The plant circadian clock regulates autophagy rhythm through transcription factor LUX ARRHYTHMO.

Autophagy is an evolutionarily conserved degradation pathway in eukaryotes; it plays a critical role in nutritional stress tolerance. The circadian clock is an endogenous timekeeping system that generates biological rhythms to adapt to daily changes in the environment. Accumulating evidence indicates that the circadian clock and autophagy are intimately interwoven in animals. However, the role of the circadian clock in regulating autophagy has been poorly elucidated in plants. Here, we show that autophagy exhibits a robust circadian rhythm in both light/dark cycle (LD) and in constant light (LL) in Arabidopsis. However, autophagy rhythm showed a different pattern with a phase-advance shift and a lower amplitude in LL compared to LD. Moreover, mutation of the transcription factor LUX ARRHYTHMO (LUX) removed autophagy rhythm in LL and led to an enhanced amplitude in LD. LUX represses expression of the core autophagy genes ATG2, ATG8a, and ATG11 by directly binding to their promoters. Phenotypic analysis revealed that LUX is responsible for improved resistance of plants to carbon starvation, which is dependent on moderate autophagy activity. Comprehensive transcriptomic analysis revealed that the autophagy rhythm is ubiquitous in plants. Taken together, our findings demonstrate that the LUX-mediated circadian clock regulates plant autophagy rhythms.

[Output Characteristics and Driving Mechanism of Agricultural Non-point Source (AGNPS) Pollutant in Plain and Valley Region of Upper Yangtze River, China].

Research on the pattern and mechanism of agricultural non-point source (AGNPS) pollution in rural areas is of great significance to the governance of the regional ecological environment. This study took the plain and hilly area of the upper Yangtze River as the research area, relied on multivariate data, and used a pollutant measurement method based on spatial distance correction, and Kriging interpolation and logistic regression methods (LR) were used to study the emission pattern and impact mechanism of AGNPS pollutants. The results showed that the total emissions of COD, BOD5, NH4+-N, TN, and TP increased by 15.46×104, 25.66×104, 3.49×104, 1.26×104, and 0.38×104 t, respectively, and the emissions of these five pollutants had strong spatial regularity from 2005 to 2015. The Chengdu Plain, the hills in central Sichuan, and the parallel ridge valley farming areas in eastern Sichuan were the high-value areas, whereas urban areas and hinterland of the Three Gorges Reservoir (TGRA) were low-value areas. The risk levels of COD, BOD5, and NH4+-N increased; TN pollution was more serious; and the emission risk level was gradually increasing. The emission risk of TP was high and had a tendency to continue to deteriorate. The overall risk level was in a spatial pattern of "high in the middle and low in the surrounding area," with extremely high and second-highest risk levels in a mosaic distribution. The Chengdu Plain and the Parallel Ridge and Valley areas in eastern Sichuan were high-risk clusters. The main driving factors of non-point source pollution from 2005 to 2010 were grain output, livestock and poultry production, and the number of rural populations, which were categorized as "production-driven" GDP and annual average precipitation were the main driving factors, which were categorized as "production and life synergy-driven." These results can provide a basis for analyzing the driving mechanism and prevention and control of NPSP in the hilly area of the upper Yangtze River.

A multi-level feature-fusion-based approach to breast histopathological image classification.

Previously, convolutional neural networks mostly used deep semantic feature information obtained from several convolutions for image classification. Such deep semantic features have a larger receptive field, and the features extracted are more effective as the number of convolutions increases, which helps in the classification of targets. However, this method tends to lose the shallow local features, such as the spatial connectivity and correlation of tumor region texture and edge contours in breast histopathology images, which leads to its recognition accuracy not being high enough. To address this problem, we propose a multi-level feature fusion method for breast histopathology image classification. First, we fuse shallow features and deep semantic features by attention mechanism and convolutions. Then, a new weighted cross entropy loss function is used to deal with the misjudgment of false negative and false positive. And finally, the correlation of spatial information is used to correct the misjudgment of some patches. We have conducted experiments on our own datasets and compared with the base network Inception-ResNet-v2, which has a high accuracy. The proposed method achieves an accuracy of 99.0% and an AUC of 99.9%.

miR-155 increases stemness and decitabine resistance in triple-negative breast cancer cells by inhibiting TSPAN5.

Effective therapeutic targets for triple-negative breast cancer (TNBC), a special type of breast cancer (BC) with rapid metastasis and poor prognosis, are lacking, especially for patients with chemotherapy resistance. Decitabine (DCA) is a Food and Drug Administration-approved DNA methyltransferase inhibitor that has been proven effective for the treatment of tumors. However, its antitumor effect in cancer cells is limited by multidrug resistance. Cancer stem cells (CSCs), which are thought to act as seeds during tumor formation, regulate tumorigenesis, metastasis, and drug resistance through complex signaling. Our previous study found that miR-155 is upregulated in BC, but whether and how miR-155 regulates DCA resistance is unclear. In this study, we demonstrated that miR-155 was upregulated in CD24- CD44+ BC stem cells (BCSCs). In addition, the overexpression of miR-155 increased the number of CD24- CD44+ CSCs, DCA resistance and tumor clone formation in MDA-231 and BT-549 BC cells, and knockdown of miR-155 inhibited DCA resistance and stemness in BCSCs in vitro. Moreover, miR-155 induced stemness and DCA resistance by inhibiting the direct target gene tetraspanin-5 (TSPAN5). We further confirmed that overexpression of TSPAN5 abrogated the effect of miR-155 in promoting stemness and DCA resistance in BC cells. Our data show that miR-155 increases stemness and DCA resistance in BC cells by targeting TSPAN5. These data provide a therapeutic strategy and mechanistic basis for future possible clinical applications targeting the miR-155/TSPAN5 signaling axis in the treatment of TNBC.

[Protective effect of HIF-1alpha-dependent HO-1 overexpression on hypoxic human hepatoma cells in vitro].

OBJECTIVE: To investigate the protective effect of overexpressed heme oxygenase-1 (HO-1) in hypoxia and the correlation between HO-1 overexpressoin and hypoxia inducible factor-1alpha (HIF-1alpha) in human hepatoma HepG2 cells. METHODS: The expressions of HO-1 and HIF-1alpha mRNA as well as the protein were detected by RT-PCR and Western blotting, respectively. MTT assay was used to examine the relative cell survival rate. The total superoxide dismutase (SOD) activity was examined with a SOD kit. RESULTS: Hypoxia induced overexpression of HO-1 gene in HepG2 cells at transcriptional and translational levels. The relative survival rate of HepG2 cells under hypoxia was significantly decreased after the HO-1 protein overexpression was inhibited by ZnPPIX (P < 0.01). The total SOD activity of cells was significantly increased after cells were treated by hypoxia for 16 hours (P < 0.05), while decreased significantly by HO-1 inhibitor ZnPPIX treatment (P < 0.01). HIF-1alpha was upregulated under hypoxia. In addition, the HO-1 overexpression under hypoxia was decreased by HIF-1alpha inhibitor, while the HIF-1alpha expression level under hypoxia was not significantly changed after HO-1 expression was inhibited by ZnPPIX. CONCLUSION: The overexpression of HO-1 in hypoxic HepG2 cells is HIF-1alpha-dependent or at least partly HIF-1alpha-dependent. The relative survival rate of hypoxic hepatoma cells was significantly decreased by HO-1 inhibitor treatment. The results of this study may offer new thought and drug target for the therapy of human hepatoma in the future.