Transcriptome and glycome profiling of human hematopoietic CD133+ and CD34+ cells

New blood cells are continuously provided by self-renewing multipotent hematopoietic stem cells (HSC). The capacity of HSCs to regenerate the hematopoietic system is utilized in the treatment of patients with hematological malignancies. HSCs can be enriched using an antibody-based recognition of CD34 or CD133 glycoproteins on the cell surface. The CD133+ and CD34+ cells may have partly different roles in hematopoiesis. Furthermore, each cell has a glycome typical for that cell type. Knowledge of HSC glycobiology can be used to design therapeutic cells with improved cell proliferation or homing properties. The present studies characterize the global gene expression profile of human cord blood-derived CD133+ and CD34+ cells, and demonstrate the differences between CD133+ and CD34+ cell populations that may have an impact in transplantation when CD133+ and CD34+ selected cells are used. In addition, these studies unravel the glycome profile of primitive hematopoietic cells and reveal the transcriptional regulation of N-glycan biosynthesis in CD133+ and CD34+ cells. The gene expression profile of CD133+ cells represents 690 differentially expressed transcripts between CD133+ cells and CD133- cells. CD34+ cells have 620 transcripts differentially expressed when compared to CD34- cells. The integrated CD133+/CD34+ cell gene expression profiles proffer novel transcripts to specify HSCs. Furthermore, the differences between the gene expression profiles of CD133+ and CD34+ cells indicate differences in the transcriptional regulation of CD133+ and CD34+ cells. CD133+ cells express a lower number of hematopoietic lineage differentiation marker genes than CD34+ cells. The expression profiles suggest a more primitive nature of CD133+ cells. Moreover, CD133+ cells have characteristic glycome that differ from the glycome of CD133- cells. High mannose-type and biantennary complex-type N-glycans are enriched in CD133+ cells. N-glycosylation-related gene expression pattern of CD133+ cells identify the key genes regulating the CD133+ cell-specific glycosylation including the overexpression of MGAT2 and underexpression of MGAT4. The putative role of MAN1C1 in the increase of unprocessed high mannose-type N-glycans in CD133+ cells is also discussed. These studies provide new information on the characteristics of HSCs. Improved understanding of HSC biology can be used to design therapeutic cells with improved cell proliferation and homing properties. As a result, HSC engineering could further their clinical use.

Periodontitis and peri-implantitis biomarkers in human oral fluids and the null-allele mouse model

Tissue destruction associated with the periodontal disease progression is caused by a cascade of host and microbial factors and proteolytic enzymes. Aberrant laminin-332 (Ln-332), human beta defensin (hBD), and matrix metalloproteinase (MMP) functions have been found in oral inflammatory diseases. The null-allele mouse model appears as the next step in oral disease research. The MMP-8 knock-out mouse model allowed us to clarify the involvement of MMP-8 in vivo in oral and related inflammatory diseases where MMP-8 is suggested to play a key role in tissue destruction. The cleaved Ln-332 γ2-chain species has been implicated in the apical migration of sulcular epithelial cells during the formation of periodontal pockets. We demonstrated that increased Ln-332 fragment levels in gingival crevicular fluid (GCF) are strongly associated with the severity of inflammation in periodontitis. Porphyromonas gingivalis trypsin-like proteinase can cleave an intact Ln-332 γ2-chain into smaller fragments and eventually promote the formation of periodontal pockets. hBDs are components of an innate mucosal defense against pathogenic microbes. Our results suggest that P. gingivalis trypsin-like proteinase can degrade hBD and thus reduce the innate immune response. Elevated levels and the increased activity of MMPs have been detected in several pathological tissue-destructive conditions where MMPs are shown to cleave extracellular matrix (ECM) and basement membrane (BM) molecules and to facilitate tissue destruction. Elevated levels of MMP-8 have been reported in many inflammatory diseases. In periodontitis, MMP-8 levels in gingival crevicular fluid (GCF) and in peri-implant sulcular fluid (PISF) are elevated at sites of active inflammation, and the increased levels of MMP-8 are mainly responsible for collagenase activity, which leads to tissue destruction. MMP-25, expressed by neutrophils, is involved in inflammatory diseases and in ECM turnover. MMP-26 can degrade ECM components and serve as an activator of other MMP enzymes. We further confirmed that increased levels and activation of MMP-8, -25, and -26 in GCF, PISF, and inflamed gingival tissue are associated with the severity of periodontal/peri-implant inflammation. We evaluated the role of MMP-8 in P. gingivalis-induced periodontitis by comparing MMP-8 knock-out (MMP8-/-) and wild-type mice. Surprisingly, MMP-8 significantly attenuated P. gingivalis-induced site-specific alveolar bone loss. We also evaluated systemic changes in serum immunoglobulin and lipoprotein profiles among these mouse groups. P. gingivalis infection increased HDL/VLDL particle size in the MMP-8-/- mice, which is an indicator of lipoprotein responses during systemic inflammation. Serum total LPS and IgG antibody levels were enhanced in both mice groups. P. gingivalis-induced periodontitis, especially in MMP-8-/- mice, is associated with severe alveolar bone loss and with systemic inflammatory and lipoprotein changes that are likely to be involved in early atherosclerosis.

Design and testing of stand-specific bucking instructions for use on modern cut-to-length harvesters

This study addresses three important issues in tree bucking optimization in the context of cut-to-length harvesting. (1) Would the fit between the log demand and log output distributions be better if the price and/or demand matrices controlling the bucking decisions on modern cut-to-length harvesters were adjusted to the unique conditions of each individual stand? (2) In what ways can we generate stand and product specific price and demand matrices? (3) What alternatives do we have to measure the fit between the log demand and log output distributions, and what would be an ideal goodness-of-fit measure? Three iterative search systems were developed for seeking stand-specific price and demand matrix sets: (1) A fuzzy logic control system for calibrating the price matrix of one log product for one stand at a time (the stand-level one-product approach); (2) a genetic algorithm system for adjusting the price matrices of one log product in parallel for several stands (the forest-level one-product approach); and (3) a genetic algorithm system for dividing the overall demand matrix of each of the several log products into stand-specific sub-demands simultaneously for several stands and products (the forest-level multi-product approach). The stem material used for testing the performance of the stand-specific price and demand matrices against that of the reference matrices was comprised of 9 155 Norway spruce (Picea abies (L.) Karst.) sawlog stems gathered by harvesters from 15 mature spruce-dominated stands in southern Finland. The reference price and demand matrices were either direct copies or slightly modified versions of those used by two Finnish sawmilling companies. Two types of stand-specific bucking matrices were compiled for each log product. One was from the harvester-collected stem profiles and the other was from the pre-harvest inventory data. Four goodness-of-fit measures were analyzed for their appropriateness in determining the similarity between the log demand and log output distributions: (1) the apportionment degree (index), (2) the chi-square statistic, (3) Laspeyres quantity index, and (4) the price-weighted apportionment degree. The study confirmed that any improvement in the fit between the log demand and log output distributions can only be realized at the expense of log volumes produced. Stand-level pre-control of price matrices was found to be advantageous, provided the control is done with perfect stem data. Forest-level pre-control of price matrices resulted in no improvement in the cumulative apportionment degree. Cutting stands under the control of stand-specific demand matrices yielded a better total fit between the demand and output matrices at the forest level than was obtained by cutting each stand with non-stand-specific reference matrices. The theoretical and experimental analyses suggest that none of the three alternative goodness-of-fit measures clearly outperforms the traditional apportionment degree measure. Keywords: harvesting, tree bucking optimization, simulation, fuzzy control, genetic algorithms, goodness-of-fit

The Quest for Well-being in Growth Industries: Contexts, Research Design and Methodological Development

This Working Paper reports the background to the first stage of the ongoing research project, The Quest for Well-being in Growth Industries: A Collaborative Study in Finland and Scotland, conducted under the auspices of the Academy of Finland research programme The Future of Work and Well-being (2008-2011). This collaborative project provides national and transnational data, analysis and outputs. The study is being conducted in the Department of Management and Organisation, Hanken School of Economics, Finland, in collaboration with Glasgow Caledonian University, University of East London, Heriot-Watt University and Reading University, UK. The project examines policies and practices towards the enhancement of work-related well-being in growth industries, and contradictory pressures and tensions posed in this situation. The overall aim is to evaluate the development, implementation and use of work-related well-being policies in four selected growth industries. These sectors – electronics, care, finance and accounting, and tourism – have been selected on the basis of European Union and national forecasts, and demographic and socio-economic trends in employment. In this working paper we outline the background to the research study, the initial research plan, and how the survey of employers has been constructed. The working paper concludes with a brief discussion of general ongoing research issues arising in the project.