Lifeboat Foundation: Safeguarding Humanity
Toggle light / dark theme

Blog

Category: genetics – Page 171

Researchers have taught an AI to make artificial genomes — possibly overcoming the problem of how to protect people’s genetic information while also amassing enough DNA for research.

Generative adversarial networks (GANs) pit two neural networks against each other to produce new, synthetic data that is so good it can pass for real data. Examples have been popping up all over the web — generating pictures and videos (a la “this city does not exist”). AIs can even generate convincing news articles, food blogs, or human faces (take a look here for a complete list of all the oddities created by GANs).

Now, researchers from Estonia are going more in-depth with deepfakes of human DNA. They created an algorithm that repeatedly generates the genetic code of people that don’t exist.

Read more | >

While the world has been captivated by recent advances in artificial intelligence, researchers at Johns Hopkins University have identified a new form of intelligence: organoid intelligence. A future where computers are powered by lab-grown brain cells may be closer than we could ever have imagined.

What is an organoid? Organoids are three-dimensional tissue cultures commonly derived from human pluripotent stem cells. What looks like a clump of cells can be engineered to function like a human organ, mirroring its key structural and biological characteristics. Under the right laboratory conditions, genetic instructions from donated stem cells allow organoids to self-organize and grow into any type of organ tissue, including the human brain.

Although this may sound like science-fiction, brain organoids have been used to model and study neurodegenerative diseases for nearly a decade. Emerging studies now reveal that these lab grown brain cells may be capable of learning. In fact, a research team from Melbourne recently reported that they trained 800,000 brain cells to perform the computer game, Pong (see video). As this field of research continues to grow, researchers speculate that this so-called “intelligence in a dish” may be able to outcompete artificial intelligence.

Read more | >

The potential of satellite-based synthetic biology and genetic engineering to revolutionize healthcare is becoming increasingly clear. Recent advances in the field have opened up a world of possibilities for medical professionals and researchers, allowing them to diagnose and treat diseases more effectively and efficiently than ever before.

Satellite-based synthetic biology and genetic engineering have already been used to develop treatments for a variety of conditions, including cancer, heart disease, and neurological disorders. By using satellite-based techniques, researchers can quickly and accurately identify genetic mutations and other abnormalities in a patient’s DNA. This allows them to develop personalized treatments that are tailored to the individual’s specific needs.

The use of satellite-based synthetic biology and genetic engineering also has the potential to reduce healthcare costs. By identifying genetic mutations and other abnormalities at an early stage, doctors can avoid costly and unnecessary treatments. This could lead to significant savings for both patients and healthcare providers.

Read more | >

Join us on Patreon! https://www.patreon.com/MichaelLustgartenPhD

Discount Links:
NAD+ Quantification: https://www.jinfiniti.com/intracellular-nad-test/
Use Code: ConquerAging At Checkout.

Green Tea: https://www.ochaandco.com/?ref=conqueraging.

Oral Microbiome: https://www.bristlehealth.com/?ref=michaellustgarten.

Epigenetic Testing: https://trudiagnostic.com/?irclickid=U-s3Ii2r7xyIU-LSYLyQdQ6…M0&irgwc=1
Use Code: CONQUERAGING

At-Home Blood Testing: https://getquantify.io/mlustgarten.

Continue reading “AnthropoAge: Biological Age Prediction Without Blood Testing” | >

What the human genome is lacking compared with the genomes of other primates might have been as crucial to the development of humankind as what has been added during our evolutionary history, according to a new study led by researchers at Yale and the Broad Institute of MIT and Harvard.

The new findings, published April 28 in the journal Science, fill an important gap in what is known about historical changes to the human genome. While a revolution in the capacity to collect data from genomes of different species has allowed scientists to identify additions that are specific to the human —such as a gene that was critical for humans to develop the ability to speak—less attention has been paid to what’s missing in the .

For the new study researchers used an even deeper genomic dive into primate DNA to show that the loss of about 10,000 bits of genetic information—most as small as a few base pairs of DNA—over the course of our differentiate humans from chimpanzees, our closest primate relative. Some of those “deleted” pieces of genetic information are closely related to genes involved in neuronal and cognitive functions, including one associated with the formation of cells in the developing brain.

Read more | >

A team of researchers at the Broad Institute of MIT and Harvard has developed a new approach to next-generation sequencing that detects genetic mutations within single molecules of DNA.

The method, called Concatenating Original Duplex for Error Correction (CODEC), makes next-generation sequencing about 1,000 times more accurate and opens up the possibility of a range of applications including detecting tiny numbers of cancer mutations in , monitoring cancer during and after treatment, and identifying mutations underlying rare diseases, all at relatively low cost. The study appears today in Nature Genetics.

“The beauty of this approach is that it’s not an overhaul of how sequencing is done,” said Viktor Adalsteinsson, senior author on the study and director of the Gerstner Center for Cancer Diagnostics and leader of the Blood Biopsy Team at the Broad. “It’s not something that requires new instrumentation or —it’s a simple set of steps added into existing sample preparation workflows to improve the accuracy of DNA sequencing.”

Read more | >

Why do some people live lawful lives, while others gravitate toward repeated criminal behavior? Do people choose to be moral or immoral, or is morality simply a genetically inherited function of the brain? Research suggests that psychopathy as a biological condition explained by defective neural circuits that mediate empathy, but what does that mean when neuroscience is used as evidence in criminal court? How can understanding neuroscience give us an insight into the actions and behaviors of our political leaders?

Forensic psychiatrist Dr. Octavio Choi https://med.stanford.edu/profiles/ochoi will explore how emerging neuroscience challenges long-held assumptions underlying the basis—and punishment—of criminal behavior.

$5 suggested donation.
If you are able, please support us on Patreon:
https://www.patreon.com/MakeYouThink.
OR
Make a one-time donation to Make You Think, Inc:

Support

Read more | >

Protein-coding sequence differences have failed to fully explain the evolution of multiple mammalian phenotypes. This suggests that these phenotypes have evolved at least in part through changes in gene expression, meaning that their differences across species may be caused by differences in genome sequence at enhancer regions that control gene expression in specific tissues and cell types. Yet the enhancers involved in phenotype evolution are largely unknown. Sequence conservation–based approaches for identifying such enhancers are limited because enhancer activity can be conserved even when the individual nucleotides within the sequence are poorly conserved. This is due to an overwhelming number of cases where nucleotides turn over at a high rate, but a similar combination of transcription factor binding sites and other sequence features can be maintained across millions of years of evolution, allowing the function of the enhancer to be conserved in a particular cell type or tissue. Experimentally measuring the function of orthologous enhancers across dozens of species is currently infeasible, but new machine learning methods make it possible to make reliable sequence-based predictions of enhancer function across species in specific tissues and cell types.

Read more | >