THE CONSEQUENCES OF DISRUPTING THE MDM2-P53 BALANCE IN HEMATOPOIESIS

The bone marrow accommodates hematopoietic stem cells and progenitors. These cells provide an indispensible resource for replenishing the blood constituents throughout an organism’s life. A tissue with such a high turn-over rate mandates intact cycling checkpoint and apoptotic pathways to avoid inappropriate cell proliferation and ultimately the development of leukemias. p53, a major tumor suppressor, is a transcription factor that regulates cell cycle, and induces apoptosis and senescence. Mice inheriting a hypomorphic p53 allele in the absence of Mdm2, a p53 inhibitor, have elevated p53 cell cycle activity and die by postnatal day 13 due to hematopoietic failure. Hematopoiesis progresses normally during embryogenesis until it moves to the bone marrow in late development. Increased oxidative stress in the bone marrow compartment postnatally is the impediment for normal hematopoiesis via activation of p53. p53 in turn stimulates the generation of more reactive oxygen species and depletes bone marrow cellularity. Also, p53 exerts various defects on the hematopoietic niche by increasing mesenchymal lineage populations and their differentiation. Hematopoietic defects are rescued with antioxidants or when cells are cultured at low oxygen levels. Deletion of p16 partially rescues bone marrow cellularity and progenitors via a p53-independent pathway. Thus, although p53 is required to inhibit tumorigenesis, Mdm2 is required to control ROS-induced p53 levels for sustainable hematopoiesis and survival during homeostasis.

A nonparametric method of comparing the partial areas under two correlated receiver operating characteristic curves

A non-parametric method was developed and tested to compare the partial areas under two correlated Receiver Operating Characteristic curves. Based on the theory of generalized U-statistics the mathematical formulas have been derived for computing ROC area, and the variance and covariance between the portions of two ROC curves. A practical SAS application also has been developed to facilitate the calculations. The accuracy of the non-parametric method was evaluated by comparing it to other methods. By applying our method to the data from a published ROC analysis of CT image, our results are very close to theirs. A hypothetical example was used to demonstrate the effects of two crossed ROC curves. The two ROC areas are the same. However each portion of the area between two ROC curves were found to be significantly different by the partial ROC curve analysis. For computation of ROC curves with large scales, such as a logistic regression model, we applied our method to the breast cancer study with Medicare claims data. It yielded the same ROC area computation as the SAS Logistic procedure. Our method also provides an alternative to the global summary of ROC area comparison by directly comparing the true-positive rates for two regression models and by determining the range of false-positive values where the models differ. ^

IDENTIFICATION AND CHARACTERIZATION OF DISTINCT POPULATIONS OF CLONOGENIC BONE MARROW STROMAL CELLS CAPABLE OF TRANSFERRING THE HEMATOPOIETIC MICROENVIRONMENT IN VIVO AND SUPPORTING LT-HSCs IN VITRO

Bone marrow (BM) stromal cells are ascribed two key functions, 1) stem cells for non-hematopoietic tissues (MSC) and 2) as components of the hematopoietic stem cell niche. Current approaches studying the stromal cell system in the mouse are complicated by the low yield of clonogenic progenitors (CFU-F). Given the perivascular location of MSC in BM, we developed an alternative methodology to isolate MSC from mBM. An intact ‘plug’ of bone marrow is expelled from bones and enzymatically disaggregated to yield a single cell suspension. The recovery of CFU-F (1917.95+199) reproducibly exceeds that obtained using the standard BM flushing technique (14.32+1.9) by at least 2 orders of magnitude (P<0.001; N = 8) with an accompanying 196-fold enrichment of CFU-F frequency. Purified BM stromal and vascular endothelial cell populations are readily obtained by FACS. A detailed immunophenotypic analysis of lineage depleted BM identified PDGFRαβPOS stromal cell subpopulations distinguished by their expression of CD105. Both subpopulations retained their original phenotype of CD105 expression in culture and demonstrate MSC properties of multi-lineage differentiation and the ability to transfer the hematopoietic microenvironment in vivo. To determine the capacity of either subpopulation to support long-term multi-lineage reconstituting HSCs, we fractionated BM stromal cells into either the LinNEGPDGFRαβPOSCD105POS and LINNEGPDGFRαβPOSCD105LOW/- populations and tested their capacity to support LT-HSC by co-culturing each population with either 1 or 10 HSCs for 10 days. Following the 10 day co-culture period, both populations supported transplantable HSCs from 10 cells/well co-cultures demonstrating high levels of donor repopulation with an average of 65+23.6% chimerism from CD105POS co-cultures and 49.3+19.5% chimerism from the CD105NEG co-cultures. However, we observed a significant difference when mice were transplanted with the progeny of a single co-cultured HSC. In these experiments, CD105POS co-cultures (100%) demonstrated long-term multi- lineage reconstitution, while only 4 of 8 mice (50%) from CD105NEG -single HSC co-cultures demonstrated long-term reconstitution, suggesting a more limited expansion of functional stem cells. Taken together, these results demonstrate that the PDGFRαβCD105POS stromal cell subpopulation is distinguished by a unique capacity to support the expansion of long-term reconstituting HSCs in vitro.

Functional Characterization of AtxA, the Bacillus anthracis Virulence Regulator

Coordinated expression of virulence genes in Bacillus anthracis occurs via a multi-faceted signal transduction pathway that is dependent upon the AtxA protein. Intricate control of atxA gene transcription and AtxA protein function have become apparent from studies of AtxA-induced synthesis of the anthrax toxin proteins and the poly-D-glutamic acid capsule, two factors with important roles in B. anthracis pathogenesis. The amino-terminal region of the AtxA protein contains winged-helix (WH) and helix-turn-helix (HTH) motifs, structural features associated with DNA-binding. Using filter binding assays, I determined that AtxA interacted non-specifically at a low nanomolar affinity with a target promoter (Plef) and AtxA-independent promoters. AtxA also contains motifs associated with phosphoenolpyruvate: sugar phosphotransferase system (PTS) regulation. These PTS-regulated domains, PRD1 and PRD2, are within the central amino acid sequence. Specific histidines in the PRDs serve as sites of phosphorylation (H199 and H379). Phosphorylation of H199 increases AtxA activity; whereas, H379 phosphorylation decreases AtxA function. For my dissertation, I hypothesized that AtxA binds target promoters to activate transcription and that DNA-binding activity is regulated via structural changes within the PRDs and a carboxy-terminal EIIB-like motif that are induced by phosphorylation and ligand binding. I determined that AtxA has one large protease-inaccessible domain containing the PRDs and the carboxy-terminal end of the protein. These results suggest that AtxA has a domain that is distinct from the putative DNA-binding region of the protein. My data indicate that AtxA activity is associated with AtxA multimerization. Oligomeric AtxA was detected when co-affinity purification, non-denaturing gel electrophoresis, and bis(maleimido)hexane (BMH) cross-linking techniques were employed. I exploited the specificity of BMH for cysteine residues to show that AtxA was cross-linked at C402, implicating the carboxy-terminal EIIB-like region in protein-protein interactions. In addition, higher amounts of the cross-linked dimeric form of AtxA were observed when cells were cultured in conditions that promote toxin gene expression. Based on the results, I propose that AtxA multimerization requires the EIIB-like motif and multimerization of AtxA positively impacts function. I investigated the role of the PTS in the function of AtxA and the impact of phosphomimetic residues on AtxA multimerization. B. anthracis Enzyme I (EI) and HPr did not facilitate phosphorylation of AtxA in vitro. Moreover, markerless deletion of ptsHI in B. anthracis did not perturb AtxA function. Taken together, these results suggest that proteins other than the PTS phosphorylate AtxA. Point mutations mimicking phosphohistidine (H to D) and non-phosphorylated histidine (H to A) were tested for an impact on AtxA activity and multimerization. AtxA H199D, AtxA H199A, and AtxA H379A displayed multimerization phenotypes similar to that of the native protein, whereas AtxA H379D was not susceptible to BMH cross-linking or co-affinity purification with AtxA-His. These data suggest that phosphorylation of H379 may decrease AtxA activity by preventing AtxA multimerization. Overall, my data support the following model of AtxA function. AtxA binds to target gene promoters in an oligomeric state. AtxA activity is increased in response to the host-related signal bicarbonate/CO2 because this signal enhances AtxA multimerization. In contrast, AtxA activity is decreased by phosphorylation at H379 because multimerization is inhibited. Future studies will address the interplay between bicarbonate/CO2 signaling and phosphorylation on AtxA function.

Resource Review of Walking the Equity Talk: A Guide for Culturally Courageous Leadership in School Communities

Resource Review of: Walking the Equity Talk: A Guide for Culturally Courageous Leadership in School Communities by Robert Brownell II.

The cost of insuring the uninsured in the U.S.

Objectives: This study included two overarching objectives. Through a systematic review of the literature published between 1990 and 2012, the first objective aimed to assess whether insuring the uninsured would result in higher costs compared to insuring the currently insured. Studies that quantified the actual costs associated with insuring the uninsured in the U.S. were included. Based upon 2009 data from the Medical Expenditure Panel Survey (MEPS), the second objective aimed to assess and compare the self-reported health of populations with four different insurance statuses. The second part of this study involved a secondary data analysis of both currently insured and currently uninsured individuals who participated in the MEPS in 2009. The null hypothesis was that there were no differences across the four categories of health insurance status for self-reported health status and healthcare service use. The alternative hypothesis was that were differences across the four categories of health insurance status for self-reported health status and healthcare service use. Methods: For the systematic review, three databases were searched using search terms to identify studies that actually quantified the cost of insuring the uninsured. Thirteen studies were selected, discussed, and summarized in tables. For the secondary data analysis of MEPS data, this study compared four categories of health insurance status: (1) currently uninsured persons who will become eligible for Medicaid under the Patient Protection and Affordable Care Act (PPACA) healthcare reforms in 2014; (2) currently uninsured persons who will be required to buy private insurance through the PPACA health insurance exchanges in 2014; (3) persons currently insured under Medicaid or SCHIP; and (4) persons currently insured with private insurance. The four categories were compared on the basis of demographic information, health status information, and health conditions with relatively high prevalence. Chi-square tests were run to determine if there were differences between the four groups in regard to health insurance status and health status. With some exceptions, the two currently insured groups had worse self-reported health status compared to the two currently uninsured groups. Results: The thirteen studies that met the inclusion criteria for the systematic review included: (1) three cost studies from 1993, 1995, and 1997; (2) four cost studies from 2001, 2003, and 2004; (3) one study of disabilities and one study of immigrants; (4) two state specific studies of uninsured status; and (5) two current studies of healthcare reform. Of the thirteen studies reviewed, four directly addressed the study question about whether insuring the uninsured was more or less expensive than insuring the currently insured. All four of the studies provided support for the study finding that the cost of insuring the uninsured would generally not be higher than insuring those already insured. One study indicated that the cost of insuring the uninsured would be less expensive than insuring the population currently covered by Medicaid, but more expensive to insure than the populations of those covered by employer-sponsored insurance and non-group private insurance. While the nine other studies included in the systematic review discussed the costs associated with insuring the uninsured population, they did not directly compare the costs of insuring the uninsured population with the costs associated with insuring the currently insured population. For the MEPS secondary data analysis, the results of the chi-square tests indicated that there were differences in the distribution of disease status by health insurance status. As anticipated, with some exceptions, the uninsured reported lower rates of disease and healthcare service use. However, for the variable attention deficit disorder, the uninsured reported higher disease rates than the two insured groups. Additionally, for the variables high blood pressure, high cholesterol, and joint pain, the currently insured under Medicaid or SCHIP group reported a lower rate of disease than the two currently insured groups. This result may be due to the lower mean age of the currently insured under Medicaid or SCHIP group. Conclusion: Based on this study, with some exceptions, the costs for insuring the uninsured should not exceed healthcare-related costs for insuring the currently uninsured. The results of the systematic review indicated that the U.S. is already paying some of the costs associated with insuring the uninsured. PPACA will expand health insurance coverage to millions of Americans who are currently uninsured, as the individual mandate and insurance market reforms will require. Because many of the currently uninsured are relatively healthy young persons, the costs associated with expanding insurance coverage to the uninsured are anticipated to be relatively modest. However, for the purposes of construing these results, it is important to note that once individuals obtain insurance, it is anticipated that they will use more healthcare services, which will increase costs. (Abstract shortened by UMI.)^