Insects are the most speciose group of animals, but the phylogenetic relationships of many major lineages remain unresolved. We inferred the phylogeny of insects from 1478 protein-coding genes. Phylogenomic analyses of nucleotide and amino acid sequences, with site-specific nucleotide or domain-specific amino acid substitution models, produced statistically robust and congruent results resolving previously controversial phylogenetic relations hips. We dated the origin of insects to the Early Ordovician [~479 million years ago (Ma)], of insect flight to the Early Devonian (~406 Ma), of major extant lineages to the Mississippian (~345 Ma), and the major diversification of holometabolous insects to the Early Cretaceous. Our phylogenomic study provides a comprehensive reliable scaffold for future comparative analyses of evolutionary innovations among insects.

Background The latest advancements in DNA sequencing technologies have facilitated the resolution of the phylogeny of insects, yet parts of the tree of Holometabola remain unresolved. The phylogeny of Neuropterida has been extensively studied, but no strong consensus exists concerning the phylogenetic relationships within the order Neuroptera. Here, we assembled a novel transcriptomic dataset to address previously unresolved issues in the phylogeny of Neuropterida and to infer divergence times within the group. We tested the robustness of our phylogenetic estimates by comparing summary coalescent and concatenation-based phylogenetic approaches and by employing different quartet-based measures of phylogenomic incongruence, combined with data permutations. Results Our results suggest that the order Raphidioptera is sister to Neuroptera + Megaloptera. Coniopterygidae is inferred as sister to all remaining neuropteran families suggesting that larval cryptonephry could be a ground plan feature of Neuroptera. A clade that includes Nevrorthidae, Osmylidae, and Sisyridae (i.e. Osmyloidea) is inferred as sister to all other Neuroptera except Coniopterygidae, and Dilaridae is placed as sister to all remaining neuropteran families. Ithonidae is inferred as the sister group of monophyletic Myrmeleontiformia. The phylogenetic affinities of Chrysopidae and Hemerobiidae were dependent on the data type analyzed, and quartet-based analyses showed only weak support for the placement of Hemerobiidae as sister to Ithonidae + Myrmeleontiformia. Our molecular dating analyses suggest that most families of Neuropterida started to diversify in the Jurassic and our ancestral character state reconstructions suggest a primarily terrestrial environment of the larvae of Neuropterida and Neuroptera. Conclusion Our extensive phylogenomic analyses consolidate several key aspects in the backbone phylogeny of Neuropterida, such as the basal placement of Coniopterygidae within Neuroptera and the monophyly of Osmyloidea. Furthermore, they provide new insights into the timing of diversification of Neuropterida. Despite the vast amount of analyzed molecular data, we found that certain nodes in the tree of Neuroptera are not robustly resolved. Therefore, we emphasize the importance of integrating the results of morphological analyses with those of sequence-based phylogenomics. We also suggest that comparative analyses of genomic meta-characters should be incorporated into future phylogenomic studies of Neuropterida.

The analysis of different biomolecules is of prime importance for life science research and medical diagnostics. Due to the discovery of new molecules and new emerging bioanalytical problems, there is an ongoing demand for a technology platform that provides a broad range of assays with a user-friendly flexibility and rapid adaptability to new applications. Here we describe a highly versatile microscopy platform, VideoScan, for the rapid and simultaneous analysis of various assay formats based on fluorescence microscopic detection. The technological design is equally suitable for assays in solution, microbead-based assays and cell pattern recognition. The multiplex real-time capability for tracking of changes under dynamic heating conditions makes it a useful tool for PCR applications and nucleic acid hybridization, enabling kinetic data acquisition impossible to obtain by other technologies using endpoint detection. The paper discusses the technological principle of the platform regarding data acquisition and processing. Microbead-based and solution applications for the detection of diverse biomolecules, including antigens, antibodies, peptides, oligonucleotides and amplicons in small reaction volumes, are presented together with a high-content detection of autoimmune antibodies using a HEp-2 cell assay. Its adaptiveness and versatility gives VideoScan a competitive edge over other bioanalytical technologies.

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The standard screening test for the recognition of autoimmune diseases is the proof of autoantibodies in serum of patients by indirect immunofluorescence (IIF) based on HEp-2 cells. Manual evaluation of this test is very subjective, slow, and there are no objective parameters as guidelines available. Interlaboratory tests showed occasionally large deviations in the test evaluation resulting in a high variance of results. The aim of this project is fast, objective, safe, and economical automatic analysis of HEp-2 IIF patterns. Images of IIF patterns were completely and automatically captured using an inverse motorized fluorescence microscope. Thereby, device-specific parameters were controlled automatically, too. For fast analysis of IIF patterns new algorithms of image processing were developed. Artifacts were recognized and excluded from analysis by the developed software. Analysis of more than 80,000 images clearly demonstrated full automatization and fast processing of IIF patterns. Additionally serum-specific fluorescence could be easily distinguished from background. Even very weak but positive patterns can be recognized and used for diagnosis. A detailed separation into different basic patterns is possible. Objective, fast, and disease-related economical analysis of HEp-2 immunofluorescence patterns is feasible. The implemented software algorithms allowed a mathematical way of describing IIF patterns and can therefore be a useful tool for the needed standardization process.