quang-n-nguyen.bsky.social

Interested in learning about how some cool follicular T cells modulate B cell and antibody responses in #hooman ? PM me 🤣😁🫠 #vaccinology #immunology #computationalimmunology #bluedevils #follicularTcells

I am no longer active on social media. Reports of my accounts being hacked have been noted. Please always reach out face-to-face as needed regarding any suspicious message.☺️

Following suit, I too will no longer be on the dark X -- Plz join me (quang-n-nguyen.bsky.social) catching butterflies on @bluesky

🇨🇦 expat living in 🇺🇸. Got PhD in the 🇺🇸 and stay as I love the people and the innovative spirit of this country. Long had a green card but became a citizen after the previous president said he could kick us out. I voted today for the first time to ensure that won't happen again.

@schwabpa It is not the tools built to solve the problem is the problem. It is how we use such a tool is the problem and importantly how trainees are trained to use or abuse the interpretation of results from such tools

A central mistake in biology was to name genes. This over-simplification made reconciling what is happening on the molecular level a mess - it's not rare to find reports of opposite mechanisms in different contexts, claimed involvement in dozens if not hundreds of different processes, sometimes inhibiting and sometimes amplifying and most of the time being oblivious to the potential for sequence-level variation. Nobody would be surprised about this diversity of findings if we instead recognized genes as (sometimes quite lengthy and complex) pieces of sequence that carry state and interact with and are interpreted by their environment - often producing dozens of gene products that are in turn themselves context-dependent and modulated. Naturally, such a highly amorphous composition of objects has many diverse effects, and masking this complexity behind a single name more often than not ends up being a harmful abstraction. The primary role of gene names then is to give us the false appearance of comfort in the face of enormous biological complexity. One under-appreciated potential of the emergence of AI tools in biology is to undo this mistake, and - instead of assuming it away - extend our ability to lean further into this complexity.

Brain tumors hijack neural language circuits to fuel their growth 😳 nature.com/articles/s4158…

Really cool paper: refueling T cells by sending mitochondria via a tunnel empowers the T cells to fight tumors better. cell.com/cell/fulltext/…

FDCs, Tfh/Tfr, and B cells, NK cells, et al. but there is always a place for something else -- a tingible body macrophages that autocorrect will continue to fix into tangible. 😅 #germinalcenters #follicular #humoral #vaccinology annualreviews.org/content/journa…

Non-resolving inflammation can induce "bad" lymphoid rxns, leading to dysregulation of host defense & pathogenic autoreactivity. But not in all #autoimmunedisease & cancer patients #Tfh #Tfr #GCreactions nature.com/articles/nri37…

Excited to share our new paper on temporal analysis of vaccine+/- adjuvant hours to 100 days (14 time pts). Vax alone induces new baseline immune state early & persists to 100 days, and that state predicts vax responses in an indep cohort. cell.com/cell-reports/f….

Adaptive and innate immune cell diversity and composition underlying #immunevariations between human populations, and how they are influenced by both host genetics and non-genetic factors. Quite an insightful read on #systemsimmunology w historical touch cell.com/cell/fulltext/…

Mapping cellular interactions from spatially resolved transcriptomics data👏 nature.com/articles/s4159…

"Several HLA haplotypes, some of which encode ligands for natural killer cell receptors (KIRs), were acquired through admixture with Denisovans or Neanderthals." 😎 #introgression cell.com/cell/fulltext/…

What if we could map every cell in the body, revealing its location and molecular identity? In this @NatureMethods perspective, we discuss the new era of 3D-omics by tissue clearing and AI, called Deep 3D Histology: rdcu.be/dNBe8 PDF: bit.ly/3WaD0QU 🧵👇🏼

Directly selecting cell-type marker genes for single-cell clustering analyses cell.com/cell-reports-m…

Single cell profiling is costly and not yet scalable across large population cohorts. Here an interesting ‘semi-profiling’ approach combines active learning and deep generative models to improve cell type decomposition from bulk data ⁦@NatureComms⁩ nature.com/articles/s4146…

Love Immunology? Hate Cancer? Come join the Centre for Immuno-Oncology as a senior postdoc in Immunopeptidomics. jobs.ac.uk/job/DIT166/sen…

Extremely proud and excited to share my thesis work from the Choi lab @jaehyukchoimd, in collaboration with @Deepakarao and @@vwacle, online today @Nature where we investigate pathological CXCL13+ Tph cell circuitry in SLE, online here:nature.com/articles/s4158…

Stanford Medicine is making a large investment to hire multiple faculty in AI/ML. I'm one of the co-chairs. If you have questions, do not hesitate to reach out: facultypositions.stanford.edu/cw/en-us/job/4…

📢Hot off the press: our review on "tissue active matter" Together with @EdouardHannezo, we review theoretical approaches for tissue dynamics, integrating active mechanics, cell-cell interactions and biochemical signaling Now out in CSH Perspectives: ➡️cshperspectives.cshlp.org/content/early/…

R package to query the Human Cell Atlas at the tissue, condition or sample level stemangiola.github.io/CuratedAtlasQu…