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Category: biotech/medical – Page 118

Kindness emerges intuitively in young children before reflection catches up, study finds

While humans are inherently social beings, psychology studies suggest that their social skills are gradually fine-tuned over time and with experience. Understanding when different social skills emerge and how they typically develop could help devise new strategies that encourage people to behave prosocially and cooperate with others around them.

Researchers at London School of Economics, University of Stavanger and University of Milan-Bicocca recently carried out a study exploring how social behaviors emerge and become stable across childhood. Their findings, published in Nature Human Behavior, suggest that while kindness and cooperation are intuitive behaviors in early childhood, they later become deliberate and part of children’s personal disposition.

“Our study was initially motivated by the wish to extend findings of our previous paper in Scientific Reports,” Elena Nava, senior author of the paper, told Medical Xpress.

Genome tool places large genetic sequences precisely in rice and tobacco without DNA breaks

Researchers at King Abdullah University of Science and Technology (KAUST) have developed a new way to add large pieces of genetic information to plants, overcoming a challenge that has limited plant biotechnology for decades. The advance could help scientists build more complex traits into plants in the future, supporting research into areas such as crop resilience, sustainable agriculture, biotechnology and the use of plants as scalable platforms for producing therapeutics and biologics.

Published in Nature Biotechnology, the study introduces a new genome engineering approach that allows scientists to place large genes into specific locations within plant genomes. The approach was successfully demonstrated in both tobacco and rice, opening new possibilities for future research in agricultural biotechnology, synthetic biology and plant-based biomanufacturing.

Physics-based AI could boost biomedical imaging and autonomous vehicle sensors

A research team led by UCLA and the University of Rochester has demonstrated a promising evolution of an imaging system designed to capture details within “complex media,” which scatter light, from depicting structures inside body tissue to seeing obstacles through heavy fog. The system uses physics-based machine learning to improve an existing imaging technique.

In tests with standard calibration images obscured by complex media, the new system more than doubled the signal-to-noise ratio compared with a previous generation of the technology. The system also created images in near real time—thousandths of a second. The findings are published in the journal Light: Science & Applications.

How a pandemic detour helped researchers uncover clues to a mysterious disease

When the COVID-19 pandemic shut down international travel in 2020, Michigan State University researcher Eric Benbow faced a problem. A $2.5 million research project designed to study an environmental pathogen in South America was suddenly on hold. With fieldwork canceled and uncertainty surrounding when travel might resume, Benbow and his collaborators needed a new plan.

That unexpected detour led to a surprising discovery—and new insights into a disease that has puzzled scientists for decades.

In their study published in Communications Medicine, the international team of researchers examined the environmental and human factors that influence the distribution of Buruli ulcer, a neglected tropical disease caused by the bacterium Mycobacterium ulcerans. The work helps explain how ecosystems, climate, land use and human activities interact to shape disease risk.

New tool uncovers overlooked disease-linked genes by accounting for ancestry and family ties

Every person’s DNA tells a unique story. To unlock the full potential of genetic research, scientists need tools that reflect the complexity of the people they study.

Researchers at Baylor College of Medicine and Texas Children’s Duncan Neurological Research Institute (Duncan NRI) have developed a new computational method that enables scientists to more accurately identify genetic changes linked to disease by accounting for the ancestry and family relationships found in real-world populations.

Published in Nature Genetics, the new approach, called Tractor-Mix, addresses a longstanding challenge in genetic research. Many existing methods struggle to accurately analyze people whose DNA reflects ancestry from more than one ancestral population, as well as relatives participating in the same study. As a result, researchers often must simplify their data or exclude participants altogether.

Brain-penetrating nanoparticles, ultrasound and microbubbles show promise in treating glioblastoma

University of Virginia Comprehensive Cancer Center scientists have developed a promising new experimental approach to targeting glioblastoma, the most common and deadliest brain cancer. The approach could overcome many of the limitations of treatments using existing drugs.

UVA’s Roger Abounader, MD, Ph.D., and colleagues have identified “microRNAs” that can simultaneously suppress multiple malfunctioning genes responsible for glioblastoma’s formation and growth. The scientists use a combination of brain-penetrating nanoparticles, focused ultrasound waves and microbubbles to deliver the miRNAs through the brain’s natural protective barrier—a barrier that typically blocks treatments for tumors and neurodegenerative diseases. The study is published in the Journal of Clinical Investigation.

“This new approach could help target numerous molecules that promote cancer growth, including those for which no drugs exist, at the same time to achieve better therapies,” said Abounader, a professor at UVA’s School of Medicine, Department of Microbiology, Immunology and Cancer Biology, Comprehensive Cancer Center and Center for RNA Science and Medicine. “We are hoping to translate our findings into future clinical trials for patients with glioblastoma and other brain tumors.”