Mina Rahmati, Naser Mobarra, Hossein Ghannadan,
Volume 7, Issue 2 (7-2019)
Abstract
Background and objectives: Ischemic stroke (IS) is a life-threatening disease which lacks reliable prognostic and/or diagnostic biomarkers. In the present study, we examined the serum oxidative stress balance (OSB) and evaluated its diagnostic and prognostic value for IS.
Methods: Sera from 52 IS patients and 52 sex- and age-matched healthy volunteers were obtained. All patients were subjected to the collection of samples at the time of admission, 24 and 48 hours later, at the time of discharge and three months later. OSB levels were assessed by spectrophotometry. Statistical analyses for diagnostic accuracy of quantitative measures were performed.
Results: We showed that OSB levels were elevated at the time of admission in comparison to normal subjects. ROC curve analysis expressed that OSB could be an acceptable diagnostic marker to discriminate IS patients from normal subjects (AUC = 0.7337; P<0.0001). Kaplan-Meier survival analysis showed that OSB had no prognostic value (P=0.8584).
Conclusion: Oxidative stress balance could be introduced as a suggested biomarker to segregate IS patients from normal subjects.
Milad Ahmad-Aghdami , Saeed Mohammadi ,
Volume 13, Issue 1 (9-2025)
Abstract
Systemic Lupus Erythematosus (SLE) is a complex autoimmune disease characterized by heterogeneous clinical manifestations and the production of autoantibodies, making early diagnosis challenging. Traditional diagnostic methods lack sensitivity and specificity, leading to delayed intervention and irreversible organ damage. Single-cell technologies offer a novel opportunity to investigate the cellular landscape of SLE at the level of individual cells. By profiling the gene expression, protein expression, and functional states of thousands of individual cells simultaneously, these technologies can reveal critical findings such as the expansion of type I interferon-producing pDCs and dysregulated T/B cell subsets involved in SLE pathogenesis. This editorial highlights the transformative potential of single-cell analysis in identifying disease-relevant cell populations and their functional states, ultimately paving the way for earlier diagnosis, personalized treatment, and improved outcomes for patients with SLE.
