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Record W2786629238 · doi:10.1016/j.stemcr.2018.01.035

Ihor Lemischka (1953-2017)

2018· article· de· W2786629238 on OpenAlexaffabout
Peter M. Lansdorp

Bibliographic record

VenueStem Cell Reports · 2018
Typearticle
Languagede
FieldBiochemistry, Genetics and Molecular Biology
TopicSingle-cell and spatial transcriptomics
Canadian institutionsBC Cancer Agency
Fundersnot available
KeywordsBiologyStem cellHaematopoiesisEmbryonic stem cellProgenitor cellReceptor tyrosine kinaseCell biologyGeneComputational biologySignal transductionGenetics

Abstract

fetched live from OpenAlex

Ihor Lemischka, PhD, Professor at the Icahn School of Medicine at Mount Sinai in New York died, much too young, from a stroke early in December 2017. Ihor will be remembered for his great sense of humor and his pioneering work on embryonic and hematopoietic stem cells. Throughout his career he showed an unwavering desire to understand the behavior of stem cells from a mechanistic, biochemical point of view. He wanted to know how cell fate decisions were made. In his quest he applied a variety of approaches from transistor models used in electronics to large gene expression and proteomics datasets from various laboratories, including his own. Notable contributions from his laboratory were the cloning and characterization of fetal liver cell surface tyrosine kinases 1 and 2 (flk-1 or KDR/VEGFR2 and flk-2). Flk-2 is selectively expressed on hematopoietic stem and progenitor cells and the flk-2 gene in humans is encoded by the FLT3 gene (CD135), the receptor for the cytokine Flt3 ligand (FLT3L). FLT3 and its ligand are key signal transducing components in the hematopoietic system, and it is now known that the FLT3 gene is one of the most frequently mutated genes in acute myeloid leukemia (AML). His laboratory pioneered and refined perturbation of gene expression using RNAi approaches. He was a true “systems biologist” who aimed to integrate data from very different sources into testable models to understand the behavior of normal and malignant stem cells. Given inevitably incomplete knowledge of all the molecular interactions and pathways operating in a cell, he always stressed that “everything should be made as simple as possible, but not simpler,” a quote from Einstein that he liked to use. He always remained true to his original interest in fundamental biological questions, and his approach to research was original and uncompromising. However, he also did see the need to translate fundamental discoveries if possible, and his laboratory was one of the first to capitalize on the use of pluripotent stem cells (iPSCs) to study complex genetic disorders by showing that in vitro-derived cardiomyocytes from LEOPARD syndrome iPSCs provide molecular insights into signaling pathways that promote the disease phenotype. His presentations inevitably gave food for thought, and the stellar careers of some of his trainees attest to his talent as a mentor and teacher. He actively participated in various stem cell meetings and was an active member of both the International Society for Stem Cell Research, where he served on the board of directors for six years, and the International Society for Experimental Hematology. At meetings he often asked pointed question with his unmistakable low, booming voice. During meetings he was also very active outside the scientific sessions. I fondly remember Ihor as friend whom I got to know well at stem cell meetings in Germany organized by Lothar Kanz. These meetings were always incredibly well organized, with a very busy scientific as well as social agenda. As a result, most participants in the evening wisely retired to their hotel rooms, but for some jet-lagged, globe-trotting scientists there was always time for one more of those excellent German beers. Ihor tremendously enjoyed these sessions, where discussions would range from science to politics and from soccer to gossip. He often was the last person to leave but he somehow always managed to show up the next morning ready to tackle another day. Perhaps one personal tale can bring Ihor’s personality and sense of humor back for a moment. I had been staying with Ihor and Kateri Moore, his wife and collaborator, in their beautiful house in Princeton. In this house, which was previously lived in by the science philosopher (“paradigm shift”) Thomas Kuhn, I was welcomed by “Coach,” a large Labrador who, after Kateri, was probably Ihor’s best friend and companion. Ihor was an avid collector of art and several beautiful Japanese prints decorated the walls. The following day I wanted to go to New York, where my wife, Claudia Bos, had an opening at an art gallery. Ihor and Teri decided to join me and we found ourselves on a late Saturday afternoon at Penn Station in Manhattan in a long taxi line-up. Without hesitation Ihor commandeered an unsuspecting female bicycle rickshaw driver to bring us to Bleeker Street “on the double.” The three of us, with carry-on luggage, were clearly a very heavy load for our driver on the hills of Manhattan. While I was trying to hide behind the suitcase on my lap from embarrassment, Ihor continued his conversation with our driver, who clearly needed all the oxygen she could retrieve from the New York street air. When we finally made it to the show and had given the driver a generous tip, Ihor mingled effortlessly with the mixed crowd at the gallery. After a few minutes and clearly disappointed he asked me, “Where is David Bowie?” Moments later he pouted, “Where is Andy Warhol? I had hoped to meet Lou Reed.” This line of enquiry continued throughout the evening during a Thai dinner with Pat Passlof and friends where he dominated the conversation as if he was the famous art critic Clement Greenberg himself. Ihor often ignored social conventions, but he did it with such flair that any offensive behavior was readily forgiven. I will always foster the memory of Ihor that day: alive, full of sparks, and bigger than life. He will be sorely missed. My warmest thoughts are with Kateri, who will need to go on without him and his wild adventurous spirit.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.464
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.015
GPT teacher head0.231
Teacher spread0.216 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2018
Admission routes2
Has abstractyes

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