Extracting the winter wheat using the decision tree based on time series dual-polarization SAR feature and NDVI.

Winter wheat is one of the most important crops in the world. It is great significance to obtain the planting area of winter wheat timely and accurately for formulating agricultural policies. Due to the limited resolution of single SAR data and the susceptibility of single optical data to weather conditions, it is difficult to accurately obtain the planting area of winter wheat using only SAR or optical data. To solve the problem of low accuracy of winter wheat extraction only using optical or SAR images, a decision tree classification method combining time series SAR backscattering feature and NDVI (Normalized Difference Vegetation Index) was constructed in this paper. By synergy using of SAR and optical data can compensate for their respective shortcomings. First, winter wheat was distinguished from other vegetation by NDVI at the maturity stage, and then it was extracted by SAR backscattering feature. This approach facilitates the semi-automated extraction of winter wheat. Taking Yucheng City of Shandong Province as study area, 9 Sentinel-1 images and one Sentinel-2 image were taken as the data sources, and the spatial distribution of winter wheat in 2022 was obtained. The results indicate that the overall accuracy (OA) and kappa coefficient (Kappa) of the proposed method are 96.10% and 0.94, respectively. Compared with the supervised classification of multi-temporal composite pseudocolor image and single Sentinel-2 image using Support Vector Machine (SVM) classifier, the OA are improved by 10.69% and 5.66%, respectively. Compared with using only SAR feature for decision tree classification, the producer accuracy (PA) and user accuracy (UA) for extracting the winter wheat are improved by 3.08% and 8.25%, respectively. The method proposed in this paper is rapid and accurate, and provide a new technical method for extracting winter wheat.

FOXG1 regulates the proliferation and apoptosis of human lung cancer cells.

FOXG1, a transcriptional factor belonging to the Forkhead Box (Fox) superfamily, is highly expressed in the brain tissue during brain development and plays an important role in cellular proliferation. Recently, FOXG1 was reported to play important roles in oncogenesis, wherein its abnormal expression regulates tumor cell proliferation. However, the expression and role of FOXG1 in lung cancer remain largely unknown. This study investigated the clinical significance, expression, and role of FOXG1 in lung cancer. We found that FOXG1 was highly expressed in lung cancer tissues. MTT, CCK-8 and colony formation assays showed that FOXG1 overexpression could enhance the proliferation of A549 lung cancer cells. Flow cytometry analysis revealed that FOXG1 promoted the cell cycle and suppressed cell apoptosis. Additionally, the expression levels of PTEN, phosphorylated AKT, mTOR, p53, and Bax were significantly altered in response to changes in FOXG1 expression, indicating that FOXG1 regulated the PI3K pathway. Furthermore, in the xenograft mouse model, the upregulated FOXG1 expression strongly promoted tumor growth. In conclusion, these results suggested that FOXG1 was a critical regulator of the proliferation of lung cancer cells and enhanced tumor growth in vivo.

N6-methyladenosine (m6A) writer METTL3 accelerates the apoptosis of vascular endothelial cells in high glucose.

Recent studies have shown that N6-methyladenosine (m6A) methylation, one of the most prevalent epigenetic modifications, is involved in diabetes mellitus. However, whether m6A regulates diabetic vascular endothelium injury is still elusive. Present research aimed to investigate the regulation and mechanism of m6A on vascular endothelium injury. Upregulation of METTL3 was observed in the high glucose (HG)-induced human umbilical vein endothelial cells (HUVECs), following with the upregulation of m6A methylation level. Functionally, METTL3 silencing repressed the apoptosis and recovered the proliferation of HUVECs disposed by HG. Moreover, HG exposure upregulated the expression of suppressor of cytokine signaling3 (SOCS3). Mechanistically, METTL3 targeted the m6A site on SOCS3 mRNA, which positively regulated the mRNA stability of SOCS3. In conclusion, METTL3 silencing attenuated the HG-induced vascular endothelium cells injury via promoting SOCS3 stability. In conclusion, this research expands the understanding of m6A on vasculopathy in diabetes mellitus and provides a potential strategy for the protection of vascular endothelial injury.

CircSHOC2 Knockdown Alleviates High Glucose-Induced Vascular Endothelial Cell Pyroptosis via Targeting miR-145/FOXO1 Axis In Vitro Condition.

Emerging evidence indicates that pyroptosis participates in the pathogenic process of vascular endothelial cells in cardiovascular system complications of diabetes. The roles of circular RNAs (circRNAs) in high glucose (HG)-induced vascular endothelial cells are still unclear. Here, our research investigated the function and mechanism of circRNA circSHOC2 in pyroptosis of vascular endothelial cells. Results indicated that circSHOC2 was up-regulated in HG-induced human umbilical vein endothelial cells (HUVECs). Functionally, cellular assays indicated that circSHOC2 silencing repressed HG-induced HUVECs pyroptosis. Moreover, circSHOC2 targeted miR-145 through miRNA sponge, and FOXO1 functioned as downstream target of miR-145. In conclusion, these findings suggested the potential roles of circSHOC2 on HG-induced vascular endothelial cells in vitro condition, providing new insights for cardiovascular system complications of diabetes.

Field-scale rice yield estimation based on UAV-based MiniSAR data with Ku band and modified water-cloud model of panicle layer at panicle stage.

Scientific and accurate estimation of rice yield is of great significance to food security protection and agricultural economic development. Due to the weak penetration of high frequency microwave band, most of the backscattering comes from the rice canopy, and the backscattering coefficient is highly correlated with panicle weight, which provides a basis for inversion of wet biomass of rice ear. To solve the problem of rice yield estimation at the field scale, based on the traditional water cloud model, a modified water-cloud model based on panicle layer and the radar data with Ku band was constructed to estimate rice yield at panicle stage. The wet weight of rice ear scattering model and grain number per rice ear scattering model were constructed at field scale for rice yield estimation. In this paper, the functional area of grain production in Xiashe Village, Xin'an Town, Deqing County, Zhejiang Province, China was taken as the study area. For the first time, the MiniSAR radar system carried by DJI M600 UAV was used in September 2019 to obtain the SAR data with Ku band under polarization HH of the study area as the data source. Then the rice yield was estimated by using the newly constructed modified water-cloud model based on panicle layer. The field investigation was carried out simultaneously for verification. The study results show: the accuracies of the inversion results of wet weight of rice ear scattering model and grain number per rice ear scattering model in parcel B were 95.03% and 94.15%; and the accuracies of wet weight of rice ear scattering model and grain number per rice ear scattering model in parcel C+D+E were over 91.8%. In addition, different growth stages had effects on yield estimation accuracy. For rice at fully mature, the yield estimation accuracies of wet weight of ear and grain number per ear were basically similar, both exceeding 94%. For rice at grouting stage, the yield estimation accuracy of wet weight of ear was 92.7%, better than that of grain number per ear. It was proved that it can effectively estimate rice yield using the modified water-cloud model based on panicle layer constructed in this paper at panicle stage at field scale.

An Effective Approach of Vehicle Detection Using Deep Learning.

With the rise of unmanned driving and intelligent transportation research, great progress has been made in vehicle detection technology. The purpose of this paper is employing the method of deep learning to study the vehicle detection algorithm, in which primary-stage target detection algorithms, namely, YOLOv3 algorithm and SSD algorithm, are adopted. Therefore, the method first processes the image data in the open-source road vehicle dataset for training. Then, the vehicle detection model is trained by using YOLOv3 and SSD algorithms to show the detection effect, respectively. The result is by comparing the detection effects of the two models on vehicles. The researchers accomplished the result analysis and summarized the characteristics of various models obtained by training, to apply to target tracking, semantic segmentation, and unmanned driving.

Long noncoding RNA GAS5 impairs the proliferation and invasion of endometrial carcinoma induced by high glucose via targeting miR-222-3p/p27.

Long noncoding RNAs (lncRNAs) have been identified to be critical functional regulator in the human tumors, while the deepgoing mechanism by which lncRNAs modulates the endometrial carcinoma is still elusive. In this work, we found that lncRNA GAS5 was under-expressed in the endometrial carcinoma tissue specimens, especially these samples with type 2 diabetes mellitus. Besides, the aberrant under-expression of GAS5 was correlated with the advanced tumor stage as well as poor prognosis outcome. In cellular experiments, GAS5 was decreased in the cells exposed to the high glucose. Enforced GAS5 expression repressed the tumor phenotype of endometrial carcinoma cells, including proliferation and invasion. Molecular mechanism study further demonstrated that GAS5 functioned as a sponge for miR-222-3p, abrogating its ability of inhibiting p27 protein expression. In conclusion, these results confirmed the vital regulation of GAS5/miR-222-3p/p27 axis in the endometrial carcinoma tumorigenesis.

miR-194 suppresses high glucose-induced non-small cell lung cancer cell progression by targeting NFAT5.

BACKGROUND: Diabetes mellitus (DM) is linked to an increased risk of lung cancer; however, the exact molecular basis is unclear. METHODS: We used a microarray method and found a group of microRNAs differently expressed in lung cancer cells at high or low glucose treatment. RESULTS: Among these, miR-194 changed significantly, which indicated further analysis. miR-194 was significantly downregulated in non-small cell lung cancer (NSCLC) cells cultured in high glucose (HG) medium and clinical NSCLC tissues with DM. The introduction of miR-194 significantly suppressed the proliferation, migration, and invasion of lung cancer cells induced by HG, suggesting that miR-194 may be a suppressor during HG-induced NSCLC progression. Further analysis indicated that NFAT5 was a direct target gene of miR-194, evidenced by the direct binding of miR-194 with the 3'untranslated region of NFAT5. MiR-194 could decrease the expression of NFAT5 at both messenger RNA and protein levels, while overexpression of NFAT5 reversed the decreased proliferation, migration, and invasion ability mediated by miR-194 in lung cancer cells. CONCLUSION: Our findings provide new insight into the mechanism of NSCLC progression. Therapeutically, miR-194 may serve as a potential target for the treatment of lung cancer patients with DM.

LncRNA LINC00968 accelerates the proliferation and fibrosis of diabetic nephropathy by epigenetically repressing p21 via recruiting EZH2.

Emerging evidence have indicated the vital roles of long noncoding RNAs (lncRNAs) in the pathophysiological process of diabetic nephropathy. However, the deepgoing mechanism that lncRNAs regulate the diabetic nephropathy pathogenesis is still ambiguous. In present study, we found that lncRNA LINC00968 expression was high-expressed in the diabetic db/db mouse tissue and high-glucose induced mesangial cells. Functional experiments indicated that LINC00968 silencing by siRNAs significantly inhibited the proliferation and cycle progression, and decreased the extracellular matrix (ECM) proteins (fibronectin, collagen IV) expression in the high glucose induced of mesangial cells. RNA immunoprecipitation (RIP) and chromatin immunoprecipitation (ChIP) assay revealed that LINC00968 recruit EZH2 to the promoter of p21 to inhibit its expression. In summary, our results support the conclusion that lncRNA LINC00968 accelerates the proliferation and fibrosis of mesangial cells by epigenetically repressing p21 via recruiting EZH2, providing a novel insight for the diabetic nephropathy pathogenesis.