Happy Halloween from the Goodell Lab! High #Fashion - lab style!
Peggy Goodell
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The Goodell Lab. Hematopoietic stem cells, epigenetics, DNA methylation. Chair, Dept of Mol Cell Biology at Baylor College of Medicine. Tweets my own.
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Latest posts 5
Great to see innovation in publishing! Thoughtful progress by Editor in Chief of @BiologyOpen @gorelicklab
Paying peer reviewers led to faster first editorial decisions — an average of 5.5 working days, down from nearly 38 for unpaid reviews.
The review quality, as judged by handling editors on the basis of helpfulness in making an editorial decision, went up.
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Two Presidents of @BCMhouston! Excited to welcome Jakub Tolar as our new President and CEO! He brings enormous energy and enthusiasm to take BCM into the next era, bringing deep experience leading a learning health system and his own interests in clinical translation of basic discoveries. Also grateful for the 16-year leadership of Paul E Klotman, who brought us through financial challenges, the pandemic, and a changing academic landscape with calm and humor. He modernized medical education, our infrastructure, and bolstered our finances; we grew and evolved. We are in a fantastic position for the future. Hope to be recruiting soon- watch this space!
Amazing paper showing somatic mutations and massive clonal selection for lymphocytes that drive autoimmune disease.
Autoimmune diseases are varied and individually relatively uncommon but as a group highly prevalent. These cause lots of morbidity to very many people, with huge personal, societal, and economic impact. If these findings are extended to other autoimmune conditions, they will have huge implications for treatment.
Lots in this paper - somatic evolution, new tech, old theories, mutations in your favorite genes... The thread is a great TL;DR for the paper.
Go deep and read the cited 2007 Goodnow paper (post#6) - amazingly detailed and prescient- from ~20 years ago!
Autoimmune diseases are varied and individually relatively uncommon but as a group highly prevalent. These cause lots of morbidity to very many people, with huge personal, societal, and economic impact. If these findings are extended to other autoimmune conditions, they will have huge implications for treatment.
Lots in this paper - somatic evolution, new tech, old theories, mutations in your favorite genes... The thread is a great TL;DR for the paper.
Go deep and read the cited 2007 Goodnow paper (post#6) - amazingly detailed and prescient- from ~20 years ago!
Excited to share our latest work. Applying advanced single-molecule and single-cell DNA sequencing methods, we uncover an extraordinary landscape of somatic mutations in immune checkpoint genes in autoimmune lymphocytes. [1/n] rdcu.be/fdqbrView quoted post on X
Data on factors impacting time-to-acceptance could be crowd-sourced.
Major factors:
- time before first editor desk decision (varies a lot by editor and journal)
- review time (huge variation; also heavily influenced by the editors)
- editor decision time after reviews come in (can be longer than one would think)
– revision time (authors chasing very time-consuming experiments for the win; heavily influenced by (lack of) editor guidance, but also topic, model system...)
- second round (all same variables)
- possible appeal time (appeals are high at top journals and take even more time and can add to total time)
Journals track all this data. Authors should have it too.
Decent crowd-sourced data could be in ~real-time, and would help authors make informed decisions. I think many ppl would contribute data from their experience.
Major factors:
- time before first editor desk decision (varies a lot by editor and journal)
- review time (huge variation; also heavily influenced by the editors)
- editor decision time after reviews come in (can be longer than one would think)
– revision time (authors chasing very time-consuming experiments for the win; heavily influenced by (lack of) editor guidance, but also topic, model system...)
- second round (all same variables)
- possible appeal time (appeals are high at top journals and take even more time and can add to total time)
Journals track all this data. Authors should have it too.
Decent crowd-sourced data could be in ~real-time, and would help authors make informed decisions. I think many ppl would contribute data from their experience.
Monthly median Received to Accepted time (days) at Nature GeneticsView quoted post on X
