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Category: biotech/medical – Page 66

Cellular death is a fundamental concept in biological sciences. Despite its importance, its definition varies depending on the context in which it occurs and lacks a general mathematical definition.

Researchers from the University of Tokyo propose a new mathematical definition of death based on whether a potentially dead cell can return to a predefined “representative state of living,” which are the states of being that we can confidently call “alive.” The researchers’ work could be useful for biological researchers and future medical research.

While it’s not something we like to think about, death comes for us all eventually, whether you’re an animal, a plant, or even a cell. And even though we can all differentiate between what is alive and dead, it might be surprising to know that death at a cellular level lacks a widely recognized mathematical definition.

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Researchers have developed a device that can simultaneously measure six markers of brain health. The sensor, which is inserted through the skull into the brain, can pull off this feat thanks to an artificial intelligence (AI) system that pieces apart the six signals in real time.

Being able to continuously monitor biomarkers in patients with traumatic brain injury could improve outcomes by catching swelling or bleeding early enough for doctors to intervene. But most existing devices measure just one marker at a time. They also tend to be made with metal, so they can’t easily be used in combination with magnetic resonance imaging.

Simultaneous access to measurements could improve outcomes for brain injuries.

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Researchers have developed a new, fast, and rewritable method for DNA computing that promises smaller, more powerful computers.

This method mimics the sequential and simultaneous gene expression in living organisms and incorporates programmable DNA circuits with logic gates. The improved process places DNA on a solid glass surface, enhancing efficiency and reducing the need for manual transfers, culminating in a 90-minute reaction time in a single tube.

Advancements in DNA-Based Computation.

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Different types of cancer have unique molecular “fingerprints” which are detectable in early stages of the disease and can be picked up with near-perfect accuracy by small, portable scanners in just a few hours, according to a study published today in the journal Molecular Cell.

The discovery by researchers at the Centre for Genomic Regulation (CRG) in Barcelona sets the foundation for creating new, non-invasive diagnostic tests that detect different types of cancer faster and earlier than currently possible.

The study centers around the ribosome, the protein factories of a cell. For decades, ribosomes were thought to have the same blueprint across the human body. However, researchers discovered a hidden layer of complexity—tiny chemical modifications which vary between different tissues, developmental stages, and disease.

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A research team from the Nagoya University Graduate School of Medicine has discovered a promising way to slow the progression of heart failure in mice. They fed mice a diet rich in the soybean protein, β-conglycinin (β-CG), which can support heart health by influencing gut bacteria. Their analysis revealed that the soybean protein rich diet increased the production of the short-chain fatty acids (SCFAs) in the intestine that play a role in protecting the heart. Their findings were published in Clinical Nutrition.

Many people with heart problems try to eat a nutritious diet to reduce their risk of disease. As part of a healthy diet, soybeans have long been recognized for their antioxidant and anti-inflammatory properties. Based on this, the researchers suspected that proteins in soy may help prevent heart damage.

Dr. Nozomi Furukawa and colleagues fed the soy-derived protein β-CG to mice prone to heart failure and investigated its effects on the heart. The mice showed improved heart function, less muscle thickening, and reduced scarring of the heart tissue, common problems associated with the progression of heart disease.

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Nonlinear optics explores how powerful light (e.g. lasers) interacts with materials, resulting in the output light changing colour (i.e. frequency) or behaving differently based on the intensity of the incoming light. This field is crucial for developing advanced technologies such as high-speed communication systems and laser-based applications. Nonlinear optical phenomena enable the manipulation of light in novel ways, leading to breakthroughs in fields like telecommunications, medical imaging, and quantum computing. Two-dimensional (2D) materials, such as graphene—a single layer of carbon atoms in a hexagonal lattice—exhibit unique properties due to their thinness and high surface area. Graphene’s exceptional electronic properties, related to relativistic-like Dirac electrons and strong light-matter interactions, make it promising for nonlinear optical applications, including ultrafast photonics, optical modulators, saturable absorbers in ultrafast lasers, and quantum optics.

Dr. Habib Rostami, from the Department of Physics at the University of Bath, has co-authored pioneering research published in Advanced Science. This study involved an international collaboration between an experimental team at Friedrich Schiller University Jena in Germany and theoretical teams at the University of Pisa in Italy and the University of Bath in the UK. The research aimed to investigate the ultrafast opto-electronic and thermal tuning of nonlinear optics in graphene.

This study discovers a new way to control high-harmonic generation in a graphene-based field-effect transistor. The team investigated the impact of lattice temperature, electron doping, and all-optical ultrafast tuning of third-harmonic generation in a hexagonal boron nitride-encapsulated graphene opto-electronic device. They demonstrated up to 85% modulation depth along with gate-tuneable ultrafast dynamics, a significant improvement over previous static tuning. Furthermore, by changing the lattice temperature of graphene, the team could enhance the modulation of its optical response, achieving a modulation factor of up to 300%. The experimental fabrication and measurement took place at Friedrich Schiller University Jena. Dr. Rostami played a crucial role in the study by crafting theoretical models. These models were developed in collaboration with another theory team at the University of Pisa to elucidate new effects observed in graphene.

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Globally, approximately 139 million people are expected to have Alzheimer’s disease (AD) by 2050. Magnetic resonance imaging (MRI) is an important tool for identifying changes in brain structure that precede cognitive decline and progression with disease; however, its cost limits widespread use.

A new study by investigators from Massachusetts General Hospital (MGH), a founding member of the Mass General Brigham health care system, demonstrates that a simplified, low magnetic field (LF) MRI machine, augmented with machine learning tools, matches conventional MRI in measuring brain characteristics relevant to AD. Findings, published in Nature Communications, highlight the potential of the LF-MRI to help evaluate those with cognitive symptoms.

“To tackle the growing, global health challenge of dementia and cognitive impairment in the aging population, we’re going to need simple, bedside tools that can help determine patients’ underlying causes of cognitive impairment and inform treatment,” said senior author W. Taylor Kimberly, MD, Ph.D., chief of the Division of Neurocritical Care in the Department of Neurology at MGH.

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