According to Claude they were first studied for cancer but the first actual FDA approval was for acne.

I’ve read the article and notice that all the negative side-effects listed are due to issues with oral Retinoids rather than topical Retinoids.

Several of the articles I’ve read indicate that topical retinoids actually DECREASE the risk of cancer, though I agree this is confusing since they supposedly increase cell turnover rates, which should theoretically cause more mitosis-induced mutations to occur. But Retinoids are actually frequently used as anti-cancer drugs.

Google’s AI summarizer says you the mechanism of action is promotion of cell differentiation and inhibiting the progression of pre-malignant cells to malignant cells.

It also reduces "keratinocyte differentiation and decrease keratin deposition" which makes skin more fragile, and it increases sensitivity to UV light.

This is correct of course and why I specifically recommend in the post that people wear sunscreen when using retinoids.

Hard to say. Retinols are recommended as a preventative. Though incidentally I have noticed acne fading much faster after using them. I suspect this is because they speed up the healing process of the skin.

I've started a gene therapy company, raised money, opened a lab, hired the inventor of one of the best multiplex gene editing techniques to be our chief scientific officer, and am currently working on cell culture experiments with the help of a small team.

I may write a post about what's happened at some point. But things are moving.

Can you explain in more detail what the problems are?

You can definitely extrapolate out of distribution on tests where the baseline is human performance. We do this with chess ELO ratings all the time.

I don't think this is the case. You can make a corn plant with more protein than any other corn plant, and using standard deviatios to describe it will still be useful.

Granted, you may need a new IQ test to capture just how much smarter these new people are, but that's different than saying they're all the same.

Apart from coming across as quite repulsive to most people, I wonder at the cost and success rate of maturing immature oocytes.

This is already an issue for child cancer patients who want to preserve future fertility but haven't hit puberty yet. As of 2021, there were only ~150 births worldwide using this technique.

The costs are also going to be a major issue here. Gain scales with sqrt(ln(number of embryos)). But cost per embryo produced and tested scales almost linearly. So the cost per IQ point is going to scale at like $e^{x^2}$, which is hilariously, absurdly bad.

I'd also want to see data on the number of immature oocytes we could actually extract with this technique, the rate at which those immature oocytes could be converted into mature oocytes, and the cost per oocyte.

So a human with IQ 300 is probably about the same as IQ 250 or IQ 1000 or IQ 10,000, i.e. at the upper limit of that range.

I would be quite surprised if this were true. We should expect scaling laws for brain volume alone to continue well beyond the current human range, and brain volume only explains about 10% of the variance in intelligence.

Without any double-strand breaks, base editors are less toxic to cells and less prone to off-target effects.

It's worth noting that most base editors actually DO involve nicking of one strand, which is done after the chemical base alternation to bias the cell towards repairing the non-edited strand.

The editing efficiency of non-nicking base editors is significantly lower than that of nicking versions (though the precise ratio varies depending on the specific edit site)

Finally the cell's enzymes also notice a mismatch between the strand with the new template DNA and the old strand without it, and decide that the longer, newer strand is “correct” and connect it back to the main DNA sequence.

It's worth noting that this only happens some of the time. Often the cell will either fail to ligate the edited strand back together or it will remove the edited bases, undoing the first half of the edit.

In regards to bridge RNAs, I do not yet believe they will work for any human applications. The work in Hsu's paper was all done in prokaryotes. If this tool worked in plants or animals, they would have shown it.

In fact, despite what human geneticists often say about epistasis being minor and rare, plant genetics people seem to find that interactions between genes are a big deal, explaining most (!) of the variance in crop yields.[5] So, if I’m not mistaken, “of all these genetic variants statistically associated with the polygenic trait, what’s the best subset of edits to make, if I want the largest expected impact” is a nontrivial question.[6]

I was curious about the finding of epistatic effects explaining more of the variance than traditionally assumed, so I took a look at the study you referenced and found something worth mentioning.

The study is ludicrously underpowered to detect anything like what they're trying to show. They only have 413 genetically distinct rice plants in the study, compared to 36,901 SNPs.

This study is underpowered to detect even SNPs that have an effect on the trait in question, let alone epistatic effects. So I don't give their results that much weight.

I agree with your overall conclusion though; I think we'll likely see the first applications of polygenic embryo selection in animals (perhaps cows?) before we see it in humans.