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Record W4385968652 · doi:10.26508/lsa.202302303

Structural evidence for elastic tethers connecting separating chromosomes in crane-fly spermatocytes

2023· article· en· W4385968652 on OpenAlexafffund
Arthur Forer, Shotaro Otsuka

Bibliographic record

VenueLife Science Alliance · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMicrotubule and mitosis dynamics
Canadian institutionsYork University
FundersMedizinische Universität WienNatural Sciences and Engineering Research Council of CanadaUniversität WienVienna Science and Technology FundGovernment of Canada
KeywordsAnaphaseTelomereBiologyMitosisCell biologyMeiosisChromosomeGeneticsDNA

Abstract

fetched live from OpenAlex

Different types of anaphase bridges are reported to form between segregating chromosomes during cell division. Previous studies using laser microsurgery suggested that elastic tethers connect the telomeres of separating anaphase chromosomes in many animal meiotic and mitotic cells. However, structural evidence is lacking for their existence. In this study, by correlating live imaging with electron tomography, we examined whether visible structures connect separating telomeres in meiosis I of crane-fly primary spermatocytes. We found structures extending between separating telomeres in all stages of anaphase. The structures consist of two components: one is darkly stained, looking somewhat like chromatin, whereas the other is more lightly stained, appearing filamentous. Although in early anaphase both structures extend between telomeres, in later anaphase, the darker structure extends shorter distances from the telomeres but the lighter structure still extends between the separating telomeres. From these observations, we deduced that these structures represent the "tethers" inferred from the laser-cutting experiments. Because elastic tethers have been detected in a variety of animal cells, they probably are present during anaphase in all animal cells.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.221
Threshold uncertainty score0.533

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.048
GPT teacher head0.347
Teacher spread0.298 · 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.

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

Citations5
Published2023
Admission routes2
Has abstractyes

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