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Diabetes mellitus is a chronic metabolic disorder which is associated with hyperglycemia. It is caused by a derangement in the secretion or function of the endocrinal portion of the pancreas. There is a close anatomical and functional relationship between its exocrine and endocrine portions. The current study was designed to evaluate the changes in amylase levels in diabetic patients and study the correlation of amylase activity with chronic hyperglycemia and duration of diabetes mellitus. The results of study were revealed that amylase activity was low in diabetic patients compared with control and there was negative correlation between amylase activity and hyperglycemia and duration .

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This study was conducted to describe the role of the chloroplast maturase K (matK) genetic polymorphism in the reciprocal crossing between five barley varieties using several in vitro / in silico tools. Besides, the final consequences of the matK gene polymorphism on its protein structure, function, and interactions were predicted computationally. Five parental varieties were crossed to each other by full reciprocal crossing design, DNA was extracted from seeds and two different primers’ pairs were designed to scan matK gene. Then, polymerase chain reaction - single-stranded conformation polymorphism (PCR-SSCP) were performed. Two distinct haplotypes in both parents and artificial F1 hybrids in the matK gene were observed in both amplified fragments. This finding indicated that the studied gene had no participation in the reciprocal crossing performed. Three SNPs were identified; two of them are non-synonymous (nsSNPs), namely G387V and L459M. The effect of these missense mutations on the matK protein was analyzed by several in silico tools. It was shown that the coding SNP, L459M was predicted to have much more effective consequences on matK protein structure and function. While the I-Mutant 2.0 prediction tool showed a decrease in stability for these two nsSNPs, which may destabilize the protein interactions to some extent. In conclusion, though the observed missense mutations in the matK gene have no suggestive role in the reciprocally crossed barley varieties, they caused dramatic alterations in several matK protein moieties, which may lead to potential subsequent changes in the matK protein-mediated RNA splicing mechanisms.

Diabetes is one of the most common diseases that has had devastating effects on the general population. It is also among the most popular research trends in modern medicine. Thus, due to the complexity and desirability of this particular affliction, there is a lot of demand towards understanding this disease better, so that it can pave the way towards better solutions in combating diabetes. The aim of this review is to provide a categorization of the risk factors leading to Type II Diabetes. In order to provide a justification for the type of diabetes, an explanation is provided which covers the other types of diabetes and their relative infliction rate. Once the basics understanding of diabetes established, the various aspects that increase the risk of Type II Diabetes (T2D) can be classified. Several different facets are studied in order to come up with a novel classification of the disease. The classification divides the risk factors into sociodemographic and pathophysiological attributes. The major affecting attribute is identified to be genetics, as it is intertwined with other attributes. With the use of bioinformatics, advanced gene sequencing techniques can be applied that would enable the identification of patterns more closely affecting Type II Diabetes. These patterns can be cross-analyzed with pre-existing conditions in order to identify similarities and possible risk factors from other diseases. Ultimately, this classification provides a deeper understanding of the factors affecting Type II Diabetes.