Cause and context: place-based approaches to investigate how environments affect mental health

Objectives Our surroundings affect our mood, our recovery from stress, our behavior, and, ultimately, our mental health. Understanding how our surroundings influence mental health is central to creating healthy cities. However, the traditional observational methods now dominant in the psychiatric epidemiology literature are not sufficient to advance such an understanding. In this essay we consider potential alternative strategies, such as randomizing people to places, randomizing places to change, or harnessing natural experiments that mimic randomized experiments. Methods We discuss the strengths and weaknesses of these methodological approaches with respect to (1) defining the most relevant scale and characteristics of context, (2) disentangling the effects of context from the effects of individuals’ preferences and prior health, and (3) generalizing causal effects beyond the study setting. Results Promising alternative strategies include creating many small-scale randomized place-based trials, using the deployment of place-based changes over time as natural experiments, and using fluctuations in the changes in our surroundings in combination with emerging data collection technologies to better understand how surroundings influence mood, behavior, and mental health. Conclusions Improving existing research strategies will require interdisciplinary partnerships between those specialized in mental health, those advancing new methods for place effects on health, and those who seek to optimize the design of local environments

Global turnover of histone post-translational modifications and variants in human cells

<p>Abstract</p> <p>Background</p> <p>Post-translational modifications (PTMs) on the N-terminal tails of histones and histone variants regulate distinct transcriptional states and nuclear events. Whereas the functional effects of specific PTMs are the current subject of intense investigation, most studies characterize histone PTMs/variants in a non-temporal fashion and very few studies have reported kinetic information about these histone forms. Previous studies have used radiolabeling, fluorescence microscopy and chromatin immunoprecipitation to determine rates of histone turnover, and have found interesting correlations between increased turnover and increased gene expression. Therefore, histone turnover is an understudied yet potentially important parameter that may contribute to epigenetic regulation. Understanding turnover in the context of histone modifications and sequence variants could provide valuable additional insight into the function of histone replacement.</p> <p>Results</p> <p>In this study, we measured the metabolic rate of labeled isotope incorporation into the histone proteins of HeLa cells by combining stable isotope labeling of amino acids in cell culture (SILAC) pulse experiments with quantitative mass spectrometry-based proteomics. In general, we found that most core histones have similar turnover rates, with the exception of the H2A variants, which exhibit a wider range of rates, potentially consistent with their epigenetic function. In addition, acetylated histones have a significantly faster turnover compared with general histone protein and methylated histones, although these rates vary considerably, depending on the site and overall degree of methylation. Histones containing transcriptionally active marks have been consistently found to have faster turnover rates than histones containing silent marks. Interestingly, the presence of both active and silent marks on the same peptide resulted in a slower turnover rate than either mark alone on that same peptide. Lastly, we observed little difference in the turnover between nearly all modified forms of the H3.1, H3.2 and H3.3 variants, with the notable exception that H3.2K36me2 has a faster turnover than this mark on the other H3 variants.</p> <p>Conclusions</p> <p>Quantitative proteomics provides complementary insight to previous work aimed at quantitatively measuring histone turnover, and our results suggest that turnover rates are dependent upon site-specific post-translational modifications and sequence variants.</p

Timing and effect of a safe routes to school program on child pedestrian injury risk during school travel hours: Bayesian changepoint and difference-in-differences analysis

Background: In 2005, the US Congress allocated $612 million for a national Safe Routes to School (SRTS) program to encourage walking and bicycling to schools. We evaluated the effectiveness of a Safe Routes to School Program (SRTS) in controlling pedestrian injuries among school-age children. Methods: Bayesian changepoint analysis of quarterly counts of pedestrian injuries among 5 to 19-year- old children in New York City between 2001 and 2010 during school-travel hours in census tracts with and without SRTS. Overdispersed Poisson modeling for difference in differences following the changepoint. Results: In SRTS-intervention census tracts, a change point in the quarterly counts of injuries was identified in the second quarter of 2008, which was consistent with the timing of the implementation of SRTS interventions. In census tracts with SRTS interventions, the estimated quarterly rates of pedestrian injury per 10,000 population among school-age children during school-travel hours were 3.47 (95% Credible Interval [CrI] 2.67, 4.39) prior to the changepoint, and 0.74 (95% CrI 0.30, 1.50) after the changepoint. There was no change in the average number of quarterly injuries in non-SRTS census tracts . Overdispersed Poisson modeling revealed that SRTS implementation was associated with a 44% reduction (95% Confidence Interval [CI] 87% decrease to 130% increase) in school-age pedestrian injury risk during school-travel hours. Conclusions: Bayesian changepoint analysis of quarterly counts of school-age pedestrian injuries correctly identified the timing of SRTS intervention in New York City. Implementation of the SRTS program in New York City appears to be effective in reducing school-age pedestrian injuries during school-travel hours

The Cost-Effectiveness of New York City’s Safe Routes to School Program

Objective. We evaluated the cost-effectiveness of a package of roadway modifications in New York City funded under the Safe Routes to School (SRTS) program. Methods. We used a Markov model to estimate long-term impacts of SRTS on injury reduction and the associated savings in medical costs, lifelong disability, and death. Model inputs included societal costs (in 2013 US dollars) and observed spatiotemporal changes in injury rates associated with New York City’s implementation of SRTS relative to control intersections. Structural changes to roadways were assumed to last 50 years before further investment is required. Therefore, costs were discounted over 50 consecutive cohorts of modified roadway users under SRTS. Results. SRTS was associated with an overall net societal benefit of $230 million and 2055 quality-adjusted life years gained in New York City. Conclusions. SRTS reduces injuries and saves money over the long run

Community Structure in Congressional Cosponsorship Networks

We study the United States Congress by constructing networks between Members of Congress based on the legislation that they cosponsor. Using the concept of modularity, we identify the community structure of Congressmen, as connected via sponsorship/cosponsorship of the same legislation, to investigate the collaborative communities of legislators in both chambers of Congress. This analysis yields an explicit and conceptually clear measure of political polarization, demonstrating a sharp increase in partisan polarization which preceded and then culminated in the 104th Congress (1995-1996), when Republicans took control of both chambers. Although polarization has since waned in the U.S. Senate, it remains at historically high levels in the House of Representatives.Comment: 8 pages, 4 figures (some with multiple parts), to appear in Physica A; additional background info and explanations added from last versio

Evaluation Research and Institutional Pressures: Challenges in Public-Nonprofit Contracting

This article examines the connection between program evaluation research and decision-making by public managers. Drawing on neo-institutional theory, a framework is presented for diagnosing the pressures and conditions that lead alternatively toward or away the rational use of evaluation research. Three cases of public-nonprofit contracting for the delivery of major programs are presented to clarify the way coercive, mimetic, and normative pressures interfere with a sound connection being made between research and implementation. The article concludes by considering how public managers can respond to the isomorphic pressures in their environment that make it hard to act on data relating to program performance.This publication is Hauser Center Working Paper No. 23. The Hauser Center Working Paper Series was launched during the summer of 2000. The Series enables the Hauser Center to share with a broad audience important works-in-progress written by Hauser Center scholars and researchers

International Coercion, Emulation and Policy Diffusion: Market-Oriented Infrastructure Reforms, 1977-1999

Why do some countries adopt market-oriented reforms such as deregulation, privatization and liberalization of competition in their infrastructure industries while others do not? Why did the pace of adoption accelerate in the 1990s? Building on neo-institutional theory in sociology, we argue that the domestic adoption of market-oriented reforms is strongly influenced by international pressures of coercion and emulation. We find robust support for these arguments with an event-history analysis of the determinants of reform in the telecommunications and electricity sectors of as many as 205 countries and territories between 1977 and 1999. Our results also suggest that the coercive effect of multilateral lending from the IMF, the World Bank or Regional Development Banks is increasing over time, a finding that is consistent with anecdotal evidence that multilateral organizations have broadened the scope of the “conditionality” terms specifying market-oriented reforms imposed on borrowing countries. We discuss the possibility that, by pressuring countries into policy reform, cross-national coercion and emulation may not produce ideal outcomes.http://deepblue.lib.umich.edu/bitstream/2027.42/40099/3/wp713.pd

Novel Phosphorylation Sites in the S. cerevisiae Cdc13 Protein Reveal New Targets for Telomere Length Regulation

The S. cerevisiae Cdc13 is a multifunctional protein with key roles in regulation of telomerase, telomere end protection, and conventional telomere replication, all of which are cell cycle-regulated processes. Given that phosphorylation is a key mechanism for regulating protein function, we identified sites of phosphorylation using nano liquid chromatography-tandem mass spectrometry (nanoLC-MS/MS). We also determined phosphorylation abundance on both wild type (WT) and a telomerase deficient form of Cdc13, encoded by the cdc13-2 allele, in both G1 phase cells, when telomerase is not active, and G2/M phase cells, when it is. We identified 21 sites of in vivo phosphorylation, of which only five had been reported previously. In contrast, phosphorylation of two in vitro targets of the ATM-like Tel1 kinase, S249 and S255, was not detected. This result helps resolve conflicting data on the importance of phosphorylation of these residues in telomerase recruitment. multiple residues showed differences in their cell cycle pattern of modification. For example, phosphorylation of S314 was significantly higher in the G2/M compared to the G1 phase and in WT versus mutant Cdc13, and a S314D mutation negatively affected telomere length. Our findings provide new targets in a key telomerase regulatory protein for modulation of telomere dynamics. [Image: see text

Means to an End: An Assessment of the Status-blind Approach to Protecting Undocumented Worker Rights

This article applies the tenets of bureaucratic incorporation theory to an investigation of bureaucratic decision making in labor standards enforcement agencies (LSEAs), as they relate to undocumented workers. Drawing on 25 semistructured interviews with high-level officials in San Jose and Houston, I find that bureaucrats in both cities routinely evade the issue of immigration status during the claims-making process, and directly challenge employers’ attempts to use the undocumented status of their workers to deflect liability. Respondents offer three institutionalized narratives for this approach: (1) to deter employer demand for undocumented labor, (2) the conviction that the protection of undocumented workers is essential to the agency’s ability to regulate industry standards for all workers, and (3) to clearly demarcate the agency’s jurisdictional boundaries to preserve institutional autonomy and scarce resources. Within this context, enforcing the rights of undocumented workers becomes simply an institutional means to an end

Biclustering via optimal re-ordering of data matrices in systems biology: rigorous methods and comparative studies

<p>Abstract</p> <p>Background</p> <p>The analysis of large-scale data sets via clustering techniques is utilized in a number of applications. Biclustering in particular has emerged as an important problem in the analysis of gene expression data since genes may only jointly respond over a subset of conditions. Biclustering algorithms also have important applications in sample classification where, for instance, tissue samples can be classified as cancerous or normal. Many of the methods for biclustering, and clustering algorithms in general, utilize simplified models or heuristic strategies for identifying the "best" grouping of elements according to some metric and cluster definition and thus result in suboptimal clusters.</p> <p>Results</p> <p>In this article, we present a rigorous approach to biclustering, OREO, which is based on the Optimal RE-Ordering of the rows and columns of a data matrix so as to globally minimize the dissimilarity metric. The physical permutations of the rows and columns of the data matrix can be modeled as either a network flow problem or a traveling salesman problem. Cluster boundaries in one dimension are used to partition and re-order the other dimensions of the corresponding submatrices to generate biclusters. The performance of OREO is tested on (a) metabolite concentration data, (b) an image reconstruction matrix, (c) synthetic data with implanted biclusters, and gene expression data for (d) colon cancer data, (e) breast cancer data, as well as (f) yeast segregant data to validate the ability of the proposed method and compare it to existing biclustering and clustering methods.</p> <p>Conclusion</p> <p>We demonstrate that this rigorous global optimization method for biclustering produces clusters with more insightful groupings of similar entities, such as genes or metabolites sharing common functions, than other clustering and biclustering algorithms and can reconstruct underlying fundamental patterns in the data for several distinct sets of data matrices arising in important biological applications.</p