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Record W4402374356 · doi:10.3390/cancers16173106

Amitotic Cell Division, Malignancy, and Resistance to Anticancer Agents: A Tribute to Drs. Walen and Rajaraman

2024· article· en· W4402374356 on OpenAlexaff
Razmik Mirzayans, David Murray

Bibliographic record

VenueCancers · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMicrotubule and mitosis dynamics
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsBiologyCell divisionMitosisSomatic cellCancer cellCellCell biologyCarcinogenesisAsymmetric cell divisionCancer stem cellCancer researchStem cellCancerGenetics

Abstract

fetched live from OpenAlex

Cell division is crucial for the survival of living organisms. Human cells undergo three types of cell division: mitosis, meiosis, and amitosis. The former two types occur in somatic cells and germ cells, respectively. Amitosis involves nuclear budding and occurs in cells that exhibit abnormal nuclear morphology (e.g., polyploidy) with increased cell size. In the early 2000s, Kirsten Walen and Rengaswami Rajaraman and his associates independently reported that polyploid human cells are capable of producing progeny via amitotic cell division, and that a subset of emerging daughter cells proliferate rapidly, exhibit stem cell-like properties, and can contribute to tumorigenesis. Polyploid cells that arise in solid tumors/tumor-derived cell lines are referred to as polyploid giant cancer cells (PGCCs) and are known to contribute to therapy resistance and disease recurrence following anticancer treatment. This commentary provides an update on some of these intriguing discoveries as a tribute to Drs. Walen and Rajaraman.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.016
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.011
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.016
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0020.005
Scholarly communication0.0040.005
Open science0.0030.002
Research integrity0.0110.035
Insufficient payload (model declined to judge)0.0040.003

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 head0.006
GPT teacher head0.246
Teacher spread0.240 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations9
Published2024
Admission routes1
Has abstractyes

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