Dynamic Muscle Function Parameters in Indian Children and Adolescents with Type 1 Diabetes Mellitus: A Case-Control Study.

Introduction: Recent evidence reveals that type 1 diabetes mellitus (T1DM) impairs muscle function (MF) in adolescents. However, despite its importance in physical well-being, data on dynamic MF in Indian children and adolescents (C and Y) with T1DM are scarce. We assessed MF using Jumping Mechanography (JM, a measurement method for motion analysis and assessment of muscle power and force). (1) To assess dynamic MF by JM in C and Y with T1DM as compared to healthy controls (2) To determine predictors of MF in children with T1DM. Methods: A cross-sectional observational study on 266 children (133 - T1DM duration >1 year with no known comorbidities + 133 age and gender-matched healthy controls) aged 6-19 years. Anthropometry, body composition, and MF (maximum relative power Pmax/mass, maximum relative force Fmax/BW by JM) were recorded. The lean mass index (LMI) was calculated as lean mass (kg)/height (m2). HbA1c was assessed in T1DM. Independent sample t-test and linear regression were performed. Results: MF parameters (Pmax/mass 33.5 ± 7.2 vs 38.0 ± 8.6 W/kg and Fmax/BW 10.5 ± 2.9 vs 11.4 ± 4.1 N/kg, P < 0.05) were significantly lower in T1DM group vs controls. Positive association of body mass index and LMI with both MF parameters and negative association of insulin requirement and HbA1c with Fmax was observed in T1DM. Predictors of MF identified were MMI (Pmax/mass:b = 1.6,95%CI = 0.6-2.6; Fmax/BW:b =2.0,95%CI = 1.6-2.4) and HbA1c (Pmax/mass:b = -2.1,95%CI = -4.5--0.5; Fmax/BW:b = -1.1,95%CI = -2.0--0.2) (P < 0.05). Conclusion: C and Y with T1DM exhibits compromised muscle function. Poor glycaemic control increases the risk of having decreased MF, irrespective of diabetes duration and may contribute to sarcopenia in adulthood.

Algorithmic approach to find S -consistency in Common-Edge signed graph.

Common-Edge signed graph C E ( S ) of a signed graph S is a signed graph whose vertex-set is the pairs of adjacent edges in S and two vertices are adjacent if the corresponding pairs of adjacent edges of S have exactly one edge in common, with the sign same as that of Common-Edge. S -Marked signed graph T is a signed graph which receives the marking µ due to the signed graph S called marker. Further, T is S -consistent if a marker S is defined and if S -marking µ of T with respect to which marked signed graph T µ is consistent. In this paper, we give an algorithm to detect if C E ( S ) is S -consistent or not and determine its complexity. • Algorithm to detect if C E ( S ) is S -consistent or not. • Determination of algorithm's complexity.

An Algorithm to detect balancing of iterated line sigraph.

A signedgraph (or sigraph in short) S is a graph G in which each edge x carries a value [Formula: see text] called its sign   denoted specially as [Formula: see text]. Given a sigraph S,  H = L(S)   called the line sigraph of S is that sigraph in which edges of S are represented as vertices, two of these vertices are defined to be adjacent whenever the corresponding edges in S have a vertex in common and any such edge ef is defined to be negative whenever both e and f are negative edges in S. Here S is called root sigraph of H. Iterated signed line graphs [Formula: see text] = [Formula: see text] k [Formula: see text] [Formula: see text], S:= [Formula: see text] is defined similarly. In this paper, we give an algorithm to obtain iterated line sigraph and detect for which value of 'k' it is balanced and determine its complexity. In the end we will propose a technique that will use adjacency matrix of S and adjacency matrix of [Formula: see text] which is balanced for some 'k' as a parameter to encrypt a network and forward the data in the form of balanced [Formula: see text] and will decrypt it by applying inverse matrix operations.

Student's critical appraisal on the evaluation of analgesics in laboratory animal verses simulated clinical trail.

Effective feedback is an integral part of medical education in helping the medical students to reach their maximum potential. Without feedback mistakes may go uncorrected which results poor performances of learners as well as tutors. At present teaching learning methodology used in many medical colleges includes lectures, tutorials, practical and occasionally small groups teaching and case discussions. The curriculum of undergraduate medical and dental students of BP Koirala Institute of Health Sciences, Dharan, Nepal is need based, integrated, co mmunity oriented, partially problem based. The practical lessons are an important part of Pharmacology curricula of undergraduate courses. So the aim of this study was to evaluate the student opinion towards animal experimentation as well as simulated clinical trial (SCT) on analgesics in terms of understanding the objectives. To conduct the study a semistructure questionnaire were provided to 2nd years MBBS and BDS students to obtain their view. Of the 164 questionnaires 154 students submitted completed questionnaire. On analysis of the feedback, it was observed that 77.9% students liked animal experiments and most of them wee happy with simulated clinical trial. The majority of the students 74.1% favoured both exercises for improved understanding of the subject and 66.2% agreed the sequential sessions. So the study concludes with the view that sequential sessions of laboratory experiments as well as SCT are required for a rectified learning of Pharmacology.