ArticleBioengineering (Basel, Switzerland)2024
Spatial Transcriptomics, Proteomics, and Epigenomics as Tools in Tissue Engineering and Regenerative Medicine.
Article in Bioengineering (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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.
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.
Who cites it
3 citing papers in PubMed.
- BART-spatial unravels biologically significant transcriptional regulators from spatial omics data.bioRxiv : the preprint server for biology · 2026Article
- Spatial omics in 3D culture model systems: decoding cellular positioning mechanisms and microenvironmental dynamics.Journal of translational medicine · 2025Review
- Innovative Method for Fully Automated, Enzyme-Free Tissue Dissociation and Preparation for Single-Cell Analysis.Cellular and molecular bioengineering · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Spatial transcriptomics, proteomics, and epigenomics are innovative technologies which offer an unparalleled resolution and wealth of data in understanding and the interpretation of cellular functions and interactions. These techniques allow researchers to investigate gene and protein expressions at an individual cell level, revealing cellular heterogeneity within, for instance, bioengineered tissues and classifying novel and rare cell populations that could be essential for the function of the tissues and in disease processes. It is possible to analyze thousands of cells simultaneously, which gives thorough insights into the transcriptomic view of complex tissues. Spatial transcriptomics combines gene expressions with spatial information, conserving tissue architecture and making the mapping of gene activity across different tissue regions possible. Despite recent advancements in these technologies, they face certain limitations. Single-cell transcriptomics can suffer from technical noise and dropout events, leading to incomplete data. Its applicability has been limited by the complexity of data integration and interpretation, although better resolution and tools for the interpretation of data are developing fast. Spatial proteomics and spatial epigenomics provide data on the distribution of proteins and the gene regulatory aspects in tissues, respectively. The disadvantages of these approaches include rather costly and time-consuming analyses. Nevertheless, combining these techniques promises a more comprehensive understanding of cell function and tissue organization, which can be predicted to be useful in achieving better knowledge of cell guidance in tissue-engineered constructs and a higher quality of tissue technology products.
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Registered trials
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.