Pine bark and sponge compounds could counter drug-resistant malaria and babesiosis
As parasites become increasingly resistant to existing drugs, researchers at the University of California, Riverside, are working to develop a new generation of treatments for two.
Key points
- Focus: As parasites become increasingly resistant to existing drugs, researchers at the University of California, Riverside, are working to develop a new
- Detail: Science reporting: verify primary technical documentation
- Editorial reading: science reporting; whenever possible, verify the cited primary source.
As parasites become increasingly resistant to existing drugs, researchers at the University of California, Riverside, are working to develop a new generation of treatments for two serious infectious diseases: malaria and babesiosis. The science-journalism coverage adds useful context, while the strongest evidential footing still comes from the underlying data, papers or institutional documentation.
It matters because Earth science becomes stronger when local observations can be placed inside a broader physical pattern that spans time and geography. The planet operates as a coupled system in which atmospheric, oceanic, cryospheric and solid-Earth processes interact across timescales from days to millions of years. A measurement that captures one variable at one location and one moment has limited interpretive value until it is embedded in the longer series and wider spatial coverage that allow natural variability to be separated from forced change. This article has been reviewed according to Science X's editorial process and policies. The National Institute of Allergy and Infectious Diseases, part of the National Institutes of Health, has awarded two collaborative grants totaling more than $8 million to.
UC Riverside will receive more than $2.5 million through the awards. The second investigates pyrroloiminoquinones (PIQs), a family of compounds originally isolated from marine sponges.
Although the compounds come from different natural sources, both have shown potent activity against malaria and babesiosis parasites, including drug-resistant strains. Understanding their mechanisms of action will help the team refine the compounds and determine whether they target biological pathways that differ from those affected by today's.
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The broader interest lies in linking the observation to climatic, geophysical or environmental dynamics that extend well beyond the immediate event or location. Earth science is unusual in that its most important questions operate on timescales that no single research career can observe directly, making the archival record, whether in ice, sediment, rock or satellite data, as important as any new measurement. Results that can be embedded in that record, and that either confirm or challenge the patterns it reveals, carry disproportionate scientific weight.
The second, "Optimization of the Pyrroloiminoquinone Scaffold for Malaria and Babesiosis Treatment," provides $3.94 million, including $1.34 million for UC Riverside. We definitely need new treatments against these devastating diseases. " PhD nano-engineering from Delft University.
Because this item comes through Phys. org Biology as science journalism, it should be treated as contextual reporting rather than primary evidence. Good science reporting can identify why a result matters, connect it to the wider literature and make technical work readable, but the decisive evidence remains in the original paper, dataset, mission release or technical record. That distinction is especially important when a story is later repeated by aggregators, because repetition increases visibility, not evidential strength.
The next step is to place the result inside longer time series and to compare it with independent instruments and independent sites. Earth system observations gain most of their interpretive power from network density and temporal depth, not from any single measurement however precise. Model simulations that assimilate the new data will help clarify whether the observation fits comfortably within known natural variability or represents a shift that existing models do not reproduce.
Original source: Phys. org Biology