Expression of infectious bovine rhinotracheitis virus glycoprotein D in bacterial cell

Bovine Herpesvirus 1 (BHV-1) belongs to the genus of Varicellovirus and the family of Herpesviridae which contains three main gB, gC and gD genes. In order to cloning of the coding region of gD gene of IBR virus , PCR product of the open reading frame of the gene from IBR virus isolated in Iran was amplified by PCR. A 1047bp PCR product of the gD gene with EcoRI, HindIII restriction sites were subcloned of pTZ57R/T and digested by the mentioned endonucleases. Digested insert cloned in to pET-32a and transfered in E.coli cells. For the expression of gD protein, the pET-32a recombinant vector was transformed and then induced in BL21 (DE3) strain of E.coli competent cells using IPTG. The presence of gD expressed protein was shown in immunoblotting and SDS-PAGE system. With respect to the remarkable frequency of infection to IBR in Iran and the necessity of controlling it through vaccination with recombinant vaccines of thymidine kinase, manufacturing and applying the recombinant gD protein are vital goals in recognition and distinction between infection and responsescaused by vaccine

Numerical simulation of dynamic pore fluid-solid interaction in fully saturated non-linear porous media

In this paper, a large deformation formulation for dynamic analysis of the pore fluid-solid interaction in a fully saturated non-linear medium is presented in the framework of the Arbitrary Lagrangian-Eulerian method. This formulation is based on Biot’s theory of consolidation extended to include the momentum equations of the solid and fluid phases, large deformations and non-linear material behaviour. By including the displacements of the solid skeleton, u, and the pore fluid pressure, p, a (u-p) formulation is obtained, which is then discretised using finite elements. Time integration of the resulting highly nonlinear equations is accomplished by the generalized–α method, which assures second order accuracy as well as unconditional stability of the solution. Details of the formulation and its practical implementation in a finite element code are discussed. The formulation and its implementation are validated by solving some classical examples in geomechanics

Radiation therapy effects on white matter fiber tracts of the limbic circuit

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/134834/1/mp5560.pd

Investigating the Relationship between hs-CRP Serum Level and Insulin Resistance (HOMA IR) Six Weeks after Childbirth in Patients with Gestational Diabetes Mellitus

Background: Some patients with GDM (Gestational Diabetes Mellitus) still experience impaired glucose tolerance after childbirth and will be affected by diabetes mellitus type 2. Objectives: The aim of this study is to investigate the relationship between hs-CRP serum levels with insulin resistance six weeks after childbirth in patients with gestational diabetes mellitus type 2. Methods: In this descriptive cross-sectional study, 110 patients with GDM were evaluated in terms of the insulin resistance index (HOMA), hs-CRP serum, and the oral glucose tolerance test (OGTT) six weeks after childbirth. Their anthropometric indices were measured in the early pregnancy. Spearman’s rank correlation coefficient and linear regression analysis were used to analyze data in SPSS 16. Results: The mean of hs-CRP was 8.72 µg/ml among the patients in this study. It is higher than the normal range. Moreover, 24.5% of the patients were suffering from impaired glucose tolerance, and hs-CRP levels were higher than the normal range in 92.6% of these patients. Furthermore, 41.8% of patients showed insulin resistance, and hs-CRP levels were high among 73.9% of them. After age adjustment, the increase in hs-CRP serum level was significantly correlated with insulin resistance (HOMA) and the one-hour and two-hour OGTTs (p=0.007 and p<0.001, respectively). Conclusion: It appears that age adjustment can help us figure out the relationship between the increase in hs-CRP serum and insulin resistance in pregnant mothers with diabetes six weeks after childbirth

Metabolic resting-state brain networks in health and disease

The delineation of resting state networks (RSNs) in the human brain relies on the analysis of temporal fluctuations in functional MRI signal, representing a small fraction of total neuronal activity. Here, we used metabolic PET, which maps nonfluctuating signals related to total activity, to identify and validate reproducible RSN topographies in healthy and disease populations. In healthy subjects, the dominant (first component) metabolic RSN was topographically similar to the default mode network (DMN). In contrast, in Parkinson\u27s disease (PD), this RSN was subordinated to an independent disease-related pattern. Network functionality was assessed by quantifying metabolic RSN expression in cerebral blood flow PET scans acquired at rest and during task performance. Consistent task-related deactivation of the DMN-like dominant metabolic RSN was observed in healthy subjects and early PD patients; in contrast, the subordinate RSNs were activated during task performance. Network deactivation was reduced in advanced PD; this abnormality was partially corrected by dopaminergic therapy. Time-course comparisons of DMN loss in longitudinal resting metabolic scans from PD and Alzheimer\u27s disease subjects illustrated that significant reductions appeared later for PD, in parallel with the development of cognitive dysfunction. In contrast, in Alzheimer\u27s disease significant reductions in network expression were already present at diagnosis, progressing over time. Metabolic imaging can directly provide useful information regarding the resting organization of the brain in health and disease

Observation of cardiac profile among the adult population of Sreemangal

Background: Cardiovascular diseases are a leading cause of morbidity and mortality worldwide. The prevalence and risk factors of CVDs vary across different populations and regions. This study aimed to observe the cardiac profile among the adult population of Sreemangal, Bangladesh, to identify the prevalence and risk factors of CVDs in this population. Methods: This prospective observational study was conducted over a six-month period at a public health camp in Sreemangal, Bangladesh. A total of 137 adult participants were purposively selected. Data were collected through a structured questionnaire and physical examination, including measurements of blood pressure and laboratory analysis of blood samples. Results: The study found that 44.53% of participants had elevated blood pressure, and 21.90% had stage 1 hypertension. Interestingly, 36.50% of participants were unaware of their hypertension status. Furthermore, 26.28% of participants had a known history of diabetes, but blood glucose level analysis revealed an additional 14.85% of participants were prediabetic, and 6.93% were diabetic based on fasting blood glucose levels. A statistically significant association was found between increasing age and the stage of hypertension (p&lt;0.001), and between fasting and normal blood glucose levels and the stage of hypertension (p&lt;0.005 and p&lt;0.05, respectively). Conclusions: The findings of this study underscore the need for targeted interventions to prevent and manage CVDs in the adult population of Sreemangal, Bangladesh. These interventions should include regular screening for CVD risk factors, health education to increase awareness of these risk factors, and strategies to promote healthy lifestyle behaviors

Segmentation of corpus callosum using diffusion tensor imaging: validation in patients with glioblastoma

Abstract Background This paper presents a three-dimensional (3D) method for segmenting corpus callosum in normal subjects and brain cancer patients with glioblastoma. Methods Nineteen patients with histologically confirmed treatment naïve glioblastoma and eleven normal control subjects underwent DTI on a 3T scanner. Based on the information inherent in diffusion tensors, a similarity measure was proposed and used in the proposed algorithm. In this algorithm, diffusion pattern of corpus callosum was used as prior information. Subsequently, corpus callosum was automatically divided into Witelson subdivisions. We simulated the potential rotation of corpus callosum under tumor pressure and studied the reproducibility of the proposed segmentation method in such cases. Results Dice coefficients, estimated to compare automatic and manual segmentation results for Witelson subdivisions, ranged from 94% to 98% for control subjects and from 81% to 95% for tumor patients, illustrating closeness of automatic and manual segmentations. Studying the effect of corpus callosum rotation by different Euler angles showed that although segmentation results were more sensitive to azimuth and elevation than skew, rotations caused by brain tumors do not have major effects on the segmentation results. Conclusions The proposed method and similarity measure segment corpus callosum by propagating a hyper-surface inside the structure (resulting in high sensitivity), without penetrating into neighboring fiber bundles (resulting in high specificity)