Protective effects of catalpol on cardio-cerebrovascular diseases: A comprehensive review

Catalpol, an iridoid glucoside isolated from Rehmannia glutinosa, has gained attention due to its potential use in treating cardio-cerebrovascular diseases (CVDs). This extensive review delves into recent studies on catalpol's protective properties in relation to various CVDs, such as atherosclerosis, myocardial ischemia, infarction, cardiac hypertrophy, and heart failure. The review also explores the compound's anti-oxidant, anti-inflammatory, and anti-apoptotic characteristics, emphasizing the role of vital signaling pathways, including PGC-1α/TERT, PI3K/Akt, AMPK, Nrf2/HO-1, estrogen receptor (ER), Nox4/NF-κB, and GRP78/PERK. The article discusses emerging findings on catalpol's ability to alleviate diabetic cardiovascular complications, thrombosis, and other cardiovascular-related conditions. Although clinical studies specifically addressing catalpol's impact on CVDs are scarce, the compound's established safety and well-tolerated nature suggest that it could be a valuable treatment alternative for CVD patients. Further investigation into catalpol and related iridoid derivatives may unveil new opportunities for devising natural and efficacious CVD therapies

Stability Evaluation on Surrounding Rocks of Underground Powerhouse Based on Microseismic Monitoring

To study the stability of underground powerhouse at Houziyan hydropower station during excavation, a microseismic monitoring system is adopted. Based on the space-time distribution characteristics of microseismic events during excavation of the main powerhouse, the correlation between microseismic events and blasting construction is established; and the microseismic clustering areas of the underground powerhouse are identified and delineated. The FLAC3D code is used to simulate the deformation of main powerhouse. The simulated deformation characteristics are consistent with that recorded by microseismic monitoring. Finally, the correlation between the macroscopic deformation of surrounding rock mass and microseismic activities is also revealed. The results show that multiple faults between 1# and 3# bus tunnels are activated during excavation of floors V and VI of the main powerhouse. The comprehensive method combining microseismic monitoring with numerical simulation as well as routine monitoring can provide an effective way to evaluate the surrounding rock mass stability of underground caverns

Ginsenoside Rc: A potential intervention agent for metabolic syndrome

Ginsenoside Rc, a dammarane-type tetracyclic triterpenoid saponin primarily derived from Panax ginseng, has garnered significant attention due to its diverse pharmacological properties. This review outlined the sources, putative biosynthetic pathways, extraction, and quantification techniques, as well as the pharmacokinetic properties of ginsenoside Rc. Furthermore, this study explored the pharmacological effects of ginsenoside Rc against metabolic syndrome (MetS) across various phenotypes including obesity, diabetes, atherosclerosis, non-alcoholic fatty liver disease, and osteoarthritis. It also highlighted the impact of ginsenoside Rc on multiple associated signaling molecules. In conclusion, the anti-MetS effect of ginsenoside Rc is characterized by its influence on multiple organs, multiple targets, and multiple ways. Although clinical investigations regarding the effects of ginsenoside Rc on MetS are limited, its proven safety and tolerability suggest its potential as an effective treatment option

Probability Prediction Approach of Fatigue Failure for the Subsea Wellhead Using Bayesian Regularization Artificial Neural Network

The subsea wellhead (SW) system is a crucial connection between blowout preventors (BOPs) and subsea oil and gas wells. Excited by cyclical fatigue dynamic loadings, the SW is prone to fatigue failure, which would lead to the loss of well integrity and catastrophic accidents. Based on the Bayesian Regularization Artificial Neuron Network (BRANN), this paper proposes an efficient probability approach to predict the fatigue failure probability of SW during its entire life. In the proposed method, the BRANN fatigue damage (BRANN-FD) model reflecting the non-linear relationship between the input and output data was developed by the limited fatigue damage analysis data, which was utilized to generate thousands of non-numerical fatigue damage data of SW rapidly. Combining parametric and non-parametric estimation methods, the probability density function (PDF) of SW fatigue damage was determined to calculate the accumulation fatigue damage during service life. Using the logistic regression, the fatigue failure probability of SW was predicted. The application of the proposed approach was demonstrated by a case study. The results illustrated that the fatigue damage of SW would be viewed as obeying the Lognormal distribution, which could be used to obtain the accumulation fatigue damage in operation conveniently. Furthermore, the fatigue failure probability of SW nonlinearly increased with the increment in the accumulation fatigue damage of SW, which could be helpful to ensure the operation safety of SW in deepwater oil and gas development, especially for aged wellhead

Probability Prediction Approach of Fatigue Failure for the Subsea Wellhead Using Bayesian Regularization Artificial Neural Network

The subsea wellhead (SW) system is a crucial connection between blowout preventors (BOPs) and subsea oil and gas wells. Excited by cyclical fatigue dynamic loadings, the SW is prone to fatigue failure, which would lead to the loss of well integrity and catastrophic accidents. Based on the Bayesian Regularization Artificial Neuron Network (BRANN), this paper proposes an efficient probability approach to predict the fatigue failure probability of SW during its entire life. In the proposed method, the BRANN fatigue damage (BRANN-FD) model reflecting the non-linear relationship between the input and output data was developed by the limited fatigue damage analysis data, which was utilized to generate thousands of non-numerical fatigue damage data of SW rapidly. Combining parametric and non-parametric estimation methods, the probability density function (PDF) of SW fatigue damage was determined to calculate the accumulation fatigue damage during service life. Using the logistic regression, the fatigue failure probability of SW was predicted. The application of the proposed approach was demonstrated by a case study. The results illustrated that the fatigue damage of SW would be viewed as obeying the Lognormal distribution, which could be used to obtain the accumulation fatigue damage in operation conveniently. Furthermore, the fatigue failure probability of SW nonlinearly increased with the increment in the accumulation fatigue damage of SW, which could be helpful to ensure the operation safety of SW in deepwater oil and gas development, especially for aged wellhead

Activating the PGC-1α/TERT Pathway by Catalpol Ameliorates Atherosclerosis via Modulating ROS Production, DNA Damage, and Telomere Function: Implications on Mitochondria and Telomere Link

Catalpol, an iridoid glucoside, has been found present in large quantities in the root of Rehmannia glutinosa L. and showed a strong antioxidant capacity in the previous study. In the present work, the protective effect of catalpol against AS via inhibiting oxidative stress, DNA damage, and telomere shortening was found in LDLr−/− mice. This study also shows that activation of the peroxisome proliferator-activated receptor-γ coactivator-1α (PGC-1α)/telomerase reverse transcriptase (TERT) pathway, which is the new link between mitochondria and telomere, was involved in the protective effects of catalpol. Further, by using PGC-1α or TERT siRNA in oxLDL-treated macrophages, it is proved that catalpol reduced oxidative stress, telomere function, and related DNA damage at least partly through activating the PGC-1α/TERT pathway. Moreover, dual luciferase activity assay-validated catalpol directly enhanced PGC-1α promoter activity. In conclusion, our study revealed that the PGC-1α/TERT pathway might be a possible therapeutic target in AS and catalpol has highly favorable characteristics for the treatment of AS via modulating this pathway