In Vitro Engineering of High Modulus Cartilage-Like Constructs.

To date, the outcomes of cartilage repair have been inconsistent and have frequently yielded mechanically inferior fibrocartilage, thereby increasing the chances of damage recurrence. Implantation of constructs with biochemical composition and mechanical properties comparable to natural cartilage could be advantageous for long-term repair. This study attempted to create such constructs, in vitro, using tissue engineering principles. Bovine synoviocytes were seeded on nonwoven polyethylene terephthalate fiber scaffolds and cultured in chondrogenic medium for 4 weeks, after which uniaxial compressive loading was applied using an in-house bioreactor for 1 h per day, at a frequency of 1 Hz, for a further 84 days. The initial loading conditions, determined from the mechanical properties of the immature constructs after 4 weeks in chondrogenic culture, were strains ranging between 13% and 23%. After 56 days (sustained at 84 days) of loading, the constructs were stained homogenously with Alcian blue and for type-II collagen. Dynamic compressive moduli were comparable to the high end values for native cartilage and proportional to Alcian blue staining intensity. We suggest that these high moduli values were attributable to the bioreactor setup, which caused the loading regime to change as the constructs developed, that is, the applied stress and strain increased with construct thickness and stiffness, providing continued sufficient cell stimulation as further matrix was deposited. Constructs containing cartilage-like matrix with response to load similar to that of native cartilage could produce long-term effective cartilage repair when implanted.

PlasmoPredict: a gene function prediction website for Plasmodium falciparum.

The genome sequence of the malaria parasite Plasmodium falciparum was published in 2002 and revealed that approximately 60% of its genes could not be assigned a function. Eight years later the majority of P. falciparum proteins are still of unknown function. We therefore present PlasmoPredict, an easy-to-use online gene function prediction tool that integrates a wide range of functional genomics data for P. falciparum to aid in the annotation of these genes.

Liver segmentation using automatically defined patient specific B-spline surface models.

This paper presents a novel liver segmentation algorithm. This is a model-driven approach; however, unlike previous techniques which use a statistical model obtained from a training set, we initialize patient-specific models directly from their own pre-segmentation. As a result, the non-trivial problems such as landmark correspondences, model registration etc. can be avoided. Moreover, by dividing the liver region into three sub-regions, we convert the problem of building one complex shape model into constructing three much simpler models, which can be fitted independently, greatly improving the computation efficiency. A robust graph-based narrow band optimal surface fitting scheme is also presented. The proposed approach is evaluated on 35 CT images. Compared to contemporary approaches, our approach has no training requirement and requires significantly less processing time, with an RMS error of 2.44 +/- 0.53 mm against manual segmentation.