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  1. forestglip

    Still to open [Houston, Texas, USA] Effect of Metabolic Modulation on a Post-acute COVID-19 Vaccination Syndrome (PACVS) Cohort (ViTAL-SCAN19)

    Protocol Paper: Effectiveness of metabolic modulation in treating post-vaccination syndrome: study protocol for a prospective and randomized controlled trial Halma, Matthew; Varon, Joseph Background Post-acute COVID-19 vaccination syndrome (PACVS) emerged as a rare complication of the...
  2. forestglip

    Still to open [Houston, Texas, USA] Effect of Metabolic Modulation on a Post-acute COVID-19 Vaccination Syndrome (PACVS) Cohort (ViTAL-SCAN19)

    Effect of Metabolic Modulation on a Post-acute COVID-19 Vaccination Syndrome (PACVS) Cohort (ViTAL-SCAN19) Brief Summary The goal of this clinical trial is to evaluate whether metabolic modulation with a combined nutraceutical product can improve symptoms and metabolic health in adults...
  3. forestglip

    Chronic Lyme disease, post-treatment Lyme disease syndrome (PTLDS)

    Yeah, I'm not sure if this is only based on his own word. NIH, at least, denied it:
  4. forestglip

    Chronic Lyme disease, post-treatment Lyme disease syndrome (PTLDS)

    Maybe I should have put "bad science" in quotes to indicate that it was McSweegan's claim. I have no knowledge of the Lyme Disease Foundation or what kind of science they do. I just thought the story of how he stopped getting work so he started writing books on NIH time was interesting.
  5. forestglip

    Chronic Lyme disease, post-treatment Lyme disease syndrome (PTLDS)

    Just the story is interesting. That he called out the Lyme Disease Foundation for bad science, and the NIH appeared to make him stop doing any important work because of that.
  6. forestglip

    Advancing regulatory variant effect prediction with AlphaGenome 2026 Avsec et al

    Can you give a simpler explanation for what you're doing? No idea what I'm looking at on the linked pages.
  7. forestglip

    Advancing regulatory variant effect prediction with AlphaGenome 2026 Avsec et al

    Yeah, it is odd. They seem to mostly be consistent within the same tissues, but I did find a few that flip within the same tissue. Some examples below. Again based on chr20:48935095:C>CTCTTTTTT and ZNFX1. I see that at least for cerebellum and frontal cortex, there's a difference in signs but...
  8. forestglip

    Advancing regulatory variant effect prediction with AlphaGenome 2026 Avsec et al

    The scores I posted are all for predicted brain expression, but looking at the scores across all tissues for the same variant-gene pair of chr20:48935095:C>CTCTTTTTT and ZNFX1, it's similarly high for pretty much all tissues. I attached all the predicted scores for RNAseq that include that...
  9. forestglip

    Advancing regulatory variant effect prediction with AlphaGenome 2026 Avsec et al

    Sure, they're in the first column of the tables. These are the first two: chr20:48914387:T>TA chr20:48935095:C>CTCTTTTTT
  10. forestglip

    Problems arising for pwME from additional diagnoses of MCAS, hEDS and POTS. Advocacy discussion.

    Thanks for sharing. This is one of my concerns. The diagnosis of ME/CFS felt like a lifeline to me, and I'd be very upset if I needed to go back to the far greater uncertainty I had before that point.
  11. forestglip

    Mike's EU Marathons

    Incredible work! Just please take care of your body and don't overdo it. I see the section about increasingly bad injuries. You'll still want your joints to work when you're older.
  12. forestglip

    Chronic Lyme disease, post-treatment Lyme disease syndrome (PTLDS)

    Yes, interesting. Story from Wikipedia:
  13. forestglip

    Advancing regulatory variant effect prediction with AlphaGenome 2026 Avsec et al

    Out of curiosity, I looked only at the most significant variant in DecodeME only (20:48914387:T:TA). The model predicts that it has effects on these genes. Positive scores mean the ME/CFS risk allele increases expression. Interestingly, it seems to say it has large effects on almost all genes...
  14. forestglip

    Advancing regulatory variant effect prediction with AlphaGenome 2026 Avsec et al

    Ok, well I did that. I didn't initially filter to brain - I just had the model do all RNAseq predictions for all tissues, using all the variants with p-value less than 1x10^-7 (342 variants). That resulted in 3,800,412 scores, which are all the combinations of variants-genes-tissues. (It's...
  15. forestglip

    Advancing regulatory variant effect prediction with AlphaGenome 2026 Avsec et al

    The batch variant scoring tool looks like it'll be useful to test many variants at once: https://www.alphagenomedocs.com/colabs/batch_variant_scoring.html I think the goal is basically looking for variants that produce a large (or small if negatives are possible) quantile or raw score. For...
  16. forestglip

    Advancing regulatory variant effect prediction with AlphaGenome 2026 Avsec et al

    An LD pattern tells a story in terms of helping identify where the causal SNP is, or helping determine if a phenotype might contain the same causal SNP as another phenotype, but I don't think that's what AlphaGenome is doing. If we knew the specific causal variant in ME/CFS, and gave it that in...
  17. forestglip

    Advancing regulatory variant effect prediction with AlphaGenome 2026 Avsec et al

    Yeah, I'll need to try to understand this more. It looks interesting, but I'm not exactly sure what it's doing. I think there might be two modes? 1. Check the difference in predicted effect between a single ref and alt allele. 2. Just give a long sequence of DNA and see what the prediction is...
  18. forestglip

    Advancing regulatory variant effect prediction with AlphaGenome 2026 Avsec et al

    Maybe the plot should be zoomed out more? It's only showing one gene at the moment, but the variant could be affecting something else Edit: I think just a bigger number here: interval=variant_output.reference.rna_seq.interval.resize(2**15),
  19. forestglip

    Advancing regulatory variant effect prediction with AlphaGenome 2026 Avsec et al

    I haven't tried this yet. Been a bit confused about the docs so far. But maybe its better to test all the significant variants in a locus [edit: at the same time] instead of one? I'd be interested in each locus's variants' predicted effect on the brain.
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