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One of the hallmarks of aging, cellular senescence is what happens when aging cells do not die in the usual way (a process known as apoptosis) and start to accumulate in our bodies. The accumulation of these “senescent” cells is implicated in diseases including dementias, atherosclerosis, cancers, diabetes and arthritis. But senescence is not just part of the aging process – it tends to occur in individuals who develop frailty and multiple illnesses, and this can occur at any point during life.

In 2015, a team of researchers at the Mayo Clinic, led by Dr James L Kirkland, published a seminal paper in Aging Cell that introduced a new class of drugs called senolytics. Based on the idea that removing senescent cells may enhance human healthspan, these drugs were identified based on their ability to selectively target and eliminate those cells.

Longevity. Technology: Since the discovery of the first senolytics, hundreds of others have since been identified or created, and senotherapeutics is now one of the hottest areas in longevity, with a host of clinical trials under way and companies pursuing senolytic therapies for a range of age-related conditions. But what does the man who started it all think about the therapeutic field he helped create? In the first of two articles, we bring you Dr Kirkland’s unique perspective on the world of senolytics.

This video is the 1st of a series of “What is Aging” webinars that aims to unravel what aging is, how we age, why we age, and how to reverse it.

We welcome Jason C. Mercurio, MFE, Dr. Jose Cordeiro, and Dr. Ian Hale to discuss the topic.

Thanks to our transhumanist influencers including:
@G. Stolyarov II @Ray Kurzweil 2017 @The Singularity is Near.
#ageless #agelesspartners #agereveal #longevity #biohacking #biotechnology #agingbackwards.

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“The idea was to build a society like we have for all the other disciplines in medicine,” says Evelyne Bischof, a professor of medicine at Shanghai University of Medicine and Health Sciences and the inaugural vice president of the society. She has previously spearheaded educational efforts with Zhavoronkov and others, co-developing a formal course on longevity medicine for doctors. At the ARDD meeting, Bischof announced their course had just received continuing medical education (CME) accreditation from the American Medical Association.

“Longevity medicine is crystallizing as a discipline,” says Andrea Maier, an internal medicine specialist and geriatrician at National University of Singapore who is serving as the society’s inaugural president. One thing that’s not yet clear, several experts told me, is whether longevity will come to be established as a sub-discipline of geriatrics or internal medicine or whether it will become a separate medical specialty unto itself.

“Whichever way it goes,” Maier says, “it’s happening.”

Building A Clinically Credible Platform For Longevity Medicine — Prof. Dr. Andrea Maier MD, PhD, National University of Singapore, Centre for Healthy Longevity.


Professor Dr. Andrea B. Maier, MD, Ph.D., is the Oon Chiew Seng Professor in Medicine, Healthy Ageing and Dementia Research, and Co-Director of the Centre for Healthy Longevity, at the National University Of Singapore (https://discovery.nus.edu.sg/19564-andrea-britta-maier).

Professor Maier also holds professorship appointments at VU University Medical Centre — https://research.vu.nl/en/persons/andrea-maier, Amsterdam, Netherlands, and University of Melbourne (https://findanexpert.unimelb.edu.au/profile/773728-andrea-maier), Australia, as well as is Director of Medicine and Community Care at the Royal Melbourne Hospital, Australia.

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Free Video Series: Open Questions in AI and Neuroscience:

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Show notes: https://braininspired.co/podcast/103/

Randal, Ken, and I discuss a host of topics around the future goal of uploading our minds into non-brain systems, to continue our mental lives and expand our range of experiences. The basic requirement for such a subtrate-independent mind is to implement whole brain emulation. We discuss two basic approaches to whole brain emulation. The “scan and copy” approach proposes we somehow scan the entire structure of our brains (at whatever scale is necessary) and store that scan until some future date when we have figured out how to us that information to build a substrate that can house your mind. The “gradual replacement” approach proposes we slowly replace parts of the brain with functioning alternative machines, eventually replacing the entire brain with non-biological material and yet retaining a functioning mind.

Michael Levin is a biologist at Tufts University working on novel ways to understand and control complex pattern formation in biological systems. Please support this podcast by checking out our sponsors:
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EPISODE LINKS:
Michael’s Twitter: https://twitter.com/drmichaellevin.
Michael’s Website: https://drmichaellevin.org.
Michael’s Papers:
Biological Robots: https://arxiv.org/abs/2207.00880
Synthetic Organisms: https://tandfonline.com/doi/full/10.1080/19420889.2021.2005863
Limb Regeneration: https://science.org/doi/10.1126/sciadv.abj2164

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Full episodes playlist: https://www.youtube.com/playlist?list=PLrAXtmErZgOdP_8GztsuKi9nrraNbKKp4
Clips playlist: https://www.youtube.com/playlist?list=PLrAXtmErZgOeciFP3CBCIEElOJeitOr41

OUTLINE:

Foresight Biotech & Health Extension Meeting sponsored by 100 Plus Capital.
Program & apply to join: https://foresight.org/biotech-health-extension-program/

Jennifer Garrison, Buck Institute.
Reframing Health and Aging through the Lens of Reproduct.

Jennifer Garrison is an assistant professor at the Buck Institute for Research on Aging and also holds appointments in the Department of Cellular and Molecular Pharmacology at University of California, San Francisco (UCSF) and the Davis School of Gerontology at the University of Southern California. During her doctoral studies at UCSF with Jack Taunton, she discovered the molecular target of a natural product and elucidated a novel mechanism by which small molecules can regulate protein biogenesis.

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Brain-age (BA) estimates based on deep learning are increasingly used as neuroimaging biomarker for brain health; however, the underlying neural features have remained unclear. We combined ensembles of convolutional neural networks with Layer-wise Relevance Propagation (LRP) to detect which brain features contribute to BA. Trained on magnetic resonance imaging (MRI) data of a population-based study (n = 2,637, 18–82 years), our models estimated age accurately based on single and multiple modalities, regionally restricted and whole-brain images (mean absolute errors 3.37–3.86 years). We find that BA estimates capture ageing at both small and large-scale changes, revealing gross enlargements of ventricles and subarachnoid spaces, as well as white matter lesions, and atrophies that appear throughout the brain. Divergence from expected ageing reflected cardiovascular risk factors and accelerated ageing was more pronounced in the frontal lobe. Applying LRP, our study demonstrates how superior deep learning models detect brain-ageing in healthy and at-risk individuals throughout adulthood.