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Sexual reproduction through seeds is an effective way to renew plant populations and increase their genetic diversity, but seed germination process is complicated and relatively difficult due to the restriction of environmental conditions. Wetland plants that reproduce sexually through seeds may be affected by changes in moisture and temperature. This study aims to explore the ecological adaptation strategies of seed germination of Lilium concolor var. megalanthum under different hydrothermal conditions. Controlled experiments were conducted to investigate the germination performance of L. concolor var. megalanthum seeds at different temperatures (10°C, 15°C, 20°C, 25°C, and 30°C) and simulated drought stress conditions using PEG-6000 solutions (0%, 5%, 10%, 15%, and 20%). The results showed that temperature, drought stress, and their interaction significantly affected the days to first germination, germination percentage, coefficient of germination rate, germination energy, germination index, and vigor index of seeds (p

Mercury (Hg), as a global pollutant, is persistent, migratory, insidious, highly biotoxic and highly enriched, and is widely distributed in the atmosphere, hydrosphere, biosphere and lithosphere. Wetland ecosystems, as active mercury reservoirs, have become the most important sources and sinks of heavy metal mercury. Distinguished from natural wetlands, artificial wetlands located in urban sections of rivers face problems such as diverse urban pollution sources and complex spatial and temporal changes. Therefore, in this study, five intermittently distributed artificial wetlands were selected from the upstream to the downstream of the Changchun section of the Yitong River, a tributary of the Songhua River basin in the old industrial base of Northeast China. The mercury levels in the water bodies, sediments and plants of the artificial wetlands were collected and tested in four quarters from April 2023 to analyse the spatial and temporal distribution characteristics of total mercury. The results showed that the mercury levels in the water bodies, sediments and plants of the five wetlands showed a fluctuating trend with the river flow direction and had certain spatial and temporal distribution characteristics. This phenomenon was attributed to the sinking of external mercury pollution sources. In general, the wetland ecosystems showed a decreasing trend in the total Hg output of the downstream watershed. This may be due to the retention of particulate matter by aquatic plants in artificial wetlands to regular salvage of dead aquatic plants. At the same time urbanization and industrialization affect mercury levels in aquatic environments, so the risk of residential exposure needs to be looked at.

Background: To investigate the correlation between inflammasomes and coronary artery calcification (CAC), and develop and validating a nomogram for predicting the risk of CAC in patients with coronary artery disease (CAD). Methods: A total of 626 patients with CAD at the Affiliated Hospital of Xuzhou Medical University were enrolled in this study. The patients were divided into the calcification group and the non-calcification group based on the assessment of coronary calcification. We constructed a training set and a validation set through random assignment. The least absolute shrinkage and selection operator (LASSO) regression and multivariate analysis were performed to identify independent risk factors of CAC in patients with CAD. Based on these independent predictors, we developed a web-based dynamic nomogram prediction model. The area under the receiver operating characteristic curve (AUC-ROC), calibration curves, and decision curve analysis (DCA) were used to evaluate this nomogram. Results: Age, smoking, diabetes mellitus (DM), hyperlipidemia, the serum level of nucleotide-binding oligomerization domain (NOD)-like receptor protein 1 (NLRP1), alkaline phosphatase (ALP) and triglycerides (TG) were identified as independent risk factors of CAC. The AUC-ROC of the nomogram is 0.881 (95% confidence interval (CI): 0.850–0.912) in the training set and 0.825 (95% CI: 0.760–0.876) in the validation set, implying high discriminative ability. Satisfactory performance of this model was confirmed using calibration curves and DCA. Conclusions: The serum NLRP1 level is an independent predictor of CAC. We established a web-based dynamic nomogram, providing a more accurate estimation and comprehensive perspective for predicting the risk of CAC in patients with CAD.

Background: Breast cancer is one of the most common malignant tumors in women. A noninvasive ultrasound examination can identify mammary-gland-related diseases and is well tolerated by dense breast, making it a preferred method for breast cancer screening and of significant clinical value. However, the diagnosis of breast nodules or masses via ultrasound is performed by a doctor in real time, which is time-consuming and subjective. Junior doctors are prone to missed diagnoses, especially in remote areas or grass-roots hospitals, due to limited medical resources and other factors, which bring great risks to a patient’s health. Therefore, there is an urgent need to develop fast and accurate ultrasound image analysis algorithms to assist diagnoses. Methods: We propose a breast ultrasound image-based assisted-diagnosis method based on convolutional neural networks, which can effectively improve the diagnostic speed and the early screening rate of breast cancer. Our method consists of two stages: tumor recognition and tumor classification. (1) Attention-based semantic segmentation is used to identify the location and size of the tumor; (2) the identified nodules are cropped to construct a training dataset. Then, a convolutional neural network for the diagnosis of benign and malignant breast nodules is trained on this dataset. We collected 2057 images from 1131 patients as the training and validation dataset, and 100 images of the patients with accurate pathological criteria were used as the test dataset. Results: The experimental results based on this dataset show that the MIoU of tumor location recognition is 0.89 and the average accuracy of benign and malignant diagnoses is 97%. The diagnosis performance of the developed diagnostic system is basically consistent with that of senior doctors and is superior to that of junior doctors. In addition, we can provide the doctor with a preliminary diagnosis so that it can be diagnosed quickly. Conclusion: Our proposed method can effectively improve diagnostic speed and the early screening rate of breast cancer. The system provides a valuable aid for the ultrasonic diagnosis of breast cancer.

Plant pathogens present in soil cause severe losses to plants every year. Among them, Ralstonia solanacearum, because of its destructive nature, is the world’s second most damaging bacterial phytopathogen. Over 310 species of plants belonging to 42 plant families are infected by this deadly pathogen. Around the world, the bacterial wilt (BW) disease causes yield losses that range from 20 to 100%. Control measures for managing this pathogen comprises several diverse approaches. Regardless of whether several control methods are developed to manage the BW disease, efficient management strategies with eco-friendly effects and the desired level of effective control is still awaited and there is need to developed effective management methods to eliminate this fetal disease in several crops under field conditions. An analysis of development in the management strategies will provide an effective way to search and develop control methods with desirable level of effectiveness. In this review, we discussed and analyzed the information reported on the development of various management strategies for the management of R. solanacearum along with the comprehensive presentation on action mechanism of these management strategies. We have also made an effort to summarize the challenges that make hurdle in the effective management of this deadly pathogen. The analysis of the information in this review article will assist in future implications of management strategies and help in developing effective control measures with more efficacy.

Background. The pathogenesis of coronary artery disease is complex, and inflammation is one of the regulatory factors. The nucleotide-binding oligomerization domain (NOD)-like receptor protein 1 (NLRP1) plays an important role in the cellular inflammatory response, cell apoptosis, cell death, and autoimmune diseases. Whether the level of NLRP1 is related to the severity of coronary artery stenosis in patients with coronary artery disease (CAD) has not been reported. Objective. To test the serum level of NLRP1 in unstable angina (UA) patients and investigate the effect of NLRP1 on coronary stenosis severity of the coronary artery disease (CAD). Methods. 307 patients hospitalized in the Department of Cardiology of the Affiliated Hospital of Xuzhou Medical University for coronary angiography from January 1, 2021, to December 31, 2022 were included. We detect the level of NLRP1 in the serum of the included patients. Patients were divided into UA group and control group according to coronary angiography results and other clinical data. We use logistic regression to screen the influencing factors of UA. Then, subgroups were divided according to the Gensini score and the number of coronary artery lesions, and the difference of serum NLRP1 level between the groups was compared. Spearman correlation analysis was used to explore the correlation between the serum NLRP1 level and Gensini score. We analyze the diagnostic value of NLRP1 for UA by drawing ROC curve. Results. The median level of serum NLRP1 in patients with UA (n = 257) was 49.71 pg/ml, IQR 30.15, 80.21, and that in patients without UA (n = 50) was 24.75 pg/ml, IQR 13.49, 41.95. Serum NLRP1 levels were significantly different among different subgroups. The patient’s Gensini score was correlated with the patient’s serum NLRP1 level. Conclusion. The serum NLRP1 level is increased in patients with UA, which is increased with the increasing severity of coronary lesions.

Dam safety assessment is usually conducted regularly to investigate the risks associated with the dam and propose remedies to ensure effective reservoir operations. One crucial aspect of the evaluation involves performing hydrological analyses to determine if the existing spillway can successfully deliver the probable maximum flood (PMF) downstream. This study applied storm transposition and typhoon rainstorm methods for PMP estimations. The resulting PMP values were then used as input for runoff models to generate flood hydrographs for PMF determination. A modification for the storm transposition method was proposed to determine the barrier height considering the moisture inflow direction. In estimating the orographic rainfall in the typhoon rainstorm model, an effective terrain slope was suggested according to different windward directions based on DEM analysis. Shihmen Reservoir and Feitsui Reservoir, located in northern Taiwan, were used as examples to conduct the PMP and PMF analysis. The obtained PMPs were further compared with the results generated by Hershfield’s method to assess the reasonability of the estimation. The results show that the maximum deviation of the 24-h PMP values estimated by the three methods is within 30% in the Shihmen watershed and 16% in the Feitsui watershed. The PMF estimations in the two reservoir watersheds are larger than the design discharges of the existing spillways. Hence, extending the capacity of the existing spillways or constructing upstream bypasses to avoid catastrophic flooding downstream is required.

In recent years, artificial intelligence (AI) technology has promoted the development of electroencephalogram (EEG) emotion recognition. However, existing methods often overlook the computational cost of EEG emotion recognition, and there is still room for improvement in the accuracy of EEG emotion recognition. In this study, we propose a novel EEG emotion recognition algorithm called FCAN–XGBoost, which is a fusion of two algorithms, FCAN and XGBoost. The FCAN module is a feature attention network (FANet) that we have proposed for the first time, which processes the differential entropy (DE) and power spectral density (PSD) features extracted from the four frequency bands of the EEG signal and performs feature fusion and deep feature extraction. Finally, the deep features are fed into the eXtreme Gradient Boosting (XGBoost) algorithm to classify the four emotions. We evaluated the proposed method on the DEAP and DREAMER datasets and achieved a four-category emotion recognition accuracy of 95.26% and 94.05%, respectively. Additionally, our proposed method reduces the computational cost of EEG emotion recognition by at least 75.45% for computation time and 67.51% for memory occupation. The performance of FCAN–XGBoost outperforms the state-of-the-art four-category model and reduces computational costs without losing classification performance compared with other models.

Background Dysimmunity plays a key role in diabetes, especially type 1 diabetes mellitus. Islet-specific autoantibodies (ISAs) have been used as diagnostic markers for different phenotypic classifications of diabetes. This study was aimed to explore the relationships between ISA titers and the clinical characteristics of diabetic patients. Methods A total of 509 diabetic patients admitted to Department of Endocrinology and Metabolism at the Affiliated Hospital of Nantong University were recruited. Anthropometric parameters, serum biochemical index, glycosylated hemoglobin, urinary microalbumin/creatinine ratio, ISAs, fat mass, and islet β-cell function were measured. Multiple linear regression analysis was performed to identify relationships between ISA titers and clinical characteristics. Results Compared with autoantibody negative group, blood pressure, weight, total cholesterol (TC), low density lipoprotein cholesterol (LDL-C), visceral fat mass, fasting C-peptide (FCP), 120 minutes C-peptide (120minCP) and area under C-peptide curve (AUCCP) of patients in either autoantibody positive or glutamate decarboxylase antibody (GADA) positive group were lower. Body mass index (BMI), waist circumference, triglycerides (TGs), body fat mass of patients in either autoantibody positive group were lower than autoantibody negative group. GADA titer negatively correlated with TC, LDL-C, FCP, 120minCP, and AUCCP. The islet cell antibody and insulin autoantibody titers both negatively correlated with body weight, BMI, TC, TG, and LDL-C. After adjusting confounders, multiple linear regression analysis showed that LDL-C and FCP negatively correlated with GADA titer. Conclusion Diabetic patients with a high ISA titer, especially GADA titer, have worse islet β-cell function, but less abdominal obesity and fewer features of the metabolic syndrome.

Mercury is a global pollutant that has attracted widespread attention due to its persistence, concealment, and ease of migration. As the main setting for human production and life, urban ecosystems play significant roles in the global mercury cycle. Urban vegetation also plays an important role in regional mercury cycles. In this study, several common tree species in the green vegetation of Changchun were used as research objects to examine the mercury pollution characteristics of leaf litter and the surrounding soil. In this investigation, 100 sampling sites were set up in Changchun City to collect leaf litter and the surrounding topsoil. An RA-915+ Hg analyzer was used to determine the total mercury concentration levels. The results showed that content levels of mercury in plants ranged between 0.0133 and 0.1945 mg/kg, and different species displayed varying levels of mercury accumulation. For example, the content of mercury in Pyrus ussuriensis Maxim. was found to be 0.0755 mg/kg higher than that in the other examined subjects. It was also determined that the plant mercury concentration levels were the highest in the older industrial zones, while the lowest mercury levels were found in the new economic development zones. Furthermore, the plant mercury levels of the roadside areas were higher due to vehicle pollution discharge. Regarding the mercury pollution levels of the surface-layer soil, the soil of old industrial zones’ surface layers had higher levels of mercury pollution than the other tested sites. However, no notable connection was observed between the mercury concentration levels of the vegetation and those of the soil. This study’s results revealed that the mercury pollution of plants in Changchun City is not severe. The mercury levels in the industrial zones were graded as moderate, and those in the other regions were graded as low.

This paper presents a machine learning method, Gaussian Mixture Hidden Markov Model (GMM-HMM), for device-free activity recognition using WiFi channel state information (CSI). The basic concept of CSI is introduced and signal changes caused by human activity are described, which demonstrates that human activity can be identified using a unique mapping between action and signal variations. The phase difference expanded matrix is built by the mean and standard deviation of phase difference as feature matrix after linear correction and Savitzky-Golay filter is performed on the CSI raw phase information. The GMM-HMM is used for classification as the human activity can be modeled as the Markov process and the complex activity patterns can be fitted by multiple Gaussian density functions, respectively. The proposed system is verified on the self-collected datasets and several factors affecting the recognition accuracy are analyzed. Furthermore, the system has compared with the previous work. High accuracy and robustness in universal scenarios are realized. Experimental results show that the average recognition accuracy of the proposed system is over 97%.

Context Genistein (Gen) has shown protective effects against ageing process. Objective To explore the role of Gen on the senescence of H2O2-induced human umbilical vein endothelial cells (HUVECs) and investigate the possible mechanism. Materials and methods HUVECs were treated with different concentrations of H2O2 (50, 100, 200 and 400 μmol/L) for 1 h or Gen administration (20, 40, 80 and 160 μg/mL) for 24 h. Functional experiments (cell counting kit-8, β-galactosidase staining and flow cytometry) were used to detect the effect of Gen on H2O2-induced HUVECs. After HUVECs were transfected with TXNIP overexpression plasmids, the expression of p16, p21, thioredoxin-interacting protein (TXNIP), nucleotide-binding and oligomerization domain-like receptor 3 (NLRP3), cleaved caspase-3 and cleaved caspase-1 in HUVECs were detected by quantitative real-time polymerase chain reaction (qRT-PCR) and western blot. Results H2O2 (200 and 400 μmol/L) inhibited the proliferation of HUVECs. At concentrations of >50 μmol/L, H2O2 induced the cell cycle progression arrests in G1 phase and promoted cell senescence of HUVECs. Gen had no obvious cytotoxicity to HUVECs below 160 µg/mL. H2O2-induced HUVEC senescence and the expression of TXNIP and NLRP3 in HUVECs were down-regulated by Gen (40 and 80 µg/mL). Expressions of TXNIP and NLRP3 in HUVECs were up-regulated by H2O2 but down-regulated by Gen. Overexpressed TXNIP partially reversed the suppressive effect of Gen on H2O2-induced senescence and apoptosis of HUVECs. Expressions of p16, p21, TXNIP, NLRP3, cleaved caspase-3 and cleaved caspase-1 in H2O2-treated HUVECs were inhibited by Gen, while the inhibition as such was partially reversed by overexpressed TXNIP. Discussion and conclusions H2O2-induced HUVEC senescence was alleviated by Gen via suppressing the TXNIP/NLRP3 axis, which may offer a potential therapeutic approach for improving HUVEC senescence and provide a new direction for the treatment of cardiovascular disease.

Aims: Krüppel-like Factor 9 (KLF9) is a transcription factor that regulates multiple disease processes. Studies have focused on the role of KLF9 in the redox system. In this study, we aimed to explore the effect of KLF9 on diabetic cardiomyopathy. Methods and Results: Cardiac-specific overexpression or silencing of KLF9 in C57BL/6 J mice was induced with an adeno-associated virus 9 (AAV9) delivery system. Mice were also subjected to streptozotocin injection to establish a diabetic cardiomyopathy model. In addition, neonatal rat cardiomyocytes were used to assess the possible role of KLF9 in vitro by incubation with KLF9 adenovirus or small interfering RNA against KLF9. To clarify the involvement of peroxisome proliferator-activated receptors (PPARγ), mice were subjected to GW9662 injection to inhibit PPARγ. KLF9 was upregulated in the hearts of mice with diabetic cardiomyopathy and in cardiomyocytes. In addition, KLF9 overexpression in the heart deteriorated cardiac function and aggravated hypertrophic fibrosis, the inflammatory response and oxidative stress in mice with diabetic cardiomyopathy. Conversely, cardiac-specific silencing of KLF9 ameliorated cardiac dysfunction and alleviated hypertrophy, fibrosis, the cardiac inflammatory response and oxidative stress. In vitro, KLF9 silencing in cardiomyocytes enhanced inflammatory cytokine release and oxidative stress; KLF9 overexpression increased these detrimental responses. Moreover, KLF9 was found to regulate the transcription of PPARγ, which suppressed the expression and nuclear translocation of nuclear Factor E2-related Factor 2 (NRF2). In mice injected with a PPARγ inhibitor, the protective effects of KLF9 knockdown on diabetic cardiomyopathy were counteracted by GW9662 injection. Conclusions: KLF9 aggravates cardiac dysfunction, the inflammatory response and oxidative stress in mice with diabetic cardiomyopathy. KLF9 may become a therapeutic target for diabetic cardiomyopathy.

Background/Aims: Nuclear localization leucine-rich-repeat protein 1 (NLRP1) is a cytoplasmic protein, involved in autoimmune diseases, mammalian reproduction, neuronal cell death, and stroke. However, the role of NLRP1 in cardiac hypertrophy remains unclear. We used in vivo and in vitro models to investigate the effects of NLRP1 on cardiac hypertrophy. Methods: We used NLRP1-deficient mice and cultured neonatal rat cardiomyocytes with gain and loss of NLRP1 function. Cardiac hypertrophy was estimated by echocardiographic and hemodynamic measurements, and by pathological and molecular analysis. Results: Eight weeks after aortic banding (AB), NLRP1 deficiency significantly inhibited aortic banding–induced cardiac hypertrophy, inflammation, and fibrosis. Activation of MAPK, NF-κB, and TGF-β/Smad pathways was reduced in NLRP1-knockout (KO) mice compared with that in wild-type (WT) mice. Consistent with these results, in vitro studies, performed using cultured neonatal mouse cardiomyocytes, confirmed that NLRP1 deficiency protects against cardiomyocyte hypertrophy induced by isoproterenol (PE); this protective activity was associated with the arrest of MAPK and NF-κB signaling. Conclusions: Our data illustrates that NLRP1 plays a crucial role in the development of cardiac hypertrophy via positive regulation of the MAPK, NF-κB, and TGF-β/Smad signaling pathways.

Potassium represents one of the most crucial minerals in infant formula that supports healthy growth and development of infants. Here, a novel strategy for the real-time quantification of potassium in infant formula samples is introduced. Using laser-induced breakdown spectroscopy (LIBS) in a data-driven approach, a modified random frog algorithm (MRFA) is adopted in a higher-density discrete wavelet transform (HDWT) domain for the selection of the most important features related to potassium, which is named as DD-LIBS. In DD-LIBS, the HDWT oversamples the LIBS signals in both time and frequency domains by a factor of two, enhancing the spectral expandability in an approximately shift-invariant way. The MRFA is thus capable of isolating the features of potassium with experience accumulated from the collected LIBS data. Such pretreatment combined with a partial least squared (PLS) model can significantly suppress the uncontrolled shift and broadening effects on multivariate calibration, improving the capability of LIBS for accurate quantification of potassium. The present work demonstrates the feasibility of DD-LIBS for the quantification of potassium content of 90 commercial infant formula samples. A satisfactory result illustrates DD-LIBS as a feasible tool for real-time analysis of potassium content with little sample preparation. This strategy may be well extended to other element detection in the presence of uncontrolled interference.

Orientin is a flavonoid extracted from Chinese traditional herb, Polygonum orientale L. Previous study has reported that orientin protected myocardial from ischemia reperfusion injury. However, whether orientin could protect against cardiac remodeling after myocardial injury remains unclear. The aim of our study is to investigate the effects of orientin in the progression of cardiac remodeling after myocardial infarction (MI). Mice cardiac remodeling model was established by left coronary artery ligation surgery. Experimental groups were as follows: vehicle-sham, orientin-sham, vehicle-MI, and orientin-MI. Animals were treated with vehicle or orientin (40 mg/kg) for 25 days starting 3 days after surgery. After 4 weeks of MI, mice with orientin treatment had decreased mortality and improved cardiac function. Significantly, at 4 weeks post-MI, orientin treatment decreased fibrosis, inflammatory response, and cardiomyocyte apoptosis. Furthermore, orientin treatment attenuated the hypoxia-induced neonatal rat cardiomyocyte apoptosis and increased cell viability. Additionally, orientin supplementation mitigated oxidative stress in remodeling heart tissue and cardiomyocytes exposed to hypoxia as measured by 2′,7′-dichlorodihydrofluorescein diacetate fluorescent probe. Mechanistically, orientin promotes cardioprotection by activating the eNOS/NO signaling cascades, which was confirmed by eNOS inhibitor (L-NAME) in vitro and in vivo. Inhibition of oxidative stress by orientin via eNOS/NO signaling cascades in the heart may represent a potential therapy for cardiac remodeling.

PURPOSE: 3,3'-Diindolylmethane (DIM) is a natural component of cruciferous plants. It has strong antioxidant and anti-angiogenic effects and promotes the apoptosis of a variety of tumor cells. However, little is known about the critical role of DIM on cardiac hypertrophy. In the present study, we investigated the effects of DIM on cardiac hypertrophy. METHODS: Multiple molecular techniques such as Western blot analysis, real-time PCR to determine RNA expression levels of hypertrophic, fibrotic and oxidative stress markers, and histological analysis including H&E for histopathology, PSR for collagen deposition, WGA for myocyte cross-sectional area, and immunohistochemical staining for protein expression were used. RESULTS: In pre-treatment and reverse experiments, C57/BL6 mouse chow containing 0.05% DIM (dose 100 mg/kg/d DIM) was administered one week prior to surgery or one week after surgery, respectively, and continued for 8 weeks after surgery. In both experiments, DIM reduced to cardiac hypertrophy and fibrosis induced by aortic banding through the activation of 5'-adenosine monophosphate-activated protein kinase-α2 (AMPKα2) and inhibition of mammalian target of the rapamycin (mTOR) signaling pathway. Furthermore, DIM protected against cardiac oxidative stress by regulating expression of estrogen-related receptor-alpha (ERRα) and NRF2 etc. The cardioprotective effects of DIM were ablated in mice lacking functional AMPKα2. CONCLUSION: DIM significantly improves left ventricular function via the activation of AMPKα2 in a murine model of cardiac hypertrophy.

The inducible IκB kinase (IKKi/IKKε) is a recently described serine-threonine IKK-related kinase. Previous studies have reported the role of IKKi in infectious diseases and cancer. However, its role in the cardiac response to pressure overload remains elusive. In this study, we investigated the effects of IKKi deficiency on the development of pathological cardiac hypertrophy using in vitro and in vivo models. First, we developed mouse models of pressure overload cardiac hypertrophy induced by pressure overload using aortic banding (AB). Four weeks after AB, cardiac function was then assessed through echocardiographic and hemodynamic measurements. Western blotting, real-time PCR and histological analyses were used to assess the pathological and molecular mechanisms. We observed that IKKi-deficient mice showed significantly enhanced cardiac hypertrophy, cardiac dysfunction, apoptosis and fibrosis compared with WT mice. Furthermore, we recently revealed that the IKKi-deficient mice spontaneously develop cardiac hypertrophy. Moreover, in vivo experiments showed that IKKi deficiency-induced cardiac hypertrophy was associated with the activation of the AKT and NF-κB signaling pathway in response to AB. In cultured cells, IKKi overexpression suppressed the activation of this pathway. In conclusion, we demonstrate that IKKi deficiency exacerbates cardiac hypertrophy by regulating the AKT and NF-κB signaling pathway.

Activating transcription factor 3 (ATF3), which is encoded by an adaptive-response gene induced by various stimuli, plays an important role in the cardiovascular system. However, the effect of ATF3 on cardiac hypertrophy induced by a pathological stimulus has not been determined. Here, we investigated the effects of ATF3 deficiency on cardiac hypertrophy using in vitro and in vivo models. Aortic banding (AB) was performed to induce cardiac hypertrophy in mice. Cardiac hypertrophy was estimated by echocardiographic and hemodynamic measurements and by pathological and molecular analysis. ATF3 deficiency promoted cardiac hypertrophy, dysfunction and fibrosis after 4 weeks of AB compared to the wild type (WT) mice. Furthermore, enhanced activation of the MEK-ERK1/2 and JNK pathways was found in ATF3-knockout (KO) mice compared to WT mice. In vitro studies performed in cultured neonatal mouse cardiomyocytes confirmed that ATF3 deficiency promotes cardiomyocyte hypertrophy induced by angiotensin II, which was associated with the amplification of MEK-ERK1/2 and JNK signaling. Our results suggested that ATF3 plays a crucial role in the development of cardiac hypertrophy via negative regulation of the MEK-ERK1/2 and JNK pathways.

To study the bending behavior of segmental precast diaphragm walls using bolted sleeve joints, 2 full size specimens were tested. Both BC and EC specimens were connected using bolts with steel sleeves as positioner. BC specimen was consisted of two fully RC plates while EC specimen had precast holes in the concrete walls for lightweight treatment. Ultimate strengths, deformations, strains and failure modes were obtained from the test results. Finite element models were developed using ABAQUS and verified against the test results. The verified finite element models were used to further analyze the stress state of specimens under different loading. It indicated that the bolted sleeve joint exhibited good bearing capacity and bending stiffness. The lightweight treatment in the concrete part had minor effect and the design requirement could be satisfied. [ABSTRACT FROM AUTHOR]

Dam safety assessment is usually conducted regularly to investigate the risks associated with the dam and propose remedies to ensure effective reservoir operations. One crucial aspect of the evaluation involves performing hydrological analyses to determine if the existing spillway can successfully deliver the probable maximum flood (PMF) downstream. This study applied storm transposition and typhoon rainstorm methods for PMP estimations. The resulting PMP values were then used as input for runoff models to generate flood hydrographs for PMF determination. A modification for the storm transposition method was proposed to determine the barrier height considering the moisture inflow direction. In estimating the orographic rainfall in the typhoon rainstorm model, an effective terrain slope was suggested according to different windward directions based on DEM analysis. Shihmen Reservoir and Feitsui Reservoir, located in northern Taiwan, were used as examples to conduct the PMP and PMF analysis. The obtained PMPs were further compared with the results generated by Hershfield's method to assess the reasonability of the estimation. The results show that the maximum deviation of the 24-h PMP values estimated by the three methods is within 30% in the Shihmen watershed and 16% in the Feitsui watershed. The PMF estimations in the two reservoir watersheds are larger than the design discharges of the existing spillways. Hence, extending the capacity of the existing spillways or constructing upstream bypasses to avoid catastrophic flooding downstream is required. [ABSTRACT FROM AUTHOR]

In recent years, MXenes has been recognized as a promising material due to its unique physical and chemical properties. Compared with traditional two-dimensional nanomaterials, MXenes has the advantages of large specific surface area, high hydrophilicity, abundant surface active sites, and excellent chemical stability, which makes it have a wide application prospect in environmental remediation technologies such as adsorption. In this paper, the structure and physicochemical properties of MXenes were introduced. The research progress of MXenes for water pollution adsorption remediation was reviewed. The current status of adsorption treatment of heavy metals, dyes, radioactive substances and antibiotics by MXene-based adsorption materials were listed. The characteristics, adsorption conditions, adsorption capacity and corresponding adsorption mechanism of each adsorbent were introduced.The reuse ability of MXenes was discussed. On this basis, the challenges and prospects of MXenes application in the field of water treatment were discussed.