Lifeboat Foundation

In the 1980s, biologist Dr Michael Rose started to selectively breed Drosophila fruit flies for increased longevity. Today, the descendants of the original Methuselah flies are held by biotech firm Genescient Corporation and live 4.5 times longer than normal fruit flies.

The flies’ increased lifespan is explained by a significant number of systemic genetic changes — but how many of these variations represent lessons that can be used to design longevity therapies for humans? Dr. Ben Goertzel and his bio-AI colleagues at SingularityNET and Rejuve. AI are betting the answer is quite a few.

SingularityNET and Rejuve. AI have launched a partnership with Genescient to apply advanced machine learning and machine reasoning methods to transfer insights gained from the Methuselah fly genome to the human genome. The goal is to acquire new information regarding gene therapies, drugs or nutraceutical regimens for prolonging healthy human life.

Damage to the ends of your chromosomes can create “zombie cells” that are still alive but can’t function, according to our recently published study in Nature Structural and Molecular Biology.

When cells prepare to divide, their DNA is tightly wound around proteins to form chromosomes that provide structure and support for genetic material. At the ends of these chromosomes are repetitive stretches of DNA called telomeres that form a protective cap to prevent damage to the genetic material.

However, telomeres shorten each time a cell divides. This means that as cells divide more and more as you age, your telomeres become increasingly shorter and more likely to lose their ability to protect your DNA.

Speaking at the Longevity Leaders conference earlier this year, King’s College London Professor Georgina Ellison-Hughes shared a fascinating insight into her work to establish the adult heart as a self-renewing organ with regenerative capacity.

Longevity. Technology: The heart is generally considered a “post-mitotic” organ, or one without regenerative capacity. As we age and encounter chronic disease, senescent cells accumulate in the heart, just as they do in other tissues and organs. Ellison-Hughes’ work has shown that cellular senescence may impact the efficacy of regenerative therapies, and that senolytics have the potential to rejuvenate the heart’s capacity to regenerate. We caught up with the professor to learn more.

Cellular senescence is one of the nine hallmarks of aging. It occurs when our cells stop reproducing and enter a zombie state where they refuse to die – hanging around and causing problems throughout our bodies. Ellison-Hughes is professor of regenerative muscle physiology at King’s and in 2019 was co-author of a study in Aging Cell, which found that senescent cells impaired regeneration in the human heart.

Down the line, the researchers hope to develop an injectable protein solution that forms a gel inside the body. The ability to design hydrogels with specific functions opens up for a range of possible applications. Such a gel could, for example, be used to achieve a controlled release of drugs into the body. In the chemical industry, it could be fused to enzymes, a form of proteins used to speed up various chemical processes.

“In the slightly longer term, I think injectable gels can become very useful in regenerative medicine,” says the study’s first author Tina Arndt, a PhD student in Anna Rising’s research group at Karolinska Institute. “We have a long way to go, but the fact that the protein solution quickly forms a gel at body temperature and that the spider silk has been shown to be well tolerated by the body is promising.”

The ability of spiders to spin incredibly strong fibers from a silk protein solution in fractions of a second has sparked an interest in the underlying molecular mechanisms. The researchers at KI and SLU have been particularly interested in the spiders’ ability to keep proteins soluble so that they do not clump together before the spinning of the spider silk. They have previously developed a method for the production of valuable proteins which mimics the process the spider uses to produce and store its silk proteins.

To evaluate the accuracy of the models²⁸, we sampled from the BNN or deep ensemble to determine their uncertainty predictions (Extended Data Fig. 3a, b). Correct predictions are oriented toward the lower and higher range of the output, representing greater certainty about samples’ states, whereas incorrect predictions tend towards the 0.5 threshold. We can therefore assume higher confidence in a model’s predictions by removing the predictions in the middle using thresholds. We evaluated a range of thresholds with several models (Extended Data Fig. 3c–f), which show a substantial increase in accuracy due to the ambiguous samples being discarded, including the ensemble of normalized models reaching accuracy of 97.2%. A similar approach was applied to other models, including the IR and RS models (Extended Data Fig. 3g, h), raising accuracy by 10–15%, although this reduces the number of cells considered.

To better understand the development of the senescent phenotype and how nuclear morphology changes over time, we analyzed human fibroblasts induced to senescence by 10 Gy IR and imaged at days 10, 17, 24 and 31. The predictor identifies senescence at all four times points with probability that increases from days 10 to 17 but declines by day 31 (Extended Data Fig. 4a). Interestingly, examining the probability distribution of the predictor it was apparent that a growing peak of nonsenescent cells appear after day 17, suggesting that a small number of cells were able to escape senescence induction and eventually overgrow the senescent cells (Extended Data Fig. 4b). Indeed, when investigating markers of proliferation, we see that over the time course, PCNA declines until day 17, after which the expression starts to return (Extended Data Fig. 4c). p21^Cip1 follows an inverse pattern with stain intensity increasing initially and then declining slightly by day 31 (Extended Data Fig. 4D). We also saw a decrease in DAPI intensity for days 10 and 17, indicating senescence, but a reversion to control level by day 31 (Extended Data Fig. 4e). To confirm that the predictor accurately determined senescence even 31 days after IR, we evaluated if markers of proliferation and senescence correlated with predicted senescence. Accordingly, cells with predicted senescence had higher p21^Cip1 levels, lower PCNA and lower DAPI intensities and vice versa (Extended Data Fig. 4f–h). Morphologically, area and aspect are higher for predicted senescence, whereas convexity is lower (Extended Data Fig. 4i–k). Finally, a simple nuclei count confirms growth, following IR treatment (Extended Data Fig. 4l). Overall, the senescence predictor captures the state during development in agreement with multiple markers and morphological signs.

Senescent cells are associated with the appearance of persistent nuclear foci of the DNA damage markers γH2AX and 53BP1 (refs. ^31,32). Our base data set including control, RS and IR lines were examined for damage foci using high-content microscopy, where we found the mean count for controls to be below 1 for each marker, whereas RS had 4.0 γH2AX and 2.0 53BP1 foci and IR had 3.4 γH2AX and 3.0 53BP1 foci (Fig. 4a, b and Extended Data Fig. 5a). We calculated the Pearson correlation between predicted senescence and γH2AX and 53BP1 foci counts and found that across all conditions, there is a moderately strong correlation of around 0.5 (Fig. 4c). This association is also visible when simply plotting foci counts and senescence prediction, which shows predicted senescence flipping from low to high, along with shifts in foci counts (Extended Data Fig. 5b). Our feature reduction masked internal nuclear structure, but it is nonetheless notable that senescence prediction correlates with foci count. We also compared the correlation between predicted senescence and area, where we see a correlation of around 0.5. In sum, there is a considerable correlation between foci counts and senescence.

AgeX Therapeutics, a preclinical biotech looking to turn back the clock on aging, may have to wind down, announcing “substantial doubt” about its ability to continue as money runs dry and debts mount.

The California biotech made $12,000 in revenue for the second quarter and recorded $1.6 million in operating expenses over the same period, according to financial results posted August 12.

During the first quarter, the biotech borrowed the final half million of credit available under a 2020 agreement with Juvenescence—a separate anti-aging biotech—and entered a new deal in which Juvenescence will provide $13.2 million in credit for a year. AgeX drew an initial $8.2 million of the line of credit and used $7.2 million to refinance the principal and the loan origination fees under a 2019 loan agreement with Juvenescence.

Circa 2021 immortality of the pancreas by inducing pluripotent cells of the pancreas.

A microwell chip facilitates the single-cell characterization of the differentiation of aggregates of human induced pluripotent stem cells into pancreatic duct-like organoids and the discovery of secreted markers of pancreatic carcinogenesis.

Circa 2000

Immortal epithelial cell lines were previously established after transduction of the HPV16-E6E7 genes into primary cultures of normal pancreatic duct epithelial cells. Single clones were isolated that demonstrated near normal genotype and phenotype. The proliferation of HPDE6-E6E7c7 and c11 cells is anchorage-dependent, and they were nontumorigenic in SCID mice. The cell lines demonstrated many phenotypes of normal pancreatic duct epithelium, including mRNA expression of carbonic anhydrase II, MUC-1, and cytokeratins 7, 8, 18, and 19.

August 9, 2022 – A new national poll of registered voters in the United States demonstrates broad bipartisan support for advancing research into longevity treatments that would extend healthy human lifespan.