An extensive amount of information is currently available to clinical specialists, ranging from details ofclinical symptoms to various types of biochemical data and outputs of imaging devices. Each type of dataprovides information that must be evaluated and assigned to a particular pathology during the diagnosticprocess. To streamline the diagnostic process in daily routine and avoid misdiagnosis, artificial intelligencemethods (especially computer aided diagnosis and artificial neural networks) can be employed. Theseadaptive learning algorithms can handle diverse types of medical data and integrate them into categorizedoutputs. In this paper, we briefly review and discuss the philosophy, capabilities, and limitations of artificialneural networks in medical diagnosis through selected examples

The International Stem Cell Initiative analyzed 125 human embryonic stem (ES) cell lines and 11 induced pluripotent stem (iPS) cell lines, from 38 laboratories worldwide, for genetic changes occurring during culture. Most lines were analyzed at an early and late passage. Single-nucleotide polymorphism (SNP) analysis revealed that they included representatives of most major ethnic groups. Most lines remained karyotypically normal, but there was a progressive tendency to acquire changes on prolonged culture, commonly affecting chromosomes 1, 12, 17 and 20. DNA methylation patterns changed haphazardly with no link to time in culture. Structural variants, determined from the SNP arrays, also appeared sporadically. No common variants related to culture were observed on chromosomes 1, 12 and 17, but a minimal amplicon in chromosome 20q11.21, including three genes, ID1, BCL2L1 and HM13, expressed in human ES cells, occurred in >20% of the lines. Of these genes, BCL2L1 is a strong candidate for driving culture adaptation of ES cells.

The International Stem Cell Initiative characterized 59 human embryonic stem cell lines from 17 laboratories worldwide. Despite diverse genotypes and different techniques used for derivation and maintenance, all lines exhibited similar expression patterns for several markers of human embryonic stem cells. They expressed the glycolipid antigens SSEA3 and SSEA4, the keratan sulfate antigens TRA-1-60, TRA-1-81, GCTM2 and GCT343, and the protein antigens CD9, Thy1 (also known as CD90), tissue-nonspecific alkaline phosphatase and class 1 HLA, as well as the strongly developmentally regulated genes NANOG, POU5F1 (formerly known as OCT4), TDGF1, DNMT3B, GABRB3 and GDF3. Nevertheless, the lines were not identical: differences in expression of several lineage markers were evident, and several imprinted genes showed generally similar allele-specific expression patterns, but some gene-dependent variation was observed. Also, some female lines expressed readily detectable levels of XIST whereas others did not. No significant contamination of the lines with mycoplasma, bacteria or cytopathic viruses was detected.

Flow cytometry is a powerful method, which is widely used for high-throughput quantitative and qualitative analysis of cells. However, its straightforward applicability for extracellular vesicles (EVs) and mainly exosomes is hampered by several challenges, reflecting mostly the small size of these vesicles (exosomes: ~80–200 nm, microvesicles: ~200–1,000 nm), their polydispersity, and low refractive index. The current best and most widely used protocol for beads-free flow cytometry of exosomes uses ultracentrifugation (UC) coupled with floatation in sucrose gradient for their isolation, labeling with lipophilic dye PKH67 and antibodies, and an optimized version of commercial high-end cytometer for analysis. However, this approach requires an experienced flow cytometer operator capable of manual hardware adjustments and calibration of the cytometer. Here, we provide a novel and fast approach for quantification and characterization of both exosomes and microvesicles isolated from cell culture media as well as from more complex human samples (ascites of ovarian cancer patients) suitable for multiuser labs by using a flow cytometer especially designed for small particles, which can be used without adjustments prior to data acquisition. EVs can be fluorescently labeled with protein-(Carboxyfluoresceinsuccinimidyl ester, CFSE) and/or lipid- (FM) specific dyes, without the necessity of removing the unbound fluorescent dye by UC, which further facilitates and speeds up the characterization of microvesicles and exosomes using flow cytometry. In addition, double labeling with protein- and lipid-specific dyes enables separation of EVs from common contaminants of EV preparations, such as protein aggregates or micelles formed by unbound lipophilic styryl dyes, thus not leading to overestimation of EV numbers. Moreover, our protocol is compatible with antibody labeling using fluorescently conjugated primary antibodies. The presented methodology opens the possibility for routine quantification and characterization of EVs from various sources. Finally, it has the potential to bring a desired level of control into routine experiments and non-specialized labs, thanks to its simple bead-based standardization.

Fully grown oocytes (FGOs) contain all the necessary transcripts to activate molecular pathways underlying the oocyte-to-embryo transition (OET). To elucidate this critical period of development, an extensive survey of the FGO transcriptome was performed by analyzing 19,000 expressed sequence tags of the Mus musculus FGO cDNA library. Expression of 5400 genes and transposable elements is reported. For a majority of genes expressed in mouse FGOs, homologs transcribed in eggs of Xenopus laevis or Ciona intestinalis were found, pinpointing evolutionary conservation of most regulatory cascades underlying the OET in chordates. A large proportion of identified genes belongs to several gene families with oocyte-restricted expression, a likely result of lineage-specific genomic duplications. Gene loss by mutation and expression in female germline of retrotransposed genes specific to M. musculus is documented. These findings indicate rapid diversification of genes involved in female reproduction. Comparison of the FGO and two-cell embryo transcriptomes demarcated the processes important for oogenesis from those involved in OET and identified novel motifs in maternal mRNAs associated with transcript stability. Discovery of oocyte-specific eukaryotic translation initiation factor 4E distinguishes a novel system of translational regulation. These results implicate conserved pathways underlying transition from oogenesis to initiation of development and illustrate how genes acquire and lose reproductive functions during evolution, a potential mechanism for reproductive isolation.[Keywords: Eukaryotic initiation factor-4E; gene expression profiling; maternal effect gene; mRNA stability; multigene family; reproductive isolation; retroelements] Supplemental material is available at http://www.genesdev.org.