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Simon Lin

Publications and source records attributed to Simon Lin.

6 recordsLinked to original sources
PubMed2005

Molecular profile and partial functional analysis of novel endothelial cell-derived growth factors that regulate hematopoiesis.

Recent progress has been made in the identification of the osteoblastic cellular niche for hematopoietic stem cells (HSCs) within the bone marrow (BM). Attempts to identify the soluble factors that regulate HSC self-renewal have been less successful. We have demonstrated that primary human brain endothelial cells (HUBECs) support the ex vivo amplification of primitive human BM and cord blood cells capable of repopulating non-obese diabetic/severe combined immunodeficient repopulating (SCID) mice (SCID repopulating cells [SRCs]). In this study, we sought to characterize the soluble hematopoietic activity produced by HUBECs and to identify the growth factors secreted by HUBECs that contribute to this HSC-supportive effect. Extended noncontact HUBEC cultures supported an eight-fold increase in SRCs when combined with thrombopoietin, stem cell factor, and Flt-3 ligand compared with input CD34(+) cells or cytokines alone. Gene expression analysis of HUBEC biological replicates identified 65 differentially expressed, nonredundant transcripts without annotated hematopoietic activity. Gene ontology studies of the HUBEC transcriptome revealed a high concentration of genes encoding extracellular proteins with cell-cell signaling function. Functional analyses demonstrated that adrenomedullin, a vasodilatory hormone, synergized with stem cell factor and Flt-3 ligand to induce the proliferation of primitive human CD34(+)CD38(-)lin(-) cells and promoted the expansion of CD34(+) progenitors in culture. These data demonstrate the potential of primary HUBECs as a reservoir for the discovery of novel secreted proteins that regulate human hematopoiesis.

Adrenomedullin↗
PubMed2005

Differential cardiac gene expression during cardiopulmonary bypass: ischemia-independent upregulation of proinflammatory genes.

OBJECTIVE: Cardiac surgery with cardiopulmonary bypass induces both systemic and local inflammatory responses implicated in the pathogenesis of myocardial dysfunction. Multifactorial perioperative sources of myocardial injury complicate understanding of the molecular mechanisms involved. By using microarray technology, this study examines myocardial gene expression responses to cardiopulmonary bypass in the absence of cardioplegic arrest and ischemia-reperfusion injury. METHODS: We used a unique rat model of cardiopulmonary bypass in which sternotomy, direct operations on the heart, aortic crossclamping, and cardioplegic arrest were not performed. Hearts from 6 animals randomized to either 90 minutes of cardiopulmonary bypass or sham control animals were used to perform cDNA microarray analyses of 2343 genes. Real-time quantitative polymerase chain reaction was used to confirm the microarray results for a subset of genes. RESULTS: Compared with sham-operated control animals, myocardium from animals undergoing cardiopulmonary bypass revealed 42 differentially expressed genes. Upregulated genes include the transcription activator nuclear factor kappaB, adhesion molecules (vascular cell adhesion molecule 1 and P-selectin), and interleukin 6 receptor subunits; downregulated genes include transforming growth factor beta receptor 2, tissue inhibitor of metalloproteinase 3, and mitogen-activated protein kinase 1. Distinct proinflammatory gene cascades were confirmed by means of category overrepresentation analysis. CONCLUSIONS: This study represents an initial report on the use of microarray technology to elucidate cardiac transcriptional programs in response to cardiopulmonary bypass-specific injury in vivo. These preliminary findings, combined with future functional genomic studies superimposing ischemia and reperfusion and other inflammatory stimuli, should improve our understanding of the molecular regulatory networks involved in myocardial responses to injury and aid in the development of novel cardioprotective and perfusion strategies.

Animals↗
PubMed2004

Impaired cell adhesion and apoptosis in a novel CLN9 Batten disease variant.

We describe the ninth variant of neuronal ceroid lipofuscinosis (NCL) or Batten disease, due to defects in a putative new gene, CLN9. We therefore refer to the new variant as CLN9-deficient. Two Serbian sisters and two German brothers are described. Their clinical history is characteristic for juvenile NCL. They show similar gene expression patterns. The existence of this variant is supported by the presence of curvilinear inclusions, fingerprint profiles, and granular osmiophilic deposits in neurons, lymphocytes, and conjunctival cells. Enzyme screening and sequencing of the coding regions of other NCL genes was negative. CLN9-deficient cells have a distinctive phenotype. They have rounded cell bodies, have prominent nucleoli, attach poorly to the culture dish, and are sensitive to apoptosis but have increased growth rates. Gene expression of proteins involved in cell adhesion and apoptosis is altered in these cells. Sphingolipid metabolism is also perturbed. They have decreased levels of ceramide, sphingomyelin, lactosylceramide, ceramide trihexoside, and globoside and increased activity of serine palmitoyl transferase.

Adolescent↗
PubMed2002

Applications of Tree-Maps to hierarchical biological data.

UNLABELLED: A brief overview of Tree-Maps provides the basis for understanding two new implementations of Tree-Map methods. TreeMapClusterView provides a new way to view microarray gene expression data, and GenePlacer provides a view of gene ontology annotation data. We also discuss the benefits of Tree-Maps to visualize complex hierarchies in functional genomics. AVAILABILITY: Java class files are freely available at http://mendel.mc.duke.edu/bioinformatics/ CONTACT: mccon012@mc.duke.edu SUPPLEMENTARY INFORMATION: For more information on TreeMapClusterView (see http://mendel.mc.duke.edu/bioinformatics/software/boxclusterview/), and http://mendel.mc.duke.edu/bioinformatics/software/geneplacer/).

Algorithms↗
PubMedDate not supplied

Data mining issues and opportunities for building nursing knowledge.

Health care information systems tend to capture data for nursing tasks, and have little basis in nursing knowledge. Opportunity lies in an important issue where the knowledge used by expert nurses (nursing knowledge workers) in caring for patients is undervalued in the health care system. The complexity of nursing's knowledge base remains poorly articulated and inadequately represented in contemporary information systems. There is opportunity for data mining methods to assist with discovering important linkages between clinical data, nursing interventions, and patient outcomes. Following a brief overview of relevant data mining techniques, a preterm risk prediction case study illustrates the opportunities and describes typical data mining issues in the nontrivial task of building knowledge. Building knowledge in nursing, using data mining or any other method, will make progress only if important data that capture expert nurses' contributions are available in clinical information systems configurations.

Artificial Intelligence↗