Search

C3G and PCA enhanced testicular heat stress tolerance, and alleviated oxidative stress and ER stress so as to guarantee the orderly progress of spermatogenesis.

Androgen is a kind of steroid hormone that plays a vital role in reproductive system and homeostasis of the body. Disrupted androgen balance serves as the causal contributor to a series of physiological disorders and even diseases. Flavonoids, as an extremely frequent family of natural polyphenols, exist widely in plants and foods and have received great attention when considering their inevitable consumption and estrogen-like effects. Mounting evidence illustrates that flavonoids have a propensity to interfere with androgen synthesis and metabolism, and also have a designated improvement effect on androgen disorders. Therefore, flavonoids were divided into six subclasses based on the structural feature in this paper, and the literature about their effects on androgens published in the past ten years was summarized. It could be concluded that flavonoids have the potential to regulate androgen levels and biological effects, mainly by interfering with the hypothalamic-pituitary-gonadal axis, androgen synthesis and metabolism, androgen binding with its receptors and membrane receptors, and antioxidant effects. The faced challenges about androgen regulation by flavonoids masterly include target mechanism exploration, individual heterogeneity, food matrixes interaction, and lack of clinical study. This review also provides a scientific basis for nutritional intervention using flavonoids to improve androgen disorder symptoms.

Di-(2-ethylhexyl)-phthalate (DEHP) is the most commonly used plasticizer and it has been a ubiquitous environmental contaminant which affects health. The purpose of this study was to investigate the protective effect of the Lycium barbarum polysaccharide (LBP) at dosages of 100, 200, and 300 mg/kg bw on DEHP-induced (3000 mg/kg) toxicity in rat liver through a 28-day animal experiment. The results showed that LBP attenuated oxidative stress slightly by lowering the production of ROS and improving the activity of SOD and GSH-Px in liver and serum of DEHP treatment rats. At the same time, the levels of PXR, CYP450, CYP2E1, CYP3A1, UGT1, and GST were reduced after LBP treatment. Moreover, LBP decreased the mRNA expression of PXR, UGT1, and GST significantly. These findings suggested that LBP might ameliorate DEHP-induced liver injury by down-regulating the expression of PXR in liver, further down-regulating the downstream phase I and II detoxification enzymes, thus reducing the damage caused by DEHP. Therefore, LBP may have the potential to become an auxiliary therapeutic agent as a natural ingredient of health food.

Tight sandstone reservoirs are widely distributed worldwide. The Upper Triassic Chang 6 member of the Yanchang Formation is characterized by low permeability and porosity. The facies model offers a unique approach for understanding the characteristics of various environments also heterogeneity, scale, and control of physical processes. The role of subsurface facies features and petrophysical properties was unclear. Notable insufficient research has been conducted based on facies and petrophysical modeling and that demands to refine the role of reservoir properties. To tackle this problem, a reservoir model is to be estimated using various combinations of property modeling algorithms for discrete (facies) and continuous (petrophysical) properties. Chang 6 member consists of three main facies, i.e., channel, lobe main body, and lobe margin facies. The current research is aimed at comparing the applicability and competitiveness of various facies and petrophysical modeling methods. Further, well-log data was utilized to interpret unique facies and petrophysical models to better understand the reservoir architecture. Methods for facies modeling include indicator kriging, multiple-point geostatistics, surface-based method, and sequential indicator simulation. Overall, the indicator kriging method preserved the local variability and accuracy, but some facies are smoothed out. The surface-based method showed far better results by showing the ability to reproduce the geometry, extent, connectivity, and facies association. The multiple-point geostatistics (MPG) model accurately presented the facies profiles, contacts, geometry, and geomorphological features. Sequential indicator simulation (SIS) honored the facies spatial distribution and input statistical parameters. The porosity model built using sequential Gaussian simulation (SGS) showed low porosity (74% values

The prediction of traffic flow is of great significance in the traffic field. However, because of the high uncertainty and complexity of traffic data, it is challenging that doing traffic flow prediction. Most of the existing methods have achieved good results in traffic flow prediction, but are not accurate enough to capture the dynamic temporal and spatial relationship of data by using the structural information of traffic flow. In this study, we propose a traffic flow prediction method with temporal attention mechanism and spatial attention mechanism based on neural architecture search (TS-NAS). Firstly, based on temporal and spatial attention mechanisms, we design a new attention mechanism. Secondly, we define a novel model to learn temporal flow and space flow in traffic network. Finally, the proposed method uses different modules about time, space and convolution and neural architecture search to be used for optimizing the model. We use two datasets to test the method. Experimental results show that the performance of the method is better than that of the existing method.

Nonylphenol (NP) is an endocrine-disrupting chemical (EDC) that can lead to thyroid disruption. We explored NP-induced toxicity in the rat thyroid and evaluated the mitigating effects of mulberry crude extract (MCE) on NP toxicity. First, we aimed to evaluate NP-induced thyroid disruption by dosing Sprague–Dawley (SD) rats with NP (0, 30, 90, or 270 mg/kg body weight) daily for 28 days. Second, we aimed to determine whether MCE had a detoxifying effect on NP-induced thyroid disruption by dosing SD rats with NP (270 mg/kg body weight) or/and MCE (30, 60, or 120 mg/kg body weight) daily for 28 days. We found that NP significantly inhibited free triiodothyronin (FT3) and free thyroxine (FT4) activity in rat serum (P

Bisphenol A (BPA) is a globally utilized industrial chemical and is commonly used as a monomer of polycarbonate plastics and epoxy resins. Recent research reveals that BPA could cause potential adverse biological effects and liver dysfunction. However, the underlying mechanisms of BPA-induced hepatoxicity and gut dysbiosis remain unclear and deserve further study. In this study, male Sprague Dawley rats were exposed to different doses (0, 30, 90, and 270 mg/kg bw) of BPA by gavage for 30 days. The results showed that the high dose of BPA decreased superoxide dismutase (SOD), glutathione (GSH), and increased malondialdehyde (MDA) levels. Moreover, a high dose of BPA caused a significant increase in serum alanine aminotransferase (ALT), aspartate aminotransferase (AST), total cholesterol (TC), and low-density lipoprotein cholesterol (LDL-C), while high-density lipoprotein cholesterol (HDL-C) was significantly decreased in BPA-treated rats. The gene expression of PGC-1α and Nrf1 were decreased in the liver of high doses of BPA-administrated rats, as well as the protein levels of SIRT1, PGC-1α, Nrf2, and TFAM. However, the protein expression of IL-1β was significantly increased in BPA-treated rats. In addition, BPA weakened the mitochondrial function of hepatocytes and promoted cell apoptosis in the liver by up-regulating the protein levels of Bax, cleaved-Caspase3, and cleaved-PARP1 while down-regulating the Bcl-2 in the liver. More importantly, a high dose of BPA caused a dramatic change in microbiota structure, as characterized at the genus level by increasing the ratio of Firmicutes to Bacteroidetes (F/B), and the relative abundance of Proteobacteria in feces, while decreasing the relative abundance of Prevotella_9 and Ruminococcaceae_UCG-014, which is positively correlated with the content of short-chain fatty acids (SCFAs). In summary, our data indicated that BPA exposure caused hepatoxicity through apoptosis and the SIRT1/PGC-1α pathway. BPA-induced intestinal flora and SCFA changes may be associated with hepatic damage. The results of this study provide a new sight for the understanding of BPA-induced hepatoxicity.

Environmental di(2-Ethylhexyl) phthalate (DEHP) is widely used in various industries as a plasticizer, and has been reported to induce reproductive and developmental toxicities in organisms. The purpose of this study was to evaluate the detoxification capacity of Lycium barbarum polysaccharides (LBP) and wolfberry juice (WJ) against DEHP-induced hepatotoxicity. Two groups of rats were purchased to study two different intervention method experiments: LBP (50, 100, 200 mg/kg·bw) intervention before DEHP (2000 mg/kg·bw) exposure, and LBP (200 mg/kg·bw) or WJ (8 mL/kg·bw) intervention after DEHP (3000 mg/kg·bw) exposure. The rats were exposed to DEHP once, while the intervention lasted for seven days. At the end of the intervention, enzyme-linked immunosorbent assay (ELISA) was used to measure the related index. The LBP intervention before DEHP exposure experiment (the first experimental method) found that LBP group rats showed a strong capacity toward DEHP detoxification, evidenced by the significant upregulation of activities and concentrations of the partner retinoid, X receptor alpha (RXRα), and downstream regulators Cytochrome P4502E1 (CYP2E1), Cytochrome P4503A1 (CYP3A1), Glutathione S-Transferase Pi (GSTpi), and UDP-glucuronosyltransferase 1 (UGT1) in a dose-dependent manner. The LBP and WJ intervention after DEHP exposure experiment (the second intervention experiment) found that WJ could downregulate pregnane X receptor (PXR), and upregulate downstream regulators, CYP2E1, CYP3A1, and Glutathione S-Transferase (GST) with the extension of intervention time, to alleviate the toxicity of DEHP. However, the intervention effect of WJ was more obvious than that of LBP. These results suggested that LBP and WJ might be effective detoxification agents against DEHP-induced toxic effects, by activating PXR and PXR-related detoxifying enzymes.

Acute lymphoblastic leukemia is a major problem in people's lives. At present, the most widespread detection method is mainly manual, which is time-consuming and laborious. With the development of deep learning, specifically targeting the complexity of traditional convolutional neural network models, substantial resource costs, and non-conducive deployment. This paper proposes a simple and effective classification method. The use of lightweight convolutional neural network classified microscopic images of acute leukemia can more effectively assist doctors in the diagnosis of diseases. The method is evaluated in C-NMC 2019 data set and achieves an accuracy rate is 86.29%, F1 coefficient is 89.98%, and a recall rate of an astonishing 95.73% on the test set. Meanwhile, the model parameters are one ninth of those in the traditional convolution neural network. On the premise of ensuring high accuracy, this paper discuss that reduced complexity of the model, the facilitation of deployment and application of the model in the mobile terminal and the potential to help doctors to carry out auxiliary diagnosis of diseases with the help of portable instruments or modern equipment.

This study was to evaluate the detoxification ability of mulberry crude extract against NP-induced toxic effects in rats. The structures of the main active substances in mulberry crude extract were first identified by HPLC-Q-TOF-MS. Male Sprague–Dawley rats were exposed to NP (270 mg/kg) or/and mulberry crude extract (30, 60, 120 mg/kg·bw) for 28 days. Mulberry crude extract was found to contain 34.86 mg/mL polyphenols and 7.39 mg/mL flavonoids. GST and UGT2b1 in rat liver microsomes were inhibited by 270 mg/kg NP, whereas their levels increased by 120 mg/kg·bw mulberry crude extract treatment. The expression inhibition of Nrf2, GST and Ugt2b1 mRNA by 270 mg/kg NP significantly improved by 120 mg/kg·bw mulberry crude extract treatment. Taken together, mulberry crude extract may be an efficient detoxification agent against NP-induced toxic effects by activation of Nrf2 and Nrf2-related detoxifying enzymes in rat.

The geological and geophysical characterization of hydrocarbon-bearing sandstones of fluvial origin is a challenging task. Channel sandbodies occurring at different stratigraphic levels (i.e., in a reservoir interval of interest as well as in overlying and underlying stratigraphic intervals) but overlapping in planview usually cause significant seismic interference due to limitations in seismic resolution: this can produce significant error in the prediction of sand location and thickness using seismic attributes. To mitigate the effect of seismic interferences by zones neighboring a target reservoir interval, a new method is proposed that combines multiple seismic attributes of the target interval and of its interfering neighboring zones, implemented by a supervised machine learning algorithm using support vector regression (SVR). Since the thickness of neighboring intervals causing seismic interference has a constant value of a quarter of a wavelength (1/4 λ), the stratal slice corresponding with the top horizon of the target interval is taken as the base of a window of 1/4 λ to calculate seismic attributes for the overlying zone; similarly, the stratal slice corresponding with the bottom horizon is taken as the top of a window of 1/4 λ to calculate seismic attributes for the underlying zone. The proposed method was applied to a subsurface dataset (including a 3D seismic dataset and 255 wells) of the Chengdao oilfield, in the Bohai Bay Basin (China). The interval of interest is located in the Neogene Guantao Formation, whose successions are interpreted as fluvial in origin. This application demonstrates how the proposed method results in remarkably improved sandstone thickness prediction, and how consideration of multiple attributes further improves the accuracy of predicted values of sandstone thickness.