Lifeboat Foundation

Ralph Lydic, professor in the UT Department of Psychology, and Dmitry Bolmatov, a research assistant professor in the UT Department of Physics and Astronomy, are part of a UT/ORNL research team studying how bio-inspired materials might inform the design of next-generation computers. Their results, published recently in the Proceedings of the National Academy of Sciences, could have big implications for both edge computing and human health.

Scientists at ORNL and UT discovered an artificial cell membrane is capable of long-term potentiation, or LTP, a hallmark of biological learning and memory. This is the first evidence that a cell membrane alone—without proteins or other biomolecules embedded within it—is capable of LTP that persists for many hours. It is also the first identified nanoscale structure in which memory can be encoded.

“When facilities were shut down as a result of COVID, this led us to pivot away from our usual membrane research,” said John Katsaras, a biophysicist in ORNL’s Neutron Sciences Directorate specializing in neutron scattering and the study of biological membranes at ORNL. “Together with postdoc Haden Scott, we decided to revisit a system previously studied by Pat Collier and co-workers, this time with an entirely different electrical stimulation protocol that we termed ‘training.’”.

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Better treatments are definitely on the way.

Nanomedicines took the spotlight during the COVID-19 pandemic. Researchers are using these very small and intricate materials to develop diagnostic tests and treatments. Nanomedicine is already used for various diseases, such as the COVID-19 vaccines and therapies for cardiovascular disease. The “nano” refers to the use of particles that are only a few hundred nanometers in size, which is significantly smaller than the width of a human hair.

NIH Image Gallery/Flickr.

Continue reading “How these factors could lead to better nanomedicine treatments” »

Aging appears to progress similarly across species, from worms and flies to mice and humans, and involves pathways related to early development. Guest Linda Partridge talks with Gordon while visiting the Buck Institute to discuss the evolutionary trade offs of aging mechanisms, the role of nutrient-sensing pathways, and how we might get the most benefit from preventative interventions in midlife.

Linda Partridge, born in 1950 in Bath, England, studied and graduated in biology at the University of Oxford. After three years of postdoctoral research at the University of York, she was Demonstrator, Lecturer, Reader and finally Professor at the University of Edinburgh. After many years in Scotland, in 1994 she became Professor of Biometry, University College London. She is both a founding director of the new Max Planck Institute for Biology of Ageing in Cologne and Director of the UCL Institute of Healthy Ageing. Linda Partridge’s research is directed to understanding both how the rate of aging evolves in nature and the mechanisms by which healthy lifespan can be extended in laboratory model organisms. Her work has focussed in particular on the role of nutrient-sensing pathways, such as the insulin/insulin-like growth factor signaling pathway, and on dietary restriction.

Over the past few decades, several imaging protocols based on quantum technologies have been realized^1,2, which have expanded the application capabilities of optical imaging. These include ghost imaging (GI)^3,4, quantum imaging with undetected photons (QIUP)⁵, and interaction-free measurements (IFMs)^6,7. The quantum GI scheme relies on the spatial correlations of entangled photon pairs and requires two-photon coincident measurements. Furthermore, ghost imaging can also be realized with classical intensity-fluctuation correlations⁸. Later, various single-pixel imaging (SPI) protocols were proposed^{9,10,11,12,13}, where the spatial correlations are not between two photons but between one photon and a programmable mask held in a spatial light modulator (SLM).

In contrast to modern digital cameras employing array sensors to capture images, SPI use a sequence of masks to interrogate the scene along with the correlated intensity measurements by a single-pixel detector. The spatially resolved masks are usually generated by computer and displayed by SLM. Combined with compressive techniques¹⁰, the number of sampling measurements is fewer than the total number of pixels in the image. Thereby, SPI can reduce the data processing requirement, and shows potential capability for high dimensional sensing¹². On the other hand, the modern single-photon detector is featured by improved detection efficiency, lower dark counts, and faster timing response¹⁴. Such enhancements have significance to applying SPI into weak signal detection scenarios, such as scattering medium imaging or long-range 3D imaging¹¹.

The QIUP scheme is based on induced coherence (IC), which was first proposed by Zou, Wang, and Mandel¹⁵. They used two photon sources to generate photon pairs. By overlapping path of two sources for one photon (idler)^15,16,17 and establishing the so-called path identity^18,19, there is no information about the origin of the other photon (signal). Thus, the signal photon is in the superposition state of being created in either of the sources. The phase and transmissivity of the idler photon are encoded in the interference of the signal photon. Inserting one object onto the idler path between two sources, one can obtain images exclusively with the signal photons which have no interaction with the object⁵. In contrast to GI, QIUP does not involve the detection of the photon illuminating the object or any coincidence measurement. This is an advantage of QIUP, as the wavelength of the detected photon can be chosen independently from that of the photon interacting with the object⁵. This concept was further explored in infrared (IR) spectroscopy²⁰, optical coherence tomography^21,22, mid-IR imaging^23,24,25, terahertz (THz) sensing²⁶, biological microscopy²⁷, and holography²⁸. Recently, the related SU(1,1) interferometer has been investigated and employed in quantum-enhanced metrology^{29,30,31,32,33}.

Let me assure you that my intent in this article is not to refute any empirical data or established theories about telomeres. Instead, I will explain why I believe that the historical course of scientific discoveries and an outdated paradigm about the biological cause of aging have led to the use of inaccurate language in describing the roles and functions of telomeres.

Is the Director General of the Pacific Community (SPC — https://www.spc.int/about-us/director-general) which is the largest intergovernmental organization in the Pacific and serves as a science and technology for development organization owned by the 26 Member countries and territories in the Pacific region.

SPC’s 650 member staff deliver services and scientific advice to the Pacific across the domains of Oceans, Islands and People, and has deep expertise in food security, water resources, fisheries, disasters, energy, maritime, health, statistics, education, human rights, social development and natural resources.

Continue reading “Dr. Stuart Minchin, Ph.D. — Sustainable Pacific Development Through Science, Knowledge & Innovation” »

Researchers from Carnegie Mellon University and the Chinese University of Hong Kong have developed a strategy for creating ultrahigh-resolution, complex 3D nanostructures out of various materials.

Carnegie Mellon University’s Yongxin (Leon) Zhao and the Chinese University of Hong Kong’s Shih-Chi Chen have a big idea for manufacturing nanodevices.

Continue reading “Shrinking hydrogels enlarge nanofabrication options” »

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Irina Rish is a world-renowned professor of computer science and operations research at the Université de Montréal and a core member of the prestigious Mila organisation. She is a Canada CIFAR AI Chair and the Canadian Excellence Research Chair in Autonomous AI. Irina holds an MSc and PhD in AI from the University of California, Irvine as well as an MSc in Applied Mathematics from the Moscow Gubkin Institute. Her research focuses on machine learning, neural data analysis, and neuroscience-inspired AI. In particular, she is exploring continual lifelong learning, optimization algorithms for deep neural networks, sparse modelling and probabilistic inference, dialog generation, biologically plausible reinforcement learning, and dynamical systems approaches to brain imaging analysis. Prof. Rish holds 64 patents, has published over 80 research papers, several book chapters, three edited books, and a monograph on Sparse Modelling. She has served as a Senior Area Chair for NeurIPS and ICML. Irina’s research is focussed on taking us closer to the holy grail of Artificial General Intelligence. She continues to push the boundaries of machine learning, continually striving to make advancements in neuroscience-inspired AI.

Continue reading “Prof. IRINA RISH — AGI, Complex Systems, Transhumanism #NeurIPS” »