A preliminary evaluation of tick cement-cone protein extract for a vaccine against Hyalomma infestation.

Background: Vaccines have been widely exploited to prevent tick-borne infections in cattle. Most vaccines have faced failure in the field because of inconsistency in an immune response. It is presumed that the cement-cone proteins of ticks that participate in the acquisition of blood meal for ticks possess strong immune-stimulating properties and, hence, could be a useful candidate in vaccine development. Aims: We evaluated cement-cone proteins of tick Hyalomma anatolicum as a vaccine candidate against infestations of H. anatolicum and H. aegyptium in cattle. Methods: The cement-cone proteins were extracted from H. anatolicum to develop stage-reactive and immunogenic cross-reactive vaccine against the infestation of two species of ticks H. anatolicum and H. aegyptium. The immune response of the vaccine was tested against cement-cone proteins starved, partially fed, and richly fed ticks. Results: The findings of the present study demonstrated the cross-reactivity among the two species of ticks that belonged to the same genus (Hyalomma). The antigenic similarity between the two ticks species suggests that a common antigen may possibly be suitable for a vaccine against the two different species of ticks. The results have also indicated that the 23 kDa cement-cone protein of H. anatolicum and H. aegyptium may be responsible for the induction, or elicitation of immunogenic, common stage reactive, and cross-reactive host immune responses with consistent intensity throughout the life stages of ticks. Conclusion: The vaccine based upon cement-cone proteins of ticks may be a useful deterrent against tick-borne infections in cattle in countries like Pakistan.

Necessity of accreditation standards for quality assurance of medical basic sciences.

BACKGROUND: The present article reviews the significance of accreditation standards while emphasizing the necessity of implementation of such standards by basic medical science council, with an eye on such international standards as those published by WFME. This review article had to decide on the key words and expressions, data bases, to review relevant literature, review higher and medical education journals at GOOGLE, ELSEVIER, PUBMED, and such web sites as those of WFME and WMA's. Accreditation is a powerful leverage for institutional change and improvement and must be actively supported by academic and national health authorities worldwide. Considering the mission of the Basic Medical Science, Health and Post grad. Education, Ministry of Health and Medical Education, Tehran, Iran as accountable medical education, all specialists of the spectrum of disciplines agreed on the necessity of formulating the medical education standards for all disciplines of their interest. It is important that all efforts be joined in the endeavor to create effective and reliable instruments for quality assurance of Basic Medical Sciences Education.

A comparative study on the functional response of Wolbachia-infected and uninfected forms of the parasitoid wasp Trichogramma brassicae.

Trichogramma species (Hymenoptera: Trichogrammatidae) are haplo-diploid egg parasitoids that are frequently used as biological control agents against lepidopteran pests. These wasps display two reproductive modes, including arrhenotoky (bisexuality) and thelytoky (unisexuality). Thelytokous forms are often associated with the presence of endosymbiotic Wolbachia bacteria. The use of thelytokous wasps has long been considered as a way to enhance the efficacy of biological control. The present study investigates the potential of a thelytokous Wolbachia-infected and an arrhenotokous uninfected Trichogramma brassicae Bezdenko strain as inundative biocontrol agents by evaluating their functional response towards different egg densities of the factitious host, the Angoumois grain moth, Sitotroga cerealella (Olivier) (Lepidoptera: Gelechiidae). The results revealed a type II functional response for both strains in which parasitism efficiency decreases with host egg density because of an increasing host handling time. A model with an indicator variable was used to compare the parameters of Holling's disc equation in different data sets. It was demonstrated that the two strains did not differ in host attack rate. However, the Wolbachia-infected strain did have an increased host handling time when compared to the bisexual strain. Some applied aspects of the findings are discussed.

On the use of machine learning to identify topological rules in the packing of beta-strands.

The machine learning program GOLEM was applied to discover topological rules in the packing of beta-sheets in alpha/beta-domain proteins. Rules (constraints) were determined for four features of beta-sheet packing: (i) whether a beta-strand is at an edge; (ii) whether two consecutive beta-strands pack parallel or anti-parallel; (iii) whether two beta-strands pack adjacently; and (iv) the winding direction of two consecutive beta-strands. Rules were found with high predictive accuracy and coverage. The errors were generally associated with complications in domain folds, especially in one doubly would domains. Investigation of the rules revealed interesting patterns, some of which were known previously, others that are novel. Novel features include (i) the relationship between pairs of sequential strands is in general one of decreasing size; (ii) more sequential pairs of strands wind in the direction out than in; and (iii) it takes a larger alteration in hydrophobicity to change a strand from winding in the direction out than in. These patterns in the data may be the result of folding pathways in the domains. The rules found are of predictive value and could be used in the combinatorial prediction of protein structure, or as a general test of model structures, e.g. those produced by threading. We conclude that machine learning has a useful role in the analysis of protein structures.

Inductive logic programming used to discover topological constraints in protein structures.

This paper describes the application of the Inductive Logic Programming (ILP) program GOLEM to the discovery of constraints in the packing of beta-sheets in alpha/beta proteins. These constraints (rules) have a role in understanding the protein folding problem. Constraints were learnt for four features of beta-sheet packing: the winding direction of two sequential strands, whether two consecutive strands pack parallel or anti-parallel, whether two strands pack adjacently, and whether a beta-strand is at an edge. Investigation of the learnt constraints revealed interesting patterns, some of which were previously known, others that were novel. Novel features include the discovery: that the relationship between pairs of sequential strands is in general one of decreasing size, and that more sequential pairs of strands wind in the direction out than the direction in. We conclude that machine learning has a useful place in molecular biology as a pattern discovery tool.

Protein topology prediction through parallel constraint logic programming.

In this paper, two programs are described (CBS1e and CBS2e). These are implemented in the parallel constraint logic programming language ElipSys. These predict protein alpha/beta-sheet and beta-sheet topologies from secondary structure assignments and topological folding rules (constraints). These programs illustrate how recent developments in logic programming environments can be applied to solve large-scale combinatorial problems in molecular biology. We demonstrate that parallel constraint logic programming is able to overcome some of the important limitations of more established logic programming languages i.e. Prolog. This is particularly the case in providing features that enhance the declarative nature of the program and also in addressing directly the problems of scaling-up logic programs to solve scientifically realistic problems. Moreover, we show that for large topological problems CBS1e was approximately 60 times faster than an equivalent Prolog implementation (CBS1) on a sequential device with further performance enhancements possible on parallel computer architectures. CBS2e is an extension of CBS1e that addresses the important problem of integrating the use of uncertain (weighted) protein folding constraints with categorical ones, through the use of a cost function that is minimized. CBS2e achieves this with a relatively minor reduction of performance. These results significantly extend the range and complexity of protein structure prediction methods that can reasonably be addressed using AI languages.

Protein topology prediction through constraint-based search and the evaluation of topological folding rules.

An algorithm for predicting protein alpha/beta-sheet topologies from secondary structure and topological folding rules (constraints) has been developed and implemented in Prolog. This algorithm (CBS1) is based on constraint satisfaction and employs forward pruned breadth-first search and rotational invariance. CBS1 showed a 37-fold increase in efficiency over an exhaustive generate and test algorithm giving the same solution for a typical sheet of five strands whose topology was predicted from secondary structure with four topological folding constraints. Prolog specifications of a range of putative protein folding rules were then used to (i) replicate published protein topology predictions and (ii) validate these rules against known protein structures of nucleotide-binding domains. This demonstrated that (i) manual techniques for topology prediction can lead to non-exhaustive search and (ii) most of these protein folding principles were violated by specific proteins. Various extensions to the algorithm are discussed.