Systemic lupus erythematosus (SLE) is an autoimmune disease that is frequently diagnosed in female patients, caused by multiple interacting factors. It has a complex pathogenesis which can affect almost any organ, from the kidneys to the cardiovascular, pulmonary, neurological, osteoarticular, and hematological systems. The present narrative review seeks to elucidate the role of reactive oxygen species (ROS) in the pathogenesis of SLE. The central question guiding this study is to what extent these serum protein modifications correlate with disease activity and organ damage in SLE. It is characterized by the decreased apoptosis and increased necrosis of T cells and the NETosis of granulocytes. Given the impact of an SLE diagnosis on one’s life, this narrative review aims to evaluate the intricacies of oxidative stress and its relevance to the pathogenesis and treatment of the disease. Topics such as understanding processes of oxidative stress, their damaging pathways, oxidative stress biomarkers, and their role in the future assistance of clinical decisions will be discussed in the article. The accurate determination of biomarkers is taught to improve both the diagnosis and the management of the disease, while antioxidant therapy may open a new door for the treatment.

Objectives: Pediatric obesity represents a significant public health challenge, requiring accurate and accessible tools for assessing body composition in pediatric populations. This systematic review (PROSPERO CRD42024592366) compares the methodological accuracy and clinical utility of bioelectrical impedance analysis (BIA) and dual x-ray absorptiometry (DXA) in evaluating obesity among children and adolescents. Methods: Utilizing a comprehensive search across PubMed, EMBASE, and Web of Science between 1 January 2014 and 31 December 2024, we identified 28 studies meeting our inclusion criteria. The studies included involved participants aged 2–17 years with obesity and compared BIA with DXA as the reference standard. The exclusion criteria were studies focusing on adults, those that assessed BC solely using anthropometry, and those that did not report primary outcomes relevant to the comparison of BIA vs. DXA. Results: The findings reveal that despite recent technological advances improving BIA’s precision, it consistently underestimates body fat percentage and fat mass, particularly in overweight and obese pediatric populations. DXA it is often used as a reference method in the evaluation of whole-body composition due to its higher accuracy and reliability. BIA offers significant practical advantages in accessibility, cost-effectiveness, and portability, but enhancements are needed to improve its accuracy for individual-level assessments. Conclusions: While BIA shows promise as a practical tool for body composition assessment in children, its accuracy varies significantly by device type. Multi-frequency segmental analyzers, such as InBody 720, demonstrate better agreement with DXA, whereas simpler models tend to underestimate fat mass. Therefore, conclusions regarding BIA performance should be device-specific and its clinical utility should be carefully weighed based on the technology used.

Childhood stroke can lead to lifelong disability. Developing algorithms for timely recognition of clinical and paraclinical signs is crucial to ensure prompt stroke diagnosis and minimize decision-making time. This study aimed to characterize clinical and paraclinical symptoms of childhood and neonatal stroke as relevant diagnostic criteria encountered in clinical practice, in order to develop algorithms for prompt stroke diagnosis. The analysis included data from 402 pediatric case histories from 2010 to 2016 and 108 prospective stroke cases from 2017 to 2020. Stroke cases were predominantly diagnosed in newborns, with 362 (71%, 95% CI 68.99–73.01) cases occurring within the first 28 days of birth, and 148 (29%, 95% CI 26.99–31.01) cases occurring after 28 days. The findings of the study enable the development of algorithms for timely stroke recognition, facilitating the selection of optimal treatment options for newborns and children of various age groups. Logistic regression serves as the basis for deriving these algorithms, aiming to initiate early treatment and reduce lifelong morbidity and mortality in children. The study outcomes include the formulation of algorithms for timely recognition of newborn stroke, with plans to adopt these algorithms and train a fuzzy classifier-based diagnostic model using machine learning techniques for efficient stroke recognition.

The paper reports on monitoring methylmalonic aciduria (MMA)-specific and non-specific metabolites via NMR urinomics. Five patients have been monitored over periods of time; things involved were diet, medication and occasional episodes of failing to comply with prescribed diets. An extended dataset of targeted metabolites is presented, and correlations with the type of MMA are underlined. A survey of previous NMR studies on MMA is also presented.

VASCULAR ENDOTHELIAL GROWTH FACTOR: AN IMPORTANT BIOMARKER IN PEDIATRIC ISCHEMIC STROKE

Neurological development is the foundation of the learning process and is essential for brain maturation. Brain development is a complex process that begins early, prenatally, and continues throughout life, consisting of a series of complex biological processes that shape the development of the nervous system, such as the formation of neurons, synapses, and neural circuits, as well as the establishment of neural communication pathways, the final product of which is the formation of brain structures, the development of skills and the individual configuration of each child. Optimal early childhood development spans diverse domains, including physical, social-emotional, and linguistic-cognitive aspects. Timely identification of at-risk children is of critical importance, as prompt referral to specialist interventions reduces the likelihood of long-term problems and improves outcomes in adulthood. Ensuring early access to interventions is a key priority in addressing developmental delays. Estimating prevalence and understanding specific types of delays are essential initial steps in early intervention planning.