Akt Inhibition Enhanced the Growth Inhibition Effects of Low-Dose Heavy-Ion Radiation via the PI3K/Akt/p53 Signaling Pathway in C6 Glioblastoma Cells

BackgroundGlioma has one of the highest mortality rates of all tumors of the nervous system and commonly used treatments almost always fail to achieve tumor control. Low-dose carbon-ion radiation can effectively target cancer and tumor cells, but the mechanisms of growth inhibition induced by heavy-ion radiation via the PI3K/Akt signaling pathway are unknown, and inhibition by heavy-ion radiation is minor in C6 cells.MethodsCarbon-ion radiation was used to investigate the effects of heavy-ion radiation on C6 cells, and suppression of Akt was performed using perifosine. MTT assays were used to investigate optimal perifosine treatment concentrations. Clone formation assays were used to investigate the growth inhibition effects of carbon-ion radiation and the effects of radiation with Akt inhibition. Lactate dehydrogenase release, superoxide dismutase activity, and malondialdehyde content were assessed to investigate oxidative stress levels. Expression levels of proteins in the PI3K/Akt/p53 signaling pathway were assessed via western blotting.ResultsThe 10% maximum inhibitory concentration of perifosine was 19.95 μM. In clone formation assays there was no significant inhibition of cell growth after treatment with heavy-ion irradiation, whereas perifosine enhanced inhibition. Heavy-ion radiation induced lactate dehydrogenase release, increased the level of malondialdehyde, and reduced superoxide dismutase activity. Akt inhibition promoted these processes. Heavy-ion radiation treatment downregulated Akt expression, and upregulated B-cell lymphoma-2 (Bcl-2) expression. p53 and Bcl-2 expression were significantly upregulated, and Bcl-2-associated X protein (Bax) expression was downregulated. The expression profiles of pAkt, Bcl-2, and Bax were reversed by perifosine treatment. Caspase 3 expression was upregulated in all radiation groups.ConclusionsThe growth inhibition effects of low-dose heavy-ion irradiation were not substantial in C6 cells, and Akt inhibition induced by perifosine enhanced the growth inhibition effects via proliferation inhibition, apoptosis, and oxidative stress. Akt inhibition enhanced the effects of heavy-ion radiation, and the PI3K/Akt/p53 signaling pathway may be a critical component involved in the process

Anomaly Detection Based on Mining Six Local Data Features and BP Neural Network

Key performance indicators (KPIs) are time series with the format of (timestamp, value). The accuracy of KPIs anomaly detection is far beyond our initial expectations sometimes. The reasons include the unbalanced distribution between the normal data and the anomalies as well as the existence of many different types of the KPIs data curves. In this paper, we propose a new anomaly detection model based on mining six local data features as the input of back-propagation (BP) neural network. By means of vectorization description on a normalized dataset innovatively, the local geometric characteristics of one time series curve could be well described in a precise mathematical way. Differing from some traditional statistics data characteristics describing the entire variation situation of one sequence, the six mined local data features give a subtle insight of local dynamics by describing the local monotonicity, the local convexity/concavity, the local inflection property and peaks distribution of one KPI time series. In order to demonstrate the validity of the proposed model, we applied our method on 14 classical KPIs time series datasets. Numerical results show that the new given scheme achieves an average F1-score over 90%. Comparison results show that the proposed model detects the anomaly more precisely

A Novel Low-Cost GNSS Solution for the Real-Time Deformation Monitoring of Cable Saddle Pushing: A Case Study of Guojiatuo Suspension Bridge

Extreme loadings, a hostile environment and dangerous operation lead to the unsafe state of bridges under construction, especially large-span bridges. Global Navigation Satellite Systems (GNSS) tend to be the best choice for real-time deformation monitoring due to the significant advantage of automation, continuation, all-weather operation and high precision. Unfortunately, the traditional geodetic GNSS instrument with its high price and large volume is limited in its applications. Hence, we design and develop low-cost GNSS equipment by simplifying the monitoring module. The performance of the proposed solution is evaluated through an experimental dynamic scenario, proving its ability to track abrupt deformation down to 3–5 mm. We take Chongqing Guojiatuo Suspension Bridge in China as a case study. We build a real-time low-cost GNSS monitoring cloud platform. The low-cost bridge GNSS monitoring stations are located at the top of the south and north towers, midspan upstream and downstream respectively and the reference station is located in the stable zone 400 m away from the bridge management buildings. We conducted a detailed experimental assessment of low-cost GNSS on 5 April and a real-time deformation detection experiment of the towers and main cables during the dynamic cable saddle pushing process on 26 February 2022. In the static experiment, the standard deviation of the residual using the multi-GNSS solution is 2 mm in the horizontal direction and 5 mm in the vertical direction. The multi-GNSS solution significantly outperforms the BDS/GPS single system. The dynamic experiment shows that, compared with the movement measured by the robotic total station, the horizontal error of the south tower and north tower measured by low-cost GNSS is below 0.005 m and 0.008 m respectively. This study highlights the potential of low-cost GNSS solutions for Structural Health Monitoring (SHM) applications

A Novel Low-Cost GNSS Solution for the Real-Time Deformation Monitoring of Cable Saddle Pushing: A Case Study of Guojiatuo Suspension Bridge

Extreme loadings, a hostile environment and dangerous operation lead to the unsafe state of bridges under construction, especially large-span bridges. Global Navigation Satellite Systems (GNSS) tend to be the best choice for real-time deformation monitoring due to the significant advantage of automation, continuation, all-weather operation and high precision. Unfortunately, the traditional geodetic GNSS instrument with its high price and large volume is limited in its applications. Hence, we design and develop low-cost GNSS equipment by simplifying the monitoring module. The performance of the proposed solution is evaluated through an experimental dynamic scenario, proving its ability to track abrupt deformation down to 3–5 mm. We take Chongqing Guojiatuo Suspension Bridge in China as a case study. We build a real-time low-cost GNSS monitoring cloud platform. The low-cost bridge GNSS monitoring stations are located at the top of the south and north towers, midspan upstream and downstream respectively and the reference station is located in the stable zone 400 m away from the bridge management buildings. We conducted a detailed experimental assessment of low-cost GNSS on 5 April and a real-time deformation detection experiment of the towers and main cables during the dynamic cable saddle pushing process on 26 February 2022. In the static experiment, the standard deviation of the residual using the multi-GNSS solution is 2 mm in the horizontal direction and 5 mm in the vertical direction. The multi-GNSS solution significantly outperforms the BDS/GPS single system. The dynamic experiment shows that, compared with the movement measured by the robotic total station, the horizontal error of the south tower and north tower measured by low-cost GNSS is below 0.005 m and 0.008 m respectively. This study highlights the potential of low-cost GNSS solutions for Structural Health Monitoring (SHM) applications