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Timestamps:

- What Causes Aging and Why It Happens 03:00.
- How to Slow Down the Aging Process 08:57.
- Why Do Sirtuin Genes Promote Longevity 11:50.
- Xenohormesis and Resveratrol 13:55
- What is NAD and How It Affects Aging 18:55.
- Different Types of NAD Boosters 20:46
- Signs of Aging 25:00
- How Dr Sinclair Exercises 29:25
- Metformin, mTOR, and Insulin 34:00
- What’s the Upper Limit for Human Lifespan 39:58.
- What Area of Research Is Most Promising 43:58.

David Sinclair Lifespan Book: https://amzn.to/2nb1dds

Use Code MZFALL2019 for a 25% Discount for Bioptimizers Masszymes Digestive Enzymes: https://bit.ly/30PYUud

Podcast About Longevity Pathways: https://www.youtube.com/watch?v=4mDPEoyKQSg

Breast cancer is the second most common cancer diagnosed in women in the United States, right behind skin cancer. But how far have we come in understanding this disease?
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While breast cancer largely affects women, it can also occur in men. Fortunately, thanks to awareness, early detection, and research, survival rates have increased. But, there’s still a lot to learn, so Seeker sat down with Professor Donald McDonnell from the Duke School of Medicine to find out more.

So what exactly is breast cancer?

Breast cancer affects the cells in the tissue of the breast. It starts when these cells develop abnormally and begin to divide and accumulate rapidly, eventually forming a lump or mass.

Under the breast cancer umbrella, there are three major types: estrogen receptor-positive breast cancer, HER2-positive breast cancer, and triple-negative breast cancers. They’re all different, they progress differently, and the treatments for them vary.

While knowing the breakdown of the most common types of breast cancer is a start, there are also factors that can put someone at a greater risk of contracting this disease.

He lay in a hospital bed at the University of Arkansas, stricken with a rare disease. His blood platelet count was so low that even a slight bump to his body could trigger a lethal brain bleed. A doctor told him to write his living will on a piece of paper.

Fajgenbaum was rushed to a CT scan. Tears streamed down his face and fell on his hospital gown. He thought about the first patient who’d died under his care in medical school, and how her brain had bled in a similar way from a stroke.

He didn’t believe he’d live out the scan.

It was a pleasure speaking to Dr. Ronald Kohanski at the 2019 Ending Age-Related Diseases conference. Dr. Kohanski joined the field of aging research in 2005 as a Program Officer for the Division of Aging Biology at the National Institute on Aging. He moved on to become its Deputy Director in 2007 and has held the position ever since. Within aging research, he has focused his efforts on the areas of stem cell and cardiovascular biology.

Besides his work at the NIA, Ronald Kohanski is a co-founder and co-leader of the trans-NIH Geroscience Interest Group (GSIG) with which he has organized several summits to discuss and disseminate the group’s focus. The GSIG directs its attention toward aging as the major risk factor for most chronic age-related diseases, and Dr. Kohanski actively encourages researchers to expand studies beyond laboratory animals. He underwrites the importance of addressing the basic biology of aging explicitly in human and non-laboratory animal populations. He believes that age should be considered a fundamental parameter in research that uses animal models of chronic disease.

Dr. Kohanski was trained in the field of biochemistry. He received his PhD from the University of Chicago in 1981, after which he conducted a postdoctoral fellowship with M. Daniel Lane at the Johns Hopkins University School of Medicine. He held a faculty position at the Mount Sinai School of Medicine for 17 years before returning to Johns Hopkins as a faculty member and researcher in the areas of enzymology and developmental biology of the insulin receptor.

Dr. Qingsong Zhu, the COO of Insilico Medicine, discussed the use of deep learning in creating biomarkers for aging. Initially discussing existing clocks and the problems with animal translation, he went on to discuss what sorts of markers are ideal for age-related research and the details of training and testing a model that works with these markers, showing that a deep model compares favorably to other models.

He also used his model to show that smoking does, in fact, cause accelerated aging.