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Abstract Special-cause burn injuries are usually more severe and difficult to manage, and often contribute to a high mortality in severely injured patients. The aim of this study was to present the epidemiological characteristics of special-cause burn in a major regional burn center in China between 2004 and 2021 and determine the risk factors associated with the mortality of burn patients. A total of 33,619 burn patients were included the study, among which 4,452 (13.2%) were special-cause burn patients. Compared to the thermal burn group, the special-cause burn patients were usually male, elder, married and III-IV degree of burn with onset of upper extremity in summer and autumn. Moreover, a greater proportion of patients in the special-cause burn group underwent surgical treatment and amputation and had a higher median hospital stay and treatment costs. During the multivariate logistic regression, older age, male, unmarried, winter, III-IV degree of burn, ≥ 3 burn sites, and larger total body surface area (TBSA) of burn were significantly associated with higher burn mortality (all P 0.05). These results suggested that special cause-burn patients suffer more severe injuries, resulting in longer hospital stays and higher health care expenditures, but it did not significantly increase the mortality risk. Therefore, burn clinicians should not only have the responsibility to cure burns, but also need to know and popularize burn epidemiological characteristic and precaution.

Objective The precise segmentation of kidneys from a 2D ultrasound (US) image is crucial for diagnosing and monitoring kidney diseases. However, achieving detailed segmentation is difficult due to US images’ low signal-to-noise ratio and low-contrast object boundaries. Methods This paper presents an approach called deep supervised attention with multi-loss functions (MLAU-Net) for US segmentation. The MLAU-Net model combines the benefits of attention mechanisms and deep supervision to improve segmentation accuracy. The attention mechanism allows the model to selectively focus on relevant regions of the kidney and ignore irrelevant background information, while the deep supervision captures the high-dimensional structure of the kidney in US images. Results We conducted experiments on two datasets to evaluate the MLAU-Net model's performance. The Wuerzburg Dynamic Kidney Ultrasound (WD-KUS) dataset with annotation contained kidney US images from 176 patients split into training and testing sets totaling 44,880. The Open Kidney Dataset’s second dataset has over 500 B-mode abdominal US images. The proposed approach achieved the highest dice, accuracy, specificity, Hausdorff distance (HD95), recall, and Average Symmetric Surface Distance (ASSD) scores of 90.2%, 98.26%, 98.93%, 8.90 mm, 91.78%, and 2.87 mm, respectively, upon testing and comparison with state-of-the-art U-Net series segmentation frameworks, which demonstrates the potential clinical value of our work. Conclusion The proposed MLAU-Net model has the potential to be applied to other medical image segmentation tasks that face similar challenges of low signal-to-noise ratios and low-contrast object boundaries.

The degree of crushing blocks during open-air blasting is the primary measurement standard for comprehensive costs such as drilling, shoveling, transportation, and follow-up processes. Powder factor is the primary influencing factor and is typically used in blasting model tests to perform related research. However, high costs, test results for errors, and other shortcomings exist. Uniaxial compression, modulus of elasticity, fracture toughness, and other tests were conducted on the model materials based on the basic theory of explosive rock-breaking using basic mechanical testing equipment to calibrate the parameters of the riedel hiermaiver thoma (RHT) intrinsic model to optimize the powder factor of explosives to reduce the percentage of large blocks, reduce the average block size, and predict the block size of blasts in actual projects. Using the numerical simulation software LS-DYNA and the SPH particle flow algorithm to construct a three-dimensional open-air step blasting numerical simulation model, the numerical simulation results of blasting rock breakage to realize the block degree of accurate statistics and blasting rock breakage block degree with the powder factor rule of change were systematically performed. The results of this study show that when increasing the powder factor from 0.23 to 0.79 kg·m−3, the maximum block size is less than 240 mm and shows a different declining trend, which is divided into three zones of a similar decline in block size corresponding to the maximum block size gradient of 240, 220, and 140 mm, and two zones of a significant decline in the maximum block size with corresponding powder factors of 0.31–0.39 and 0.55–0.71 kg·m−3, respectively. The average block size shows an overall decreasing trend with an increasing powder factor of 0.23–0.55 kg·m−3, the average block size decreases from 120 mm to 67.7 mm, and the homogeneity index n decreases from 0.85 to 0.60. The fractal dimension D increases from 2.15 to 2.40. The powder factor is 0.55–0.79 kg·m−3, and the average block size fluctuates up and down, with maximum and minimum values of 76.83 and 65.65 mm, respectively. The homogeneity index n increases and then decreases, and the fractal dimension D decreases and then increases. The block size distribution pattern after blasting is consistent with the feedback from an actual engineering site, and the block size distribution curve of the powder factor is fitted using the G–G–S function. The correlation coefficients are between 0.91 and 0.97, verifying the feasibility and accuracy of the statistics of rock fragmentation block size in the blasting simulation results of the SPH method. This result overcomes the problems of high costs and large experimental errors in the traditional model test. The results of this study have specific significance for improving the distribution law of blast crushing bulkiness and bulkiness control engineering.

Synthetic aperture radar (SAR) is an active remote sensing system that utilizes radar to produce images of the Earth's surface. Due to its ability to operate under diverse weather conditions and throughout the day, SAR has gained significant attention in both civilian and military domains. The utilization of multiview SAR sequences enables the acquisition of a more comprehensive range of information than a single image, and facilitates adaptation to diverse scenarios, thereby enhancing the ability to accommodate variations in samples. Drawing inspiration from the Transformer architecture, this article proposes a multiview SAR target recognition method, called Res-Xformer, that not only deconstructs the deep learning procedure into single image feature extraction and sequence feature fusion but also divides the task of sequence feature extraction into sequence information fusion and feature channel fusion. Different from the Transformers focusing on the attention mechanism to fuse sequence information, alternative fusion methods such as multilayer perceptron (MLP) and pooling are also proposed in this study. Experimental results using the Moving and Stationary Target Acquisition and Recognition dataset demonstrate that the proposed method performs well across various operational conditions, with MLP and pooling as sequence token mixers yielding comparable performance to the attention mechanism.

In response to the new developments in high temperature microwave dielectrometers, (1), (2) a field analysis of a composite sample insertion hole in a coaxial re-entrant cavity is performed via a mode-matching formulation. In this paper, the formulation and the numerical method are presented. The numerical results are discussed with attention focused on the hole effects on the dielectric loaded cavity. By virtue of this analysis and the structure which allows for the sample insertion holes, a new dielectrometer is obtained featuring both ease of sample insertion and accuracy in dielectric determinations. This paper demonstrates that solid, liquid or powdered samples can be readily accommodated and measured, and the dielectric data obtained via two theoretically calculated calibration curves are in good agreement with published data.

Abstract Background With the increase of geriatric burns, it’s urgent to summarize its characteristics. The aim of this study was to analyze the epidemiological and clinical characteristics of older adults with burns in a large center, and to provide suggestions for the prevention and treatment of geriatric burns. Methods This retrospective study was conducted at Wuhan Institute of Burns which is the largest burn center in central China between 2004 to 2018. Demographic and clinical data of the 60 years or above older burn inpatients were collected from medical records, analyzed and compared among groups. Results This study analyzed 2554 elderly burns, which included 50.9% in young geriatric group (60–69 years old), 32.9% in middle geriatric group (70–79 years old) and 16.2% in the oldest geriatric group (80 years old or above). The most common causes of elderly burns were flames (1081, 42.3%) and scalding (1041, 40.8%). Elderly burns with total body surface area (TBSA) of 0–9% accounted for 60.6% and the larger TBSA, the fewer number of patients. The majority of patients (70.5%) injured at home.The median of time interval from injury to admission was 7 h and the oldest geriatric group (24 h) was highest. One hundred and twenty-one cases (8.5%) were treated by cooling treatment, and 72.7% of these patients were treated less than 10 min. The median number of pre-injury diseases was one. Ninety patients (6.3%) had inhalation injury.The median length of stay (LOS) was 14 days.The median hospital cost was 10,410 CNY or 2137 CNY per % TBSA, which was correlated with TBSA, LOS, surgery, inhalation injury, number of pre-injury diseases and etiology. The mortality rate was 3.0% and correlated with TBSA, inhalation injury, pulmonary disease and Alzheimer’s disease. The lethal area 50% (LA50) for total admitted elderly burns was 78.3% TBSA (95% confidence interval [CI] = 69.8 ~ 89.9% TBSA). Conclusion Geriatric burns was still common and even increasing in central China, with flame burns and scalds the most common causes, majority of whom injured at home and often had problems such as few cooling treatment, improper emergency management and delayed admission. TBSA, etiology, pre-injury diseases and inhalation injury were the risk factors of length of stay, hospital cost and treatment outcomes.

The Baise Hydropower Project (hereinafter referred to as “Project”) is the second tier of the comprehensive exploration plan for the Yujiang River of the Xijiang River system in the Pearl River Basin in China. The construction was completed in December 2006. First, the basic facts, layout, and essential structures of the Project were introduced in the article. Second, the primary technological advancements were discussed, including (1) changing layout to accommodate complex topographical and geological conditions, (2) site-specific engineering considerations for the development and construction of high roller compacted concrete (RCC) dams, (3) extensive utilization of diabase for artificial aggregates, and (4) enhanced procedures for expedited construction and quality assurance. Third, intelligent operation and administration used in the Project were described. Finally, the Project’s accomplishments were outlined, followed by project images.

The No.4 tailings pond of the Dexing Copper Mine is the second largest in Asia. The tailing pond is a dangerous source of man-made debris flow with high potential energy. In view of the lack of effective and low-cost global safety monitoring means in this region, in this paper, the time-series InSAR technology is innovatively introduced to monitor the deformation of tailings dam and significant key findings are obtained. First, the surface deformation information of the tailings pond and its surrounding areas was extracted by using SBAS-InSAR technology and Sentinel-1A data. Second, the cause of deformation is explored by analyzing the deformation rate, deformation accumulation, and three typical deformation rate profiles of the representative observation points on the dam body. Finally, the power function model is used to predict the typical deformation observation points. The results of this paper indicated that: (1) the surface deformation of the tailings dam can be categorized into two directions: the upper portion of the dam moving away from the satellite along the Line of Sight (LOS) at a rate of −40 mm/yr, whereas the bottom portion approaching the satellite along the LOS at a rate of 8 mm/yr; (2) the deformation of the dam body is mainly affected by the inventory deposits and the construction materials of the dam body; (3) according to the current trend, deformation of two typical observation points in the LOS direction will reach the cumulative deformation of 80 mm and −360 mm respectively. The research results can provide data support for safety management of No.4 tailings dam in the Dexing Copper Mine, and provide a method reference for monitoring other similar tailings dams.

ObjectiveThe aim of this review is to provide guidance on the selection of approaches to the screening and assessment of enthesitis in patients with spondyloarthritis (SpA).MethodsTwenty-four questions regarding the approaches to the screening and assessment of enthesitis and the implementation details were devised, followed by a systemic literature review. The Grading of Recommendations Assessment, Development, and Evaluation methodology was employed in the development of this guideline, with modifications to evaluate non-interventional approaches under comprehensive consideration of costs, accessibility, and evidence strength. A consensus from the voting panel was required for the inclusion of the final recommendations and the strength of each recommendation.ResultsSeventeen recommendations (including five strong recommendations) were included in this guideline. The voting panel expressed unequivocal support for the necessity of screening and assessment of enthesitis in patients with SpA. It was agreed unanimously that symptom evaluation and physical examination should serve as the initial steps to the recognition of enthesitis, whereas Maastricht Ankylosing Spondylitis Enthesitis Score is a reliable tool in both clinical trials and daily medical practice. Ultrasound examination is another reliable tool, with power Doppler ultrasound as an informative addition. Notwithstanding its high resolution, MRI is limited by the costs and relatively low accessibility, whereas radiographs had low sensitivity and therefore should be rendered obsolete in the assessment of enthesitis. PET/CT was strongly opposed in the detection of enthesitis.ConclusionThis guideline provides clinicians with information regarding the screening and assessment of enthesitis in patients with SpA. However, this guideline does not intend on dictating choices, and the ultimate decisions should be made in light of the actual circumstances of the facilities.

Using the monthly data from December 2008 to March 2018 and a panel vector autoregression (PVAR) model, this paper empirically analyzes the spillover effects of U.S. monetary policy normalization on the total output, inflation, trade balance, and exchange rates in BRICS. The results show that the Fed’s interest rate hike and balance sheet shrinking will both lead to a decrease in BRICS’ output, a decline in inflation, a deterioration in the trade balance, and a depreciation of the exchange rate. In addition, the spillover effects of the Fed’s interest rate hike and shrinking of a balance sheet are both relatively long lasting, but there is a certain difference between the two effects; that is, the Fed’s interest rate hike has a greater impact on the macroeconomic variables of BRICS countries than the shrinking of balance sheet. Based on the conclusions, we propose to establish and improve the regulatory system of international capital flows, pay close attention to commodity prices, and strengthen policy coordination and communication among BRICS countries so as to mitigate the adverse impact of U.S. monetary policy normalization.

Using a set of Chinese economic data and a Bayesian vector autoregression (BVAR) model, this study empirically analyzes the spillover effects of U.S. trade policy uncertainty on the output, consumption, investment, and net export in China. The results find that U.S. trade policy uncertainty is an important factor influencing China’s real economy. Specifically, an increase in U.S. trade policy uncertainty has a significant negative effect on China’s output, consumption, and net export in the short and long run, but it will have a negative impact on investment in the short run and a positive impact in the medium and long run.

The extraction of travel-time curve of seismic phase is very important for the subsequent inference of the structural properties of underground media in seismology. In recent years, with the increase in the amount of data, manual processing is facing significant challenges, and automatic signal processing has gradually become the mainstream. According to the similarity of array signals and considering the elimination of outliers, we propose an improved multi-channel cross-correlation method using the L1 norm measure to obtain preliminary results, which builds on a new controllable measurement mode. Then, the post-correction step is carried out in combination with the signal gain property of beamforming technique. Based on these two methods, this paper proposes a new scheme of automatic arrival time picking. We apply the scheme to actual data to verify the effects of the two methods step by step. The entire scheme achieves fine results: direct water waves, seismic waves refracted by the crust and seismic waves reflected by the upper mantle are automatically detected. In addition, compared with the two traditional methods, the scheme proposed in this paper has a better overall effect and a reasonable computation cost.

Abstract Background Burns are life-threatening with high morbidity and mortality. Reliable diagnosis supported by accurate burn area and depth assessment is critical to the success of the treatment decision and, in some cases, can save the patient’s life. Current techniques such as straight-ruler method, aseptic film trimming method, and digital camera photography method are not repeatable and comparable, which lead to a great difference in the judgment of burn wounds and impede the establishment of the same evaluation criteria. Hence, in order to semi-automate the burn diagnosis process, reduce the impact of human error, and improve the accuracy of burn diagnosis, we include the deep learning technology into the diagnosis of burns. Method This article proposes a novel method employing a state-of-the-art deep learning technique to segment the burn wounds in the images. We designed this deep learning segmentation framework based on the Mask Regions with Convolutional Neural Network (Mask R-CNN). For training our framework, we labeled 1150 pictures with the format of the Common Objects in Context (COCO) data set and trained our model on 1000 pictures. In the evaluation, we compared the different backbone networks in our framework. These backbone networks are Residual Network-101 with Atrous Convolution in Feature Pyramid Network (R101FA), Residual Network-101 with Atrous Convolution (R101A), and InceptionV2-Residual Network with Atrous Convolution (IV2RA). Finally, we used the Dice coefficient (DC) value to assess the model accuracy. Result The R101FA backbone network gains the highest accuracy 84.51% in 150 pictures. Moreover, we chose different burn depth pictures to evaluate these three backbone networks. The R101FA backbone network gains the best segmentation effect in superficial, superficial thickness, and deep partial thickness. The R101A backbone network gains the best segmentation effect in full-thickness burn. Conclusion This deep learning framework shows excellent segmentation in burn wound and extremely robust in different burn wound depths. Moreover, this framework just needs a suitable burn wound image when analyzing the burn wound. It is more convenient and more suitable when using in clinics compared with the traditional methods. And it also contributes more to the calculation of total body surface area (TBSA) burned.

Recent breakthroughs of deep learning algorithms in medical imaging, automated detection, and segmentation techniques for renal (kidney) in abdominal computed tomography (CT) images have been limited. Radiomics and machine learning analyses of renal diseases rely on the automatic segmentation of kidneys in CT images. Inspired by this, our primary aim is to utilize deep semantic segmentation learning models with a proposed training scheme to achieve precise and accurate segmentation outcomes. Moreover, this work aims to provide the community with an open-source, unenhanced abdominal CT dataset for training and testing the deep learning segmentation networks to segment kidneys and detect kidney stones. Five variations of deep segmentation networks are trained and tested both dependently (based on the proposed training scheme) and independently. Upon comparison, the models trained with the proposed training scheme enable the highly accurate 2D and 3D segmentation of kidneys and kidney stones. We believe this work is a fundamental step toward AI-driven diagnostic strategies, which can be an essential component of personalized patient care and improved decision-making in treating kidney diseases.

Using a set of Chinese economic data and a structural vector autoregression (SVAR) model, this paper investigates the transmission channels of fiscal policy to bank credit in China. We find that increases in tax revenue can increase bank credit through external financing premium channel, collateral channel, and bank liquidity channel. We also find that increases in government spending can reduce bank credit through bank liquidity channel and increase bank credit through external financing premium channel and collateral channel.

Multiple myeloma (MM) is an incurable hematologic malignancy due to inevitable relapse and chemoresistance development. Our preliminary data show that MM cells express high levels of PGC1β and LDHA. In this study, we investigated the mechanism behind PGC1β‐mediated LDHA expression and its contribution to tumorigenesis, to aid in the development of novel therapeutic approaches for MM. Real‐time PCR and western blotting were first used to evaluate gene expression of PGC1β and LDHA in different MM cells, and then, luciferase reporter assay, chromatin immunoprecipitation, LDHA deletion report vectors, and siRNA techniques were used to investigate the mechanism underlying PGC1β‐induced LDHA expression. Furthermore, knockdown cell lines and lines stably overexpressing PGC1β or LDHA lentivirus were established to evaluate in vitro glycolysis metabolism, mitochondrial function, reactive oxygen species (ROS) formation, and cell proliferation. In addition, in vivo xenograft tumor development studies were performed to investigate the effect of PGC1β or LDHA expression on tumor growth and mouse survival. We found that PGC1β and LDHA are highly expressed in different MM cells and LDHA is upregulated by PGC1β through the PGC1β/RXRβ axis acting on the LDHA promoter. Overexpression of PGC1β or LDHA significantly potentiated glycolysis metabolism with increased cell proliferation and tumor growth. On the other hand, knockdown of PGC1β or LDHA largely suppressed glycolysis metabolism with increased ROS formation and apoptosis rate, in addition to suppressing tumor growth and enhancing mouse survival. This is the first time the mechanism underlying PGC1β‐mediated LDHA expression in multiple myeloma has been identified. We conclude that PGC1β regulates multiple myeloma tumor growth through LDHA‐mediated glycolytic metabolism. Targeting the PGC1β/LDHA pathway may be a novel therapeutic strategy for multiple myeloma treatment.

Abstract Background Recent literatures indicate that maternal hormone exposure is a risk factor for autism spectrum disorder (ASD). We hypothesize that prenatal progestin exposure may counteract the neuroprotective effect of estrogen and contribute to ASD development, and we aim to develop a method to ameliorate prenatal progestin exposure-induced autism-like behavior. Methods Experiment 1: Prenatal progestin exposure-induced offspring are treated with resveratrol (RSV) through either prenatal or postnatal exposure and then used for autism-like behavior testing and other biomedical analyses. Experiment 2: Prenatal norethindrone (NET) exposure-induced offspring are treated with ERβ knockdown lentivirus together with RSV for further testing. Experiment 3: Pregnant dams are treated with prenatal NET exposure together with RSV, and the offspring are used for further testing. Results Eight kinds of clinically relevant progestins were used for prenatal exposure in pregnant dams, and the offspring showed decreased ERβ expression in the amygdala with autism-like behavior. Oral administration of either postnatal or prenatal RSV treatment significantly reversed this effect with ERβ activation and ameliorated autism-like behavior. Further investigation showed that RSV activates ERβ and its target genes by demethylation of DNA and histone on the ERβ promoter, and then minimizes progestin-induced oxidative stress as well as the dysfunction of mitochondria and lipid metabolism in the brain, subsequently ameliorating autism-like behavior. Conclusions We conclude that resveratrol ameliorates prenatal progestin exposure-induced autism-like behavior through ERβ activation. Our data suggest that prenatal progestin exposure is a strong risk factor for autism-like behavior. Many potential clinical progestin applications, including oral contraceptive pills, preterm birth drugs, and progestin-contaminated drinking water or seafood, may be risk factors for ASD. In addition, RSV may be a good candidate for clinically rescuing or preventing ASD symptoms in humans, while high doses of resveratrol used in the animals may be a potential limitation for human application.

Abstract Background Severe burns injury is a serious pathology, leading to teratogenicity and significant mortality, and it also has a long-term social impact. The aim of this article is to describe the hospitalized population with severe burns injuries in eight burn centers in China between 2011 and 2015 and to suggest future preventive strategies. Methods This 5-year retrospective review included all patients with severe burns in a database at eight institutions. The data collected included gender, age, month distribution, etiology, location, presence of inhalation injury, total burn surface area, depth of the burn, the length of hospitalization, and mortality. SPSS 19.0 software was used to analyze the data. Results A total of 1126 patients were included: 803 (71.3%) male patients and 323 (28.7%) female patients. Scalds were the most common cause of burns (476, 42.27%), followed by fire (457, 40.59%). The extremities were the most frequently affected areas, followed by the trunk. The median length of hospitalization was 30 (15, 52) days. The overall mortality rate was 14.21%. Conclusions Although medical centers have devoted intensive resources to improving the survival rates of burn patients, expenditures for prevention and education programs are minimal. Our findings suggest that more attention should be paid to the importance of prevention and the reduction of injury severity. This study may contribute to the establishment of a nationwide burn database and the elaboration of strategies to prevent severe burns injury.

Abstract: Background: The clinical significance of anti-neutrophil cytoplasmic antibodies in patients with new-onset systemic lupus erythematosus, especially in systemic disease accompanied by interstitial lung disease remains to be elucidated. Objectives: This study was designed to investigate the role of anti-neutrophil cytoplasmic antibodies in new-onset systemic lupus erythematosus patients. Methods: A hundred and seven patients with new-onset SLE were enrolled. Presence of anti-neutrophil cytoplasmic antibodies in the sera was assessed by indirect immunofluorescence as well as enzyme linked immunosorbent assay against proteinase-3 and myeloperoxidase. Clinical features and laboratory parameters of patients were also recorded. All patients were subjected to chest X-ray, chest high-resolution computed tomography and pulmonary function test. Results: Forty-five systemic lupus erythematosus patients (45/107, 42%) were seropositive for anti-neutrophil cytoplasmic antibodies. Compared with anti-neutrophil cytoplasmic antibodies-negative patients, the anti-neutrophil cytoplasmic antibodies-positive patients had significantly higher incidence of renal involvement, anemia, and Raynaud's phenomenon as well as decreased serum level of complement 3/complement 4 and elevated erythrocyte sedimentation rate. In addition, there was a positive correlation between serum anti-neutrophil cytoplasmic antibodies level and disease activity of systemic lupus erythematosus. Furthermore, prevalence of interstitial lung disease in the anti-neutrophil cytoplasmic antibodies -positive patients (25/45, 55.6%) was obviously higher than that in the anti-neutrophil cytoplasmic antibodies-negative patients (15/62, 24.2%). Study limitations: The sample size was limited and the criteria for screening new-onset systemic lupus erythematosus patients might produce bias. Conclusions: The level of anti-neutrophil cytoplasmic antibodies in new-onset systemic lupus erythematosus patients correlates positively with the disease activity and the prevalence of interstitial lung disease.

Abstract Background Autism spectrum disorder (ASD) is characterized by impairments in social communication and restricted or repetitive behaviors or interests. ASD is now diagnosed in more than one out of 100 children and is biased towards males by a ratio of at least 4:1. Many possible explanations and potential causative factors have been reported, such as genetics, sex, and environmental factors, although the detailed mechanisms of ASD remain unclear. Methods The dams were exposed through oral contraceptives to either vehicle control (VEH) alone, levonorgestrel (LNG) alone, ethinyl estradiol (EE) alone, or a combination of LNG/EE for 21 days during their pregnancy. The subsequent 10-week-old offspring were used for autism-like behavior testing, and the limbic tissues were isolated for analysis. In another experimental group, 8-week-old male offspring were treated by infusion of ERβ overexpression/knockdown lentivirus in the amygdala, and the offspring were analyzed after 2 weeks. Results We show that prenatal exposure of either LNG alone or a LNG/EE combination, but not EE alone, results in suppression of ERβ (estrogen receptor β) and its target genes in the amygdala with autism-like behavior in male offspring, while there is a much smaller effect on female offspring. However, we find that there is no effect on the hippocampus and hypothalamus. Further investigation shows that ERβ suppression is due to LNG-mediated altered methylation on the ERβ promoter and results in tissue damage with oxidative stress and the dysfunction of mitochondria and fatty acid metabolism, which subsequently triggers autism-like behavior. Overexpression of ERβ in the amygdala completely restores LNG-induced ERβ suppression and autism-like behaviors in offspring, while ERβ knockdown mimics this effect, indicating that ERβ expression in the amygdala plays an important role in autism-like behavior development. Conclusions We conclude that prenatal levonorgestrel exposure induces autism-like behavior in offspring through ERβ suppression in the amygdala. To our knowledge, this is the first time the potential effect of oral contraceptives on the contribution of autism-like behavior in offspring has been discovered.

Impaired wound healing is one of the major complications of diabetes, involving prolonged inflammation, delayed re-epithelialization, and consistent oxidative stress. The detailed mechanism remains unclear, and there is currently no effective treatment for diabetic wound healing. In this study, we aim to investigate the potential role and effect of nuclear factor erythroid-2–related factor-2 (Nrf2) activation on diabetic wound healing. In vitro experiments in rat macrophages showed that hyperglycemia treatment suppresses Nrf2 activation, resulting in oxidative stress with decreased expression of antioxidant genes, including NAD(P)H:quinone oxidoreductase 1 and heme oxygenase 1, together with increased secretion of proinflammatory cytokines, including interleukin 1β (IL1β), IL6, and monocyte chemoattractant protein-1. Both Nrf2 overexpression and Nrf2 activator dimethyl fumarate (DMF) treatment significantly ameliorated oxidative stress and inflammation. On the other hand, both Nrf2 knockdown or Nrf2 inhibitor ML385 mimicked the effect of diabetes. Further in vivo experiments in rats showed that DMF treatment significantly accelerated wound healing in streptozocin-induced diabetic rats with increased expression of antioxidant enzymes and decreased secretion of proinflammatory cytokines, while Nrf2 inhibitor ML385 mimicked the effect of diabetes. We conclude that Nrf2 activation accelerates impaired wound healing by ameliorating diabetes-mediated oxidative stress and inflammation. This provides a new clinical treatment strategy for diabetic wound healing using Nrf2 activator DMF.

Delayed wound healing in diabetic patients is a serious diabetic complication, resulting in major health problems as well as high mortality and disability. The detailed mechanism still needs to be fully understood. In this study, we aim to investigate potential mechanisms and explore an efficient strategy for clinical treatment of diabetic wound healing. Human umbilical endothelial cells were exposed to hyperglycemia for 4 days, then switched to normoglycemia for an additional 4 days. The cells were harvested for the analysis of reactive oxygen species (ROS) generation, gene expression and VEGF signaling pathway. Furthermore, the diabetic wound model was established in rats for the evaluation of wound healing rates under the treatment of either ERβ agonist/antagonist or SOD mimetic MnTBAP. Our results show that transient hyperglycemia exposure results in persistent ROS overgeneration after the switch to normoglycemia, along with suppressed expression of ERβ, SOD2, and the VEGF signaling pathway. Either ERβ expression or activation diminishes ROS generation. In vivo experiments with diabetic rats show that ERβ activation or SOD mimetic MnTBAP diminishes ROS generation in tissues and accelerates diabetic wound healing. Transient hyperglycemia exposure induces ROS generation and suppresses ERβ expression, subsequently resulting in SOD2 suppression with additional elevated ROS generation. This forms a positive-feed forward loop for ROS generation with persistent oxidative stress. ERβ expression or activation breaks this loop and ameliorates this effect, thereby accelerating diabetic wound healing. We conclude that ERβ accelerates diabetic wound healing by ameliorating hyperglycemia-induced persistent oxidative stress. This provides a new strategy for clinical treatment of diabetic wound healing based on ERβ activation.

Background: Breast cancer is a very common cancer with significant premature mortality in women. In this study, we show that HKDC1 expression in breast cancer cells is increased significantly. We aim to investigate the detailed mechanism for the regulation of HKDC1 expression and its potential contribution to tumorigenesis.Methods: Gene expression was evaluated by real time PCR, western blotting, and immunohistochemistry. The mechanism for PGC1β/SREBP1-mediated HKDC1 expression was investigated using luciferase reporter assay, chromatin immunoprecipitation, and siRNA techniques. In addition, HKDC1 was overexpressed or knocked down by lentivirus to evaluate the potential effect on in vitro cell proliferation, glucose uptake, mitochondrial function, apoptosis, and reactive oxygen species (ROS) formation. Furthermore, an in vivo xenograft tumor development study was employed to investigate the effect of HKDC1 on tumor growth and mouse survival.Results: HKDC1 is highly expressed in both breast cancer cells and clinical tumor tissues. HKDC1 expression is upregulated and co-activated by PGC1β through SREBP1 binding motif on the HKDC1 promoter. HKDC1 is located on the mitochondrial membrane and regulates the permeability transition pore opening by binding with VDAC1, subsequently modulating glucose uptake and cell proliferation. Overexpression of HKDC1 increases while knockdown of HKDC1 decreases in vitro breast cancer cell proliferation and in vivo tumor growth, metastasis, and mouse survival.Conclusions: PGC1β regulates breast cancer tumor growth and metastasis by SREBP1-mediated HKDC1 expression. This provides a novel therapeutic strategy through targeting the PGC1β/HKDC1 signaling pathway for breast cancer treatment.

Extranodal nasal-type natural killer/T-cell lymphoma (NKTCL) is an Epstein-Barr virus (EBV)-associated lymphoma with a strong tendency relapse or be refractory in response to chemotherapy. Development of a new strategy for NKTCL treatment is still quite necessary. In this study, we found that aspirin treatment suppresses VEGF expression in NKTCL SNK-6 cells. Further investigation showed that aspirin treatment increases histone methylation in the range of −100~0 that is proximal to the transcription start site on the VEGF promoter, subsequently decreasing the binding ability of Sp1 to the VEGF promoter with VEGF suppression. Furthermore, aspirin treatment modulates mitochondrial function with increased ROS formation and apoptosis in NKTCL cells. Aspirin treatment alone slightly inhibits NKTCL SNK-6 tumor growth and EBV replication; while in the presence of histone deacetylase inhibitor (HDACi) chidamide (CDM), aspirin significantly suppresses the VEGF signaling pathway with increased ROS overgeneration and EBV inhibition. We also showed that with the addition of chidamide, aspirin significantly suppresses NKTCL tumor growth in both in vitro cell culture and in vivo mouse model with prolonged mouse survival. This is the first time that the potential mechanism for aspirin-mediated VEGF suppression and anti-tumor effect has been discovered, and this study provides a new strategy for anti-tumor drug development for NKTCL treatment based on aspirin-mediated targeting of the VEGF signaling pathway and ROS formation.

We have previously reported that prenatal progestin exposure induces autism-like behavior in offspring through ERβ (estrogen receptor β) suppression in the brain, indicating that progestin may induce autism spectrum disorders (ASD). In this study, we aim to investigate whether prenatal progestin exposure is associated with ASD. A population-based case-control epidemiology study was conducted in Hainan province of China. The ASD children were first screened with the Autism Behavior Checklist (ABC) questionnaire, and then diagnosed by clinical professionals using the ASD diagnosis criteria found in the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-V). Eventually, 235 cases were identified as ASD from 37863 children aged 0–6 years old, and 682 matched control subjects with typically developing children were selected for the analysis of potential impact factors on ASD prevalence using multivariate logistic regression. Our data show that the ASD prevalence rate in Hainan was 0.62% with a boy:girl ratio of 5.4:1. Interestingly, we found that the following factors were strongly associated with ASD prevalence: use of progestin to prevent threatened abortion, use of progestin contraceptives at the time of conception, and prenatal consumption of progestin-contaminated seafood during the first trimester of pregnancy. All the above factors were directly or indirectly involved with prenatal progestin exposure. Additionally, we conducted in vivo experiments in rats to further confirm our findings. Either endogenous (progesterone) or synthetic progestin (norethindrone)-treated seafood zebrafish were used to feed pregnant dams, and the subsequent offspring showed autism-like behavior, which further demonstrated that prenatal progestin exposure may induce ASD. We conclude that prenatal progestin exposure may be associated with ASD development.

Recent clinical cohort study shows that testosterone therapy increases cardiovascular diseases in men with low testosterone levels, excessive circulating androgen levels may play a detrimental role in the vascular system, while the potential mechanism and effect of testosterone exposure on the vascular function in offspring is still unknown. Our preliminary results showed that perinatal testosterone exposure in mice induces estrogen receptor β (ERβ) suppression in endothelial progenitor cells (EPCs) in offspring but not mothers, while estradiol (E2) had no effect. Further investigation showed that ERβ suppression is due to perinatal testosterone exposure-induced epigenetic changes with altered DNA methylation on the ERβ promoter. During aging, EPCs with ERβ suppression mobilize to the vascular wall, differentiate into ERβ-suppressed mouse endothelial cells (MECs) with downregulated expression of SOD2 (mitochondrial superoxide dismutase) and ERRα (estrogen-related receptor α). This results in reactive oxygen species (ROS) generation and DNA damage, and the dysfunction of mitochondria and fatty acid metabolism, subsequently potentiating vascular dysfunction. Bone marrow transplantation of EPCs that overexpressed with either ERβ or a SIRT1 single mutant SIRT1-C152(D) that could modulate SIRT1 phosphorylation significantly ameliorated vascular dysfunction, while ERβ knockdown worsened the problem. We conclude that perinatal testosterone exposure potentiates vascular dysfunction through ERβ suppression in EPCs.

Invasive fungal infection is one of the major complication of severe burns which can induce local or systemic inflammatory response and cause serious substantial damage to the patient. The incidence of fungal infection for burn victims is increasing dramatically during recent years. This guideline, organized by Chinese Society of Burn Surgeons, aims to standardize the diagnosis, prevention and treatment of burn invasive fungal infection. It can be used as one of the tools for treatment of major burn patients.