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Background: Sickle cell disease (SCD) is a genetic monogenic disorder with variable clinical manifestations and is characterized by the presence of the variant hemoglobin S. Renal damage is common in patients with SCD, which begins in childhood, progressing with age, a fact that makes nephropathy one of the possible complications. This can compromise patients’ quality of life and decrease survival. Classical biomarkers such as creatinine, are not able to detect early renal lesions, which makes kidney injury molecule-1 (Kim-1) and N-acetyl-β-D-glucosaminidase (NAG) possible biomarker candidates in the prediction of renal disease in sickle cell anemia patients. Objective: Determine KIM-1 and NAG urine levels in sickle cell anemia patients and a control group. Methods: The study was a cross-sectional study with 56 individuals up to 17 years of age, 32 of whom had sickle cell disease and 24 healthy individuals. All were treated at the Laboratorio de Analises Clinicas da Faculdade de Farmácia da UFBA. The local ethical committee approved the study and blood samples were collected after signing informed consent forms. Hematological analyses were performed with automated protocols. KIM-1 and NAG urine levels were investigated by immunoenzymatic assay (ELISA) as per manufacturer protocols (USCN, USA). All data were analyzed in Epi Info v. 7.2 (CDC, EUA), considering p < 0.05. Results: The results showed that patients with sickle cell anemia have a characteristic hemolytic profile. This is indicated by reticulocyte count and LDH values (mean of 8.7% ± 4.5% and 914.55 ± 382.12 mg/dL, respectively) lipid profile with low HDL, with a mean of 33.29 ± 8.30 mg/dL, compared to 44.47 ± 10.05 mg/dL in the control group. KIM-1 and NAG levels were significantly higher (p < 0.0001 for both) in the patients’ group, compared with the control group (6.95 ± 7.13 pg/mL vs 1.72 ± 1.87 pg/mL for KIM-1 and 0.43 ± 042 ng/mL vs 0, 07 ± 0.11 ng/mL for NAG). Discussion: Previous studies have shown that KIM-1 has been associated with albuminuria and hemolysis and may be a potential biomarker in pediatric SCA patients SCA (Hamideh et al., 2014, Belisario et. 2019). According to Unal and others NAG levels were found to be insufficient for the evaluation of SCA nephropathy in their studies. However, Tchernychev and others (2021) used NAG as a predictor of nephrophathy in Townes HbSS mice. Conclusion: KIM-1 and NAG levels were higher in the patients’ group, which suggests it may be incorporated in a follow up of sickle cell anemia patients in focus to identify early renal damage.

This systematic review explores the application of machine learning (ML) algorithms in sickle cell disease (SCD), focusing on diagnosis and several clinical characteristics, such as early detection of organ failure, identification of drug dosage, and classification of pain intensity. A comprehensive analysis of recent studies reveals promising results in using ML techniques for diagnosing and monitoring SCD. The review covers various ML algorithms, including Multilayer Perceptron, Support Vector Machine, Random Forest, Logistic Regression, Long short-term memory, Extreme Learning Machines, Convolutional Neural Networks, and Transfer Learning methods. Despite significant advances, challenges such as limited dataset sizes, interpretability concerns, and risks of overfitting are identified in studies. Future research directions entail addressing these limitations by harnessing larger and more representative datasets, enhancing model interpretability, and exploring advanced ML techniques like deep learning. Overall, this review underscores the transformative potential of ML in increasing the diagnosis, monitoring and define prognosis of sickle cell disease while also highlighting the need for further investigation in the field., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Machado et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

SARS-CoV-2 has caused a high number of deaths in several countries. In Brazil, there were 37 million confirmed cases of COVID-19 and 700,000 deaths caused by the disease. The population size and heterogeneity of the Brazilian population should be considered in epidemiological surveillance due to the varied tropism of the virus. As such, municipalities and states must be factored in for their unique specificities, such as socioeconomic conditions and population distribution. Here, we investigate the spatiotemporal dispersion of emerging SARS-CoV-2 lineages and their dynamics in each microregion from Sergipe state, northeastern Brazil, in the first 3 years of the pandemic. We analyzed 586 genomes sequenced between March 2020 and November 2022 extracted from the GISAID database. Phylogenetic analyses were carried out for each data set to reconstruct evolutionary history. Finally, the existence of a correlation between the number of lineages and infection cases by SARS-CoV-2 was evaluated. Aracaju, the largest city in northeastern Brazil, had the highest number of samples sequenced. This represented 54.6% (320) of the genomes, and consequently, the largest number of lineages identified. Studies also analyzed the relationship between mean lineage distributions and mean monthly infections, daily cases, daily deaths, and hospitalizations of vaccinated and unvaccinated patients. For this, a correlation matrix was created. Results revealed that the increase in the average number of SARS-CoV-2 variants was related to the average number of SARS-CoV-2 cases in both unvaccinated and vaccinated individuals. Thus, our data indicate that it is necessary to maintain epidemiological surveillance, especially in capital cities, since they have a high rate of circulation of resident and non-resident inhabitants, which contributes to the dynamics of the virus., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Freitas, Sena, Fukutani, Santos, Neto, Ribeiro, dos Reis, Balbino, Sá Paiva Leitão, de Aragão Batista, Lipscomb and Moura.)