The demonstration that carbon monoxide releasing molecules (CORMs) affect experimental systems by the release of carbon monoxide, and not via the interaction of the inactivated CORM, has been an accepted paradigm for decades. However, it has recently been documented that a radical intermediate formed during carbon monoxide release from ruthenium (Ru)-based CORM (CORM-2) interacts with histidine and can inactivate bee phospholipase A activity. Using a thrombelastographic based paradigm to assess procoagulant activity in human plasma, this study tested the hypothesis that a Ru-based radical and not carbon monoxide was responsible for CORM-2 mediated inhibition of , and species snake venoms. Assessment of the inhibitory effects of ruthenium chloride (RuCl) on snake venom activity was also determined. CORM-2 mediated inhibition of the three venoms was found to be independent of carbon monoxide release, as the presence of histidine-rich albumin abrogated CORM-2 inhibition. Exposure to RuCl had little effect on venom activity, but and venom had procoagulant activity significantly reduced. In conclusion, a Ru-based radical and ion inhibited procoagulant snake venoms, not carbon monoxide. These data continue to add to our mechanistic understanding of how Ru-based molecules can modulate hemotoxic venoms, and these results can serve as a rationale to focus on perhaps other, complementary compounds containing Ru as antivenom agents in vitro and, ultimately, in vivo.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7216138 | PMC |
http://dx.doi.org/10.3390/ijms21082970 | DOI Listing |
Acc Chem Res
January 2025
The Department of Chemistry, State University of New York at Binghamton, Binghamton, New York 13902, United States.
ConspectusIn the search for efficient and selective electrocatalysts capable of converting greenhouse gases to value-added products, enzymes found in naturally existing bacteria provide the basis for most approaches toward electrocatalyst design. Ni,Fe-carbon monoxide dehydrogenase (Ni,Fe-CODH) is one such enzyme, with a nickel-iron-sulfur cluster named the C-cluster, where CO binds and is converted to CO at high rates near the thermodynamic potential. In this Account, we divide the enzyme's catalytic contributions into three categories based on location and function.
View Article and Find Full Text PDFBackground: Several modifiable risk factors for dementia and related neurodegenerative diseases have been identified including education level, socio-economic status, and environmental exposures - however, how these population-level risks relate to individual risk remains elusive. To address this, we assess over 450 potential risk factors in one deeply clinically and demographically phenotyped cohort using random forest classifiers to determine predictive markers of poor cognitive function. This study aims to understand early risk factors for dementia by identifying predictors of poor cognitive performance amongst a comprehensive battery of imaging, blood, atmospheric pollutant and socio-economic measures.
View Article and Find Full Text PDFBackground: Household air pollution is a major contributor to cardiovascular disease burden in women in Sub-Saharan Africa. However, little is known about exposures during pregnancy or the effect of clean cooking interventions on postpartum blood pressure trajectories.
Methods: The Ghana Randomized Air Pollution and Health Study (GRAPHS) randomized 1414 non-smoking women in the first and second trimesters to liquefied petroleum gas (LPG) or improved biomass stoves - vs control (traditional three-stone open fire).
ACS Omega
January 2025
School of Information and Control Engineering, China University of Mining and Technology, Xuzhou 221116, China.
It is of great significance to realize the accurate prediction of the key output response of the chemical synthetic ammonia process for optimizing system performance and operation monitoring. Because many key intermediate variables of complex systems are difficult to measure comprehensively, there are great difficulties and errors in mechanism analysis and identification modeling techniques. Based on random forest (RF) variable selection, a deep neural network combining temporal convolutional network (TCN) and transformer is proposed to predict the output variables of the synthetic ammonia process.
View Article and Find Full Text PDFHeliyon
January 2025
Department of Mechanical Engineering, Addis Ababa Science and Technology University, Addis Ababa, 16417, Ethiopia.
Many approaches have been implemented in order to reduce the emissions of particular pollutants without compromising engine performance. Cotton and castor mixed seed oil was chosen for the current study due to their distinct fatty acid composition and potential as a feedstock for bio-additives. Three fuel samples-99 % diesel and 1 % blended fuel (cottonseed oil + castor seed oil), 99.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!