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Category: biotech/medical – Page 298

Flatiron Institute senior research scientist Shiwei Zhang and his team have utilized the Hubbard model to computationally re-create key features of the superconductivity in materials called cuprates that have puzzled scientists for decades.

Superfast hovering trains, long-distance power transmission without energy loss, and quicker MRI scanners — all these incredible technological innovations could be within reach if we could develop a material that conducts electricity without any resistance, or “superconducts,” at approximately room temperature.

In a paper recently published in the journal Science, researchers report a breakthrough in our understanding of the origins of superconductivity at relatively high (though still frigid) temperatures. The findings concern a class of superconductors that has puzzled scientists since 1986, called ‘cuprates.’

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Since the first microbial genome was sequenced in 1995, scientists have reconstructed the genomic makeup of hundreds of thousands of microorganisms and have even devised methods to take a census of bacterial communities on the skin, in the gut, or in soil, water and elsewhere based on bulk samples, leading to the emergence of a relatively new field of study known as metagenomics.

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Engineers at MIT have developed a groundbreaking method for detecting bioluminescent light within the brain.

By modifying the brain’s blood vessels to express a specific protein, they induced dilation in response to light exposure.

The approach enabled researchers to visualize the dilation using magnetic resonance imaging (MRI), facilitating precise localization of light sources within the brain.

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Chapters 00:00 — Intro + Background 05:06 — From KART to KAN 07:56 — MLP vs KAN 16:05 — Accuracy: Scaling of KANs 26:35 — Interpretability: KAN for Science 38:04 — Q+A Break 57:15 — Strengths and Weaknesses 59:28 — Philosophy 1:08:45 — Anecdotes Behind the Scenes…

Portal is the home of the AI for drug discovery community. Join for more details on this talk and to connect with the speakers: https://portal.valencelabs.com/logg.

Abstract: Inspired by the Kolmogorov-Arnold representation theorem, we propose Kolmogorov-Arnold Networks (KANs) as promising alternatives to Multi-Layer Perceptrons (MLPs). While MLPs have fixed activation functions on nodes (\.

Continue reading “KAN: Kolmogorov-Arnold Networks | Ziming Liu” | >

The coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a global health problem that the WHO declared a pandemic. COVID-19 has resulted in a worldwide lockdown and threatened to topple the global economy. The mortality of COVID-19 is comparatively low compared with previous SARS outbreaks, but the rate of spread of the disease and its morbidity is alarming. This virus can be transmitted human-to-human through droplets and close contact, and people of all ages are susceptible to this virus. With the advancements in nanotechnology, their remarkable properties, including their ability to amplify signal, can be used for the development of nanobiosensors and nanoimaging techniques that can be used for early-stage detection along with other diagnostic tools.

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Editor’s note: This story is being highlighted in ASU Now’s year in review. Read more top stories from 2018 here.

In a major advancement in nanomedicine, Arizona State University scientists, in collaboration with researchers from the National Center for Nanoscience and Technology (NCNST) of the Chinese Academy of Sciences, have successfully programmed nanorobots to shrink tumors by cutting off their blood supply.

“We have developed the first fully autonomous, DNA robotic system for a very precise drug design and targeted cancer therapy,” said Hao Yan, director of the ASU Biodesign Institute’s Center for Molecular Design and Biomimetics and the Milton Glick Professor in the School of Molecular Sciences.

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Almost 99% of all human ancestors may have been wiped out around 930,000 years ago, a new paper has claimed.

The new research, published in the journal Science, used DNA from living people to suggest that humans went through a bottleneck, an event where populations shrink drastically. The paper estimates that as few as 1,300 humans were left for a period of around 120,000 years.

While the exact causes aren’t certain, the near-extinction has been blamed on Africa’s climate getting much colder and drier.

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Scientists have published the most detailed data set to date on the neural connections of the brain, which was obtained from a cubic millimeter of tissue sample.

A cubic millimeter of brain tissue may not sound like much. But considering that that tiny square contains 57,000 cells, 230 millimeters of blood vessels, and 150 million synapses, all amounting to 1,400 terabytes of data, Harvard and Google researchers have just accomplished something stupendous.

Led by Jeff Lichtman, the Jeremy R. Knowles Professor of Molecular and Cellular Biology and newly appointed dean of science, the Harvard team helped create the largest 3D brain reconstruction to date, showing in vivid detail each cell and its web of connections in a piece of temporal cortex about half the size of a rice grain.

Published in Science, the study is the latest development in a nearly 10-year collaboration with scientists at Google Research, combining Lichtman’s electron microscopy imaging with AI algorithms to color-code and reconstruct the extremely complex wiring of mammal brains. The paper’s three first co-authors are former Harvard postdoc Alexander Shapson-Coe, Michał Januszewski of Google Research, and Harvard postdoc Daniel Berger.

Continue reading “Researchers publish largest-ever dataset of neural connections” | >