Lifeboat Foundation

Biological age and biomarkers improved to that of rats half their age. Blog post from the Live Forever Club.

Revealing yet another super-power in the skillful squid, scientists have discovered that squid massively edit their own genetic instructions not only within the nucleus of their neurons, but also within the axon — the long, slender neural projections that transmit electrical impulses to other neurons. This is the first time that edits to genetic information have been observed outside of the nucleus of an animal cell.

The study, led by Isabel C. Vallecillo-Viejo and Joshua Rosenthal at the Marine Biological Laboratory (MBL), Woods Hole, is published this week in Nucleic Acids Research.

Scientists who were melting permafrost ice to look for ancient microbes were surprised to see a pile of 41,000 year-old worms wake up and wiggle around.

Strong coupling between cavity photon modes and donor/acceptor molecules can form polaritons (hybrid particles made of a photon strongly coupled to an electric dipole) to facilitate selective vibrational energy transfer between molecules in the liquid phase. The process is typically arduous and hampered by weak intermolecular forces. In a new report now published on Science, Bo Xiang, and a team of scientists in materials science, engineering and biochemistry at the University of California, San Diego, U.S., reported a state-of-the-art strategy to engineer strong light-matter coupling. Using pump-probe and two-dimensional (2-D) infrared spectroscopy, Xiang et al. found that strong coupling in the cavity mode enhanced the vibrational energy transfer of two solute molecules. The team increased the energy transfer by increasing the cavity lifetime, suggesting the energy transfer process to be a polaritonic process. This pathway on vibrational energy transfer will open new directions for applications in remote chemistry, vibration polariton condensation and sensing mechanisms.

Vibrational energy transfer (VET) is a universal process ranging from chemical catalysis to biological signal transduction and molecular recognition. Selective intermolecular vibrational energy transfer (VET) from solute-to-solute is relatively rare due to weak intermolecular forces. As a result, intermolecular VET is often unclear in the presence of intramolecular vibrational redistribution (IVR). In this work, Xiang et al. detailed a state-of-the-art method to engineer intermolecular vibrational interactions via strong light-matter coupling. To accomplish this, they inserted a highly concentrated molecular sample into an optical microcavity or placed it onto a plasmonic nanostructure. The confined electromagnetic modes in the setup then reversibly interacted with collective macroscopic molecular vibrational polarization for hybridized light-matter states known as vibrational polaritons.

Every once in a while I have a contentious discussion with someone about traveling to Mars, and the risks involved. One of the hardest risks to describe is the threat from galactic cosmic rays. Here is a short article about a new facility investigating the effects of galactic cosmic rays.

The very important point here is that we are not discussing electromagnetic radiation. These ions have been shown to sometimes penetrate spacecraft and inflict damage on astronauts brains. Earthlings do not have to worry about these as much because we have a magnetosphere that shields us from ions.

To better understand and mitigate the health risks faced by astronauts from exposure to space radiation, we ideally need to be able to test the effects of Galactic Cosmic Rays (GCRs) here on Earth under laboratory conditions. An article publishing on May 19, 2020 in the open access journal PLOS Biology from Lisa Simonsen and colleagues at the NASA Langley Research Center, USA, describes how NASA has developed a ground-based GCR Simulator at the NASA Space Radiation Laboratory (NSRL), located at Brookhaven National Laboratory.

Continue reading “Galactic cosmic rays now available for study on Earth, thanks to NASA” »

Modeling and rendering of dynamic scenes is challenging, as natural scenes often contain complex phenomena such as thin structures, evolving topology, translucency, scattering, occlusion, and biological motion. Mesh-based reconstruction and tracking often fail in these cases, and other approaches (e.g., light field video) typically rely on constrained viewing conditions, which limit interactivity. We circumvent these difficulties by presenting a learning-based approach to representing dynamic objects inspired by the integral projection model used in tomographic imaging. The approach is supervised directly from 2D images in a multi-view capture setting and does not require explicit reconstruction or tracking of the object. Our method has two primary components: an encoder-decoder network that transforms input images into a 3D volume representation, and a differentiable ray-marching operation that enables end-to-end training. By virtue of its 3D representation, our construction extrapolates better to novel viewpoints compared to screen-space rendering techniques. The encoder-decoder architecture learns a latent representation of a dynamic scene that enables us to produce novel content sequences not seen during training. To overcome memory limitations of voxel-based representations, we learn a dynamic irregular grid structure implemented with a warp field during ray-marching. This structure greatly improves the apparent resolution and reduces grid-like artifacts and jagged motion. Finally, we demonstrate how to incorporate surface-based representations into our volumetric-learning framework for applications where the highest resolution is required, using facial performance capture as a case in point.

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face_with_colon_three circa 2015 this guppy could lead to rapid biological singularity.

Some species are evolving far more quickly than Darwin ever imagined.

Hey all! I’ve recently made a video on how humans can one day become AI and how this can be good for individuals and humanity on its own! If you are interested, please give it a watch!

AI is oftentimes the ultimate bane of science-fiction. Artificial intelligence oftentimes becomes smarter than humanity and turns on us in sci-fi movies and films. However, what if people could become AI one day and use this to their advantage? And if so, would people choose to become AI? Here’s why I believe this may be possible and why people may actually voluntarily choose to become AI themselves- thus blurring the lines between computer science and biology.

Continue reading “Why Fear AI When You Can Become It? | Mind Uploading” »