PubMed · 9688209
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J W Davies. 1998. Recent references.. https://doi.org/10.1016/s0305-4179(98)90067-5
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BACKGROUND: Burn injuries trigger complex immune responses and gene expression changes, impacting wound healing and systemic inflammation. Understanding these changes is crucial for identifying biomarkers and therapeutic targets. METHODS: We analyzed two gene expression omnibus datasets (wound tissue [GSE8056] and blood [GSE37069]) to identify differentially expressed genes (DEGs) in burn injury samples versus controls. Immune cell proportions were assessed using CIBERSORT. Functional enrichment analyses (Gene Ontology and Kyoto Encyclopedia of Genes and Genomes) and protein-protein interaction networks were constructed to identify key genes and pathways. RESULTS: We identified 1170 upregulated and 1227 downregulated DEGs. Gene Ontology analysis revealed enrichment in neutrophil activation, inflammatory response, and extracellular matrix organization. Kyoto Encyclopedia of Genes and Genomes analysis highlighted cytokine-cytokine receptor interaction, TNF, and IL-17 signaling pathways. Immune infiltration analysis showed significant changes in neutrophils, macrophages (M1/M2), and T-cell subsets. Protein-protein interaction network analysis identified five hub genes: JUN, STAT1, Bcl2, MMP9, and TLR2. CONCLUSIONS: This study provides a comprehensive bioinformatic analysis of gene expression and immune responses in burn injuries. The identified DEGs, hub genes, and pathways offer insights into the immune response mechanisms and suggest potential targets for diagnostic and therapeutic interventions in burn injury management.
Various diseases cause abnormalities in the composition of blood and urine by increase or decrease of concentrations of its constituents or through the appearance of new compounds therein. The analysis of blood samples obtained from a healthy individual and burns patients, for its cystine contents has been done successfully using direct current poloragraphy (DCP), differential pulse polarography (DPP) and differential pulse anodic stripping voltammetry (DPASV). The observed data was analysed statistically. The standard deviation and coefficient of variance of the data proved high reliability and accuracy of the method. In Bredicka Cobaltous solution (0.001 M CoCl(2)+0.1 M NH(4)OH+0.1 M NH(4)Cl) at pH 8.5+/-0.02, cystine present in blood samples produces two step catalytic hydrogen reduction wave with peak potential (E(P)) values equal to -l.22 and -1.46 V vs SCE. The height of the second wave was found to be proportional to cystine concentration. Blood samples obtained from a healthy individual and those from cases of burns having different percentages (16, 13, 9 and 6%) were analysed. Monitoring of the recovery of a patient (burn case 58%) after different time intervals during the treatment period was also done, till the patient was relieved from the hospital. The method has proved to be convenient and less time consuming for the clinical purpose.
We provide non-parametric estimates of the marginal cumulative distribution of stage occupation times (waiting times) and non-parametric estimates of marginal cumulative incidence function (proportion of persons who leave stage j for stage j' within time t of entering stage j) using right-censored data from a multi-stage model. We allow for stage and path dependent censoring where the censoring hazard for an individual may depend on his or her natural covariate history such as the collection of stages visited before the current stage and their occupation times. Additional external time dependent covariates that may induce dependent censoring can also be incorporated into our estimates, if available. Our approach requires modelling the censoring hazard so that an estimate of the integrated censoring hazard can be used in constructing the estimates of the waiting times distributions. For this purpose, we propose the use of an additive hazard model which results in very flexible (robust) estimates. Examples based on data from burn patients and simulated data with tracking are also provided to demonstrate the performance of our estimators.