MétaCan
Menu
Back to cohort
Record W3205497581 · doi:10.1016/j.stemcr.2021.09.020

A new platform for high-throughput therapy testing on iPSC-derived lung progenitor cells from cystic fibrosis patients

2021· article· en· W3205497581 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueStem Cell Reports · 2021
Typearticle
Languageen
FieldMedicine
TopicCystic Fibrosis Research Advances
Canadian institutionsSickKids FoundationUniversity of TorontoHospital for Sick Children
Fundersnot available
KeywordsCystic fibrosisProgenitor cellInduced pluripotent stem cellBiologyLungStem cellBioinformaticsProgenitorCancer researchComputational biologyInternal medicineMedicineEmbryonic stem cellCell biologyGeneticsGene

Abstract

fetched live from OpenAlex

For those people with cystic fibrosis carrying rare CFTR mutations not responding to currently available therapies, there is an unmet need for relevant tissue models for therapy development. Here, we describe a new testing platform that employs patient-specific induced pluripotent stem cells (iPSCs) differentiated to lung progenitor cells that can be studied using a dynamic, high-throughput fluorescence-based assay of CFTR channel activity. Our proof-of-concept studies support the potential use of this platform, together with a Canadian bioresource that contains iPSC lines and matched nasal cultures from people with rare mutations, to advance patient-oriented therapy development. Interventions identified in the high-throughput, stem cell-based model and validated in primary nasal cultures from the same person have the potential to be advanced as therapies.

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 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 score0.091
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0000.000
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 head0.026
GPT teacher head0.280
Teacher spread0.254 · 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