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The histone demethylase lysine‐specific demethylase 4A (KDM4A) is reported to be overexpressed and plays a vital in multiple cancers through controlling gene expression by epigenetic regulation of H3K9 or H3K36 methylation marks. However, the biological role and mechanism of KDM4A in prostate cancer (PC) remain unclear. Herein, we reported KDM4A expression was upregulation in phosphatase and tensin homolog knockout mouse prostate tissue. Depletion of KDM4A in PC cells inhibited their proliferation and survival in vivo and vitro. Further studies reveal that USP1 is a deubiquitinase that regulates KDM4A K48‐linked deubiquitin and stability. Interestingly, we found c‐Myc was a key downstream effector of the USP1‐KDM4A/androgen receptor axis in driving PC cell proliferation. Notably, upregulation of KDM4A expression with high USP1 expression was observed in most prostate tumors and inhibition of USP1 promotes PC cells response to therapeutic agent enzalutamide. Our studies propose USP1 could be an anticancer therapeutic target in PC. This study identifies USP1 as a critical deubiquitinase for stabilizing KDM4A, thereby promoting prostate cancer growth and tumorigenesis. Targeting KDM4A stabilization through pharmacological inhibition of USP1 by ML323 could thus open an avenue for therapeutic intervention in prostate cancer patients.

We have recently reported that epigallocatechin gallate (EGCG) could extend lifespan in healthy rats. This study aimed to investigate the effects and mechanisms of a high dose of EGCG in extending the lifespan of obese rats. Ninety adult male Wistar rats were randomly divided into the control (NC), high‐fat (HF) and EGCG groups. Serum glucose and lipids, inflammation and oxidative stress were dynamically determined from adulthood to death, and the transcriptome and proteome of the liver were also examined. The median lifespans of the NC, HF and EGCG groups were 693, 599 and 683 days, respectively, and EGCG delayed death by 84 days in obese rats. EGCG improved serum glucose and lipids and reduced inflammation and oxidative stress associated with aging in obese rats induced by a high‐fat diet. EGCG also significantly decreased the levels of total free fatty acids (FFAs), SFAs and the n‐6/n‐3 ratio but significantly increased the n‐3 FFAs related to longevity. The joint study of the transcriptome and proteome in liver found that EGCG exerted its effects mainly by regulating the suppression of hydrogen peroxide and oxygen species metabolism, suppression of oxidative stress, activation of fatty acid transport and oxidation and cholesterol metabolism. EGCG significantly increased the protein expression of FOXO1, Sirt1, CAT, FABP1, GSTA2, ACSL1 and CPT2 but significantly decreased NF‐κB, ACC1 and FAS protein levels in the livers of rats. All the results indicate that EGCG extends lifespan by improving FFA metabolism and reducing the levels of inflammatory and oxidative stress in obese rats. This study investigates the effects and mechanisms of a high dose of epigallocatechin gallate (EGCG) in extending the lifespan of obese rats. We find that EGCG improved serum glucose, lipids, inflammation, oxidative stress associated with ageing in obese rats induced by a high‐fat diet, total free fatty acids (FFAs), transcriptome, and proteome. The results indicate that EGCG extends lifespan by improving FFA metabolism and reducing the levels of inflammatory and oxidative stress in obese rats.

Tourism increasingly reflects living standards, with its economic impact steadily growing. This research employs a modified gravity model and social network analysis to assess tourism-driven economic linkages among 284 Chinese prefecture-level cities (2007–2019). It investigates the spatial network structure of urban tourism sectors and identifies key influencing factors. The findings indicate that tourism economic connections have been consistently strengthened, but such connections’ overall level remains low, with significant intercity disparities, reflecting the “Matthew effect” prevalent in core cities. The interconnected web of urban tourism economies demonstrates strong mutual influence and ripple effects. The network’s structure is strengthening, but its unity could be enhanced. Furthermore, the spatial network is characterized by a “diamond” configuration, with the Beijing-Tianjin-Hebei region, the Yangtze River Delta, the Pearl River Delta, the Wuhan area, and the Chengdu-Chongqing regions serving as pivotal axes connected by boundaries, demonstrating an evolution from points to lines and from lines to surfaces. The layout of urban tourism economies is really shaped by a few key things. Being close to other cities, having different attractions, and not being on the same level economically tends to bring cities together. On the flip side, if cities have very different industries, that can actually create some distance between them when it comes to tourism. This study puts forward specific strategies and suggestions. Plain Language Summary Tourism has become an important indicator of the standard of living, and the scale of the tourism economy has been continuously expanding as well. Based on tourism-related indicators from 284 prefecture-level cities in China between 2007 and 2019, this study employs a modified gravity model and social network analysis to measure the strength of tourism-related economic connections among the cities over 13 years. It analyzes the spatial network structure characteristics of urban tourism economies and discusses the influencing factors. The findings indicate that tourism economic connections have been consistently strengthened, but such connections’ overall level remains low, with significant intercity disparities, reflecting the “Matthew effect” prevalent in core cities. The spatial network of urban tourism economies exhibits significant correlation and spillover effects; although the network structure is gradually stabilizing, the overall network density requires further enhancement. Furthermore, the spatial network is characterized by a “diamond” configuration, with the Beijing-Tianjin-Hebei region, the Yangtze River Delta, the Pearl River Delta, the Wuhan area, and the Chengdu-Chongqing regions serving as pivotal axes connected by boundaries, demonstrating an evolution from points to lines and from lines to surfaces. Factors, such as geographical proximity, variations in tourism resource endowment, and differences in economic development levels, positively influence the formation of the urban tourism economic spatial network, while disparities in regional industrial structures exert a negative impact. This study proposes targeted countermeasures and recommendations. These include enhancing the economic strength of urban tourism, strengthening the spatial network connections within the tourism economy, and optimizing the spatial network structure in a rational manner.

How does air pollution affect road safety? This study examines the impact of local PM 2.5 concentrations on traffic violations and accident severity in Guangdong Province, China, from 2006 to 2014. Using instrumental variable methods to address endogeneity, we find a significant relationship between PM 2.5 concentrations and the occurrence of high-penalty traffic violations and severe accidents. Robustness checks confirm these results hold when using alternative pollutants (PM 10 , SO 2 , and SO 4 ). To account for the bias caused by nonlinear relationships between air pollution and weather, we employ a random forest model to isolate the weather-independent component of PM 2.5 concentrations. Further analysis reveals significant heterogeneity in these effects across driver characteristics and geographic areas. This paper also explores potential visual and psychological mechanisms through which PM 2.5 influences traffic safety. Our findings offer valuable policy implications for environmental and traffic management strategies.

The Bass diffusion model has been successfully applied in product sales forecasting, and it performs particularly well in consumer durables sales forecasting. However, the traditional Bass model only uses historical sales data and cannot contain important market information concerning products. How to improve the Bass model through user-generated Internet information and macroeconomic data to achieve more accurate predictions is addressed in this paper. First, a sentiment analysis is adopted to convert online reviews concerning various attributes of a product into sentiment scores, and then, the product word-of-mouth index (WoM index), which is integrated into the imitation coefficient of the Bass model, is calculated by the entropy weight method. Subsequently, the Baidu product index is calculated through the Baidu search traffic of product-related words and is integrated into the innovation coefficient of the Bass model. Finally, macroeconomic data are collected to estimate the total number of potential adopters, which relaxes the assumption that the market potential in the Bass model remains unchanged over time. We conduct comparison experiments of forecasting automobile product sales, and the results are as follows. (1) The improved Bass model can significantly improve the forecast accuracy, and its average forecast accuracy (0.9983) is approximately 2.15% higher than the traditional Bass model (0.9773). The RMSE (0.3124) and WAPE (0.0017) are 90.98% and 92.38% lower compared with the traditional Bass model, respectively. (2) as for the calculation of WoM index, it is better to divide a whole review into separate reviews concerning each attribute. (3) Macroeconomic data play the biggest role in improving the prediction power of the Bass model, followed by online review data and search traffic data.

Objective: A robust, quick, and reliable ultra-performance liquid chromatography–tandem mass spectrometry (UPLC-MS/MS) method for the quantification of erdafitinib in beagle dog plasma was developed and validated to evaluate the changes of posaconazole and isavuconazole on the pharmacokinetics of erdafitinib in beagle dogs, respectively. Methods: This experiment adopted a three-period self-control experimental design. In the first period (group A), erdafitinib was orally administered to six beagle dogs at a dose of 4 mg/kg. In the second period (group B), the same six beagle dogs were orally given posaconazole at a dose of 7 mg/kg, and after 30 min, erdafitinib was orally given. In the third period (group C), isavuconazole at a dose of 7 mg/kg was given orally, and then, erdafitinib was orally given. At the different time points after erdafitinib was given in the three periods, the blood samples were collected. The concentration of erdafitinib was detected by the developed UPLC-MS/MS method. DAS 2.0 was used to calculate the pharmacokinetic parameters of erdafitinib. Results: Erdafitinib had a good linear relationship in the range of 1–500 ng/ml, and the lower limit of quantification was 1 ng/ml. The precision, accuracy, extraction recovery, matrix effect, and stability meet the requirements of the guiding principles. After erdafitinib was combined with posaconazole, the C max and AUC 0→t of erdafitinib increased by 27.19% and 47.62%, respectively, and the t 1/2 was prolonged to 6.33 h. After erdafitinib was combined with isavuconazole, the C max and AUC 0→t of erdafitinib increased by 23.13% and 54.46%, respectively, and the t 1/2 was prolonged to 6.31 h. Conclusion: A robust and reliable UPLC-MS/MS method was fully optimized and developed to detect the plasma concentration of erdafitinib in beagle dogs. Posaconazole and isaconazole could inhibit the metabolism of erdafitinib in beagle dogs and increase the plasma exposure of erdafitinib.

Weather forecasting requires a comprehensive analysis of various types of meteorology data, and with the wide application of deep learning in various fields, deep learning has proved to have powerful feature extraction capabilities. In this paper, from the viewpoint of an image semantic segmentation problem, a deep learning framework based on semantic segmentation is proposed to nowcast Cloud-to-Ground and Intra-Cloud lightning simultaneously within an hour. First, a dataset with spatiotemporal features is constructed using radar echo reflectivity data and lightning observation data. More specifically, each sample in the dataset consists of the past half hour of observations. Then, a Light3DUnet is presented based on 3D U-Net. The three-dimensional structured network can extract spatiotemporal features, and the encoder–decoder structure and the skip connection can handle small targets and recover more details. Due to the sparsity of lightning observations, a weighted cross-loss function was used to evaluate network performance. Finally, Light3DUnet was trained using the dataset to predict Cloud-to-Ground and Intra-Cloud lightning in the next hour. We evaluated the prediction performance of the network using a real-world dataset from middle China. The results show that Light3DUnet has a good ability to nowcast IC and CG lightning. Meanwhile, due to the spatial position coupling of IC and CG on a two-dimensional plane, predictions from summing the probabilistic prediction matrices will be augmented to obtain accurate prediction results for total flashes.

Background Chemotherapy can induce premature ovarian insufficiency (POI). POI causes multiple sequelae and is currently incurable. As shown in our previous studies, systemically transplanted human amnion-derived mesenchymal stem cells (hAD-MSCs) home to ovaries with chemotherapy-induced POI and subsequently reduce ovarian injury and improve ovarian function in rats with POI. However, the cellular mechanisms that direct the migration and homing of hAD-MSCs to ovaries with chemotherapy-induced POI are incompletely understood. This study investigated the role of the SDF-1/CXCR4 axis in the migration and homing of systemically transplanted hAD-MSCs to ovaries with chemotherapy-induced POI and its relevant downstream signalling pathways. Methods CXCR4 expression in hAD-MSCs was assessed using Western blotting and immunofluorescence staining. hAD-MSC migration was tested using Transwell migration assays. SDF-1 levels were detected using ELISA. Seventy-two female SD rats were randomly divided into the control, POI, hAD-MSCs and hAD-MSCs + AMD3100 groups. Cyclophosphamide was used to establish rat POI models. For inhibitor treatment, hAD-MSCs were pretreated with AMD3100 before transplantation. PKH26-labeled hAD-MSCs were injected into the tail vein of POI rats 24 h after chemotherapy. After hAD-MSC transplantation, the homing of hAD-MSCs to ovaries and ovarian function and pathological changes were examined. We further investigated the molecular mechanisms by detecting the PI3K/Akt and ERK1/2 signalling pathways. Results hAD-MSCs expressed CXCR4. SDF-1 induced hAD-MSC migration in vitro. SDF-1 levels in ovaries and serum were significantly increased in rats with chemotherapy-induced POI, and ovaries with POI induced the homing of hAD-MSCs expressing CXCR4. Blocking the SDF-1/CXCR4 axis with AMD3100 significantly reduced the number of hAD-MSCs homing to ovaries with POI and further reduced their efficacy in POI treatment. The binding of SDF-1 to CXCR4 activated the PI3K/Akt signalling pathway, and LY294002 significantly inhibited hAD-MSC migration induced by SDF-1 in vitro. Moreover, inhibition of the PI3K/Akt signalling pathway significantly reduced the number of systemically transplanted hAD-MSCs homing to chemotherapy-induced ovaries in rats with POI. Conclusions SDF-1/CXCR4 axis partially mediates the migration and homing of systemically transplanted hAD-MSCs to the ovaries of rats with chemotherapy-induced POI, and the PI3K/Akt signalling pathway might be involved in the migration and homing of hAD-MSCs mediated by the SDF-1/CXCR4 axis.

Although localized prostate cancer (PCa) can be cured by prostatectomy and radiotherapy, the development of effective therapeutic approaches for advanced prostate cancer, including castration-resistant PCa (CRPC) and neuroendocrine PCa (NEPC), is lagging far behind. Identifying a novel prognostic and diagnostic biomarker for early diagnosis and intervention is an urgent clinical need. Here, we report that apolipoprotein A-I (ApoA-I), the major component of high-density lipoprotein (HDL), is upregulated in PCa based on both bioinformatics and experimental evidence. The fact that advanced PCa shows strong ApoA-I expression reflects its potential role in driving therapeutic resistance and disease progression by reprogramming the lipid metabolic network of tumor cells. Molecularly, ApoA-I is regulated by MYC, a frequently amplified oncogene in late-stage PCa. Altogether, our findings have revealed a novel indicator to predict prognosis and recurrence, which would benefit patients who are prone to progress to metastasis or even NEPC, which is the lethal subtype of PCa.