British health tech startup Twinn Health recently emerged from stealth, boasting an AI-powered platform that analyzes MRI scans to detect preventable disease “earlier than ever before.” Starting with metabolic disease, the company’s AI platform leverages validated imaging biomarkers to improve diagnosis and treatment decisions.
With age-related frailty and liver disease also on its roadmap, Twinn Health is positioning itself squarely in the domain of longevity and preventive healthcare. The company is supported by WAED, a $500 million venture capital fund backed by Saudi Aramco, which invests in innovative tech-based startups.
Longevity. Technology: Magnetic resonance imaging (MRI) has been used in healthcare for decades and is widely used in hospitals and clinics for the diagnosis and follow-up of disease. In recent years, AI tools have appeared that help identify the presence of specific conditions within MRI scans, but the technology is not yet widely used in healthcare to support healthspan and longevity improvements. Twinn Health aims to change that, combining MRI and AI to enable the early detection and management of multiple age-related diseases. To learn more, we caught up with founder and CEO Dr Wareed Alenaini.
Part of NCI’s Division of Cancer Biology’s research portfolio, studies supported include the characterization of basic mechanisms relevant to anti-tumor immune responses and hematologic malignancies.
All navigations reported in Fig. 2 were performed autonomously within 150 s and without intraoperative imaging. Specifically, each navigation was performed according to the pre-determined optimal actuation fields and supervised in real time by intraoperative localization. Therefore, the set of complex navigations performed by the magnetic tentacle was possible without the need for exposure to radiation-based imaging. In all cases, the soft magnetic tentacle is shown to conform by design to the anatomy thanks to its low stiffness, optimal magnetization profile and full-shape control. Compared to a stiff catheter, the non-disruptive navigation achieved by the magnetic tentacle can improve the reliability of registration with pre-operative imaging to enhance both navigation and targeting. Moreover, compared to using multiple catheters with different pre-bent tips, the optimization approach used for the magnetic tentacle design determines a single magnetization profile specific to the patient’s anatomy that can navigate the full range of possible pathways illustrated in Fig. 2. Supplementary Movies S1 and S2 report all the experiments. Supplementary Movie S1 shows the online tracking capabilities of the proposed platform.
In Table 1, we report the results of the localization for four different scenarios. These cases highlight diverse navigations in the left and right bronchi. The error is referred to as the percentage of tentacles outside the anatomy. This was computed by intersecting the shape of the catheter, as predicted by the FBG sensor, and the anatomical mesh grid extracted from the CT scan. The portion of the tentacle within the anatomy was measured by using “inpolyhedron” function in MATLAB. In Supplementary Movie S1, this is highlighted in blue, while the section of the tentacle outside the anatomy is marked in red. The error in Table 1 was computed using the equation.
The wings of a butterfly are made of chitin, an organic polymer that is the main component of the shells of arthropods like crustaceans and other insects. As a butterfly emerges from its cocoon in the final stage of metamorphosis, it will slowly unfold its wings into their full grandeur.
During the unfolding, the chitinous material becomes dehydrated while blood pumps through the veins of the butterfly, producing forces that reorganize the molecules of the material to provide the unique strength and stiffness necessary for flight. This natural combination of forces, movement of water, and molecular organization is the inspiration behind Associate Professor Javier G. Fernandez’s research.
Summary: Researchers created a revolutionary tiny and efficient thermoelectric device, which can help amputees feel temperature with their phantom limbs.
Known as the wearable thin-film thermoelectric cooler (TFTEC), this device is lightweight, incredibly fast, and energy-efficient, potentially revolutionizing applications such as prosthetics, augmented reality haptics, and thermally-modulated therapeutics. Additionally, this technology has potential in industries like electronics cooling and energy harvesting in satellites.
The study conducted to test the TFTEC demonstrated its ability to elicit cooling sensations in phantom limbs, doing so significantly faster, with more intensity, and less energy than traditional thermoelectric technology.
The astonishing discovery is “important for the understanding of evolutionary processes because generation times could be stretched from days to millennia, and long-term survival of individuals of species can lead to the refoundation of otherwise extinct lineages,” according to a study published on Thursday in the journal PLoS Genetics.
“Their evolution was literally suspended for 40k years,” wrote Philipp Schiffer, an evolutionary biologist at the University of Cologne and a co-author of the study, in an email to Motherboard.
“We are now comparing them to species from the same genus, which my team samples around the world,” he continued, noting that he is currently conducting fieldwork in the Australian Outback. “Studying their genomes we hope to understand a lot about how these populations became different in the last 40k years.”
For many people, depression turns out to be one of the most disabling illnesses that we have in society. Despite the treatments that we have available, many people are not responding that well. It’s a disorder that can be very disabling in society. It’s also a disorder that has medical consequences. By understand the neurobiology of depression we hope to be able more to find the right treatment for the patient suffering from this disease. The current standard of care for the treatment of depression is based on what we call the monoamine deficiency hypothesis. Essentially, presuming that one of three neurotransmitters in the brain is deficient or underactive. But the reality is, there are more than 100 neurotransmitters in the brain. And billions of connections between neurons. So we know that that’s a limited hypothesis. Neurotransmitters can be thought of as the chemical messengers within the brain, it’s what helps one cell in the brain communicate with another, to pass that message along from one brain region to another. For decades, we thought that the primary pathology, the primary cause of depression was some abnormality in these neurotransmitters, specifically serotonin or norepinephrine. However, norepinephrine and serotonin did not seem to be able to account for this cause, or to cause the symptoms of depression in people who had major depression. Instead, the chemical messengers between the nerve cells in the higher centers of the brain, which include glutamate and GABA, were possibilities as alternative causes for the symptoms of depression. When you’re exposed to severe and chronic stress like people experience when they have depression, you lose some of the connections between the nerve cells. The communication in these circuits becomes inefficient and noisy, we think that the loss of these synaptic connections contributes to the biology of depression. There are clear differences between a healthy brain and a depressed brain. And the exciting thing is, when you treat that depression effectively, the brain goes back to looking like a healthy brain, both at the cellular level and at a global scale. It’s critical to understand the neurobiology of depression and how the brain plays a role in that for two main reasons. One, it helps us understand how the disease develops and progresses, and we can start to target treatments based on that. We are in a new era of psychiatry. This is a paradigm shift, away from a model of monoaminergic deficiency to a fuller understanding of the brain as a complex neurochemical organ. All of the research is driven by the imperative to alleviate human suffering. Depression is one of the most substantial contributors to human suffering. The opportunity to make even a tiny dent in that is an incredible opportunity.
A tiny robot which can travel deep into the lungs to detect and treat the first signs of cancer has been developed by researchers at the University of Leeds. The ultra-soft tentacle, which measures just two millimeters in diameter, and is controlled by magnets, can reach some of the smallest bronchial tubes and could transform the treatment of lung cancer. The researchers tested the magnetic tentacle robot on the lungs of a cadaver and found that it can travel 37 percent deeper than the standard equipment and leads to less tissue damage. It paves the way for a more accurate, tailored, and far less invasive approach to treatment.
“This new approach has the advantage of being specific to the anatomy, softer than the anatomy and fully-shape controllable via magnetics,” notes Pietro Valdastri, PhD, director of the Science and Technologies Of Robotics in Medicine (STORM) Lab at the University of Leeds. “These three main features have the potential to revolutionize navigation inside the body.”
