Parth Shah

Spot on. This is a Trillion dollar idea that will transform healthcare delivery.

Jensen Huang on how to structure a company: "Don't worry about how other companies' or charts look. You start from first principles. Remember what an organization is designed to do. The organizations of the past where there was a king, you know, CEO, and then you have all these, you know, the royal subjects, you know, the royal court, and then e-staff. And then you keep working your way down. Eventually, they're employees. But the reason why it was designed that way is because they wanted the employees to have as little information as possible because the fundamental purpose of the soldiers is to die in the field of battle, to die without asking questions. You guys know this. I only have 30,000 employees. I would like none of them to die. I would like them to question everything. Does that make sense? And so the way you organize in the past and the way you organize today is very different. Second, the question is, what does NVIDIA build? An organization is designed so that we could build whatever it is we build better. And so if we all build different things, why are we organized the same way? Why would this organizational machinery be exactly the same, irrespective of what you build? It doesn't make any sense. You build computers, you organize this way. You build health care services, you build the same way. It makes no sense whatsoever. And so you have to go back to first principles. Just ask yourself, what kind of machinery? What is the input? What is the output? What are the properties of this environment? What is the forest that this animal has to live in? What are its characteristics? Is it stable most of the time? You're trying to squeeze out the last drop of water? Or is it changing all the time, being attacked by everybody? And so you've got to understand, if you're the CEO, your job is to architect this company. That's my first job, to create the conditions by which you can do your life's work. And the architecture has to be right. And so you have to go back to first principles and think about those things. And I was fortunate that when I was 29 years old, I had the benefit of taking a step back and asking myself, how would I build this company for the future, and what would it look like? And what's the operating system, which is called culture? What kind of behavior do we encourage, enhance? And what do we discourage and not enhance? So on and so forth..."

The model of gene expression taught in school is highly misleading! Transcription factors are proteins that bind to DNA and then help repress, or activate, the expression of genes. Cells have hundreds of different types of transcription factors, each tuned to regulate different genes based on short snippets of DNA located near those genes. The basic model, taught in school, says that these transcription factor proteins float around the cell and, when they bump into a DNA sequence, either latch onto it strongly (CORRECT SITE!) or fall off quickly (WRONG SITE) and keep searching. All the other DNA in a cell is basically abstracted away as unimportant or irrelevant; mere background noise. But again, this model is naive! And a new paper, published in Cell, beautifully shows how the sequences SURROUNDING a transcription factor's binding site also matter a great deal. This won't be surprising to many biologists, as "cracks" in the standard two-state model began emerging decades(?) ago. Biologists have tagged transcription factors with fluorescent tags and then watched them move around living cells. And they have noticed that when transcription factors land in a "wrong" location in the genome, they skip or hop to a nearby location and repeat this until finally connecting with the "correct" sequence. So in other words, there are actually three states that a transcription factor can exist in: free-floating, "searching", or "bound." (More technically, transcription factors first do a 3D search, then latch onto DNA and do a 1D search to find the correct location.) For this new paper, though, scientists exhaustively quantified *how* the sequences flanking a transcription factor binding site influence the search of the protein. They did a huge in vitro experiment, wherein they placed a specific transcription factor with a known binding site, called KLF1, in a huge library of 11,812 different DNA sequences. These sequences had mutated "core" binding sites and variations in the flanking sequences. They also prepared negative controls. Then, these researchers measured the binding kinetics of KLF1 with each sequence to understand which bases in the flanking sites impact the 1D search. What they found is that KLF1 has a basically flat disocciation rate from its core sequence, but that the PROBABILITY that it finds this sequence depends a lot on the surrounding context. Even mutations located dozens of bases away from the core site matter a lot, either pushing KLF1 to "hop" faster to find the site, or "trapping" KLF1 and slowing down its search. These flanking sequences can cause up to a 40-fold variation in the affinity of a transcription factor for its target site! This is just one small part of the paper, though, so I encourage anyone interested to read the whole thing. It is challenging throughout.