Evidence map›Paper›PMID 38191636›Full record

ArticleCommunications biology2024

Stochastic biological system-of-systems modelling for iPSC culture.

Hua Zheng, Sarah W Harcum, Jinxiang Pei, Wei Xie

Abstract read
In one paragraph

Article in Communications biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed.

  1. Article
  2. Review
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  6. Review
  7. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Hua ZhengMechanical and Industrial Engineering, Northeastern University, Boston, MA, 02115, USA.ORCID 0000-0001-9555-7132
Sarah W HarcumBioengineering, Clemson University, Clemson, SC, USA. harcum@clemson.edu.ORCID 0000-0001-9417-0489
Jinxiang PeiMechanical and Industrial Engineering, Northeastern University, Boston, MA, 02115, USA.
Wei XieMechanical and Industrial Engineering, Northeastern University, Boston, MA, 02115, USA. w.xie@northeastern.edu.ORCID 0000-0001-9563-4927

Funding

National Science Foundation (NSF) EEC-2100442National Science Foundation (NSF) OIA-1736123United States Department of Commerce | National Institute of Standards and Technology (NIST) 70NANB17H002United States Department of Commerce | National Institute of Standards and Technology (NIST) 70NANB21H086
6 · The paper itself

Abstract

Large-scale manufacturing of induced pluripotent stem cells (iPSCs) is essential for cell therapies and regenerative medicines. Yet, iPSCs form large cell aggregates in suspension bioreactors, resulting in insufficient nutrient supply and extra metabolic waste build-up for the cells located at the core. Since subtle changes in micro-environment can lead to a heterogeneous cell population, a novel Biological System-of-Systems (Bio-SoS) framework is proposed to model cell-to-cell interactions, spatial and metabolic heterogeneity, and cell response to micro-environmental variation. Building on stochastic metabolic reaction network, aggregation kinetics, and reaction-diffusion mechanisms, the Bio-SoS model characterizes causal interdependencies at individual cell, aggregate, and cell population levels. It has a modular design that enables data integration and improves predictions for different monolayer and aggregate culture processes. In addition, a variance decomposition analysis is derived to quantify the impact of factors (i.e., aggregate size) on cell product health and quality heterogeneity.

Indexed as

Induced Pluripotent Stem CellsAnalysis of VarianceBioreactorsCell- and Tissue-Based TherapyCell Communication

Identifiers

PMID38191636
PMCPMC10774284

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.