Unlock the potential of nanotechnology. Explore breakthroughs and challenges in energy, biomedicine, and more in our executive summary.
This biomaterials Insights Report explores eight key areas transforming healthcare with self-healing implants, targeted drug delivery, and more.
Carbon nanotubes (CNTs) are nanometer-scale structures with immense potential to improve different materials, but inconsistencies in their chemical and electrical properties, purity, cost, and concerns over possible toxicity present ongoing challenges. CNTs are a one-dimensional carbon allotrope made of an sp2 hybridized carbon lattice in a cylindrical shape. Single-walled CNTs are a simple tube, while multi-walled CNTs are nested concentrically or wrapped like a scroll (Figure 1).
These nanoscale materials feature a high Young’s modulus and tensile strength and can have either metallic or semiconducting electrical properties. Controlling their atomic arrangement (chirality) affects their conductivity, and because of this, researchers have been trying to understand how synthesis parameters can be used to generate CNTs with predictable electrical properties. The development of various chemical vapor deposition (CVD)-based recipes within the last 20 years to synthesize CNTs has improved this situation.
As we’ve seen in our analysis of the CAS Content Collection™, the world’s largest human-curated collection of published scientific information, the increase in patent activity indicates a high amount of interest in commercial applications for CNTs (Figure 2).
There used to be the concept of a “singularity”. The idea was that computers would become smarter than humans and start to replace them. Even the idea that humanity would be substituted by silicon-based computing machines (robots) was suggested. Against that two years ago we set the concept of “The convergence”. This assumes that biological and silicon-based computation would merge in the sense of better control over biological processes like diseases and longevity. It is essentially a deeply humanistic perspective, in spite of being futuristic, and not taking misuses actively into account.
“Engineering the brain”. There was no intelligent design, and as a result, body organs do not resemble machines. Once we start building machines like body organs — with utility functions, self-organization and cells as building blocks, we can mesh engineering and evolutionary principles to arrive at better organisms.
In a paper titled, “Multimodal MRI reveals brainstem connections that sustain wakefulness in human consciousness,” published today in Science Translational Medicine, a group of researchers at Massachusetts General Hospital, a founding member of the Mass General Brigham healthcare system, and Boston Children’s Hospital, created a connectivity map of a brain network that they propose is critical to human consciousness.
The study involved high-resolution scans that enabled the researchers to visualize brain connections at submillimeter spatial resolution. This technical advance allowed them to identify previously unseen pathways connecting the brainstem, thalamus, hypothalamus, basal forebrain, and cerebral cortex.
Together, these pathways form a “default ascending arousal network” that sustains wakefulness in the resting, conscious human brain. The concept of a “default” network is based on the idea that specific networks within the brain are most functionally active when the brain is in a resting state of consciousness. In contrast, other networks are more active when the brain is performing goal-directed tasks.
Summary: Researchers developed a groundbreaking model called Brain Language Model (BrainLM) using generative artificial intelligence to map brain activity and its implications for behavior and disease. BrainLM leverages 80,000 scans from 40,000 subjects to create a foundational model that captures the dynamics of brain activity without the need for specific disease-related data.
This model significantly reduces the cost and scale of data required for traditional brain studies, offering a robust framework that can predict conditions like depression, anxiety, and PTSD more effectively than other tools. The BrainLM demonstrates a potent application in clinical trials, potentially halving the costs by identifying patients most likely to benefit from new treatments.
Explore how AI transforms clinical screening and preventative healthcare. Dive into the impact on efficiency, patient outcomes, and more.
Borophene is already thinner and more conductive than graphene, and scientists have altered it to make it even more special.
Google DeepMind’s groundbreaking new AI predicts not only the structure of proteins, ligands, DNA, RNA and “all of life’s molecules,” but how they’ll interact. It promises a radical, revolutionary acceleration in many fields of science.
