Tidal and Meteorological Influences on the Growth of Invasive Spartina alterniflora: Evidence from UAV Remote Sensing

Rapid invasion of Spartina alterniflora into Chinese coastal wetlands has attracted much attention. Many field and remote sensing studies have examined the spatio-temporal dynamics of S. alterniflora invasion; however, spatially explicit quantitative analyses of S. alterniflora invasion and its underlying mechanisms at both patch and landscape scales are seldom reported. To fill this knowledge gap, we integrated multi-temporal unmanned aerial vehicle (UAV) imagery, light detection and ranging (LiDAR)-derived elevation data, and tidal and meteorological time series to explore the growth potential (lateral expansion rates and canopy greenness) of S. alterniflora over the intertidal zone in a subtropical coastal wetland (Zhangjiang estuarine wetland, Fujian, China). Our analyses of patch expansion indicated that isolated S. alterniflora patches in this wetland experienced high lateral expansion over the past several years (averaged at 4.28 m/year in patch diameter during 2014–2017), and lateral expansion rates ( y role= presentation style= box-sizing: border-box; max-height: none; display: inline; line-height: normal; word-spacing: normal; overflow-wrap: normal; white-space: nowrap; float: none; direction: ltr; max-width: none; min-width: 0px; min-height: 0px; border: 0px; padding: 0px; margin: 0px; position: relative; \u3ey , m/year) showed a statistically significant declining trend with increasing inundation ( x role= presentation style= box-sizing: border-box; max-height: none; display: inline; line-height: normal; word-spacing: normal; overflow-wrap: normal; white-space: nowrap; float: none; direction: ltr; max-width: none; min-width: 0px; min-height: 0px; border: 0px; padding: 0px; margin: 0px; position: relative; \u3ex , h/day; 3≤x≤18 role= presentation style= box-sizing: border-box; max-height: none; display: inline; line-height: normal; word-spacing: normal; overflow-wrap: normal; white-space: nowrap; float: none; direction: ltr; max-width: none; min-width: 0px; min-height: 0px; border: 0px; padding: 0px; margin: 0px; position: relative; \u3e3≤x≤18 ): y=−0.17x+5.91 role= presentation style= box-sizing: border-box; max-height: none; display: inline; line-height: normal; word-spacing: normal; overflow-wrap: normal; white-space: nowrap; float: none; direction: ltr; max-width: none; min-width: 0px; min-height: 0px; border: 0px; padding: 0px; margin: 0px; position: relative; \u3ey=−0.17x+5.91 , R2=0.78 role= presentation style= box-sizing: border-box; max-height: none; display: inline; line-height: normal; word-spacing: normal; overflow-wrap: normal; white-space: nowrap; float: none; direction: ltr; max-width: none; min-width: 0px; min-height: 0px; border: 0px; padding: 0px; margin: 0px; position: relative; \u3eR2=0.78 . Our analyses of canopy greenness showed that the seasonality of the growth potential of S. alterniflora was driven by temperature (Pearson correlation coefficient r=0.76 role= presentation style= box-sizing: border-box; max-height: none; display: inline; line-height: normal; word-spacing: normal; overflow-wrap: normal; white-space: nowrap; float: none; direction: ltr; max-width: none; min-width: 0px; min-height: 0px; border: 0px; padding: 0px; margin: 0px; position: relative; \u3er=0.76 ) and precipitation ( r=0.68 role= presentation style= box-sizing: border-box; max-height: none; display: inline; line-height: normal; word-spacing: normal; overflow-wrap: normal; white-space: nowrap; float: none; direction: ltr; max-width: none; min-width: 0px; min-height: 0px; border: 0px; padding: 0px; margin: 0px; position: relative; \u3er=0.68 ), with the growth potential peaking in early/middle summer with high temperature and adequate precipitation. Together, we concluded that the growth potential of S. alterniflora was co-regulated by tidal and meteorological regimes, in which spatial heterogeneity is controlled by tidal inundation while temporal variation is controlled by both temperature and precipitation. To the best of our knowledge, this is the first spatially explicit quantitative study to examine the influences of tidal and meteorological regimes on both spatial heterogeneity (over the intertidal zone) and temporal variation (intra- and inter-annual) of S. alterniflora at both patch and landscape scales. These findings could serve critical empirical evidence to help answer how coastal salt marshes respond to climate change and assess the vulnerability and resilience of coastal salt marshes to rising sea level. Our UAV-based methodology could be applied to many types of plant community distributions

PMA and ionomycin induce glioblastoma cell death: activation-induced cell-death-like phenomena occur in glioma cells.

Phorbol myristate acetate (PMA) and ionomycin (Io) can induce T cell activation and proliferation. Furthermore, they stimulate activation-induced cell death (AICD) in mature lymphocytes via Fas/Fas ligand (FasL) up-regulation. In this study, we explored the influence of PMA/Io treatment on glioblastoma cells, and found that AICD-like phenomena may also occur in glioma. Using the MTT assay and cell counting, we demonstrated that treatment of PMA/Io significantly inhibited the proliferation of glioma cell lines, U87 and U251. TUNEL assays and transmission electron microscopy revealed that PMA/Io markedly induced U87 and U251 cell apoptosis. Propidium iodide staining and flow cytometry showed that treatment with PMA/Io resulted in an arrestment of cell cycle and an increase in cell death. Using real-time PCR and western blot, we found that PMA/Io up-regulated the expression of Fas and FasL at both mRNA and protein level, which confirmed that PMA/Io induced glioma cell death. Specific knockdown of NFAT1 expression by small hairpin RNA greatly reduced the PMA/Io induced cell death and apoptosis by inhibition of FasL expression. Microarray analysis showed that the expression of NFAT1 significantly correlated with the expression of Fas. The coexistence of Fas with NFAT1 in vivo provides the background for AICD-like phenomena to occur in glioma. These findings demonstrate that PMA/Io can induce glioblastoma cell death through the NFAT1-Fas/FasL pathway. Glioma-related AICD-like phenomena may provide a novel avenue for glioma treatment

Plasma IGFBP-2 levels after postoperative combined radiotherapy and chemotherapy predict prognosis in elderly glioblastoma patients.

It has been found that preoperative plasma IGFBP-2 levels correlate with prognosis in glioma patients. The prognostic value of plasma IGFBP-2 after postoperative combined radiotherapy and chemotherapy in glioma patients is unknown. Plasma IGFBP-2 levels in 83 glioblastoma patients after postoperative radiotherapy plus chemotherapy were analyzed using an IGFBP-2 ELISA kit. We found that after standard therapy plasma IGFBP-2 levels significantly correlated with the patient's age (R = 0.738, P<0.001) and Karnofsky performance status (KPS, R =  -0.633, P<0.05). Cox proportional hazards models were used to calculate hazard ratios (HRs) of death according to plasma IGFBP-2 levels adjusted for patient clinical characteristics. Plasma IGFBP-2 levels significantly correlated with overall survival in glioblastoma patients (multivariate HR = 1.035; 95% CI, 1.024-1.047; P<0.001). The effect of plasma IGFBP-2 levels on survival seemed to differ according to patients' age. Among patients older than 60, high plasma IGFBP-2 levels were associated with a significant increase in overall mortality (HR = 1.097; 95% CI, 1.055-1.140; P<0.001). In contrast, plasma IGFBP-2 levels conferred no significant effect on mortality among patients younger than 60. Elevated plasma IGFBP-2 levels after combined postoperative radiotherapy and chemotherapy in elderly glioblastoma patients correlate with poor KPS score and predicts poor prognosis

Tidal and Meteorological Influences on the Growth of Invasive <i>Spartina alterniflora</i>: Evidence from UAV Remote Sensing

Rapid invasion of Spartina alterniflora into Chinese coastal wetlands has attracted much attention. Many field and remote sensing studies have examined the spatio-temporal dynamics of S. alterniflora invasion; however, spatially explicit quantitative analyses of S. alterniflora invasion and its underlying mechanisms at both patch and landscape scales are seldom reported. To fill this knowledge gap, we integrated multi-temporal unmanned aerial vehicle (UAV) imagery, light detection and ranging (LiDAR)-derived elevation data, and tidal and meteorological time series to explore the growth potential (lateral expansion rates and canopy greenness) of S. alterniflora over the intertidal zone in a subtropical coastal wetland (Zhangjiang estuarine wetland, Fujian, China). Our analyses of patch expansion indicated that isolated S. alterniflora patches in this wetland experienced high lateral expansion over the past several years (averaged at 4.28 m/year in patch diameter during 2014&#8722;2017), and lateral expansion rates ( y , m/year) showed a statistically significant declining trend with increasing inundation ( x , h/day; 3 &#8804; x &#8804; 18 ): y = &#8722; 0.17 x + 5.91 , R 2 = 0.78 . Our analyses of canopy greenness showed that the seasonality of the growth potential of S. alterniflora was driven by temperature (Pearson correlation coefficient r = 0.76 ) and precipitation ( r = 0.68 ), with the growth potential peaking in early/middle summer with high temperature and adequate precipitation. Together, we concluded that the growth potential of S. alterniflora was co-regulated by tidal and meteorological regimes, in which spatial heterogeneity is controlled by tidal inundation while temporal variation is controlled by both temperature and precipitation. To the best of our knowledge, this is the first spatially explicit quantitative study to examine the influences of tidal and meteorological regimes on both spatial heterogeneity (over the intertidal zone) and temporal variation (intra- and inter-annual) of S. alterniflora at both patch and landscape scales. These findings could serve critical empirical evidence to help answer how coastal salt marshes respond to climate change and assess the vulnerability and resilience of coastal salt marshes to rising sea level. Our UAV-based methodology could be applied to many types of plant community distributions

Upright and Crawling Locomotion and Its Transition for a Wheel-Legged Robot

To face the challenge of adapting to complex terrains and environments, we develop a novel wheel-legged robot that can switch motion modes to adapt to different environments. The robot can perform efficient and stable upright balanced locomotion on flat roads and flexible crawling in low and narrow passages. For passing through low and narrow passages, we propose a crawling motion control strategy and methods for transitioning between locomotion modes of wheel-legged robots. In practical applications, the smooth transition between the two motion modes is challenging. By optimizing the gravity work of the body, the optimal trajectory of the center of mass (CoM) for the transition from standing to crawling is obtained. By constructing and solving an optimization problem regarding the posture and motion trajectories of the underactuated model, the robot achieves a smooth transition from crawling to standing. In experiments, the wheel-legged robot successfully transitioned between the crawling mode and the upright balanced moving mode and flexibly passed a low and narrow passage. Consequently, the effectiveness of the control strategies and algorithms proposed in this paper are verified by experiments

NFAT1 is highly expressed in, and regulates the invasion of, glioblastoma multiforme cells.

Members of the nuclear factor of activated T cells (NFAT) family have been identified as regulators of oncogenic transformation in several human malignancies. A prominent member of this family, NFAT1, is associated with tumor cell survival, apoptosis, migration and invasion. Here, we investigated the role of NFAT1 in glioma cells. In 111 clinical samples, microarray analysis demonstrated that NFAT1 was over-expressed in glioblastoma multiforme (GBM), compared with low-grade gliomas, a result confirmed by RT-PCR in 24 clinical samples and in the U87 and U251 cell lines. Immunohistochemistry and immunofluorescence stain indicated that over-expressed NFAT1 was mainly located in the nucleus, where it acted as a transcription factor. After treatment with the NFAT antagonist cyclosporin A (CsA) and FK506, levels of NFAT1 in the nuclei of U87 GBM cells were dramatically reduced. The invasive potential of U87 cells was reduced by the same treatment, as well as by inhibition of NFAT1 expression using small hairpin RNA. Proliferation of U87 cells was unaffected by CsA, FK506 and NFAT1 shRNA transfection. Clustering analysis and Pearson correlation analysis of microarray data showed that the expression of NFAT1 correlated with the expression of the invasion-related genes cyclooxygenase-2 (COX-2), matrix metalloproteinase-7 (MMP-7) and MMP-9, a result confirmed by in vitro analysis. These findings demonstrate that NFAT1 contributes to the invasive potential but not the proliferation of GBM cells, and suggest that CsA may find application as an adjuvant in combined treatment strategies for GBM

TERT promoter mutations lead to high transcriptional activity under hypoxia and temozolomide treatment and predict poor prognosis in gliomas.

This study explored the effects of telomerase reverse transcriptase (TERT) promoter mutations on transcriptional activity of the TERT gene under hypoxic and temozolomide (TMZ) treatment conditions, and investigated the status and prognostic value of these mutations in gliomas.The effect of TERT promoter mutations on the transcriptional activity of the TERT gene under hypoxic and TMZ treatment conditions was investigated in glioma cells using the luciferase assay. TERT promoter mutations were detected in 101 glioma samples (grades I-IV) and 49 other brain tumors by sequencing. TERT mRNA expression in gliomas was examined by real-time PCR. Hazard ratios from survival analysis of glioma patients were determined relative to the presence of TERT promoter mutations.Mutations in the TERT promoter enhanced gene transcription even under hypoxic and TMZ treatment conditions, inducing upregulation of TERT mRNA expression. Mutations were detected in gliomas, but not in meningiomas, pituitary adenomas, cavernomas, intracranial metastases, normal brain tissues, or peripheral blood of glioma patients. Patients with TERT promoter mutations had lower survival rates, even after adjusting for other known or potential risk factors, and the incidence of mutation was correlated with patient age.TERT promoter mutations were specific to gliomas. TERT promoter mutations maintained its ability of inducing high transcriptional activity even under hypoxic and TMZ treatment conditions, and the presence of mutations was associated with poor prognosis in glioma patients. These findings demonstrate that TERT promoter mutations are novel prognostic markers for gliomas that can inform prospective therapeutic strategies

Real-Time Detection of Ground Objects Based on Unmanned Aerial Vehicle Remote Sensing with Deep Learning: Application in Excavator Detection for Pipeline Safety

Unmanned aerial vehicle (UAV) remote sensing and deep learning provide a practical approach to object detection. However, most of the current approaches for processing UAV remote-sensing data cannot carry out object detection in real time for emergencies, such as firefighting. This study proposes a new approach for integrating UAV remote sensing and deep learning for the real-time detection of ground objects. Excavators, which usually threaten pipeline safety, are selected as the target object. A widely used deep-learning algorithm, namely You Only Look Once V3, is first used to train the excavator detection model on a workstation and then deployed on an embedded board that is carried by a UAV. The recall rate of the trained excavator detection model is 99.4%, demonstrating that the trained model has a very high accuracy. Then, the UAV for an excavator detection system (UAV-ED) is further constructed for operational application. UAV-ED is composed of a UAV Control Module, a UAV Module, and a Warning Module. A UAV experiment with different scenarios was conducted to evaluate the performance of the UAV-ED. The whole process from the UAV observation of an excavator to the Warning Module (350 km away from the testing area) receiving the detection results only lasted about 1.15 s. Thus, the UAV-ED system has good performance and would benefit the management of pipeline safety.ISSN:2072-429

Fast Tailings Pond Mapping Exploiting Large Scene Remote Sensing Images by Coupling Scene Classification and Sematic Segmentation Models

In the process of extracting tailings ponds from large scene remote sensing images, semantic segmentation models usually perform calculations on all small-size remote sensing images segmented by the sliding window method. However, some of these small-size remote sensing images do not have tailings ponds, and their calculations not only affect the model accuracy, but also affect the model speed. For this problem, we proposed a fast tailings pond extraction method (Scene-Classification-Sematic-Segmentation, SC-SS) that couples scene classification and semantic segmentation models. The method can map tailings ponds rapidly and accurately in large scene remote sensing images. There were two parts in the method: a scene classification model, and a semantic segmentation model. Among them, the scene classification model adopted the lightweight network MobileNetv2. With the help of this network, the scenes containing tailings ponds can be quickly screened out from the large scene remote sensing images, and the interference of scenes without tailings ponds can be reduced. The semantic segmentation model used the U-Net model to finely segment objects from the tailings pond scenes. In addition, the encoder of the U-Net model was replaced by the VGG16 network with stronger feature extraction ability, which improves the model’s accuracy. In this paper, the Google Earth images of Luanping County were used to create the tailings pond scene classification dataset and tailings pond semantic segmentation dataset, and based on these datasets, the training and testing of models were completed. According to the experimental results, the extraction accuracy (Intersection Over Union, IOU) of the SC-SS model was 93.48%. The extraction accuracy of IOU was 15.12% higher than the U-Net model, while the extraction time was shortened by 35.72%. This research is of great importance to the remote sensing dynamic observation of tailings ponds on a large scale