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Record W4390511540 · doi:10.1186/s13287-023-03574-3

Metabolic switching, growth kinetics and cell yields in the scalable manufacture of stem cell-derived insulin-producing cells

2024· article· en· W4390511540 on OpenAlex
Diepiriye G. Iworima, Robert K. Baker, Cara E. Ellis, Chris Sherwood, Lisa Zhan, Alireza Rezania, James M. Piret, Timothy J. Kieffer

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueStem Cell Research & Therapy · 2024
Typearticle
Languageen
FieldMedicine
TopicPancreatic function and diabetes
Canadian institutionsUniversity of British Columbia HospitalCanada's Michael Smith Genome Sciences CentreUniversity of British Columbia
FundersBreakthrough T1D CanadaCanadian Institutes of Health ResearchStem Cell NetworkCanadian Federation of University WomenDiabetes CanadaJuvenile Diabetes Research Foundation Canada
KeywordsStem cellProgenitor cellBiologyInsulinInduced pluripotent stem cellBioprocessCellular differentiationCell therapyCell biologyTransplantationInternal medicineEndocrinologyMedicineBiochemistryEmbryonic stem cell

Abstract

fetched live from OpenAlex

BACKGROUND: Diabetes is a disease affecting over 500 million people globally due to insulin insufficiency or insensitivity. For individuals with type 1 diabetes, pancreatic islet transplantation can help regulate their blood glucose levels. However, the scarcity of cadaveric donor islets limits the number of people that could receive this therapy. To address this issue, human pluripotent stem cells offer a potentially unlimited source for generating insulin-producing cells through directed differentiation. Several protocols have been developed to make stem cell-derived insulin-producing cells. However, there is a lack of knowledge regarding the bioprocess parameters associated with these differentiation protocols and how they can be utilized to increase the cell yield. METHODS: We investigated various bioprocess parameters and quality target product profiles that may influence the differentiation pipeline using a seven-stage protocol in a scalable manner with CellSTACKs and vertical wheel bioreactors (PBS-Minis). RESULTS: Cells maintained > 80% viability through all stages of differentiation and appropriately expressed stage-specific markers. During the initial four stages leading up to the development of pancreatic progenitors, there was an increase in cell numbers. Following pancreatic progenitor stage, there was a gradual decrease in the percentage of proliferative cells, as determined by Ki67 positivity, and a significant loss of cells during the period of endocrine differentiation. By minimizing the occurrence of aggregate fusion, we were able to enhance cell yield during the later stages of differentiation. We suggest that glucose utilization and lactate production are cell quality attributes that should be considered during the characterization of insulin-producing cells derived from stem cells. Our findings also revealed a gradual metabolic shift from glycolysis, during the initial four stages of pancreatic progenitor formation, to oxidative phosphorylation later on during endocrine differentiation. Furthermore, the resulting insulin-producing cells exhibited a response to several secretagogues, including high glucose. CONCLUSION: This study demonstrates process parameters such as glucose consumption and lactate production rates that may be used to facilitate the scalable manufacture of stem cell-derived insulin-producing cells.

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)0.002
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: Empirical
Teacher disagreement score0.036
Threshold uncertainty score0.653

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.042
GPT teacher head0.305
Teacher spread0.263 · 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