Twenty‐five years of PTHrP progress: From cancer hormone to multifunctional cytokine

Twenty‐five years ago a “new” protein was identified from cancers that caused hypercalcemia. It was credited for its ability to mimic parathyroid hormone (PTH), and hence was termed parathyroid hormone‐related protein (PTHrP). Today it is recognized for its widespread distribution, its endocrine, paracrine, and intracrine modes of action driving numerous physiologic and pathologic conditions, and its central role in organogenesis. The multiple biological activities within a complex molecule with paracrine modulation of adjacent target cells present boundless possibilities. The protein structure of PTHrP has been traced, dissected, and deleted comprehensively and conditionally, yet numerous questions lurk in its past that will carry into the future. Issues of the variable segments of the protein, including the enigmatic nuclear localization sequence, are only recently being clarified. Aspects of PTHrP production and action in the menacing condition of cancer are emerging as dichotomies that may represent intended temporal actions of PTHrP. Relative to PTH, the hormone regulating calcium homeostasis, PTHrP “controls the show” locally at the PTH/PTHrP receptor throughout the body. Great strides have been made in our understanding of PTHrP actions, yet years of exciting investigation and discovery are imminent. © 2012 American Society for Bone and Mineral Research.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/91351/1/1617_ftp.pd

Developing predictive models of health literacy.

IntroductionLow health literacy (LHL) remains a formidable barrier to improving health care quality and outcomes. Given the lack of precision of single demographic characteristics to predict health literacy, and the administrative burden and inability of existing health literacy measures to estimate health literacy at a population level, LHL is largely unaddressed in public health and clinical practice. To help overcome these limitations, we developed two models to estimate health literacy.MethodsWe analyzed data from the 2003 National Assessment of Adult Literacy (NAAL), using linear regression to predict mean health literacy scores and probit regression to predict the probability of an individual having 'above basic' proficiency. Predictors included gender, age, race/ethnicity, educational attainment, poverty status, marital status, language spoken in the home, metropolitan statistical area (MSA) and length of time in U.S.ResultsAll variables except MSA were statistically significant, with lower educational attainment being the strongest predictor. Our linear regression model and the probit model accounted for about 30% and 21% of the variance in health literacy scores, respectively, nearly twice as much as the variance accounted for by either education or poverty alone.ConclusionsMultivariable models permit a more accurate estimation of health literacy than single predictors. Further, such models can be applied to readily available administrative or census data to produce estimates of average health literacy and identify communities that would benefit most from appropriate, targeted interventions in the clinical setting to address poor quality care and outcomes related to LHL

Local Residential Sorting and Public Goods Provision: A Classroom Demonstration

This classroom exercise illustrates the Tiebout (1956) hypothesis that residential sorting across multiple jurisdictions leads to a more efficient allocation of local public goods. The exercise places students with heterogeneous preferences over a public good into a single classroom community. A simple voting mechanism determines the level of public good provision in the community. Next, the classroom is divided in two, and students may choose to move between the two smaller communities, sorting themselves according to their preferences for public goods. The exercise places cost on movement at first, then allows for costless sorting. Students have the opportunity to observe how social welfare rises through successive rounds of the exercise, as sorting becomes more complete. They may also observe how immobile individuals can become worse off because of incomplete sorting when the Tiebout assumptions do not hold perfectly

The geographic distribution of breast cancer incidence in Massachusetts 1988 to 1997, adjusted for covariates

BACKGROUND: The aims of this study were to determine whether observed geographic variations in breast cancer incidence are random or statistically significant, whether statistically significant excesses are temporary or time-persistent, and whether they can be explained by covariates such as socioeconomic status (SES) or urban/rural status? RESULTS: A purely spatial analysis found fourteen geographic areas that deviated significantly from randomness: ten with higher incidence rates than expected, four lower than expected. After covariate adjustment, three of the ten high areas remained statistically significant and one new high area emerged. The space-time analysis identified eleven geographic areas as statistically significant, seven high and four low. After covariate adjustment, four of the seven high areas remained statistically significant and a fifth high area also identified in the purely spatial analysis emerged. CONCLUSIONS: These analyses identify geographic areas with invasive breast cancer incidence higher or lower than expected, the times of their excess, and whether or not their status is affected when the model is adjusted for risk factors. These surveillance findings can be a sound starting point for the epidemiologist and has the potential of monitoring time trends for cancer control activities

What Do We Think We Think We Are Doing?: Metacognition and Self-Regulation in Programming

Metacognition and self-regulation are popular areas of interest in programming education, and they have been extensively researched outside of computing. While computing education researchers should draw upon this prior work, programming education is unique enough that we should explore the extent to which prior work applies to our context. The goal of this systematic review is to support research on metacognition and self-regulation in programming education by synthesizing relevant theories, measurements, and prior work on these topics. By reviewing papers that mention metacognition or self-regulation in the context of programming, we aim to provide a benchmark of our current progress towards understanding these topics and recommendations for future research. In our results, we discuss eight common theories that are widely used outside of computing education research, half of which are commonly used in computing education research. We also highlight 11 theories on related constructs (e.g., self-efficacy) that have been used successfully to understand programming education. Towards measuring metacognition and self-regulation in learners, we discuss seven instruments and protocols that have been used and highlight their strengths and weaknesses. To benchmark the current state of research, we examined papers that primarily studied metacognition and self-regulation in programming education and synthesize the reported interventions used and results from that research. While the primary intended contribution of this paper is to support research, readers will also learn about developing and supporting metacognition and self-regulation of students in programming courses

Purkinje cell loss in experimental autoimmune encephalomyelitis

Gray matter atrophy observed by brain MRI is an important correlate to clinical disability and disease duration in multiple sclerosis. The objective of this study was to link brain atrophy visualized by neuroimaging to its underlying neuropathology using the MS model, experimental autoimmune encephalomyelitis (EAE). Volumetric changes in brains of EAE mice, as well as matched healthy normal controls, were quantified by collecting post-mortem high-resolution T2-weighted magnetic resonance microscopy and actively stained magnetic resonance histology images. Anatomical delineations demonstrated a significant decrease in the volume of the whole cerebellum, cerebellar cortex, and molecular layer of the cerebellar cortex in EAE as compared to normal controls. The pro-apoptotic marker caspase-3 was detected in Purkinje cells and a significant decrease in Purkinje cell number was found in EAE. Cross modality and temporal correlations revealed a significant association between Purkinje cell loss on neuropathology and atrophy of the molecular layer of the cerebellar cortex by neuroimaging. These results demonstrate the power of using combined population atlasing and neuropathology approaches to discern novel insights underlying gray matter atrophy in animal models of neurodegenerative disease

Which literacy skills are associated with smoking?

Background Research has demonstrated associations between smoking and reading skills, but other literacy skills such as speaking, listening and numeracy are less studied despite our dependence on the use of numbers and the oral exchange to deliver information on the risks of smoking. Methods We used multivariable logistic regression to examine the effects of reading, numeracy, speaking and listening skills on 1) becoming a regular smoker and 2) smoking cessation. Further, multivariable linear regression was used to examine the relation between literacy skills and amount smoked among current smokers. Models controlled for education, gender, age, race/ethnicity, income, and, when relevant, age they became a regular smoker. Results For each grade equivalent increase in reading skills, the odds of quitting smoking increased by about 8% (OR=1.08, 95%CI: 1.01–1.15). For every point increase in numeracy skills, the odds of quitting increased by about 24% (OR=1.24, 95%CI: 1.06 – 1.46). No literacy skills were associated with becoming a regular smoker or current amount smoked. Conclusion The ability to locate, understand and use information related to the risks of smoking may impact one’s decision to quit. Messaging should be designed with the goal of being easily understood by all individuals regardless of literacy level

Beryllium-specific CD4+ T cells induced by chemokine neoantigens perpetuate inflammation

Discovering dominant epitopes for T cells, particularly CD4+ T cells, in human immune-mediated diseases remains a significant challenge. Here, we used bronchoalveolar lavage (BAL) cells from HLA-DP2-expressing patients with chronic beryllium disease (CBD), a debilitating granulomatous lung disorder characterized by accumulations of beryllium (Be)-specific CD4+ T cells in the lung. We discovered lung resident CD4+ T cells that expressed a disease-specific public CDR3β T cell receptor motif and were specific to Be-modified self-peptides derived from C-C motif ligands 4 (CCL4) and 3 (CCL3). HLA-DP2-CCL/Be tetramer staining confirmed that these chemokine-derived peptides represented major antigenic targets in CBD. Furthermore, Be induced CCL3 and 4 secretion in the lungs of mice and humans. In a murine model of CBD, the addition of LPS to Be oxide exposure enhanced CCL4 and CCL3 secretion in the lung and significantly increased the number and percentage of CD4+ T cells specific for the HLA-DP2-CCL/Be epitope. Thus, we demonstrate a direct link between Be-induced innate production of chemokines and the development of a robust adaptive immune response to those same chemokines presented as Be-modified self-peptides, creating a vicious cycle of innate and adaptive immune activation

Beryllium-specific CD4\u3csup\u3e+\u3c/sup\u3e T cells induced by chemokine neoantigens perpetuate inflammation

Discovering dominant epitopes for T cells, particularly CD4+ T cells, in human immune-mediated diseases remains a significant challenge. Here, we used bronchoalveolar lavage (BAL) cells from HLA-DP2–expressing patients with chronic beryllium disease (CBD), a debilitating granulomatous lung disorder characterized by accumulations of beryllium-specific (Be-specific) CD4+ T cells in the lung. We discovered lung-resident CD4+ T cells that expressed a disease-specific public CDR3β T cell receptor motif and were specific to Be-modified self-peptides derived from C-C motif ligand 4 (CCL4) and CCL3. HLADP2–CCL/Be tetramer staining confirmed that these chemokine-derived peptides represented major antigenic targets in CBD. Furthermore, Be induced CCL3 and CCL4 secretion in the lungs of mice and humans. In a murine model of CBD, the addition of LPS to Be oxide exposure enhanced CCL4 and CCL3 secretion in the lung and significantly increased the number and percentage of CD4+ T cells specific for the HLA-DP2–CCL/Be epitope. Thus, we demonstrate a direct link between Be-induced innate production of chemokines and the development of a robust adaptive immune response to those same chemokines presented as Be-modified self-peptides, creating a cycle of innate and adaptive immune activation