Association of Serum Ferritin with Risk of Anemia in Non-Diabetic Adolescents with Family History of Type 2 Diabetes Mellitus

Background: Controversy occurs in the relationship between serum ferritin levels, insulin resistance and risk of developing anemia in adolescents with family history of diabetes. Aims & Objectives: This study was designed to find out the association between serum ferritin levels with risk of developing anemia in non-diabetic adolescents with family history of type 2 diabetes mellitus (T2DM). Materials & Methods: A descriptive cross-sectional was conducted in a local medical institute of Lahore. Study included 50 non-diabetic, non-obese male / female adolescent with family history of type 2 diabetes mellitus and 50 healthy male/female non-obese adolescents without family history of T2DM considered as controls. Level of serum ferritin and serum insulin was estimated by Enzyme Linked Immunosorbent Assay. Blood glucose was estimated by auto-analyzer. Insulin resistance was calculated by HOMA-IR index and beta cell function was assessed by HOMA- beta index. Results: Levels of fasting blood sugar, insulin resistance were found to be increased with decreased level of serum ferritin and decrease beta cell function in both male as well as female cases as compared to controls. Negative correlation was found between serum ferritin and insulin resistance while a positive correlation was found between serum ferritin and beta cell function. Conclusions: Low level of serum ferritin is associated with reduced beta cell function and increased insulin resistance. This may increase the risk of developing iron deficiency anemia that can affect both immune system as well as increase susceptibility to infections.

Similarity Identification and Measurement Between Two Web Ontologies

Nowadays, the web is the main collection of information resources but the retrieval of relevant and precise information from the web is a serious problem. The reason of this problem is the way web-contents are stored and formalized. With the realization of the ontology-based web, it is being tried to overcome this problem, but the ontologies may themselves suffer from heterogeneity when they are simultaneously used. Then, a need arises to identify and measure the similarity between concepts of those ontologies to overcome the said problem. Many investigators did work on this problem but still some issues need to be addressed. In this dissertation, a semi-automatic technique has been proposed for similarity identification and measurement between two web ontologies. The explicit semantics of concepts, in addition to their linguistic and taxonomic characteristics, is the key consideration and feature of the proposed technique. This proposed technique identifies all candidate pairs of similar concepts without omitting any similar-pair. The semantic relations and degree of similarity computed from new criteria, make the technique well-suited with the theme of semantic web. This technique can be used with different types of operations on ontology such as merging, mapping and aligning. We have implemented the proposed technique in Java, and validated it through different case studies. By comparing and analyzing the results of these case studies, a reasonable improvement in terms of completeness, correctness and overall quality of results, has been found.