lesion-to-liver contrast (LLC) was measured and calculated for each phase and then compared between the 2 contrast agents. A P value 0.750). When conducting a total evaluation of the combined data across the 5 phases, the display efficiency was excellent (AUC > 0.950). Conclusion Gd-BOPTA and Gd-EOB-DTPA are liver-specific contrast agents widely used in clinical practice. They have their own characteristics in displaying the 3 main signs of HCC. For accurate noninvasive diagnosis, the choice of agent should be made according to the specific situation.

Background: Although the health impacts of ambient ozone (O3) have been widely assessed, studies simultaneously investigating the acute and chronic effects of O3 on mortality from respiratory diseases (RESP) are scarce. Methods: We extracted personal information of all recorded deaths from RESP throughout 2013–2018 in six provinces in China. The daily, seasonal, and annual mean air pollutant concentrations at the township/subdistrict level were estimated by a random forest model. The acute association between the maximum daily average 8h ozone (MDA8 O3) and RESP mortality was examined by a time-stratified case-crossover study design, and the chronic association was estimated by a difference-in-differences (DID) analysis approach. We also calculated the attributable fraction (AF) of RESP mortality attributable to MDA8 O3. Results: There were 1,034,226 RESP deaths included in this study. The excess risks (ERs) of overall RESP mortality for each 10 μg/m3 increase in short-term (lag03 days) and long-term (one-year average) exposure to MDA8 O3 were 0.38 % (95%CI: 0.26 %, 0.50 %) and 4.37 % (3.91 %, 4.84 %), respectively. The AFs of overall RESP mortality ascribed to short- and long-term MDA8 O3 exposures were 3.00 % (2.03 %, 3.95 %) and 29.45 % (26.86 %, 31.95 %), respectively. The average annual number of RESP deaths attributable to short-term MDA8 O3 exposure was 30,790 and 302,254 were attributable to long-term MDA8 O3 exposure across China during 2013–2018. Conclusion: Both short- and long-term exposure to ambient MDA8 O3 were positively associated with RESP mortality, and long-term exposure to MDA8 O3 may lead to a greater RESP mortality burden than short-term exposure to MDA8 O3.