Lifeboat Foundation: Safeguarding Humanity
Toggle light / dark theme

Blog

Category: biotech/medical

The central principle of superconductivity is that electrons form pairs. But can they also condense into foursomes? Recent findings have suggested they can, and a physicist at KTH Royal Institute of Technology today published the first experimental evidence of this quadrupling effect and the mechanism by which this state of matter occurs.

Reporting in Nature Physics, Professor Egor Babaev and collaborators presented evidence of fermion quadrupling in a series of experimental measurements on the iron-based material, Ba1−xKxFe2As2. The results follow nearly 20 years after Babaev first predicted this kind of phenomenon, and eight years after he published a paper predicting that it could occur in the material.

The pairing of electrons enables the quantum state of superconductivity, a zero-resistance state of conductivity which is used in MRI scanners and quantum computing. It occurs within a material as a result of two electrons bonding rather than repelling each other, as they would in a vacuum. The phenomenon was first described in a theory by, Leon Cooper, John Bardeen and John Schrieffer, whose work was awarded the Nobel Prize in 1972.

Read more | >

For most of the time since the first description of multiple sclerosis (MS) in 1,868 the causes of this disabling disease have remained uncertain. Genes have been identified as important, which is why having other family members with MS is associated with a greater risk of developing the disease.

A recent study my colleagues and I conducted found that several types of infection during the teenage years are associated with MS after age 20. Our study didn’t investigate whether people who are more likely to have genetic risks for MS were also more likely to have worse infections.

This might explain why people with MS also have more infections that need hospital treatment.

Read more | >

If the properties of materials can be reliably predicted, then the process of developing new products for a huge range of industries can be streamlined and accelerated. In a study published in Advanced Intelligent Systems, researchers from The University of Tokyo Institute of Industrial Science used core-loss spectroscopy to determine the properties of organic molecules using machine learning.

The spectroscopy techniques energy loss near-edge structure (ELNES) and X-ray near-edge structure (XANES) are used to determine information about the electrons, and through that the atoms, in materials. They have high sensitivity and high resolution and have been used to investigate a range of materials from electronic devices to drug delivery systems.

However, connecting spectral data to the properties of a material—things like optical properties, electron conductivity, density, and stability—remains ambiguous. Machine learning (ML) approaches have been used to extract information for large complex sets of data. Such approaches use artificial neural networks, which are based on how our brains work, to constantly learn to solve problems. Although the group previously used ELNES/XANES spectra and ML to find out information about materials, what they found did not relate to the properties of the material itself. Therefore, the information could not be easily translated into developments.

Read more | >

While the pandemic is still raging, the chaos of the past 18 months has calmed a bit, and the dust is starting to settle. Now the time has come for healthcare CIOs and other health IT leaders to look forward and plan their IT investments – shaped, in no small part, by the lessons of the recent past.

Read more | >

Conventional lung cancer treatments include surgery, chemotherapy and radiotherapy; however, these treatments are often poorly tolerated by patients. Cannabinoids have been studied for use as a primary cancer treatment. Cannabinoids, which are chemically similar to our own body’s endocannabinoids, can interact with signalling pathways to control the fate of cells, including cancer cells. We present a patient who declined conventional lung cancer treatment. Without the knowledge of her clinicians, she chose to self-administer ‘cannabidiol (CBD) oil’ orally 2–3 times daily. Serial imaging shows that her cancer reduced in size progressively from 41 mm to 10 mm over a period of 2.5 years. Previous studies have failed to agree on the usefulness of cannabinoids as a cancer treatment. This case appears to demonstrate a possible benefit of ‘CBD oil’ intake that may have resulted in the observed tumour regression. The use of cannabinoids as a potential cancer treatment justifies further research.

Read more | >

Field doctors still diagnose burns by sight, smell and touch. A smart bandage and smart phone camera may be all we need to change that — and prevent serious and lasting complications.

This article was produced for AMEDD by Scientific American Custom Media, a division separate from the magazine’s board of editors.

Read more | >

Duke professor becomes second recipient of AAAI Squirrel AI Award for pioneering socially responsible AI.

Whether preventing explosions on electrical grids, spotting patterns among past crimes, or optimizing resources in the care of critically ill patients, Duke University computer scientist Cynthia Rudin wants artificial intelligence (AI) to show its work. Especially when it’s making decisions that deeply affect people’s lives.

While many scholars in the developing field of machine learning were focused on improving algorithms, Rudin instead wanted to use AI’s power to help society. She chose to pursue opportunities to apply machine learning techniques to important societal problems, and in the process, realized that AI’s potential is best unlocked when humans can peer inside and understand what it is doing.

Read more | >