24 research outputs found
Dihydrophenazine:a multifunctional new weapon that kills multidrug-resistant Acinetobacter baumannii and restores carbapenem and oxidative stress susceptibilities
AimsThe current work aims to fully characterize a new antimicrobial agent against Acinetobacter baumannii, which continues to represent a growing threat to healthcare settings worldwide. With minimal treatment options due to the extensive spread of resistance to almost all the available antimicrobials, the hunt for new antimicrobial agents is a high priority. Methods and resultsAn Egyptian soil-derived bacterium strain NHM-077B proved to be a promising source for a new antimicrobial agent. Bioguided fractionation of the culture supernatants of NHM-077B followed by chemical structure elucidation identified the active antimicrobial agent as 1-hydroxy phenazine. Chemical synthesis yielded more derivatives, including dihydrophenazine (DHP), which proved to be the most potent against A. baumannii, yet it exhibited a safe cytotoxicity profile against human skin fibroblasts. Proteomics analysis of the cells treated with DHP revealed multiple proteins with altered expression that could be correlated to the observed phenotypes and potential mechanism of the antimicrobial action of DHP. DHP is a multi-pronged agent that affects membrane integrity, increases susceptibility to oxidative stress, interferes with amino acids/protein synthesis, and modulates virulence-related proteins. Interestingly, DHP in sub-inhibitory concentrations resensitizes the highly virulent carbapenem-resistant A. baumannii strain AB5075 to carbapenems providing great hope in regaining some of the benefits of this important class of antibiotics. ConclusionsThis work underscores the potential of DHP as a promising new agent with multifunctional roles as both a classical and non-conventional antimicrobial agent that is urgently needed.<br/
Linkages between GRACE water storage, hydrologic extremes, and climate teleconnections in major African aquifers
Water resources management is a critical issue in Africa where many regions are subjected to sequential droughts and floods. The objective of our work was to assess spatiotemporal variability in water storage and related controls (climate, human intervention) in major African aquifers and consider approaches toward more sustainable development. Different approaches were used to track water storage, including GRACE/GRACE Follow On satellites for Total Water Storage (TWS); satellite altimetry for reservoir storage, MODIS satellites for vegetation indices, and limited ground-based monitoring. Results show that declining trends in TWS (60â73 km3 over the 18 yr GRACE record) were restricted to aquifers in northern Africa, controlled primarily by irrigation water use in the Nubian and NW Saharan aquifers. Rising TWS trends were found in aquifers in western Africa (23â49 km3), attributed to increased recharge from land use change and cropland expansion. Interannual variability dominated TWS variability in eastern and southern Africa, controlled primarily by climate extremes. Climate teleconnections, particularly El Nino Southern Oscillation and Indian Ocean Dipole, strongly controlled droughts and floods in eastern and southern Africa. Huge aquifer storage in northern Africa suggests that the recent decadal storage declines should not impact the regional aquifers but may affect local conditions. Increasing groundwater levels in western Africa will need to be managed because of locally rising groundwater flooding. More climate resilient water management can be accomplished in eastern and southern Africa by storing water from wet to dry climate cycles. Accessing the natural water storage provided by aquifers in Africa is the obvious way to manage the variability between droughts and floods
Comparative study of the chemical composition and anti-proliferative activities of the aerial parts and roots of Apium graveolens L. (celery) and their biogenic nanoparticles
Apiaceae plants are multipurpose folk remedies and bioactive foods that show a remarkable ability to biosynthesize a large number of secondary metabolites with antitumor and chemopreventive potential. Among the various members of the Apiaceae, celery (Apium graveolens L.) has long been used as a popular edible and medicinal plant owing to its plentiful health benefits and nutraceutical properties; however, the anticancer potential of this important species has been seldom studied, mostly focusing on its seeds. Therefore, this work was designed to delve into the chemical composition and anti-proliferative potential of the total ethanolic extracts of the aerial parts (TEEAGA) and roots (TEEAGR) of A. graveolens var. dulce (Mill.) Pers. as well as their green synthesized silver nanoparticles (AgNPs). In general, both TEEAGA and TEEAGR exhibited moderate to potent inhibitory activities against human liver (HepG-2), colon (Caco-2), and breast (MCF-7) cancer cell lines, with interesting IC50 profiles [(41.37 ± 0.12, 27.65 ± 0.27, and 9.48 ± 0.04 ÎŒg/mL) and (11.58 ± 0.02, 7.13 ± 0.03, and 6.58 ± 0.02 ÎŒg/mL), respectively] as compared with doxorubicin, while more pronounced anti-proliferative effects were observed for their biogenic AgNPs, which showed IC50 values ranging between 25.41 ± 0.16 and 1.37 ± 0.03 ÎŒg/mL. Moreover, HPLCâHESIâHRMS-based metabolomics analysis of both extracts showed the presence of a varied group of secondary metabolites, including flavonoids, phenylpropanoids, phthalides, coumarins, and sesquiterpenes that further displayed moderate to promising binding affinities to the active site of cyclin G-associated kinase (GAK), particularly graveobioside A, graveobioside B, and celeroside C, suggesting their possible contribution as GAK modulators to the anti-proliferative potential of celery. These findings can help broaden future research on the utilization of different parts of celery and their NPs as functional foods and medicines in cancer chemoprevention and therapy
Rapid mapping of global flood precursors and impacts using novel five-day GRACE solutions
Abstract Floods affect communities and ecosystems worldwide, emphasizing the importance of identifying their precursors and enhancing resilience to these events. Here, we calculated Antecedent Total Water Storage (ATWS) anomalies from the new 5-day (5D) Gravity Recovery and Climate Experiment (GRACE) and its Follow-On (GRACE-FO) satellite solutions to enhance the detection of pre-flood and active flood conditions and to map post-flood storage anomalies. The GRACE data were compared withâ~â3300 flood events reported by the Dartmouth Flood Observatory (2002â2021), revealing distinct ATWS precursor signals in 5D solutions, in contrast to the monthly solutions. Specifically, floods caused by saturation-excess runoffâtriggered by persistent rainfall, monsoonal patterns, snowmelt, or rain-on-snow eventsâshow detectable ATWS increases 15 to 50 days before and during floods, providing a valuable opportunity to improve flood monitoring. These 5D solutions also facilitate a more rapid mapping of post-flood storage changes to assess flood recovery from tropical cyclones and sub-monthly weather extremes. Our findings show the promising potential of 5D GRACE solutions, which are still in the development phase, for future integration into operational frameworks to enhance flood detection and recovery, facilitating the rapid analysis of storage changes relative to monthly solutions
Reconstruction of GRACE Mass Change Time Series Using a Bayesian Framework
Abstract Gravity Recovery and Climate Experiment and its Follow On (GRACE (âFO)) missions have resulted in a paradigm shift in understanding the temporal changes in the Earth's gravity field and its drivers. To provide continuous observations to the user community, missing monthly solutions within and between GRACE (âFO) missions (33 solutions) need to be imputed. Here, we modeled GRACE (âFO) data (196 solutions) between 04/2002â04/2021 to infer missing solutions and derive uncertainties in the existing and missing observations using Bayesian inference. First, we parametrized the GRACE (âFO) time series using an additive generative model comprising longâterm variability (secular trend + interannual to decadal variations), annual, and semiâannual cycles. Informative priors for each component were used and Markov Chain Monte Carlo (MCMC) was applied to generate 2,000 samples for each component to quantify the posterior distributions. Second, we reconstructed the new data (229 solutions) by joining medians of posterior distributions of all components and adding back the residuals to secure the variability of the original data. Results show that the reconstructed solutions explain 99% of the variability of the original data at the basin scale and 78% at the oneâdegree grid scale. The results outperform other reconstructed data in terms of accuracy relative to land surface modeling. Our dataâdriven approach relies only on GRACE (âFO) observations and provides a total uncertainty over GRACE (âFO) data from the dataâgeneration process perspective. Moreover, the predictive posterior distribution can be potentially used for ânowcastingâ in GRACE (âFO) nearârealâtime applications (e.g., data assimilations), which minimize the current mission data latency (40â60 days)
System Dynamics Modeling in Local Water Management: Assessing Strategies for the City of Boerne, Texas
As more pressure is exerted onto water sources, hydrologic systems may be altered in ways that are difficult to predict. In Texas, water deficits can become widespread as sources are strained beyond capacity. For smaller communities, such as Boerne, Texas, water management and planning is a way to prepare. The supply-demand water balance in Boerne is conceptualized through causal loop diagrams and system dynamics modeling. Through stakeholder engagement, xeriscaping, rainwater harvesting, and smart meters were chosen as interventions, each varied in adoption levels. The resulting 125 combinations were analyzed under three scenarios: a base case assuming maximum supply of water is firm, and two responses to a meteorological drought. Results show that the city can effectively forestall a deficit. Different combinations of adoptions can achieve the same goal, giving the city optionality in choosing strategies that are best suited for its needs and constraints. Rainwater harvesting was found to be the dominant intervention influencing demand, but its influence is reduced in the two drought scenarios. Xeriscaping was the second most influential intervention and smart meters for irrigation had no effect on demand. The approach used in this study highlights the interdependency between community adoption of conservation strategies and the importance of considering these relationships using systems modeling
System Dynamics Modeling in Local Water Management: Assessing Strategies for the City of Boerne, Texas
As more pressure is exerted onto water sources, hydrologic systems may be altered in ways that are difficult to predict. In Texas, water deficits can become widespread as sources are strained beyond capacity. For smaller communities, such as Boerne, Texas, water management and planning is a way to prepare. The supply-demand water balance in Boerne is conceptualized through causal loop diagrams and system dynamics modeling. Through stakeholder engagement, xeriscaping, rainwater harvesting, and smart meters were chosen as interventions, each varied in adoption levels. The resulting 125 combinations were analyzed under three scenarios: a base case assuming maximum supply of water is firm, and two responses to a meteorological drought. Results show that the city can effectively forestall a deficit. Different combinations of adoptions can achieve the same goal, giving the city optionality in choosing strategies that are best suited for its needs and constraints. Rainwater harvesting was found to be the dominant intervention influencing demand, but its influence is reduced in the two drought scenarios. Xeriscaping was the second most influential intervention and smart meters for irrigation had no effect on demand. The approach used in this study highlights the interdependency between community adoption of conservation strategies and the importance of considering these relationships using systems modeling
Exploring groundwater and soil water storage changes across the CONUS at 12.5 km resolution by a Bayesian integration of GRACE data into W3RA
Exploring groundwater and soil water storage changes across the CONUS at 12.5 km resolution by a Bayesian integration of GRACE data into W3RA
Climate variability and change along with anthropogenic water use have affected the (re)distribution of water storage and fluxes across the Contiguous United States (CONUS). Available hydrological models, however, do not represent recent changes in the water cycle. Therefore, in this study, a novel Bayesian Markov Chain Monte Carlo-based Data Assimilation (MCMC-DA) approach is formulated to integrate Terrestrial Water Storage changes (TWSC) from the Gravity Recovery and Climate Experiment (GRACE) satellite mission into the W3RA water balance model. The benefit of this integration is its dynamic solution that uses GRACE TWSC to update W3RA's individual water storage estimates while rigorously accounting for uncertainties. It also down-scales GRACE data and provides groundwater and soil water storage changes at ~12.5 km resolution across the CONUS covering 2003â2017. Independent validations are performed against in-situ groundwater data (from USGS) and Climate Change Initiative (CCI) soil moisture products from the European Space Agency (ESA). Our results indicate that MCMC-DA introduces trends, which exist in GRACE TWSC, mostly to the groundwater storage and to a lesser extent to the soil water storage. Higher similarity is found between groundwater estimation of MCMC-DA and those of USGS in the southeastern CONUS. We also show a stronger linear trend in MCMC-DA soil water storage across the CONUS, compared to W3RA (changing from ±0.5 mm/yr to ±2 mm/yr), which is closer to independent estimates from the ESA CCI. MCMC-DA also improves the estimation of soil water storage in regions with high forest intensity, where ESA CCI and hydrological models have difficulties in capturing the soil-vegetation-atmosphere continuum. The representation of El Niño Southern Oscillation (ENSO)-related variability in groundwater and soil water storage are found to be considerably improved after integrating GRACE TWSC with W3RA. This new hybrid approach shows promise for understanding the links between climate and the water balance over broad regions