The processing quality of indica rice must undergo ripening after harvest to achieve stability and improvement. However, the mechanism underlying this process remains incompletely elucidated. Starch, ...the predominant component in indica rice, plays a crucial role in determining its properties. This study focused on analyzing the rheological properties and starch fine structure, as well as the related biosynthetic enzymes of indica rice during the after-ripening process. The results showed that after-ripened rice exhibited increased elastic modulus (G′) and viscous modulus (G″), accompanied by a decrease in the loss tangent (Tan δ), indicating an enhancement in viscoelasticity and the gel network structure. Moreover, the proportions of amylopectin super long chains (DP 37–60) decreased, while those of medium chains (DP 13–24 and DP 25–36) or short chains (DP 6–12) of amylopectin increased. Additionally, the activities of starch branching enzyme (SBE) and starch debranching enzyme (DBE) declined over the after-ripening period. Pearson correlation analysis revealed that the rheological properties of after-ripened rice were correlated with the chain length distribution (CLD) of starch, which, in turn, was associated with its related endogenous enzymes. These findings provied new insights into understanding the quality changes of after-ripened indica rice.
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•The elastic modulus and viscous modulus of rice increased during after-ripening.•The chain length distribution of amylopectin undergoed changes during after-ripening.•The activities of starch branching enzyme and starch branching enzyme decreased during after-ripening.•The starch biosynthesis enzymes changed the starch structure and thus affected the rheological properties of rice.
The aim of this study was to investigate the effect of quercetin on hepatic fibrosis, a characteristic response to acute or chronic liver injury. Mice were randomized to bile duct ligation (BDL) or ...carbon tetrachloride (CCl
) cirrhosis models. Quercetin (100 mg/kg or 200 mg/kg daily) was administered by gavage for 2 or 4 weeks. Liver tissue and blood samples were collected for histological and molecular analysis. The results of our experiments showed that quercetin reduced BDL or CCl
liver fibrosis, inhibited extracellular matrix formation, and regulated matrix metallopeptidase (MMP)-9 and tissue inhibitor of metalloproteinase (TIMP)-1. Quercetin attenuated liver damage by suppressing the TGF-β1/Smads signaling pathway and activating the PI3K/Akt signaling pathway to inhibit autophagy in BDL- or CCl
- induced liver fibrosis. Quercetin prevented hepatic fibrosis by attenuating hepatic stellate cell activation and reducing autophagy through regulating crosstalk between the TGF-β1/Smads and PI3K/Akt pathways.
Hepatocellular carcinoma (HCC) is one of the few cancers with a continuous increase in incidence and mortality. Drug resistance is a major problem in the treatment of HCC. In this study, two ...sorafenib‐resistant HCC cell lines and a nude mouse subcutaneously tumor model were used to explore the possible mechanisms leading to sorafenib resistance, and to investigate whether aspirin could increase the sensitivity of hepatoma cells to sorafenib. The combination of aspirin and sorafenib resulted in a synergistic antitumor effect against liver tumors both in vitro and in vivo. High glycolysis and PFKFB3 overexpression occupied a dominant position in sorafenib resistance, and can be targeted and overcome by aspirin. Aspirin plus sorafenib induced apoptosis in tumors without inducing weight loss, hepatotoxicity or inflammation. Our results suggest that aspirin overcomes sorafenib resistance and their combination may be an effective treatment approach for HCC.
What's new?
Sorafenib, a kinase inhibitor, is one of the most effective drugs available for the treatment of hepatocellular carcinoma (HCC). Its use, however, is limited by acquired resistance. The present study shows that the expression of PFKFB3, a gene involved in glycolytic flux that encodes 6‐phosphofructo‐1‐kinase 2 (PFK2), is strongly associated with sorafenib resistance in HCC cells. PFK is a suspected target of aspirin, a drug associated with reduced HCC risk. Experiments in cells and animals reveal the existence of a synergistic antitumor effect between aspirin and sorafenib, suggesting that sorafenib‐resistant HCC patients may benefit from combined treatment with aspirin.
Genistein is a natural isoflavone with many health benefits, including antitumour effects. Increased hypoxia-inducible factor 1 α (HIF-1α) levels and glycolysis in tumour cells are associated with an ...increased risk of mortality, cancer progression, and resistance to therapy. However, the effect of genistein on HIF-1α and glycolysis in hepatocellular carcinoma (HCC) is still unclear.
Cell viability, apoptosis rate, lactate production, and glucose uptake were measured in HCC cell lines with genistein incubation. Lentivirus-expressed glucose transporter 1 (GLUT1) or/and hexokinase 2 (HK2) and siRNA of HIF-1α were used to test the direct target of genistein. Subcutaneous xenograft mouse models were used to measure in vivo efficacy of genistein and its combination with sorafenib.
Genistein inhibited aerobic glycolysis and induced mitochondrial apoptosis in HCC cells. Neither inhibitors nor overexpression of HK2 or GLUTs enhance or alleviate this effect. Although stabiliser of HIF-1α reversed the effect of genistein, genistein no longer has effects on HIF-1α siRNA knockdown HCC cells. In addition, genistein enhanced the antitumour effect of sorafenib in sorafenib-resistant HCC cells and HCC-bearing mice.
Genistein sensitised aerobic glycolytic HCC cells to apoptosis by directly downregulating HIF-1α, therefore inactivating GLUT1 and HK2 to suppress aerobic glycolysis. The inhibitory effect of genistein on tumour cell growth and glycolysis may help identify effective treatments for HCC patients at advanced stages.
Field-road classification is a key task in processing spatio-temporal trajectories in the agricultural field. This task involves classifying agricultural machinery trajectories into field operation ...and road driving trajectories. Accurately classifying these trajectories is essential for precision agriculture. However, the existing methods for field-road classification do not address the issue of data imbalance between the numbers of field and road points in trajectories. To improve the accuracy of field-road classification and solve the data imbalance problem in agricultural machinery trajectories, a generative adversarial network-bidirectional long short-term memory network (GAN-BiLSTM) field-road classification model is proposed in this paper. First, we use a GAN for data augmentation to obtain a balanced dataset. Second, we propose a BiLSTM with attention mechanism (Att-BiLSTM) to capture data features. Finally, we train the model using focal loss to further learn points that are difficult to classify for field-road classification. To evaluate the effectiveness of our proposed model, we conducted experiments and compared our results with those of the current field-road classification methods on 160 agricultural trajectory samples. Our model achieved 92.3% accuracy and a 92.1% F1 score, exhibiting improvements of 5.9% in accuracy and 6.4% in F1 score compared with the current state-of-the-art method. The source code is publicly available at https://github.com/hysyyds/GAN-BiLSTM.
•Alleviating data imbalance in field-road classification via CTGAN.•Enhancing features through time window-based augmentation.•Field-road classification employing attention-based BiLSTM.•Outperforming previous field-road classification approaches in F1 and accuracy.
Field-road trajectory classification, in which the semantic labels of unknown trajectory points are predicted by learning the features of agricultural machinery trajectories, has recently received ...considerable attention in agriculture. At present, most agricultural machinery trajectory samples have imbalanced data distribution problems, and existing field-road trajectory classification methods, which usually use a small set of trajectory features, cannot fully mine the potential information of trajectories, resulting in a low classification accuracy. To address these problems, this paper proposes a Bagging-SVM field-road trajectory classification model based on feature enhancement. First, we use oversampling and undersampling methods to obtain balanced agricultural machinery trajectory data. Second, local features and global features are defined to perform in-depth mining of the spatiotemporal information. Specifically, the local features are derived by calculating the attributes of the dataset, and then the global features are calculated from the local features using the statistical magnitude. Next, principal component analysis (PCA) is employed to identify significant features and decrease the dimensionality. Finally, we introduce the bagging integrated learning method in support vector machines to construct Bagging-SVM as a classifier for field-road trajectory classification. To verify the effectiveness of the proposed method, we conduct experiments using 20 trajectory samples with high-frequency sampling frequencies and 20 trajectory samples with low-frequency sampling frequencies, and the classification F1 score of this method reach 97.01% and 98.71% on two trajectory dataset, respectively. The experimental results show that our method outperforms existing field-road trajectory classification methods.
•A Bagging-SVM field-road trajectory classification model based on feature enhancement was proposed.•Oversampling and undersampling were used to balance the dataset.•Local features and global features were extracted from trajectories by different feature extraction operators.•Principal component analysis was used to select significant features.
Objective. Fucosterol is derived from the brown alga Eisenia bicyclis and has various biological activities, including antioxidant, anticancer, and antidiabetic properties. The aim of this study was ...to investigate the protective effects of fucosterol pretreatment on Concanavalin A- (ConA-) induced acute liver injury in mice, and to understand its molecular mechanisms. Materials and Methods. Acute liver injury was induced in BALB/c mice by ConA (25 mg/kg), and fucosterol (dissolved in 2% DMSO) was orally administered daily at doses of 25, 50, and 100 mg/kg. The levels of hepatic necrosis, apoptosis, and autophagy associated with inflammatory cytokines were measured at 2, 8, and 24 h. Results. Fucosterol attenuated serum liver enzyme levels and hepatic necrosis and apoptosis induced by TNF-α, IL-6, and IL-1β. Fucosterol also inhibited apoptosis and autophagy by upregulating Bcl-2, which decreased levels of functional Bax and Beclin-1. Furthermore, reduced P38 MAPK and NF-κB signaling were accompanied by PPARγ activation. Conclusion. This study showed that fucosterol could alleviate acute liver injury induced by ConA by inhibiting P38 MAPK/PPARγ/NF-κB signaling. These findings highlight that fucosterol is a promising potential therapeutic agent for acute liver injury.
Abstract
Background and Aim
Liver fibrosis is a worldwide clinical challenge during the progression of chronic liver disease to liver cirrhosis. Shikonin is extracted from the root of
Lithospermum ...erythrorhizon
with antioxidant, anti‐inflammatory, anticancer, and wound‐healing properties. The study aims to investigate the protective effect of shikonin on liver fibrosis and its underlying mechanism.
Methods
Two liver fibrosis models were established in male C57 mice by intraperitoneal injection of CCl
4
or bile duct ligation. Shikonin was administered orally three times weekly at a dose of 2.5 or 5 mg/kg. Protein and mRNA expressions were assayed by quantitative real‐time polymerase chain reaction, Western blotting, and immunohistochemical staining.
Results
Shikonin significantly inhibited activation of hepatic stellate cells and extracellular matrix formation by downregulating the transforming growth factor‐β1 expression and maintaining the normal balance between metalloproteinase‐2 and tissue inhibitor of metalloproteinase‐1. Shikonin also decreased hepatic stellate cell energy production by inhibiting autophagy.
Conclusions
The results confirmed that shikonin attenuated liver fibrosis by downregulating the transforming growth factor‐β1/Smads pathway and inhibiting autophagy.
Background and Aim
Liver fibrosis is a worldwide clinical challenge during the progression of chronic liver disease to liver cirrhosis. Shikonin is extracted from the root of Lithospermum ...erythrorhizon with antioxidant, anti‐inflammatory, anticancer, and wound‐healing properties. The study aims to investigate the protective effect of shikonin on liver fibrosis and its underlying mechanism.
Methods
Two liver fibrosis models were established in male C57 mice by intraperitoneal injection of CCl4 or bile duct ligation. Shikonin was administered orally three times weekly at a dose of 2.5 or 5 mg/kg. Protein and mRNA expressions were assayed by quantitative real‐time polymerase chain reaction, Western blotting, and immunohistochemical staining.
Results
Shikonin significantly inhibited activation of hepatic stellate cells and extracellular matrix formation by downregulating the transforming growth factor‐β1 expression and maintaining the normal balance between metalloproteinase‐2 and tissue inhibitor of metalloproteinase‐1. Shikonin also decreased hepatic stellate cell energy production by inhibiting autophagy.
Conclusions
The results confirmed that shikonin attenuated liver fibrosis by downregulating the transforming growth factor‐β1/Smads pathway and inhibiting autophagy.
Field-road segmentation is one of the key tasks in the processing of the trajectory of agricultural machinery. To improve the accuracy of the field-road segmentation, this study proposed an XGBoost ...model based on dual feature extraction and recursive feature elimination called DR-XGBoost. DR-XGBoost takes only a small amount of agricultural machine trajectory features as input. Firstly, the model adopted the dual feature extraction method we designed to rapidly expand the number of features and then adequately extract local trajectory features by the time window and feature extraction operator. Secondly, the model applies the recursive feature elimination algorithm to eliminate redundant features from the perspective of the model segmentation effect and thus reduce the computational consumption of model training. Thirdly, it trains XGBoost to complete the trajectory segmentation. To evaluate the effectiveness of DR-XGBoost, we conducted a series of experiments on a real trfsajectory dataset of agricultural machines. The model achieves a 98.2% Macro-Fl score on the dataset, which is 10.9% higher than the previous state-of-art. The proposal of DR-XGBoost fills the knowledge gap of trajectory feature extraction for agricultural machinery and provides a reasonable and effective feature selection scheme for the field-road segmentation problem.
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