Malpositioning of Central Venous Catheter from Right to Left Subclavian Vein: A Rare Complication.

Invasive monitoring with central venous catheter (CVC) is a valuable tool now a day in Intensive Care Units and in postoperative hemodynamically unstable patients. It is often employed for administering medications and parenteral nutrition. In most of the instances, these catheters are inserted using proper topographical landmarks and ultrasonography-guided methods. Central venous cannulation is associated now and then with unexpected complications despite the use of all precautions and help of imaging techniques. There is a wide variety of complications related to the central venous cannulation including malpositioning. Malpositioning of the catheter into contralateral subclavian is an extremely unusual event. Here, we report a rare case of malpositioning of CVC from the right to the left subclavian vein also we outline how the misplacement was identified and effectively managed.

GEANT4 simulation of cyclotron radioisotope production in a solid target.

The use of radioisotopes in nuclear medicine is essential for diagnosing and treating cancer. The optimization of their production is a key factor in maximizing the production yield and minimizing the associated costs. An efficient approach to this problem is the use of Monte Carlo simulations prior to experimentation. By predicting isotopes yields, one can study the isotope of interest expected activity for different energy ranges. One can also study the target contamination with other radioisotopes, especially undesired radioisotopes of the wanted chemical element which are difficult to separate from the irradiated target and might result in increasing the dose when delivering the radiopharmaceutical product to the patient. The aim of this work is to build and validate a Monte Carlo simulation platform using the GEANT4 toolkit to model the solid target system of the South Australian Health and Medical Research Institute (SAHMRI) GE Healthcare PETtrace cyclotron. It includes a GEANT4 Graphical User Interface (GUI) where the user can modify simulation parameters such as the energy, shape and current of the proton beam, the target geometry and material, the foil geometry and material and the time of irradiation. The paper describes the simulation and presents a comparison of simulated and experimental/theoretical yields for various nuclear reactions on an enriched nickel 64 target using the GEANT4 physics model QGSP_BIC_AllHP, a model recently developed to evaluate with high precision the interaction of protons with energies below 200MeV available in Geant4 version 10.1. The simulation yield of the (64)Ni(p,n)(64)Cu reaction was found to be 7.67±0.074 mCi·µA(-1) for a target energy range of 9-12MeV. Szelecsenyi et al. (1993) gives a theoretical yield of 6.71mCi·µA(-1) and an experimental yield of 6.38mCi·µA(-1). The (64)Ni(p,n)(64)Cu cross section obtained with the simulation was also verified against the yield predicted from the nuclear database TENDL and compared to experimental yield obtained from literature.

Local receptor revision and class switching to IgE in chronic rhinosinusitis with nasal polyps.

BACKGROUND: Chronic rhinosinusitis with nasal polyps (NP) and allergic rhinitis (AR) is characterized by local Th2 inflammation and up-regulation of IgE; however, IgE in NP is 'polyclonal' and allergen specific, whereas IgE in AR is 'oligoclonal' and allergen specific. Germinal center (GC) reactions occur in AR, while only the formation of GC-like structures in NP is described. The aim of this study was to investigate the involvement of local IgE production, class switch recombination, and receptor revision in NP. METHODS: We compared the levels of local IgE, germline gene transcripts, and mature Ig mRNA expression, recombination activating gene (RAG1 and RAG2), key markers of Th2 inflammation, and GC reactions in NP tissue vs AR and control tissue. Nasal mucosa was immunostained for the co-expression of RAG1 and RAG2 in B cells, plasma cells, and T cells, using dual or triple immunofluorescence (IF). RESULTS: In NP, local IgE level and key markers of local class switching are increased compared with AR and normal controls (NC). In NP, switch circle transcripts reveal ongoing local class switch recombination to IgE. Up to 30% of B cells, plasma cells, and T cells in nasal polyps re-express both RAG1 and RAG2, required for receptor revision. RAG1 and RAG2 mRNA concentrations are increased in NP and correlated with the magnitude of inflammation and the presence of S. aureus enterotoxin (superantigen)-specific IgE in the nasal polyp mucosa. CONCLUSION: Our results provide the first evidence of local receptor revision and class switching to IgE, and B-cell differentiation into IgE-secreting plasma cells in NP.

Fractional differential equations based modeling of microbial survival and growth curves: model development and experimental validation.

A fractional differential equations (FDEs)-based theory involving 1- and 2-term equations was developed to predict the nonlinear survival and growth curves of foodborne pathogens. It is interesting to note that the solution of 1-term FDE leads to the Weibull model. Nonlinear regression (Gauss-Newton method) was performed to calculate the parameters of the 1-term and 2-term FDEs. The experimental inactivation data of Salmonella cocktail in ground turkey breast, ground turkey thigh, and pork shoulder; and cocktail of Salmonella, E. coli, and Listeria monocytogenes in ground beef exposed at isothermal cooking conditions of 50 to 66 degrees C were used for validation. To evaluate the performance of 2-term FDE in predicting the growth curves-growth of Salmonella typhimurium, Salmonella Enteritidis, and background flora in ground pork and boneless pork chops; and E. coli O157:H7 in ground beef in the temperature range of 22.2 to 4.4 degrees C were chosen. A program was written in Matlab to predict the model parameters and survival and growth curves. Two-term FDE was more successful in describing the complex shapes of microbial survival and growth curves as compared to the linear and Weibull models. Predicted curves of 2-term FDE had higher magnitudes of R(2) (0.89 to 0.99) and lower magnitudes of root mean square error (0.0182 to 0.5461) for all experimental cases in comparison to the linear and Weibull models. This model was capable of predicting the tails in survival curves, which was not possible using Weibull and linear models. The developed model can be used for other foodborne pathogens in a variety of food products to study the destruction and growth behavior.