Translational pediatrics最新文献

Background: Pneumonia remains a leading cause of morbidity and mortality in critically ill children, yet comprehensive prognostic biomarkers specifically validated in pediatric intensive care settings remain limited. Identifying readily available blood parameters that predict mortality risk could enhance early risk stratification and guide therapeutic interventions. This study aimed to evaluate the prognostic value of blood parameters for hospital mortality in critically ill pediatric pneumonia patients and develop machine learning (ML)-based predictive models.

Methods: This retrospective cohort study analyzed pediatric pneumonia patients (aged 3 months to 18 years) admitted to intensive care units for ≥24 hours from the Pediatric Intensive Care (PIC) database version 1.1. Multivariate Cox regression analyses assessed associations between blood parameters and hospital mortality, adjusting for age, gender, bacterial infection status, and pathogen detection. Restricted cubic spline analyses examined dose-response relationships. Six ML algorithms incorporating significant blood parameters and clinical covariates were developed and validated using 7:3 train-test split.

Results: A total of 606 children were included, with an overall hospital mortality of 14.4% (87/606). Multivariate Cox regression identified three significant prognostic factors: neutrophil percentage adjusted hazard ratio (HR): 1.017, 95% confidence interval (CI): 1.004-1.031, P=0.01], lymphocyte percentage (adjusted HR: 0.985, 95% CI: 0.970-0.999, P=0.04), and platelet-to-neutrophil ratio (PNR) (adjusted HR: 0.995, 95% CI: 0.989-1.000, P=0.04). Restricted cubic spline analyses revealed predominantly linear or U-shaped dose-response relationships. Among ML models, random forest demonstrated superior predictive performance with test area under the curve (AUC) of 0.877 (95% CI: 0.860-0.895), sensitivity of 80.9%, specificity of 79.1%, and accuracy of 79.5%. The model significantly outperformed individual blood parameters (neutrophil percentage AUC: 0.712; lymphocyte percentage AUC: 0.660; PNR AUC: 0.689), and decision curve analysis confirmed positive net benefit across threshold probabilities of 5-50%.

Conclusions: Neutrophil percentage, lymphocyte percentage, and PNR are independent prognostic indicators for mortality in critically ill pediatric pneumonia. ML-based models incorporating these parameters show promise for early mortality risk stratification in pediatric intensive care settings.

Background: Kawasaki disease (KD) is an acute, self-limited febrile illness primarily affecting children under 5 years of age. Platelets play a crucial dual role in both hemostasis and inflammatory/immune responses, contributing to vascular damage in diseases such as KD, making their study essential for the diagnosis and treatment of KD. Therefore, this study aimed to identify platelet-related diagnostic biomarkers, construct a machine learning-based diagnostic model, and computationally characterize their associated immune features, pathway activities, and regulatory networks in KD.

Methods: This study integrated transcriptomic datasets from 4 KD cohorts in the Gene Expression Omnibus database (training set: GSE68004/GSE73461; validation set: GSE100154/GSE63881). Platelet-associated differentially expressed genes were screened through differential analysis and Weighted Gene Co-expression Network Analysis. Four diagnostic biomarkers were identified via cross-validation using least absolute shrinkage and selection operator, random forest, and eXtreme Gradient Boosting algorithms, with model efficacy assessed through Receiver operating characteristic curve analysis. Immune infiltration characteristics were analyzed using single sample Gene Set Enrichment Analysis (GSEA) and CIBERSORT, pathway enrichment was performed via GSEA, molecular subtypes were classified using the non-negative Matrix Factorization algorithm, and miRNA and transcription factor (TF) regulatory networks were predicted through miRNet/NetworkAnalyst.

Results: We identified 4 platelet-associated biomarkers (CD63, F5, STXBP2, and SERPINA1) with exceptional diagnostic power. These genes orchestrate KD pathogenesis through dysregulated coagulation (F5), immune hyperactivation (CD63/STXBP2), and vascular injury (SERPINA1), further validated by their strong correlations with neutrophil infiltration and ribosome pathway suppression. Molecular subtyping revealed distinct immune-endotypes (e.g., neutrophil-dominant vs. natural killer-cell-enriched clusters), while regulatory network analysis uncovered has-miR-155-5p and TF hubs (SMAD5/SAP30/PHF8) as potential master regulators.

Conclusions: This study utilized platelet-associated biomarkers to establish a machine learning-based diagnostic model for KD and elucidated their pathogenic roles in immune dysregulation and vascular injury, thereby laying the foundation for improved diagnosis and targeted therapy in KD.

Background: Infants are at a high risk of food allergy (FA); however, owing to the lack of commonly recognized simple and noninvasive diagnostic tools, definitive diagnosis of infantile FA is challenging. In this study, we aimed to establish a diagnostic model comprising highly suggestive indicators to facilitate the early identification of infantile FA.

Methods: In this case-control study, we enrolled two groups of infants with suspected FA. FA diagnoses were confirmed through oral food challenges (OFCs). The training set, which included infants enrolled between 2022 and 2023, was used to develop a logistic regression diagnostic model and perform internal cross-validation. The testing set comprising previous cases between 2016 and 2021 was used to perform external validation. We assessed the discrimination and calibration of the diagnostic model using the area under the curve (AUC), Hosmer-Lemeshow goodness-of-fit test, calibration curve, and decision curve analysis (DCA).

Results: We identified variables for the diagnostic model, including eczema, stool form, hematochezia, failure to thrive (FTT), respiratory symptoms, and family history of allergic diseases. The AUCs for the training set, internal cross-validation, and external validation were 0.86 (0.83-0.90), 0.86 (0.76-0.95), and 0.87 (0.83-0.92), respectively, showing good diagnostic performance of the model. The Hosmer-Lemeshow goodness-of-fit test results and calibration curve showed that the model had good calibration. DCA results showed a high net benefit value in clinical decision-making.

Conclusions: The diagnostic model, constructed with the six aforementioned variables, can serve as a simple and noninvasive diagnostic tool for clinicians to effectively distinguish FA from similar diseases.

Background: Neuroblastoma (NB) is recognized as the predominant extracranial malignant solid tumor in children and adolescent; the prognosis for high-risk patients remains poor. This limitation stems from its low mutational burden, an absence of antigen-presenting molecules, and vascular irregularities, which collectively impede immune cell infiltration, characterizing NB as a prototypical "cold tumor". Intriguingly, metabolic pathways, especially through a novel glucose-dependent cellular death mechanism termed disulfidptosis and fatty acid metabolism (FAM), are pivotal in modulating the tumor's energy dynamics and activating the tumor microenvironment (TME). Therefore, this study aims to explore the prognostic value and immunological implications of disulfidptosis-related fatty acid metabolism (DFAM) within the NB TME.

Methods: To elucidate the implications of DFAM within the NB TME, this research included 971 NB patients. By using weighted gene co-expression network analysis (WGCNA), we constructed a prognostic risk score model based on DFAM, aimed at enhancing prognostication accuracy and informing therapeutic choices. The biological role of TFAP2D was validated in SK-N-AS and SK-N-BE2 cells via Cell Counting Kit-8 (CCK-8) assay, wound healing, and Transwell.

Results: Two distinct novel molecular subtypes were identified, revealing the correlations between DFAM and clinical-pathological features, prognostic outcomes, and TME infiltration patterns. The DFAM risk score model was established as an independent prognostic factor, correlated with immune cell infiltration and immunotherapeutic response. A novel discovery was the inhibitory effect of TFAP2D downregulation in NB cells on cellular survival, migration, and invasion.

Conclusions: This research demonstrates that the crosstalk between DFAM and immune cells plays an important role in forming the "cold" TME of NB. The construction of DFAM-related score and the identification of a novel molecular subtype significantly contribute to the evolution of immunotherapeutic strategies. Furthermore, the discovery of TFAP2D as a metabolic driver of tumor progression provides a potential target to disrupt the metabolic plasticity of high-risk NB.

Background: Sepsis, defined as life-threatening organ dysfunction due to a dysregulated host response to infection, remains a leading cause of pediatric mortality. High mobility group box 1 (HMGB1), a late inflammatory mediator, has shown prognostic value in adult sepsis, but its utility in pediatric populations remains inadequately investigated. This study aimed to evaluate HMGB1 as a prognostic biomarker for septic shock in children with sepsis and to develop a clinical prediction model.

Methods: In this prospective cohort study, we enrolled 46 pediatric patients (aged 1 month to 18 years) with sepsis and organ dysfunction at a tertiary hospital in China (March 2022 to December 2023). Serum HMGB1 levels were measured within 24 hours of admission. Patients were stratified into shock (n=17) and non-shock (n=29) groups. Receiver operating characteristic (ROC) curve analysis evaluated the diagnostic performance of HMGB1 and other biomarkers. Multivariable logistic regression identified independent predictors, which were integrated into a nomogram prediction model.

Results: Septic shock developed in 17 patients (37.0%). The shock group exhibited significantly elevated levels of HMGB1, procalcitonin (PCT), serum amyloid A (SAA), interleukin-6 (IL-6), fibrin degradation products, and urea (all P<0.05). ROC analysis showed that HMGB1 [area under the curve (AUC) 0.755], PCT (AUC 0.843), IL-6 (AUC 0.738), and SAA (AUC 0.704) predicted shock development. Multivariable analysis identified HMGB1 and PCT as independent risk factors. The nomogram combining these biomarkers achieved excellent discrimination (C-index 0.869, AUC 0.874) with sensitivity of 82.4% and specificity of 89.7%.

Conclusions: Serum HMGB1, particularly when combined with PCT in a nomogram model, demonstrates excellent prognostic accuracy for early identification of septic shock risk in pediatric sepsis. This practical bedside tool may facilitate timely risk stratification and guide clinical decision-making, though external validation is needed.

Rapid and accurate methods of assessing organ damage following radiation therapy (RT) in pediatric cancer patients represent a vital need. This is the pilot study that assesses critical organ damage during pediatric RT using cell-free DNA (cfDNA) methylation analysis, providing insights for future research on cfDNA methylation detection of organ damage and offering a method for rapid clinical detection of multi-organ injury. In this study, three pediatric patients with medulloblastoma, one with a germ cell tumor, one with a mixed germ cell tumor, and one with a neuroepithelial tumor were enrolled. They were divided by therapeutic intervention: two patients underwent conventional photon-based craniospinal irradiation (CSI), while four received proton therapy. One patient receiving photodynamic therapy experienced Grade 3 gastrointestinal toxicity during treatment. We measured the levels of fraction of cfDNA methylation in these patients before and after CSI with photon and proton RT. We then compared the trends in cell-free DNA methylation changes between proton and photon therapy with their respective dose distributions and clinical outcomes. cfDNA methylation trends correlated well with both the organ-specific dose profiles and clinical outcomes observed between proton and photon RT. A comparative analysis of pre-/post-CSI cfDNA methylation changes, clinical outcomes, dose volume histogram (DVH) data, and isodose distribution maps suggests that cfDNA methylation is expected to become a biomarker for detecting organ damage, and that proton therapy provides better critical organ protection than photon therapy in pediatric patients.

Background: High-altitude environments present unique challenges to brain adaptability. This study aimed to explore the brain magnetic resonance imaging (MRI) characteristics of neurologically normal Tibetan neonates, and to compare brain volumes and myelination status across different altitude levels.

Methods: This was a case-control exploratory study. A total of 30 neurologically normal infants in the high-altitude group (altitude: 3,650 m) and a total of 30 neurologically normal infants in the sea-level group (altitude: 4 m) were included in the study. The infants in the two groups were matched 1:1 using propensity score matching (PSM) for gestational age at birth, birth weight, sex, and postnatal age at MRI examination. The primary outcomes were differences in volumetrically segmented tissue (lateral ventricles, gray matter, and white matter) and intracranial volume (ICV) between the two groups. We further compared the differences among altitude subgroups. Myelination status was also assessed using the T1-weighted/T2-weighted (T1w/T2w) ratio.

Results: Compared with the sea-level group, ICV was significantly increased in the high-altitude group, an increase that appeared to be primarily attributable to larger gray matter and lateral ventricular volumes. The T1w/T2w ratio in the middle cerebellar peduncle (MCP) was significantly lower in the high-altitude group than the sea-level group. In the altitude subgroup analysis, ICV was found to be significantly increased in altitude subgroup 2 (4,000-4,800 m) but not in altitude subgroup 1 (3,500-4,000 m).

Conclusions: ICV was significantly increased in the high-altitude group compared to the sea-level group, especially in altitude areas above 4,000 m. Additionally, delayed myelination in the MCP was observed in the high-altitude group.

Background and objective: Pediatric emergency care (PEC) is a specialized field that addresses the unique physiological, psychological, and social needs of children, presenting distinct challenges compared to adult emergency medicine. These differences influence disease presentation, treatment response, and communication, necessitating tailored care strategies and robust parental involvement. This narrative review aimed to systematically synthesize current evidence and clinical practices to identify and discuss the primary challenges in PEC and an effective strategy for improving the quality of care.

Methods: We adopted a narrative review methodology to explore the unique challenges and coping strategies in PEC. A comprehensive literature search was conducted using the PubMed database with combinations of keywords "pediatric emergency", "child health", "coping strategies", "multidisciplinary care team", and "best practices", focusing on studies published between 2010 and 2024.

Key content and findings: This review highlights that the physiological peculiarities of children, such as differences in airway anatomy and drug metabolism, often lead to diagnostic complexities. Psychological factors, including anxiety and fear in both children and their parents, significantly impact clinical outcomes. Key findings show that a comprehensive approach integrating multidisciplinary teamwork, standardized protocols, continuous training, and leveraging appropriate technologies like simulation and digital tools is essential. Furthermore, family-centered care emerged as a critical component, enhancing patient cooperation and reducing distress.

Conclusions: A multifaceted strategy that combines clinical expertise with family engagement and systemic-level improvements is needed to improve PEC and ensure patient safety and optimize outcomes.

Background: High fructose corn syrup (HFCS) has increasingly displaced sucrose throughout the world due to its lower cost. Importantly, there has been more fructose in HFCS, vis a vis glucose, than is considered safe, and generally-recognized-as-safe (GRAS). Fructose is linked to hypertension, lipid dysregulation and insulin resistance, all of which increase the risk for cardiovascular disease (CVD). This study aimed to evaluate the long-term effects of adolescent high fructose intake on adult cardiac function and elucidate the mechanisms. Most studies to date overemphasize the overconsumption of sugar, HFCS, and sugar-sweetened beverages (SSBs) in particular as the primary culprit, while placing insufficient emphasis on the inherently unsafe fructose-to-glucose ratio in HFCS. Moreover, a growing body of research has identified a close correlation between direct fructose exposure and the pathogenesis of various diseases.

Methods: Young mice were given high-fructose drinking (HFD) water from 3 to 8 weeks of age. Cardiac ultrasound and histochemical staining were performed to assess cardiac structure and pathology. Heart tissues and cells were collected for quantitative reverse transcriptase polymerase chain reaction (qRT-PCR) and Western blot analysis to determine the mRNA levels of Anp, Bnp, β-MHC, Col1a1, Col3a1, Cpt1b, as well as histone acetylation status.

Results: Compared with controls, HFD mice exhibited ventricular dilation, impaired cardiac function, cardiomyocyte hypertrophy, and increased myocardial fibrosis. In the high-fructose group, Bnp and β-MHC mRNA expression was upregulated, whereas Cpt1b expression was reduced. Mechanistically, histone acetylation levels were elevated in the high-fructose group, accompanied by decreased SIRT1 protein expression in heart tissues-a key indicator of aging related heart changes and CVD.

Conclusions: Adolescent high fructose intake impairs adult cardiac function by downregulating Cpt1b and increasing histone acetylation, suggesting novel mechanisms and therapeutic targets for fructose-induced cardiac dysfunction.