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Summary: Text-to-image generation deep learning models like OpenAI’s DALL-E 2 can be a promising new tool for image augmentation, generation, and manipulation in a healthcare setting.

Source: JMIR Publications

A new paper published in the Journal of Medical Internet Research describes how generative models such as DALL-E 2, a novel deep learning model for text-to-image generation, could represent a promising future tool for image generation, augmentation, and manipulation in health care.

“It’s poor for that particular cell, but it protects the whole colony of bacteria so that virus doesn’t spread through it,” said Jackson.

CRISPR vs. cancer: The newly published papers detail the structure and function of Cas12a2, but more research is needed to determine how we might be able to harness this system for our benefit.

Continue reading “New killer CRISPR system is unlike any scientists have seen” »

A small nucleus in the brainstem called locus coeruleus (literally the “blue spot,”) is the primary source of a major neuromodulator, norepinephrine (NE), an important mediator of the ‘fight or flight’ response in animals. However, very little is known about the local connections of this small albeit critically important group of neurons. A recent pioneering study published in eLife from the laboratory of Dr. Xiaolong Jiang, investigator at the Jan and Dan Duncan Neurological Research Institute (Duncan NRI) at Texas Children’s Hospital and assistant professor at Baylor College of Medicine, now reveals the cellular composition and circuit organization of the locus coeruleus in adult mice.

“In this study, we undertook the arduous task of mapping local connections of NE-producing neurons in the locus coeruleus,” Dr. Jiang said. “This is the first study of such an unprecedented magnitude and detail to be performed on the locus coeruleus, and in fact, on any monoamine neurotransmitter system. Our study has revealed that the neurons in the locus coeruleus have an unexpectedly rich cellular heterogeneity and local wiring logic.”

Locus coeruleus (LC) is known to house the vast majority of norepinephrine-releasing neurons in the brain and regulates many fundamental brain functions including the fight and flight response, sleep/wake cycles, and attention control. Present in the pontine region of the brainstem, LC neurons sense any existential dangers or threats in our external environment and send signals to alert other brain regions of the impending danger.

Breakthroughs don’t often happen in neuroscience, but we just had one. In a tour-de-force, an international team released the full brain connectivity map of the young fruit fly, described in a paper published last week in Science. Containing 3,016 neurons and 548,000 synapses, the map—called a connectome—is the most complex whole-brain wiring diagram to date.

“It’s a ‘wow,’” said Dr. Shinya Yamamoto at Baylor College of Medicine, who was not involved in the work.

Continue reading “The First Complete Brain Map of an Insect May Reveal Secrets for Better AI” »

A study of the electron excitation response of DNA to proton radiation has elucidated mechanisms of damage incurred during proton radiotherapy.

Radiobiology studies on the effects of ionizing radiation on human health focus on the deoxyribonucleic acid (DNA) molecule as the primary target for deleterious outcomes. The interaction of ionizing radiation with tissue and organs can lead to localized energy deposition large enough to instigate double strand breaks in DNA, which can lead to mutations, chromosomal aberrations, and changes in gene expression. Understanding the mechanisms behind these interactions is critical for developing radiation therapies and improving radiation protection strategies. Christopher Shepard of the University of North Carolina at Chapel Hill and his colleagues now use powerful computer simulations to show exactly what part of the DNA molecule receives damaging levels of energy when exposed to charged-particle radiation (Fig. 1) [1]. Their findings could eventually help to minimize the long-term radiation effects from cancer treatments and human spaceflight.

The interaction of radiation with DNA’s electronic structure is a complex process [2, 3]. The numerical models currently used in radiobiology and clinical radiotherapy do not capture the detailed dynamics of these interactions at the atomic level. Rather, these models use geometric cross-sections to predict whether a particle of radiation, such as a photon or an ion, crossing the cell volume will transfer sufficient energy to cause a break in one or both of the DNA strands [4– 6]. The models do not describe the atomic-level interactions but simply provide the probability that some dose of radiation will cause a population of cells to lose their ability to reproduce.

Graph neural networks (GNNs) are promising machine learning architectures designed to analyze data that can be represented as graphs. These architectures achieved very promising results on a variety of real-world applications, including drug discovery, social network design, and recommender systems.

As graph-structured data can be highly complex, graph-based machine learning architectures should be designed carefully and effectively. In addition, these architectures should ideally be run on efficient hardware that support their computational demands without consuming too much power.

Continue reading “A system integrating echo state graph neural networks and analogue random resistive memory arrays” »

Micron-sized “bow ties,” self-assembled from nanoparticles, form a variety of different curling shapes that can be precisely controlled, a research team led by the University of Michigan has shown.

The development opens the way for easily producing materials that interact with twisted light, providing new tools for machine vision and producing medicines.

While biology is full of twisted structures like DNA, known as chiral structures, the degree of twist is locked in—trying to change it breaks the structure. Now, researchers can engineer the degree of twist.

Our trusted and proven sources were correct once again, as just hours after we broke the news that a Gattaca series is in development at Showtime, The Hollywood Reporter confirmed our exclusive. One of our writers here at Giant Freakin Robot wrote just two weeks ago that the 1997 dystopian sci-fi classic would be perfect as a television series, and it’s amazing how quickly we went from hoping it would happen to confirming that it is. The new series will be coming from the creators of Homeland, Howard Gordan and Alex Gansa.

As noted in our initial report, this is not the first time the film, starring Ethan Hawke, Uma Thurman, and Jude Law, has been optioned as a series. Back in 2009, Sony attempted to turn the movie into a procedural from Gil Grant, a writer on 24 and NCIS. The underrated cult-classic movie is ideal for transforming into a prestige series on a premium network as its themes on transhumanism, genetic manipulation, and a stratified society have become more relevant as technology leaps forwards every year.

In Gattaca, eugenics separates society into “valids” and “in-valids,” even if genetic discrimination is illegal; that hasn’t stopped businesses from profiling, giving the best jobs to the former and only menial labor opportunities to the latter. Ethan Hawke plays Vincent, an in-valid with a heart defect that uses samples from Jude Law’s Jerome Morrow, a paralyzed Olympic champion swimmer that’s also a valid. Using the purloined DNA, Vincent cons his way into a job at Gattaca Aerospace Corporation, eventually being selected as a navigator for a trip to Saturn’s moon, Titan.

A new University of Illinois project is using advanced object recognition technology to keep toxin-contaminated wheat kernels out of the food supply and to help researchers make wheat more resistant to fusarium head blight, or scab disease, the crop’s top nemesis.

“Fusarium head blight causes a lot of economic losses in wheat, and the associated toxin, deoxynivalenol (DON), can cause issues for human and animal health. The disease has been a big deterrent for people growing wheat in the Eastern U.S. because they could grow a perfectly nice crop, and then take it to the elevator only to have it get docked or rejected. That’s been painful for people. So it’s a big priority to try to increase resistance and reduce DON risk as much as possible,” says Jessica Rutkoski, assistant professor in the Department of Crop Sciences, part of the College of Agricultural, Consumer and Environmental Sciences (ACES) at Illinois. Rutkoski is a co-author on the new paper in the Plant Phenome Journal.

Increasing resistance to any crop disease traditionally means growing a lot of genotypes of the crop, infecting them with the disease, and looking for symptoms. The process, known in plant breeding as phenotyping, is successful when it identifies resistant genotypes that don’t develop symptoms, or less severe symptoms. When that happens, researchers try to identify the genes related to disease resistance and then put those genes in high-performing hybrids of the crop.