IIRC, this is still true if you exclude the spike protein and use a higher similarity threshold.
Why would one do that? Well, two reasons. First, the spike more variable as it is subject to greater evolutionary pressure as the major component of the viral surface. Second, in coronavirus reverse genetics typically the virus is segmented into multiple pieces, most of which compose the non-spike backbone and a subset which compose the spike protein. This is intentional to enable the swapping of spike proteins. So, if SARS-CoV-2 is spike-swap or spike variant assembly, a RaTG13-like virus could be the "backbone" of SARS-CoV-2.
Moreover, a hypothetical SARS-CoV-2 backbone could exist in the viral sequences list the WIV took down in Sept. 2019. They sequenced RaTG13 a few years prior. The lab's raison d'etre is collecting and sequencing coronaviruses poised for spillover. And, with modern DNA synthesis technology, it's not difficult to print out arbitrary backbone contigs for a viral assembly.
This doesn't test the "epigenetic information theory of aging."
First, there is no survival analysis. How is the mouse younger if it doesn't live longer? Similarly, the OSK "rejuvenated" mice display lower lean muscle mass.
Second, the causality is (willfully?) misinterpreted. The endonuclease used to causes DNA double-strand breaks does NOT directly alter the epigenome. Instead, it induces DNA-damage repair stress. One consequence, of many, is epigenetic (chromatin) dysregulation. DNA damage stress is well known to accelerate aging phenotypes. In fact, David published on how p53 stress from repeated DNA damage - using the same endonuclease setup - initiates a DNA damage response in turn promoting cell-cycle exit and cell elimination [0].
Third, cutting "non-coding" DNA in this case involves cutting specific ribosomes (cell translation machinery). Given that this pressure is constitutive, it's likely that these ribosomes evolve resistance to the nuclease by mutating functional sequences. However, the authors never assessed the mutation and function of these ribosomes.
Lastly, the in vivo AAV transduction efficiency isn't measured. This makes the OSK "rejuvenation" result hard to interpret. All cells get DNA damage (germline edit), but only transduced cells (<10% at best in whole organism) get some OSK exposure. Yet, the whole organism is "rejuvenated"? Is there a positive spill-over from OSK expression?
All the core claims about epigenetic information are either incorrect or grossly misleading. The perturbation, site-specific DNA damage, does not cause only loss of whole-cell epigenetic information. Hard to imagine how this got into Cell. I guess a big name and 20+ figures is all you need these days?
I'm interested to see where this line of research goes. Given that this paper was published in Cell, and the preceding one was published in Nature, I think we can rule out gross negligence in the writeup. I can't speak to all your points, but I can speak to a couple.
There was no claim that the whole mouse was rejuvenated, so far as I can tell. The only metrics they presented on actual rejuvenation were some chemical markers in a couple of organs - heart and liver, IIRC. In a CNN interview published ~5 days ago, Sinclair points out that he hasn't yet figured out how to deliver the OSK to the whole organism - which is presumably why he's only demonstrated rejuvenation at very localized sites. He also mentions that another team has figured it out, and did actually manage to extend a mouse's lifespan (see my other post with the CNN link). Thus,
> How is the mouse younger if it doesn't live longer?
It isn't, because it doesn't, because the study didn't aim to show that.
> Yet, the whole organism is "rejuvenated"?
Again, no. That was not the claim, according to the actual published article.
So I think you missed a couple things. Probably not "willfully". I may have the advantage of you, though, because I did manage to find a copy of the Cell article itself (and I did a bit of additional digging).
I'm surprised the insurance will pay for this. The judgment, and actions by Oberlin's administration, strongly suggest they were acting in bad faith. The college's behavior exceed negligence, the typical threshold in these sort of insurance contracts.
Pretty incredible Oberlin can get out of this considering what other insurers will do to avoid paying for incidents with cause.
Yeah I'm a bit surprised by that, too. The negotiations with their insurer must have been really something. Only thing I can imagine is that they cut some sort of deal that makes it worth the insurance company not trying to fight with them over it. Maybe they have to basically pay it back over time with interest..?
My guess is Oberlin pays them a whole lot of money every year. And will pay increased premiums moving forward. For the insurance company it may be a no brainer to keep their business. It will pay for itself in 5-10 years.
Yeah, I was wondering about that. I would expect that, at a minimum, the insurer would raise Oberlin’s rates and/or required them to make changes in policy.
And who would be that someone else ? There is really only YC, 500 Startups etc. which are highly competitive and accept you only at certain times of the year.
Plus fundraising is extremely time consuming and not every startups wants to throw away 3-6 months.
What you’re saying is explicitly false about the a16z START program, which says its applications are always open on a rolling basis.
Also, as much help as a program like YC can be, if you ‘wait’ between sessions, rather than keep making as much progress as you can, you may not be what they’re looking for. (Longtime YC observers will also know that for good applicants, they sometimes act outside the normal deadlines/cycles.)
Are you using your creativity, & skill in arguing, to convince yourself things are harder than they are?
No one is saying do nothing between applications. Just pointing out that it takes time to apply, opportunities coming around a few times a year and for many startups lack of funding can hurt/kill them.
The time it takes to apply for these seed programs is days not months. Many (including a16z START & 500startups) don't limit applications to "a few times a year" nor "accept you only at certain times of the year".
And the 'etc' of your claim "[t]here is really only YC, 500 Startups etc" hides a ton of options, including this a16z START program, programs from other VCs, TechStars, & a world of other seed-level options from other individual, syndicate (AngelList), or regionally-motivated investors. And, plenty have always-open rolling, or diverse staggered, investment windows.
So you never have to "throw away 3-6 months" or "wait 3-6 months" if you're making demonstrable progress on a good concept.
(Sure, once you've got a big burn rate, fundraising is likely to be a year-round time-suck with many-month closing cycles. But that's not the "even if you don’t yet have a fully formed idea and haven’t yet quit your day job" point this early-seed "market" targets.)
there are thousands of pre-seed investors at this point
The advice I got, which helped me: Series A intros come from Seed investors. Seed intros come from domain specialist angels. So start with angels who know your niche.
If you don't know how to do that, join a pre-seed coaching program like https://www.lindsayt.com/ this costs $1000 for 6 months of weekly calls and comes with tons of training that you don't realize you need, and will put you into contact with dozens of other founders.
Never thought of this distinction before! Thanks for making this distinction.
This seems to hold in other contexts. People tend to tolerate price discrimination at an aggregate level (e.g. senior/student discounts) but loathe individual-level price discrimination (e.g. college tuition). I wonder if it's the unfairness or uncertainty
There a quite a few things missing from this paper that would make it a good a good drug discovery paper.
First, they didn't discover a drug - they found a hit. 30 days from target to hit using conventional high-throughput biochemical screening would take 2-4 months. So, this is 3x faster, but that's not the rate limiting step. Validation and in vivo studies will take >4 mo and 1-12mo respectively.
Second, if we take this as a "we found a hit" paper, I want to know how specific your hit is. This would be one of the major advantages of using AF2 - screen against related proteins with some structural or functional similarity. This is the time intensive and oft overlooked part of good in vitro screening campaigns. Potency is nice (although 9 μM isn't impressive), but ultimately selectivity is paramount when targeting a class of proteins with well conserved binding sites, like kinases. If they found a promiscuous CDK inhibitor that happens to hit CDK20, then I bet there are tons of previously reported promiscuous CDK inhibitors that will hit CDK20 too.
Third, this paper is surprising because it exploits none of the cool new things AF2 could enable. In addition to what you mention above, the authors could have tried to counter screen (much faster in silico!), find an allosteric inhibitor, identify a PPI/complex inhibitor, or take a leap by generating a SAR series in silico and validating a few selected compounds in vitro.
Overall, this paper seems both incremental and misdirected. Saving 2 months in the discovery phase, pre-IP, is worth ~0. Not sure anyone there has much experience developing drugs. Hits are nice, but rarely the hard part. However, a hit on a protein from a structurally divergent class would be a major accomplishment.
NIH likely funds 2/3rds of US biomedical research and ~1/3rd of global biomedical research by dollar value [0]. That link lists other big sources (ERC, MRC, US DoD, HHMI). My sense is that this landscape will change rather quickly with pandemic-inspired biomedical/defense initiatives and more private institutes in the US.
Moreover, NIH funding, due to its central role in supporting biomedical research, is often necessary for getting a tenured PI position. Many high caliber R1 schools require multiple R01 NIH grants for tenure. Often private funding sources are less valuable to universities because they pay lower indirect rates (<10% vs >40%) on sponsored research. As institutions are so dependent on NIH funding, the NIH can exert influence far beyond the research it funds directly.
Somewhat surprised asymmetric organocatalysis was awarded over asymmetric photocatalysis or photoredox chemistry. Photocatalysis is newer, has more demonstrated use cases, and holds more promise.
The list price will nearly always be a multiple of your cost with insurance. The issue here is that insurers have provisions in their network contracts that prevent providers from publically advertising lower prices than what's charged to the insurer, which mandates discounting. In many other industries, these most favored nation arrangements are considered anti-competitive and, thus, illegal.
Large hospital systems totally separate business and care, so it can be difficult to negotiate a discount. Smaller and independent providers are often more accommodating. However, you need to ask for a discount, you can't simply offer to pay cash (i.e. "If I pay cash, can I get 40% off"). The providers can counter your offer, but can't discount you off the bat or else they invite legal action from insurers.
Why would one do that? Well, two reasons. First, the spike more variable as it is subject to greater evolutionary pressure as the major component of the viral surface. Second, in coronavirus reverse genetics typically the virus is segmented into multiple pieces, most of which compose the non-spike backbone and a subset which compose the spike protein. This is intentional to enable the swapping of spike proteins. So, if SARS-CoV-2 is spike-swap or spike variant assembly, a RaTG13-like virus could be the "backbone" of SARS-CoV-2.
Moreover, a hypothetical SARS-CoV-2 backbone could exist in the viral sequences list the WIV took down in Sept. 2019. They sequenced RaTG13 a few years prior. The lab's raison d'etre is collecting and sequencing coronaviruses poised for spillover. And, with modern DNA synthesis technology, it's not difficult to print out arbitrary backbone contigs for a viral assembly.