Fracture response of fibre-reinforced materials with macro/microcrack damage using the Boundary Element Technique

The Boundary Element Method (BEM) incorporating the Embedded Cell Approach (ECA) has been used to analyse the effects of constituent material properties, fibre spatial distribution and microcrack damage on the localised behaviour of transversely fractured, unidirectional fibre-reinforced composites. Three specific composites, i.e., glass fibre reinforced polyester, carbon fibre reinforced epoxy and a glass-carbon hybrid, are considered. The geometrical structures examined were perfectly periodic, uniformly spaced fibre arrangements in square and hexagonal embedded cells. In addition, numerical simulations were also conducted using embedded cells containing randomly distributed fibres. The models involve both elastic fibres and matrix, with the interfaces between the different phases being fully bonded. The results indicate that the constituent material properties (two phase composite) and spatial distribution have a significant effect on the localised stress distributions around the primary crack tip. However, the strain energy release rate associated with crack propagation is predominantly influenced by the material composition. The three-phase hybrid composite exhibited an apparent intermediate fracture toughness value, compared to the all-glass and all-carbon models. Furthermore, the strain energy release rate for the macrocrack lowers as it enters a zone of localised damage (microcracking). The presence of microcracks relaxes the stress field, which can result in a significant reduction in the energetics of the primary crack.     

Duodenal erosions and ulcers in patients with pancreatobiliary obstruction

The authors compared in a controlled clinical study two groups of patients after a first renal transplantation treated by triple drug immunosuppressive therapy. In a group of 31 patients the triple combination comprised Sandimmune Neoral. In the control group there were 30 patients who received Sandimmune. No differences were found between the two groups as regards the effectiveness of this treatment and the authors did not confirm a lower incidence of rejections described in patients treated with Sandimmune Neoral. They confirmed, however, a lower interindividual variability of Cy-A levels assessed specifically in patients treated with Sandimmune Neoral.     

D-AKAP2, a novel protein kinase A anchoring protein with a putative RGS domain

Subcellular localization directed by specific A kinase anchoring proteins (AKAPs) is a mechanism for compartmentalization of cAMP-dependent protein kinase (PKA). Using a two-hybrid screen, a novel AKAP was isolated. Because it interacts with both the type I and type II regulatory subunits, it was defined as a dual specific AKAP or D-AKAP1. Here we report the cloning and characterization of another novel cDNA isolated from that screen. This new member of the D-AKAP family, D-AKAP2, also binds both types of regulatory subunits. A message of 5 kb pairs was detected for D-AKAP2 in all embryonic stages and in all adult tissues tested. In brain, skeletal muscle, kidney, and testis, a 10-kb mRNA was identified. In testis, several small mRNAs were observed. Therefore, D-AKAP2 represents a novel family of proteins. cDNA cloning from a mouse testis library identified the full length D-AKAP2. It is composed of 372 amino acids which includes the R binding fragment, residues 333-372, at its C-terminus. Based on coprecipitation assays, the R binding domain interacts with the N-terminal dimerization domain of RIalpha and RIIalpha. A putative RGS domain was identified near the N-terminal region of D-AKAP2. The presence of this domain raises the intriguing possibility that D-AKAP2 may interact with a Galpha protein thus providing a link between the signaling machinery at the plasma membrane and the downstream kinase.     

Epidemiological study of hypertension and its determinants in an urban population of North India

OBJECTIVES: To determine age-specific prevalence of hypertension and blood pressure (BP) levels in relation to diet and lifestyle factors in North Indians. DESIGN AND SETTING: Cross-sectional survey in 20 randomly selected streets in Moradabad, North India. SUBJECTS AND METHODS: A total of 1806 subjects from North India (904 males and 902 females) age range 25-64 years. The survey methods were as follows: dietary diaries for 7 days food intake record; BP measurements; physician administered questionnaire and anthropometric measurements. Diagnosis of hypertension was based on new World Health Organization/International Society of Hypertension (WHO/ISH) criteria. Risk factors were assessed based on WHO guidelines. RESULTS: The prevalence of hypertension according to WHO/ISH criteria was 23.7% and by old WHO criteria 13.3%. In the WHO/ISH hypertensive group, isolated diastolic hypertension was present in 47.3% males and 40.6% females. Males have a slightly higher prevalence than females in the young age group, however, the prevalence rates are comparable in the older age groups. In both sexes, the prevalence rates and BP level increased with older age. Multivariate analysis revealed that age, higher body mass index, central obesity and higher socioeconomic status were independently and strongly associated with hypertension in both sexes. Higher dietary fat and salt intake and lower physical activity were weakly but significantly associated with hypertension. CONCLUSION: Association of higher socioeconmic status, higher body mass index and central obesity in North Indian adults with higher fat intake, lower physical activity and higher prevalence and level of hypertension indicate that these populations may benefit by decreasing the dietary fat intake and increasing physical activity, with an aim to decrease central obesity for decreasing hypertension in North Indians.     

Infections in patients with cystic fibrosis following lung transplantation

BACKGROUND: There is controversy over whether colonization with drug-resistant organisms is a contraindication to lung transplantation. METHODS: We undertook a retrospective review of the results of lung transplantation for patients with cystic fibrosis (CF) at Duke University Medical Center. RESULTS: As of May 1996, 21 patients with CF underwent bilateral lung transplantation. The first patient died within 24 h of transplantation from sepsis due to Stenotrophomonas maltophilia. Of the remaining 20 patients, 17 (85%) are alive and in stable condition. The three deaths were related primarily to bronchiolitis obliterans at 4 and 18 months in two patients and to cytomegalovirus pneumonitis at 5 months in the other patient. The 17 surviving patients have been followed up for a mean of 13 months (range, 0.5 to 34 months). Most of them were colonized and infected with multidrug-resistant organisms before transplantation. Following transplantation, 11 patients had complications from infections. One patient had bacteremia due to a panresistant Burkholderia cepacia and was treated successfully. Two patients had bacteremia and wound infection due to Burkholderia gladioli, previously thought to be pathogenic only in plants. Both patients were treated successfully. Of the six patients with Aspergillus fumigatus isolated from cultures before transplantation, only one had invasive disease following transplantation and responded to treatment. CONCLUSION: The organisms present before transplantation were not the primary cause of mortality in our patient population. Our findings suggest that lung transplantation should be considered in CF patients infected with multidrug-resistant organisms.     

A new method to estimate parameters of linear compartmental models using artificial neural networks

At present, the preferred tool for parameter estimation in compartmental analysis is an iterative procedure; weighted nonlinear regression. For a large number of applications, observed data can be fitted to sums of exponentials whose parameters are directly related to the rate constants/coefficients of the compartmental models. Since weighted nonlinear regression often has to be repeated for many different data sets, the process of fitting data from compartmental systems can be very time consuming. Furthermore the minimization routine often converges to a local (as opposed to global) minimum. In this paper, we examine the possibility of using artificial neural networks instead of weighted nonlinear regression in order to estimate model parameters. We train simple feed-forward neural networks to produce as outputs the parameter values of a given model when kinetic data are fed to the networks' input layer. The artificial neural networks produce unbiased estimates and are orders of magnitude faster than regression algorithms. At noise levels typical of many real applications, the neural networks are found to produce lower variance estimates than weighted nonlinear regression in the estimation of parameters from mono- and biexponential models. These results are primarily due to the inability of weighted nonlinear regression to converge. These results establish that artificial neural networks are powerful tools for estimating parameters for simple compartmental models.