Automatic identification of algae: neural network analysis of flow cytometric data

The performance of an artificial neural network for automaticidentification of phytoplankton was investigated with data fromalgal laboratory cultures, analysed on the Optical PlanktonAnalyser (OPA), a flow cytometer especially developed for theanalysis of phytoplankton. Data from monocultures of eight algalspecies were used to train a neural network. The performanceof the trained network was tested with OPA data from mixturesof laboratory cultures. The network could distinguish Cyanobacteriafrom other algae with 99% accuracy. The identification of specieswas performed with less accuracy, but was generally >90%.This indicates that a neural network under supervised learningcan be used for automatic identification of species in relativelycomplex mixtures. Incorporation of such a system may also increasethe operational size range of a flow cytometer. The combinationof the OPA and neural network data analysis offers the elementsto build an operational automatic algal identification system.     

The miRNA and mRNA Signatures of Peripheral Blood Cells in Humans Infected with Trypanosoma brucei gambiense

Simple, reliable tools for diagnosis of human African Trypanosomiases could ease field surveillance and enhance patient care. In particular, current methods to distinguish patients with (stage II) and without (stage I) brain involvement require samples of cerebrospinal fluid. We describe here an exploratory study to find out whether miRNAs from peripheral blood leukocytes might be useful in diagnosis of human trypanosomiasis, or for determining the stage of the disease. Using microarrays, we measured miRNAs in samples from Trypanosoma brucei gambiense-infected patients (9 stage I, 10 stage II), 8 seronegative parasite-negative controls and 12 seropositive, but parasite-negative subjects. 8 miRNAs (out of 1205 tested) showed significantly lower expression in patients than in seronegative, parasite-negative controls, and 1 showed increased expression. There were no clear differences in miRNAs between patients in different disease stages. The miRNA profiles could not distinguish seropositive, but parasitologically negative samples from controls and results within this group did not correlate with those from the trypanolysis test. Some of the regulated miRNAs, or their predicted mRNA targets, were previously reported changed during other infectious diseases or cancer. We conclude that the changes in miRNA profiles of peripheral blood lymphocytes in human African trypanosomiasis are related to immune activation or inflammation, are probably disease-non-specific, and cannot be used to determine the disease stage. The approach has little promise for diagnostics but might yield information about disease pathology.     

Random amplified polymorphic DNA (RAPD) detection of dwarf off-types in micropropagated Cavendish (Musa spp. AAA) bananas

Summary A RAPD marker specific to the dwarf off-type (hereafter known as dwarf) from micropropagation of Cavendish banana (Musa spp. AAA) cultivars New Guinea Cavendish and Williams was identified following an analysis of 57 normal (true-to-type) and 59 dwarf plants generated from several different micropropagation events. Sixty-six random decamer primers were used in the initial screen, of which 19 (28.8%) revealed polymorphisms between normal and dwarf plants. Primer OPJ-04 (5'-CCGAACACGG-3') was found to amplify an approx. 1.5 kb band which was consistently present in all normal but absent in all dwarf plants of both cultivars. Reliable detection of dwarf plants was achieved using this marker, providing the only available means ofin vitro detection of dwarfs. The use of this marker could facilitate early detection and elimination of dwarfs from batches of micropropagated bananas, and may be a useful tool in determining what factors in the tissue culture process lead to this off type production.Other micropropagation-induced RAPD polymorphisms were observed but were not associated with the dwarf trait.     

Combined multimodal ctDNA analysis and radiological imaging for tumor surveillance in Non-small cell lung cancer

BackgroundRadiology is the current standard for monitoring treatment responses in lung cancer. Limited sensitivity, exposure to ionizing radiations and related sequelae constitute some of its major limitation. Non-invasive and highly sensitive methods for early detection of treatment failures and resistance-associated disease progression would have additional clinical utility.MethodsWe analyzed serially collected plasma and paired tumor samples from lung cancer patients (61 with stage IV, 48 with stages I-III disease) and 61 healthy samples by means of next-generation sequencing, radiological imaging and droplet digital polymerase chain reaction (ddPCR) mutation and methylation assays.ResultsA 62% variant concordance between tumor-reported and circulating-free DNA (cfDNA) sequencing was observed between baseline liquid and tissue biopsies in stage IV patients. Interestingly, ctDNA sequencing allowed for the identification of resistance-mediating p.T790M mutations in baseline plasma samples for which no such mutation was observed in the corresponding tissue. Serial circulating tumor DNA (ctDNA) mutation analysis by means of ddPCR revealed a general decrease in ctDNA loads between baseline and first reassessment. Additionally, serial ctDNA analyses only recapitulated computed tomography (CT) -monitored tumor dynamics of some, but not all lesions within the same patient. To complement ctDNA variant analysis we devised a ctDNA methylation assay (^methcfDNA) based on methylation-sensitive restriction enzymes. cfDNA methylation showed and area under the curve (AUC) of > 0.90 in early and late stage cases. A decrease in ^methcfDNA between baseline and first reassessment was reflected by a decrease in CT-derive tumor surface area, irrespective of tumor mutational status.ConclusionTaken together, our data support the use of cfDNA sequencing for unbiased characterization of the molecular tumor architecture, highlights the impact of tumor architectural heterogeneity on ctDNA-based tumor surveillance and the added value of complementary approaches such as cfDNA methylation for early detection and monitoring