Evidence map›Paper›PMID 40843445›Full record

ArticleFrontiers in bioengineering and biotechnology2025

Development and optimization of an ammonia removal strategy for sustainable recycling of cell culture spent media in cultivated meat production: from concept to implementation.

Babak Pakbin, Armaghan Amanipour, Arian Amirvaresi, Arash Shahsavari, Reza Ovissipour

Abstract read
In one paragraph

Article in Frontiers in bioengineering and biotechnology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

5 authors.

Babak PakbinDepartment of Food Science and Technology, Texas A&M University, College Station, TX, United States.
Armaghan AmanipourDepartment of Food Science and Technology, Texas A&M University, College Station, TX, United States.
Arian AmirvaresiDepartment of Food Science and Technology, Texas A&M University, College Station, TX, United States.
Arash ShahsavariDepartment of Food Science and Technology, Texas A&M University, College Station, TX, United States.
Reza OvissipourDepartment of Food Science and Technology, Texas A&M University, College Station, TX, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Ammonia is a toxic metabolic waste produced during mammalian cell metabolism, with inhibitory effects against cell growth. Methods: This study focuses on developing and optimizing an ammonia removal approach to support spent media recycling throughout sustainable cultivated meat biomanufacturing. Results: Among the various methods evaluated, the alkalization-stripping method was found to be significantly more efficient and rapid than other strategies to remove ammonia ions while preserving the remaining glucose contents. The optimized process parameters were determined to be a pH of 12 following a 15-minute stripping process, achieving more than 82% ammonia removal efficiency. When applied to lamb satellite cells, the treated spent media improved the cell growth rate without inducing any morphological changes. Discussion: A 50:50 ratio formulation of treated spent media to fresh media demonstrated an efficient, cost-effective, and environmentally friendly solution for spent media recycling, providing a practical approach to implementing sustainable media recycling in cultivated meat production.

Indexed as

cultivated meatlamb muscle cell growthoptimizationrecirculating mediaresponse surface methodologyspent media

Identifiers

PMID40843445
PMCPMC12364936

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.