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Record W1987939090 · doi:10.1091/mbc.e12-12-0901

Measurements of forces produced by the mitotic spindle using optical tweezers

2013· article· en· W1987939090 on OpenAlexafffund
Jessica Ferraro‐Gideon, Rozhan Sheykhani, Qingyuan Zhu, Michelle L. Duquette, Michael W. Berns, Arthur Forer

Bibliographic record

VenueMolecular Biology of the Cell · 2013
Typearticle
Languageen
FieldPhysics and Astronomy
TopicOrbital Angular Momentum in Optics
Canadian institutionsYork University
FundersAir Force Office of Scientific ResearchYork UniversityUniversity of California, San DiegoHarvard University
KeywordsBiologyOptical tweezersMitosisCell biologySpindle apparatusBiophysicsCell divisionGeneticsOpticsCellPhysics

Abstract

fetched live from OpenAlex

We used a trapping laser to stop chromosome movements in Mesostoma and crane-fly spermatocytes and inward movements of spindle poles after laser cuts across Potorous tridactylus (rat kangaroo) kidney (PtK2) cell half-spindles. Mesostoma spermatocyte kinetochores execute oscillatory movements to and away from the spindle pole for 1-2 h, so we could trap kinetochores multiple times in the same spermatocyte. The trap was focused to a single point using a 63× oil immersion objective. Trap powers of 15-23 mW caused kinetochore oscillations to stop or decrease. Kinetochore oscillations resumed when the trap was released. In crane-fly spermatocytes trap powers of 56-85 mW stopped or slowed poleward chromosome movement. In PtK2 cells 8-mW trap power stopped the spindle pole from moving toward the equator. Forces in the traps were calculated using the equation F = Q'P/c, where P is the laser power and c is the speed of light. Use of appropriate Q' coefficients gave the forces for stopping pole movements as 0.3-2.3 pN and for stopping chromosome movements in Mesostoma spermatocytes and crane-fly spermatocytes as 2-3 and 6-10 pN, respectively. These forces are close to theoretical calculations of forces causing chromosome movements but 100 times lower than the 700 pN measured previously in grasshopper spermatocytes.

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 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 score0.012
Threshold uncertainty score0.243

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 integrity0.0000.000
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 head0.014
GPT teacher head0.239
Teacher spread0.225 · 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

Citations36
Published2013
Admission routes2
Has abstractyes

Explore more

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