Summary: Neurons in the hippocampus vary in function depending on their exact genetic identity. The study revealed these neurons, once believed to be homogeneous, are quite diverse and encode task-related information differently based on their location. This newfound understanding of neuronal diversity could lead to better comprehension of brain functions, memory capacity, and potentially advance disease treatment strategies.
Key Facts:
Quantum biology explores how quantum effects influence biological processes, potentially leading to breakthroughs in medicine and biotechnology. Despite the assumption that quantum effects rapidly disappear in biological systems, research suggests these effects play a key role in physiological processes. This opens up the possibility of manipulating these processes to create non-invasive, remote-controlled therapeutic devices. However, achieving this requires a new, interdisciplinary approach to scientific research.
Imagine using your cell phone to control the activity of your own cells to treat injuries and diseases. It sounds like something from the imagination of an overly optimistic science fiction writer. But this may one day be a possibility through the emerging field of quantum biology.
Over the past few decades, scientists have made incredible progress in understanding and manipulating biological systems at increasingly small scales, from protein folding to genetic engineering. And yet, the extent to which quantum effects influence living systems remains barely understood.
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“We now understand that having one map of a single human genome cannot adequately represent all of humanity,” says Karen Miga, a professor at the University of California, Santa Cruz, and a participant in the new project.
People’s genomes are largely alike, but it’s the hundreds of thousands of differences, often just single DNA letters, that explain why each of us is unique. The new pangenome, researchers say, should make it possible to observe this diversity in more detail than ever before, highlighting so-called evolutionary hot spots as well as thousands of surprisingly large differences, like deleted, inverted, or duplicated genes, that aren’t observable in conventional studies.
Tactile stimulation improved motor performance, reduced phosphorylated tau, preserved neurons and synapses, and reduced DNA
DNA, or deoxyribonucleic acid, is a molecule composed of two long strands of nucleotides that coil around each other to form a double helix. It is the hereditary material in humans and almost all other organisms that carries genetic instructions for development, functioning, growth, and reproduction. Nearly every cell in a person’s body has the same DNA. Most DNA is located in the cell nucleus (where it is called nuclear DNA), but a small amount of DNA can also be found in the mitochondria (where it is called mitochondrial DNA or mtDNA).
Alzheimer’s disease (AD) is a complex neurodegenerative illness with genetic and environmental origins. Females experience faster cognitive decline and cerebral atrophy than males, while males have greater mortality rates. Using a new machine-learning method they developed called “Evolutionary Action Machine Learning (EAML),” researchers at Baylor College of Medicine and the Jan and Dan Duncan Neurological Research Institute (Duncan NRI) at Texas Children’s Hospital have discovered sex-specific genes and molecular pathways that contribute to the development and progression of this condition. The study was published in Nature Communications.
“We have developed a unique machine-learning software that uses an advanced computational predictive metric called the evolutionary action (EA) score as a feature to identify genetic factors that influence AD risk separately in males and females,” Dr. Olivier Lichtarge, MD, Ph.D., professor of biochemistry and molecular biology at Baylor College of Medicine, said. “This approach lets us exploit a massive amount of evolutionary data efficiently, so we can now probe with greater accuracy smaller cohorts and identify genes involved in sex-specific differences in AD.”
EAML is an ensemble computational approach that includes nine machine learning algorithms to analyze the functional impact of non-synonymous coding variants, defined as DNA mutations that affect the structure and function of the resulting protein, and estimates their deleterious effect on biological processes using the evolutionary action (EA) score.
In my work, I build instruments to study and control the quantum properties of small things like electrons. In the same way that electrons have mass and charge, they also have a quantum property called spin. Spin defines how the electrons interact with a magnetic field, in the same way that charge defines how electrons interact with an electric field. The quantum experiments I have been building since graduate school, and now in my own lab, aim to apply tailored magnetic fields to change the spins of particular electrons.
Research has demonstrated that many physiological processes are influenced by weak magnetic fields. These processes include stem cell development and maturation, cell proliferation rates, genetic material repair, and countless others. These physiological responses to magnetic fields are consistent with chemical reactions that depend on the spin of particular electrons within molecules. Applying a weak magnetic field to change electron spins can thus effectively control a chemical reaction’s final products, with important physiological consequences.
Currently, a lack of understanding of how such processes work at the nanoscale level prevents researchers from determining exactly what strength and frequency of magnetic fields cause specific chemical reactions in cells. Current cell phone, wearable, and miniaturization technologies are already sufficient to produce tailored, weak magnetic fields that change physiology, both for good and for bad. The missing piece of the puzzle is, hence, a “deterministic codebook” of how to map quantum causes to physiological outcomes.