ArticleFrontiers in immunology2026
Identification of potential biomarkers related to mannose metabolism in keloids: analysis of integrated bulk RNA-seq and scRNA-seq.
Article in Frontiers in immunology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Keloid (KD) is a benign cutaneous fibrotic disorder characterized by excessive proliferation of dermal fibroblasts. Mannose plays a key role in cellular metabolism, yet its specific mechanism associated with KD remains unclear. Therefore, identifying mannose metabolism-related potential biomarkers and their regulatory mechanisms in KD is crucial. Methods: Differentially expressed genes (DEGs) were identified between KD and control samples, and their intersection with mannose metabolism-related genes (MMRGs) was obtained to determine candidate genes. Feature genes underwent machine learning-based screening to identify characteristic genes, while potential biomarkers were determined through integrated analysis of gene expression profiles and Receiver Operating Characteristic (ROC) curve assessment. Subsequently, reverse transcription-quantitative polymerase chain reaction (RT-qPCR) methodology was employed to validate the expression patterns of these identified potential biomarkers. Subsequently, nomogram construction and enrichment analysis were conducted. Finally, key cells were identified through single-cell analysis, followed by performing cell communication, pseudotime, and transcription factor regulation analyses. Results: A total of 1,372 DEGs were identified, from which two mannose metabolism-related potential biomarkers ( Conclusion: This study successfully identified two potential biomarkers (
Indexed as
Identifiers
What Socratic holds
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 Socratic graph.