A recent study introduces an innovative method for analyzing body composition using advanced 3D imaging and deep learning techniques. This approach aims to provide more accurate assessments of body fat and muscle distribution, which are crucial for understanding health risks associated with various conditions.

The study, “3D Convolutional Deep Learning for Nonlinear Estimation of Body Composition from Whole Body Morphology,” authored by researchers from Pennington Biomedical Research Center, University of Washington, University of Hawaii and University of California-San Francisco was recently published in NPJ Digital Medicine, a journal of the Nature portfolio.

Key Highlights of the study include:

Advanced Imaging: The researchers utilized 3D imaging technology to capture detailed representations of the body's shape.

Deep Learning Application: By applying sophisticated deep learning algorithms, the study achieved more precise estimations of body composition compared to traditional methods.

Health Implications: Accurate body composition analysis is essential for assessing health risks related to obesity, cardiovascular diseases, and other metabolic disorders.

Low-density lipoproteins (LDL) — commonly known as bad cholesterol — have long been on scientists’ radar as a major contributor to heart disease. But these microscopic troublemakers have hidden their inner workings behind a maze of complexity. That is, until now.

In a new study published in Nature, University of Missouri researchers have, for the first time, revealed the specific shape and structure of one of the body’s most important yet complicated proteins: ApoB100. Acting as a kind of molecular exoskeleton, this protein wraps around LDL particles, allowing them to travel through the bloodstream, researchers found.

Research has revealed clear evidence that changes in the orchestration of brain oxygenation dynamics and neuronal function in Alzheimer’s disease contribute to the neurodegeneration.

The study “Neurovascular phase coherence is altered in Alzheimer’s Disease” is published in Brain Communications. Researchers found that the median respiration rate was approximately 13 breaths per minute for the control group, and approximately 17 breaths per minute for the Alzheimer’s group.

Prof Stefanovska said: This is a revolutionary discovery that may open a whole new world in the study of the Alzheimer's disease. It most likely reflects an inflammation, maybe in the brain, that once detected can probably be treated and severe states of Alzheimer's might be prevented in the future.”