Chinese researchers unlock nanorod spacing control for more efficient solar cells
A team led by Prof. Mingtai Wang at the Hefei Institutes of Physical Science has developed a breakthrough method to control the spacing of titanium di...
Israeli researchers have unveiled an artificial intelligence tool that can determine a person’s true biological age from tiny DNA samples with remarkable precision.
Israeli scientists from the Hebrew University of Jerusalem have created a groundbreaking AI-based tool capable of accurately predicting a person’s biological age from minimal DNA traces. The research, published in Cell Reports, could revolutionise medicine, forensics, and ageing research.
The tool, named "MAgeNet", uses a deep learning model to assess molecular ageing by analysing specific chemical changes in DNA known as methylation. Remarkably, the tool relies on just two DNA regions to deliver its prediction, achieving a median error of only 1.36 years in individuals under 50.
Unlike many existing age estimation techniques, MAgeNet’s accuracy remains consistent regardless of a person's smoking habits, weight, or gender, the university said in a statement.
According to the researchers, the innovation could be used in clinical settings to tailor treatments according to a patient’s biological age rather than their chronological age. This approach may better reflect the body’s actual condition and potential response to therapies.
In addition to medical applications, the tool holds promise in forensic science, allowing investigators to estimate the age of individuals from minute DNA traces left at crime scenes.
The research team believes MAgeNet could also help deepen scientific understanding of how humans age at the molecular level, potentially opening new paths for studying age-related diseases and longevity.
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A team led by Prof. Mingtai Wang at the Hefei Institutes of Physical Science has developed a breakthrough method to control the spacing of titanium dioxide nanorods without changing their size, significantly improving solar cell efficiency.
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