Robin Friedman

RNA N-glycosylation enables immune evasion and homeostatic efferocytosis by chemically caging acp3U. Excited to report this work lead by Vinnie @vinnieviruses.bsky.social and in collaboration with @vijayrathinam.bsky.social in @nature.com www.nature.com/articles/s41...

🚨 Our parent-of-origin study is out in Nature! 🧬
Maternal and paternal alleles can have distinct — even opposite — effects on human traits, revealing a hidden layer of genetic architecture that standard GWAS miss.
🔗 www.nature.com/articles/s41...

Highlights below!

Leveraging data as a patient–scientist: frustrations and opportunities - Nature Reviews Nephrology The transition from data scientist to patient–scientist has given me new perspectives into clinical research and strengthened my commitment to open science. Although limitations on data availability h...

I wrote a short piece on how becoming an IgA Nephropathy patient has changed my perspective on biomedical research, developing an appreciation for the challenges in data interpretability & availability and the importance of patient engagement www.nature.com/articles/s41...

Which FDA-approved vaccines had randomized, placebo-controlled trials?

ALL OF THEM.

Polio?
Measles, mumps, rubella?
Haemophilus influenzae B?
Diphtheria, tetanus, pertussis?
Meningococcus?
Varicella?
Pneumococcus?
Rotavirus?
RSV?
Hepatitis B?
Influenza?
HPV?
COVID-19?
Shingles?

YEP.

A thread🧵
1/

If true, that has implications for how western biotech can compete. I'm not holding my breath for a change in the regulatory regime to rescue us.

1. Scale. I'm sure China's huge population helps with trial enrollment across many indications
2. Cost. If research costs are 4x lower, you can place 4x the number of bets and/or throw more people and experiments at problems to accelerate timelines.

Haven't seen anything saying it's a lower bar than Australia, for example. Instead, low visibility into the Chinese biotech ecosystem probably contributed to the perception of fast clinical data. Other factors seem more important:

After reading several pieces about the rise of China biotech, I think one of the narratives seems to be incorrect. The assumption that a faster regulatory path to first-in-human clinical trials compared to the west doesn't seem borne out by the data.

Nice list of thoughtful starting places for thinking about the implications of China's rising drug discovery capabilities.

Strange, works now for me. Thanks for posting!

Looks like the Asimov Press link is broken?

Tissue-resident memory T cells have high levels of mRNA of proinflammatory cytokines but produce the proteins only upon stimulation. 🧪⑂
The integrated stress response inhibits mRNA translation in these cells, having these cells poised for rapid responses in 🐭 and 🧓. 1/2

Zero-shot evaluation reveals limitations of single-cell foundation models - Genome Biology Foundation models such as scGPT and Geneformer have not been rigorously evaluated in a setting where they are used without any further training (i.e., zero-shot). Understanding the performance of mode...

genomebiology.biomedcentral.com/articles/10....

Quite an indictment of some of the current single cell "virtual cell" foundation models. Even for the relatively mundane applications, cell labeling, batch correction etc, they are poor compared to much simpler & cheaper methods.

What happened to pathology AI companies? 4k words, 19 minutes reading time

This was such an interesting post! It's awesome how much bio and biotech blogging are happening now and this is one of my newest favourites.

How population stratification led to a decade of sensationally false genetic findings Stratification makes environments look like genes

Finally read this by @sashagusevposts.bsky.social - very interesting piece. There's some fascinating bit of sociology of science to be done on when things get counted as replication crises versus when they're seen as healthy methodological progress.

theinfinitesimal.substack.com/p/how-popula...

RNA-binding proteins and glycoRNAs form domains on the cell surface for cell-penetrating peptide entry Mammalian cells present RNA-binding proteins on the cell surface that form clustered domains containing glycoRNAs.

Mindblowing new study by @raflynn5.bsky.social @bostonchildrens.bsky.social, cell surface RNA-binding proteins form nanoclusters with #glycoRNA and mediate cell-penetrating peptide entry into cells 👏

www.cell.com/cell/abstrac...

More below regarding layoffs at FDA h/t @alecgaffney.bsky.social. The layoffs are being run in a disorganized way by the new Secretary of Health & Human Services—Kennedy #medsky #biosky

It’s been a tough few weeks. My 10yo daughter was diagnosed with a very rare, aggressive cancer called interdigitating dendritic cell sarcoma (IDCS). I’m reaching out to identify clinicians/patients who have encountered pediatric IDCS or other (non-LCH) dendritic or histiocytic sarcomas cases.

Blown away

Using OpenAI’s Deep Research is like collaborating with a PhD student

(It told me it would get right on it then ghosted me)

Long somatic DNA-repeat expansion drives neurodegeneration in Huntington’s disease Single-cell measurement of the Huntington’s disease-causing CAG repeat reveals that somatic expansion of this repeat drives pathological changes in neurons, providing insights into disease progression...

I started working on genetic therapies for Mendelian disease in 2000 - and in the subsequent 25 years have never seen a disease where the molecular aetiology has undergone as giant an "OH WOW" moment as this.
www.cell.com/cell/fulltex...

Predicting RNA-seq coverage from DNA sequence as a unifying model of gene regulation - Nature Genetics Borzoi adapts the Enformer sequence-to-expression model to directly predict RNA-seq coverage, enabling the in-silico analysis of variant effects across multiple layers of gene regulation.

Super excited to announce our latest flagship model Borzoi: major props to Johannes & David Kelley et al for advancing it. It's been a long journey from our prior Enformer model into this one. A few innovations: i) longer DNA context, ii) adaptation to predict RNA-seq abundance and splice isoforms,

Excited to share our review article "Finding functional microproteins", published in @TrendsGenetics. It was fun writing it together with Alex and @FeiyueYang1 in the lab. #microprotein authors.elsevier.com/a/1kNCscQbJB...

This pair of papers demonstrating strong and systemic immune responses to skin commensals applied topically to unbroken skin, including induction of B cells for vaccination.
www.nature.com/articles/s41...
www.nature.com/articles/s41...

Insightful for anyone interested in LLMs

Many academics point to bioRxiv as “the one thing improving science publishing”.

If so, the one thing you all can do is persuade colleagues to submit and make this a norm. 1/2

Decrease in conformational entropy of an antibody between germline/naive sequence (left, green) and affinity-matured sequence (yellow, right)

2D free energy landscape before and after affinity maturation. Features are sin/cos of CDRH3 backbone dihedrals

Ideal test is antibody CDRH3s which often conformationally rigidify during affinity maturation. MSAs only report inter-species evolution, not intra-species maturation, so existing methods fail. Pics from doi.org/10.3389/fimmu.2018.03065 & doi.org/10.3389/fmolb.2020.00182

One of the biggest mysteries in Alzheimer's disease that is yet to be solved is the pathogenic mechanism of ApoE4 variant (and the protective mechanism of ApoE2).
A new study reports that LDL receptor binding affinity in brain cells linearly increase from E2 to E3 to E4 1/

Exactly why it should be easier to make progress! The efforts get less outside attention than other areas like protein-protein interactions though, no?

Thermostability feels like it should be one of the easier properties to predict, is super important for drugs, and yet gets very little attention. Thanks for posting

A general temperature-guided language model to design proteins of enhanced stability and activity The PRIME model improves protein mutants’ key properties with a 30% success rate, using machine learning without prior data.

Pretraining PLMs with both the standard MLM loss and a growth temperature loss dramatically improves prediction of thermostability, as well as identification of thermostabilizing point mutants. Lots of wet lab evaluation www.science.org/doi/10.1126/...