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Scinderin, an Actin Severing and Nucleating Protein: Molecular Structure and Possible Roles in Cell Secretion, Maturation, Differentiation and Cancer

2019· article· en· W3160725556 on OpenAlexaff
J.M. Trifaró

Bibliographic record

VenueScience Reviews - from the end of the world · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicProtease and Inhibitor Mechanisms
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsCell biologyBiologyActinSecretionChemistryBiochemistry

Abstract

fetched live from OpenAlex

Scinderin is a filamentous actin-severing and capping protein. Segmental deletion and point-mutation studies have shown that this scinderin actin-severing activity resides in its NH2 terminal half, precisely in domains 1 and 2. The actin nucleating activity of scinderin is in its domain 5. Scinderin’s F-actin severing activity plays a role in cell secretion. In secretory cells, scinderin is highly concentrated in the cell cortex, showing a distribution similar to that of filamentous actin. Two PIP2-binding sites have been described in scinderin domains 1 and 2. PIP2 inhibits the actin-severing activity of the protein. Several approaches [recombinant scinderin, antisence oligonucleotide, gene promoter activation, vector-mediated expression of scinderin active domains] were used to prove the role of scinderin in secretion. The promoter of SCIN, the scinderin gene, has been characterized and its responsive elements have been described. The activation of the SCIN promoter by two ligands of the aryl hydrocarbon receptor [AhR] transcription factor has been shown. This activation increased scinderin expression with a resulting increase in stimulation-induced cortical actin disassembly and exocytosis. A role for scinderin in the life cycle of megakaryocytes has also been demonstrated. Scinderin seems to be involved in the maturation, differentiation and apoptosis processes of these cells, releasing newly formed platelets. This completes the life cycle of a megakaryocyte. A role for scinderin in cancer is also emerging. The SCIN gene is silenced in megakaryocyte leukemia cells and its re-expression induces cell maturation, differentiation, apoptosis, as well as the release of platelet-like particles and anti-tumor effects. These are always accompanied by changes in cell morphology due to cytoskeleton re-arrangements. Scinderin over-expression is necessary to see anti–proliferation effects, which are always accompanied by maturation and differentiation. If there were methods to differentiate other types of tumor cells, a new area of treatment would be developed by inducing “cell maturation and/or differentiation”.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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: Review · Consensus signal: none
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.007
GPT teacher head0.237
Teacher spread0.231 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreReview

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

Citations2
Published2019
Admission routes1
Has abstractyes

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