Inherited memory was a popular theory in the past, inspiring stories like Frank Herbert’s Dune, but could it be possible with alien biologies or cybernetic civilizations, and what is it? Music Courtesy of: Epidemic Sound http://epidemicsound.com/creator
Plant genomics has come a long way since Cold Spring Harbor Laboratory (CSHL) helped sequence the first plant genome. But engineering the perfect crop is still, in many ways, a game of chance. Making the same DNA mutation in two different plants doesn’t always give us the crop traits we want. The question is why not? CSHL plant biologists just dug up a reason.
CSHL Professor and HHMI Investigator Zachary Lippman and his team discovered that tomato and Arabidopsis thaliana plants can use very different regulatory systems to control the same exact gene. Incredibly, they linked this behavior to extreme genetic makeovers that occurred over 125 million years of evolution.
The scientists used genome editing to create over 70 mutant strains of tomato and Arabidopsis thaliana plants. Each mutation deleted a piece of regulatory DNA around a gene known as CLV3. They then analyzed the effect each mutation had on plant growth and development. When the DNA keeping CLV3 in check was mutated too much, fruit growth exploded. They published their findings in PLoS Genetics.
Paclitaxel is the world’s best-selling plant-based anticancer drug and one of the most effective anticancer drugs over the past 30 years. It is widely used in the treatment of various types of cancer, including breast cancer, lung cancer, and ovarian cancer.
In the late 1990s and early 21st century, the annual sales of paclitaxel exceeded $1.5 billion and reached $2.0 billion in 2001, making it the best-selling drug in 2001. In 2019, the market for paclitaxel and its derivatives was approximately $15 billion, and it is expected to reach $20 billion by 2025.
As an anticancer drug, the molecular structure of paclitaxel is extremely complex, with highly oxidized, intricate bridged rings and 11 stereocenters, making it widely recognized as one of the most challenging natural products to synthesize chemically. Since the first total synthesis of paclitaxel was reported by the Holton and Nicolaou research groups in 1994, more than 40 research teams have been engaged in the total synthesis of paclitaxel.
Inspired by nature, nanotechnology researchers have identified ‘spontaneous curvature’ as the key factor determining how ultra-thin, artificial materials can transform into useful tubes, twists and helices.
Greater understanding of this process—which mimics how some seed pods open in nature—could unlock an array of new chiral materials that are 1,000 times thinner than a human hair, with the potential to improve the design of optical, electronic and mechanical devices.
Chiral shapes are structures that cannot be superimposed on their mirror image, much like how your left hand is a mirror image of your right hand but cannot fit perfectly on top of it.
Plate tectonics is not something most people would associate with Mars. In fact, the planet’s dead core is one of the primary reasons for its famous lack of a magnetic field. And since active planetary cores are one of the primary driving factors of plate tectonics, it seems obvious why that general conception holds.
However, Mars has some features that we think of as corresponding with plate tectonics—volcanoes. A new paper from researchers at the University of Hong Kong (HKU) looks at how different types of plate tectonics could have formed different types of volcanoes on the surface of Mars.
Continue reading “Mars had its own version of plate tectonics” »
When it was first discovered in 2004, Apophis was identified as one of the most dangerous asteroids in that there was a risk that it could impact Earth. But that impact assessment changed over the years after astronomers tracked Apophis, also known as asteroid 99,942, and its orbit became better determined, and it became clear that it was on course to miss our planet.
In a study published in The Astrophysical Journal, researchers from the Yunnan Observatories of the Chinese Academy of Sciences depicted a complete physical image of the anomalous heating in the upper atmosphere of the sun (the solar corona and the solar chromosphere).
The enigma of the corona’s anomalous heating stands as one of the eight challenges in modern astronomy. Similarly, the anomalous heating of the chromosphere continues to baffle solar physicists.
Observations gleaned from large telescopes and satellites have revealed potential magnetic activities that could be the cause of this heating. Theoretical research has proposed various heating modes, yet none have been definitively proven to be the cause. As it stands, our understanding of how the sun’s upper atmosphere is heated remains incomplete.
New research has identified iron deficiencies in the blood as a major culprit in long COVID cases.
A new report from the University of Cambridge was able to connect that low iron levels contributed to inflammation and anemia and halted healthy red blood cell production in patients just two weeks after being diagnosed with COVID-19.
Many of those individuals reported having long COVID — which has recently been associated with a frightening IQ loss from brain fog — within months, according to the study, published in Nature Immunology.
Artificial Intelligence (AI) and Deep Learning, with a focus on Natural Language Processing (NLP), have seen substantial changes in the last few years. The area has advanced quickly in both theoretical development and practical applications, from the early days of Recurrent Neural Networks (RNNs) to the current dominance of Transformer models.
Models that are capable of processing and producing natural language with efficiency have advanced significantly as a result of research and development in the field of neural networks, particularly with regard to managing sequences. RNN’s innate ability to process sequential data makes them well-suited for tasks involving sequences, such as time-series data, text, and speech. Though RNNs are ideally suited for these kinds of jobs, there are still problems with scalability and training complexity, particularly with lengthy sequences.
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