Reconciling Flux Experiments for Quantitative Modeling of Normal and Malignant Hematopoietic Stem/Progenitor Dynamics.

Hematopoiesis serves as a paradigm for how homeostasis is maintained within hierarchically organized cell populations. However, important questions remain as to the contribution of hematopoietic stem cells (HSCs) toward maintaining steady state hematopoiesis. A number of in vivo lineage labeling and propagation studies have given rise to contradictory interpretations, leaving key properties of stem cell function unresolved. Using processed flow cytometry data coupled with a biology-driven modeling approach, we show that in vivo flux experiments that come from different laboratories can all be reconciled into a single unifying model, even though they had previously been interpreted as being contradictory. We infer from comparative analysis that different transgenic models display distinct labeling efficiencies across a heterogeneous HSC pool, which we validate by marker gene expression associated with HSC function. Finally, we show how the unified model of HSC differentiation can be used to simulate clonal expansion in the early stages of leukemogenesis

Experimental Investigation of Subcutaneous Pressure and Shear Force Changes Using a Bone Protrusion Model as a Risk Factor for Pressure Ulcer Development

Objectives: Subcutaneous pressure and subcutaneous shear force were investigated using a bone protrusion model to investigate a polyurethane film dressing (hereinafter referred to as adhesive film) for preventing shear force. Our hypothesis was that when pressure or shear force was applied to the body surface, the adhesive film would 1) decrease the shear force on the skin surface and 2) decrease the effect of the external force on the subcutaneous layer. Methods: We built a bone protrusion model using pig skin equipped with a plastic stand and sensors that can simultaneously measure subcutaneous pressure and shear force. In this experimental model, changes in shear force and pressure were measured using a surface friction-measuring device and a subcutaneous sensor. Results: In the bone protrusion model, the effect of body weight on the surface shear force was significant. Contrarily, in the subcutaneous fat model, the effect of the body weight on the subcutaneous shear force was particularly small. When the adhesive film was applied, the surface friction, subcutaneous pressure, and subcutaneous shear force all significantly decreased. Conclusions: A bone protrusion model was created, and the surface friction, subcutaneous pressure, and subcutaneous shear force were continuously measured and found to decrease. The pressure and shear force were reduced when the adhesive film was used. These results will be of great help in the treatment of bedsores

Age-related changes in the hematopoietic stem cell pool revealed via quantifying the balance of symmetric and asymmetric divisions.

Acknowledgements: We thank the University of Tokyo Institute of Medical Science (IMSUT) FACS core laboratory for expert technical assistance.Hematopoietic stem cells (HSCs) are somatic stem cells that continuously generate lifelong supply of blood cells through a balance of symmetric and asymmetric divisions. It is well established that the HSC pool increases with age. However, not much is known about the underlying cause for these observed changes. Here, using a novel method combining single-cell ex vivo HSC expansion with mathematical modeling, we quantify HSC division types (stem cell-stem cell (S-S) division, stem cell-progenitor cell (S-P) division, and progenitor cell-progenitor cell (P-P) division) as a function of the aging process. Our time-series experiments reveal how changes in these three modes of division can explain the increase in HSC numbers with age. Contrary to the popular notion that HSCs divide predominantly through S-P divisions, we show that S-S divisions are predominant throughout the lifespan of the animal, thereby expanding the HSC pool. We, therefore, provide a novel mathematical model-based experimental validation for reflecting HSC dynamics in vivo

The proportion of the expressed transcripts in the RefSeq homologs (control) and unidentified transcripts

Cerebrum, cerebellum, liver, and testis of a male macaque were used for the microarray experiments with duplicated hybridizations. The transcripts were classified into no expression (blue), expressed in 1–3 tissues (grey), or expressed in all tissues (red).<p><b>Copyright information:</b></p><p>Taken from "Large-scale analysis of transcripts and inference of genetic divergence between and "</p><p>http://www.biomedcentral.com/1471-2164/9/90</p><p>BMC Genomics 2008;9():90-90.</p><p>Published online 24 Feb 2008</p><p>PMCID:PMC2287170.</p><p></p

Distribution of transcript expression levels of the RefSeq homologs (blue) and the intergenic transcripts (red)

Only the transcripts that were determined as significantly expressed on the microarray are presented in the figure. Log-transformed signal intensity in the tissue with the highest expression was shown. The intergenic transcripts showed significantly lower expression levels than the RefSeq homologs.<p><b>Copyright information:</b></p><p>Taken from "Large-scale analysis of transcripts and inference of genetic divergence between and "</p><p>http://www.biomedcentral.com/1471-2164/9/90</p><p>BMC Genomics 2008;9():90-90.</p><p>Published online 24 Feb 2008</p><p>PMCID:PMC2287170.</p><p></p

Sequence conservation of the brain-expressed and testis-expressed transcripts between humans and macaques

For the RefSeq homologs (control), the non-synonymous () and synonymous () substitution rates were estimated using the Li-Pamilo-Bianchi method [48]. The substitution rates in the intergenic and intronic transcripts were estimated using Kimura's two parameter methods [55]. The heights of the boxes represent the lower and upper quartile points, and the whiskers show the minimum and maximum points.<p><b>Copyright information:</b></p><p>Taken from "Large-scale analysis of transcripts and inference of genetic divergence between and "</p><p>http://www.biomedcentral.com/1471-2164/9/90</p><p>BMC Genomics 2008;9():90-90.</p><p>Published online 24 Feb 2008</p><p>PMCID:PMC2287170.</p><p></p

RT-PCR gel images for the expression of the intergenic transcripts in the human (H) and the macaque (Q) brain

Transcript names indicate whether the expression was detected by the microarray experiments (red) or not (blue). Expected PCR products are marked by the white arrows.<p><b>Copyright information:</b></p><p>Taken from "Large-scale analysis of transcripts and inference of genetic divergence between and "</p><p>http://www.biomedcentral.com/1471-2164/9/90</p><p>BMC Genomics 2008;9():90-90.</p><p>Published online 24 Feb 2008</p><p>PMCID:PMC2287170.</p><p></p