
Thomas Perlmann
@perlmannlab
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Members of Thomas Perlmann's group at Karolinska Institutet mostly tweet about exciting science and the Nobel Prize in Physiology or Medicine.
Stockholm, Sweden
Joined September 2019
RT @Dev_journal: New insights into what makes midbrain progenitors tick. Read this Research Highlight showcasing work from Laura Lahti, Tho….
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Incredible research lecture by the brilliant @michelle_monje today at Nobel Forum! A true treat for a packed auditorium!
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RT @ScienceAcad_swe: 🌟Sjöberg Laureate discovered new targets for cancer therapies in the immune system!🌟.@MiriamMerad, Mount Sinai Health….
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Excellent presentations yesterday @NobelWeek in Nobel Forum @karolinskainst. Thanks to Jim Allison, Padmanee Sharma, Laurence Zitvogel, Mikael Karlsson, and Camilla Engblom!
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Great meeting in Utrecht today! Many thanks for the opportunity to participate!.
Here today at @DPSConference24 , fascinating keynote from @perlmannlab all about dopamine neurons and their origins #parkinsonsdisease
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In about 24 hours, the votes from Nobel Assembly members will be collected in this brass bucket. Welcome to watch the announcement of the 2024 Nobel Prize in Physiology or Medicine @NobelPrize CEST 11:30 am!
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It was great participating in this year's @LaskerFDN award ceremony! Mike Brown introduced James Chen to the basic award for the discovery of cGAMP/cGAS.
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Such a pleasure being your collaborator, Ioannis! Great work!.
I am pleased to share our publication on the crucial role of Nurr1 in modulating the response to hallucinogens in the claustrum. A huge thank you to @perlmannlab, @giacomello_lab, @CarlenLab and @Boehringer.#Claustrum #Nurr1 #Hallucinations.
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Finally, our dopamine neuron atlas is out, uncovering unexpected diversity and differential vulnerability of different groups of DA neurons. Great job by @b_yaghmaeian, @DrGloom, Linda, Jesper, and Ioannis. Thanks to @PerSvenningsson for a great collaboration.
In @eLife: Transcriptomic atlas of midbrain dopamine neurons uncovers differential vulnerability in a Parkinsonism lesion model
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