A large-scale analysis of U.S. water quality data reveals that most toxic chemicals remain poorly characterized or undetected in routine monitoring. This is largely due to sparse risk assessment data, as well as detection limits that are too high to capture ecologically relevant concentrations, researchers report. The findings suggest that the true scale of chemical risk to biodiversity and ecosystems may be significantly underestimated. Chemical pollution is widely recognized as a major threat to biodiversity, human health, and the stability of ecosystems worldwide. However, the accelerating rate at which new chemicals are introduced into the environment outpaces the current ability to fully assess their ecological risks. Large-scale risk assessments depend on both knowing where chemicals are present and understanding how harmful they are to living organisms, yet for most substances, such data are lacking. While new computational and lab-based approaches can estimate toxicity, they are still constrained by limitations in environmental monitoring, especially when extremely toxic substances are present in concentrations too low to be reliably detected.

 

To better understand how gaps in monitoring data affect risk assessments, Sascha Bub and colleagues analyzed 112 million chemical monitoring records for nearly 2,000 substances in U.S. surface waters spanning 62 years, alongside 78 million records of environmental conditions. Bub et al. compared these data with established toxicity thresholds for over 170,000 chemicals, derived from laboratory and computation studies, that indicate concentrations likely to cause ecological harm. According to the findings, large-scale assessments of chemical risks in U.S. surface waters are primarily constrained by the lack of monitoring data. While regulatory toxicity thresholds are available for over 170,000 chemicals and span a wide range of potencies, only a small fraction of these substances – less than 1% – have corresponding environmental monitoring records. What’s more, routine water monitoring programs are often unable to detect many chemicals, including highly toxic and widespread agricultural pesticides, because the detection thresholds are set too high relative to the concentrations known to be ecologically damaging. These shortcomings suggest that a large portion of chemical risks may remain hidden, especially for substances that are highly potent at low doses.

Researchers present a new method to safely and preferentially generate CAR T cells directly inside the body using targeted lipid nanoparticles that deliver mRNA directly to T cells. The approach showed rapid and sustained immune reprogramming in preclinical models, highlighting its promise for treating cancer and autoimmune diseases. Adoptive immunotherapy, which harnesses a patient’s own immune cells to treat disease, holds immense therapeutic potential. Among its most prominent forms is CAR T cell therapy, in which T cells are genetically engineered to recognize and attack tumor cells. However, because CAR T cells are generated outside the body, these therapies are complex, costly, and dependent on specialized medical infrastructure. To overcome the hurdles of traditional CAR T cell therapies, Theresa Hunter and colleagues developed a new strategy for generating CAR T cells directly inside the body using targeted lipid nanoparticles (tLNPs) that carry a desired mRNA cargo. The use of mRNA in this approach should avoid the risk of permanent genetic alteration because, unlike DNA-based methods, mRNA does not integrate into the T cell genome.

 

A major obstacle in delivering mRNA with lipid nanoparticles (LNPs), however, is their tendency to be absorbed by the liver’s reticuloendothelial system, which filters out foreign particles from the bloodstream. To address this, Hunter et al. designed a specialized ionizable lipid (L829) and used it to create LNPs targeted to CD5, a protein found on T cells. When tested in mice, rats, and cynomolgus monkeys, these CD5-L829-tLNPs showed reduced liver uptake and more precise delivery to T cells, demonstrating improved targeting and biodistribution. To evaluate the efficacy of the system, the authors used blood samples from humans with autoimmune disease and showed that patient-derived T cells could be engineered with similar efficiency to those from healthy donors and that they could successfully eliminate the patients’ B cells. In mouse models engrafted with human immune cells, a single dose of the tLNPs led to rapid, targeted B cell depletion within hours, with effects lasting up to two weeks. In a leukemia xenograft experimental model, repeated dosing of the tLNPs produced near-complete tumor clearance, underscoring the potential of this in vivo approach for treating both cancer and autoimmune conditions.

Researchers at Washington University in St. Louis are using machine learning to better predict who will experience persistent pain after surgery.

On March 28, 2025, a devastating 7.7 magnitude earthquake struck Myanmar, causing an estimated 3,600-5,350 fatalities and leaving around 200,000 people homeless. A rapid damage assessment by the United Nations University Institute for Water, Environment and Health (UNU-INWEH) utilized satellite radar data to analyze seven major cities, including Mandalay. The analysis estimated that over 157,000 buildings were likely damaged, with damage rates in the assessed cities ranging from 20% to 73%. The catastrophic losses are attributed to the widespread collapse of vulnerable structures, exacerbated by failures to enforce the Myanmar National Building Code. The report advocates for comprehensive mitigation strategies, including the adoption and enforcement of modern seismic codes, retrofitting existing buildings, and improved land-use planning to enhance resilience against future seismic events.