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Record W3126495739

The Study of Loss of Mitochondrial Membrane Protein mgr2 Gene Results in Changes of Cell Dynamics in Fission Yeast

2020· article· en· W3126495739 on OpenAlexvenueno aff
Xiumei Tan, Xiang Ding, Rongmei Yuan, Yiling Hou

Bibliographic record

VenueMolecular Microbiology Research · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMicrotubule and mitosis dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsSpindle pole bodyMitosisCell biologyBiologySchizosaccharomyces pombeKinetochoreMetaphaseSpindle apparatusAnaphaseChromosome segregationMicrotubuleCell divisionCell cycleGeneticsCellChromosomeGeneSaccharomyces cerevisiae
DOInot available

Abstract

fetched live from OpenAlex

The mgr2 gene encodes an important transmembrane protein in mitochondria, which plays an important role in cell growth and survival. The model of Schizosaccharomyces pombe and the live cell imaging was used to explore the effect of mgr2 gene deletion on cell dynamics in mitosis. The results showed that the deletion of mgr2 gene would cause the number and length of microtubules abnormality and affect microtubule dynamics at interphase. At the same time, spindle microtubule dynamics were different in mgr2 Δ cells compared with wild type cells. Spindle length statistics showed that there was delayed spindle breakage in mgr2 Δ cells. The mgr2 gene deletion can also affect the spindle growth rate in the metaphase,metaphase time and anaphase time. Live-cell imaging were performed on mutant strains to observe two distinct chromosome behaviors: normal and lagging. In addition, there was abnormal spindle breakage. It is concluded that the loss of mgr2 gene from mitochondria caused abnormal cell mitosis, which would contribute to the spindle maintenance deficiency, chromosome segregation deficiency, spindle breakage deficiency.

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)0.001
metaresearch head score (Gemma)0.000
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 score0.002
Threshold uncertainty score0.526

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0010.000
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 head0.019
GPT teacher head0.288
Teacher spread0.268 · 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

Citations0
Published2020
Admission routes1
Has abstractyes

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