RESUMO
BACKGROUND: Intellectual disability (ID) is registered in 2%-3% of newborns. In most cases, the causes are not identifiable. OBJECTIVE: We explored the correlation between the intellectual disability and gestational age, birth weight, Apgar score, familial diseases, congenital anomalies, and acquired medical disorders, with the aim to estimate the prevalence and severity of comorbidities in the affected children. METHODS: Our study included 22 children with ID, and 24 with proper psychomotor development, aged 5-10 who were not considered to have ID. RESULTS: The presence of familial disorders and CNS congenital anomalies increased the risk of ID 4.147 and 2.59 times, respectively. The risk for other congenital and noncongenital diseases was higher (7.38 and 1.4 times, respectively) in children with intellectual disability. CONCLUSIONS: Children with intellectual disabilities have higher incidence of congenital diseases, family disorders and a higher frequency of acquired disorders during childhood. Apgar score is a sensitive predictor of morbidity regarding congenital as well as noncongenital medical conditions.
Assuntos
Comorbidade , Anormalidades Congênitas/epidemiologia , Deficiência Intelectual/epidemiologia , Índice de Apgar , Peso ao Nascer , Criança , Pré-Escolar , Doença , Epidemiologia , Feminino , Idade Gestacional , Humanos , Incidência , Masculino , Prevalência , Fatores de RiscoRESUMO
Carbonic anhydrase is a metalloprotein, an enzyme with strong inhibition in antibacterial treatment. This study presents QSAR modeling for a series of 41 chemical compounds, 40 sulfonamides and one sulfamate, including 13 clinically tested drugs as carbonic anhydrase inhibitors based on the Monte Carlo optimization with molecular descriptors based on the SMILES notation and local invariants of the molecular graph, and field 3D based methods. Conformation independent QSAR models were developed for three random splits and a 3D QSAR model for one random split into the training and test sets. The statistical quality of the developed models, including robustness and predictability, was tested using various statistical approaches and the results that were obtained were very good. An excellent correlation between the results from the conformation independent and the 3D QSAR model was obtained. A novel statistical metric known as the index of ideality of correlation was used for the final assessment of the model, and the obtained results were good. Molecular fragments responsible for the increases and decreases of a studied activity were defined and further used for the computer-aided design of new compounds as potential carbonic anhydrase inhibitors. Molecular docking was applied for the final assessment of the developed QSAR model and designed inhibitors, and an excellent correlation between the results from QSAR modeling and molecular docking studies was obtained.Communicated by Ramaswamy H. Sarma.