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Record W4288455377 · doi:10.1016/j.scr.2022.102877

Generation of two human induced pluripotent stem cell lines from peripheral blood mononuclear cells of clozapine-tolerant and clozapine-induced myocarditis patients with treatment-resistant schizophrenia

2022· article· en· W4288455377 on OpenAlexafffund
Nazanin Vaziri, Diogo Luís Marques, Xuemei Wang, Pranav Machiraju, Ankita Narang, Katerina Vlahos, Christos Pantelis, Steven C. Greenway, Chad Bousman

Bibliographic record

VenueStem Cell Research · 2022
Typearticle
Languageen
FieldMedicine
TopicViral Infections and Immunology Research
Canadian institutionsLibin Cardiovascular Institute of AlbertaHotchkiss Brain InstituteAlberta Children's HospitalUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of CanadaCumming School of Medicine, University of CalgaryAlberta Children's Hospital Research InstituteUniversity of MelbourneUniversity of Calgary
KeywordsClozapinePeripheral blood mononuclear cellInduced pluripotent stem cellMyocarditisBiologySchizophrenia (object-oriented programming)ImmunologyCell cultureCancer researchPharmacologyMedicineInternal medicinePsychiatry

Abstract

fetched live from OpenAlex

Clozapine has superior efficacy in the treatment of refractory schizophrenia; however, use of clozapine is limited due to severe side effects, including myocarditis. Using non-integrative Sendai virus, we generated induced pluripotent stem cell lines from peripheral blood mononuclear cells of two patients with refractory schizophrenia, one clozapine-tolerant and one clozapine-induced myocarditis. Both cell lines exhibited a normal karyotype and pluripotency was validated by flow cytometry, immunofluorescence and their ability to differentiate into the three germ layers. These lines can be used to generate 2D and 3D patient-specific human cellular models to identify the mechanism by which clozapine induces myocardial inflammation.

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)0.001
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.078
GPT teacher head0.321
Teacher spread0.243 · 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
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

Citations4
Published2022
Admission routes2
Has abstractyes

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