Penetration and encapsulation of the larval endoparasitoid Exorista larvarum (Diptera: Tachinidae) in the factitious host Galleria mellonella (Lepidoptera: Pyralidae).

The tachinid fly Exorista larvarum (L.) (Diptera: Tachinidae) is a polyphagous larval endoparasitoid that deposits its eggs on the host exoskeleton of lepidopteran and tenthredinid larvae. The attachment of larval E. larvarum and the formation of the respiratory funnel were studied during infestation in the last larval instar of the wax moth, Galleria mellonella (L.) (Lepidoptera: Pyralidae). The tachinid larvae burrow through the host integument after hatching, using their robust cephalopharyngeal skeleton, leaving a dark spot at the point of their penetration as a result of host cuticle melanization. Endoparasitoid penetration induces the host cellular defence, resulting in the formation of a haemocyte capsule consisting of multi-cellular sheaths. This enveloping capsule later undergoes melanization, which is mostly obvious towards the posterior part of the endoparasitoid. The endoparasitoid uses the host encapsulation response to build a respiratory funnel from the modified host integument, leading to the host surface. The encapsulated larva remains attached to the respiratory funnel via an anal hook and cuticular spines until fully developed. Additional immunohistochemical analyses were used to study host-parasitoid interactions. Indirect immunofluorescence showed no labelling of potential tachinid antigens and confirmed no effect on the surrounding host tissues. A simulated parasitization with coated polybead microspheres revealed the mortal impact of tachinid antigens to the host. Hosts injected with antigen-coated polybeads died as a consequence of an acute and extensive immunological response to the tachinid antigens and not due to the trauma caused by foreign objects inside their body.

Polyphasic approach applying artificial neural networks, molecular analysis and postabdomen morphology to West Palaearctic Tachina spp. (Diptera, Tachinidae).

Artificial neural networks (ANN) methodology, molecular analyses and comparative morphology of the male postabdomen were used successfully in parallel for species identification and resolution of some taxonomic problems concerning West Palaearctic species of the genus Tachina Meigen, 1803. Supervised feed-forward ANN with back-propagation of errors was applied on morphometric and qualitative characters to solve known taxonomic discrepancies. Background molecular analyses based on mitochondrial markers CO I, Cyt b, 12S and 16S rDNA and study of male postabdominal structures were published separately. All three approaches resolved taxonomic doubts with identical results in the following five cases: case 1, the four presently recognized subgenera of the genus Tachina were confirmed and the description of a new subgenus was recommended; case 2, the validity of a new boreo-alpine species (sp.n.) was confirmed; case 3, the previously supposed presence of T. casta (Rondani, 1859) in central Europe was not supported; case 4, West Palaearctic T. nupta (Rondani, 1859) was contrasted with East Palaearctic specimens from Japan, which seem to represent a valid species not conspecific with central European specimens; T. nupta needs detailed further study; case 5, T. nigrohirta (Stein, 1924) resurrected recently from synonymy with T. ursina Meigen, 1824 was confirmed as a valid species. This parallel application of three alternative methods has enabled the principle of 'polyphasic taxonomy' to be tested and verified using these separate results. For the first time, the value of using the ANN approach in taxonomy was justified by two non-mathematical methods (molecular and morphological).

Thrips (Thysanoptera) identification using artificial neural networks.

We studied the use of a supervised artificial neural network (ANN) model for semi-automated identification of 18 common European species of Thysanoptera from four genera: Aeolothrips Haliday (Aeolothripidae), Chirothrips Haliday, Dendrothrips Uzel, and Limothrips Haliday (all Thripidae). As input data, we entered 17 continuous morphometric and two qualitative two-state characters measured or determined on different parts of the thrips body (head, pronotum, forewing and ovipositor) and the sex. Our experimental data set included 498 thrips specimens. A relatively simple ANN architecture (multilayer perceptrons with a single hidden layer) enabled a 97% correct simultaneous identification of both males and females of all the 18 species in an independent test. This high reliability of classification is promising for a wider application of ANN in the practice of Thysanoptera identification.