Aceruloplasminemia presenting with microcytic anemia in a Turkish boy due to a novel pathogenic variant.

Aceruloplasminemia inherited autosomal recessively in the ceruloplasmin gene is a progressive disease with iron accumulation in various organs such as the brain, liver, pancreas, and retina. Ceruloplasmin gene encodes ceruloplasmin protein, which has ferroxidase activity and is involved in copper and iron metabolism. Progressive neurotoxicity, retinopathy, and diabetes may develop in about 40-60 decades. In addition, microcytic anemia accompanied by high ferritin and low ceruloplasmin level that develop at earlier ages can be first manifestation. Iron chelation may be utilized in the treatment to reduce the toxicity. Early diagnosis and treatment may delay the onset of symptoms. A 14-year-old male patient was followed up with microcytic anemia since an eight-years old. Anemia was accompanied by microcytosis, high ferritin, and low copper and ceruloplasmin levels. A novel homozygous c.690delG variant was detected in ceruloplasmin by whole exome sequencing. Clinical, laboratory and imaging findings of the patient demonstrated aceruloplasminemia. We present a boy with persistent microcytic anemia of the first manifestation at the age of eight, as the youngest case of aceruloplasminemia in the literature. Thereby, aceruloplasminemia should be kept in mind in the etiology of microcytic anemia whose cause couldn't found in childhood.

An Investigation into the Relationship among Psychiatric, Demographic and Socio-Economic Variables with Bayesian Network Modeling.

The aim of this paper is to investigate the factors influencing the Beck Depression Inventory score, the Beck Hopelessness Scale score and the Rosenberg Self-Esteem score and the relationships among the psychiatric, demographic and socio-economic variables with Bayesian network modeling. The data of 823 university students consist of 21 continuous and discrete relevant psychiatric, demographic and socio-economic variables. After the discretization of the continuous variables by two approaches, two Bayesian networks models are constructed using the b n l e a r n package in R, and the results are presented via figures and probabilities. One of the most significant results is that in the first Bayesian network model, the gender of the students influences the level of depression, with female students being more depressive. In the second model, social activity directly influences the level of depression. In each model, depression influences both the level of hopelessness and self-esteem in students; additionally, as the level of depression increases, the level of hopelessness increases, but the level of self-esteem drops.