Identification and verification of feature biomarkers associated with immune cells in neonatal sepsis.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:36855207", "kind": "science-record", "revision": 3, "content_hash": "sha256:f9bb812e9481b5c3ac4fb8e836c9888bb692fb7536a70e632b90c5af85cbd6f7", "created_at": "2026-11-01T19:01:29Z", "updated_at": "2026-11-01T22:08:57Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identification and verification of feature biomarkers associated with immune cells in neonatal sepsis.", "doi": "10.1186/s40001-023-01061-2", "pmid": "36855207", "authors": ["Weiqiang Liao", "Huimin Xiao", "Jinning He", "Lili Huang", "Yanxia Liao", "Jiaohong Qin", "Qiuping Yang", "Liuhong Qu", "Fei Ma", "Sitao Li"], "journal": "European journal of medical research", "year": 2023, "abstract": "BACKGROUND: Neonatal sepsis (NS), a life-threatening condition, is characterized by organ dysfunction and is the most common cause of neonatal death. However, the pathogenesis of NS is unclear and the clinical inflammatory markers currently used are not ideal for diagnosis of NS. Thus, exploring the link between immune responses in NS pathogenesis, elucidating the molecular mechanisms involved, and identifying potential therapeutic targets is of great significance in clinical practice. Herein, our study aimed to explore immune-related genes in NS and identify potential diagnostic biomarkers. Datasets for patients with NS and healthy controls were downloaded from the GEO database; GSE69686 and GSE25504 were used as the analysis and validation datasets, respectively. Differentially expressed genes (DEGs) were identified and Gene Set Enrichment Analysis (GSEA) was performed to determine their biological functions. Composition of immune cells was determined and immune-related genes (IRGs) between the two clusters were identified and their metabolic pathways were determined. Key genes with correlation coefficient > 0.5 and p < 0.05 were selected as screening biomarkers. Logistic regression models were constructed based on the selected biomarkers, and the diagnostic models were validated.\nRESULTS: Fifty-two DEGs were identified, and GSEA indicated involvement in acute inflammatory response, bacterial detection, and regulation of macrophage activation. Most infiltrating immune cells, including activated CD8 + T cells, were significantly different in patients with NS compared to the healthy controls. Fifty-four IRGs were identified, and GSEA indicated involvement in immune response and macrophage activation and regulation of T cell activation. Diagnostic models of DEGs containing five genes (PROS1, TDRD9, RETN, LOC728401, and METTL7B) and IRG with one gene (NSUN7) constructed using LASSO algorithm were validated using the GPL6947 and GPL13667 subset datasets, respectively. The IRG model outperformed the DEG model. Additionally, statistical analysis suggested that risk scores may be related to gestational age and birth weight, regardless of sex.\nCONCLUSIONS: We identified six IRGs as potential diagnostic biomarkers for NS and developed diagnostic models for NS. Our findings provide a new perspective for future research on NS pathogenesis.", "claims": [{"id": "claim-method", "statement": "LASSO algorithm was used to construct a diagnostic model to classify the training dataset into NS and control groups.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36855207", "locator": "sections[5] \"Significance of gene expression signatures in NS diagnosis\" paragraph 2", "quote": "LASSO algorithm was used to construct a diagnostic model to classify the training dataset into NS and control groups."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36855207", "locator": "sections[23] \"Availability of data and materials\" paragraph 2", "quote": "The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request."}], "state": "complete"}, {"id": "claim-target-result", "statement": "We identified six IRGs as potential diagnostic biomarkers for NS and developed diagnostic models for NS.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:36855207", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "We identified six IRGs as potential diagnostic biomarkers for NS and developed diagnostic models for NS."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "We identified six IRGs as potential diagnostic biomarkers for NS and developed diagnostic models for NS.", "steps": [{"id": "read_published_estimate", "order": 1, "name": "Read the published estimate from the source", "kind": "other", "state": "complete", "blocked_on": null, "description": "The claim, method and evidence span published with the source article.", "duration_hours": null, "parameters": {}, "inputs": ["source:pmid:36855207"], "outputs": ["the published estimate and its evidence"], "instruments": [], "reagents": []}, {"id": "obtain_source_data", "order": 2, "name": "Obtain the source data from the named repository", "kind": "data-preparation", "state": "complete", "blocked_on": null, "description": "The GEO series accession resolves and its sample accessions are listed. This lane did not download the dataset or read its licence.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE25504"], "outputs": ["the source data with its repository provenance"], "instruments": [], "reagents": []}, {"id": "run_analysis", "order": 3, "name": "Run the published analysis", "kind": "analysis", "state": "complete", "blocked_on": null, "description": "Apply the paper's statistical method to the resolved series and compare the result with the published target.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE25504"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:36855207", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1186/s40001-023-01061-2", "sha256": 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