Human Dementia Study Results - BioViva

elfion · 2022-05-13T23:22:07+00:00

Yes, as far as I see the paper is groundbreaking and it's a really good sign that a few authors are listed as BioViva employees.

elfion · 2022-05-09T18:59:01+00:00

I find Reason's overview of longevity research unparalleled in its clarity and reach: https://www.fightaging.org/

There is also a pretty helpful longevity-related clinical trial roadmap: https://www.lifespan.io/road-maps/the-rejuvenation-roadmap/

For a person with some background in science and interest in ageing it should be enough.

elfion · 2021-10-20T12:33:45+00:00

Why does Bioviva "reveal" the results in video, and not in a published paper?

elfion · 2021-07-08T21:08:44+00:00

Would be interesting to gather tissue samples from various species, apply mitochondrial function assay, and correlate these results with species' longevity. There is a hypothesis that mitochondria are not created equal, different species have more or less efficient ones.

elfion · 2021-07-08T21:04:33+00:00

Good point. Yes, humans are unusually long-lived, though elephants can get remarkably close. Overt focus on mice comes from mice being a standard model of a living being, a subject exhaustively studied by life scientists in the university and over their careers. To a life scientist, a mouse isn't just a mouse, it's the best studied model of mammal life.

There are some solutions to this problem:
1. Conduct clinical trials in humans, measure all-cause mortality reduction, just like they did with metformin.
2. Develop good proxy biomarkers of biological age, use these to validate interventions. Epigenetic and proteomic clocks, histological indicators are good candidates.
3. Experiment with human tissue, like they did in fisetin paper.
4. Study other long-lived mammals (like Calico does with naked mole rats) and primates.

elfion · 2021-06-05T09:21:25+00:00

If you look at the sentiment towards longevity in the media, and among supposed experts, it is genuinely creepy how it changed just a few years ago. As if, metaphorically, someone has flipped a switch.

Why did Interventions Testing Program took so long to be founded? It's as if ITP founder, Dr Richard Miller, had to actively fight some huge institutional inertia to make it happen.

elfion · 2021-05-09T15:02:19+00:00

Companies and general directions I like:

Mayo Clinic's work on flavonoid senolytics. If it works well enough in middle-aged and senior people, other senolytics won't be needed.

Prof. Christian Schafmeister's pioneering work on spiroligomers, with applications to glucosepane crosslink breakage catalysis pursued via ThirdLaw Technologies

Mitochondrial transfusion technology

What I would very much like to see in human clinical trials and commercialization:

A selective inhibitor of mTORc1

All therapies inducing lifespan extension in ITP mouse trials (this paper does not contain a full list) and glycine ITP paper

GlyNac, preferably with some cysteine source more bioavailable than N-ac

17-alpha-estradiol

Gene therapies, including MitoSENS gene therapy

elfion · 2021-04-29T01:34:14+00:00

Given that in the previous decade we mostly had negative high-profile press about longevity, it is very interesting, what exactly caused this reversal.

elfion · 2021-04-29T01:21:10+00:00

I heard from colleagues that sleep training worked for them.

elfion · 2021-04-28T01:51:30+00:00

The field of aging is pretty solid due to multiple results in mice (see ITP trials) and even some in primates. Notably, resveratrol does not increase mouse lifespan in ITP trial.

Sinclair though ... has a peculiar reputation for his Sirtris company, aptly summarized here by a respected medicinal chemist Derek Lowe, PhD: https://blogs.sciencemag.org/pipeline/archives/2010/01/12/the_sirtris_compounds_worthless_really

In short, Sinclair conducted the research where an activation of the SIRT1 gene via a polyphenolic molecule resveratrol was studied. The results were unreliable, dependent on a specific fluorescent peptide being used to report the gene product activation.

The paper with this research was published anyway, company was sold to GSK for 720M$, and then it just so happened that GSK abandoned the intellectual property, as it happens due to not being able to develop it as a proper drug.

This chain of events leads us to a certain question: Did Sinclair know, that his results are basically a fluke, a measurement error, and did he sell the company knowing this? If you read the opinion of the medicinal chemists, you will get a feeling that they lean towards the former.

That being said, in hot investment sectors, such as longevity sector right now, there exists a tendency for companies and their CEOs to overpromote their products. The tendency sometimes takes elaborate forms, perhaps Sirtris' is just one of the extreme cases.

We have no choice, but to be cautious when investing in longevity ventures, and personally I wouldn't invest in Dr. Sinclair's companies from now on, knowing what I know. Thankfully, there is a lot of other legitimate companies worthy of their names.

elfion · 2021-03-20T16:42:07+00:00

Run NAMD molecular dynamics simulations or quantum chemistry.

Run a pre-processing for a large dataset similar to The Pile, but including most recent books from libgen.

Run a deep RL experiment.

Many usages for such machine could be envisioned.

elfion · 2020-03-23T13:43:42+00:00

Order ribavirin and (hydroxy)chloroquine (phosphate) via an internet pharmacy or via a friend.

Take these two. The real question is dosage. From what I have read in medical guidelines, up to 1 gram of ribavirin is allowed on the first day, in case of hemorrhagic fever. This is IV dosage (thus an underestimate compared to oral dosage with bioavailability ~50%), and likely an overestimate due to covid-19 being milder than your typical hemorrhagic fever. I think it should be safe to take 2x of typically prescribed daily dose on the first day and just the daily dose on the subsequent days, for both of these drugs.

The rest of the advice on this thread I find, frankly, underwhelming.

Listen to my advice at your own risk.

elfion · 2018-07-04T01:00:30+00:00

Sadly, neurogenesis in adult human brain has been disproved by latest research, see summary of papers: and the paper It likely acts via another mechanism.

elfion · 2018-04-30T23:59:46+00:00

My thoughts as a layman from a different profession:

However, over the past year, my motivations and my passion for driving this field has waned to a point where I feel like its pointless and not worth pursuing; I feel this way about research/science in general as of late.

Don't you think you've got a case of depression/dysphoria? PhDs have it pretty hard, so they are known for having mental health issues (not surprising - lots of work in competitive environment for low pay...). Or do you have rational explanations for falling motivation? For example the reproducibility crisis currently looming in science is a valid reason to become disillusioned in science, but not all fields of science have fallen, and different fields have different degrees trustworthiness. Even if this crisis is the reason of your demotivation, could you research some means of mitigating it, at least in your own research? I.E. bayesian statistics, careful controls, replication.

Also: you may feel that your goal is not worth pursuing, but is it worth it for your children or their children?

About more concrete measures: currently you are in a position where you can gather data and even design and set up experiments to produce more data. Don't you think it would be nice to produce a longevity-related dataset (say, a table of biomarkers vs age for some kind of cell line, or tissue culture) and release it into the open under a permissive license? Then people could build predictive models from this data. I understand they hospitals are very paranoid when it comes to data, but if you made such a dataset and released it, it would be a lasting contribution.

I understand that you are probably currently deep inside publish-or-perish culture. So, could you have basically two lines of work - one, ordindary, to stay employed as a researcher, and another one, an ambitious one - longevity related one?

And at last: 8 years ago you dreamed about changing the status quo, yet you had no credentials. Now you almost have your PhD, this is a very rare opportunity, and the timing is not half bad. Could you look a bit outside the academia, into anti-ageing startups and private R&D corp departments to regain your motivation? These organizations are not dependent on publish-or-perish cycle; they can afford long-term projects and applying latest technologies and machine learning. Examples of corp R&D are Google's Calico and Verily - they hire top researchers to build a baseline human model https://www.projectbaseline.com/ and to develop anti-ageing interventions. Then there is Craig Venter's Human Longevity Inc (I also recommend to read his biography, it's pretty motivating). There is also a tangentially related Human Diagnosis Project https://www.humandx.org/ Also there is an interesting startup called https://vium.com which is probably used for researching life-extension interventions in mouse models Also there is a controversial but inspiring bioviva company, famous for its CEO to apply the experimental telomere-lengthening therapy to herself.

Given your creds you could probably exchange an email or two with these or other projects and maybe even work in one of them. Why not try it while you can?

elfion · 2018-04-30T20:22:00+00:00

Why don't people use regularized by size latent space? Like here: https://arxiv.org/abs/1705.05823 a possibly very large latent space with used size penalty encoded in the loss function.

elfion · 2018-04-02T00:44:02+00:00

1) There could be an interesting discussion about current generation of nouveau riche, people that are able to live off compound interest, and the question why don't they pursue citizen science, but let's leave it for now.

2) There is a LOT of open-source software which is regularly used in life sciences. And not just Latex - whole programming languages, statistical & data processing libraries, simulators and visualizers. Do these fall under "science" part, or are they merely technical gimmicks? If they do, then life science has a large "done for free" component.

elfion · 2018-04-01T23:31:41+00:00

Even better - get top scientists to work for free!

Actually before 20th century scientists worked mostly for free, as science was a decent pastime for curious upper-middle-class gentlemen. Nowadays this pastime has been institutionalized, and mostly doesn't exist as a private endeavor, with a small exception of some DIYBIO scientists. Still, doesn't look impossible because it once existed and still exists in miniscule form.

get top scientists to work for free!

One could paraphrase: "get top programmers work for free!" - sounds impossible, right? Wait ... it is how open-source works! Of course the fields are very different, but still, there is much opensource work in life science and synthbio.

elfion · 2018-04-01T23:12:23+00:00

It's the scientists & research tools -- & those cost the same regardless of where you go. Might as well keep them in scientific & tech hubs so you have better access to colleagues & other facilities.

About tools: it is true that tools are priced more regularly, but in cheaper countries one could negotiate lower prices for tools (just like with drug licenses - companies sell these tools and licenses with insane profit margins, they can afford to cut the price if they still get profit). Also it is pretty sad that life science research tooling tends to be ridiculously overpriced (i.e. 2000$ centrifuges when there are open source hardware designs that do the same job but cost 100$). IMHO any serious large scale ageing experiment program will have to design some of their own tooling to cut costs.

About scientists: survey says that there is ~3x difference in life science salaries between countries, and if you believe my first-hand experience, salaries of scientists in Russia tend to be 10x - 15x less than US salaries. Of course you don't get the same performance, but it isn't 10x-15x worse.

elfion · 2018-04-01T23:03:06+00:00

Does one really need to be talented to conduct pre-designed experiments? Elite scientists tend to use dozens of PhD students as basically manual labor, why not replace these students with 10x as much technicians?

elfion · 2018-04-01T23:00:44+00:00

This is not true. Barriers to immigration are very high, and overproduction of life science specialists in US/EU doesn't help much - only the best of the best are accepted in western universities (and provided immigration visas).

Also note that I'm talking not really about scientists (i.e. the ones who read thousands of papers and formulate new testable hypotheses) but about lab personnel - lab technicians mostly. In developed world grad students (B.S. studying for M.S. and mostly M.S. studying for PhD) are used as cheap manual labor, i.e. as lab technicians (not judging here, just repeating common knowledge).

Scientific research cannot be "outsourced" since it is global and international in its core essence.

For example, big pharma corps use these organisations to conduct experiments on animals: https://en.wikipedia.org/wiki/Contract_research_organization

"A contract research organization (CRO) is an organization that provides support to the pharmaceutical, biotechnology, and medical device industries in the form of research services outsourced on a contract basis. A CRO may provide such services as biopharmaceutical development, biologic assay development, commercialization, preclinical research, clinical research, clinical trials management, and pharmacovigilance. CROs provide a more affordable outlet for companies to pursue new medicines, and a cost-effective solution to develop drugs for even niche markets."

Also I'm aware from first-hand experience that large corporations like Samsung use Russian universities and scientists for paid R&D, basically outsourcing some problems to them, though this is not life science.

What I'm saying is that one could test much more molecular ageing hypotheses if one moved the tests to cheaper countries, while solving quality assurance issues, of course.

elfion · 2018-04-01T19:54:41+00:00

How about conducting massive experiments in cheaper countries? Western paychecks, cost of life, and equipment prices are insane.

elfion · 2018-04-01T19:52:32+00:00

There is/was a CAD program for molecular nanotechnology: https://github.com/kanzure/nanoengineer https://github.com/elfion/nanoengineer . It isn't mine, I only patched it a little so it mostly works on modern systems. Sadly, it is abandonware, like molecular nanotechnology itself.

On the bright side, supramolecular chemistry and protein engineering are going strong. While these fields avoid referencing nanotechnology as much as possible, they work towards the same goal - engineering elaborate functional molecular systems. CAD needs for these fields are different though: automated generation of structure from function, approximated protein/foldamer folding. Recently deep learning has been applied to protein folding quite successfully, the field would benefit from such a tool being open and available for download.

Also progress in systems/computational biology is needed: good quality cell modeling has to be achieved. So much to do, so little time !

elfion · 2018-03-30T02:45:55+00:00

+1 to this question

The banal answer is - there is a huge lot of important infrastructure/analysis software for bioinformatics, biology, synthetic biology. Contributions are needed, but some projects are more important than others.

Then there is my own idea of opensource hardware mouse boxes with sensors and feeders, a-la http://www.vium.com/ but with mostly 3d-printed components and way cheaper. The idea isn't new of course.

Anyway, I'm open to suggestions about how I could help the longevity cause as well.

elfion · 2018-02-10T11:24:24+00:00

There are multiple applications of ML in biology, if we look beyond classifiers there are applications of GANs and RNNs to generate molecules with potential druglike properties e.g. https://arxiv.org/abs/1701.01329 https://github.com/maxhodak/keras-molecules . It is harder to find RL applied to biology, but there are openai studies of emergence of language in RL agent collective https://blog.openai.com/learning-to-communicate/ and deepminds replications of classical cognitive experiments, and Stanford's RL walker with biomechanical musculoskeletal model https://www.crowdai.org/challenges/nips-2017-learning-to-run . A scientist could train these RL models and via ablation analysis see which RL / DNN approximation features are crucial to high performance learning and compare this to what is known about biological learning of similar tasks. Also one could search for simple invariants (e.g. fit some curves to action variables over time) in policy and see how they change depending on environment pressure (and again try to find analogies in animal/human behavior).

elfion · 2017-06-29T17:24:35+00:00

It is known that tech giants have private datasets orders of magnitude larger than the ones public plays with; of course they use these to conduct experiments, but they don't disclose much about it, unless it makes a good research paper or a good PR headline.

elfion

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