Numerical prediction of load-displacement behaviors of adhesively bonded joints at different extension rates and temperatures

The present work focuses on simulation of nonlinear mechanical behaviors of adhesively bonded DLS (double lap shear) joints for variable extension rates and temperatures using the implicit ABAQUS solver. Load-displacement curves of DLS joints at nine combinations of extension rates and environmental temperatures are initially obtained by conducting tensile tests in a UTM. The joint specimens are made from dual phase (DP) steel coupons bonded with a rubber-toughened adhesive. It is shown that the shell-solid model of a DLS joint, in which substrates are modeled with shell elements and adhesive with solid elements, can effectively predict the mechanical behavior of the joint. Exponent Drucker-Prager or Von Mises yield criterion together with nonlinear isotropic hardening is used for the simulation of DLS joint tests. It has been found that at a low temperature (-20 degrees C), both Von Mises and exponent Drucker-Prager criteria give close prediction of experimental load-extension curves. However. at a high temperature (82 degrees C), Von Mises condition tends to yield a perceptibly softer joint behavior, while the corresponding response obtained using exponent Drucker-Prager criterion is much closer to the experimental load-displacement curve.

Prevalence and analysis of t(14;18) and t(11;14) chromosomal translocations in healthy Indian population

Hematopoietic malignancies like leukemia and lymphoma are characteristically associated with various chromosomal translocations. Follicular lymphoma (FL) and mantle cell lymphoma (MCL) are two subtypes of non-Hodgkin's lymphoma which possess t(14;18) and t(11;14) translocations, respectively. The incidence of FL and MCL is higher in the western countries as compared to India. Interestingly, the associated translocations are also found in healthy individuals in western population, which is 50-80% for t(14;18), whereas t(11;14) occurs at a very low frequency. However, there are no studies to explore thes translocations in healthy Indian population, which could explain the lower incidence of FL and MCL. We employed Southern hybridization following nested PCR to detect above translocations in healthy individuals from India. Our results suggest that this assay can detect one t(14;18) translocation event in up to 10(7) normal cells where as one t(11;14) in 10(8) normal cells. According to our results, 87 out of 253 individuals carry t(14;18) indicating 34% prevalence in the population. The presence of this translocation was also detectable at the transcript level. Although, no gender-based difference was observed, an age-dependent increase in the prevalence of translocation was found in adults. However, even after studying 210 people, we could not detect any t(11;14) translocation, indicating that it is uncommon in Indian population. These results suggest that lower incidence of FL and MCL in India could be attributed to lower prevalence of these translocations in healthy individuals.

Chromosomal translocations among the healthy human population: implications in oncogenesis

Chromosomal translocations are characteristic features of many cancers, especially lymphoma and leukemia. However, recent reports suggest that many chromosomal translocations can be found in healthy individuals, although the significance of this observation is still not clear. In this review, we summarize recent studies on chromosomal translocations in healthy individuals carried out in different geographical areas of the world and discuss the relevance of the observation with respect to oncogenesis.

On finding a set of healthy individuals from a large population

In this paper, we explore fundamental limits on the number of tests required to identify a given number of ``healthy'' items from a large population containing a small number of ``defective'' items, in a nonadaptive group testing framework. Specifically, we derive mutual information-based upper bounds on the number of tests required to identify the required number of healthy items. Our results show that an impressive reduction in the number of tests is achievable compared to the conventional approach of using classical group testing to first identify the defective items and then pick the required number of healthy items from the complement set. For example, to identify L healthy items out of a population of N items containing K defective items, when the tests are reliable, our results show that O(K(L - 1)/(N - K)) measurements are sufficient. In contrast, the conventional approach requires O(K log(N/K)) measurements. We derive our results in a general sparse signal setup, and hence, they are applicable to other sparse signal-based applications such as compressive sensing also.

Post-absorptive glucose lowering in normal healthy individuals: An epidemiological observation

Post-absorptive glucose lowering (PALG) is observed in individuals with glucose intolerance and in healthy individuals. We report a prevalence of about 23% among healthy Asian Indians. Individuals with PALG are characterized by leaner phenotype, low body fat percentage, increased insulin sensitivity and higher fasting glucose levels. (C) 2014 Elsevier Ireland Ltd. All rights reserved.

An Eighteen Serum Cytokine Signature for Discriminating Glioma from Normal Healthy Individuals

Glioblastomas (GBM) are largely incurable as they diffusely infiltrate adjacent brain tissues and are difficult to diagnose at early stages. Biomarkers derived from serum, which can be obtained by minimally invasive procedures, may help in early diagnosis, prognosis and treatment monitoring. To develop a serum cytokine signature, we profiled 48 cytokines in sera derived from normal healthy individuals (n = 26) and different grades of glioma patients (n = 194). We divided the normal and grade IV glioma/GBM serum samples randomly into equal sized training and test sets. In the training set, the Prediction Analysis for Microarrays (PAM) identified a panel of 18 cytokines that could discriminate GBM sera fromnormal sera with maximum accuracy (95.40%) and minimum error (4.60%). The 18-cytokine signature obtained in the training set discriminated GBM sera from normal sera in the test set as well (accuracy 96.55%; error 3.45%). Interestingly, the 18-cytokine signature also differentiated grade II/Diffuse Astrocytoma (DA) and grade III/Anaplastic Astrocytoma (AA) sera from normal sera very efficiently (DA vs. normal-accuracy 96.00%, error 4.00%; AA vs. normal-accuracy 95.83%, error 4.17%). Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis using 18 cytokines resulted in the enrichment of two pathways, cytokine-cytokine receptor interaction and JAK-STAT pathways with high significance. Thus our study identified an 18-cytokine signature for distinguishing glioma sera fromnormal healthy individual sera and also demonstrated the importance of their differential abundance in glioma biology.