Jennifer Hipp

Sources of Stem Cells for Regenerative Medicine

The shortage of organ donors for regenerative medicine has stimulated research on stem cells as a potential resource for cell-based therapy. Stem cells have been used widely for regenerative medicine applications. The development of innovative methods to generate stem cells from different sources suggests that there may be new alternatives for cell-based therapies. Here, we provide an overview of human embryonic stem cells (hES) and the methods for obtaining these cells and other broadly multipotent or pluripotent cell types. These methods include somatic cell nuclear transfer, single cell embryo biopsy, arrested embryos, altered nuclear transfer, and reprogramming somatic cells. We also discuss the use of amniotic-fluid derived stem cells (AFS) for potential patient-specific therapies.

GeneChip analysis of human embryonic stem cell differentiation into hemangioblasts: an in silico dissection of mixed phenotypes

BackgroundMicroarrays are being used to understand human embryonic stem cell (hESC) differentiation. Most differentiation protocols use a multi-stage approach that induces commitment along a particular lineage. Therefore, each stage represents a more mature and less heterogeneous phenotype. Thus, characterizing the heterogeneous progenitor populations upon differentiation are of increasing importance. Here we describe a novel method of data analysis using a recently developed differentiation protocol involving the formation of functional hemangioblasts from hESCs. Blast cells are multipotent and can differentiate into multiple lineages of hematopoeitic cells (erythroid, granulocyte and macrophage), endothelial and smooth muscle cells.ResultsLarge-scale transcriptional analysis was performed at distinct time points of hESC differentiation (undifferentiated hESCs, embryoid bodies, and blast cells, the last of which generates both hematopoietic and endothelial progenies). Identifying genes enriched in blast cells relative to hESCs revealed a genetic signature indicative of erythroblasts, suggesting that erythroblasts are the predominant cell type in the blast cell population. Because of the heterogeneity of blast cells, numerous comparisons were made to publicly available data sets in silico, some of which blast cells are capable of differentiating into, to assess and characterize the blast cell population. Biologically relevant comparisons masked particular genetic signatures within the heterogeneous population and identified genetic signatures indicating the presence of endothelia, cardiomyocytes, and hematopoietic lineages in the blast cell population.ConclusionThe significance of this microarray study is in its ability to assess and identify cellular populations within a heterogeneous population through biologically relevant in silico comparisons of publicly available data sets. In conclusion, multiple in silico comparisons were necessary to characterize tissue-specific genetic signatures within a heterogeneous hemangioblast population.

SIVQ-aided laser capture microdissection: A tool for high-throughput expression profiling

Introduction: Laser capture microdissection (LCM) facilitates procurement of defined cell populations for study in the context of histopathology. The morphologic assessment step in the LCM procedure is time consuming and tedious, thus restricting the utility of the technology for large applications. Results: Here, we describe the use of Spatially Invariant Vector Quantization (SIVQ) for histological analysis and LCM. Using SIVQ, we selected vectors as morphologic predicates that were representative of normal epithelial or cancer cells and then searched for phenotypically similar cells across entire tissue sections. The selected cells were subsequently auto-microdissected and the recovered RNA was analyzed by expression microarray. Gene expression profiles from SIVQ-LCM and standard LCM-derived samples demonstrated highly congruous signatures, confirming the equivalence of the differing microdissection methods. Conclusion: SIVQ-LCM improves the work-flow of microdissection in two significant ways. First, the process is transformative in that it shifts the pathologist′s role from technical execution of the entire microdissection to a limited-contact supervisory role, enabling large-scale extraction of tissue by expediting subsequent semi-autonomous identification of target cell populations. Second, this work-flow model provides an opportunity to systematically identify highly constrained cell populations and morphologically consistent regions within tissue sections. Integrating SIVQ with LCM in a single environment provides advanced capabilities for efficient and high-throughput histological-based molecular studies.

Microarray analysis of bladder smooth muscle from patients with myelomeningocele

To examine whether gene profiles can provide a molecular evaluation of the quality and therapeutic potential in patients with myelomeningocele (MM), by comparing genetic profiles of smooth muscle cells (SMCs) from healthy bladders and bladders from patients, to identify genes that are over‐ and under‐expressed in MM bladder SMCs.

Ethanol Alters the Osteogenic Differentiation of Amniotic Fluid-Derived Stem Cells

BACKGROUND Fetal alcohol spectrum disorder (FASD) is a set of developmental defects caused by prenatal alcohol exposure. Clinical manifestations of FASD are highly variable and include mental retardation and developmental defects of the heart, kidney, muscle, skeleton, and craniofacial structures. Specific effects of ethanol on fetal cells include induction of apoptosis as well as inhibition of proliferation, differentiation, and migration. This complex set of responses suggests that a bioinformatics approach could clarify some of the pathways involved in these responses. METHODS In this study, the responses of fetal stem cells derived from the amniotic fluid (AFSCs) to treatment with ethanol have been examined. Large-scale transcriptome analysis of ethanol-treated AFSCs indicates that genes involved in skeletal development and ossification are up-regulated in these cells. Therefore, the effect of ethanol on osteogenic differentiation of AFSCs was studied. RESULTS Exposure to ethanol during the first 48 hours of an osteogenic differentiation protocol increased in vitro calcium deposition by AFSCs and increased alkaline phosphatase activity. In contrast, ethanol treatment later in the differentiation protocol (day 8) had no significant effect on the activity of alkaline phosphatase. CONCLUSIONS These results suggest that transient exposure of AFSCs to ethanol during early differentiation enhances osteogenic differentiation of the cells.

Diagnostic yield of ThinPrep preparation in the assessment of fine‐needle aspiration biopsy of salivary gland neoplasms

Fine‐needle aspiration (FNA) has been widely recognized as an important modality in assessment of salivary gland neoplasms, and specimens are often processed as conventional smears. We conducted the current study to evaluate the diagnostic utility of ThinPrep preparation as an alternative method for assessment of salivary gland neoplasms.

Functional genomics: new insights into the 'function' of low levels of gene expression in stem cells.

Understanding the global gene expression profile of stem cells and their multilineage differentiation will be essential for their ultimate therapeutic application. Efforts to characterize stem cells have relied on analyzing the genome-wide expression profiles that are biased towards the identification of genes that display the most pronounced differential expression. Rather than being viewed as a “blank” state, recent studies suggest that stem cells express low levels of multiple lineage specific genes prior to differentiation, a phenomenon known as “lineage priming.” It is not likely that low levels of lineage-specific genes produce sufficient amounts of differentiation factors, but rather to provide rapid transcription to a wide range of lineage programs prior to differentiation. Thus, stem cell differentiation may involve the elimination of other potential pathways and the activation of a specific lineage program.

Poorly Differentiated ("Insular") Thyroid Carcinoma on Fine-Needle Aspiration

Abstract Poorly differentiated thyroid carcinoma (PDTC) is a distinct entity of thyroid follicular origin (without follicular or papillary differentiation), with high-grade features and an aggressive clinical behavior intermediate between that of well-differentiated and undifferentiated thyroid carcinoma. It accounts for 4% to 7% of thyroid malignancies. Poorly differentiated thyroid carcinoma often presents at an advanced stage and tends to metastasize to regional lymph nodes, lungs, and bones. A variety of histological patterns exists for PDTC and the corresponding cytomorphological features are also varied and depend on the growth pattern of the individual neoplasm. We report the cytomorphology of PDTC sampled by fine-needle aspiration and review previously reported cases in the literature. While PDTC do not possess specific cytomorphological features that would allow for a definitive diagnosis on fine-needle aspiration, the presence of certain features may suggest the possibility of this rare neoplasm. In particular, cells with overlapping bland nuclei found both in groups and individually are common features. Lesions are often cellular and lack colloid, providing the sense of a neoplasm. It may be difficult to exclude the more common possibility of a papillary thyroid carcinoma or follicular neoplasm; however, familiarity with this uncommon entity allows one to include it in the differential diagnosis.

Tryggo: Old norse for truth: The real truth about ground truth: New insights into the challenges of generating ground truth maps for WSI CAD algorithm evaluation.

Tryggo: Old Norse for Truth Ground truth mapping has its origins in the computer science pattern recognition and machine vision fields and is a major activity associated with remote sensing (i.e. satellite images). Additionally, ground truth maps not infrequently find use in the following plurality of settings: motion video road detection and tracking, motion tasks, geoscience applications, sensor data and document analysis. Ground truth maps are needed to perform objective analysis and comparative evaluation of image analysis algorithms[1] and are “defined as a representation of the agreed correct result of the ideal layout analysis method (i.e., the result of the method that, if it existed, would put an end to the research problem).”[2] Operationally, such ground truth maps may be regarded as the “gold standard” by which results of other algorithms are compared.

Image microarrays derived from tissue microarrays (IMA-TMA): New resource for computer-aided diagnostic algorithm development

Background: Conventional tissue microarrays (TMAs) consist of cores of tissue inserted into a recipient paraffin block such that a tissue section on a single glass slide can contain numerous patient samples in a spatially structured pattern. Scanning TMAs into digital slides for subsequent analysis by computer-aided diagnostic (CAD) algorithms all offers the possibility of evaluating candidate algorithms against a near-complete repertoire of variable disease morphologies. This parallel interrogation approach simplifies the evaluation, validation, and comparison of such candidate algorithms. A recently developed digital tool, digital core (dCORE), and image microarray maker (iMAM) enables the capture of uniformly sized and resolution-matched images, with these representing key morphologic features and fields of view, aggregated into a single monolithic digital image file in an array format, which we define as an image microarray (IMA). We further define the TMA-IMA construct as IMA-based images derived from whole slide images of TMAs themselves. Methods: Here we describe the first combined use of the previously described dCORE and iMAM tools, toward the goal of generating a higher-order image construct, with multiple TMA cores from multiple distinct conventional TMAs assembled as a single digital image montage. This image construct served as the basis of the carrying out of a massively parallel image analysis exercise, based on the use of the previously described spatially invariant vector quantization (SIVQ) algorithm. Results: Multicase, multifield TMA-IMAs of follicular lymphoma and follicular hyperplasia were separately rendered, using the aforementioned tools. Each of these two IMAs contained a distinct spectrum of morphologic heterogeneity with respect to both tingible body macrophage (TBM) appearance and apoptotic body morphology. SIVQ-based pattern matching, with ring vectors selected to screen for either tingible body macrophages or apoptotic bodies, was subsequently carried out on the differing TMA-IMAs, with attainment of excellent discriminant classification between the two diagnostic classes. Conclusion: The TMA-IMA construct enables and accelerates high-throughput multicase, multifield based image feature discovery and classification, thus simplifying the development, validation, and comparison of CAD algorithms in settings where the heterogeneity of diagnostic feature morphologic is a significant factor.