Fully Automatic Segmentation of Brain Tumor Images using Support Vector Machine Classiffication in Combination with Hierarchical Conditional Random Field Regularization

Delineating brain tumor boundaries from magnetic resonance images is an essential task for the analysis of brain cancer. We propose a fully automatic method for brain tissue segmentation, which combines Support Vector Machine classification using multispectral intensities and textures with subsequent hierarchical regularization based on Conditional Random Fields. The CRF regularization introduces spatial constraints to the powerful SVM classification, which assumes voxels to be independent from their neighbors. The approach first separates healthy and tumor tissue before both regions are subclassified into cerebrospinal fluid, white matter, gray matter and necrotic, active, edema region respectively in a novel hierarchical way. The hierarchical approach adds robustness and speed by allowing to apply different levels of regularization at different stages. The method is fast and tailored to standard clinical acquisition protocols. It was assessed on 10 multispectral patient datasets with results outperforming previous methods in terms of segmentation detail and computation times.

Improved detection of amnestic MCI by means of discriminative vector quantization of single-trial cognitive ERP responses

Cognitive event-related potentials (ERPs) are widely employed in the study of dementive disorders. The morphology of averaged response is known to be under the influence of neurodegenerative processes and exploited for diagnostic purposes. This work is built over the idea that there is additional information in the dynamics of single-trial responses. We introduce a novel way to detect mild cognitive impairment (MCI) from the recordings of auditory ERP responses. Using single trial responses from a cohort of 25 amnestic MCI patients and a group of age-matched controls, we suggest a descriptor capable of encapsulating single-trial (ST) response dynamics for the benefit of early diagnosis. A customized vector quantization (VQ) scheme is first employed to summarize the overall set of ST-responses by means of a small-sized codebook of brain waves that is semantically organized. Each ST-response is then treated as a trajectory that can be encoded as a sequence of code vectors. A subject's set of responses is consequently represented as a histogram of activated code vectors. Discriminating MCI patients from healthy controls is based on the deduced response profiles and carried out by means of a standard machine learning procedure. The novel response representation was found to improve significantly MCI detection with respect to the standard alternative representation obtained via ensemble averaging (13% in terms of sensitivity and 6% in terms of specificity). Hence, the role of cognitive ERPs as biomarker for MCI can be enhanced by adopting the delicate description of our VQ scheme.

Alphaviral cytotoxicity and its implication in vector development

A great variety of viruses have been engineered to serve as expression vectors. Among them, the alphaviruses Semliki Forest virus and Sindbis virus represent promising tools for heterologous gene expression in a wide variety of host cells. Several applications have already been described in neurobiological studies, in gene therapy, for vaccine development and in cancer therapy. Both viruses trigger stress pathways in the cells they infect, sometimes culminating in the death of the host. This inherent property is either an advantage or a drawback, depending on the type of application. This review covers the development and applications of alphavirus vectors and, as our work has been mainly with Semliki Forest virus, we have focused on this virus with special emphasis on how the understanding of Semliki Forest virus cytotoxicity enables it to be manipulated and used.

New Shuttle Vector-Based Expression System To Generate Polyhistidine-Tagged Fusion Proteins in Staphylococcus aureus and Escherichia coli.

Four Staphylococcus aureus-Escherichia coli shuttle vectors were constructed for gene expression and production of tagged fusion proteins. Vectors pBUS1-HC and pTSSCm have no promoter upstream of the multiple cloning site (MCS), and this allows study of genes under the control of their native promoters, and pBUS1-Pcap-HC and pTSSCm-Pcap contain the strong constitutive promoter of S. aureus type 1 capsule gene 1A (Pcap) upstream of a novel MCS harboring codons for the peptide tag Arg-Gly-Ser-hexa-His (rgs-his6). All plasmids contained the backbone derived from pBUS1, including the E. coli origin ColE1, five copies of terminator rrnB T1, and tetracycline resistance marker tet(L) for S. aureus and E. coli. The minimum pAMα1 replicon from pBUS1 was improved through either complementation with the single-strand origin oriL from pUB110 (pBUS1-HC and pBUS1-Pcap-HC) or substitution with a pT181-family replicon (pTSSCm and pTSSCm-Pcap). The new constructs displayed increased plasmid yield and segregational stability in S. aureus. Furthermore, pBUS1-Pcap-HC and pTSSCm-Pcap offer the potential to generate C-terminal RGS-His6 translational fusions of cloned genes using simple molecular manipulation. BcgI-induced DNA excision followed by religation converts the TGA stop codon of the MCS into a TGC codon and links the rgs-his6 codons to the 3' end of the target gene. The generation of the rgs-his6 codon-fusion, gene expression, and protein purification were demonstrated in both S. aureus and E. coli using the macrolide-lincosamide-streptogramin B resistance gene erm(44) inserted downstream of Pcap. The new His tag expression system represents a helpful tool for the direct analysis of target gene function in staphylococcal cells.

Resisting infection by Plasmodium berghei increases the sensitivity of the malaria vector Anopheles gambiae to DDT

BACKGROUND The evolution of insecticide resistance threatens current malaria control methods, which rely heavily on chemical insecticides. The magnitude of the threat will be determined by the phenotypic expression of resistance in those mosquitoes that can transmit malaria. These differ from the majority of the mosquito population in two main ways; they carry sporozoites (the infectious stage of the Plasmodium parasite) and they are relatively old, as they need to survive the development period of the malaria parasite. This study examines the effects of infection by Plasmodium berghei and of mosquito age on the sensitivity to DDT in a DDT-resistant strain of Anopheles gambiae. METHODS DDT-resistant Anopheles gambiae (ZANU) mosquitoes received a blood meal from either a mouse infected with Plasmodium berghei or an uninfected mouse. 10 and 19 days post blood meal the mosquitoes were exposed to 2%, 1% or 0% DDT using WHO test kits. 24 hrs after exposure, mortality and Plasmodium infection status of the mosquitoes were recorded. RESULTS Sensitivity to DDT increased with the mosquitoes' age and was higher in mosquitoes that had fed on Plasmodium-infected mice than in those that had not been exposed to the parasite. The latter effect was mainly due to the high sensitivity of mosquitoes that had fed on an infected mouse but were not themselves infected, while the sensitivity to DDT was only slightly higher in mosquitoes infected by Plasmodium than in those that had fed on an uninfected mouse. CONCLUSIONS The observed pattern indicates a cost of parasite-resistance. It suggests that, in addition to the detrimental effect of insecticide-resistance on control, the continued use of insecticides in a population of insecticide-resistant mosquitoes could select mosquitoes to be more susceptible to Plasmodium infection, thus further decreasing the efficacy of the control.