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<i>Viscum album</i> agglutinin‐I induces degradation of cytoskeletal proteins in leukaemia PLB‐985 cells differentiated toward neutrophils: cleavage of non‐muscle myosin heavy chain‐IIA by caspases

2007· article· en· W2006019871 on OpenAlexafffund
Valérie Lavastre, François Binet, Éliane Moisan, Sonia Chiasson, Denis Girard

Bibliographic record

VenueBritish Journal of Haematology · 2007
Typearticle
Languageen
FieldImmunology and Microbiology
TopicToxin Mechanisms and Immunotoxins
Canadian institutionsInstitut National de la Recherche Scientifique
FundersCanadian Institutes of Health Research
KeywordsCytoskeletonMyosinCell biologyActinApoptosisVimentinGelsolinMolecular biologyBiologyChemistryCellImmunologyBiochemistry

Abstract

fetched live from OpenAlex

The role of the anti-cancer agent Viscum album agglutinin-I (VAA-I) in leukaemia PLB-985 cells differentiated toward a neutrophil-like phenotype by dimethylsulphoxide (PLB-985D) has never been studied. This study investigated whether or not VAA-I can induce cytoskeletal breakdown in PLB-985D cells, as previously observed in undifferentiated PLB-985 cells. VAA-I was found to induce apoptosis in PLB-985D cells, as assessed by cytology and by degradation of gelsolin, an event known to occur via caspase-3 activation. VAA-I induced cytoskeletal breakdown based on the disruption of the F-actin network and cleavage of paxillin, vimentin and lamin B(1). In addition, we demonstrated, for the first time, that non-muscle myosin heavy chain IIA (NMHC-IIA) was cleaved by VAA-I treatment. Degradation of NMHC-IIA was reversed by the pan caspase inhibitor z-VAD-fmk in PLB-985D cells and neutrophils. However, unlike lamin B(1), no NMHC-IIA was detected on the cell surface of apoptotic neutrophils. In conclusion, PLB-985D cells responded in a similar manner to neutrophils regarding the degradation of the tested cytoskeletal. Therefore, PLB-985D cells may provide a suitable substitute for neutrophils in screening experiments, preventing extensive neutrophil cell isolation.

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 categoriesMeta-epidemiology (narrow)
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 score0.014
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
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 head0.010
GPT teacher head0.228
Teacher spread0.218 · 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.

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

Citations11
Published2007
Admission routes2
Has abstractyes

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