“If you lease it like you lease a car, a $30,000 car, your price point per month is 300 bucks,” says author, futurist, investor, doctor, and engineer Peter Diamandis in a recent TechFirst podcast. “And that translates amazingly to $10 a day and 40 cents an hour. So you’ve got labor that’s waiting for whatever your wish is. You know, clean up the house, go mow the lawn, you know, please change the baby’s diapers.”
SMC proteins can reverse direction, reshaping DNA
DNA, or deoxyribonucleic acid, is a molecule composed of two long strands of nucleotides that coil around each other to form a double helix. It is the hereditary material in humans and almost all other organisms that carries genetic instructions for development, functioning, growth, and reproduction. Nearly every cell in a person’s body has the same DNA. Most DNA is located in the cell nucleus (where it is called nuclear DNA), but a small amount of DNA can also be found in the mitochondria (where it is called mitochondrial DNA or mtDNA).
Examples of endosymbiosis are everywhere. Mitochondria, the energy factories in your cells, were once free-living bacteria. Photosynthetic plants owe their sun-spun sugars to the chloroplast, which was also originally an independent organism. Many insects get essential nutrients from bacteria that live inside them. And last year researchers discovered the “nitroplast,” an endosymbiont that helps some algae process nitrogen.
So much of life relies on endosymbiotic relationships, but scientists have struggled to understand how they happen. How does an internalized cell evade digestion? How does it learn to reproduce inside its host? What makes a random merger of two independent organisms into a stable, lasting partnership?
Now, for the first time, researchers have watched the opening choreography of this microscopic dance by inducing endosymbiosis in the lab. After injecting bacteria into a fungus—a process that required creative problem-solving (and a bicycle pump)—the researchers managed to spark cooperation without killing the bacteria or the host. Their observations offer a glimpse into the conditions that make it possible for the same thing to happen in the microbial wild.
LEV is upon us.
OpenAI chief executive Sam Altman, who provided the initial $180mn to seed the start-up, will put in more money in the series A. The company is in talks with family offices, venture capitalists and sovereign wealth funds, as well as a US “hyperscaler” data centre to provide computing power to run the AI models it uses to create and test its treatments.
In partnership with OpenAI, the start-up has built a bespoke AI model that designs proteins to temporarily turn regular cells into stem cells, which it says can reverse their ageing process.
The San Francisco-based biotech will use the money to fund clinical trials for three drugs, including a potential treatment for Alzheimer’s disease, which will be tested in an early stage study in Australia this year. It is also working on drugs for rejuvenating blood and brain cells.
The study’s full text can be found here.
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Engineered enzymes are poised to have transformative impacts across applications in energy, materials, biotechnology, and medicine. Recently, machine learning has emerged as a useful tool for enzyme engineering. Now, a team of bioengineers and synthetic biologists says they have developed a machine-learning guided platform that can design thousands of new enzymes, predict how they will behave in the real world, and test their performance across multiple chemical reactions.
Their results are published in Nature Communications in an article titled, “Accelerated enzyme engineering by machine-learning guided cell-free expression,” and led by researchers at Stanford University and Northwestern University.
“Enzyme engineering is limited by the challenge of rapidly generating and using large datasets of sequence-function relationships for predictive design,” the researchers wrote. “To address this challenge, we develop a machine learning (ML)-guided platform that integrates cell-free DNA assembly, cell-free gene expression, and functional assays to rapidly map fitness landscapes across protein sequence space and optimize enzymes for multiple, distinct chemical reactions.”
AI is redefining healthcare by predicting breast cancer years early, saving lives and empowering proactive care.
A study by the University of the Basque Country (UPV/EHU) demonstrates that the drug WIN55,212–2 protects the brain and reverses early cognitive damage caused by dementia, while also explaining its mechanism of action.
Over two decades of research conducted by the Neurochemistry and Neurodegeneration group at UPV/EHU, led by Dr. Rafael Rodríguez-Puertas, has uncovered a promising pathway for developing therapies aimed at improving memory in cases of cognitive impairment caused by neurodegenerative diseases like Alzheimer’s.
Alzheimer’s disease is a progressive neurological disorder that primarily affects older adults, leading to memory loss, cognitive decline, and behavioral changes. It is the most common cause of dementia. The disease is characterized by the buildup of amyloid plaques and tau tangles in the brain, which disrupt cell function and communication. There is currently no cure, and treatments focus on managing symptoms and improving quality of life.
A research team at KAIST has identified the core gene expression networks regulated by key proteins that fundamentally drive phenomena such as cancer development, metastasis, tissue differentiation from stem cells, and neural activation processes. This discovery lays the foundation for developing innovative therapeutic technologies.
A joint research team led by Professors Seyun Kim, Gwangrog Lee, and Won-Ki Cho from the Department of Biological Sciences has uncovered essential mechanisms controlling gene expression in animal cells.
The findings were published on January 7 in the journal Nucleic Acids Research in a paper titled “Single-molecule analysis reveals that IPMK enhances the DNA-binding activity of the transcription factor SRF.”
Cancer cells need to acquire a different metabolic state than that of non-tumor cells in order to proliferate, invade, and metastasize. During cancer progression, cancer cells encounter various kinds of metabolic stress. First, tumor microenvironments are generally hypoxic and acidic and have a distinct nutrient composition compared to non-tumor tissues from the primary site, which forces cancer cells to adapt in order to grow and invade in these environments. Second, to enter and survive in vessels, cancer cells must reprogram their metabolic state, allowing for anchorage-independent growth that induces extensive oxidative stress in cancer cells. Finally, once cancer cells colonize other organs, they must adapt to quite distinct metabolic environments than those present in primary sites [1]. Overall, because cancer cells need to reprogram their metabolic state during each step of cancer progression, metabolic reprogramming has been recognized as one of the hallmarks of cancer [2].
Elucidating the mechanisms underlying metabolic reprogramming during cancer progression can reveal the metabolic vulnerabilities of cancer cells. This may ultimately result in the identification of new therapeutic targets for cancer and improvement of patients’ prognosis. In this review, we describe each step of the metabolic reprogramming that occurs in cancer cells during cancer progression, including during growth and invasion in primary sites, survival in vessels, and colonization of other organs. Finally, we also describe emerging therapeutic strategies that target cancer-specific metabolism.