Production of recombinant protein in Escherichia coli cultured in extract from waste product alga, Ulva lactuca.

This study examined the potential for waste product alga, Ulva lactuca, to serve as a media component for recombinant protein production in Escherichia coli. To facilitate this investigation, U. lactuca harvested from Jamaica Bay was dried, and nutrients acid extracted for use as a growth media. The E. coli cell line BL21(DE3) was used to assess the effects on growth and production of recombinant green fluorescent protein (GFP). This study showed that media composed of acid extracts without further nutrient addition maintained E. coli growth and recombinant protein production. Extracts made from dried algae lots less than six-months-old were able to produce two-fold more GFP protein than traditional Lysogeny Broth media.

Adaptive Bolus Chasing Computed Tomography Angiography: Control Scheme and Experimental Results.

In this paper, a new adaptive bolus-chasing control scheme is proposed to synchronize the bolus peak in a patient's vascular system and the imaging aperture of a computed tomography (CT) scanner. The proposed control scheme is theoretically evaluated and experimentally tested on a modified Siemens SOMATOM Volume Zoom CT scanner. The first set of experimental results are reported on bolus-chasing CT angiography using realistic bolus dynamics, real-time CT imaging and adaptive table control with physical vasculature phantoms. The data demonstrate that the proposed control approach tracks the bolus propagation well, and clearly outperforms the constant-speed scheme that is the current clinical standard.

Bolus characteristics based on Magnetic Resonance Angiography.

BACKGROUND: A detailed contrast bolus propagation model is essential for optimizing bolus-chasing Computed Tomography Angiography (CTA). Bolus characteristics were studied using bolus-timing datasets from Magnetic Resonance Angiography (MRA) for adaptive controller design and validation. METHODS: MRA bolus-timing datasets of the aorta in thirty patients were analyzed by a program developed with MATLAB. Bolus characteristics, such as peak position, dispersion and bolus velocity, were studied. The bolus profile was fit to a convolution function, which would serve as a mathematical model of bolus propagation in future controller design. RESULTS: The maximum speed of the bolus in the aorta ranged from 5-13 cm/s and the dwell time ranged from 7-13 seconds. Bolus characteristics were well described by the proposed propagation model, which included the exact functional relationships between the parameters and aortic location. CONCLUSION: The convolution function describes bolus dynamics reasonably well and could be used to implement the adaptive controller design.