Lifeboat Foundation: Safeguarding Humanity
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Researchers at Korea’s Daegu Gyeongbuk Institute of Science and Technology (DGIST) have developed a porous laser-induced graphene (LIG) sensor array that functions as a “next-generation AI electronic nose” capable of distinguishing scents like the human olfactory system does and analyzing them using artificial intelligence.

This technology converts scent molecules into electrical signals and trains AI models on their unique patterns. It holds great promise for applications in personalized health care, the cosmetics industry, and environmental monitoring.

While conventional electronic noses (e-noses) have already been developed and used in areas such as food safety and gas detection in industrial settings, they struggle to distinguish subtle differences between similar smells or analyze complex scent compositions. For instance, distinguishing among floral perfumes with similar notes or detecting the faint odor of fruit approaching spoilage remains challenging for current systems. This gap has driven demand for next-generation e-nose technologies with greater precision, sensitivity, and adaptability.

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Northwestern University engineers have developed a pacemaker so tiny that it can fit inside the tip of a syringe — and be non-invasively injected into the body.

Smaller than a single grain of rice, the pacemaker is paired with a small, soft, flexible, wireless, wearable device that mounts onto a patient’s chest to control pacing. When the wearable device detects an irregular heartbeat, it automatically shines a light pulse to activate the pacemaker. These short pulses— which penetrate through the patient’s skin, breastbone and muscles — control the pacing. #Repost

Although it can work with hearts of all sizes, the pacemaker is particularly well-suited to the tiny, fragile hearts of newborn babies with congenital heart defects.

Designed for patients who only need temporary pacing, the pacemaker simply dissolves after it’s no longer needed. All the pacemaker’s components are biocompatible, so they naturally dissolve into the body’s biofluids, bypassing the need for surgical extraction.

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Four children have gained life-changing improvements in sight following treatment with a pioneering new genetic medicine through Moorfields Eye Hospital and UCL Institute of Ophthalmology.

The work was funded by the NIHR Research Professorship, Meira GTx and Moorfields Eye Charity.

The 4 children were born with a severe impairment to their sight due to a rare genetic deficiency that affects the ‘AIPL1’ gene. The defect causes the retinal cells to malfunction and die. Children affected are only able to distinguish between light and darkness. They are legally certified as blind from birth.

The new treatment is designed to enable the retinal cells to work better and to survive longer. The procedure, developed by UCL scientists, consists of injecting healthy copies of the gene into the retina through keyhole surgery. These copies are contained inside a harmless virus, so they can penetrate the retinal cells and replace the defective gene.

The condition is very rare, and the first children identified were from overseas. To mitigate any potential safety issues, the first 4 children received this novel therapy in only one eye.

The eye gene therapy was delivered via keyhole surgery at Great Ormond Street Hospital. The children were assessed in the NIHR Moorfields Clinical Research Facility, and the NIHR Moorfields Biomedical Research Centre provided infrastructure support for the research.

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In a large population-based cohort of individuals who underwent electron-beam CT, coronary artery calcium score was independently associated with incident lung cancer diagnosis but did not demonstrate potential to improve risk stratification in lung cancer screening.

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The James Webb Space Telescope (JWST) has been giving us a fabulous new view on the Universe since its launch.

This new image of the protostar HH30 is in amazing new detail thanks to the JWST. It was first discovered using the Hubble Space Telescope, but this Herbig-Haro object, which is a dark molecular cloud, is a perfect object for JWST.

The image shows the protoplanetary disk seen edge on, with a conical outflow of gas and dust, with a narrow jet blasting out into space.

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A machine-learning algorithm rapidly generates designs that can be simpler than those developed by humans.

Researchers in optics and photonics rely on devices that interact with light in order to transport it, amplify it, or change its frequency, and designing these devices can be painstaking work requiring human ingenuity. Now a research team has demonstrated that the discovery of the core design concepts can be automated using machine learning, which can rapidly provide efficient designs for a wide range of uses [1]. The team hopes the approach will streamline research and development for scientists and engineers who work with optical, mechanical, or electrical waves, or with combinations of these wave types.

When a researcher needs a transducer, an amplifier, or a similar element in their experimental setup, they draw on design concepts tested and proven in earlier experiments. “There are literally hundreds of articles that describe ideas for the design of devices,” says Florian Marquardt of the University of Erlangen-Nuremberg in Germany. Researchers often adapt an existing design to their specific needs. But there is no standard procedure to find the best design, and researchers could miss out on simpler designs that would be easier to implement.

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Doctors are increasingly detecting stomach tumors at an early stage, raising hopes for lifesaving treatment for one of the deadliest types of cancer. Stomach cancer, the disease that killed country music star Toby Keith in 2024, is typically difficult to catch early and tends to be discovered at an advanced stage when cancer cells have spread, researchers reported Saturday at Digestive Disease Week, a major international conference for doctors and researchers in gastroenterology, liver diseases and endoscopy.

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