ArticleBiochemical genetics2026
Screening Therapeutic Core Genes in Sepsis Using Network Pharmacology and Single-Cell RNA Sequencing.
Article in Biochemical genetics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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
1 citing paper in PubMed.
- Combination of machine learning and protein‑protein interaction network established one ATM‑DPP4‑TXN ferroptotic diagnostic model with experimental validation.Molecular medicine reports · 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
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Sepsis, a life-threatening condition characterized by a systemic inflammatory response, leads to organ dysfunction and high mortality rates. Honeysuckle, a traditional herbal remedy, has shown promise in attenuating organ damage and inhibiting pro-inflammatory factors in sepsis. However, the underlying molecular mechanisms remain unclear. We employed a multi-omics approach to elucidate honeysuckle's potential therapeutic effects in sepsis. RNA sequencing was performed on blood samples from 22 sepsis patients and 10 healthy controls to identify differentially expressed genes. Network pharmacology was utilized to predict effective ingredients and therapeutic targets of honeysuckle in sepsis. Meta-analysis compared gene expression between sepsis survivors and non-survivors. Single-cell RNA sequencing was employed to localize target gene expression at the cellular level. We identified 1328 differentially expressed genes in sepsis, with 221 upregulated and 1107 downregulated. Network analysis revealed 15 genes linked to 12 honeysuckle components. Four genes-DPP4, CD40LG, BCL2, and TP53-emerged as core therapeutic targets, showing decreased expression in non-survivors but upregulation in survivors. Single-cell analysis demonstrated that these genes were primarily expressed in T cells and other immune cells, suggesting their role in regulating immune response and inflammation. This study uses single-cell RNA sequencing and network analysis to identify DPP4, CD40LG, BCL2, and TP53 as key regulatory targets in sepsis, providing insights into disease mechanisms and potential therapeutic interventions. Network pharmacology analysis suggests possible interactions with honeysuckle compounds, though experimental validation is needed.
Indexed as
Identifiers
40113718What 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.