Lifeboat Foundation

A new tool helps researchers explore the types of cells that make up brain organoids — clusters of cells that can mimic the basic structure, function and development of different parts of the brain.

The software, detailed in Cell Stem Cell, maps information about when and where genes are expressed in brain organoids onto a reference atlas of the developing mouse brain. Scientists can use the resulting overlay to develop organoids that better recapitulate the developing brain, the team says, or to uncover the effects of gene mutations and other experimental perturbations.

Brain organoids derived from the cells of people with conditions such as autism have proved useful in capturing neuronal abnormalities. But the findings are muddied by methodological differences in how researchers develop these lab-grown blobs. Advanced techniques to profile gene expression in single cells have made it easier to identify the cell types in any given organoid. But it’s remained difficult to map those cell types onto different brain regions.

Three pioneering technologies have forever altered how researchers do their work and promise to revolutionize medicine, from correcting genetic disorders to treating degenerative brain diseases.

Some mutations that disable SCN2A, one of the genes most strongly linked to autism, can unexpectedly make neurons hyperexcitable, a study in mice shows. The findings may help explain why a sizeable proportion of autistic children with mutations in SCN2A experience epileptic seizures.

Deleterious mutations in an autism-associated gene can make neurons hyperexcitable, raising the risk of epileptic seizures.

A couple people from TRIM are in TRIM-X to see how it works a second time.

In this video Dr. Fahy discusses what we can do to make the most of our thymus without the growth hormone treatment, what the timing makes sense for rejuvenation of the thymus and whether the thymus is tied to the other hallmarks of aging.

Continue reading “How To Improve On Our Thymus Health | Dr Greg Fahy Episode 5” »

Driver Clocks And Longevity — Dissecting True Functional “Drivers” Of Aging Phenotypes — Dr. Daniel Ives Ph.D., Founder and CEO — Shift Bioscience Ltd.

Dr. Daniel Ives, Ph.D. is Founder and CEO of Shift Bioscience Ltd. (https://shiftbioscience.com), a biotech company making drugs for cellular rejuvenation in humans through the application of machine-learning ‘driver’ clocks to cellular reprogramming, and is the scientific founder who first discovered the gene shifting targets upon which the Shift drug discovery platform is based.

Continue reading “Dr. Daniel Ives, Ph.D. — Founder and CEO — Shift Bioscience Ltd. — Driver Clocks And Longevity” »

Upon an otherwise unruly landscape of choppy sea and craggy peaks, the salmon farms that dot many of Norway’s remote fjords impose a neat geometry. The circular pens are placid on the surface, but hold thousands of churning fish, separated by only a net from their wild counterparts. And that is precisely the conundrum. Although the pens help ensure the salmon’s welfare by mimicking the fish’s natural habitat, they also sometimes allow fish to escape, a problem for both the farm and the environment.

In an attempt to prevent escaped fish from interbreeding with their wild counterparts and threatening the latter’s genetic diversity, molecular biologist Anna Wargelius and her team at the Institute of Marine Research in Norway have spent years working on ways to induce sterility in Atlantic salmon. Farmed salmon that cannot reproduce, after all, pose no threat to the gene pool of wild stocks, and Wargelius has successfully developed a technique that uses the gene-editing technology Crispr to prevent the development of the cells that would otherwise generate functioning sex organs.

Continue reading “A sterile solution: How Crispr could protect wild salmon” »

Hundreds of genetic loci associated with age at menopause, combined with experimental evidence in mice, highlight mechanisms of reproductive ageing across the lifespan.

Summary: Blood tests revealed specific epigenetic biomarkers for schizophrenia. Researchers applied machine learning to analyze the CoRSIVs region of the human genome to identify the schizophrenia biomarkers. Testing the model with an independent data set revealed the AI technology can detect schizophrenia with 80% accuracy.

Source: Baylor College of Medicine.

An innovative strategy that analyzes a region of the genome offers the possibility of early diagnosis of schizophrenia, reports a team led by researchers at Baylor College of Medicine. The strategy applied a machine learning algorithm called SPLS-DA to analyze specific regions of the human genome called CoRSIVs, hoping to reveal epigenetic markers for the condition.

Using a technique called optogenetics, researchers added light-sensitive proteins to the man’s retina, giving him a blurry view of objects.