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Record W4311527165 · doi:10.1002/btm2.10461

Lethal effects of mitochondria via microfluidics

2022· article· en· W4311527165 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueBioengineering & Translational Medicine · 2022
Typearticle
Languageen
FieldEngineering
TopicNanopore and Nanochannel Transport Studies
Canadian institutionsToronto General HospitalUniversity of TorontoUniversity Health Network
FundersMinistry of Science and ICT, South KoreaNational Research Foundation of Korea
KeywordsMitochondrionApoptosisProgrammed cell deathCell biologyCellMicrofluidicsIntracellularChemistryBiophysicsNanotechnologyBiologyMaterials scienceBiochemistry

Abstract

fetched live from OpenAlex

Tumor cells can respond to therapeutic agents by morphologic alternations including formation of tunneling nanotubes. Using tomographic microscope, which can detect the internal structure of cells, we found that mitochondria within breast tumor cells migrate to an adjacent tumor cell through a tunneling nanotube. To investigate the relationship between mitochondria and tunneling nanotubes, mitochondria were passed through a microfluidic device that mimick tunneling nanotubes. Mitochondria, through the microfluidic device, released endonuclease G (Endo G) into adjacent tumor cells, which we referred to herein as unsealed mitochondria. Although unsealed mitochondria did not induce cell death by themselves, they induced apoptosis of tumor cells in response to caspase-3. Importantly, Endo G-depleted mitochondria were ineffective as lethal agents. Moreover, unsealed mitochondria had synergistic apoptotic effects with doxorubicin in further increasing tumor cell death. Thus, we show that the mitochondria of microfluidics can provide novel strategies toward tumor cell death.

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.

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: none
Teacher disagreement score0.616
Threshold uncertainty score0.806

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 head0.006
GPT teacher head0.189
Teacher spread0.183 · 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