Graphical abstract

In the absence of medical diagnosis evidences, it is difficult for the experts to opine about the grade of disease with affirmation. Generally many tests are done that involve clustering or classification of large scale data. However many tests could complicate the main diagnosis process and lead to the difficulty in obtaining the end results, particularly in the case where many tests are performed. This kind of difficulty could be resolved with the aid of machine learning techniques. In this research, we present a comparative study of different classification techniques using three data mining tools named WEKA, TANAGRA and MATLAB. The aim of this paper is to analyze the performance of different classification techniques for a set of large data. A fundamental review on the selected techniques is presented for introduction purpose. The diabetes data with a total instance of 768 and 9 attributes (8 for input and 1 for output) will be used to test and justify the differences between the classification methods. Subsequently, the classification technique that has the potential to significantly improve the common or conventional methods will be suggested for use in large scale data, bioinformatics or other general applications.

A protocol was established for mass propagation of the valuable medicinal plant Ficus religiosa L. (Moraceae) through in vitro culture using apical and axillary buds of young sprouts from selected plants. Best shoot induction was observed on MS basal medium supplemented with 0.5 mg/l BAP + 0.1 mg/l IAA, in which 78 per cent of the explants produced 16 shoots per culture. Repeated subcultures in the same medium, resulted rapid shoot multiplication with 24 shoots per culture. In vitro raised shoots rooted on half strength MS supplemented with 2.0 mg/l IBA + 0.1 mg/l NAA. For acclimatization and transplantation, the plantlets in the rooting culture tubes were kept in normal room temperature for seven days before transplanting in pots where plantlets were reared for three weeks. The survival rate of regenerated plantlets was 85 per cent.

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Background and objectives: Low vitamin D is a global problem in all age groups as is osteoporosis in postmenopausal women. The present study was carried out in an urban hospital to assess serum 25-hydroxyvitamin D [25(OH)D] level and bone mineral density (BMD) in postmenopausal women (PMW) and to evaluate correlation between serum 25(OH)D levels and BMD. Methods: A single center cross-sectional study was conducted among 133 apparently healthy PMW aged 45 years and above with the history of complete cessation of menstruation over a period of more than 1 year. Serum 25(OH)D, BMD and serum intact parathyroid hormone (iPTH) were determined. Patients having both vitamin D and BMD values were analyzed for correlations. Similarly, correlation of vitamin D, iPTH and BMD were determined. Results: Among the study population, 63 (47.4%) had deficient (<20 ng/ml), 46 (34.6%) had insufficient (20-30ng/ml) and 24(18%) had sufficient (30-100ng/ml) levels of serum 25(OH)D. Among the 121 patients whose BMD was done, 52 (43.0%) and 60 (49.6%) had osteoporosis and osteopenia respectively. Serum iPTH levels were normal in 34 (89.5%) patients. The proportion of osteopenia and osteoporosis in vitamin D deficient group were 44.1% and 50.8% and in insufficient group 47.5 and 45.0%, respectively. Age had significant negative correlation with BMD value (r=-0.246, p=.005) and significant positive correlation with serum iPTH (r=0.358, p=.024). There was no statistically significant influence of serum 25(OH)D or iPTH on occurrence of osteoporosis (P=0.322 and P=0.592 respectively). Conclusion: A large proportion of postmenopausal women had low vitamin D levels and as well as osteopenia and osteoporosis. Low vitamin D level coexisted with low BMD. However, there was no correlation between serum 25(OH)D levels and BMD status. IMC J Med Sci 2018; 12(2): 44-49

Objectives: To describe the prevalence of depression among post-graduate medical students and to evaluate some related risk factors.Methodology: This cross-sectional survey was done in three post-graduate medical teaching institutes in Dhaka, Bangladesh in February 2013. A preformed questionnaire including some demographic, socio-economic and work related variables was used for the purpose and depression was diagnosed and severity assessed by using Hamilton Rating Scale for Depression (HAM-D).Results: A total of 100 post-graduate medical trainees were given a preformed questionnaire. Among them 53 students filled it up properly and sent back in given time (response rate was 53%

An efficient protocol was established for rapid and large scale propagation of woody aromatic medicinal plant Vitex negundo L. by in vitro shoot multiplication from shoot tips and nodal segments of mature plant. Of the four different growth regulators BA, Kn, GA 3 , NAA and coconut water, MS fortified with BA 1.0 mg/l was found to be the most effective for inducing multiple shoots from nodal explants. The percentage (96%) of shoot multiplication per node (21.83) was highest up to second subculture passages, after which there was a gradual decline in shoot development. Best rooting was induced (93%) in excised shoots on half strength MS medium supplemented with an optimal combination of NAA (0.3 mg/l). Soil, compost and sand (1:1:1) mixture was the most suitable planting substrate for hardening. The survival rate was 80% and the regenerated plants were successfully transferred to the soil.

Melioidosis is an under-recognized fatal disease in humans, caused by the Gram-negative bacterium Burkholderia pseudomallei. Globally, more than 35,000 human melioidosis cases have been reported since 1911. Soil acts as the natural reservoir of B. pseudomallei. Humans may become infected by this pathogen through direct contact with contaminated soil and/or water. Melioidosis commonly occurs in patients with diabetes mellitus, who increase the occurrence of melioidosis in a population. We carried out a systematic review and meta-analysis to investigate to what extent diabetes mellitus affects the patient in getting melioidosis. We selected 39 articles for meta-analysis. This extensive review also provided the latest updates on the global distribution, clinical manifestation, preexisting underlying diseases, and risk factors of melioidosis. Diabetes mellitus was identified as the predominant predisposing factor for melioidosis in humans. The overall proportion of melioidosis cases having diabetes was 45.68% (95% CI: 44.8–46.57, p < 0.001). Patients with diabetes mellitus were three times more likely to develop melioidosis than patients with no diabetes (RR 3.40, 95% CI: 2.92–3.87, p < 0.001). The other potential risk factors included old age, exposure to soil and water, preexisting underlying diseases (chronic kidney disease, lung disease, heart disease, and thalassemia), and agricultural activities. Evidence-based clinical practice guidelines for melioidosis in patients with diabetes mellitus may be developed and shared with healthcare professionals of melioidosis endemic countries to reduce morbidity.