Evidence map›Paper›PMID 41290777›Full record

ArticleNPJ science of food2025

Unravelling bovine preadipocyte differentiation and their three-dimensional cultivation for cellular agriculture.

Apeksha Bharatgiri Goswami, Laurence Don Wai Luu, Joanna M Biazik, Mark S Rybchyn, Johannes le Coutre

Abstract read
In one paragraph

Article in NPJ science of food, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Review
  3. Fat forward: Cultivating bovine adipocytes on bioscaffolds.Current research in food science · 2025
    Article
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

5 authors.

Apeksha Bharatgiri GoswamiSchool of Chemical Engineering, University of New South Wales, Sydney, NSW, Sydney, Australia.
Laurence Don Wai LuuSchool of Biotechnology and Biomolecular Sciences, UNSW Sydney, Sydney, NSW, Australia.
Joanna M BiazikElectron Microscope Unit, Mark Wainwright Analytical Centre, University of New South Wales, Sydney, NSW, Sydney, Australia.
Mark S RybchynSchool of Civil and Environmental Engineering, University of New South Wales, Sydney, NSW, Sydney, Australia.
Johannes le CoutreSchool of Chemical Engineering, University of New South Wales, Sydney, NSW, Sydney, Australia. Johannes.lecoutre@unsw.edu.au.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cultured meat is an attractive concept to address environmental and ethical issues of livestock farming. Replication of conventional meat requires fat tissue, for flavour, texture, and mouthfeel. However, cultured meat production is limited by the lack of bovine adipogenic cells that are both proliferative and differentiable. Here, we demonstrate the isolation and characterisation of spontaneously immortalised bovine preadipocytes proliferating over 100 days and 21 passages, showing adipogenic differentiation. Upon induction, the cells accumulate lipids and express key adipogenic markers. Comparative RNA sequencing and proteomic analysis between induced and non-induced cells confirmed bovine origin, cell identity, and low tumour suppressor expression. Proteomic profiling identified over 2000 proteins, with enrichment in adipogenesis-associated pathways, including PPAR signalling and the ERK1/2 cascade. Additionally, the cells demonstrate viability in suspension and strong scaffold attachment. These results establish a reproducible bovine cell source for cultured fat supporting scale-up and bioprocess research in cellular agriculture.

Identifiers

PMID41290777
PMCPMC12647845

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.