BTW if finite-time blowup happens it arguably means NS was the wrong model for physical reality. And in fact there are plausible modifications (e.g., a time delay in the nonlinearity, solved by Varnhorn 10 or so years ago).
It would be so funny if mRNA cancer vaccines “worked” because the mRNA itself is so immunogenic (adjuvant-like)
Systemically stimulate the immune system and hot tumors clear, cold tumors become hot
First, a paper suggesting that random-sequence mRNA vaccines enhance anti-tumor effects, and now another claiming that random, nonspecific T cells are sufficient to eliminate tumors. So much for antigen specificity.
#science#immunology
https://t.co/aPAGZQOm3K
@BetterCallMedhi@MelindaBChu1@sama AlphaFold is open? That’s a new one. Point to one of the scientific breakthroughs AF causally contributed to bc there aren’t many
Did DM ever release their training setup? Is AF3 even open weight? You fell for DM over OAI PR
Even though biology is experiment rather than hypothesis bottlenecked, we may see people become less attached to ideas and willing to change their minds because hypothesis generation and literature review now takes hours instead of weeks
Helpful for breaking dogma
Protein sequences were evolutionarily optimized under metabolic cost constraints, with WFYHM as expensive amino acids
Since biotech relaxes the energy constraint, we should search WFYHM-enriched sequences because evolution hasn't searched this distribution as much
@bayeslord I expect most humans have cortex patches > 5mm^2 that are "enslaved" by the rest of the brain.
Organoid computers are potentially evil but not uniquely evil compared to growing brains via factory farming (humans included)
@aaronmring@EganPeltan Got it, so the auto/polyreactivity difference is number of antigens an antibody recognizes. My understanding then is
autoantibody:polyreactive antibody::number of recognized targets
which feels similar to
peptide:protein::chain length
@aaronmring@EganPeltan I’m probably misunderstanding something
It feels like autoantibodies ARE polyreactive. If we magically assay’d all antigens, including historical, in the microbiome, I would expect an autoantibody that hits a single human antigen to light up microbial antigens as well
@aaronmring@EganPeltan IGHV4-34 is good at recognizing bacteria and viral glycans
maybe evolution is justifying V4-34 self-reactivity because it protects against infection? there's a chance to reduce self-reactivity during affinity maturation
https://t.co/vSRXQ7BRM9
https://t.co/1Tj9HhAYJC
@aaronmring@EganPeltan auto vs polyreactive antibodies maybe a false dichotomy and we just haven’t figured out the intended target of the “autoantibodies” yet
e.g. some mechanism data shows anti-TSHR antibodies cross react with Y. enterocolitica / H. pylori which was the “intended” target
a highly ordered 2D array of a endogenous protein that's tolerated on its own breaks B cell tolerance.
because evolutionarily, viruses present as 2D crystal arrays of protein
repeated molecular geometry is itself a pathogen signal !!
@daphnesolves Step 0.5 is predicting yes/no does it bind
Step 1 is affinity prediction to within 1-2 OOMs which is still unsolved by both simulation and ML models
There are around 10 more steps to have a drug ready for the clinic